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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c1cb077cf4696f9f4abe4af42be150f0b1441974
| 146
|
py
|
Python
|
voter/admin.py
|
emre/steeminator
|
1f1a162be838ae5d90db1ea36786a80d362af0ad
|
[
"MIT"
] | 4
|
2018-07-31T20:55:34.000Z
|
2019-05-28T06:39:05.000Z
|
voter/admin.py
|
emre/steeminator
|
1f1a162be838ae5d90db1ea36786a80d362af0ad
|
[
"MIT"
] | 5
|
2018-08-01T07:05:25.000Z
|
2018-08-01T07:11:42.000Z
|
voter/admin.py
|
emre/steeminator
|
1f1a162be838ae5d90db1ea36786a80d362af0ad
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import VotingRule, SteemAccount
admin.site.register(SteemAccount)
admin.site.register(VotingRule)
| 20.857143
| 44
| 0.835616
| 18
| 146
| 6.777778
| 0.555556
| 0.278689
| 0.344262
| 0.47541
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.089041
| 146
| 6
| 45
| 24.333333
| 0.917293
| 0
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| 0
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| 0
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| 0
| true
| 0
| 0.5
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| 0
| null | 1
| 1
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
e7362bc7cc22ced5738bd3d141a12699695fcd66
| 91
|
py
|
Python
|
src/reliapy/limit_state/__init__.py
|
reliapy/reliapy
|
3efd48af5cc3bedbcbc5de64fb43e6c5625e3f6d
|
[
"BSD-3-Clause"
] | null | null | null |
src/reliapy/limit_state/__init__.py
|
reliapy/reliapy
|
3efd48af5cc3bedbcbc5de64fb43e6c5625e3f6d
|
[
"BSD-3-Clause"
] | null | null | null |
src/reliapy/limit_state/__init__.py
|
reliapy/reliapy
|
3efd48af5cc3bedbcbc5de64fb43e6c5625e3f6d
|
[
"BSD-3-Clause"
] | null | null | null |
from reliapy.limit_state._model import LimitState
from reliapy.limit_state._model import *
| 30.333333
| 49
| 0.857143
| 13
| 91
| 5.692308
| 0.538462
| 0.297297
| 0.432432
| 0.567568
| 0.864865
| 0.864865
| 0
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| 0
| 0
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| 0
| 0.087912
| 91
| 3
| 50
| 30.333333
| 0.891566
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| 0
| 0
| 0
|
0
| 9
|
e7369892979e17607e228824da00ea3ffffaf971
| 143
|
py
|
Python
|
tests/test_pyins.py
|
Zhang-Haipeng/pyins
|
4d8c120c6a50249309653340d4ef0b9a905e8a90
|
[
"MIT"
] | null | null | null |
tests/test_pyins.py
|
Zhang-Haipeng/pyins
|
4d8c120c6a50249309653340d4ef0b9a905e8a90
|
[
"MIT"
] | 2
|
2020-07-18T19:31:22.000Z
|
2020-07-19T07:03:11.000Z
|
tests/test_pyins.py
|
Zhang-Haipeng/pyins
|
4d8c120c6a50249309653340d4ef0b9a905e8a90
|
[
"MIT"
] | null | null | null |
from pyins import pyins
def test_land_split():
return
def test_split_black_all():
return
def test_split_white_all():
return
| 13
| 27
| 0.713287
| 21
| 143
| 4.47619
| 0.52381
| 0.223404
| 0.276596
| 0.382979
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.223776
| 143
| 11
| 28
| 13
| 0.846847
| 0
| 0
| 0.428571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.428571
| true
| 0
| 0.142857
| 0.428571
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 8
|
99da16ef8a5a4ab9977aa9cd71a7020f084b5439
| 148
|
py
|
Python
|
bobtemplates/mbaechtold/django_project/src/website/settings_example.py
|
mbaechtold/django-project-template
|
cdbac7de9c7cf9d20291dace39ff3000987d79f8
|
[
"MIT"
] | null | null | null |
bobtemplates/mbaechtold/django_project/src/website/settings_example.py
|
mbaechtold/django-project-template
|
cdbac7de9c7cf9d20291dace39ff3000987d79f8
|
[
"MIT"
] | 2
|
2021-12-20T08:48:46.000Z
|
2021-12-20T08:48:59.000Z
|
bobtemplates/mbaechtold/django_project/src/website/settings_example.py
|
mbaechtold/django-project-template
|
cdbac7de9c7cf9d20291dace39ff3000987d79f8
|
[
"MIT"
] | null | null | null |
from website.config.common import BaseSettings
from website.config.mixins import DevMixin
class DevDefaultSite(DevMixin, BaseSettings):
pass
| 18.5
| 46
| 0.817568
| 17
| 148
| 7.117647
| 0.647059
| 0.181818
| 0.280992
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128378
| 148
| 7
| 47
| 21.142857
| 0.937985
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.25
| 0.5
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 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
| 1
| 1
| 0
| 1
| 0
|
0
| 7
|
824308634ec7f9aa4c0b3134998ee245a7f4f9ae
| 61,232
|
py
|
Python
|
tests/test_syncope.py
|
dj-wasabi/python-syncope
|
56d7b17e942af4f2d0c4be3783f6f81bba3ad20c
|
[
"Apache-2.0"
] | 2
|
2015-10-11T21:05:41.000Z
|
2019-12-18T03:21:01.000Z
|
tests/test_syncope.py
|
dj-wasabi/python-syncope
|
56d7b17e942af4f2d0c4be3783f6f81bba3ad20c
|
[
"Apache-2.0"
] | null | null | null |
tests/test_syncope.py
|
dj-wasabi/python-syncope
|
56d7b17e942af4f2d0c4be3783f6f81bba3ad20c
|
[
"Apache-2.0"
] | 3
|
2015-10-12T15:42:40.000Z
|
2020-02-11T02:15:13.000Z
|
"""Test script for python-syncope"""
import sys
import os
import pytest
import xml.etree.ElementTree as ET
my_path = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, my_path + '/../')
import syncope
def test___init__syncope_url():
""" Will test __init__ function if syncope_url is provided.
:return:
"""
with pytest.raises(ValueError) as excinfo:
syn = syncope.Syncope(username="admin", password="password")
assert excinfo.value.message == 'This interface needs an Syncope URL to work!'
def test___init__username():
""" Will test __init__ function if username is provided.
:return:
"""
with pytest.raises(ValueError) as excinfo:
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", password="admin")
assert excinfo.value.message == 'This interface needs an username to work!'
def test___init__password():
""" Will test __init__ function if password is provided.
:return:
"""
with pytest.raises(ValueError) as excinfo:
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin")
assert excinfo.value.message == 'This interface needs an password to work!'
def test__post():
""" Will test __init__ function.
:return:
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="admin")
with pytest.raises(ValueError) as excinfo:
data = syn._post("/syncope/cxf/users")
assert excinfo.value.message == 'No arguments are given to POST.'
def test_get_users_count():
"""Will count the amount of users stored in the Syncope database.
:return: Should return: 5
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
assert syn.get_users_count() == 5
def test_get_user_by_id():
"""Will get all information for user with id: 5.
:return: Should return: puccini
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.get_user_by_id(5)
username = user_data['username']
assert username == "puccini"
def test_get_users_id_false():
"""Will get all information for user with id: 15.
:return: Should return: False.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
assert syn.get_user_by_id(15) == False
def test_get_users_by_query():
"""Will search on username to find "vivaldi"
:return: Should return: vivaldi
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
search_req = '{"type":"LEAF","attributableCond":{"type":"EQ","schema":"username","expression":"vivaldi"}}'
user_data = syn.get_users_by_query(search_req)
username = user_data[0]['username']
assert username == "vivaldi"
def test_get_user_count_by_query():
"""Will count the amount of user which has 'vivaldi' as username.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
search_req = '{"type":"LEAF","attributableCond":{"type":"EQ","schema":"username","expression":"vivaldi"}}'
assert syn.get_user_count_by_query(search_req) == 1
def test_get_user_by_name():
"""Will get all information for user with username: vivaldi
:return: Should return: 3
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.get_user_by_name("vivaldi")
assert user_data['id'] == 3
def test_get_paged_users_by_query():
"""Will search for all active users and return 1 user per page, getting the first page.
:return: Should return: rossini
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
search_req = '{"type":"LEAF","attributableCond":{"type":"EQ","schema":"status","expression":"active"}}'
user_data = syn.get_paged_users_by_query(search_req, 1, 1)
username = user_data[0]['username']
assert username == "rossini"
def test_suspend_user_by_id():
"""Will suspend the user for user id 1.
:return: Should return: suspended
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.suspend_user_by_id(1)
assert user_data['status'] == "suspended"
def test_reactivate_user_by_id():
"""Will reactivate the user for user id 1.
:return: Should return: active
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.reactivate_user_by_id(1)
assert user_data['status'] == "active"
def test_suspend_user_by_name():
"""Will suspend the user for user username vivaldi.
:return: Should return: suspended
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.suspend_user_by_name("vivaldi")
assert user_data['status'] == "suspended"
def test_reactivate_user_by_name():
"""Will reactivate the user for user username vivaldi.
:return: Should return: active
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.reactivate_user_by_name("vivaldi")
assert user_data['status'] == "active"
def test_create_user():
"""Will create an user weedijkerman
:return: Should return: weedijkerman
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
create_user = '{"attributes": [{"schema": "aLong","values": [],"readonly": false},{"schema": "activationDate","values": [""],"readonly": false},{"schema": "cool","values": ["false"],"readonly": false},{"schema": "email","values": ["ikben@werner-dijkerman.nlx"],"readonly": false},{"schema": "firstname","values": ["Werner"],"readonly": false},{"schema": "fullname","values": ["Werner Dijkerman"],"readonly": false},{"schema": "gender","values": ["M"],"readonly": false},{"schema": "loginDate","values": [""],"readonly": false},{"schema": "makeItDouble","values": [],"readonly": false},{"schema": "surname","values": ["Dijkerman"],"readonly": false},{"schema": "type","values": ["account"],"readonly": false},{"schema": "uselessReadonly","values": [""],"readonly": true},{"schema": "userId","values": ["werner@dj-wasabi.nl"],"readonly": false}],"id": 0,"derivedAttributes": [{"schema": "cn","values": [],"readonly": false}],"virtualAttributes": [],"password": "password1234","status": null,"token": null,"tokenExpireTime": null,"username": "weedijkerman","lastLoginDate": null,"creationDate": null,"changePwdDate": null,"failedLogins": null}'
user_data = syn.create_user(create_user)
assert user_data['username'] == "weedijkerman"
def test_update_user():
"""Will update the user weedijkerman to wdijkerman.
:return: Should return: wdijkerman
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.get_user_by_name("weedijkerman")
user_id = int(user_data['id'])
update_user = '{"id":' + str(user_id) + ',"attributesToBeUpdated":[{"schema":"uselessReadonly","valuesToBeAdded":[],"valuesToBeRemoved":[]},{"schema":"loginDate","valuesToBeAdded":[],"valuesToBeRemoved":[]},{"schema":"activationDate","valuesToBeAdded":[],"valuesToBeRemoved":[]}],"attributesToBeRemoved":["aLong","makeItDouble"],"derivedAttributesToBeAdded":[],"derivedAttributesToBeRemoved":[],"virtualAttributesToBeUpdated":[],"virtualAttributesToBeRemoved":[],"resourcesToBeAdded":[],"resourcesToBeRemoved":[],"password":null,"username":"wdijkerman","membershipsToBeAdded":[],"membershipsToBeRemoved":[],"pwdPropRequest":{"resources":[],"onSyncope":false}}'
user_data = syn.update_user(update_user)
assert user_data['username'] == "wdijkerman"
def test_delete_user_by_id():
"""Will delete the user with username wdijkerman.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.get_user_by_name("wdijkerman")
user_id = int(user_data['id'])
print str(user_id)
assert syn.delete_user_by_id(user_id) == True
def test_get_users():
"""Will test to get all users.
:return: Should return: 5
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
user_data = syn.get_users()
assert len(user_data) == 5
# def test_create_users_to_enable():
# syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
# create_user = '{"attributes": [{"schema": "aLong","values": [],"readonly": false},{"schema": "activationDate","values": [1420074061],"readonly": false},{"schema": "cool","values": ["false"],"readonly": false},{"schema": "email","values": ["ikben@werner-dijkerman.nlx"],"readonly": false},{"schema": "firstname","values": ["Werner"],"readonly": false},{"schema": "fullname","values": ["Werner Dijkerman"],"readonly": false},{"schema": "gender","values": ["M"],"readonly": false},{"schema": "loginDate","values": [""],"readonly": false},{"schema": "makeItDouble","values": [],"readonly": false},{"schema": "surname","values": ["Dijkerman"],"readonly": false},{"schema": "type","values": ["account"],"readonly": false},{"schema": "uselessReadonly","values": [""],"readonly": true},{"schema": "userId","values": ["werner@dj-wasabi.nl"],"readonly": false}],"id": 0,"derivedAttributes": [{"schema": "cn","values": [],"readonly": false}],"virtualAttributes": [],"password": "password1234","status": null,"token": null,"tokenExpireTime": null,"username": "wdijkerman","lastLoginDate": null,"creationDate": null,"changePwdDate": null,"failedLogins": null}'
# user_data = syn.create_users(create_user)
# assert user_data['username'] == "wdijkerman"
def test_get_roles():
"""Will test to get all roles.
:return: Should return: 14
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
roles_data = syn.get_roles()
assert len(roles_data) == 14
def test_get_roles_false():
"""Will test to get all roles. (Wrong password)
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
roles_data = syn.get_roles()
assert roles_data == False
def test_get_role_by_id():
"""Will get all information for the role with id: 2.
:return: Should return: child
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
role_data = syn.get_role_by_id(2)
role_name = role_data['name']
assert role_name == "child"
def test_get_role_by_id_false():
"""Will get all information for the role with id: 22.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
role_data = syn.get_role_by_id(22)
assert role_data == False
def test_get_role_by_id_raise():
""" Will test if an id is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_role_by_id()
assert excinfo.value.message == 'This search needs an id to work!'
def test_get_parent_role_by_id():
"""Will get all information for role with id: 2.
:return: Should return: root
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
role_data = syn.get_parent_role_by_id(2)
role_name = role_data['name']
assert role_name == "root"
def test_get_parent_role_by_id_false():
"""Will get all parent information for role with id: 21.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
role_data = syn.get_parent_role_by_id(21)
assert role_data == False
def test_get_parent_role_by_id_raise():
""" Will test if an id is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_parent_role_by_id()
assert excinfo.value.message == 'This search needs an id to work!'
def test_get_children_role_by_id():
"""Will get all children information for role with id: 4.
:return: Should return: secretary
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
role_data = syn.get_children_role_by_id(4)
role_name = role_data[0]['name']
assert role_name == "secretary"
def test_get_children_role_by_id_false():
"""Will get all children information for role with id: 24.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
role_data = syn.get_children_role_by_id(24)
assert role_data == False
def test_get_children_role_by_id_raise():
""" Will test if an id is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_children_role_by_id()
assert excinfo.value.message == 'This search needs an id to work!'
def test_create_role():
"""Will create an role with name 'my_new_role'.
:return: Should return: secretary
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
my_role = '{"attributes":[{"schema":"icon","values":[],"readonly":false},{"schema":"rderived_dx","values":[],"readonly":false},{"schema":"rderived_sx","values":[],"readonly":false},{"schema":"show","values":["false"],"readonly":false},{"schema":"title","values":["My new attribute Title."],"readonly":false}],"id":0,"derivedAttributes":[],"virtualAttributes":[],"resources":["ws-target-resource-2","ws-target-resource-1"],"propagationStatusTOs":[],"name":"my_new_role","parent":1,"userOwner":null,"roleOwner":null,"inheritOwner":true,"inheritAttributes":false,"inheritDerivedAttributes":false,"inheritVirtualAttributes":false,"inheritPasswordPolicy":false,"inheritAccountPolicy":false,"entitlements":["CONFIGURATION_CREATE","CONFIGURATION_DELETE"],"passwordPolicy":4,"accountPolicy":6}'
role_data = syn.create_role(my_role)
role_name = role_data['name']
assert role_name == "my_new_role"
def test_create_role_false():
"""Will create an rolec
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
my_role = '{}'
role_data = syn.create_role(my_role)
assert role_data == False
def test_create_role_raise():
""" Will test if an JSON is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.create_role()
assert excinfo.value.message == 'This search needs JSON data to work!'
def test_update_role():
"""Will update the role created in previous test.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
roles_data = syn.get_roles()
for role in roles_data:
if role['name'] == 'my_new_role':
role_id = role['id']
my_role = '{"id":' + str(role_id) + ',"attributesToBeUpdated":[],"attributesToBeRemoved":["icon","rderived_sx","rderived_dx"],"derivedAttributesToBeAdded":[],"derivedAttributesToBeRemoved":[],"virtualAttributesToBeUpdated":[],"virtualAttributesToBeRemoved":[],"resourcesToBeAdded":[],"resourcesToBeRemoved":["ws-target-resource-2"],"name":"my_new_role_upd","userOwner":{"id":null},"roleOwner":{"id":null},"inheritOwner":true,"inheritAttributes":false,"inheritDerivedAttributes":false,"inheritVirtualAttributes":false,"inheritAccountPolicy":false,"inheritPasswordPolicy":false,"entitlements":["CONFIGURATION_CREATE","CONFIGURATION_DELETE","CONFIGURATION_UPDATE"],"passwordPolicy":{"id":4},"accountPolicy":{"id":6}}'
role_upd_data = syn.update_role(my_role)
role_name = role_upd_data['name']
assert role_name == 'my_new_role_upd'
def test_update_role_false():
"""Will update the role created in previous test, but no correct JSON was given as argument.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
my_role = '{}'
assert syn.update_role(my_role) == False
def test_update_role_railse():
"""Will update the role created in previous test.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.update_role()
assert excinfo.value.message == 'This search needs JSON data to work!'
def test_delete_role():
"""Will delete the role created in previous test.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
roles_data = syn.get_roles()
for role in roles_data:
if role['name'] == 'my_new_role_upd':
role_id = role['id']
assert syn.delete_role_by_id(role_id) == True
def test_delete_role_false():
"""Will delete the a non existing role.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
assert syn.delete_role_by_id(9999999) == False
def test_delete_role_raise():
""" Will test if an id is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.delete_role_by_id()
assert excinfo.value.message == 'This search needs an id to work!'
def test_get_log_levels():
"""Will test to get all log levels.
:return: Should return: 17
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
roles_data = syn.get_log_levels()
assert len(roles_data) == 17
def test_get_log_levels_false():
"""Will test to get all log levels (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
roles_data = syn.get_log_levels()
assert roles_data == False
def test_get_log_level_by_name():
"""Will get all information from log level where name is "ROOT".
:return: Should return: "INFO"
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
log_level = syn.get_log_level_by_name("ROOT")
log_level = log_level['level']
assert log_level == "INFO"
def test_get_log_level_by_name_false():
"""Will get all information from non existing log name.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
log_level = syn.get_log_level_by_name("SYNCOPE")
assert log_level == False
def test_get_log_level_by_name_raise():
""" Will test if an name is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_log_level_by_name()
assert excinfo.value.message == 'This search needs log level name to work!'
def test_create_or_update_log_level_update():
"""Will update the log level to "WARN".
:return: Should return: "WARN"
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
update_log_level = '{"name": "org.apache.http", "level": "WARN"}'
log_level = syn.create_or_update_log_level(update_log_level)
assert log_level['level'] == "WARN"
def test_create_or_update_log_level_create():
"""Will create an new loglevel named 'SYNCOPE' with level 'WARN'.
:return: Should return: json string
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
update_log_level = '{"name": "SYNCOPE", "level": "WARN"}'
log_level = syn.create_or_update_log_level(update_log_level)
assert log_level == {'level': 'WARN', 'name': 'SYNCOPE'}
def test_create_or_update_log_level_false_empty():
"""Will create an new log level, without JSON data.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
update_log_level = '{}'
log_level = syn.create_or_update_log_level(update_log_level)
assert log_level == False
def test_create_or_update_log_level_create_false():
"""Will create an new loglevel named 'SYNCOPE' with level 'WARN' (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="pasword")
update_log_level = '{"name": "SYNCOPE", "level": "WARN"}'
log_level = syn.create_or_update_log_level(update_log_level)
assert log_level == False
def test_create_or_update_log_level_raise():
""" Will test if an name is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.create_or_update_log_level()
assert excinfo.value.message == 'This search needs JSON data to work!'
def test_delete_log_level_by_name():
"""Will delete an log level with name "SYNCOPE".
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
assert syn.delete_log_level_by_name("SYNCOPE") == True
def test_delete_log_level_by_name_false():
"""Will delete an log level with non existing name "SYNCOPE_AGAIN".
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
assert syn.delete_log_level_by_name("SYNCOPE_AGAIN") == False
def test_delete_log_level_by_name_raise():
""" Will test if an name is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.delete_log_level_by_name()
assert excinfo.value.message == 'This search needs log level name to work!'
def test_get_audit():
"""Will get all audit rules.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
audit_rules = syn.get_audit()
assert len(audit_rules) == 1
def test_get_audit_false():
"""Will get all audit rules (Wrong password).
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="pasword")
assert syn.get_audit() == False
def test_create_audit():
"""Will create an audit rule.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
add_audit_rule = '{"type":"REST","category":"LoggerController","subcategory":null,"event":"listAudits","result":"SUCCESS"}'
assert syn.create_audit(add_audit_rule) == True
def test_create_audit_false():
"""Will create an audit rule.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
add_audit_rule = ''
assert syn.create_audit(add_audit_rule) == False
def test_create_audit_raise():
"""Will create an audit rule.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.create_audit()
assert excinfo.value.message == 'This search needs JSON data to work!'
def test_delete_audit():
"""Will delete an audit rule.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
delete_audit_rule = '{"type":"REST","category":"LoggerController","subcategory":null,"event":"listAudits","result":"SUCCESS"}'
assert syn.delete_audit(delete_audit_rule) == True
def test_delete_audit_false():
"""Will delete an audit rule.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
delete_audit_rule = ''
assert syn.delete_audit(delete_audit_rule) == False
def test_create_audit_raise():
""" Will test if an name is given as argument.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.delete_audit()
assert excinfo.value.message == 'This search needs JSON data to work!'
def test_get_configurations():
"""Will test to get all configurations.
:return: Should return: 10
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
resource_data = syn.get_configurations()
assert len(resource_data) == 10
def test_get_configurations_false():
"""Will test to get all configurations (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_configurations() == False
def test_get_configuration_by_key():
"""Will test to get all configuration by key.
:return: Should return: {'key': 'password.cipher.algorithm', 'value': 'SHA1'}
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
resource_data = syn.get_configuration_by_key("password.cipher.algorithm")
assert resource_data == {'key': 'password.cipher.algorithm', 'value': 'SHA1'}
def test_get_configuration_by_key_false():
"""Will test to get configuration by key (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_configuration_by_key("password.cipher.algorithm") == False
def test_get_configuration_by_key_raise():
"""Will test to get configuration by key without key.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_configuration_by_key()
assert excinfo.value.message == 'This search needs an configuration key to work!'
def test_create_configuration():
"""Will create an configuration.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
create_configuration = '{"key": "my.path", "value": "/opt/path"}'
resource_data = syn.create_configuration(create_configuration)
assert resource_data == True
def test_create_configuration_false():
"""Will create an configuration (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
create_configuration = '{"key": "my.path", "value": "/opt/path"}'
assert syn.create_configuration(create_configuration) == False
def test_create_configuration_raise():
"""Will create an configuration without json data.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.create_configuration()
assert excinfo.value.message == 'This search needs JSON data to work!'
def test_update_configuration():
"""Will update the configuration.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
update_configuration = '{"key": "my.path", "value": "/opt/newpath"}'
resource_data = syn.update_configuration(update_configuration)
assert resource_data == True
def test_update_configuration_false():
"""Will update the configuration (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
update_configuration = '{"key": "my.path", "value": "/opt/newpath"}'
assert syn.update_configuration(update_configuration) == False
def test_update_configuration_false_json():
"""Will update the configuration, with "faulty" json data.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
update_configuration = '{"keys": "my.path", "values": "/opt/newpath"}'
assert syn.update_configuration(update_configuration) == False
def test_update_configuration_raise():
"""Will update the configuration, without json data.
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.update_configuration()
assert excinfo.value.message == 'This search needs JSON data to work!'
def test_delete_configuration_by_key():
"""Will delete an configuration.
:return: Should return: true
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
resource_data = syn.delete_configuration_by_key("my.path")
assert resource_data == True
def test_delete_configuration_by_key_false():
"""Will delete an configuration (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.delete_configuration_by_key("my.path") == False
def test_delete_configuration_by_key_raise():
"""Will delete an configuration without key name.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.delete_configuration_by_key()
assert excinfo.value.message == 'This search needs JSON data to work!'
def test_get_configuration_validators():
"""Will test to get all configuration validators.
:return: Should return: 10
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
resource_data = syn.get_configuration_validators()
assert len(resource_data) == 3
def test_get_configuration_validators_false():
"""Will test to get all configuration validators (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_configuration_validators() == False
def test_get_configuration_mailtemplates():
"""Will test to get all mailtemplates.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
resource_data = syn.get_configuration_mailtemplates()
assert len(resource_data) == 1
def test_get_configuration_mailtemplates_false():
"""Will test to get all mailtemplates (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_configuration_mailtemplates() == False
def test_get_configuration_stream():
"""Will test to get configuration stream.
:return: Should return: dataset
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
resource_data = syn.get_configuration_stream()
tree = ET.fromstring(resource_data.text)
assert tree.tag == "dataset"
def test_get_configuration_stream_false():
"""Will test to get configuration stream (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_configuration_stream() == False
def test_get_entitlements():
"""Will return a list of all known entitlements.
:return: Should return: dataset
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
resource_data = syn.get_entitlements()
assert len(resource_data) == 84
def test_get_entitlements_false():
"""Will return a list of all known entitlements (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_entitlements() == False
def test_get_own_entitlements():
"""Will return a list of all known entitlements.
:return: Should return: 84
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
resource_data = syn.get_own_entitlements()
assert len(resource_data) == 84
def test_get_own_entitlements_false():
"""Will return a list of all known entitlements (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_own_entitlements() == False
def test_get_notifications():
"""Will return a list of all notifications.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
notification_data = syn.get_notifications()
assert len(notification_data) == 1
def test_get_notifications_false():
"""Will return a list of all notifications (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_notifications() == False
def test_get_notification_by_id():
"""Will return information for notifications with id.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
notification_data = syn.get_notification_by_id(1)
assert len(notification_data) == 11
def test_get_notification_by_id_false():
"""Will return information for notifications with id (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_notification_by_id(1) == False
def test_get_notification_by_id_raise():
"""Will return information for notifications with id.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_notification_by_id()
assert excinfo.value.message == 'This search needs an id to work!'
def test_create_notification():
"""Will create an notification
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
create_notification = '{"events":["[REST]:[LoggerController]:[]:[deleteLog]:[SUCCESS]","[REST]:[LoggerController]:[]:[disableAudit]:[SUCCESS]"],"recipientAttrType":"Username","recipientAttrName":"Username","selfAsRecipient":true,"sender":"me@home.nl","subject":"this is very important","template":"optin","traceLevel":"FAILURES"}'
notification_data = syn.create_notification(create_notification)
assert notification_data == True
def test_create_notification_false():
"""Will create an notification (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
create_notification = '{"events":["[REST]:[LoggerController]:[]:[deleteLog]:[SUCCESS]","[REST]:[LoggerController]:[]:[disableAudit]:[SUCCESS]"],"recipientAttrType":"Username","recipientAttrName":"Username","selfAsRecipient":true,"sender":"me@home.nl","subject":"this is very important","template":"optin","traceLevel":"FAILURES"}'
notification_data = syn.create_notification(create_notification)
assert notification_data == False
def test_create_notification_raise():
"""Will return information for notifications with id.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.create_notification()
assert excinfo.value.message == 'This search needs an JSON to work!'
def test_update_notification_by_id():
"""Will update an notification
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
# Get latest notification_id
notifications_list = []
for notification in syn.get_notifications():
notifications_list.append(notification['id'])
notifications_list.reverse()
notifications_id = notifications_list[0]
update_notification = '{"id":' + str(notifications_id) + ',"events":["[REST]:[LoggerController]:[]:[deleteLog]:[SUCCESS]"],"about":null,"recipients":null,"recipientAttrType":"Username","recipientAttrName":"Username","selfAsRecipient":true,"sender":"me@home.nl","subject":"this is very important again","template":"optin","traceLevel":"FAILURES"}'
notification_data = syn.update_notification_by_id(update_notification)
assert notification_data == True
def test_update_notification_by_id_false():
"""Will update an notification (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
create_notification = '{"events":["[REST]:[LoggerController]:[]:[deleteLog]:[SUCCESS]","[REST]:[LoggerController]:[]:[disableAudit]:[SUCCESS]"],"recipientAttrType":"Username","recipientAttrName":"Username","selfAsRecipient":true,"sender":"me@home.nl","subject":"this is very important","template":"optin","traceLevel":"FAILURES"}'
notification_data = syn.update_notification_by_id(create_notification)
assert notification_data == False
def test_update_notification_by_id_raise():
"""Will update information for notifications with id.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.update_notification_by_id()
assert excinfo.value.message == 'This search needs an JSON to work!'
def test_datele_notification_by_id():
"""Will delete an notification
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
# Get latest notification_id
notifications_list = []
for notification in syn.get_notifications():
notifications_list.append(notification['id'])
notifications_list.reverse()
notifications_id = notifications_list[0]
notification_data = syn.delete_notification_by_id(notifications_id)
assert notification_data == True
def test_delete_notification_by_id_false():
"""Will delete an notification (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
notification_data = syn.delete_notification_by_id(101)
assert notification_data == False
def test_delete_notification_by_id_raise():
"""Will delete information for notifications with id.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.delete_notification_by_id()
assert excinfo.value.message == 'This search needs an JSON to work!'
def test_get_account_policies():
"""Will return a list of account policies.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
account_policies_data = syn.get_account_policies()
assert len(account_policies_data) == 1
def test_get_account_policies_false():
"""Will return a list of account policies (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_account_policies() == False
def test_get_account_policy_by_id():
"""Will return a list of account policies.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
account_policies_data = syn.get_account_policy_by_id(5)
account_policies_data_type = account_policies_data['type']
assert account_policies_data_type == "GLOBAL_ACCOUNT"
def test_get_account_policy_by_id_false():
"""Will return a list of account policies (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_account_policy_by_id(5) == False
def test_get_account_policy_by_id_raise():
"""Will update information for notifications with id.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_account_policy_by_id()
assert excinfo.value.message == 'This needs an ID to work!'
def test_create_account_policy():
"""Will create an account policy.
:return: Should return: ACCOUNT
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
create_account_policy = '{"description":"My Description","type":"ACCOUNT","usedByResources":[],"usedByRoles":[],"specification":{"maxLength":0,"minLength":0,"pattern":null,"wordsNotPermitted":[],"schemasNotPermitted":["firstname","email"],"prefixesNotPermitted":[],"suffixesNotPermitted":[],"allUpperCase":false,"allLowerCase":false,"propagateSuspension":false,"permittedLoginRetries":0}}'
account_policy_data = syn.create_account_policy(create_account_policy)
account_policy_type = account_policy_data['type']
assert account_policy_type == "ACCOUNT"
def test_create_account_policy_false():
"""Will create an account policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.create_account_policy("json") == False
def test_create_account_policy_raise():
"""Will create an account policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.create_account_policy()
assert excinfo.value.message == 'This create needs an JSON to work!'
def test_update_account_policy():
"""Will update an account policy.
:return: Should return: secretary
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
account_policies_list = []
for policy in syn.get_account_policies():
account_policies_list.append(policy['id'])
account_policies_list.reverse()
policy_id = account_policies_list[0]
update_policy = '{"id":' + str(policy_id) + ',"description":"My Description 2","type":"ACCOUNT","usedByResources":[],"usedByRoles":[],"specification":{"maxLength":0,"minLength":0,"pattern":null,"wordsNotPermitted":[],"schemasNotPermitted":["firstname"],"prefixesNotPermitted":[],"suffixesNotPermitted":[],"allUpperCase":false,"allLowerCase":false,"propagateSuspension":false,"permittedLoginRetries":0}}'
account_policy_data = syn.update_account_policy(update_policy)
account_policy_type = account_policy_data['type']
assert account_policy_type == "ACCOUNT"
def test_update_account_policy_false():
"""Will update an account policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.update_account_policy("json") == False
def test_update_account_policy_raise():
"""Will update an account policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.update_account_policy()
assert excinfo.value.message == 'This update needs an JSON to work!'
def test_delete_account_policy():
"""Will delete an account policy.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
account_policies_list = []
for policy in syn.get_account_policies():
account_policies_list.append(policy['id'])
account_policies_list.reverse()
policy_id = account_policies_list[0]
assert syn.delete_account_policy(policy_id) == True
def test_delete_account_policy_false():
"""Will delete an account policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.delete_account_policy("json") == False
def test_delete_account_policy_raise():
"""Will delete an account policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.delete_account_policy()
assert excinfo.value.message == 'This delete needs an id to work!'
def test_get_sync_policies():
"""Will return a list of sync policies.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
sync_policies_data = syn.get_sync_policies()
assert len(sync_policies_data) == 3
def test_get_sync_policies_false():
"""Will return a list of sync policies (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_sync_policies() == False
def test_get_sync_policy_by_id():
"""Will return a list of sync policies.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
sync_policies_data = syn.get_sync_policy_by_id(5)
sync_policies_data_type = sync_policies_data['type']
assert sync_policies_data_type == "GLOBAL_ACCOUNT"
def test_get_sync_policy_by_id_false():
"""Will return a list of sync policies (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_sync_policy_by_id(5) == False
def test_get_sync_policy_by_id_raise():
"""Will update information for notifications with id.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_sync_policy_by_id()
assert excinfo.value.message == 'This needs an ID to work!'
def test_create_sync_policy():
"""Will create an sync policy.
:return: Should return: ACCOUNT
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
create_sync_policy = '{"description":"My First Sync","type":"SYNC","usedByResources":[],"usedByRoles":[],"specification":{"uAltSearchSchemas":["loginDate"],"userJavaRule":null,"rAltSearchSchemas":[],"roleJavaRule":null,"conflictResolutionAction":"FIRSTMATCH"}}'
sync_policy_data = syn.create_sync_policy(create_sync_policy)
sync_policy_type = sync_policy_data['type']
assert sync_policy_type == "SYNC"
def test_create_sync_policy_false():
"""Will create an sync policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.create_sync_policy("json") == False
def test_create_sync_policy_raise():
"""Will create an sync policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.create_sync_policy()
assert excinfo.value.message == 'This create needs an JSON to work!'
def test_update_sync_policy():
"""Will update an sync policy.
:return: Should return: secretary
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
sync_policies_list = []
for policy in syn.get_sync_policies():
sync_policies_list.append(policy['id'])
sync_policies_list.reverse()
policy_id = sync_policies_list[0]
update_policy = '{"id":' + str(policy_id) + ',"description":"My First Sync 2","type":"SYNC","usedByResources":[],"usedByRoles":[],"specification":{"uAltSearchSchemas":["loginDate","firstname"],"userJavaRule":null,"rAltSearchSchemas":[],"roleJavaRule":null,"conflictResolutionAction":"FIRSTMATCH"}}'
sync_policy_data = syn.update_sync_policy(update_policy)
sync_policy_type = sync_policy_data['type']
assert sync_policy_type == "SYNC"
def test_update_sync_policy_false():
"""Will update an sync policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.update_sync_policy("json") == False
def test_update_sync_policy_raise():
"""Will update an sync policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.update_sync_policy()
assert excinfo.value.message == 'This update needs an JSON to work!'
def test_delete_sync_policy():
"""Will delete an sync policy.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
sync_policies_list = []
for policy in syn.get_sync_policies():
sync_policies_list.append(policy['id'])
sync_policies_list.reverse()
policy_id = sync_policies_list[0]
assert syn.delete_sync_policy(policy_id) == True
def test_delete_sync_policy_false():
"""Will delete an sync policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.delete_sync_policy("json") == False
def test_delete_sync_policy_raise():
"""Will delete an sync policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.delete_sync_policy()
assert excinfo.value.message == 'This delete needs an id to work!'
def test_get_password_policies():
"""Will return a list of password policies.
:return: Should return: 2
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
password_policies_data = syn.get_password_policies()
assert len(password_policies_data) == 2
def test_get_password_policies_false():
"""Will return a list of password policies (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_password_policies() == False
def test_get_password_policy_by_id():
"""Will return a list of password policies.
:return: Should return: 1
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
password_policies_data = syn.get_password_policy_by_id(5)
password_policies_data_type = password_policies_data['type']
assert password_policies_data_type == "GLOBAL_ACCOUNT"
def test_get_password_policy_by_id_false():
"""Will return a list of password policies (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.get_password_policy_by_id(5) == False
def test_get_password_policy_by_id_raise():
"""Will update information for notifications with id.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.get_password_policy_by_id()
assert excinfo.value.message == 'This needs an ID to work!'
def test_create_password_policy():
"""Will create an password policy.
:return: Should return: ACCOUNT
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
create_password_policy = '{"description":"My Password Policy","type":"PASSWORD","usedByResources":[],"usedByRoles":[],"specification":{"historyLength":10,"maxLength":0,"minLength":8,"wordsNotPermitted":[],"schemasNotPermitted":[],"nonAlphanumericRequired":true,"alphanumericRequired":true,"digitRequired":true,"lowercaseRequired":false,"uppercaseRequired":false,"mustStartWithDigit":false,"mustntStartWithDigit":false,"mustEndWithDigit":false,"mustntEndWithDigit":false,"mustStartWithNonAlpha":false,"mustStartWithAlpha":false,"mustntStartWithNonAlpha":false,"mustntStartWithAlpha":false,"mustEndWithNonAlpha":false,"mustEndWithAlpha":false,"mustntEndWithNonAlpha":false,"mustntEndWithAlpha":false,"prefixesNotPermitted":[],"suffixesNotPermitted":[]}}'
password_policy_data = syn.create_password_policy(create_password_policy)
password_policy_type = password_policy_data['type']
assert password_policy_type == "PASSWORD"
def test_create_password_policy_false():
"""Will create an password policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.create_password_policy("json") == False
def test_create_password_policy_raise():
"""Will create an password policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.create_password_policy()
assert excinfo.value.message == 'This create needs an JSON to work!'
def test_update_password_policy():
"""Will update an password policy.
:return: Should return: PASSWORD
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
password_policies_list = []
for policy in syn.get_password_policies():
password_policies_list.append(policy['id'])
password_policies_list.reverse()
policy_id = password_policies_list[0]
update_policy = '{"id":' + str(policy_id) + ',"description":"My Password Policy 2","type":"PASSWORD","usedByResources":[],"usedByRoles":[],"specification":{"historyLength":10,"maxLength":0,"minLength":8,"wordsNotPermitted":[],"schemasNotPermitted":[],"nonAlphanumericRequired":true,"alphanumericRequired":true,"digitRequired":true,"lowercaseRequired":false,"uppercaseRequired":false,"mustStartWithDigit":false,"mustntStartWithDigit":false,"mustEndWithDigit":false,"mustntEndWithDigit":false,"mustStartWithNonAlpha":false,"mustStartWithAlpha":false,"mustntStartWithNonAlpha":false,"mustntStartWithAlpha":false,"mustEndWithNonAlpha":false,"mustEndWithAlpha":false,"mustntEndWithNonAlpha":false,"mustntEndWithAlpha":false,"prefixesNotPermitted":[],"suffixesNotPermitted":[]}}'
password_policy_data = syn.update_password_policy(update_policy)
password_policy_type = password_policy_data['type']
assert password_policy_type == "PASSWORD"
def test_update_password_policy_false():
"""Will update an password policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.update_password_policy("json") == False
def test_update_password_policy_raise():
"""Will update an password policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.update_password_policy()
assert excinfo.value.message == 'This update needs an JSON to work!'
def test_delete_password_policy():
"""Will delete an password policy.
:return: Should return: True
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
password_policies_list = []
for policy in syn.get_password_policies():
password_policies_list.append(policy['id'])
password_policies_list.reverse()
policy_id = password_policies_list[0]
assert syn.delete_password_policy(policy_id) == True
def test_delete_password_policy_false():
"""Will delete an password policy (Wrong password).
:return: Should return: False
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
assert syn.delete_password_policy("json") == False
def test_delete_password_policy_raise():
"""Will delete an password policy.
:return: Should catch the ValueError.
"""
syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
with pytest.raises(ValueError) as excinfo:
syn.delete_password_policy()
assert excinfo.value.message == 'This delete needs an id to work!'
# def test_get_resources():
# """Will test to get all users.
#
# :return: Should return: 5
# """
# syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="password")
# resource_data = syn.get_resources()
# assert len(resource_data) == 18
#
#
# def test_get_resources_false():
# """Will test to get all users (Wrong password).
#
# :return: Should return: False
# """
# syn = syncope.Syncope(syncope_url="http://192.168.1.145:9080", username="admin", password="passwrd")
# assert syn.get_resources() == False
| 39.530019
| 1,153
| 0.702133
| 7,840
| 61,232
| 5.29273
| 0.044388
| 0.096831
| 0.058995
| 0.082709
| 0.890613
| 0.841089
| 0.792361
| 0.741656
| 0.714472
| 0.69565
| 0
| 0.041337
| 0.146231
| 61,232
| 1,548
| 1,154
| 39.555556
| 0.752401
| 0.032548
| 0
| 0.483384
| 0
| 0.024169
| 0.324768
| 0.14495
| 0
| 0
| 0
| 0
| 0.212991
| 0
| null | null | 0.296073
| 0.013595
| null | null | 0.001511
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
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| 1
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| 0
| 0
| 0
| 0
|
0
| 9
|
41c0051d44a1bfba4ab332191a491dcef9887566
| 53,304
|
py
|
Python
|
nova/tests/unit/virt/hyperv/test_volumeops.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/virt/hyperv/test_volumeops.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/virt/hyperv/test_volumeops.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | 2
|
2017-07-20T17:31:34.000Z
|
2020-07-24T02:42:19.000Z
|
begin_unit
comment|'# Copyright 2014 Cloudbase Solutions Srl'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# All Rights Reserved.'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may'
nl|'\n'
comment|'# not use this file except in compliance with the License. You may obtain'
nl|'\n'
comment|'# a copy of the License at'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# http://www.apache.org/licenses/LICENSE-2.0'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Unless required by applicable law or agreed to in writing, software'
nl|'\n'
comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT'
nl|'\n'
comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the'
nl|'\n'
comment|'# License for the specific language governing permissions and limitations'
nl|'\n'
comment|'# under the License.'
nl|'\n'
nl|'\n'
name|'import'
name|'os'
newline|'\n'
nl|'\n'
name|'import'
name|'mock'
newline|'\n'
name|'from'
name|'os_win'
name|'import'
name|'exceptions'
name|'as'
name|'os_win_exc'
newline|'\n'
name|'from'
name|'oslo_config'
name|'import'
name|'cfg'
newline|'\n'
nl|'\n'
name|'from'
name|'nova'
name|'import'
name|'exception'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'test'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'tests'
op|'.'
name|'unit'
name|'import'
name|'fake_block_device'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'tests'
op|'.'
name|'unit'
op|'.'
name|'virt'
op|'.'
name|'hyperv'
name|'import'
name|'test_base'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'virt'
op|'.'
name|'hyperv'
name|'import'
name|'volumeops'
newline|'\n'
nl|'\n'
DECL|variable|CONF
name|'CONF'
op|'='
name|'cfg'
op|'.'
name|'CONF'
newline|'\n'
nl|'\n'
DECL|variable|connection_data
name|'connection_data'
op|'='
op|'{'
string|"'volume_id'"
op|':'
string|"'fake_vol_id'"
op|','
nl|'\n'
string|"'target_lun'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_lun'
op|','
nl|'\n'
string|"'target_iqn'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|','
nl|'\n'
string|"'target_portal'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_portal'
op|','
nl|'\n'
string|"'auth_method'"
op|':'
string|"'chap'"
op|','
nl|'\n'
string|"'auth_username'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_user'
op|','
nl|'\n'
string|"'auth_password'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_pass'
op|'}'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|get_fake_block_dev_info
name|'def'
name|'get_fake_block_dev_info'
op|'('
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
op|'{'
string|"'block_device_mapping'"
op|':'
op|'['
nl|'\n'
name|'fake_block_device'
op|'.'
name|'AnonFakeDbBlockDeviceDict'
op|'('
op|'{'
string|"'source_type'"
op|':'
string|"'volume'"
op|'}'
op|')'
op|']'
nl|'\n'
op|'}'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|get_fake_connection_info
dedent|''
name|'def'
name|'get_fake_connection_info'
op|'('
op|'**'
name|'kwargs'
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
op|'{'
string|"'data'"
op|':'
name|'dict'
op|'('
name|'connection_data'
op|','
op|'**'
name|'kwargs'
op|')'
op|','
nl|'\n'
string|"'serial'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'serial'
op|'}'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|VolumeOpsTestCase
dedent|''
name|'class'
name|'VolumeOpsTestCase'
op|'('
name|'test_base'
op|'.'
name|'HyperVBaseTestCase'
op|')'
op|':'
newline|'\n'
indent|' '
string|'"""Unit tests for VolumeOps class."""'
newline|'\n'
nl|'\n'
DECL|member|setUp
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'VolumeOpsTestCase'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'='
name|'volumeops'
op|'.'
name|'VolumeOps'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_volutils'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_vmutils'
op|'='
name|'mock'
op|'.'
name|'Mock'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_get_volume_driver
dedent|''
name|'def'
name|'test_get_volume_driver'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'fake_conn_info'
op|'='
op|'{'
string|"'driver_volume_type'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_driver_type'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'volume_drivers'
op|'['
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_driver_type'
op|']'
op|'='
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_driver'
op|')'
newline|'\n'
nl|'\n'
name|'result'
op|'='
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_get_volume_driver'
op|'('
nl|'\n'
name|'connection_info'
op|'='
name|'fake_conn_info'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_driver'
op|','
name|'result'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_get_volume_driver_exception
dedent|''
name|'def'
name|'test_get_volume_driver_exception'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'fake_conn_info'
op|'='
op|'{'
string|"'driver_volume_type'"
op|':'
string|"'fake_driver'"
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exception'
op|'.'
name|'VolumeDriverNotFound'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_get_volume_driver'
op|','
nl|'\n'
name|'connection_info'
op|'='
name|'fake_conn_info'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'VolumeOps'
op|','
string|"'attach_volume'"
op|')'
newline|'\n'
DECL|member|test_attach_volumes
name|'def'
name|'test_attach_volumes'
op|'('
name|'self'
op|','
name|'mock_attach_volume'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_info'
op|'='
name|'get_fake_block_dev_info'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'attach_volumes'
op|'('
name|'block_device_info'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
nl|'\n'
name|'ebs_root'
op|'='
name|'True'
op|')'
newline|'\n'
nl|'\n'
name|'mock_attach_volume'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'block_device_info'
op|'['
string|"'block_device_mapping'"
op|']'
op|'['
number|'0'
op|']'
op|'['
string|"'connection_info'"
op|']'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
name|'True'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_fix_instance_volume_disk_paths_empty_bdm
dedent|''
name|'def'
name|'test_fix_instance_volume_disk_paths_empty_bdm'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'fix_instance_volume_disk_paths'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
nl|'\n'
name|'block_device_info'
op|'='
op|'{'
op|'}'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertFalse'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_vmutils'
op|'.'
name|'get_vm_physical_disk_mapping'
op|'.'
name|'called'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'VolumeOps'
op|','
string|"'get_disk_path_mapping'"
op|')'
newline|'\n'
DECL|member|test_fix_instance_volume_disk_paths
name|'def'
name|'test_fix_instance_volume_disk_paths'
op|'('
name|'self'
op|','
name|'mock_get_disk_path_mapping'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_info'
op|'='
name|'get_fake_block_dev_info'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'mock_disk1'
op|'='
op|'{'
nl|'\n'
string|"'mounted_disk_path'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'mounted_disk1_path'
op|','
nl|'\n'
string|"'resource_path'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'resource1_path'
nl|'\n'
op|'}'
newline|'\n'
name|'mock_disk2'
op|'='
op|'{'
nl|'\n'
string|"'mounted_disk_path'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'mounted_disk2_path'
op|','
nl|'\n'
string|"'resource_path'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'resource2_path'
nl|'\n'
op|'}'
newline|'\n'
nl|'\n'
name|'mock_vm_disk_mapping'
op|'='
op|'{'
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk1_serial'
op|':'
name|'mock_disk1'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk2_serial'
op|':'
name|'mock_disk2'
nl|'\n'
op|'}'
newline|'\n'
comment|'# In this case, only the first disk needs to be updated.'
nl|'\n'
name|'mock_phys_disk_path_mapping'
op|'='
op|'{'
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk1_serial'
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'actual_disk1_path'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk2_serial'
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'mounted_disk2_path'
nl|'\n'
op|'}'
newline|'\n'
nl|'\n'
name|'vmutils'
op|'='
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_vmutils'
newline|'\n'
name|'vmutils'
op|'.'
name|'get_vm_physical_disk_mapping'
op|'.'
name|'return_value'
op|'='
op|'('
nl|'\n'
name|'mock_vm_disk_mapping'
op|')'
newline|'\n'
nl|'\n'
name|'mock_get_disk_path_mapping'
op|'.'
name|'return_value'
op|'='
name|'mock_phys_disk_path_mapping'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'fix_instance_volume_disk_paths'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
nl|'\n'
name|'block_device_info'
op|')'
newline|'\n'
nl|'\n'
name|'vmutils'
op|'.'
name|'get_vm_physical_disk_mapping'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|')'
newline|'\n'
name|'mock_get_disk_path_mapping'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'block_device_info'
op|')'
newline|'\n'
name|'vmutils'
op|'.'
name|'set_disk_host_res'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'resource1_path'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'actual_disk1_path'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'VolumeOps'
op|','
string|"'_get_volume_driver'"
op|')'
newline|'\n'
DECL|member|test_disconnect_volumes
name|'def'
name|'test_disconnect_volumes'
op|'('
name|'self'
op|','
name|'mock_get_volume_driver'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_info'
op|'='
name|'get_fake_block_dev_info'
op|'('
op|')'
newline|'\n'
name|'block_device_mapping'
op|'='
name|'block_device_info'
op|'['
string|"'block_device_mapping'"
op|']'
newline|'\n'
name|'block_device_mapping'
op|'['
number|'0'
op|']'
op|'['
string|"'connection_info'"
op|']'
op|'='
op|'{'
nl|'\n'
string|"'driver_volume_type'"
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_vol_type'
op|'}'
newline|'\n'
name|'fake_volume_driver'
op|'='
name|'mock_get_volume_driver'
op|'.'
name|'return_value'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'disconnect_volumes'
op|'('
name|'block_device_info'
op|')'
newline|'\n'
name|'fake_volume_driver'
op|'.'
name|'disconnect_volumes'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'block_device_mapping'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'('
string|"'nova.block_device.volume_in_mapping'"
op|')'
newline|'\n'
DECL|member|test_ebs_root_in_block_devices
name|'def'
name|'test_ebs_root_in_block_devices'
op|'('
name|'self'
op|','
name|'mock_vol_in_mapping'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_info'
op|'='
name|'get_fake_block_dev_info'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'response'
op|'='
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'ebs_root_in_block_devices'
op|'('
name|'block_device_info'
op|')'
newline|'\n'
nl|'\n'
name|'mock_vol_in_mapping'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_default_root_device'
op|','
name|'block_device_info'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'mock_vol_in_mapping'
op|'.'
name|'return_value'
op|','
name|'response'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_get_volume_connector
dedent|''
name|'def'
name|'test_get_volume_connector'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'mock_instance'
op|'='
name|'mock'
op|'.'
name|'DEFAULT'
newline|'\n'
name|'initiator'
op|'='
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_volutils'
op|'.'
name|'get_iscsi_initiator'
op|'.'
name|'return_value'
newline|'\n'
name|'expected'
op|'='
op|'{'
string|"'ip'"
op|':'
name|'CONF'
op|'.'
name|'my_ip'
op|','
nl|'\n'
string|"'host'"
op|':'
name|'CONF'
op|'.'
name|'host'
op|','
nl|'\n'
string|"'initiator'"
op|':'
name|'initiator'
op|'}'
newline|'\n'
nl|'\n'
name|'response'
op|'='
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'get_volume_connector'
op|'('
name|'instance'
op|'='
name|'mock_instance'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_volutils'
op|'.'
name|'get_iscsi_initiator'
op|'.'
name|'assert_called_once_with'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'expected'
op|','
name|'response'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'VolumeOps'
op|','
string|"'_get_volume_driver'"
op|')'
newline|'\n'
DECL|member|test_initialize_volumes_connection
name|'def'
name|'test_initialize_volumes_connection'
op|'('
name|'self'
op|','
name|'mock_get_volume_driver'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_info'
op|'='
name|'get_fake_block_dev_info'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'initialize_volumes_connection'
op|'('
name|'block_device_info'
op|')'
newline|'\n'
nl|'\n'
name|'init_vol_conn'
op|'='
op|'('
nl|'\n'
name|'mock_get_volume_driver'
op|'.'
name|'return_value'
op|'.'
name|'initialize_volume_connection'
op|')'
newline|'\n'
name|'init_vol_conn'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'block_device_info'
op|'['
string|"'block_device_mapping'"
op|']'
op|'['
number|'0'
op|']'
op|'['
string|"'connection_info'"
op|']'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'VolumeOps'
op|','
nl|'\n'
string|"'get_mounted_disk_path_from_volume'"
op|')'
newline|'\n'
DECL|member|test_get_disk_path_mapping
name|'def'
name|'test_get_disk_path_mapping'
op|'('
name|'self'
op|','
name|'mock_get_disk_path'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_info'
op|'='
name|'get_fake_block_dev_info'
op|'('
op|')'
newline|'\n'
name|'block_device_mapping'
op|'='
name|'block_device_info'
op|'['
string|"'block_device_mapping'"
op|']'
newline|'\n'
name|'fake_conn_info'
op|'='
name|'get_fake_connection_info'
op|'('
op|')'
newline|'\n'
name|'block_device_mapping'
op|'['
number|'0'
op|']'
op|'['
string|"'connection_info'"
op|']'
op|'='
name|'fake_conn_info'
newline|'\n'
nl|'\n'
name|'mock_get_disk_path'
op|'.'
name|'return_value'
op|'='
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk_path'
newline|'\n'
nl|'\n'
name|'resulted_disk_path_mapping'
op|'='
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'get_disk_path_mapping'
op|'('
nl|'\n'
name|'block_device_info'
op|')'
newline|'\n'
nl|'\n'
name|'mock_get_disk_path'
op|'.'
name|'assert_called_once_with'
op|'('
name|'fake_conn_info'
op|')'
newline|'\n'
name|'expected_disk_path_mapping'
op|'='
op|'{'
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'serial'
op|':'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk_path'
nl|'\n'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'expected_disk_path_mapping'
op|','
nl|'\n'
name|'resulted_disk_path_mapping'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_group_block_devices_by_type
dedent|''
name|'def'
name|'test_group_block_devices_by_type'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_map'
op|'='
name|'get_fake_block_dev_info'
op|'('
op|')'
op|'['
string|"'block_device_mapping'"
op|']'
newline|'\n'
name|'block_device_map'
op|'['
number|'0'
op|']'
op|'['
string|"'connection_info'"
op|']'
op|'='
op|'{'
nl|'\n'
string|"'driver_volume_type'"
op|':'
string|"'iscsi'"
op|'}'
newline|'\n'
name|'result'
op|'='
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'_group_block_devices_by_type'
op|'('
nl|'\n'
name|'block_device_map'
op|')'
newline|'\n'
nl|'\n'
name|'expected'
op|'='
op|'{'
string|"'iscsi'"
op|':'
op|'['
name|'block_device_map'
op|'['
number|'0'
op|']'
op|']'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'expected'
op|','
name|'result'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'VolumeOps'
op|','
string|"'_get_volume_driver'"
op|')'
newline|'\n'
DECL|member|test_get_mounted_disk_path_from_volume
name|'def'
name|'test_get_mounted_disk_path_from_volume'
op|'('
name|'self'
op|','
name|'mock_get_volume_driver'
op|')'
op|':'
newline|'\n'
indent|' '
name|'fake_conn_info'
op|'='
name|'get_fake_connection_info'
op|'('
op|')'
newline|'\n'
name|'fake_volume_driver'
op|'='
name|'mock_get_volume_driver'
op|'.'
name|'return_value'
newline|'\n'
nl|'\n'
name|'resulted_disk_path'
op|'='
name|'self'
op|'.'
name|'_volumeops'
op|'.'
name|'get_mounted_disk_path_from_volume'
op|'('
nl|'\n'
name|'fake_conn_info'
op|')'
newline|'\n'
nl|'\n'
name|'mock_get_volume_driver'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'connection_info'
op|'='
name|'fake_conn_info'
op|')'
newline|'\n'
name|'get_mounted_disk'
op|'='
name|'fake_volume_driver'
op|'.'
name|'get_mounted_disk_path_from_volume'
newline|'\n'
name|'get_mounted_disk'
op|'.'
name|'assert_called_once_with'
op|'('
name|'fake_conn_info'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'get_mounted_disk'
op|'.'
name|'return_value'
op|','
nl|'\n'
name|'resulted_disk_path'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|ISCSIVolumeDriverTestCase
dedent|''
dedent|''
name|'class'
name|'ISCSIVolumeDriverTestCase'
op|'('
name|'test_base'
op|'.'
name|'HyperVBaseTestCase'
op|')'
op|':'
newline|'\n'
indent|' '
string|'"""Unit tests for Hyper-V ISCSIVolumeDriver class."""'
newline|'\n'
nl|'\n'
DECL|member|setUp
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'ISCSIVolumeDriverTestCase'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'='
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_login_storage_target_auth_exception
dedent|''
name|'def'
name|'test_login_storage_target_auth_exception'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'connection_info'
op|'='
name|'get_fake_connection_info'
op|'('
nl|'\n'
name|'auth_method'
op|'='
string|"'fake_auth_method'"
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exception'
op|'.'
name|'UnsupportedBDMVolumeAuthMethod'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'login_storage_target'
op|','
nl|'\n'
name|'connection_info'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
nl|'\n'
string|"'_get_mounted_disk_from_lun'"
op|')'
newline|'\n'
DECL|member|_check_login_storage_target
name|'def'
name|'_check_login_storage_target'
op|'('
name|'self'
op|','
name|'mock_get_mounted_disk_from_lun'
op|','
nl|'\n'
name|'dev_number'
op|')'
op|':'
newline|'\n'
indent|' '
name|'connection_info'
op|'='
name|'get_fake_connection_info'
op|'('
op|')'
newline|'\n'
name|'login_target'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|'.'
name|'login_storage_target'
newline|'\n'
name|'get_number'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|'.'
name|'get_device_number_for_target'
newline|'\n'
name|'get_number'
op|'.'
name|'return_value'
op|'='
name|'dev_number'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'login_storage_target'
op|'('
name|'connection_info'
op|')'
newline|'\n'
nl|'\n'
name|'get_number'
op|'.'
name|'assert_called_once_with'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_lun'
op|')'
newline|'\n'
name|'if'
name|'not'
name|'dev_number'
op|':'
newline|'\n'
indent|' '
name|'login_target'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_lun'
op|','
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_portal'
op|','
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_user'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_pass'
op|')'
newline|'\n'
name|'mock_get_mounted_disk_from_lun'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|','
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_lun'
op|','
name|'True'
op|')'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'assertFalse'
op|'('
name|'login_target'
op|'.'
name|'called'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_login_storage_target_already_logged
dedent|''
dedent|''
name|'def'
name|'test_login_storage_target_already_logged'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_check_login_storage_target'
op|'('
name|'dev_number'
op|'='
number|'1'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_login_storage_target
dedent|''
name|'def'
name|'test_login_storage_target'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_check_login_storage_target'
op|'('
name|'dev_number'
op|'='
number|'0'
op|')'
newline|'\n'
nl|'\n'
DECL|member|_check_logout_storage_target
dedent|''
name|'def'
name|'_check_logout_storage_target'
op|'('
name|'self'
op|','
name|'disconnected_luns_count'
op|'='
number|'0'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|'.'
name|'get_target_lun_count'
op|'.'
name|'return_value'
op|'='
number|'1'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'logout_storage_target'
op|'('
nl|'\n'
name|'target_iqn'
op|'='
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|','
nl|'\n'
name|'disconnected_luns_count'
op|'='
name|'disconnected_luns_count'
op|')'
newline|'\n'
nl|'\n'
name|'logout_storage'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|'.'
name|'logout_storage_target'
newline|'\n'
nl|'\n'
name|'if'
name|'disconnected_luns_count'
op|':'
newline|'\n'
indent|' '
name|'logout_storage'
op|'.'
name|'assert_called_once_with'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|')'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'assertFalse'
op|'('
name|'logout_storage'
op|'.'
name|'called'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_logout_storage_target_skip
dedent|''
dedent|''
name|'def'
name|'test_logout_storage_target_skip'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_check_logout_storage_target'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_logout_storage_target
dedent|''
name|'def'
name|'test_logout_storage_target'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_check_logout_storage_target'
op|'('
name|'disconnected_luns_count'
op|'='
number|'1'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
nl|'\n'
string|"'_get_mounted_disk_from_lun'"
op|')'
newline|'\n'
DECL|member|test_get_mounted_disk_path_from_volume
name|'def'
name|'test_get_mounted_disk_path_from_volume'
op|'('
name|'self'
op|','
nl|'\n'
name|'mock_get_mounted_disk_from_lun'
op|')'
op|':'
newline|'\n'
indent|' '
name|'connection_info'
op|'='
name|'get_fake_connection_info'
op|'('
op|')'
newline|'\n'
name|'resulted_disk_path'
op|'='
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'get_mounted_disk_path_from_volume'
op|'('
nl|'\n'
name|'connection_info'
op|')'
op|')'
newline|'\n'
nl|'\n'
name|'mock_get_mounted_disk_from_lun'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'connection_info'
op|'['
string|"'data'"
op|']'
op|'['
string|"'target_iqn'"
op|']'
op|','
nl|'\n'
name|'connection_info'
op|'['
string|"'data'"
op|']'
op|'['
string|"'target_lun'"
op|']'
op|','
nl|'\n'
name|'wait_for_device'
op|'='
name|'True'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'mock_get_mounted_disk_from_lun'
op|'.'
name|'return_value'
op|','
nl|'\n'
name|'resulted_disk_path'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
nl|'\n'
string|"'_get_mounted_disk_from_lun'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
string|"'logout_storage_target'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
string|"'login_storage_target'"
op|')'
newline|'\n'
DECL|member|test_attach_volume_exception
name|'def'
name|'test_attach_volume_exception'
op|'('
name|'self'
op|','
name|'mock_login_storage_target'
op|','
nl|'\n'
name|'mock_logout_storage_target'
op|','
nl|'\n'
name|'mock_get_mounted_disk'
op|')'
op|':'
newline|'\n'
indent|' '
name|'connection_info'
op|'='
name|'get_fake_connection_info'
op|'('
op|')'
newline|'\n'
name|'mock_get_mounted_disk'
op|'.'
name|'side_effect'
op|'='
name|'os_win_exc'
op|'.'
name|'HyperVException'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'os_win_exc'
op|'.'
name|'HyperVException'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'attach_volume'
op|','
name|'connection_info'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|')'
newline|'\n'
name|'mock_logout_storage_target'
op|'.'
name|'assert_called_with'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
nl|'\n'
string|"'_get_mounted_disk_from_lun'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
string|"'login_storage_target'"
op|')'
newline|'\n'
DECL|member|_check_attach_volume
name|'def'
name|'_check_attach_volume'
op|'('
name|'self'
op|','
name|'mock_login_storage_target'
op|','
nl|'\n'
name|'mock_get_mounted_disk_from_lun'
op|','
name|'ebs_root'
op|')'
op|':'
newline|'\n'
indent|' '
name|'connection_info'
op|'='
name|'get_fake_connection_info'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'get_ide_path'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'get_vm_ide_controller'
newline|'\n'
name|'get_scsi_path'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'get_vm_scsi_controller'
newline|'\n'
name|'fake_ide_path'
op|'='
name|'get_ide_path'
op|'.'
name|'return_value'
newline|'\n'
name|'fake_scsi_path'
op|'='
name|'get_scsi_path'
op|'.'
name|'return_value'
newline|'\n'
name|'fake_mounted_disk_path'
op|'='
name|'mock_get_mounted_disk_from_lun'
op|'.'
name|'return_value'
newline|'\n'
name|'attach_vol'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'attach_volume_to_controller'
newline|'\n'
nl|'\n'
name|'get_free_slot'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'get_free_controller_slot'
newline|'\n'
name|'get_free_slot'
op|'.'
name|'return_value'
op|'='
number|'1'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'attach_volume'
op|'('
nl|'\n'
name|'connection_info'
op|'='
name|'connection_info'
op|','
nl|'\n'
name|'instance_name'
op|'='
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
nl|'\n'
name|'ebs_root'
op|'='
name|'ebs_root'
op|')'
newline|'\n'
nl|'\n'
name|'mock_login_storage_target'
op|'.'
name|'assert_called_once_with'
op|'('
name|'connection_info'
op|')'
newline|'\n'
name|'mock_get_mounted_disk_from_lun'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_lun'
op|','
nl|'\n'
name|'wait_for_device'
op|'='
name|'True'
op|')'
newline|'\n'
name|'if'
name|'ebs_root'
op|':'
newline|'\n'
indent|' '
name|'get_ide_path'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
number|'0'
op|')'
newline|'\n'
name|'attach_vol'
op|'.'
name|'assert_called_once_with'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
nl|'\n'
name|'fake_ide_path'
op|','
number|'0'
op|','
nl|'\n'
name|'fake_mounted_disk_path'
op|','
nl|'\n'
name|'serial'
op|'='
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'serial'
op|')'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'get_scsi_path'
op|'.'
name|'assert_called_once_with'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|')'
newline|'\n'
name|'get_free_slot'
op|'.'
name|'assert_called_once_with'
op|'('
name|'fake_scsi_path'
op|')'
newline|'\n'
name|'attach_vol'
op|'.'
name|'assert_called_once_with'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
nl|'\n'
name|'fake_scsi_path'
op|','
number|'1'
op|','
nl|'\n'
name|'fake_mounted_disk_path'
op|','
nl|'\n'
name|'serial'
op|'='
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'serial'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume_ebs
dedent|''
dedent|''
name|'def'
name|'test_attach_volume_ebs'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_check_attach_volume'
op|'('
name|'ebs_root'
op|'='
name|'True'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume
dedent|''
name|'def'
name|'test_attach_volume'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_check_attach_volume'
op|'('
name|'ebs_root'
op|'='
name|'False'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
nl|'\n'
string|"'_get_mounted_disk_from_lun'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
string|"'logout_storage_target'"
op|')'
newline|'\n'
DECL|member|test_detach_volume
name|'def'
name|'test_detach_volume'
op|'('
name|'self'
op|','
name|'mock_logout_storage_target'
op|','
nl|'\n'
name|'mock_get_mounted_disk_from_lun'
op|')'
op|':'
newline|'\n'
indent|' '
name|'connection_info'
op|'='
name|'get_fake_connection_info'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'detach_volume'
op|'('
name|'connection_info'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|')'
newline|'\n'
nl|'\n'
name|'mock_get_mounted_disk_from_lun'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_lun'
op|','
nl|'\n'
name|'wait_for_device'
op|'='
name|'True'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'detach_vm_disk'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
nl|'\n'
name|'mock_get_mounted_disk_from_lun'
op|'.'
name|'return_value'
op|')'
newline|'\n'
name|'mock_logout_storage_target'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_get_mounted_disk_from_lun
dedent|''
name|'def'
name|'test_get_mounted_disk_from_lun'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'with'
name|'test'
op|'.'
name|'nested'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|','
nl|'\n'
string|"'get_device_number_for_target'"
op|')'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|','
nl|'\n'
string|"'get_mounted_disk_by_drive_number'"
op|')'
nl|'\n'
op|')'
name|'as'
op|'('
name|'mock_get_device_number_for_target'
op|','
nl|'\n'
name|'mock_get_mounted_disk_by_drive_number'
op|')'
op|':'
newline|'\n'
nl|'\n'
indent|' '
name|'mock_get_device_number_for_target'
op|'.'
name|'return_value'
op|'='
number|'0'
newline|'\n'
name|'mock_get_mounted_disk_by_drive_number'
op|'.'
name|'return_value'
op|'='
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk_path'
op|')'
newline|'\n'
nl|'\n'
name|'disk'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_get_mounted_disk_from_lun'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'target_iqn'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'target_lun'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk_path'
op|','
name|'disk'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_get_target_from_disk_path
dedent|''
dedent|''
name|'def'
name|'test_get_target_from_disk_path'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'result'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'get_target_from_disk_path'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'physical_drive_path'
op|')'
newline|'\n'
nl|'\n'
name|'mock_get_target'
op|'='
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|'.'
name|'get_target_from_disk_path'
op|')'
newline|'\n'
name|'mock_get_target'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'physical_drive_path'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'mock_get_target'
op|'.'
name|'return_value'
op|','
name|'result'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'('
string|"'time.sleep'"
op|')'
newline|'\n'
DECL|member|test_get_mounted_disk_from_lun_failure
name|'def'
name|'test_get_mounted_disk_from_lun_failure'
op|'('
name|'self'
op|','
name|'fake_sleep'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'flags'
op|'('
name|'mounted_disk_query_retry_count'
op|'='
number|'1'
op|','
name|'group'
op|'='
string|"'hyperv'"
op|')'
newline|'\n'
nl|'\n'
name|'with'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|','
nl|'\n'
string|"'get_device_number_for_target'"
op|')'
name|'as'
name|'m_device_num'
op|':'
newline|'\n'
indent|' '
name|'m_device_num'
op|'.'
name|'side_effect'
op|'='
op|'['
name|'None'
op|','
op|'-'
number|'1'
op|']'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exception'
op|'.'
name|'NotFound'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_get_mounted_disk_from_lun'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'target_iqn'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'target_lun'
op|')'
newline|'\n'
nl|'\n'
dedent|''
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
string|"'logout_storage_target'"
op|')'
newline|'\n'
DECL|member|test_disconnect_volumes
name|'def'
name|'test_disconnect_volumes'
op|'('
name|'self'
op|','
name|'mock_logout_storage_target'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_info'
op|'='
name|'get_fake_block_dev_info'
op|'('
op|')'
newline|'\n'
name|'connection_info'
op|'='
name|'get_fake_connection_info'
op|'('
op|')'
newline|'\n'
name|'block_device_mapping'
op|'='
name|'block_device_info'
op|'['
string|"'block_device_mapping'"
op|']'
newline|'\n'
name|'block_device_mapping'
op|'['
number|'0'
op|']'
op|'['
string|"'connection_info'"
op|']'
op|'='
name|'connection_info'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'disconnect_volumes'
op|'('
name|'block_device_mapping'
op|')'
newline|'\n'
nl|'\n'
name|'mock_logout_storage_target'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'fake_iqn'
op|','
number|'1'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_get_target_lun_count
dedent|''
name|'def'
name|'test_get_target_lun_count'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'result'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'get_target_lun_count'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'target_iqn'
op|')'
newline|'\n'
nl|'\n'
name|'mock_get_lun_count'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|'.'
name|'get_target_lun_count'
newline|'\n'
name|'mock_get_lun_count'
op|'.'
name|'assert_called_once_with'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'target_iqn'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'mock_get_lun_count'
op|'.'
name|'return_value'
op|','
name|'result'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'ISCSIVolumeDriver'
op|','
string|"'login_storage_target'"
op|')'
newline|'\n'
DECL|member|test_initialize_volume_connection
name|'def'
name|'test_initialize_volume_connection'
op|'('
name|'self'
op|','
name|'mock_login_storage_target'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'initialize_volume_connection'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'connection_info'
op|')'
newline|'\n'
name|'mock_login_storage_target'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'connection_info'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|SMBFSVolumeDriverTestCase
dedent|''
dedent|''
name|'class'
name|'SMBFSVolumeDriverTestCase'
op|'('
name|'test_base'
op|'.'
name|'HyperVBaseTestCase'
op|')'
op|':'
newline|'\n'
indent|' '
string|'"""Unit tests for the Hyper-V SMBFSVolumeDriver class."""'
newline|'\n'
nl|'\n'
DECL|variable|_FAKE_SHARE
name|'_FAKE_SHARE'
op|'='
string|"'//1.2.3.4/fake_share'"
newline|'\n'
DECL|variable|_FAKE_SHARE_NORMALIZED
name|'_FAKE_SHARE_NORMALIZED'
op|'='
name|'_FAKE_SHARE'
op|'.'
name|'replace'
op|'('
string|"'/'"
op|','
string|"'\\\\'"
op|')'
newline|'\n'
DECL|variable|_FAKE_DISK_NAME
name|'_FAKE_DISK_NAME'
op|'='
string|"'fake_volume_name.vhdx'"
newline|'\n'
DECL|variable|_FAKE_USERNAME
name|'_FAKE_USERNAME'
op|'='
string|"'fake_username'"
newline|'\n'
DECL|variable|_FAKE_PASSWORD
name|'_FAKE_PASSWORD'
op|'='
string|"'fake_password'"
newline|'\n'
name|'_FAKE_SMB_OPTIONS'
op|'='
string|"'-o username=%s,password=%s'"
op|'%'
op|'('
name|'_FAKE_USERNAME'
op|','
nl|'\n'
name|'_FAKE_PASSWORD'
op|')'
newline|'\n'
DECL|variable|_FAKE_CONNECTION_INFO
name|'_FAKE_CONNECTION_INFO'
op|'='
op|'{'
string|"'data'"
op|':'
op|'{'
string|"'export'"
op|':'
name|'_FAKE_SHARE'
op|','
nl|'\n'
string|"'name'"
op|':'
name|'_FAKE_DISK_NAME'
op|','
nl|'\n'
string|"'options'"
op|':'
name|'_FAKE_SMB_OPTIONS'
op|','
nl|'\n'
string|"'volume_id'"
op|':'
string|"'fake_vol_id'"
op|'}'
op|'}'
newline|'\n'
nl|'\n'
DECL|member|setUp
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'SMBFSVolumeDriverTestCase'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'='
name|'volumeops'
op|'.'
name|'SMBFSVolumeDriver'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_smbutils'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_volutils'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'SMBFSVolumeDriver'
op|','
nl|'\n'
string|"'_get_disk_path'"
op|')'
newline|'\n'
DECL|member|test_get_mounted_disk_path_from_volume
name|'def'
name|'test_get_mounted_disk_path_from_volume'
op|'('
name|'self'
op|','
name|'mock_get_disk_path'
op|')'
op|':'
newline|'\n'
indent|' '
name|'disk_path'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'get_mounted_disk_path_from_volume'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'conn_info'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'mock_get_disk_path'
op|'.'
name|'return_value'
op|','
name|'disk_path'
op|')'
newline|'\n'
name|'mock_get_disk_path'
op|'.'
name|'assert_called_once_with'
op|'('
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'conn_info'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'SMBFSVolumeDriver'
op|','
string|"'ensure_share_mounted'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'SMBFSVolumeDriver'
op|','
string|"'_get_disk_path'"
op|')'
newline|'\n'
DECL|member|_check_attach_volume
name|'def'
name|'_check_attach_volume'
op|'('
name|'self'
op|','
name|'mock_get_disk_path'
op|','
nl|'\n'
name|'mock_ensure_share_mounted'
op|','
name|'ebs_root'
op|'='
name|'False'
op|')'
op|':'
newline|'\n'
indent|' '
name|'mock_get_disk_path'
op|'.'
name|'return_value'
op|'='
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk_path'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'attach_volume'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
nl|'\n'
name|'ebs_root'
op|')'
newline|'\n'
nl|'\n'
name|'if'
name|'ebs_root'
op|':'
newline|'\n'
indent|' '
name|'get_vm_ide_controller'
op|'='
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'get_vm_ide_controller'
op|')'
newline|'\n'
name|'get_vm_ide_controller'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
number|'0'
op|')'
newline|'\n'
name|'ctrller_path'
op|'='
name|'get_vm_ide_controller'
op|'.'
name|'return_value'
newline|'\n'
name|'slot'
op|'='
number|'0'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'get_vm_scsi_controller'
op|'='
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'get_vm_scsi_controller'
op|')'
newline|'\n'
name|'get_vm_scsi_controller'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|')'
newline|'\n'
name|'get_free_controller_slot'
op|'='
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'get_free_controller_slot'
op|')'
newline|'\n'
name|'get_free_controller_slot'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'get_vm_scsi_controller'
op|'.'
name|'return_value'
op|')'
newline|'\n'
nl|'\n'
name|'ctrller_path'
op|'='
name|'get_vm_scsi_controller'
op|'.'
name|'return_value'
newline|'\n'
name|'slot'
op|'='
name|'get_free_controller_slot'
op|'.'
name|'return_value'
newline|'\n'
nl|'\n'
dedent|''
name|'mock_ensure_share_mounted'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|')'
newline|'\n'
name|'mock_get_disk_path'
op|'.'
name|'assert_called_once_with'
op|'('
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'attach_drive'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk_path'
op|','
nl|'\n'
name|'ctrller_path'
op|','
name|'slot'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume_ide
dedent|''
name|'def'
name|'test_attach_volume_ide'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_check_attach_volume'
op|'('
name|'ebs_root'
op|'='
name|'True'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume_scsi
dedent|''
name|'def'
name|'test_attach_volume_scsi'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_check_attach_volume'
op|'('
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'SMBFSVolumeDriver'
op|','
string|"'ensure_share_mounted'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'SMBFSVolumeDriver'
op|','
string|"'_get_disk_path'"
op|')'
newline|'\n'
DECL|member|test_attach_non_existing_image
name|'def'
name|'test_attach_non_existing_image'
op|'('
name|'self'
op|','
name|'mock_get_disk_path'
op|','
nl|'\n'
name|'mock_ensure_share_mounted'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'attach_drive'
op|'.'
name|'side_effect'
op|'='
op|'('
nl|'\n'
name|'os_win_exc'
op|'.'
name|'HyperVException'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exception'
op|'.'
name|'VolumeAttachFailed'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'attach_volume'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'SMBFSVolumeDriver'
op|','
string|"'_get_disk_path'"
op|')'
newline|'\n'
DECL|member|test_detach_volume
name|'def'
name|'test_detach_volume'
op|'('
name|'self'
op|','
name|'mock_get_disk_path'
op|')'
op|':'
newline|'\n'
indent|' '
name|'mock_get_disk_path'
op|'.'
name|'return_value'
op|'='
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk_path'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'detach_volume'
op|'('
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|','
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_vmutils'
op|'.'
name|'detach_vm_disk'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'instance_name'
op|','
name|'mock'
op|'.'
name|'sentinel'
op|'.'
name|'disk_path'
op|','
nl|'\n'
name|'is_physical'
op|'='
name|'False'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_parse_credentials
dedent|''
name|'def'
name|'test_parse_credentials'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'username'
op|','
name|'password'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_parse_credentials'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_SMB_OPTIONS'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'self'
op|'.'
name|'_FAKE_USERNAME'
op|','
name|'username'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'self'
op|'.'
name|'_FAKE_PASSWORD'
op|','
name|'password'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_get_export_path
dedent|''
name|'def'
name|'test_get_export_path'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'result'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_get_export_path'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|')'
newline|'\n'
nl|'\n'
name|'expected'
op|'='
name|'self'
op|'.'
name|'_FAKE_SHARE'
op|'.'
name|'replace'
op|'('
string|"'/'"
op|','
string|"'\\\\'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'expected'
op|','
name|'result'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_get_disk_path
dedent|''
name|'def'
name|'test_get_disk_path'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'expected'
op|'='
name|'os'
op|'.'
name|'path'
op|'.'
name|'join'
op|'('
name|'self'
op|'.'
name|'_FAKE_SHARE_NORMALIZED'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_DISK_NAME'
op|')'
newline|'\n'
nl|'\n'
name|'disk_path'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_get_disk_path'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'expected'
op|','
name|'disk_path'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'volumeops'
op|'.'
name|'SMBFSVolumeDriver'
op|','
string|"'_parse_credentials'"
op|')'
newline|'\n'
DECL|member|_test_ensure_mounted
name|'def'
name|'_test_ensure_mounted'
op|'('
name|'self'
op|','
name|'mock_parse_credentials'
op|','
name|'is_mounted'
op|'='
name|'False'
op|')'
op|':'
newline|'\n'
indent|' '
name|'mock_mount_smb_share'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_smbutils'
op|'.'
name|'mount_smb_share'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_smbutils'
op|'.'
name|'check_smb_mapping'
op|'.'
name|'return_value'
op|'='
op|'('
nl|'\n'
name|'is_mounted'
op|')'
newline|'\n'
name|'mock_parse_credentials'
op|'.'
name|'return_value'
op|'='
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_USERNAME'
op|','
name|'self'
op|'.'
name|'_FAKE_PASSWORD'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'ensure_share_mounted'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|')'
newline|'\n'
nl|'\n'
name|'if'
name|'is_mounted'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'assertFalse'
op|'('
nl|'\n'
name|'mock_mount_smb_share'
op|'.'
name|'called'
op|')'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'mock_mount_smb_share'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_SHARE_NORMALIZED'
op|','
nl|'\n'
name|'username'
op|'='
name|'self'
op|'.'
name|'_FAKE_USERNAME'
op|','
nl|'\n'
name|'password'
op|'='
name|'self'
op|'.'
name|'_FAKE_PASSWORD'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_ensure_mounted_new_share
dedent|''
dedent|''
name|'def'
name|'test_ensure_mounted_new_share'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_test_ensure_mounted'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_ensure_already_mounted
dedent|''
name|'def'
name|'test_ensure_already_mounted'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_test_ensure_mounted'
op|'('
name|'is_mounted'
op|'='
name|'True'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_disconnect_volumes
dedent|''
name|'def'
name|'test_disconnect_volumes'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'block_device_mapping'
op|'='
op|'['
nl|'\n'
op|'{'
string|"'connection_info'"
op|':'
name|'self'
op|'.'
name|'_FAKE_CONNECTION_INFO'
op|'}'
op|']'
newline|'\n'
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'disconnect_volumes'
op|'('
name|'block_device_mapping'
op|')'
newline|'\n'
name|'mock_unmount_share'
op|'='
name|'self'
op|'.'
name|'_volume_driver'
op|'.'
name|'_smbutils'
op|'.'
name|'unmount_smb_share'
newline|'\n'
name|'mock_unmount_share'
op|'.'
name|'assert_called_once_with'
op|'('
nl|'\n'
name|'self'
op|'.'
name|'_FAKE_SHARE_NORMALIZED'
op|')'
newline|'\n'
dedent|''
dedent|''
endmarker|''
end_unit
| 13.389601
| 88
| 0.642935
| 8,034
| 53,304
| 4.038462
| 0.033856
| 0.174018
| 0.080444
| 0.064293
| 0.926244
| 0.891971
| 0.844105
| 0.795593
| 0.750994
| 0.697858
| 0
| 0.001028
| 0.087517
| 53,304
| 3,980
| 89
| 13.392965
| 0.666029
| 0
| 0
| 0.956281
| 0
| 0
| 0.413234
| 0.116408
| 0
| 0
| 0
| 0
| 0.016332
| 0
| null | null | 0.003518
| 0.002261
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
68b78902c8d131cad08563d6376ec6bc6f40afff
| 94
|
py
|
Python
|
web.py
|
modrzew/animarkov
|
95898a905c8ade79ce61aff0b583344de57e559a
|
[
"MIT"
] | null | null | null |
web.py
|
modrzew/animarkov
|
95898a905c8ade79ce61aff0b583344de57e559a
|
[
"MIT"
] | null | null | null |
web.py
|
modrzew/animarkov
|
95898a905c8ade79ce61aff0b583344de57e559a
|
[
"MIT"
] | null | null | null |
try:
from .animarkov.web import app
except ImportError:
from animarkov.web import app
| 18.8
| 34
| 0.744681
| 13
| 94
| 5.384615
| 0.615385
| 0.371429
| 0.457143
| 0.628571
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.202128
| 94
| 4
| 35
| 23.5
| 0.933333
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.75
| 0
| 0.75
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| 0
| null | 1
| 1
| 1
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| 0
| 0
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| 0
| 0
| 0
| 1
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| 0
| 0
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| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
68dc8dadf22dc940c5d6b238e68fc8e8e2e069c1
| 206
|
py
|
Python
|
vb_baseapp/management/template_structures/models/__init__.py
|
vbyazilim/django-vb-baseapp
|
83a62a9d7cb349351ea64aeeb616afe9a94cda5d
|
[
"MIT"
] | null | null | null |
vb_baseapp/management/template_structures/models/__init__.py
|
vbyazilim/django-vb-baseapp
|
83a62a9d7cb349351ea64aeeb616afe9a94cda5d
|
[
"MIT"
] | 1
|
2021-10-30T16:44:15.000Z
|
2021-10-30T16:44:15.000Z
|
vb_baseapp/management/template_structures/models/__init__.py
|
vbyazilim/django-vb-baseapp
|
83a62a9d7cb349351ea64aeeb616afe9a94cda5d
|
[
"MIT"
] | null | null | null |
# isort:skip_file
# flake8: noqa
from .basemodel import TEMPLATE_MODEL_BASEMODEL
from .django import TEMPLATE_MODEL_DJANGO
from .softdelete import TEMPLATE_MODEL_SOFTDELETEMODEL
from .custom_user import *
| 25.75
| 54
| 0.849515
| 27
| 206
| 6.185185
| 0.555556
| 0.251497
| 0.341317
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005435
| 0.106796
| 206
| 7
| 55
| 29.428571
| 0.902174
| 0.135922
| 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
|
6b4d7ceb1102803dd65f4f26c38b98709f9da0bb
| 113
|
py
|
Python
|
tests/parser/aggregates.domain.max.1.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
tests/parser/aggregates.domain.max.1.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
tests/parser/aggregates.domain.max.1.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
input = """
f(one).
true :- #max{ X : f(X) } >= 0.
"""
output = """
f(one).
true :- #max{ X : f(X) } >= 0.
"""
| 10.272727
| 30
| 0.362832
| 18
| 113
| 2.277778
| 0.444444
| 0.195122
| 0.390244
| 0.536585
| 0.731707
| 0.731707
| 0.731707
| 0.731707
| 0
| 0
| 0
| 0.024096
| 0.265487
| 113
| 10
| 31
| 11.3
| 0.46988
| 0
| 0
| 0.75
| 0
| 0
| 0.725664
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
6bc795a5fc4f21559c20e9cd6b385a8cc825c420
| 126
|
py
|
Python
|
src/tests/conftest.py
|
goffstown-sports-app/Football-Field
|
9f56a8519a836e72aad6b2405e7d337858d29b65
|
[
"MIT"
] | 3
|
2021-09-24T22:46:16.000Z
|
2022-02-07T21:10:30.000Z
|
src/tests/conftest.py
|
goffstown-sports-app/Football-Field
|
9f56a8519a836e72aad6b2405e7d337858d29b65
|
[
"MIT"
] | 43
|
2019-07-01T03:44:50.000Z
|
2020-09-28T10:15:48.000Z
|
src/tests/conftest.py
|
goffstown-sports-app/Football-Field
|
9f56a8519a836e72aad6b2405e7d337858d29b65
|
[
"MIT"
] | 1
|
2019-10-14T00:09:40.000Z
|
2019-10-14T00:09:40.000Z
|
def pytest_emoji_passed(config):
return "🍏 ", "PASSED 🍏 "
def pytest_emoji_failed(config):
return "🍎 ", "FAILED 🍎 "
| 18
| 32
| 0.634921
| 18
| 126
| 4.444444
| 0.5
| 0.225
| 0.35
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206349
| 126
| 6
| 33
| 21
| 0.76
| 0
| 0
| 0
| 0
| 0
| 0.174603
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0.5
| 0
| 0.5
| 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
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 8
|
6bd2e60fa6dd2aff3c4153cbbc081e6815080b0f
| 12
|
py
|
Python
|
src/test.py
|
fudanwqd/cskg_counterfactual_generation-main
|
fb68ad0f3b29bf378915ff644accbfb3983748b2
|
[
"CC0-1.0"
] | null | null | null |
src/test.py
|
fudanwqd/cskg_counterfactual_generation-main
|
fb68ad0f3b29bf378915ff644accbfb3983748b2
|
[
"CC0-1.0"
] | null | null | null |
src/test.py
|
fudanwqd/cskg_counterfactual_generation-main
|
fb68ad0f3b29bf378915ff644accbfb3983748b2
|
[
"CC0-1.0"
] | null | null | null |
import re
| 3
| 9
| 0.666667
| 2
| 12
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 12
| 3
| 10
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| 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
|
6be14adeda77aab2c75ecfcfa8da36249a06b60d
| 28,671
|
py
|
Python
|
casa/calibration_flag.py
|
AMIGA-IAA/hcg-16
|
8c110ee6f9e39e5d285c74678c806bf273b558b3
|
[
"MIT"
] | 2
|
2019-07-10T12:16:22.000Z
|
2019-08-09T12:47:00.000Z
|
casa/calibration_flag.py
|
AMIGA-IAA/hcg-16
|
8c110ee6f9e39e5d285c74678c806bf273b558b3
|
[
"MIT"
] | 9
|
2019-03-08T16:27:07.000Z
|
2021-09-22T17:03:10.000Z
|
casa/calibration_flag.py
|
AMIGA-IAA/hcg-16
|
8c110ee6f9e39e5d285c74678c806bf273b558b3
|
[
"MIT"
] | null | null | null |
#Import the VLA archive data files
importvla(archivefiles=['AW500_C990113.xp1','AW500_D990114.xp1'],vis='HCG16_C')
importvla(archivefiles=['AW234_B891206.xp1'],vis='HCG16_D')
#Plot antennae locations
#plotants(vis='HCG16_C',figfile='ant_loc_C.png')
#plotants(vis='HCG16_D',figfile='ant_loc_D.png')
#Calibration of C-array data
#Flag dummy scan and bad RFI
flagdata(vis='HCG16_C',field='2',timerange='04:32:40~04:32:50')
flagdata(vis='HCG16_C',field='2',spw='0:10',antenna='VA07;VA10')
#Flag shadowed antennae
flagdata(vis='HCG16_C', mode='shadow', tolerance=5.0, flagbackup=False)
#Flag zero-amplitude data
flagdata(vis='HCG16_C', mode='clip', clipzeros=True, flagbackup=False)
#Quack
flagdata(vis='HCG16_C', mode='quack', quackinterval=5.0, quackmode='beg', flagbackup=False)
#Print flag summary
flagInfo = flagdata(vis='HCG16_C', mode='summary')
#Save with just the inital flags
flagmanager(vis='HCG16_C', mode='save', versionname='initial_flags')
#Gaincurve (elevation) calibration
gencal(vis='HCG16_C',caltable='gaincurve.cal',caltype='gceff')
#Set gain calibrator flux (will use current model, Perley & Butler 2013 find it only varies by ~2% in L-band)
setjy(vis='HCG16_C',field='2',spw='0',scalebychan=True,model='3C48_L.im')
#plotms(vis='HCG16_C',field='2',
# xaxis='time',yaxis='phase',correlation='RR',
# avgchannel='64',spw='0:4~58',antenna='VA11', coloraxis='antenna2')
#Fit delay calibration for the bandpass calibrator
#Use VA11 as reference antenna
gaincal(vis='HCG16_C',field='2',caltable='delays.cal',refant='VA11',gaintype='K',gaintable=['gaincurve.cal'])
#Make the bandpass calibration table
gaincal(vis='HCG16_C',field='2',caltable='bpphase.gcal',spw='0:5~55',refant='VA11',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal'])
#plotcal(caltable='bpphase.gcal',xaxis='time',yaxis='phase',
# iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
#Bandpass solution
bandpass(vis='HCG16_C',field='2',caltable='bandpass.bcal',refant='VA11',solnorm=True,solint='inf',gaintable=['gaincurve.cal','delays.cal','bpphase.gcal'])
#plotcal(caltable='bandpass.bcal',xaxis='chan',yaxis='amp',
# iteration='antenna',subplot=331)
#plotcal(caltable='bandpass.bcal',xaxis='chan',yaxis='phase',
# iteration='antenna',subplot=331)
#Apply initial solutions
applycal(vis='HCG16_C',field='2',gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'],gainfield=['','2','2'])
#plotms(vis='HCG16_C',field='2',
# xaxis='channel',yaxis='phase',ydatacolumn='corrected',
# correlation='RR',
# avgtime='1e8',spw='0:4~58',antenna='VA11', coloraxis='antenna2')
#plotms(vis='HCG16_C',field='2',
# xaxis='channel',yaxis='amp',ydatacolumn='corrected',
# correlation='RR',
# avgtime='1e8',spw='0:4~58',antenna='VA11', coloraxis='antenna2')
#Gain calibration
#Integration phase
gaincal(vis='HCG16_C',field='1,2',caltable='intphase.gcal',refant='VA11',spw='0:5~55',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
#plotcal(caltable='intphase.gcal',xaxis='time',yaxis='phase',
# iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
#Scan phase
gaincal(vis='HCG16_C',field='1,2',caltable='scanphase.gcal',refant='VA11',spw='0:5~55',calmode='p',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
#plotcal(caltable='scanphase.gcal',xaxis='time',yaxis='phase',
# iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
#Amplitude solutions
gaincal(vis='HCG16_C',field='1,2',caltable='amp.gcal',refant='VA11',spw='0:5~55',calmode='ap',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal'])
#plotcal(caltable='amp.gcal',xaxis='time',yaxis='phase',
# iteration='antenna',subplot=331,plotrange=[-1,-1,-20,20])
#Scale fluxes
fluxscale(vis='HCG16_C',caltable='amp.gcal',
fluxtable='flux.cal',reference='2',incremental=True)
#Apply calibration to bandpass/flux calibrator
applycal(vis='HCG16_C',field='2',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','2','2','2'],
calwt=False)
#plotms(vis='HCG16_C',field='2',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna1')
#Gain of first sample seems to be low - flag it
flagdata(vis='HCG16_C',field='2',timerange='04:32:50~04:33:00')
#Do a better job of flagging the RFI in channel 10
flagdata(vis='HCG16_C',field='2',spw='0:10',antenna='VA01&VA03;VA04&VA11;VA05&VA24;VA05&VA25;VA06&VA09')
flagdata(vis='HCG16_C',field='2',spw='0:10',antenna='VA03&VA20;VA04&VA23;VA05&VA23')
flagdata(vis='HCG16_C',field='2',spw='0:10',antenna='VA04&VA05;VA04&VA24;VA05&VA11;VA05&VA14;VA09&VA14;VA09&VA28;VA14&VA24;VA14&VA28')
flagdata(vis='HCG16_C',field='2',spw='0:10',antenna='VA03&VA15;VA11&VA24;VA23&VA24')
flagdata(vis='HCG16_C',field='2',spw='0:10',antenna='VA03&VA12;VA11&VA14;VA24&VA25')
flagdata(vis='HCG16_C',field='2',spw='0:11',antenna='VA05&VA07;VA05&VA10;VA07&VA10;VA07&VA14;VA07&VA24;VA10&VA23;VA10&VA24')
flagdata(vis='HCG16_C',field='2',spw='0:09',antenna='VA05&VA07;VA05&VA10;VA07&VA10;VA07&VA14;VA07&VA24;VA10&VA23;VA10&VA24')
#Repeat calibration with improved flagging
gaincal(vis='HCG16_C',field='2',caltable='delays.cal',refant='VA11',gaintype='K',gaintable=['gaincurve.cal'])
gaincal(vis='HCG16_C',field='2',caltable='bpphase.gcal',spw='0:5~55',refant='VA11',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal'])
bandpass(vis='HCG16_C',field='2',caltable='bandpass.bcal',refant='VA11',solnorm=True,solint='inf',gaintable=['gaincurve.cal','delays.cal','bpphase.gcal'])
applycal(vis='HCG16_C',field='2',gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'],gainfield=['','2','2'])
gaincal(vis='HCG16_C',field='1,2',caltable='intphase.gcal',refant='VA11',spw='0:5~55',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_C',field='1,2',caltable='scanphase.gcal',refant='VA11',spw='0:5~55',calmode='p',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_C',field='1,2',caltable='amp.gcal',refant='VA11',spw='0:5~55',calmode='ap',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal'])
fluxscale(vis='HCG16_C',caltable='amp.gcal',
fluxtable='flux.cal',reference='2',incremental=True)
applycal(vis='HCG16_C',field='2',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','2','2','2'],
calwt=False)
#plotms(vis='HCG16_C',field='2',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna1')
#There are still some very low flux spikes at particular times
flagdata(vis='HCG16_C',field='2',spw='0',antenna='VA26',timerange='04:35:00~04:35:10')
flagdata(vis='HCG16_C',field='2',spw='0',antenna='VA19',timerange='04:34:50~04:35:00')
flagdata(vis='HCG16_C',field='2',spw='0',antenna='VA21',timerange='04:36:20~04:36:30')
flagdata(vis='HCG16_C',field='2',spw='0',antenna='VA17',timerange='04:35:10~04:35:20')
#Repeat calibration steps again
gaincal(vis='HCG16_C',field='2',caltable='delays.cal',refant='VA11',gaintype='K',gaintable=['gaincurve.cal'])
gaincal(vis='HCG16_C',field='2',caltable='bpphase.gcal',spw='0:5~55',refant='VA11',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal'])
bandpass(vis='HCG16_C',field='2',caltable='bandpass.bcal',refant='VA11',solnorm=True,solint='inf',gaintable=['gaincurve.cal','delays.cal','bpphase.gcal'])
applycal(vis='HCG16_C',field='2',gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'],gainfield=['','2','2'])
gaincal(vis='HCG16_C',field='1,2',caltable='intphase.gcal',refant='VA11',spw='0:5~55',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_C',field='1,2',caltable='scanphase.gcal',refant='VA11',spw='0:5~55',calmode='p',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_C',field='1,2',caltable='amp.gcal',refant='VA11',spw='0:5~55',calmode='ap',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal'])
fluxscale(vis='HCG16_C',caltable='amp.gcal',
fluxtable='flux.cal',reference='2',incremental=True)
applycal(vis='HCG16_C',field='2',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','2','2','2'],
calwt=False)
#plotms(vis='HCG16_C',field='2',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna1')
#Apply calibration to phase calibrator
applycal(vis='HCG16_C',field='1',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','1','1','1'],
calwt=False)
#plotms(vis='HCG16_C',field='1',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna2')
#Flag RFI and bad data
flagdata(vis='HCG16_C',field='1',spw='0',antenna='VA22&VA23',timerange='1999/01/14/03:38:00~1999/01/14/03:38:10')
flagdata(vis='HCG16_C',field='1',spw='0:44',antenna='VA25;VA28',timerange='1999/01/13/23:28:00~1999/01/13/23:38:00')
#For the really bad RFI use the automated proceedures
#flagdata(vis='HCG16_C', mode='tfcrop', field='1,2', spw='0',
# datacolumn='corrected', action='calculate',
# display='both', flagbackup=False)
flagdata(vis='HCG16_C', mode='tfcrop', field='1,2', spw='0',
datacolumn='corrected', action='apply',
display='none', flagbackup=False)
#flagdata(vis='HCG16_C', mode='rflag', field='1,2', spw='0', datacolumn='corrected',
# action='calculate', display='both', flagbackup=False)
flagdata(vis='HCG16_C', mode='rflag', field='1,2', spw='0', datacolumn='corrected',
action='apply', display='none', flagbackup=False)
#Recalculate calibration
gaincal(vis='HCG16_C',field='2',caltable='delays.cal',refant='VA11',gaintype='K',gaintable=['gaincurve.cal'])
gaincal(vis='HCG16_C',field='2',caltable='bpphase.gcal',spw='0:5~55',refant='VA11',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal'])
bandpass(vis='HCG16_C',field='2',caltable='bandpass.bcal',refant='VA11',solnorm=True,solint='inf',gaintable=['gaincurve.cal','delays.cal','bpphase.gcal'])
applycal(vis='HCG16_C',field='2',gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'],gainfield=['','2','2'])
gaincal(vis='HCG16_C',field='1,2',caltable='intphase.gcal',refant='VA11',spw='0:5~55',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_C',field='1,2',caltable='scanphase.gcal',refant='VA11',spw='0:5~55',calmode='p',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_C',field='1,2',caltable='amp.gcal',refant='VA11',spw='0:5~55',calmode='ap',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal'])
fluxscale(vis='HCG16_C',caltable='amp.gcal',
fluxtable='flux.cal',reference='2',incremental=True)
applycal(vis='HCG16_C',field='2',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','2','2','2'],
calwt=False)
#plotms(vis='HCG16_C',field='2',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna1')
applycal(vis='HCG16_C',field='1',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','1','1','1'],
calwt=False)
#plotms(vis='HCG16_C',field='1',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna2')
#Looks ok now apply to target data
applycal(vis='HCG16_C',field='0',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','1','1','1'],
calwt=False)
#Calibration of D-array data
#Flag shadowed antennae
flagdata(vis='HCG16_D', mode='shadow', tolerance=5.0, flagbackup=False)
#Flag zero-amplitude data
flagdata(vis='HCG16_D', mode='clip', clipzeros=True, flagbackup=False)
#Quack
flagdata(vis='HCG16_D', mode='quack', quackinterval=5.0, quackmode='beg', flagbackup=False)
#Print flag summary
flagInfo = flagdata(vis='HCG16_D', mode='summary')
#Save with just the inital flags
flagmanager(vis='HCG16_D', mode='save', versionname='initial_flags')
#Gaincurve (elevation) calibration
gencal(vis='HCG16_D',caltable='gaincurve.cal',caltype='gceff')
#Set gain calibrator flux (will use current model, Perley & Butler 2013 find it only varies by ~2% in L-band)
setjy(vis='HCG16_D',field='2',spw='0',scalebychan=True,model='3C48_L.im')
#plotms(vis='HCG16_D',field='2',
# xaxis='time',yaxis='phase',correlation='RR',
# avgchannel='64',spw='0:4~58',antenna='VA06', coloraxis='antenna2')
#Fit delay calibration for the bandpass calibrator
#Use VA06 as reference antenna
gaincal(vis='HCG16_D',field='2',caltable='delays.cal',refant='VA06',gaintype='K',gaintable=['gaincurve.cal'])
#Make the bandpass calibration table
gaincal(vis='HCG16_D',field='2',caltable='bpphase.gcal',spw='0:5~55',refant='VA06',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal'])
#plotcal(caltable='bpphase.gcal',xaxis='time',yaxis='phase',
# iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
#Bandpass solution
bandpass(vis='HCG16_D',field='2',caltable='bandpass.bcal',refant='VA06',solnorm=True,solint='inf',gaintable=['gaincurve.cal','delays.cal','bpphase.gcal'])
#plotcal(caltable='bandpass.bcal',xaxis='chan',yaxis='amp',
# iteration='antenna',subplot=331)
#plotcal(caltable='bandpass.bcal',xaxis='chan',yaxis='phase',
# iteration='antenna',subplot=331)
#Apply initial solutions
applycal(vis='HCG16_D',field='2',gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'],gainfield=['','2','2'])
#plotms(vis='HCG16_D',field='2',
# xaxis='channel',yaxis='phase',ydatacolumn='corrected',
# correlation='RR',
# avgtime='1e8',spw='0:4~58',antenna='VA06', coloraxis='antenna2')
#plotms(vis='HCG16_D',field='2',
# xaxis='channel',yaxis='amp',ydatacolumn='corrected',
# correlation='RR',
# avgtime='1e8',spw='0:4~58',antenna='VA06', coloraxis='antenna2')
#Gain calibration
#Integration phase
gaincal(vis='HCG16_D',field='0,2',caltable='intphase.gcal',refant='VA06',spw='0:5~55',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
#plotcal(caltable='intphase.gcal',xaxis='time',yaxis='phase',
# iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
#Scan phase
gaincal(vis='HCG16_D',field='0,2',caltable='scanphase.gcal',refant='VA06',spw='0:5~55',calmode='p',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
#plotcal(caltable='scanphase.gcal',xaxis='time',yaxis='phase',
# iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
#Amplitude solutions
gaincal(vis='HCG16_D',field='0,2',caltable='amp.gcal',refant='VA06',spw='0:5~55',calmode='ap',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal'])
#plotcal(caltable='amp.gcal',xaxis='time',yaxis='phase',
# iteration='antenna',subplot=331,plotrange=[-1,-1,-20,20])
#Scale fluxes
fluxscale(vis='HCG16_D',caltable='amp.gcal',
fluxtable='flux.cal',reference='2',incremental=True)
#Apply calibration to bandpass/flux calibrator
applycal(vis='HCG16_D',field='2',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','2','2','2'],
calwt=False)
#plotms(vis='HCG16_D',field='2',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna1')
#Flag RFI
flagdata(vis='HCG16_D',field='2',spw='0',timerange='08:03:10~08:03:20')
#Use tfcrop to get rid of bad RFI
#flagdata(vis='HCG16_D', mode='tfcrop', field='2', spw='0',
# datacolumn='corrected', action='calculate',
# display='both', flagbackup=False)
flagdata(vis='HCG16_D', mode='tfcrop', field='2', spw='0',
datacolumn='corrected', action='apply',
display='none', flagbackup=False)
#Repeat calibration
gaincal(vis='HCG16_D',field='2',caltable='delays.cal',refant='VA06',gaintype='K',gaintable=['gaincurve.cal'])
gaincal(vis='HCG16_D',field='2',caltable='bpphase.gcal',spw='0:5~55',refant='VA06',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal'])
bandpass(vis='HCG16_D',field='2',caltable='bandpass.bcal',refant='VA06',solnorm=True,solint='inf',gaintable=['gaincurve.cal','delays.cal','bpphase.gcal'])
applycal(vis='HCG16_D',field='2',gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'],gainfield=['','2','2'])
gaincal(vis='HCG16_D',field='0,2',caltable='intphase.gcal',refant='VA06',spw='0:5~55',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_D',field='0,2',caltable='scanphase.gcal',refant='VA06',spw='0:5~55',calmode='p',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_D',field='0,2',caltable='amp.gcal',refant='VA06',spw='0:5~55',calmode='ap',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal'])
fluxscale(vis='HCG16_D',caltable='amp.gcal',
fluxtable='flux.cal',reference='2',incremental=True)
applycal(vis='HCG16_D',field='2',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','2','2','2'],
calwt=False)
#plotms(vis='HCG16_D',field='2',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna1')
#Apply calibration to phase calibrator
applycal(vis='HCG16_D',field='0',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','0','0','0'],
calwt=False)
#plotms(vis='HCG16_D',field='0',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna2')
#Flag obvious RFI
flagdata(vis='HCG16_D',field='0',spw='0',timerange='04:35:10~04:35:20')
flagdata(vis='HCG16_D',field='0',spw='0',timerange='04:35:40~04:35:50')
flagdata(vis='HCG16_D',field='0',spw='0',timerange='05:20:40~05:20:50')
flagdata(vis='HCG16_D',field='0',spw='0',timerange='05:20:10~05:20:20')
flagdata(vis='HCG16_D',field='0',spw='0',timerange='06:04:40~06:04:50')
flagdata(vis='HCG16_D',field='0',spw='0',timerange='06:04:10~06:04:20')
flagdata(vis='HCG16_D',field='0',spw='0',antenna='VA02&VA24',scan='5')
flagdata(vis='HCG16_D',field='0',spw='0',antenna='VA09&VA10;VA09&VA12',scan='7')
flagdata(vis='HCG16_D',field='0',spw='0',antenna='VA13&VA27;VA25&VA27',scan='3')
flagdata(vis='HCG16_D',field='0',spw='0',antenna='VA09&VA12;VA10&VA12',scan='19')
#Use automated methods to get rid of really bad RFI
#flagdata(vis='HCG16_D', mode='tfcrop', field='0', spw='0',
# datacolumn='corrected', action='calculate',
# display='both', flagbackup=False)
flagdata(vis='HCG16_D', mode='tfcrop', field='0', spw='0',
datacolumn='corrected', action='apply',
display='none', flagbackup=False)
#flagdata(vis='HCG16_D', mode='rflag', field='0', spw='0', datacolumn='corrected',
# action='calculate', display='both', flagbackup=False)
flagdata(vis='HCG16_D', mode='rflag', field='0', spw='0', datacolumn='corrected',
action='apply', display='none', flagbackup=False)
#Repeat calibration
gaincal(vis='HCG16_D',field='2',caltable='delays.cal',refant='VA06',gaintype='K',gaintable=['gaincurve.cal'])
gaincal(vis='HCG16_D',field='2',caltable='bpphase.gcal',spw='0:5~55',refant='VA06',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal'])
bandpass(vis='HCG16_D',field='2',caltable='bandpass.bcal',refant='VA06',solnorm=True,solint='inf',gaintable=['gaincurve.cal','delays.cal','bpphase.gcal'])
applycal(vis='HCG16_D',field='2',gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'],gainfield=['','2','2'])
gaincal(vis='HCG16_D',field='0,2',caltable='intphase.gcal',refant='VA06',spw='0:5~55',calmode='p',solint='10s',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_D',field='0,2',caltable='scanphase.gcal',refant='VA06',spw='0:5~55',calmode='p',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal'])
gaincal(vis='HCG16_D',field='0,2',caltable='amp.gcal',refant='VA06',spw='0:5~55',calmode='ap',solint='inf',minsnr=2.0,gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal'])
fluxscale(vis='HCG16_D',caltable='amp.gcal',
fluxtable='flux.cal',reference='2',incremental=True)
applycal(vis='HCG16_D',field='2',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','2','2','2'],
calwt=False)
applycal(vis='HCG16_D',field='0',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','0','0','0'],
calwt=False)
#plotms(vis='HCG16_D',field='0',ydatacolumn='corrected',
# xaxis='time',yaxis='amp',correlation='RR,LL',
# avgchannel='64',spw='0:4~58',antenna='', coloraxis='antenna2')
#Looks ok now apply to target data
applycal(vis='HCG16_D',field='1',
gaintable=['gaincurve.cal','delays.cal','bandpass.bcal','intphase.gcal','amp.gcal','flux.cal'],
gainfield=['','2','2','0','0','0'],
calwt=False)
#Split the target fields off
split(vis='HCG16_C',outputvis='HCG16_C.split',field='0')
split(vis='HCG16_D',outputvis='HCG16_D.split',field='1')
#Now flag the target data
flagInfo = flagdata(vis='HCG16_C.split', mode='summary')
flagmanager(vis='HCG16_C.split', mode='save', versionname='start_flags')
#Flag obvious problems by hand
flagdata(vis='HCG16_C.split',spw='0:61~62')
flagdata(vis='HCG16_C.split',spw='0',antenna='VA17&VA22',timerange='1999/01/13/01:00:00~1999/01/14/01:10:00')
flagdata(vis='HCG16_C.split',spw='0',antenna='VA01&VA22;VA04&VA22;VA10&VA22;VA20&VA22;VA22&VA23;VA22&VA25')
flagdata(vis='HCG16_C.split',spw='0',antenna='VA01&VA28',timerange='1999/01/14/02:13:25~1999/01/14/02:13:35')
flagdata(vis='HCG16_C.split',spw='0:43~45',antenna='VA07;VA28',timerange='1999/01/13/01:00:00~1999/01/14/00:23:23')
#Save these flags before automatic steps
flagInfo = flagdata(vis='HCG16_C.split', mode='summary')
flagmanager(vis='HCG16_C.split', mode='save', versionname='manual_flags')
#For the really bad RFI use the automated proceedures
flagdata(vis='HCG16_C.split', mode='tfcrop', spw='0', action='calculate',
display='none', flagbackup=False)
flagdata(vis='HCG16_C.split', mode='tfcrop', spw='0', action='apply',
display='none', flagbackup=False)
flagdata(vis='HCG16_C.split', mode='rflag', spw='0', timedevscale=4.0, freqdevscale=4.0,
action='calculate', display='none', flagbackup=False)
flagdata(vis='HCG16_C.split', mode='rflag', spw='0', timedevscale=4.0, freqdevscale=4.0,
action='apply', display='none', flagbackup=False)
flagInfo = flagdata(vis='HCG16_C.split', mode='summary')
flagmanager(vis='HCG16_C.split', mode='save', versionname='final_flags')
flagInfo = flagdata(vis='HCG16_D.split', mode='summary')
flagmanager(vis='HCG16_D.split', mode='save', versionname='start_flags')
#Flag
flagdata(vis='HCG16_D.split',spw='0:0')
flagdata(vis='HCG16_D.split',spw='0:62')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA09&VA12;VA14&VA20',timerange='04:26:55~04:27:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA04&VA10;VA09&VA12;VA14&VA20',timerange='04:44:55~04:45:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA04&VA10',timerange='03:30:00~12:00:00')
flagdata(vis='HCG16_D.split', spw='0', antenna='', mode='manual', flagbackup=False, timerange='1989/12/06/04:49:55~1989/12/06/04:50:05,1989/12/06/06:25:55~1989/12/06/06:26:05,1989/12/06/07:44:55~1989/12/06/07:46:05,1989/12/06/06:21:55~1989/12/06/06:22:05,1989/12/06/06:13:55~1989/12/06/06:14:05,1989/12/06/06:47:55~1989/12/06/06:48:05,1989/12/06/05:47:55~1989/12/06/05:48:05,1989/12/06/05:37:55~1989/12/06/05:38:05,1989/12/06/05:29:55~1989/12/06/05:30:05,1989/12/06/05:11:55~1989/12/06/05:12:05,1989/12/06/04:45:55~1989/12/06/04:46:05,1989/12/06/04:19:55~1989/12/06/04:20:05,1989/12/06/04:09:55~1989/12/06/04:10:05,1989/12/06/04:01:55~1989/12/06/04:02:05,1989/12/06/03:45:55~1989/12/06/03:46:05,1989/12/06/03:27:55~1989/12/06/03:28:05,1989/12/06/00:27:55~1989/12/06/00:28:05')
flagdata(vis='HCG16_D.split', spw='0:8~11', antenna='', mode='manual', flagbackup=False, timerange='')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA24',timerange='01:38:55~01:45:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA04;VA02&VA11;VA02&VA19;VA03&VA04;VA03&VA19;VA04&VA11;VA04&VA13;VA04&VA19;VA11&VA13;VA11&VA19;VA13&VA19;VA17&VA19',timerange='06:22:55~06:23:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA04&VA11;VA04&VA12;VA06&VA17;VA09&VA10;VA09&VA12;VA10&VA11;VA10&VA12;VA11&VA19',timerange='06:12:55~06:13:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA05;VA03&VA27;VA04&VA11;VA09&VA10;VA10&VA11;VA10&VA12;VA11&VA19',timerange='05:28:55~05:29:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='',timerange='04:44:55~04:49:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA10;VA09&VA10;VA09&VA12;VA10&VA12',timerange='06:30:55~06:31:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA10;VA09&VA10;VA09&VA12',timerange='06:20:55~06:21:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA04;VA02&VA10;VA02&VA11;VA03&VA11;VA03&VA19;VA04&VA19;VA14&VA20',timerange='06:12:55~06:13:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA04',timerange='06:10:55~06:11:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA04',timerange='06:08:55~06:09:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA01&VA11;VA01&VA19;VA02&VA04;VA02&VA11;VA04&VA11;VA09&VA10;VA10&VA12;VA11&VA19;VA14&VA20',timerange='05:54:55~05:55:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA04;VA02&VA05;VA02&VA10;VA02&VA11;VA04&VA11;VA09&VA10;VA09&VA12;VA10&VA11;VA10&VA12',timerange='05:46:55~05:47:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA10;VA04&VA11;VA10&VA11;VA10&VA12',timerange='05:44:55~05:45:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA04;VA02&VA05;VA02&VA11;VA03&VA17;VA04&VA11;VA05&VA11;VA09&VA12;VA10&VA12;VA17&VA27',timerange='05:36:55~05:37:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA04;VA02&VA10;VA02&VA11',timerange='05:28:55~05:29:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA11;VA04&VA11;VA09&VA10',timerange='05:10:55~05:11:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA04&VA11;VA09&VA12',timerange='04:52:55~04:53:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA01&VA08;VA01&VA11;VA06&VA17;VA08&VA16;VA08&VA28;VA17&VA27;VA17&VA28',timerange='04:50:55~04:51:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA09&VA10;VA09&VA12',timerange='04:18:55~04:19:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA02&VA17;VA02&VA20;VA02&VA28;VA09&VA10;VA11&VA19;VA17&VA20;VA20&VA28',timerange='04:08:55~04:09:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA01&VA02;VA01&VA19;VA02&VA03;VA02&VA17;VA02&VA20;VA02&VA28;VA09&VA10;VA09&VA12',timerange='04:00:55~04:01:05')
flagdata(vis='HCG16_D.split',spw='0',antenna='VA01&VA19;VA11&VA19',timerange='03:26:55~03:27:05')
#Save final flags
flagInfo = flagdata(vis='HCG16_C.split', mode='summary')
flagmanager(vis='HCG16_C.split', mode='save', versionname='final_flags')
flagInfo = flagdata(vis='HCG16_D.split', mode='summary')
flagmanager(vis='HCG16_D.split', mode='save', versionname='final_flags')
| 54.820268
| 776
| 0.693453
| 4,527
| 28,671
| 4.345262
| 0.068036
| 0.078084
| 0.04438
| 0.043414
| 0.897463
| 0.870571
| 0.848965
| 0.835291
| 0.819684
| 0.788877
| 0
| 0.11399
| 0.064316
| 28,671
| 522
| 777
| 54.925287
| 0.619264
| 0.244114
| 0
| 0.590308
| 0
| 0.088106
| 0.423047
| 0.106912
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.211454
| 0.008811
| 0
| 0.008811
| 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
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| null | 0
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| 1
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| 0
| 0
|
0
| 7
|
d43ed5beb6a8402a407bd4e595285290ea167e8c
| 347
|
py
|
Python
|
fgfa_rfcn/symbols/__init__.py
|
BritaryZhou/OFF_FGFA
|
dfff0f5af22dc7cb8dcbdc83b527b437299d4f2c
|
[
"MIT"
] | null | null | null |
fgfa_rfcn/symbols/__init__.py
|
BritaryZhou/OFF_FGFA
|
dfff0f5af22dc7cb8dcbdc83b527b437299d4f2c
|
[
"MIT"
] | null | null | null |
fgfa_rfcn/symbols/__init__.py
|
BritaryZhou/OFF_FGFA
|
dfff0f5af22dc7cb8dcbdc83b527b437299d4f2c
|
[
"MIT"
] | null | null | null |
import resnet_v1_101_flownet_rfcn
import resnet_v1_101_flownet_off_rfcn
import resnet_v1_101_off_rfcn
import resnet_v1_101_off_bind_rfcn
import resnet_v1_101_off3_bind_rfcn
import resnet_v1_101_off6_bind_rfcn
import resnet_v1_101_off3_concat_rfcn
import resnet_v1_101_off6_concat_rfcn
import resnet_v1_101_off_sobel_rfcn
import resnet_v1_101_rfcn
| 31.545455
| 37
| 0.942363
| 66
| 347
| 4.257576
| 0.181818
| 0.427046
| 0.498221
| 0.604982
| 0.967972
| 0.708185
| 0.3879
| 0
| 0
| 0
| 0
| 0.134557
| 0.057637
| 347
| 10
| 38
| 34.7
| 0.724771
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 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
|
d47a2a97f1e40bfec0959c9fb68f30dab3228a5f
| 2,086
|
py
|
Python
|
test/test_ssc.py
|
mfkiwl/autobern
|
7e331717572d43f24d403112027799d11c8b8847
|
[
"MIT"
] | null | null | null |
test/test_ssc.py
|
mfkiwl/autobern
|
7e331717572d43f24d403112027799d11c8b8847
|
[
"MIT"
] | null | null | null |
test/test_ssc.py
|
mfkiwl/autobern
|
7e331717572d43f24d403112027799d11c8b8847
|
[
"MIT"
] | null | null | null |
#! /usr/bin/python
#-*- coding: utf-8 -*-
from __future__ import print_function
import sys
import os
import re
import argparse
import datetime
import pybern.products.formats.ssc as ssc
#if len(sys.argv) != 2:
# print('[ERROR] Usage {:} [SSC FILE]'.format(sys.argv[0]))
# sys.exit(1)
#
#print('{:}'.format('-'*80))
#ssc_recs = ssc.parse_ssc(sys.argv[1], ['dyng', 'zimm', 'ankr', 'aut1'], datetime.datetime.now())
#for site in ssc_recs:
# x, y, z = site.extrapolate(datetime.datetime.now())
# print('{:} {:} {:12.3f} {:12.3f} {:12.3f}'.format(site.id, site.domes, x, y, z))
#
#print('{:}'.format('-'*80))
#ssc_recs = ssc.parse_ssc(sys.argv[1], ['dyng', 'zimm', 'ankr', 'aut1'], datetime.datetime.strptime('1983-01-13', '%Y-%m-%d'))
#for site in ssc_recs:
# x, y, z = site.extrapolate(datetime.datetime.now())
# print('{:} {:} {:12.3f} {:12.3f} {:12.3f}'.format(site.id, site.domes, x, y, z))
#
#print('{:}'.format('-'*80))
#ssc_recs = ssc.parse_ssc(sys.argv[1], ['dyng', 'zimm', 'ankr', 'aut1'], datetime.datetime.strptime('2015-263', '%Y-%j'))
#for site in ssc_recs:
# x, y, z = site.extrapolate(datetime.datetime.now())
# print('{:} {:} {:12.3f} {:12.3f} {:12.3f}'.format(site.id, site.domes, x, y, z))
#
#print('{:}'.format('-'*80))
#ssc_recs = ssc.parse_ssc(sys.argv[1], ['dyng', 'zimm', 'ankr', 'aut1'], datetime.datetime.strptime('2015-262', '%Y-%j'))
#for site in ssc_recs:
# x, y, z = site.extrapolate(datetime.datetime.now())
# print('{:} {:} {:12.3f} {:12.3f} {:12.3f}'.format(site.id, site.domes, x, y, z))
#
#print('{:}'.format('-'*80))
#ssc_recs = ssc.parse_ssc(sys.argv[1], ['dyng', 'zimm', 'ankr', 'aut1'], datetime.datetime.strptime('2015-270', '%Y-%j'))
#for site in ssc_recs:
# x, y, z = site.extrapolate(datetime.datetime.now())
# print('{:} {:} {:12.3f} {:12.3f} {:12.3f}'.format(site.id, site.domes, x, y, z))
fn = ['EPN_A_IGb14_C2145.SSC', 'EPND_D2150_IGS14.SSC']
dir = '/home/bpe/tables/ssc'
fns = [os.path.join(dir, f) for f in fn]
ssc.ssc2crd(['dyng', 'kasi', 'aut1', 'noa1', 'mtna', 'akyr'], datetime.datetime.now(), *fns)
| 41.72
| 126
| 0.60163
| 330
| 2,086
| 3.727273
| 0.251515
| 0.04878
| 0.02439
| 0.065041
| 0.711382
| 0.711382
| 0.711382
| 0.711382
| 0.711382
| 0.711382
| 0
| 0.061614
| 0.120805
| 2,086
| 49
| 127
| 42.571429
| 0.609051
| 0.791946
| 0
| 0
| 0
| 0
| 0.213033
| 0.052632
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.636364
| 0
| 0.636364
| 0.090909
| 0
| 0
| 0
| null | 0
| 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
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
2e2f3e473d31238c888f33d9ffc8b0fcbb7943c8
| 53,911
|
py
|
Python
|
main.py
|
AfdhalAtiffTan/Cable_Robot_Control_Panel
|
ad305eeda0a46d2cca3097d43b0423d90f407f57
|
[
"MIT"
] | 2
|
2018-05-28T22:07:39.000Z
|
2019-03-31T02:36:03.000Z
|
main.py
|
AfdhalAtiffTan/Cable_Robot_Control_Panel
|
ad305eeda0a46d2cca3097d43b0423d90f407f57
|
[
"MIT"
] | null | null | null |
main.py
|
AfdhalAtiffTan/Cable_Robot_Control_Panel
|
ad305eeda0a46d2cca3097d43b0423d90f407f57
|
[
"MIT"
] | null | null | null |
from GUI import Ui_MainWindow #Generated by Qt Designer
from PyQt4 import QtCore, QtGui
import serial
import time
import math
import Holding_Registers
import minimalmodbus
class StartQT4(QtGui.QMainWindow):
instrument = minimalmodbus
def __init__(self, parent=None):
QtGui.QWidget.__init__(self, parent)
self.ui = Ui_MainWindow()
self.ui.setupUi(self)
##################Buttons#######################################################################
self.ui.pushButton_1.clicked.connect(self.emergency_stop)
self.ui.pushButton_2.clicked.connect(self.X_Plus)
self.ui.pushButton_3.clicked.connect(self.X_Minus)
self.ui.pushButton_4.clicked.connect(self.Y_Plus)
self.ui.pushButton_5.clicked.connect(self.Y_Minus)
self.ui.pushButton_10.clicked.connect(self.Z_Plus)
self.ui.pushButton_11.clicked.connect(self.Z_Minus)
self.ui.pushButton_12.clicked.connect(self.connect)
self.ui.pushButton_13.clicked.connect(self.disconnect)
self.ui.pushButton_14.clicked.connect(self.HomeAll_Coordinate)
self.ui.pushButton_15.clicked.connect(self.HomeAll_Length)
self.ui.pushButton_18.clicked.connect(self.WinchA_Extrude)
self.ui.pushButton_19.clicked.connect(self.WinchA_Retract)
self.ui.pushButton_20.clicked.connect(self.WinchB_Extrude)
self.ui.pushButton_21.clicked.connect(self.WinchB_Retract)
self.ui.pushButton_22.clicked.connect(self.WinchC_Extrude)
self.ui.pushButton_23.clicked.connect(self.WinchC_Retract)
self.ui.pushButton_24.clicked.connect(self.WinchD_Extrude)
self.ui.pushButton_25.clicked.connect(self.WinchD_Retract)
self.ui.pushButton_26.clicked.connect(self.WinchA_Zero)
self.ui.pushButton_27.clicked.connect(self.WinchB_Zero)
self.ui.pushButton_28.clicked.connect(self.WinchC_Zero)
self.ui.pushButton_29.clicked.connect(self.WinchD_Zero)
self.ui.pushButton_30.clicked.connect(self.WinchB_ReadMonitor1)
self.ui.pushButton_31.clicked.connect(self.WinchA_ReadMonitor1)
self.ui.pushButton_32.clicked.connect(self.WinchA_Goto)
self.ui.pushButton_33.clicked.connect(self.WinchA_Read_PID)
self.ui.pushButton_34.clicked.connect(self.Waypoint_Goto)
self.ui.pushButton_35.clicked.connect(self.WinchA_Reset)
self.ui.pushButton_36.clicked.connect(self.WinchB_Goto)
self.ui.pushButton_37.clicked.connect(self.WinchB_Read_PID)
self.ui.pushButton_38.clicked.connect(self.WinchB_Reset)
self.ui.pushButton_39.clicked.connect(self.WinchC_Goto)
self.ui.pushButton_40.clicked.connect(self.WinchC_Read_PID)
self.ui.pushButton_41.clicked.connect(self.WinchC_Reset)
self.ui.pushButton_42.clicked.connect(self.WinchD_Goto)
self.ui.pushButton_43.clicked.connect(self.WinchD_Read_PID)
self.ui.pushButton_44.clicked.connect(self.Read_Target_Length)
self.ui.pushButton_45.clicked.connect(self.Read_Target_Coordinate)
self.ui.pushButton_46.clicked.connect(self.WinchD_Reset)
self.ui.pushButton_47.clicked.connect(self.WinchA_Write_PID)
self.ui.pushButton_48.clicked.connect(self.WinchB_Write_PID)
self.ui.pushButton_49.clicked.connect(self.WinchC_Write_PID)
self.ui.pushButton_50.clicked.connect(self.WinchD_Write_PID)
self.ui.pushButton_51.clicked.connect(self.WinchC_ReadMonitor1)
self.ui.pushButton_52.clicked.connect(self.Write_Field_Settings)
self.ui.pushButton_53.clicked.connect(self.Write_Motion_Settings)
self.ui.pushButton_54.clicked.connect(self.WinchD_ReadMonitor1)
##################Buttons#######################################################################
def connect(self, text):
try:
self.instrument = minimalmodbus.Instrument(str(self.ui.lineEdit.text()), 1)
self.instrument.serial.baudrate = 9600 # Baudrate
self.instrument.serial.bytesize = 8
self.instrument.serial.parity = serial.PARITY_NONE
self.instrument.serial.stopbits = 1
self.instrument.serial.timeout = 0.2 # seconds
self.instrument.address = 1 # this is the slave address number
self.instrument.mode = minimalmodbus.MODE_RTU # rtu or ascii mode
self.instrument.debug = False
if (self.instrument.serial.is_open == False):
self.instrument.serial.open()
self.ui.statusbar.showMessage("Connected.")
print str(self.instrument) + '\n\n'
except:
print "Connection failed."
self.ui.statusbar.showMessage("Connection failed.")
def disconnect(self):
try:
self.instrument.serial.close()
print "Disconnected."
self.ui.statusbar.showMessage("Disconnected.")
except:
print "Disconnect failed."
self.ui.statusbar.showMessage("Disconnect failed.")
def emergency_stop(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Soft_Reset, 1, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Soft_Reset, 1, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Soft_Reset, 1, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Soft_Reset, 1, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchA_Extrude(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchB_Extrude(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchC_Extrude(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchD_Extrude(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchA_Retract(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchB_Retract(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchC_Retract(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchD_Retract(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchA_Zero(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Current_Encoder_Count, 0, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchB_Zero(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Current_Encoder_Count, 0, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchC_Zero(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Current_Encoder_Count, 0, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchD_Zero(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Current_Encoder_Count, 0, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchA_Goto(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint, int(self.ui.lineEdit_13.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchB_Goto(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint, int(self.ui.lineEdit_14.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchC_Goto(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint, int(self.ui.lineEdit_15.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchD_Goto(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_Setpoint, int(self.ui.lineEdit_16.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchA_Reset(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Soft_Reset, 1, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchB_Reset(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Soft_Reset, 1, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchC_Reset(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Soft_Reset, 1, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchD_Reset(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Soft_Reset, 1, numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def HomeAll_Length(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Current_Encoder_Count, int(self.ui.lineEdit_6.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Current_Encoder_Count, int(self.ui.lineEdit_8.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Current_Encoder_Count, int(self.ui.lineEdit_7.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Current_Encoder_Count, int(self.ui.lineEdit_9.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def HomeAll_Coordinate(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_registers(Holding_Registers.Map.Current_X, [int(self.ui.lineEdit_79.text()), int(self.ui.lineEdit_4.text()), int(self.ui.lineEdit_5.text())])
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_registers(Holding_Registers.Map.Current_X, [int(self.ui.lineEdit_79.text()), int(self.ui.lineEdit_4.text()), int(self.ui.lineEdit_5.text())])
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_registers(Holding_Registers.Map.Current_X, [int(self.ui.lineEdit_79.text()), int(self.ui.lineEdit_4.text()), int(self.ui.lineEdit_5.text())])
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_registers(Holding_Registers.Map.Current_X, [int(self.ui.lineEdit_79.text()), int(self.ui.lineEdit_4.text()), int(self.ui.lineEdit_5.text())])
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Waypoint_Goto(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_registers(Holding_Registers.Map.Target_X, [int(self.ui.lineEdit_11.text()), int(self.ui.lineEdit_10.text()), int(self.ui.lineEdit_12.text())])
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_registers(Holding_Registers.Map.Target_X, [int(self.ui.lineEdit_11.text()), int(self.ui.lineEdit_10.text()), int(self.ui.lineEdit_12.text())])
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_registers(Holding_Registers.Map.Target_X, [int(self.ui.lineEdit_11.text()), int(self.ui.lineEdit_10.text()), int(self.ui.lineEdit_12.text())])
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_registers(Holding_Registers.Map.Target_X, [int(self.ui.lineEdit_11.text()), int(self.ui.lineEdit_10.text()), int(self.ui.lineEdit_12.text())])
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def X_Plus(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_X_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_X_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_X_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_X_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Y_Plus(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_Y_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_Y_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_Y_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_Y_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Z_Plus(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_Z_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_Z_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_Z_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_Z_Offset, int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def X_Minus(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_X_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_X_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_X_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_X_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Y_Minus(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_Y_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_Y_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_Y_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_Y_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Z_Minus(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_register(Holding_Registers.Map.Target_Z_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_register(Holding_Registers.Map.Target_Z_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_register(Holding_Registers.Map.Target_Z_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_register(Holding_Registers.Map.Target_Z_Offset, -1*int(self.ui.lineEdit_2.text()), numberOfDecimals=0, functioncode=16, signed=True)
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchA_Write_PID(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 1
self.instrument.write_registers(Holding_Registers.Map.Kp, [int(self.ui.lineEdit_17.text()), int(self.ui.lineEdit_18.text()), int(self.ui.lineEdit_19.text())])
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchB_Write_PID(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 2
self.instrument.write_registers(Holding_Registers.Map.Kp, [int(self.ui.lineEdit_48.text()), int(self.ui.lineEdit_58.text()), int(self.ui.lineEdit_59.text())])
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchC_Write_PID(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 3
self.instrument.write_registers(Holding_Registers.Map.Kp, [int(self.ui.lineEdit_66.text()), int(self.ui.lineEdit_67.text()), int(self.ui.lineEdit_68.text())])
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchD_Write_PID(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
try:
self.instrument.address = 4
self.instrument.write_registers(Holding_Registers.Map.Kp, [int(self.ui.lineEdit_69.text()), int(self.ui.lineEdit_70.text()), int(self.ui.lineEdit_71.text())])
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Write_Field_Settings(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_registers(Holding_Registers.Map.Field_Length, [int(self.ui.lineEdit_72.text()), int(self.ui.lineEdit_73.text())])
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_registers(Holding_Registers.Map.Field_Length, [int(self.ui.lineEdit_72.text()), int(self.ui.lineEdit_73.text())])
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_registers(Holding_Registers.Map.Field_Length, [int(self.ui.lineEdit_72.text()), int(self.ui.lineEdit_73.text())])
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_registers(Holding_Registers.Map.Field_Length, [int(self.ui.lineEdit_72.text()), int(self.ui.lineEdit_73.text())])
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Write_Motion_Settings(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.instrument.write_registers(Holding_Registers.Map.Max_Velocity, [int(self.ui.lineEdit_74.text()), int(self.ui.lineEdit_75.text())])
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.instrument.write_registers(Holding_Registers.Map.Max_Velocity, [int(self.ui.lineEdit_74.text()), int(self.ui.lineEdit_75.text())])
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.instrument.write_registers(Holding_Registers.Map.Max_Velocity, [int(self.ui.lineEdit_74.text()), int(self.ui.lineEdit_75.text())])
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.instrument.write_registers(Holding_Registers.Map.Max_Velocity, [int(self.ui.lineEdit_74.text()), int(self.ui.lineEdit_75.text())])
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Read_Target_Length(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.ui.lineEdit_23.setText(str(self.instrument.read_register(Holding_Registers.Map.Target_Setpoint)))
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.ui.lineEdit_22.setText(str(self.instrument.read_register(Holding_Registers.Map.Target_Setpoint)))
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.ui.lineEdit_21.setText(str(self.instrument.read_register(Holding_Registers.Map.Target_Setpoint)))
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.ui.lineEdit_3.setText(str(self.instrument.read_register(Holding_Registers.Map.Target_Setpoint)))
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def Read_Target_Coordinate(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
self.ui.lineEdit_24.setText(str(self.instrument.read_registers(Holding_Registers.Map.Target_X, 3)))
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
self.ui.lineEdit_25.setText(str(self.instrument.read_registers(Holding_Registers.Map.Target_X, 3)))
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
self.ui.lineEdit_26.setText(str(self.instrument.read_registers(Holding_Registers.Map.Target_X, 3)))
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
self.ui.lineEdit_36.setText(str(self.instrument.read_registers(Holding_Registers.Map.Target_X, 3)))
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchA_ReadMonitor1(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
data_recv = self.instrument.read_registers(Holding_Registers.Map.Current_Encoder_Count, 3)
self.ui.lineEdit_76.setText(str(data_recv[0]))
self.ui.lineEdit_77.setText(str(data_recv[1]))
self.ui.lineEdit_78.setText(str(data_recv[2]))
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchB_ReadMonitor1(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
data_recv = self.instrument.read_registers(Holding_Registers.Map.Current_Encoder_Count, 3)
self.ui.lineEdit_76.setText(str(data_recv[0]))
self.ui.lineEdit_77.setText(str(data_recv[1]))
self.ui.lineEdit_78.setText(str(data_recv[2]))
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchC_ReadMonitor1(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
data_recv = self.instrument.read_registers(Holding_Registers.Map.Current_Encoder_Count, 3)
self.ui.lineEdit_76.setText(str(data_recv[0]))
self.ui.lineEdit_77.setText(str(data_recv[1]))
self.ui.lineEdit_78.setText(str(data_recv[2]))
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchD_ReadMonitor1(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
data_recv = self.instrument.read_registers(Holding_Registers.Map.Current_Encoder_Count, 3)
self.ui.lineEdit_76.setText(str(data_recv[0]))
self.ui.lineEdit_77.setText(str(data_recv[1]))
self.ui.lineEdit_78.setText(str(data_recv[2]))
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchA_Read_PID(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 1
data_recv = self.instrument.read_registers(Holding_Registers.Map.Kp, 3)
self.ui.lineEdit_17.setText(str(data_recv[0]))
self.ui.lineEdit_18.setText(str(data_recv[1]))
self.ui.lineEdit_19.setText(str(data_recv[2]))
status_msg += "WinchA OK # "
except:
status_msg += "WinchA NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchB_Read_PID(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 2
data_recv = self.instrument.read_registers(Holding_Registers.Map.Kp, 3)
self.ui.lineEdit_48.setText(str(data_recv[0]))
self.ui.lineEdit_58.setText(str(data_recv[1]))
self.ui.lineEdit_59.setText(str(data_recv[2]))
status_msg += "WinchB OK # "
except:
status_msg += "WinchB NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchC_Read_PID(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 3
data_recv = self.instrument.read_registers(Holding_Registers.Map.Kp, 3)
self.ui.lineEdit_66.setText(str(data_recv[0]))
self.ui.lineEdit_67.setText(str(data_recv[1]))
self.ui.lineEdit_68.setText(str(data_recv[2]))
status_msg += "WinchC OK # "
except:
status_msg += "WinchC NOK * "
self.ui.statusbar.showMessage(status_msg)
def WinchD_Read_PID(self):
status_msg = ""
try:
if (self.instrument.serial.is_open == True):
status_msg = "Connected # "
else:
status_msg = "Disconnected * "
except:
status_msg = "Disconnected * "
self.ui.statusbar.showMessage(status_msg)
try:
self.instrument.address = 4
data_recv = self.instrument.read_registers(Holding_Registers.Map.Kp, 3)
self.ui.lineEdit_69.setText(str(data_recv[0]))
self.ui.lineEdit_70.setText(str(data_recv[1]))
self.ui.lineEdit_71.setText(str(data_recv[2]))
status_msg += "WinchD OK # "
except:
status_msg += "WinchD NOK * "
self.ui.statusbar.showMessage(status_msg)
if __name__ == "__main__":
import sys
app = QtGui.QApplication(sys.argv)
MainWindow = StartQT4()
MainWindow.show()
sys.exit(app.exec_())
| 37.80575
| 176
| 0.572722
| 5,703
| 53,911
| 5.210766
| 0.035245
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| 0.067638
| 0.099741
| 0.893495
| 0.876199
| 0.875257
| 0.875257
| 0.866373
| 0.866373
| 0
| 0.016966
| 0.318877
| 53,911
| 1,426
| 177
| 37.80575
| 0.79232
| 0.001966
| 0
| 0.857998
| 1
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| 0.083509
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.006843
| null | null | 0.003422
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
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| 1
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| null | 0
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| 0
| 0
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|
0
| 9
|
2e5fc86555ce6eb27c4970fa849d8f20b2287ddd
| 6,269
|
py
|
Python
|
loldib/getratings/models/NA/na_jinx/na_jinx_top.py
|
koliupy/loldib
|
c9ab94deb07213cdc42b5a7c26467cdafaf81b7f
|
[
"Apache-2.0"
] | null | null | null |
loldib/getratings/models/NA/na_jinx/na_jinx_top.py
|
koliupy/loldib
|
c9ab94deb07213cdc42b5a7c26467cdafaf81b7f
|
[
"Apache-2.0"
] | null | null | null |
loldib/getratings/models/NA/na_jinx/na_jinx_top.py
|
koliupy/loldib
|
c9ab94deb07213cdc42b5a7c26467cdafaf81b7f
|
[
"Apache-2.0"
] | null | null | null |
from getratings.models.ratings import Ratings
class NA_Jinx_Top_Aatrox(Ratings):
pass
class NA_Jinx_Top_Ahri(Ratings):
pass
class NA_Jinx_Top_Akali(Ratings):
pass
class NA_Jinx_Top_Alistar(Ratings):
pass
class NA_Jinx_Top_Amumu(Ratings):
pass
class NA_Jinx_Top_Anivia(Ratings):
pass
class NA_Jinx_Top_Annie(Ratings):
pass
class NA_Jinx_Top_Ashe(Ratings):
pass
class NA_Jinx_Top_AurelionSol(Ratings):
pass
class NA_Jinx_Top_Azir(Ratings):
pass
class NA_Jinx_Top_Bard(Ratings):
pass
class NA_Jinx_Top_Blitzcrank(Ratings):
pass
class NA_Jinx_Top_Brand(Ratings):
pass
class NA_Jinx_Top_Braum(Ratings):
pass
class NA_Jinx_Top_Caitlyn(Ratings):
pass
class NA_Jinx_Top_Camille(Ratings):
pass
class NA_Jinx_Top_Cassiopeia(Ratings):
pass
class NA_Jinx_Top_Chogath(Ratings):
pass
class NA_Jinx_Top_Corki(Ratings):
pass
class NA_Jinx_Top_Darius(Ratings):
pass
class NA_Jinx_Top_Diana(Ratings):
pass
class NA_Jinx_Top_Draven(Ratings):
pass
class NA_Jinx_Top_DrMundo(Ratings):
pass
class NA_Jinx_Top_Ekko(Ratings):
pass
class NA_Jinx_Top_Elise(Ratings):
pass
class NA_Jinx_Top_Evelynn(Ratings):
pass
class NA_Jinx_Top_Ezreal(Ratings):
pass
class NA_Jinx_Top_Fiddlesticks(Ratings):
pass
class NA_Jinx_Top_Fiora(Ratings):
pass
class NA_Jinx_Top_Fizz(Ratings):
pass
class NA_Jinx_Top_Galio(Ratings):
pass
class NA_Jinx_Top_Gangplank(Ratings):
pass
class NA_Jinx_Top_Garen(Ratings):
pass
class NA_Jinx_Top_Gnar(Ratings):
pass
class NA_Jinx_Top_Gragas(Ratings):
pass
class NA_Jinx_Top_Graves(Ratings):
pass
class NA_Jinx_Top_Hecarim(Ratings):
pass
class NA_Jinx_Top_Heimerdinger(Ratings):
pass
class NA_Jinx_Top_Illaoi(Ratings):
pass
class NA_Jinx_Top_Irelia(Ratings):
pass
class NA_Jinx_Top_Ivern(Ratings):
pass
class NA_Jinx_Top_Janna(Ratings):
pass
class NA_Jinx_Top_JarvanIV(Ratings):
pass
class NA_Jinx_Top_Jax(Ratings):
pass
class NA_Jinx_Top_Jayce(Ratings):
pass
class NA_Jinx_Top_Jhin(Ratings):
pass
class NA_Jinx_Top_Jinx(Ratings):
pass
class NA_Jinx_Top_Kalista(Ratings):
pass
class NA_Jinx_Top_Karma(Ratings):
pass
class NA_Jinx_Top_Karthus(Ratings):
pass
class NA_Jinx_Top_Kassadin(Ratings):
pass
class NA_Jinx_Top_Katarina(Ratings):
pass
class NA_Jinx_Top_Kayle(Ratings):
pass
class NA_Jinx_Top_Kayn(Ratings):
pass
class NA_Jinx_Top_Kennen(Ratings):
pass
class NA_Jinx_Top_Khazix(Ratings):
pass
class NA_Jinx_Top_Kindred(Ratings):
pass
class NA_Jinx_Top_Kled(Ratings):
pass
class NA_Jinx_Top_KogMaw(Ratings):
pass
class NA_Jinx_Top_Leblanc(Ratings):
pass
class NA_Jinx_Top_LeeSin(Ratings):
pass
class NA_Jinx_Top_Leona(Ratings):
pass
class NA_Jinx_Top_Lissandra(Ratings):
pass
class NA_Jinx_Top_Lucian(Ratings):
pass
class NA_Jinx_Top_Lulu(Ratings):
pass
class NA_Jinx_Top_Lux(Ratings):
pass
class NA_Jinx_Top_Malphite(Ratings):
pass
class NA_Jinx_Top_Malzahar(Ratings):
pass
class NA_Jinx_Top_Maokai(Ratings):
pass
class NA_Jinx_Top_MasterYi(Ratings):
pass
class NA_Jinx_Top_MissFortune(Ratings):
pass
class NA_Jinx_Top_MonkeyKing(Ratings):
pass
class NA_Jinx_Top_Mordekaiser(Ratings):
pass
class NA_Jinx_Top_Morgana(Ratings):
pass
class NA_Jinx_Top_Nami(Ratings):
pass
class NA_Jinx_Top_Nasus(Ratings):
pass
class NA_Jinx_Top_Nautilus(Ratings):
pass
class NA_Jinx_Top_Nidalee(Ratings):
pass
class NA_Jinx_Top_Nocturne(Ratings):
pass
class NA_Jinx_Top_Nunu(Ratings):
pass
class NA_Jinx_Top_Olaf(Ratings):
pass
class NA_Jinx_Top_Orianna(Ratings):
pass
class NA_Jinx_Top_Ornn(Ratings):
pass
class NA_Jinx_Top_Pantheon(Ratings):
pass
class NA_Jinx_Top_Poppy(Ratings):
pass
class NA_Jinx_Top_Quinn(Ratings):
pass
class NA_Jinx_Top_Rakan(Ratings):
pass
class NA_Jinx_Top_Rammus(Ratings):
pass
class NA_Jinx_Top_RekSai(Ratings):
pass
class NA_Jinx_Top_Renekton(Ratings):
pass
class NA_Jinx_Top_Rengar(Ratings):
pass
class NA_Jinx_Top_Riven(Ratings):
pass
class NA_Jinx_Top_Rumble(Ratings):
pass
class NA_Jinx_Top_Ryze(Ratings):
pass
class NA_Jinx_Top_Sejuani(Ratings):
pass
class NA_Jinx_Top_Shaco(Ratings):
pass
class NA_Jinx_Top_Shen(Ratings):
pass
class NA_Jinx_Top_Shyvana(Ratings):
pass
class NA_Jinx_Top_Singed(Ratings):
pass
class NA_Jinx_Top_Sion(Ratings):
pass
class NA_Jinx_Top_Sivir(Ratings):
pass
class NA_Jinx_Top_Skarner(Ratings):
pass
class NA_Jinx_Top_Sona(Ratings):
pass
class NA_Jinx_Top_Soraka(Ratings):
pass
class NA_Jinx_Top_Swain(Ratings):
pass
class NA_Jinx_Top_Syndra(Ratings):
pass
class NA_Jinx_Top_TahmKench(Ratings):
pass
class NA_Jinx_Top_Taliyah(Ratings):
pass
class NA_Jinx_Top_Talon(Ratings):
pass
class NA_Jinx_Top_Taric(Ratings):
pass
class NA_Jinx_Top_Teemo(Ratings):
pass
class NA_Jinx_Top_Thresh(Ratings):
pass
class NA_Jinx_Top_Tristana(Ratings):
pass
class NA_Jinx_Top_Trundle(Ratings):
pass
class NA_Jinx_Top_Tryndamere(Ratings):
pass
class NA_Jinx_Top_TwistedFate(Ratings):
pass
class NA_Jinx_Top_Twitch(Ratings):
pass
class NA_Jinx_Top_Udyr(Ratings):
pass
class NA_Jinx_Top_Urgot(Ratings):
pass
class NA_Jinx_Top_Varus(Ratings):
pass
class NA_Jinx_Top_Vayne(Ratings):
pass
class NA_Jinx_Top_Veigar(Ratings):
pass
class NA_Jinx_Top_Velkoz(Ratings):
pass
class NA_Jinx_Top_Vi(Ratings):
pass
class NA_Jinx_Top_Viktor(Ratings):
pass
class NA_Jinx_Top_Vladimir(Ratings):
pass
class NA_Jinx_Top_Volibear(Ratings):
pass
class NA_Jinx_Top_Warwick(Ratings):
pass
class NA_Jinx_Top_Xayah(Ratings):
pass
class NA_Jinx_Top_Xerath(Ratings):
pass
class NA_Jinx_Top_XinZhao(Ratings):
pass
class NA_Jinx_Top_Yasuo(Ratings):
pass
class NA_Jinx_Top_Yorick(Ratings):
pass
class NA_Jinx_Top_Zac(Ratings):
pass
class NA_Jinx_Top_Zed(Ratings):
pass
class NA_Jinx_Top_Ziggs(Ratings):
pass
class NA_Jinx_Top_Zilean(Ratings):
pass
class NA_Jinx_Top_Zyra(Ratings):
pass
| 15.033573
| 46
| 0.75642
| 972
| 6,269
| 4.452675
| 0.151235
| 0.223198
| 0.350739
| 0.446396
| 0.791359
| 0.791359
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177221
| 6,269
| 416
| 47
| 15.069712
| 0.839085
| 0
| 0
| 0.498195
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.498195
| 0.00361
| 0
| 0.501805
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
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| 0
| 0
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| 0
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| null | 0
| 0
| 0
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| 1
| 0
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| 0
|
0
| 7
|
2e6dbff4c98a854a000d202fc03b4d5cdad38bfd
| 10,798
|
py
|
Python
|
tests/test_integration.py
|
opendatacube/datacube-stats
|
14054f8820ddf2b79691996af8ac7d41e200fe49
|
[
"Apache-2.0"
] | 10
|
2018-11-25T13:31:10.000Z
|
2021-04-13T13:08:45.000Z
|
tests/test_integration.py
|
daleroberts/datacube-stats
|
3b29235d3e8b238756b9b12034fe79fd0915b8a4
|
[
"Apache-2.0"
] | 67
|
2018-02-26T05:53:35.000Z
|
2018-11-14T06:20:48.000Z
|
tests/test_integration.py
|
opendatacube/datacube-stats
|
14054f8820ddf2b79691996af8ac7d41e200fe49
|
[
"Apache-2.0"
] | 4
|
2019-08-26T00:57:34.000Z
|
2020-09-17T22:39:40.000Z
|
from pathlib import Path
from datacube.utils import geometry
from affine import Affine
from click.testing import CliRunner
from datacube_stats.main import main
import pytest
try:
import otps
OTPS_MODULE_EXISTS = True
except ImportError:
OTPS_MODULE_EXISTS = False
CONFIG_TEMPLATE = """
## Define inputs to perform statistics on
sources:
- product: ls8_nbar_albers
measurements: [blue, green]
group_by: solar_day
resampling: bilinear
masks:
- product: ls8_pq_albers
measurement: pixelquality
group_by: solar_day
fuse_func: datacube.helpers.ga_pq_fuser
flags:
contiguous: True
cloud_acca: no_cloud
cloud_fmask: no_cloud
cloud_shadow_acca: no_cloud_shadow
cloud_shadow_fmask: no_cloud_shadow
blue_saturated: False
green_saturated: False
red_saturated: False
nir_saturated: False
swir1_saturated: False
swir2_saturated: False
## Define whether and how to chunk over time
date_ranges:
start_date: 2015-01-01
end_date: 2015-02-01
stats_duration: 1m
step_size: 1m
storage:
driver: NetCDF CF
crs: EPSG:3577
tile_size:
x: 100000.0
y: 100000.0
resolution:
x: 250
y: -250
chunking:
x: 200
y: 200
time: 1
dimension_order: [time, y, x]
input_region:
tile: [12, -43]
location: /g/data/u46/users/ia1511/Work/data/dummy
## Define statistics to perform and how to store the data
output_products:
- name: landsat_seasonal_mean
statistic: simple
statistic_args:
reduction_function: mean
output_params:
zlib: True
fletcher32: True
file_path_template: 'SR_N_MEAN/SR_N_MEAN_3577_{x:02d}_{y:02d}_{epoch_start:%Y%m%d}.nc'
"""
CONFIG_TEMPLATE_ITEM_NDWI = """
## Define inputs to perform statistics on
sources:
- product: ls8_nbar_albers
measurements: [blue, green, red, nir, swir1, swir2]
group_by: solar_day
resampling: bilinear
masks:
- product: ls8_pq_albers
measurement: pixelquality
group_by: solar_day
fuse_func: datacube.helpers.ga_pq_fuser
flags:
contiguous: True
cloud_acca: no_cloud
cloud_fmask: no_cloud
cloud_shadow_acca: no_cloud_shadow
cloud_shadow_fmask: no_cloud_shadow
blue_saturated: False
green_saturated: False
red_saturated: False
nir_saturated: False
swir1_saturated: False
swir2_saturated: False
## Define whether and how to chunk over time
date_ranges:
start_date: 2015-01-01
end_date: 2015-04-01
stats_duration: 3m
step_size: 3m
storage:
driver: NetCDF CF
crs: EPSG:3577
tile_size:
x: 100000.0
y: 100000.0
resolution:
x: 25000
y: -25000
chunking:
x: 200
y: 200
time: 1
dimension_order: [time, y, x]
input_region:
from_file: /g/data/v10/ITEM/ITEMv2_tidalmodel.shp
feature_id: [280]
location: /g/data/u46/users/ia1511/Work/data/dummy
output_products:
- name: ndwi_mean
statistic: simple_normalised_difference
statistic_args:
name: ndwi
band1: green
band2: swir1
stats: [min, mean, max, std]
output_params:
zlib: True
fletcher32: True
file_path_template: 'ITEM_{x}_{y}_{epoch_start:%Y%m%d}_{epoch_end:%Y%m%d}.nc'
product_type: ITEM
filter_product:
method: by_tide_height
args:
# tide_range used to differentiate item with low/high composite and for exploring future incremental change
tide_range: 10
tide_percent: 10
"""
CONFIG_TEMPLATE_DRY = """
## Define inputs to perform statistics on
sources:
- product: ls5_nbar_albers
name: dry_period
measurements: [blue, green]
group_by: solar_day
masks:
- product: ls5_pq_albers
measurement: pixelquality
group_by: solar_day
fuse_func: datacube.helpers.ga_pq_fuser
flags:
contiguous: True
cloud_acca: no_cloud
cloud_fmask: no_cloud
cloud_shadow_acca: no_cloud_shadow
cloud_shadow_fmask: no_cloud_shadow
blue_saturated: False
green_saturated: False
red_saturated: False
nir_saturated: False
swir1_saturated: False
swir2_saturated: False
## Define whether and how to chunk over time
date_ranges:
start_date: 1993-01-01
end_date: 1994-01-01
storage:
driver: NetCDF CF
crs: EPSG:3577
tile_size:
x: 100000.0
y: 100000.0
resolution:
x: 250
y: -250
chunking:
x: 200
y: 200
time: 1
dimension_order: [time, y, x]
input_region:
from_file: /g/data/u46/users/ia1511/Work/data/ITEM-files/bur_dry_albers.shp
feature_id: [49]
location: /g/data/u46/users/ia1511/Work/data/dummy
output_products:
- name: dry
statistic: geomedian
output_params:
zlib: True
fletcher32: True
file_path_template: 'GW_DRY_{x}_{y}.nc'
product_type: COMPOSITE DRY
filter_product:
method: by_hydrological_months
args:
type: dry
# Here is to consider these months for the following year from polygon data
months: ['10', '11']
"""
CONFIG_TEMPLATE_WET = """
## Define inputs to perform statistics on
global_attributes:
title: WET composite
sources:
- product: ls5_nbar_albers
name: wet_period
measurements: [blue, green]
group_by: solar_day
masks:
- product: ls5_pq_albers
measurement: pixelquality
group_by: solar_day
fuse_func: datacube.helpers.ga_pq_fuser
flags:
contiguous: True
cloud_acca: no_cloud
cloud_fmask: no_cloud
cloud_shadow_acca: no_cloud_shadow
cloud_shadow_fmask: no_cloud_shadow
blue_saturated: False
green_saturated: False
red_saturated: False
nir_saturated: False
swir1_saturated: False
swir2_saturated: False
## Define whether and how to chunk over time
date_ranges:
start_date: 2008-01-01
end_date: 2012-01-01
## Define output directory and file structure
location: '/g/data/r78/tmp'
input_region:
from_file: /g/data/u46/users/ia1511/Work/data/ITEM-files/bur_dry_albers.shp
feature_id: [49]
storage:
driver: NetCDF CF
crs: EPSG:3577
tile_size:
x: 100000.0
y: 100000.0
resolution:
x: 25
y: -25
chunking:
x: 200
y: 200
time: 1
dimension_order: [time, y, x]
## Define statistics to perform and how to store the data
output_products:
- name: wet
statistic: geomedian
output_params:
zlib: True
fletcher32: True
file_path_template: 'GW_WET_{x}_{y}.nc'
product_type: COMPOSITE WET
filter_product:
method: by_hydrological_months
args:
type: wet
# Here is to consider these months for the following year from polygon data
months: ['10', '11']
"""
CONFIG_FILENAME = 'config.yaml'
def sample_geometry():
gb = geometry.GeoBox(40, 40, Affine(2500, 0.0, 1200000.0, 0.0, -2500, -4300000.0), geometry.CRS('EPSG:3577'))
json = gb.extent.json
return json
RUNNING_ON_NCI_ENV = Path('/g/data/u46').exists()
# takes ~30 seconds to complete
@pytest.mark.xfail(not RUNNING_ON_NCI_ENV,
reason="This test currently expects to be run in the DEA environment on NCI.")
def test_input_region_single_tile():
runner = CliRunner()
with runner.isolated_filesystem() as tmpdir:
with open(CONFIG_FILENAME, 'w') as f:
f.write(CONFIG_TEMPLATE)
result = runner.invoke(main, ['-v', '-v', '-v', CONFIG_FILENAME,
'--output-location', str(Path(tmpdir).absolute())])
assert 'error' not in result.output.lower()
assert 'exception' not in result.output.lower()
assert result.exit_code == 0
outputfile = Path(tmpdir) / 'SR_N_MEAN' / 'SR_N_MEAN_3577_12_-43_20150101.nc'
assert outputfile.exists()
@pytest.mark.xfail(not OTPS_MODULE_EXISTS, reason="otps module is not available")
def test_input_region_from_shapefile_item_ndwi():
runner = CliRunner()
with runner.isolated_filesystem() as tmpdir:
with open(CONFIG_FILENAME, 'w') as f:
f.write(CONFIG_TEMPLATE_ITEM_NDWI)
outputfile = Path(tmpdir) / 'ITEM_280_142.63_-10.31_PER_10_20150101_20150401.nc'
result = runner.invoke(main, ['-v', '-v', '-v', CONFIG_FILENAME,
'--output-location', str(Path(tmpdir).absolute())])
assert 'error' not in result.output.lower()
assert 'exception' not in result.output.lower()
assert result.exit_code == 0
assert outputfile.exists()
# takes ~1 mins to complete
@pytest.mark.xfail(not RUNNING_ON_NCI_ENV,
reason="This test currently expects to be run in the DEA environment on NCI.")
def test_input_region_from_shapefile_dry():
runner = CliRunner()
with runner.isolated_filesystem() as tmpdir:
with open(CONFIG_FILENAME, 'w') as f:
f.write(CONFIG_TEMPLATE_DRY)
outputfile = Path(tmpdir) / 'GW_DRY_49_1991_1992.nc'
result = runner.invoke(main, ['-v', '-v', '-v', CONFIG_FILENAME,
'--output-location', str(Path(tmpdir).absolute())])
assert 'error' not in result.output.lower()
assert 'exception' not in result.output.lower()
assert result.exit_code == 0
assert outputfile.exists()
# takes ~2 mins to complete
@pytest.mark.xfail(not RUNNING_ON_NCI_ENV,
reason="This test currently expects to be run in the DEA environment on NCI.")
def test_input_region_from_shapefile_wet():
runner = CliRunner()
with runner.isolated_filesystem() as tmpdir:
with open(CONFIG_FILENAME, 'w') as f:
f.write(CONFIG_TEMPLATE_WET)
outputfile = Path(tmpdir) / 'GW_WET_49_2007_2010.nc'
result = runner.invoke(main, ['-v', '-v', '-v', CONFIG_FILENAME,
'--output-location', str(Path(tmpdir).absolute())])
assert 'error' not in result.output.lower()
assert 'exception' not in result.output.lower()
assert result.exit_code == 0
assert outputfile.exists()
@pytest.mark.xfail
def test_input_region_from_geojson():
assert False
@pytest.mark.xfail
def test_output_to_netcdf():
assert False
@pytest.mark.xfail
def test_output_to_geotiff_single_band():
assert False
@pytest.mark.xfail
def test_output_to_geotiff_multi_band():
assert False
@pytest.mark.xfail
def test_output_to_geotiff_multi_file():
assert False
@pytest.mark.xfail
def test_output_to_envibil():
assert False
| 25.407059
| 113
| 0.656974
| 1,434
| 10,798
| 4.7106
| 0.195258
| 0.049741
| 0.022206
| 0.017765
| 0.789933
| 0.782828
| 0.751443
| 0.746114
| 0.725241
| 0.692376
| 0
| 0.049826
| 0.254677
| 10,798
| 424
| 114
| 25.466981
| 0.789513
| 0.007501
| 0
| 0.74269
| 0
| 0.011696
| 0.66536
| 0.069168
| 0
| 0
| 0
| 0
| 0.064327
| 1
| 0.032164
| false
| 0
| 0.023392
| 0
| 0.05848
| 0
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
2e7fb1ea55970c505b1a0d1ab6192f49a2af7763
| 66
|
py
|
Python
|
website/blueprints/blog_blueprint/__init__.py
|
olaruandreea/flaskbootstrapblog
|
462f2f700c3b73a794842f1fad4b318c6406c678
|
[
"MIT"
] | null | null | null |
website/blueprints/blog_blueprint/__init__.py
|
olaruandreea/flaskbootstrapblog
|
462f2f700c3b73a794842f1fad4b318c6406c678
|
[
"MIT"
] | 4
|
2020-05-03T11:45:01.000Z
|
2020-06-13T19:43:26.000Z
|
website/blueprints/blog_blueprint/__init__.py
|
olaruandreea/flaskbootstrapblog
|
462f2f700c3b73a794842f1fad4b318c6406c678
|
[
"MIT"
] | null | null | null |
from website.blueprints.blog_blueprint.blog import blog_blueprint
| 33
| 65
| 0.893939
| 9
| 66
| 6.333333
| 0.666667
| 0.45614
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.060606
| 66
| 1
| 66
| 66
| 0.919355
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 1
| 1
| 0
| 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
| 1
|
0
| 7
|
2e88fdd11a72e7a004403f1aa354dd33c9de6e43
| 3,268
|
py
|
Python
|
test/test_networking_project_network_api.py
|
hyperonecom/h1-client-python
|
4ce355852ba3120ec1b8f509ab5894a5c08da730
|
[
"MIT"
] | null | null | null |
test/test_networking_project_network_api.py
|
hyperonecom/h1-client-python
|
4ce355852ba3120ec1b8f509ab5894a5c08da730
|
[
"MIT"
] | null | null | null |
test/test_networking_project_network_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.networking_project_network_api import NetworkingProjectNetworkApi # noqa: E501
class TestNetworkingProjectNetworkApi(unittest.TestCase):
"""NetworkingProjectNetworkApi unit test stubs"""
def setUp(self):
self.api = NetworkingProjectNetworkApi() # noqa: E501
def tearDown(self):
pass
def test_networking_project_network_create(self):
"""Test case for networking_project_network_create
Create networking/network # noqa: E501
"""
pass
def test_networking_project_network_delete(self):
"""Test case for networking_project_network_delete
Delete networking/network # noqa: E501
"""
pass
def test_networking_project_network_event_get(self):
"""Test case for networking_project_network_event_get
Get networking/network.event # noqa: E501
"""
pass
def test_networking_project_network_event_list(self):
"""Test case for networking_project_network_event_list
List networking/network.event # noqa: E501
"""
pass
def test_networking_project_network_get(self):
"""Test case for networking_project_network_get
Get networking/network # noqa: E501
"""
pass
def test_networking_project_network_list(self):
"""Test case for networking_project_network_list
List networking/network # noqa: E501
"""
pass
def test_networking_project_network_service_get(self):
"""Test case for networking_project_network_service_get
Get networking/network.service # noqa: E501
"""
pass
def test_networking_project_network_service_list(self):
"""Test case for networking_project_network_service_list
List networking/network.service # noqa: E501
"""
pass
def test_networking_project_network_tag_create(self):
"""Test case for networking_project_network_tag_create
Create networking/network.tag # noqa: E501
"""
pass
def test_networking_project_network_tag_delete(self):
"""Test case for networking_project_network_tag_delete
Delete networking/network.tag # noqa: E501
"""
pass
def test_networking_project_network_tag_get(self):
"""Test case for networking_project_network_tag_get
Get networking/network.tag # noqa: E501
"""
pass
def test_networking_project_network_tag_list(self):
"""Test case for networking_project_network_tag_list
List networking/network.tag # noqa: E501
"""
pass
def test_networking_project_network_tag_put(self):
"""Test case for networking_project_network_tag_put
Replace networking/network.tag # noqa: E501
"""
pass
def test_networking_project_network_update(self):
"""Test case for networking_project_network_update
Update networking/network # noqa: E501
"""
pass
if __name__ == '__main__':
unittest.main()
| 25.732283
| 91
| 0.672889
| 367
| 3,268
| 5.645777
| 0.13624
| 0.237934
| 0.335907
| 0.141892
| 0.771236
| 0.738417
| 0.721525
| 0.702703
| 0.414093
| 0.401062
| 0
| 0.023074
| 0.257344
| 3,268
| 126
| 92
| 25.936508
| 0.830655
| 0.456548
| 0
| 0.394737
| 1
| 0
| 0.005563
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.421053
| false
| 0.394737
| 0.078947
| 0
| 0.526316
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 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
| 0
| 0
|
0
| 8
|
cf551a8f6289e299d35261c4c77d4b84c15d013c
| 1,012
|
py
|
Python
|
chemiwrap/providers/__init__.py
|
SimonBoothroyd/chemiwrap
|
7394cd44e386a9f280fd61bce5cf4d0d1567c689
|
[
"MIT"
] | 2
|
2021-06-28T15:20:02.000Z
|
2021-07-01T03:09:35.000Z
|
chemiwrap/providers/__init__.py
|
SimonBoothroyd/chemiwrap
|
7394cd44e386a9f280fd61bce5cf4d0d1567c689
|
[
"MIT"
] | 7
|
2021-06-29T08:21:40.000Z
|
2022-02-28T21:13:50.000Z
|
chemiwrap/providers/__init__.py
|
SimonBoothroyd/chemiwrap
|
7394cd44e386a9f280fd61bce5cf4d0d1567c689
|
[
"MIT"
] | null | null | null |
from chemiwrap.providers._providers import (
AromaticityProvider,
AtomStereochemistry,
BondOrderProvider,
BondStereochemistry,
ChargeProvider,
ConformerProvider,
DefaultConformerSettings,
FeatureProvider,
FileIOProvider,
ModelProvider,
SMARTSProvider,
SMILESProvider,
StereochemistryProvider,
StereoisomerProvider,
TautomerProvider,
)
__all__ = [
AromaticityProvider,
AtomStereochemistry,
BondOrderProvider,
BondStereochemistry,
ChargeProvider,
ConformerProvider,
DefaultConformerSettings,
FeatureProvider,
FileIOProvider,
ModelProvider,
SMARTSProvider,
SMILESProvider,
StereochemistryProvider,
StereoisomerProvider,
TautomerProvider,
]
__feature_types__ = [
AromaticityProvider,
BondOrderProvider,
ChargeProvider,
ConformerProvider,
FileIOProvider,
SMARTSProvider,
SMILESProvider,
StereochemistryProvider,
StereoisomerProvider,
TautomerProvider,
]
| 20.24
| 44
| 0.737154
| 48
| 1,012
| 15.333333
| 0.458333
| 0.126359
| 0.20788
| 0.289402
| 0.819293
| 0.701087
| 0.701087
| 0.701087
| 0.701087
| 0.701087
| 0
| 0
| 0.213439
| 1,012
| 49
| 45
| 20.653061
| 0.924623
| 0
| 0
| 0.869565
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.021739
| 0
| 0.021739
| 0
| 0
| 0
| 1
| null | 0
| 1
| 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
| 10
|
d87508dacad32b9f0ab6e45fc655215d1b8a10d3
| 15,673
|
py
|
Python
|
hoomd/test-py/test_snapshot_bcast_partition.py
|
schwendp/hoomd-blue
|
df7970121b19bc4f8674348ab3241055ac87153b
|
[
"BSD-3-Clause"
] | 2
|
2020-03-30T14:38:50.000Z
|
2020-06-02T05:53:41.000Z
|
hoomd/test-py/test_snapshot_bcast_partition.py
|
schwendp/hoomd-blue
|
df7970121b19bc4f8674348ab3241055ac87153b
|
[
"BSD-3-Clause"
] | null | null | null |
hoomd/test-py/test_snapshot_bcast_partition.py
|
schwendp/hoomd-blue
|
df7970121b19bc4f8674348ab3241055ac87153b
|
[
"BSD-3-Clause"
] | 1
|
2020-05-20T07:00:08.000Z
|
2020-05-20T07:00:08.000Z
|
# -*- coding: iso-8859-1 -*-
# Maintainer: jglaser
from hoomd import *
import hoomd;
if hoomd._hoomd.is_MPI_available():
# initialize with every rank == one partition
context.initialize('--nrank=1')
else:
context.initialize('')
import unittest
import os
import sys
import numpy
# test make_snapshot, read_snapshot and broadcast
class test_bcast_float (unittest.TestCase):
def setUp(self):
self.snapshot = data.make_snapshot(N=4, box=data.boxdim(L=10), dtype='float');
if comm.get_partition() == 0:
# particles
self.snapshot.particles.position[0] = [0,1,2];
self.snapshot.particles.position[1] = [1,2,3];
self.snapshot.particles.position[2] = [0,-1,-2];
self.snapshot.particles.position[3] = [-1, -2, -3];
self.snapshot.particles.velocity[0] = [10, 11, 12];
self.snapshot.particles.velocity[1] = [11, 12, 13];
self.snapshot.particles.velocity[2] = [12, 13, 14];
self.snapshot.particles.velocity[3] = [13, 14, 15];
self.snapshot.particles.acceleration[0] = [20, 21, 22];
self.snapshot.particles.acceleration[1] = [21, 22, 23];
self.snapshot.particles.acceleration[2] = [22, 23, 24];
self.snapshot.particles.acceleration[3] = [23, 24, 25];
self.snapshot.particles.typeid[:] = [0,0,1,1];
self.snapshot.particles.mass[:] = [33, 34, 35, 36];
self.snapshot.particles.charge[:] = [44, 45, 46, 47];
self.snapshot.particles.diameter[:] = [55, 56, 57, 58];
self.snapshot.particles.image[0] = [60, 61, 62];
self.snapshot.particles.image[1] = [61, 62, 63];
self.snapshot.particles.image[2] = [62, 63, 64];
self.snapshot.particles.image[3] = [63, 64, 65];
self.snapshot.particles.types = ['p1', 'p2'];
# bonds
self.snapshot.bonds.types = ['b1', 'b2'];
self.snapshot.bonds.resize(2);
self.snapshot.bonds.typeid[:] = [0, 1];
self.snapshot.bonds.group[0] = [0, 1];
self.snapshot.bonds.group[1] = [2, 3];
# angles
self.snapshot.angles.types = ['a1', 'a2'];
self.snapshot.angles.resize(2);
self.snapshot.angles.typeid[:] = [1, 0];
self.snapshot.angles.group[0] = [0, 1, 2];
self.snapshot.angles.group[1] = [2, 3, 0];
# dihedrals
self.snapshot.dihedrals.types = ['d1'];
self.snapshot.dihedrals.resize(1);
self.snapshot.dihedrals.typeid[:] = [0];
self.snapshot.dihedrals.group[0] = [0, 1, 2, 3];
# impropers
self.snapshot.impropers.types = ['i1'];
self.snapshot.impropers.resize(1);
self.snapshot.impropers.typeid[:] = [0];
self.snapshot.impropers.group[0] = [3, 2, 1, 0];
# constraints
self.snapshot.constraints.resize(1)
self.snapshot.constraints.group[0] = [0, 1]
self.snapshot.constraints.value[0] = 2.5
def test_bcast_all(self):
# broadcast to all ranks
self.snapshot.broadcast_all()
# particles
self.assertEqual(self.snapshot.particles.N, 4);
self.assertEqual(tuple(self.snapshot.particles.position[0]), (0,1,2));
self.assertEqual(tuple(self.snapshot.particles.velocity[0]), (10,11,12));
self.assertEqual(tuple(self.snapshot.particles.acceleration[0]), (20,21,22));
self.assertEqual(self.snapshot.particles.typeid[0], 0);
self.assertEqual(self.snapshot.particles.mass[0], 33);
self.assertEqual(self.snapshot.particles.charge[0], 44);
self.assertEqual(self.snapshot.particles.diameter[0], 55);
self.assertEqual(tuple(self.snapshot.particles.image[0]), (60,61,62));
self.assertEqual(tuple(self.snapshot.particles.position[1]), (1,2,3));
self.assertEqual(tuple(self.snapshot.particles.velocity[1]), (11,12,13));
self.assertEqual(tuple(self.snapshot.particles.acceleration[1]), (21,22,23));
self.assertEqual(self.snapshot.particles.typeid[1], 0);
self.assertEqual(self.snapshot.particles.mass[1], 34);
self.assertEqual(self.snapshot.particles.charge[1], 45);
self.assertEqual(self.snapshot.particles.diameter[1], 56);
self.assertEqual(tuple(self.snapshot.particles.image[1]), (61,62,63));
self.assertEqual(tuple(self.snapshot.particles.position[2]), (0,-1,-2));
self.assertEqual(tuple(self.snapshot.particles.velocity[2]), (12,13,14));
self.assertEqual(tuple(self.snapshot.particles.acceleration[2]), (22,23,24));
self.assertEqual(self.snapshot.particles.typeid[2], 1);
self.assertEqual(self.snapshot.particles.mass[2], 35);
self.assertEqual(self.snapshot.particles.charge[2], 46);
self.assertEqual(self.snapshot.particles.diameter[2], 57);
self.assertEqual(tuple(self.snapshot.particles.image[2]), (62,63,64));
self.assertEqual(tuple(self.snapshot.particles.position[3]), (-1,-2,-3));
self.assertEqual(tuple(self.snapshot.particles.velocity[3]), (13,14,15));
self.assertEqual(tuple(self.snapshot.particles.acceleration[3]), (23,24,25));
self.assertEqual(self.snapshot.particles.typeid[3], 1);
self.assertEqual(self.snapshot.particles.mass[3], 36);
self.assertEqual(self.snapshot.particles.charge[3], 47);
self.assertEqual(self.snapshot.particles.diameter[3], 58);
self.assertEqual(tuple(self.snapshot.particles.image[3]), (63,64,65));
# bonds
self.assertEqual(self.snapshot.bonds.N, 2);
self.assertEqual(self.snapshot.bonds.typeid[0], 0);
self.assertEqual(self.snapshot.bonds.group[0,0], 0);
self.assertEqual(self.snapshot.bonds.group[0,1], 1);
self.assertEqual(self.snapshot.bonds.typeid[1], 1);
self.assertEqual(self.snapshot.bonds.group[1,0], 2);
self.assertEqual(self.snapshot.bonds.group[1,1], 3);
# angles
self.assertEqual(self.snapshot.angles.N, 2);
self.assertEqual(self.snapshot.angles.typeid[0], 1);
self.assertEqual(self.snapshot.angles.group[0,0], 0);
self.assertEqual(self.snapshot.angles.group[0,1], 1);
self.assertEqual(self.snapshot.angles.group[0,2], 2);
self.assertEqual(self.snapshot.angles.typeid[1], 0);
self.assertEqual(self.snapshot.angles.group[1,0], 2);
self.assertEqual(self.snapshot.angles.group[1,1], 3);
self.assertEqual(self.snapshot.angles.group[1,2], 0);
# dihedrals
self.assertEqual(self.snapshot.dihedrals.N, 1);
self.assertEqual(self.snapshot.dihedrals.typeid[0], 0);
self.assertEqual(self.snapshot.dihedrals.group[0,0], 0);
self.assertEqual(self.snapshot.dihedrals.group[0,1], 1);
self.assertEqual(self.snapshot.dihedrals.group[0,2], 2);
self.assertEqual(self.snapshot.dihedrals.group[0,3], 3);
# impropers
self.assertEqual(self.snapshot.impropers.N, 1);
self.assertEqual(self.snapshot.impropers.typeid[0], 0);
self.assertEqual(self.snapshot.impropers.group[0,0], 3);
self.assertEqual(self.snapshot.impropers.group[0,1], 2);
self.assertEqual(self.snapshot.impropers.group[0,2], 1);
self.assertEqual(self.snapshot.impropers.group[0,3], 0);
# constraints
self.assertEqual(self.snapshot.constraints.N, 1)
self.assertAlmostEqual(self.snapshot.constraints.value[0], 2.5, 5)
self.assertEqual(self.snapshot.constraints.group[0,0], 0)
self.assertEqual(self.snapshot.constraints.group[0,1], 1)
def tearDown(self):
if hoomd._hoomd.is_MPI_available():
# initialize with every rank == one partition
context.initialize('--nrank=1')
else:
context.initialize('')
# test make_snapshot and read_snapshot in double precision
class test_bcast_double (unittest.TestCase):
def setUp(self):
self.snapshot = data.make_snapshot(N=4, box=data.boxdim(L=10), dtype='double');
if comm.get_partition() == 0:
# particles
self.snapshot.particles.position[0] = [0,1,2];
self.snapshot.particles.position[1] = [1,2,3];
self.snapshot.particles.position[2] = [0,-1,-2];
self.snapshot.particles.position[3] = [-1, -2, -3];
self.snapshot.particles.velocity[0] = [10, 11, 12];
self.snapshot.particles.velocity[1] = [11, 12, 13];
self.snapshot.particles.velocity[2] = [12, 13, 14];
self.snapshot.particles.velocity[3] = [13, 14, 15];
self.snapshot.particles.acceleration[0] = [20, 21, 22];
self.snapshot.particles.acceleration[1] = [21, 22, 23];
self.snapshot.particles.acceleration[2] = [22, 23, 24];
self.snapshot.particles.acceleration[3] = [23, 24, 25];
self.snapshot.particles.typeid[:] = [0,0,1,1];
self.snapshot.particles.mass[:] = [33, 34, 35, 36];
self.snapshot.particles.charge[:] = [44, 45, 46, 47];
self.snapshot.particles.diameter[:] = [55, 56, 57, 58];
self.snapshot.particles.image[0] = [60, 61, 62];
self.snapshot.particles.image[1] = [61, 62, 63];
self.snapshot.particles.image[2] = [62, 63, 64];
self.snapshot.particles.image[3] = [63, 64, 65];
self.snapshot.particles.types = ['p1', 'p2'];
# bonds
self.snapshot.bonds.types = ['b1', 'b2'];
self.snapshot.bonds.resize(2);
self.snapshot.bonds.typeid[:] = [0, 1];
self.snapshot.bonds.group[0] = [0, 1];
self.snapshot.bonds.group[1] = [2, 3];
# angles
self.snapshot.angles.types = ['a1', 'a2'];
self.snapshot.angles.resize(2);
self.snapshot.angles.typeid[:] = [1, 0];
self.snapshot.angles.group[0] = [0, 1, 2];
self.snapshot.angles.group[1] = [2, 3, 0];
# dihedrals
self.snapshot.dihedrals.types = ['d1'];
self.snapshot.dihedrals.resize(1);
self.snapshot.dihedrals.typeid[:] = [0];
self.snapshot.dihedrals.group[0] = [0, 1, 2, 3];
# impropers
self.snapshot.impropers.types = ['i1'];
self.snapshot.impropers.resize(1);
self.snapshot.impropers.typeid[:] = [0];
self.snapshot.impropers.group[0] = [3, 2, 1, 0];
# constraints
self.snapshot.constraints.resize(1)
self.snapshot.constraints.group[0] = [0, 1]
self.snapshot.constraints.value[0] = 2.5
def test_bcast_all(self):
# broadcast to all ranks
self.snapshot.broadcast_all()
# particles
self.assertEqual(self.snapshot.particles.N, 4);
self.assertEqual(tuple(self.snapshot.particles.position[0]), (0,1,2));
self.assertEqual(tuple(self.snapshot.particles.velocity[0]), (10,11,12));
self.assertEqual(tuple(self.snapshot.particles.acceleration[0]), (20,21,22));
self.assertEqual(self.snapshot.particles.typeid[0], 0);
self.assertEqual(self.snapshot.particles.mass[0], 33);
self.assertEqual(self.snapshot.particles.charge[0], 44);
self.assertEqual(self.snapshot.particles.diameter[0], 55);
self.assertEqual(tuple(self.snapshot.particles.image[0]), (60,61,62));
self.assertEqual(tuple(self.snapshot.particles.position[1]), (1,2,3));
self.assertEqual(tuple(self.snapshot.particles.velocity[1]), (11,12,13));
self.assertEqual(tuple(self.snapshot.particles.acceleration[1]), (21,22,23));
self.assertEqual(self.snapshot.particles.typeid[1], 0);
self.assertEqual(self.snapshot.particles.mass[1], 34);
self.assertEqual(self.snapshot.particles.charge[1], 45);
self.assertEqual(self.snapshot.particles.diameter[1], 56);
self.assertEqual(tuple(self.snapshot.particles.image[1]), (61,62,63));
self.assertEqual(tuple(self.snapshot.particles.position[2]), (0,-1,-2));
self.assertEqual(tuple(self.snapshot.particles.velocity[2]), (12,13,14));
self.assertEqual(tuple(self.snapshot.particles.acceleration[2]), (22,23,24));
self.assertEqual(self.snapshot.particles.typeid[2], 1);
self.assertEqual(self.snapshot.particles.mass[2], 35);
self.assertEqual(self.snapshot.particles.charge[2], 46);
self.assertEqual(self.snapshot.particles.diameter[2], 57);
self.assertEqual(tuple(self.snapshot.particles.image[2]), (62,63,64));
self.assertEqual(tuple(self.snapshot.particles.position[3]), (-1,-2,-3));
self.assertEqual(tuple(self.snapshot.particles.velocity[3]), (13,14,15));
self.assertEqual(tuple(self.snapshot.particles.acceleration[3]), (23,24,25));
self.assertEqual(self.snapshot.particles.typeid[3], 1);
self.assertEqual(self.snapshot.particles.mass[3], 36);
self.assertEqual(self.snapshot.particles.charge[3], 47);
self.assertEqual(self.snapshot.particles.diameter[3], 58);
self.assertEqual(tuple(self.snapshot.particles.image[3]), (63,64,65));
# bonds
self.assertEqual(self.snapshot.bonds.N, 2);
self.assertEqual(self.snapshot.bonds.typeid[0], 0);
self.assertEqual(self.snapshot.bonds.group[0,0], 0);
self.assertEqual(self.snapshot.bonds.group[0,1], 1);
self.assertEqual(self.snapshot.bonds.typeid[1], 1);
self.assertEqual(self.snapshot.bonds.group[1,0], 2);
self.assertEqual(self.snapshot.bonds.group[1,1], 3);
# angles
self.assertEqual(self.snapshot.angles.N, 2);
self.assertEqual(self.snapshot.angles.typeid[0], 1);
self.assertEqual(self.snapshot.angles.group[0,0], 0);
self.assertEqual(self.snapshot.angles.group[0,1], 1);
self.assertEqual(self.snapshot.angles.group[0,2], 2);
self.assertEqual(self.snapshot.angles.typeid[1], 0);
self.assertEqual(self.snapshot.angles.group[1,0], 2);
self.assertEqual(self.snapshot.angles.group[1,1], 3);
self.assertEqual(self.snapshot.angles.group[1,2], 0);
# dihedrals
self.assertEqual(self.snapshot.dihedrals.N, 1);
self.assertEqual(self.snapshot.dihedrals.typeid[0], 0);
self.assertEqual(self.snapshot.dihedrals.group[0,0], 0);
self.assertEqual(self.snapshot.dihedrals.group[0,1], 1);
self.assertEqual(self.snapshot.dihedrals.group[0,2], 2);
self.assertEqual(self.snapshot.dihedrals.group[0,3], 3);
# impropers
self.assertEqual(self.snapshot.impropers.N, 1);
self.assertEqual(self.snapshot.impropers.typeid[0], 0);
self.assertEqual(self.snapshot.impropers.group[0,0], 3);
self.assertEqual(self.snapshot.impropers.group[0,1], 2);
self.assertEqual(self.snapshot.impropers.group[0,2], 1);
self.assertEqual(self.snapshot.impropers.group[0,3], 0);
# constraints
self.assertEqual(self.snapshot.constraints.N, 1)
self.assertAlmostEqual(self.snapshot.constraints.value[0], 2.5, 5)
self.assertEqual(self.snapshot.constraints.group[0,0], 0)
self.assertEqual(self.snapshot.constraints.group[0,1], 1)
def tearDown(self):
if hoomd._hoomd.is_MPI_available():
# initialize with every rank == one partition
context.initialize('--nrank=1')
else:
context.initialize('')
if __name__ == '__main__':
unittest.main(argv = ['test.py', '-v'])
| 48.224615
| 87
| 0.622217
| 1,975
| 15,673
| 4.92
| 0.062278
| 0.269219
| 0.233405
| 0.266749
| 0.972214
| 0.972214
| 0.972214
| 0.972214
| 0.972214
| 0.972214
| 0
| 0.066543
| 0.211829
| 15,673
| 324
| 88
| 48.373457
| 0.720068
| 0.035028
| 0
| 0.951613
| 0
| 0
| 0.005765
| 0
| 0
| 0
| 0
| 0
| 0.524194
| 1
| 0.024194
| false
| 0
| 0.024194
| 0
| 0.056452
| 0
| 0
| 0
| 0
| null | 1
| 1
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 11
|
d8cb1350c8e064863ea3ec41b440f8fb17bf742c
| 140
|
py
|
Python
|
tests/test_misc.py
|
mag1pie/scHPF
|
926f8831b4167ad877572a5e34d1e7d2f729b1c4
|
[
"BSD-2-Clause"
] | null | null | null |
tests/test_misc.py
|
mag1pie/scHPF
|
926f8831b4167ad877572a5e34d1e7d2f729b1c4
|
[
"BSD-2-Clause"
] | null | null | null |
tests/test_misc.py
|
mag1pie/scHPF
|
926f8831b4167ad877572a5e34d1e7d2f729b1c4
|
[
"BSD-2-Clause"
] | null | null | null |
#!/usr/bin/env python
import schpf
def test_version():
assert schpf.__version__ is not None
# assert schpf.__version__ == '0.2.5'
| 17.5
| 41
| 0.692857
| 21
| 140
| 4.190476
| 0.761905
| 0.25
| 0.409091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.026316
| 0.185714
| 140
| 7
| 42
| 20
| 0.745614
| 0.4
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| true
| 0
| 0.333333
| 0
| 0.666667
| 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
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
2b0cd337bd1b26b5bdfc9278c41c7ff439d0ad77
| 9,066
|
py
|
Python
|
attacks.py
|
vv52/destitute-dreamscape
|
9573c8f01c4c62fefa0fe005999a471754d5e006
|
[
"Apache-2.0"
] | null | null | null |
attacks.py
|
vv52/destitute-dreamscape
|
9573c8f01c4c62fefa0fe005999a471754d5e006
|
[
"Apache-2.0"
] | null | null | null |
attacks.py
|
vv52/destitute-dreamscape
|
9573c8f01c4c62fefa0fe005999a471754d5e006
|
[
"Apache-2.0"
] | null | null | null |
from random import Random
import projectiles
SCREEN_WIDTH = 512
SCREEN_HEIGHT = 740
def CircleSpawner(loc, div, kind, offset, bullets, sprites):
bullet_counter = 0
angle = 360 / div
while bullet_counter < div:
if kind == "w":
new_bullet = projectiles.WarblyBullet(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "s":
new_bullet = projectiles.SpiralBullet(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "s2":
new_bullet = projectiles.SpiralBullet2(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "s3":
new_bullet = projectiles.SpiralBullet3(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "s3i":
new_bullet = projectiles.SpiralBullet3Inverse(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "s4":
new_bullet = projectiles.SpiralBullet4(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "s4i":
new_bullet = projectiles.SpiralBullet4Inverse(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "b2":
new_bullet = projectiles.Bullet2(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "cr":
new_bullet = projectiles.BulletCross(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "ma":
new_bullet = projectiles.BulletModA(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "mb":
new_bullet = projectiles.BulletModB(loc.x, loc.y, bullet_counter * angle + offset)
elif kind == "bd":
new_bullet = projectiles.BulletBarD(loc.x, loc.y, bullet_counter * angle + offset)
else:
new_bullet = projectiles.Bullet(loc.x, loc.y, bullet_counter * angle + offset)
bullets.add(new_bullet)
sprites.add(new_bullet)
bullet_counter += 1
def BarSpawner(loc_y, div, angle, kind, bullets, sprites):
bullet_counter = 0
space = SCREEN_WIDTH / div
rand = Random()
range = int(round(div / 8))
bound = rand.randint(0, div - range)
while bullet_counter < div:
if bullet_counter < bound or bullet_counter > bound + range:
if kind == "w":
new_bullet = projectiles.WarblyBullet(space * bullet_counter + 13, loc_y, angle)
elif kind == "s":
new_bullet = projectiles.SpiralBullet(space * bullet_counter + 13, loc_y, angle)
elif kind == "s2":
new_bullet = projectiles.SpiralBullet2(space * bullet_counter + 13, loc_y, angle)
elif kind == "s3":
new_bullet = projectiles.SpiralBullet3(space * bullet_counter + 13, loc_y, angle)
elif kind == "s3i":
new_bullet = projectiles.SpiralBullet3Inverse(space * bullet_counter + 13, loc_y, angle)
elif kind == "s4":
new_bullet = projectiles.SpiralBullet4(space * bullet_counter + 13, loc_y, angle)
elif kind == "s4i":
new_bullet = projectiles.SpiralBullet4Inverse(space * bullet_counter + 13, loc_y, angle)
elif kind == "b2":
new_bullet = projectiles.Bullet2(space * bullet_counter + 13, loc_y, angle)
elif kind == "cr":
new_bullet = projectiles.BulletCross(space * bullet_counter + 13, loc_y, angle)
elif kind == "ma":
new_bullet = projectiles.BulletModA(space * bullet_counter + 13, loc_y, angle)
elif kind == "mb":
new_bullet = projectiles.BulletModB(space * bullet_counter + 13, loc_y, angle)
elif kind == "bd":
new_bullet = projectiles.BulletBarD(space * bullet_counter + 13, loc_y, angle)
else:
new_bullet = projectiles.Bullet(space * bullet_counter + 13, loc_y, angle)
bullets.add(new_bullet)
sprites.add(new_bullet)
bullet_counter += 1
def QuarterSpawner(loc, div, kind, offset, bullets, sprites):
bullet_counter = 0
angle = 90 / div
while bullet_counter < div:
if kind == "w":
new_bullet = projectiles.WarblyBullet(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "s":
new_bullet = projectiles.SpiralBullet(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "s2":
new_bullet = projectiles.SpiralBullet2(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "s3":
new_bullet = projectiles.SpiralBullet3(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "s3i":
new_bullet = projectiles.SpiralBullet3Inverse(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "s4":
new_bullet = projectiles.SpiralBullet4(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "s4i":
new_bullet = projectiles.SpiralBullet4Inverse(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "b2":
new_bullet = projectiles.Bullet2(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "cr":
new_bullet = projectiles.BulletCross(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "ma":
new_bullet = projectiles.BulletModA(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "mb":
new_bullet = projectiles.BulletModB(loc.x, loc.y, bullet_counter * angle + 45 + offset)
elif kind == "bd":
new_bullet = projectiles.BulletBarD(loc.x, loc.y, bullet_counter * angle + 45 + offset)
else:
new_bullet = projectiles.Bullet(loc.x, loc.y, bullet_counter * angle + 45 + offset)
bullets.add(new_bullet)
sprites.add(new_bullet)
bullet_counter += 1
def Stream(loc, angle, kind, bullets, sprites):
if kind == "w":
new_bullet = projectiles.WarblyBullet(loc.x, loc.y, angle + 90)
elif kind == "s":
new_bullet = projectiles.SpiralBullet(loc.x, loc.y, angle + 90)
elif kind == "s2":
new_bullet = projectiles.SpiralBullet2(loc.x, loc.y, angle + 90)
elif kind == "s3":
new_bullet = projectiles.SpiralBullet3(loc.x, loc.y, angle + 90)
elif kind == "s3i":
new_bullet = projectiles.SpiralBullet3Inverse(loc.x, loc.y, angle + 90)
elif kind == "s4":
new_bullet = projectiles.SpiralBullet4(loc.x, loc.y, angle + 90)
elif kind == "s4i":
new_bullet = projectiles.SpiralBullet4Inverse(loc.x, loc.y, angle + 90)
elif kind == "b2":
new_bullet = projectiles.Bullet2(loc.x, loc.y, angle + 90)
elif kind == "cr":
new_bullet = projectiles.BulletCross(loc.x, loc.y, angle)
elif kind == "ma":
new_bullet = projectiles.BulletModA(loc.x, loc.y, angle)
elif kind == "mb":
new_bullet = projectiles.BulletModB(loc.x, loc.y, angle)
elif kind == "bd":
new_bullet = projectiles.BulletBarD(loc.x, loc.y, angle)
else:
new_bullet = projectiles.Bullet(loc.x, loc.y, angle + 90)
bullets.add(new_bullet)
sprites.add(new_bullet)
def Gatling(loc, div, dir, width, count, kind, bullets, sprites):
pos = count % div
angle = 0
if dir == "right":
angle = 0
loc.y += (pos * width) - ((div * width) / 2)
elif dir == "down":
angle = 90
loc.x += (pos * width) - ((div * width) / 2)
elif dir == "left":
angle = 180
loc.y += (pos * width) - ((div * width) / 2)
elif dir == "up":
angle = 270
loc.x += (pos * width) - ((div * width) / 2)
if kind == "w":
new_bullet = projectiles.WarblyBullet(loc.x, loc.y, angle)
elif kind == "s":
new_bullet = projectiles.SpiralBullet(loc.x, loc.y, angle)
elif kind == "s2":
new_bullet = projectiles.SpiralBullet2(loc.x, loc.y, angle)
elif kind == "s3":
new_bullet = projectiles.SpiralBullet3(loc.x, loc.y, angle)
elif kind == "s3i":
new_bullet = projectiles.SpiralBullet3Inverse(loc.x, loc.y, angle)
elif kind == "s4":
new_bullet = projectiles.SpiralBullet4(loc.x, loc.y, angle)
elif kind == "s4i":
new_bullet = projectiles.SpiralBullet4Inverse(loc.x, loc.y, angle)
elif kind == "b2":
new_bullet = projectiles.Bullet2(loc.x, loc.y, angle)
elif kind == "cr":
new_bullet = projectiles.BulletCross(loc.x, loc.y, angle)
elif kind == "ma":
new_bullet = projectiles.BulletModA(loc.x, loc.y, angle)
elif kind == "mb":
new_bullet = projectiles.BulletModB(loc.x, loc.y, angle)
elif kind == "bd":
new_bullet = projectiles.BulletBarD(loc.x, loc.y, angle)
else:
new_bullet = projectiles.Bullet(loc.x, loc.y, angle)
bullets.add(new_bullet)
sprites.add(new_bullet)
| 47.21875
| 110
| 0.59111
| 1,105
| 9,066
| 4.721267
| 0.073303
| 0.129385
| 0.249185
| 0.079739
| 0.925628
| 0.915852
| 0.915469
| 0.890933
| 0.873107
| 0.819436
| 0
| 0.025271
| 0.288551
| 9,066
| 191
| 111
| 47.465969
| 0.783566
| 0
| 0
| 0.547486
| 0
| 0
| 0.015211
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.027933
| false
| 0
| 0.011173
| 0
| 0.039106
| 0
| 0
| 0
| 0
| null | 0
| 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
| 7
|
2b1b4fc1edad30b94b42ea32fe6606004ce95fda
| 413
|
py
|
Python
|
wrappers/serial/image/gather_scatter.py
|
ChrisHad/algorithm-reference-library
|
bded1b62ea801ea4f4f5bd0794c18cd81d4b2810
|
[
"Apache-2.0"
] | 22
|
2016-12-14T11:20:07.000Z
|
2021-08-13T15:23:41.000Z
|
wrappers/serial/image/gather_scatter.py
|
ChrisHad/algorithm-reference-library
|
bded1b62ea801ea4f4f5bd0794c18cd81d4b2810
|
[
"Apache-2.0"
] | 30
|
2017-06-27T09:15:38.000Z
|
2020-09-11T18:16:37.000Z
|
wrappers/serial/image/gather_scatter.py
|
ChrisHad/algorithm-reference-library
|
bded1b62ea801ea4f4f5bd0794c18cd81d4b2810
|
[
"Apache-2.0"
] | 20
|
2017-07-02T03:45:49.000Z
|
2019-12-11T17:19:01.000Z
|
#
"""
Functions that define and manipulate images. Images are just data and a World Coordinate System.
"""
from processing_components.image.gather_scatter import image_scatter_facets
from processing_components.image.gather_scatter import image_gather_facets
from processing_components.image.gather_scatter import image_scatter_channels
from processing_components.image.gather_scatter import image_gather_channels
| 45.888889
| 96
| 0.876513
| 55
| 413
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| 0.4
| 0.190751
| 0.277457
| 0.33526
| 0.722543
| 0.722543
| 0.722543
| 0.722543
| 0.722543
| 0
| 0
| 0
| 0.082324
| 413
| 9
| 97
| 45.888889
| 0.912929
| 0.232446
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| 0
| 0
| 0
| 0
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| 1
| 0
| true
| 0
| 1
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| 1
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| 0
| null | 0
| 1
| 1
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| 1
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0
| 9
|
2b1d9b80512649556b511d15ee45b44dfc4aa87b
| 46,215
|
py
|
Python
|
test/test_visceral_slide.py
|
DIAGNijmegen/adhesion_detection
|
21a9c810a4dee3c640d31f30ee5fdff1bbce9146
|
[
"Apache-2.0"
] | 2
|
2021-10-08T13:14:49.000Z
|
2022-03-18T17:53:45.000Z
|
test/test_visceral_slide.py
|
DIAGNijmegen/adhesion_detection
|
21a9c810a4dee3c640d31f30ee5fdff1bbce9146
|
[
"Apache-2.0"
] | 6
|
2021-10-12T20:55:53.000Z
|
2021-10-12T21:03:45.000Z
|
test/test_visceral_slide.py
|
DIAGNijmegen/adhesion_detection
|
21a9c810a4dee3c640d31f30ee5fdff1bbce9146
|
[
"Apache-2.0"
] | null | null | null |
from unittest import TestCase
from pathlib import Path
import numpy as np
import pickle
import json
from visceral_slide import VisceralSlideDetectorReg, VisceralSlideDetectorDF, CumulativeVisceralSlideDetectorReg,\
CumulativeVisceralSlideDetectorDF, VSNormType, VSNormField, VSWarpingField
import SimpleITK as sitk
import matplotlib.pyplot as plt
PATIENT_ID = "CM0020"
STUDY_ID = "1.2.752.24.7.621449243.4474616"
SLICE_ID = "1.3.12.2.1107.5.2.30.26380.2019060311131653190024186.0.0.0"
plot = False
class TestVisceralSlideDetector(TestCase):
def test_get_full_deformation_field(self):
exp_path = Path("data/exp.npy")
exp_image = np.load(exp_path).astype(np.uint32)
exp_mask_path = Path("data/exp_mask.npy")
exp_mask_image = np.load(exp_mask_path).astype(np.uint32)
insp_path = Path("data/insp.npy")
insp_image = np.load(insp_path).astype(np.uint32)
insp_mask_path = Path("data/insp_mask.npy")
insp_mask_image = np.load(insp_mask_path).astype(np.uint32)
masked_field = VisceralSlideDetectorReg().get_full_deformation_field(exp_image, insp_image, exp_mask_image, insp_mask_image)
self.assertTrue(masked_field[..., 0][insp_mask_image == 0].any(),
"Full deformation filed is expeced, but it is masked with abdominal cavity")
self.assertTrue(masked_field[..., 1][insp_mask_image == 0].any(),
"Full deformation filed is expeced, but it is masked with abdominal cavity")
self.assertTrue(masked_field[..., 0][insp_mask_image == 1].any(),
"Full deformation filed is expeced, but it is masked with abdominal cavity surroundings")
self.assertTrue(masked_field[..., 1][insp_mask_image == 1].any(),
"Full deformation filed is expeced, but it is masked with abdominal cavity surroundings")
def test__calculate_visceral_slide(self):
exp_path = Path("data/exp.npy")
exp_mask_path = Path("data/exp_mask.npy")
insp_path = Path("data/insp.npy")
insp_mask_path = Path("data/insp_mask.npy")
expected_visceral_slide_fixed_mask_path = Path("data/expected_slide_with_fixed_mask.pkl")
expected_visceral_slide_no_fixed_mask_path = Path("data/expected_slide_without_fixed_mask.pkl")
exp_image = np.load(exp_path).astype(np.uint32)
exp_mask_image = np.load(exp_mask_path).astype(np.uint8)
insp_image = np.load(insp_path).astype(np.uint32)
insp_mask_image = np.load(insp_mask_path).astype(np.uint8)
detector = VisceralSlideDetectorReg()
x, y, slide = detector.get_visceral_slide(exp_image, exp_mask_image, insp_image, insp_mask_image)
visceral_slide_fixed_mask = {"x": x, "y": y, "slide": slide}
with open(expected_visceral_slide_fixed_mask_path, "r+b") as file:
expected_visceral_slide_fixed_mask = pickle.load(file)
self.assertTrue(np.array_equal(visceral_slide_fixed_mask["x"], expected_visceral_slide_fixed_mask["x"]),
"Incorrect x coordinates of contour computed with fixed mask")
self.assertTrue(np.array_equal(visceral_slide_fixed_mask["y"], expected_visceral_slide_fixed_mask["y"]),
"Incorrect y coordinates of contour computed with fixed mask")
self.assertTrue(np.array_equal(visceral_slide_fixed_mask["slide"], expected_visceral_slide_fixed_mask["slide"]),
"Incorrect visceral slide computed with fixed mask")
x, y, slide = detector.get_visceral_slide(insp_image, insp_mask_image, exp_image)
visceral_slide_no_fixed_mask = {"x": x, "y": y, "slide": slide}
with open(expected_visceral_slide_no_fixed_mask_path, "r+b") as file:
expected_visceral_slide_no_fixed_mask = pickle.load(file)
self.assertTrue(np.array_equal(visceral_slide_no_fixed_mask["x"], expected_visceral_slide_no_fixed_mask["x"]),
"Incorrect x coordinates of contour computed without fixed mask")
self.assertTrue(np.array_equal(visceral_slide_no_fixed_mask["y"], expected_visceral_slide_no_fixed_mask["y"]),
"Incorrect y coordinates of contour computed without fixed mask")
self.assertTrue(np.array_equal(visceral_slide_no_fixed_mask["slide"], expected_visceral_slide_no_fixed_mask["slide"]),
"Incorrect visceral slide computed without fixed mask")
def test_insp_exp_no_norm(self):
with open("vs_load_check_insp_exp/expected_vs_insp_exp_no_norm.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
with open("vs_load_check_insp_exp/inspexp.json") as inspexp_file:
inspexp_data = json.load(inspexp_file)
inspexp_frames = inspexp_data[PATIENT_ID][STUDY_ID][SLICE_ID]
insp_ind, exp_ind = inspexp_frames[0], inspexp_frames[1]
slice_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/slice.mha"))
insp_frame, exp_frame = slice_array[insp_ind], slice_array[exp_ind]
mask_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/mask.mha"))
insp_mask, exp_mask = mask_array[insp_ind], mask_array[exp_ind]
# With image registration performed on the fly
detector1 = VisceralSlideDetectorReg()
x1, y1, vs1 = detector1.get_visceral_slide(insp_frame, insp_mask, exp_frame, exp_mask)
if plot:
plt.figure()
plt.imshow(insp_frame, cmap="gray")
plt.scatter(x1, y1, s=5, c=vs1, cmap="jet")
plt.colorbar()
plt.savefig("vs_df_calc_insp_exp.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
self.assertTrue(np.array_equal(expected_x, x1),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y1),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs1),
"Incorrect visceral slide")
# With DFs loading
df_cavity = np.load("vs_load_check_insp_exp/df_cavity.npy")
df_rest = np.load("vs_load_check_insp_exp/df_rest.npy")
df_complete = np.load("vs_load_check_insp_exp/df_complete.npy")
moving_mask = np.load("vs_load_check_insp_exp/moving_mask.npy")
detector2 = VisceralSlideDetectorDF()
x2, y2, vs2 = detector2.get_visceral_slide(df_cavity, df_rest, df_complete, moving_mask)
self.assertTrue(np.array_equal(expected_x, x2),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y2),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs2),
"Incorrect visceral slide")
def test_insp_exp_norm_avg_anterior_rest(self):
with open("vs_load_check_insp_exp/expected_vs_insp_exp_norm_avg_anterior_rest.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
with open("vs_load_check_insp_exp/inspexp.json") as inspexp_file:
inspexp_data = json.load(inspexp_file)
inspexp_frames = inspexp_data[PATIENT_ID][STUDY_ID][SLICE_ID]
insp_ind, exp_ind = inspexp_frames[0], inspexp_frames[1]
slice_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/slice.mha"))
insp_frame, exp_frame = slice_array[insp_ind], slice_array[exp_ind]
mask_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/mask.mha"))
insp_mask, exp_mask = mask_array[insp_ind], mask_array[exp_ind]
# With image registration performed on the fly
detector1 = VisceralSlideDetectorReg()
x1, y1, vs1 = detector1.get_visceral_slide(insp_frame, insp_mask, exp_frame, exp_mask,
VSNormType.average_anterior_wall, VSNormField.rest)
if plot:
plt.figure()
plt.imshow(insp_frame, cmap="gray")
plt.scatter(x1, y1, s=5, c=vs1, cmap="jet")
plt.colorbar()
plt.savefig("vs_df_calc_insp_exp_norm_avg_anterior_rest.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
self.assertTrue(np.array_equal(expected_x, x1),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y1),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs1),
"Incorrect visceral slide")
# With DFs loading
df_cavity = np.load("vs_load_check_insp_exp/df_cavity.npy")
df_rest = np.load("vs_load_check_insp_exp/df_rest.npy")
moving_mask = np.load("vs_load_check_insp_exp/moving_mask.npy")
detector2 = VisceralSlideDetectorDF()
x2, y2, vs2 = detector2.get_visceral_slide(df_cavity, df_rest, df_rest, moving_mask,
VSNormType.average_anterior_wall)
self.assertTrue(np.array_equal(expected_x, x2),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y2),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs2),
"Incorrect visceral slide")
def test_insp_exp_norm_avg_anterior_complete(self):
with open("vs_load_check_insp_exp/expected_vs_insp_exp_norm_avg_anterior_complete.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
with open("vs_load_check_insp_exp/inspexp.json") as inspexp_file:
inspexp_data = json.load(inspexp_file)
inspexp_frames = inspexp_data[PATIENT_ID][STUDY_ID][SLICE_ID]
insp_ind, exp_ind = inspexp_frames[0], inspexp_frames[1]
slice_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/slice.mha"))
insp_frame, exp_frame = slice_array[insp_ind], slice_array[exp_ind]
mask_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/mask.mha"))
insp_mask, exp_mask = mask_array[insp_ind], mask_array[exp_ind]
# With image registration performed on the fly
detector1 = VisceralSlideDetectorReg()
x1, y1, vs1 = detector1.get_visceral_slide(insp_frame, insp_mask, exp_frame, exp_mask,
VSNormType.average_anterior_wall, VSNormField.complete)
if plot:
plt.figure()
plt.imshow(insp_frame, cmap="gray")
plt.scatter(x1, y1, s=5, c=vs1, cmap="jet")
plt.colorbar()
plt.savefig("vs_df_calc_insp_exp_norm_avg_anterior_complete.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
self.assertTrue(np.array_equal(expected_x, x1),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y1),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs1),
"Incorrect visceral slide")
# With DFs loading
df_cavity = np.load("vs_load_check_insp_exp/df_cavity.npy")
df_rest = np.load("vs_load_check_insp_exp/df_rest.npy")
df_complete = np.load("vs_load_check_insp_exp/df_complete.npy")
moving_mask = np.load("vs_load_check_insp_exp/moving_mask.npy")
detector2 = VisceralSlideDetectorDF()
x2, y2, vs2 = detector2.get_visceral_slide(df_cavity, df_rest, df_complete, moving_mask,
VSNormType.average_anterior_wall)
self.assertTrue(np.array_equal(expected_x, x2),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y2),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs2),
"Incorrect visceral slide")
def test_insp_exp_norm_vicinity_rest(self):
with open("vs_load_check_insp_exp/expected_vs_insp_exp_norm_vicinity_rest.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
with open("vs_load_check_insp_exp/inspexp.json") as inspexp_file:
inspexp_data = json.load(inspexp_file)
inspexp_frames = inspexp_data[PATIENT_ID][STUDY_ID][SLICE_ID]
insp_ind, exp_ind = inspexp_frames[0], inspexp_frames[1]
slice_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/slice.mha"))
insp_frame, exp_frame = slice_array[insp_ind], slice_array[exp_ind]
mask_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/mask.mha"))
insp_mask, exp_mask = mask_array[insp_ind], mask_array[exp_ind]
# With image registration performed on the fly
detector1 = VisceralSlideDetectorReg()
x1, y1, vs1 = detector1.get_visceral_slide(insp_frame, insp_mask, exp_frame, exp_mask,
VSNormType.contour_vicinity, VSNormField.rest)
if plot:
plt.figure()
plt.imshow(insp_frame, cmap="gray")
plt.scatter(x1, y1, s=5, c=vs1, cmap="jet")
plt.colorbar()
plt.savefig("vs_df_calc_insp_exp_norm_vicinity_rest.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
self.assertTrue(np.array_equal(expected_x, x1),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y1),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs1),
"Incorrect visceral slide")
# With DFs loading
df_cavity = np.load("vs_load_check_insp_exp/df_cavity.npy")
df_rest = np.load("vs_load_check_insp_exp/df_rest.npy")
moving_mask = np.load("vs_load_check_insp_exp/moving_mask.npy")
detector2 = VisceralSlideDetectorDF()
x2, y2, vs2 = detector2.get_visceral_slide(df_cavity, df_rest, df_rest, moving_mask,
VSNormType.contour_vicinity)
self.assertTrue(np.array_equal(expected_x, x2),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y2),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs2),
"Incorrect visceral slide")
def test_insp_exp_norm_vicinity_complete(self):
with open("vs_load_check_insp_exp/expected_vs_insp_exp_norm_vicinity_complete.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
with open("vs_load_check_insp_exp/inspexp.json") as inspexp_file:
inspexp_data = json.load(inspexp_file)
inspexp_frames = inspexp_data[PATIENT_ID][STUDY_ID][SLICE_ID]
insp_ind, exp_ind = inspexp_frames[0], inspexp_frames[1]
slice_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/slice.mha"))
insp_frame, exp_frame = slice_array[insp_ind], slice_array[exp_ind]
mask_array = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_insp_exp/mask.mha"))
insp_mask, exp_mask = mask_array[insp_ind], mask_array[exp_ind]
# With image registration performed on the fly
detector1 = VisceralSlideDetectorReg()
x1, y1, vs1 = detector1.get_visceral_slide(insp_frame, insp_mask, exp_frame, exp_mask,
VSNormType.contour_vicinity, VSNormField.complete)
if plot:
plt.figure()
plt.imshow(insp_frame, cmap="gray")
plt.scatter(x1, y1, s=5, c=vs1, cmap="jet")
plt.colorbar()
plt.savefig("vs_df_calc_insp_exp_norm_vicinity_complete.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
self.assertTrue(np.array_equal(expected_x, x1),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y1),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs1),
"Incorrect visceral slide")
# With DFs loading
df_cavity = np.load("vs_load_check_insp_exp/df_cavity.npy")
df_rest = np.load("vs_load_check_insp_exp/df_rest.npy")
df_complete = np.load("vs_load_check_insp_exp/df_complete.npy")
moving_mask = np.load("vs_load_check_insp_exp/moving_mask.npy")
detector2 = VisceralSlideDetectorDF()
x2, y2, vs2 = detector2.get_visceral_slide(df_cavity, df_rest, df_complete, moving_mask,
VSNormType.contour_vicinity)
self.assertTrue(np.array_equal(expected_x, x2),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y2),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs2),
"Incorrect visceral slide")
def load_sequences(self, path, pattern="[0-9]*.npy"):
files_glob = path.glob(pattern)
files = [file.name for file in files_glob]
files = sorted([file for file in files], key=lambda file_id: int(file_id[:-4].split("_")[-1]))
return [np.load(path / file) for file in files]
def test_cum_vs_no_norm_warp_contour(self):
with open("vs_load_check_cum/expected_cum_no_norm_warp_contour.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
contour_dfs = self.load_sequences(Path("vs_load_check_cum/df_contour"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
contour_dfs,
rest_dfs,
VSNormType.none)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_no_norm_warp_contour.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.contours,
VSNormType.none,
VSNormField.rest)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_no_norm_warp_rest(self):
with open("vs_load_check_cum/expected_cum_no_norm_warp_rest.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
rest_dfs,
rest_dfs,
VSNormType.none)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_no_norm_warp_rest.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.rest,
VSNormType.none,
VSNormField.rest)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_norm_avg_norm_rest_warp_rest(self):
with open("vs_load_check_cum/expected_cum_norm_avg_norm_rest_warp_rest.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
rest_dfs,
rest_dfs,
VSNormType.average_anterior_wall)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_norm_avg_norm_rest_warp_rest.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.rest,
VSNormType.average_anterior_wall,
VSNormField.rest)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_norm_avg_norm_rest_warp_contour(self):
with open("vs_load_check_cum/expected_cum_norm_avg_norm_rest_warp_contour.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
contour_dfs = self.load_sequences(Path("vs_load_check_cum/df_contour"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
contour_dfs,
rest_dfs,
VSNormType.average_anterior_wall)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_norm_avg_norm_rest_warp_contour.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.contours,
VSNormType.average_anterior_wall,
VSNormField.rest)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_norm_avg_norm_complete_warp_rest(self):
with open("vs_load_check_cum/expected_cum_norm_avg_norm_complete_warp_rest.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
complete_dfs = self.load_sequences(Path("vs_load_check_cum/df_complete"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
rest_dfs,
complete_dfs,
VSNormType.average_anterior_wall)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_norm_avg_norm_complete_warp_rest.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.rest,
VSNormType.average_anterior_wall,
VSNormField.complete)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_norm_avg_norm_complete_warp_contour(self):
with open("vs_load_check_cum/expected_cum_norm_avg_norm_complete_warp_contour.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
complete_dfs = self.load_sequences(Path("vs_load_check_cum/df_complete"))
contour_dfs = self.load_sequences(Path("vs_load_check_cum/df_contour"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
contour_dfs,
complete_dfs,
VSNormType.average_anterior_wall)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_norm_avg_norm_complete_warp_contour.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.contours,
VSNormType.average_anterior_wall,
VSNormField.complete)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_norm_vicinity_norm_rest_warp_rest(self):
with open("vs_load_check_cum/expected_cum_norm_vicinity_norm_rest_warp_rest.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
rest_dfs,
rest_dfs,
VSNormType.contour_vicinity)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_norm_vicinity_norm_rest_warp_rest.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.rest,
VSNormType.contour_vicinity,
VSNormField.rest)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_norm_vicinity_norm_rest_warp_contour(self):
with open("vs_load_check_cum/expected_cum_norm_vicinity_norm_rest_warp_contour.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
contour_dfs = self.load_sequences(Path("vs_load_check_cum/df_contour"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
contour_dfs,
rest_dfs,
VSNormType.contour_vicinity)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_norm_vicinity_norm_rest_warp_contour.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.contours,
VSNormType.contour_vicinity,
VSNormField.rest)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_norm_vicinity_norm_complete_warp_rest(self):
with open("vs_load_check_cum/expected_cum_norm_vicinity_norm_complete_warp_rest.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
complete_dfs = self.load_sequences(Path("vs_load_check_cum/df_complete"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
rest_dfs,
complete_dfs,
VSNormType.contour_vicinity)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_norm_vicinity_norm_complete_warp_rest.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.rest,
VSNormType.contour_vicinity,
VSNormField.complete)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
def test_cum_vs_norm_vicinity_norm_complete_warp_contour(self):
with open("vs_load_check_cum/expected_cum_norm_vicinity_norm_complete_warp_contour.pkl", "r+b") as file:
expected_vs_data = pickle.load(file)
expected_x = expected_vs_data["x"]
expected_y = expected_vs_data["y"]
expected_vs = expected_vs_data["slide"]
slice = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/slice.mha"))
mask = sitk.GetArrayFromImage(sitk.ReadImage("vs_load_check_cum/mask.mha"))
# With DFs loading
moving_masks = self.load_sequences(Path("vs_load_check_cum/moving_masks"))
cavity_dfs = self.load_sequences(Path("vs_load_check_cum/df_cavity"))
rest_dfs = self.load_sequences(Path("vs_load_check_cum/df_rest"))
complete_dfs = self.load_sequences(Path("vs_load_check_cum/df_complete"))
contour_dfs = self.load_sequences(Path("vs_load_check_cum/df_contour"))
detector = CumulativeVisceralSlideDetectorDF()
x, y, vs = detector.get_visceral_slide(moving_masks,
cavity_dfs,
rest_dfs,
contour_dfs,
complete_dfs,
VSNormType.contour_vicinity)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
if plot:
plt.figure()
plt.imshow(slice[-2], cmap="gray")
plt.scatter(x, y, s=5, c=vs, cmap="jet")
plt.colorbar()
plt.savefig("vs_load_check_cum/vs_cum_norm_vicinity_norm_complete_warp_contour.png", bbox_inches='tight', pad_inches=0)
plt.show(bbox_inches='tight', pad_inches=0)
# With image registration performed on the fly
detector = CumulativeVisceralSlideDetectorReg()
x, y, vs = detector.get_visceral_slide(slice,
mask,
VSWarpingField.contours,
VSNormType.contour_vicinity,
VSNormField.complete)
self.assertTrue(np.array_equal(expected_x, x),
"Incorrect x coordinates of contour")
self.assertTrue(np.array_equal(expected_y, y),
"Incorrect y coordinates of contour")
self.assertTrue(np.array_equal(expected_vs, vs),
"Incorrect visceral slide")
| 49.427807
| 132
| 0.596798
| 5,392
| 46,215
| 4.788576
| 0.031528
| 0.027188
| 0.049845
| 0.078079
| 0.966421
| 0.960496
| 0.953369
| 0.941247
| 0.933153
| 0.929706
| 0
| 0.008201
| 0.313967
| 46,215
| 934
| 133
| 49.480728
| 0.806182
| 0.020102
| 0
| 0.855355
| 0
| 0.001391
| 0.192911
| 0.104278
| 0
| 0
| 0
| 0
| 0.139082
| 1
| 0.025035
| false
| 0
| 0.011127
| 0
| 0.038943
| 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
|
2b1de777bc77a06aa7e69aeb75901dade7d9dd3e
| 1,978
|
py
|
Python
|
src/tests/test_ledger.py
|
cdragos/pyledger
|
d7f12a32c4e8b182123ddf06736dac51887e9c34
|
[
"MIT"
] | 1
|
2020-06-22T20:35:25.000Z
|
2020-06-22T20:35:25.000Z
|
src/tests/test_ledger.py
|
cdragos/pyledger
|
d7f12a32c4e8b182123ddf06736dac51887e9c34
|
[
"MIT"
] | null | null | null |
src/tests/test_ledger.py
|
cdragos/pyledger
|
d7f12a32c4e8b182123ddf06736dac51887e9c34
|
[
"MIT"
] | null | null | null |
from datetime import datetime
import pytest
import pandas as pd
from src.ledger import Ledger
def test_get_account_balance(mocker):
mock_read_csv = mocker.patch('src.ledger.pd.read_csv')
mock_read_csv.return_value = pd.DataFrame({
'date': pd.Series([
datetime(2015, 1, 16),
datetime(2015, 1, 17),
datetime(2015, 1, 17),
datetime(2015, 1, 17),
datetime(2015, 1, 18),
]),
'from': pd.Series([
'john',
'john',
'mary',
'dragos',
'mary',
]),
'to': pd.Series([
'mary',
'supermarket',
'insurance',
'mary',
'supermakert',
]),
'amount': pd.Series([
135.00,
20.00,
100.00,
90.00,
10.00,
]),
})
ledger = Ledger('data.csv')
assert ledger.get_account_balance('john') == '§-155.00'
assert ledger.get_account_balance('mary') == '§115.00'
def test_get_account_balance_with_date(mocker):
mock_read_csv = mocker.patch('src.ledger.pd.read_csv')
mock_read_csv.return_value = pd.DataFrame({
'date': pd.Series([
datetime(2015, 1, 16),
datetime(2015, 1, 17),
datetime(2015, 1, 17),
datetime(2015, 1, 17),
datetime(2015, 1, 18),
]),
'from': pd.Series([
'john',
'john',
'mary',
'dragos',
'mary',
]),
'to': pd.Series([
'mary',
'supermarket',
'insurance',
'mary',
'supermakert',
]),
'amount': pd.Series([
135.00,
20.00,
100.00,
90.00,
10.00,
]),
})
ledger = Ledger('data.csv')
assert ledger.get_account_balance('mary', '2015-01-17') == '§125.00'
| 24.121951
| 72
| 0.450455
| 205
| 1,978
| 4.234146
| 0.24878
| 0.138249
| 0.14977
| 0.103687
| 0.865207
| 0.809908
| 0.767281
| 0.767281
| 0.767281
| 0.767281
| 0
| 0.115807
| 0.401921
| 1,978
| 81
| 73
| 24.419753
| 0.615385
| 0
| 0
| 0.876712
| 0
| 0
| 0.130435
| 0.022245
| 0
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0
| 7
|
997dbca0e386f8e418075e4a33ac29f65af87809
| 25,322
|
py
|
Python
|
cloudmersive_nlp_api_client/api/pos_tagger_api.py
|
Cloudmersive/Cloudmersive.APIClient.Python.NLP
|
6548e61749cd1d98ddae3e3d9bd8032217d0a8b5
|
[
"Apache-2.0"
] | 1
|
2019-04-28T16:55:02.000Z
|
2019-04-28T16:55:02.000Z
|
cloudmersive_nlp_api_client/api/pos_tagger_api.py
|
Cloudmersive/Cloudmersive.APIClient.Python.NLP
|
6548e61749cd1d98ddae3e3d9bd8032217d0a8b5
|
[
"Apache-2.0"
] | 1
|
2020-08-16T17:55:35.000Z
|
2020-08-16T17:55:35.000Z
|
cloudmersive_nlp_api_client/api/pos_tagger_api.py
|
Cloudmersive/Cloudmersive.APIClient.Python.NLP
|
6548e61749cd1d98ddae3e3d9bd8032217d0a8b5
|
[
"Apache-2.0"
] | null | null | null |
# coding: utf-8
"""
nlpapiv2
The powerful Natural Language Processing APIs (v2) let you perform part of speech tagging, entity identification, sentence parsing, and much more to help you understand the meaning of unstructured text. # noqa: E501
OpenAPI spec version: v1
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from cloudmersive_nlp_api_client.api_client import ApiClient
class PosTaggerApi(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):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def pos_tagger_tag_adjectives(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to adjectives # noqa: E501
Part-of-speech (POS) tag a string, find the adjectives, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_adjectives(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.pos_tagger_tag_adjectives_with_http_info(request, **kwargs) # noqa: E501
else:
(data) = self.pos_tagger_tag_adjectives_with_http_info(request, **kwargs) # noqa: E501
return data
def pos_tagger_tag_adjectives_with_http_info(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to adjectives # noqa: E501
Part-of-speech (POS) tag a string, find the adjectives, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_adjectives_with_http_info(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method pos_tagger_tag_adjectives" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'request' is set
if ('request' not in params or
params['request'] is None):
raise ValueError("Missing the required parameter `request` when calling `pos_tagger_tag_adjectives`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'request' in params:
body_params = params['request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json', 'text/json', 'application/xml', 'text/xml', 'application/x-www-form-urlencoded']) # noqa: E501
# Authentication setting
auth_settings = ['Apikey'] # noqa: E501
return self.api_client.call_api(
'/nlp-v2/pos/tag/adjectives', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PosResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def pos_tagger_tag_adverbs(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to adverbs # noqa: E501
Part-of-speech (POS) tag a string, find the adverbs, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_adverbs(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.pos_tagger_tag_adverbs_with_http_info(request, **kwargs) # noqa: E501
else:
(data) = self.pos_tagger_tag_adverbs_with_http_info(request, **kwargs) # noqa: E501
return data
def pos_tagger_tag_adverbs_with_http_info(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to adverbs # noqa: E501
Part-of-speech (POS) tag a string, find the adverbs, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_adverbs_with_http_info(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method pos_tagger_tag_adverbs" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'request' is set
if ('request' not in params or
params['request'] is None):
raise ValueError("Missing the required parameter `request` when calling `pos_tagger_tag_adverbs`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'request' in params:
body_params = params['request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json', 'text/json', 'application/xml', 'text/xml', 'application/x-www-form-urlencoded']) # noqa: E501
# Authentication setting
auth_settings = ['Apikey'] # noqa: E501
return self.api_client.call_api(
'/nlp-v2/pos/tag/adverbs', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PosResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def pos_tagger_tag_nouns(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to nouns # noqa: E501
Part-of-speech (POS) tag a string, find the nouns, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_nouns(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.pos_tagger_tag_nouns_with_http_info(request, **kwargs) # noqa: E501
else:
(data) = self.pos_tagger_tag_nouns_with_http_info(request, **kwargs) # noqa: E501
return data
def pos_tagger_tag_nouns_with_http_info(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to nouns # noqa: E501
Part-of-speech (POS) tag a string, find the nouns, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_nouns_with_http_info(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method pos_tagger_tag_nouns" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'request' is set
if ('request' not in params or
params['request'] is None):
raise ValueError("Missing the required parameter `request` when calling `pos_tagger_tag_nouns`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'request' in params:
body_params = params['request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json', 'text/json', 'application/xml', 'text/xml', 'application/x-www-form-urlencoded']) # noqa: E501
# Authentication setting
auth_settings = ['Apikey'] # noqa: E501
return self.api_client.call_api(
'/nlp-v2/pos/tag/nouns', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PosResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def pos_tagger_tag_pronouns(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to pronouns # noqa: E501
Part-of-speech (POS) tag a string, find the pronouns, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_pronouns(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.pos_tagger_tag_pronouns_with_http_info(request, **kwargs) # noqa: E501
else:
(data) = self.pos_tagger_tag_pronouns_with_http_info(request, **kwargs) # noqa: E501
return data
def pos_tagger_tag_pronouns_with_http_info(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to pronouns # noqa: E501
Part-of-speech (POS) tag a string, find the pronouns, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_pronouns_with_http_info(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method pos_tagger_tag_pronouns" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'request' is set
if ('request' not in params or
params['request'] is None):
raise ValueError("Missing the required parameter `request` when calling `pos_tagger_tag_pronouns`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'request' in params:
body_params = params['request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json', 'text/json', 'application/xml', 'text/xml', 'application/x-www-form-urlencoded']) # noqa: E501
# Authentication setting
auth_settings = ['Apikey'] # noqa: E501
return self.api_client.call_api(
'/nlp-v2/pos/tag/pronouns', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PosResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def pos_tagger_tag_sentence(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string # noqa: E501
Part-of-speech (POS) tag a string and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_sentence(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.pos_tagger_tag_sentence_with_http_info(request, **kwargs) # noqa: E501
else:
(data) = self.pos_tagger_tag_sentence_with_http_info(request, **kwargs) # noqa: E501
return data
def pos_tagger_tag_sentence_with_http_info(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string # noqa: E501
Part-of-speech (POS) tag a string and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_sentence_with_http_info(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method pos_tagger_tag_sentence" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'request' is set
if ('request' not in params or
params['request'] is None):
raise ValueError("Missing the required parameter `request` when calling `pos_tagger_tag_sentence`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'request' in params:
body_params = params['request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json', 'text/json', 'application/xml', 'text/xml', 'application/x-www-form-urlencoded']) # noqa: E501
# Authentication setting
auth_settings = ['Apikey'] # noqa: E501
return self.api_client.call_api(
'/nlp-v2/pos/tag/sentence', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PosResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def pos_tagger_tag_verbs(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to verbs # noqa: E501
Part-of-speech (POS) tag a string, find the verbs, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_verbs(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.pos_tagger_tag_verbs_with_http_info(request, **kwargs) # noqa: E501
else:
(data) = self.pos_tagger_tag_verbs_with_http_info(request, **kwargs) # noqa: E501
return data
def pos_tagger_tag_verbs_with_http_info(self, request, **kwargs): # noqa: E501
"""Part-of-speech tag a string, filter to verbs # noqa: E501
Part-of-speech (POS) tag a string, find the verbs, and return result as JSON # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.pos_tagger_tag_verbs_with_http_info(request, async_req=True)
>>> result = thread.get()
:param async_req bool
:param PosRequest request: Input string (required)
:return: PosResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['request'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method pos_tagger_tag_verbs" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'request' is set
if ('request' not in params or
params['request'] is None):
raise ValueError("Missing the required parameter `request` when calling `pos_tagger_tag_verbs`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'request' in params:
body_params = params['request']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json', 'text/json', 'application/xml', 'text/xml', 'application/x-www-form-urlencoded']) # noqa: E501
# Authentication setting
auth_settings = ['Apikey'] # noqa: E501
return self.api_client.call_api(
'/nlp-v2/pos/tag/verbs', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PosResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
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| 220
| 0.616381
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| 5.000335
| 0.061389
| 0.048839
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| 0.953576
| 0.949685
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| 0.016048
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| 25,322
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| 40.321656
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|
0
| 7
|
5115d9e99cbec26d837994307451b378babb37ba
| 45,323
|
py
|
Python
|
coronagraph/transits.py
|
jlustigy/coronagraph
|
b321693512422343b08ada7e246413e1f4bae4cc
|
[
"MIT"
] | 4
|
2020-05-25T07:48:31.000Z
|
2022-01-04T00:40:57.000Z
|
coronagraph/transits.py
|
jlustigy/coronagraph
|
b321693512422343b08ada7e246413e1f4bae4cc
|
[
"MIT"
] | 8
|
2019-04-12T22:17:07.000Z
|
2020-05-07T00:01:11.000Z
|
coronagraph/transits.py
|
jlustigy/coronagraph
|
b321693512422343b08ada7e246413e1f4bae4cc
|
[
"MIT"
] | 6
|
2016-11-14T06:46:57.000Z
|
2021-12-31T06:50:55.000Z
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Simulate exoplanet transmission and/or emission spectroscopy without
using the coronagraph routines. This uses the same telesope and detector
parameters as the coronagraph model, but does not suppress the star's light.
As a result, stellar photons dominate the noise budget.
For transmission spectroscopy calculations use :class:`TransitNoise`,
and for emission spectroscopy use :class:`EclipseNoise`. You may also get an
example transmission and emission spectrum of the Earth by calling
:func:`get_earth_trans_spectrum`.
"""
from __future__ import (division as _, print_function as _,
absolute_import as _, unicode_literals as _)
import numpy as np
import astropy.units as u
import matplotlib.pyplot as plt
import sys, os
from .noise_routines import *
from .degrade_spec import *
from .observe import random_draw
from .teleplanstar import *
__all__ = ["TransitNoise", "EclipseNoise", "get_earth_trans_spectrum"]
h = 6.62607004e-34
c = 2.998e8
class EclipseNoise(object):
"""
Simulate exoplanet secondary eclipse emission spectroscopy with a next-generation
telescope.
Parameters
----------
telescope : Telescope
Initialized object containing ``Telescope`` parameters
planet : Planet
Initialized object containing ``Planet`` parameters
star : Star
Initialized object containing ``Star`` parameters
tdur : float
Transit duration [s]
ntran : float
Number of transits/eclipses
nout : float
Number of out-of-eclipse transit durations to observe
wantsnr : float, optional
Desired signal-to-noise ratio in each pixel
FIX_OWA : bool, optional
Set to fix OWA at ``OWA*lammin/D``, as would occur if lenslet array is
limiting the OWA
COMPUTE_LAM : bool, optional
Set to compute lo-res wavelength grid, otherwise the grid input as
variable ``lam`` is used
SILENT : bool, optional
Set to suppress print statements
NIR : bool, optional
Re-adjusts pixel size in NIR, as would occur if a second instrument
was designed to handle the NIR
THERMAL : bool, optional
Set to compute thermal photon counts due to telescope temperature
GROUND : bool, optional
Set to simulate ground-based observations through atmosphere
vod : bool, optional
"Valley of Death" red QE parameterization from Robinson et al. (2016)
"""
def __init__(self, tdur = 3432., # TRAPPIST-1e
telescope = Telescope(),
planet = Planet(),
star = Star(),
ntran = 1,
nout = 1,
wantsnr = 1000.0,
NIR = True,
THERMAL = True,
GROUND = False,
vod = False,
IMAGE = False):
self.telescope = telescope
self.planet = planet
self.star = star
self.tdur = tdur
self.ntran = ntran
self.nout = nout
self.wantsnr = wantsnr
self.NIR = NIR
self.THERMAL = THERMAL
self.GROUND = GROUND
self.vod = vod
self.IMAGE = IMAGE
self._computed = False
return
def run_count_rates(self, lamhr = None, Fphr = None, Fshr = None):
"""
Calculate the photon count rates and signal to noise on a secondary
eclipse spectrum observation
Parameters
----------
lamhr : numpy.ndarray
Wavelength [$\mu$m]
Fphr : numpy.ndarray
Dayside exoplanet TOA flux spectrum [W/m$^2$/$\mu$]
Fshr : numpy.ndarray
Stellar flux incident at the planet's TOA [W/m$^2$/$\mu$]
Calling ``run_count_rates()`` creates the following attributes for
the ``EclipseNoise`` instance:
Attributes
----------
lamhr : array
Wavelength [$\mu$m]
Fphr : array
Dayside exoplanet TOA flux spectrum [W/m$^2$/$\mu$]
Fshr : array
Stellar flux incident at the planet's TOA [W/m$^2$/$\mu$]
cs : array
Stellar photon count rate [photons/s]
cback : array
Background photon count rate [photons/s]
cz : array
Zodi photon count rate [photons/s]
cez : array
Exo-zodi photon count rate [photons/s]
cth : array
Thermal photon count rate [photons/s]
cD : array
Dark current photon count rate [photons/s]
cR : array
Read noise photon count rate [photons/s]
cmiss : array
Occulted stellar photon count rate [photons/s]
SNR1 : array
S/N for one eclipse
SNRn : array
S/N for ``ntran`` eclipses
tSNR : array
Exposure time to ``wantsnr`` [s]
nSNR : array
Number of eclipses to ``wantsnr``
lam : array
Observed wavelength grid [$\mu$m]
dlam : array
Observed wavelength grid widths [$\mu$m]
FpFslr : array
Low-res planet/star flux ratio
FpFshr : array
High-res planetr/star flux ratio
"""
self.lamhr = lamhr
self.Fphr = Fphr
self.Fshr = Fshr
if self.telescope.A_collect is None:
diam_collect = self.telescope.diameter
else:
diam_collect = 2. * (self.telescope.A_collect / np.pi)**0.5
# Set the convolution function
convolution_function = downbin_spec
# Does the telescope object already have a wavelength grid?
if (self.telescope.lam is None) or (self.telescope.dlam is None):
# Create wavelength grid
lam, dlam = construct_lam(self.telescope.lammin,
self.telescope.lammax,
self.telescope.resolution)
else:
# Use existing grids
lam = self.telescope.lam
dlam = self.telescope.dlam
# Set Quantum Efficiency
q = set_quantum_efficiency(lam,
self.telescope.qe,
NIR=self.NIR,
vod=self.vod)
# Set Dark current and Read noise
De = set_dark_current(lam,
self.telescope.darkcurrent,
self.telescope.lammax,
self.telescope.Tdet,
NIR=self.NIR)
Re = set_read_noise(lam,
self.telescope.readnoise,
NIR=self.NIR)
# Set Angular size of lenslet
theta = set_lenslet(lam,
self.telescope.lammin,
diam_collect,
self.telescope.X,
NIR=self.NIR)
# Set throughput
#sep = r/d*np.sin(alpha*np.pi/180.)*np.pi/180./3600. # separation in radians
#T = set_throughput(lam, Tput, diam, sep, IWA, OWA, lammin, FIX_OWA=FIX_OWA, SILENT=SILENT)
T = self.telescope.throughput * np.ones_like(lam)
# Apply wavelength-dependent throuput, if needed
if self.telescope.Tput_lam is not None:
# Bin input throughput curve to native res
Tlam = np.interp(lam, self.telescope.Tput_lam[0], self.telescope.Tput_lam[1])
# Multiply into regular throughput
T = T * Tlam
# Apply wavelength-dependent quantum efficiency, if needed
if self.telescope.qe_lam is not None:
# Bin input QE curve to native res
qlam = np.interp(lam, self.telescope.qe_lam[0], self.telescope.qe_lam[1])
# Multiply into regular QE
q = q * qlam
# Modify throughput by atmospheric transmission if GROUND-based
if self.GROUND:
# Use SMART calc
Tatmos = set_atmos_throughput(lam, dlam, convolution_function)
# Multiply telescope throughput by atmospheric throughput
T = T * Tatmos
# Calculate intensity of the planet [W/m^2/um/sr]
if Fphr is None:
# Using a blackbody
Bplan = planck(self.planet.Tplan, lamhr)
else:
# Using provided TOA planet flux
Bplan = Fphr / np.pi
# Calculate intensity of the star [W/m^2/um/sr]
if Fshr is None:
# Using a blackbody
Bstar = planck(self.star.Teff, lamhr)
else:
# Using provided TOA stellar flux
Bstar = Fshr / ( np.pi*(self.star.Rs*u.Rsun.in_units(u.km)/\
(self.planet.a*u.AU.in_units(u.km)))**2. )
# Solid angle in steradians
omega_star = np.pi*(self.star.Rs*u.Rsun.in_units(u.km)/\
(self.planet.distance*u.pc.in_units(u.km)))**2.
omega_planet = np.pi*(self.planet.Rp*u.Rearth.in_units(u.km)/\
(self.planet.distance*u.pc.in_units(u.km)))**2.
# Fluxes at earth [W/m^2/um]
Fs = Bstar * omega_star
Fp = Bplan * omega_planet
FpFs = Fp/Fs
# Degrade planet and stellar spectrum to instrument res
Fplr = convolution_function(Fp, lamhr, lam, dlam=dlam)
Fslr = convolution_function(Fs, lamhr, lam, dlam=dlam)
FpFslr = convolution_function(FpFs, lamhr, lam, dlam=dlam)
# Fraction of planetary signal in Airy pattern
fpa = 1.0 # No fringe pattern here --> all of stellar psf falls on CCD
########## Calculate Photon Count Rates ##########
# Planet photon count rate
cp = cplan(q, fpa, T, lam, dlam, Fplr, diam_collect)
# Stellar photon count rate
cs = cstar(q, fpa, T, lam, dlam, Fslr, diam_collect)
# Solar System Zodi count rate
cz = czodi(q, self.telescope.X, T, lam, dlam,
diam_collect, self.planet.MzV)
# Exo-Zodi count rate
cez = cezodi(q, self.telescope.X, T, lam, dlam, diam_collect,
self.planet.a,
Fstar(lam, self.star.Teff, self.star.Rs, 1., AU=True),
self.planet.Nez, self.planet.MezV)
# Dark current count rate
cD = cdark(De, self.telescope.X, lam,
diam_collect, theta,
self.telescope.DNHpix, IMAGE=self.IMAGE)
# Read noise count rate
cR = cread(Re, self.telescope.X, lam, diam_collect,
theta, self.telescope.DNHpix, self.telescope.Dtmax,
IMAGE=self.IMAGE)
# Thermal background count rate
if self.THERMAL:
# telescope internal thermal count rate
cth = ctherm(q, self.telescope.X, T, lam, dlam,
diam_collect, self.telescope.Tsys,
self.telescope.emissivity)
else:
cth = np.zeros_like(cs)
# Additional background from sky for ground-based observations
if self.GROUND:
if self.GROUND == "ESO":
# Use ESO SKCALC
wl_sky, Isky = get_sky_flux()
# Convolve to instrument resolution
Itherm = convolution_function(Isky, wl_sky, lam, dlam=dlam)
else:
# Get SMART computed surface intensity due to sky background
Itherm = get_thermal_ground_intensity(lam, dlam, convolution_function)
# Compute Earth thermal photon count rate
cthe = ctherm_earth(q, self.telescope.X, T, lam, dlam,
diam_collect, Itherm)
# Add earth thermal photon counts to telescope thermal counts
cth = cth + cthe
# Calculate background photon count rate
cback = cz + cez + cth + cD + cR
# Save count rates as attributes
self.cp = cp
self.cs = cs
self.cback = cback
self.cz = cz
self.cez = cez
self.cth = cth
self.cD = cD
self.cR = cR
# Flip the switch
self._computed = True
########## Calculate SNR-like Quantities ##########
# Count PLANET photons per eclipse
Nplan = self.tdur * 1 * cp
# Count STELLAR photons per eclipse
Nstar = self.tdur * 1 * cs
# Count BACKGROUND photons per eclipse
Nback = self.tdur * 1 * cback
# Calculate SNR on missing planet photons in one eclipse
# This formula assumes a homogeneous planet disk (i.e. no limb darkening / hot-spots),
# and comes from standard error propigation on the missing photons due to the
# star occulting the planet calculation in terms of observables
SNR1 = Nplan / np.sqrt( (1+1./self.nout)*Nstar + 1./self.nout*Nplan+(1+1./self.nout)*Nback)
# Calculate SNR on missing planet photons in ntran eclipses
SNRn = np.sqrt(self.ntran) * SNR1
# Calculate the SECONDS required to observe a given SNR as a function of the spectral res
tSNR = self.wantsnr**2 * ( (1+1./self.nout)*cs + 1./self.nout*cp+(1+1./self.nout)*cback ) / cp**2
# Calculate the NUMBER OF ECLIPSES required to observe a given SNR as a function of the spectral res
nSNR = self.wantsnr**2 * ( (1+1./self.nout) * self.tdur * cs + 1./self.nout * self.tdur * cp + (1+1./self.nout)*self.tdur*cback ) / (self.tdur * cp)**2
# Save SNR quantities as attributes
self.SNR1 = SNR1
self.SNRn = SNRn
self.tSNR = tSNR
self.nSNR = nSNR
# Save additional stuff
self.lam = lam
self.dlam = dlam
self.FpFslr = FpFslr
self.FpFshr = FpFs
# Create fake data
self.make_fake_data()
return
def make_fake_data(self):
"""
Make a fake dataset by sampling from a Gaussian.
Attributes
----------
SNRn : array
S/N in ``ntran`` eclipses
obs : array
Observed emission specrum with noise
sig : array
Observed uncertainties on emission spectrum
"""
# Ensure that simulation has been run
assert self._computed
# Calculate SNR on missing planet photons in ntran eclipses
self.SNRn = np.sqrt(self.ntran) * self.SNR1
# Generate synthetic observations
self.sig = self.FpFslr / self.SNRn
self.obs = random_draw(self.FpFslr, self.sig)
def recalc_wantsnr(self, wantsnr = None):
"""
Recalculate the time and number of eclipses required to achieve a
user specified SNR via `wantsnr`.
Attributes
----------
tSNR : array
Exposure time to ``wantsnr`` [s]
nSNR : array
Number of eclipses to ``wantsnr``
"""
assert self._computed
if wantsnr is not None:
self.wantsnr = wantsnr
# Calculate the SECONDS required to observe a given SNR as a function of the spectral res
self.tSNR = self.wantsnr**2 * ( (1+1./self.nout)*self.cs \
+ 1./self.nout*self.cp+(1+1./self.nout)*self.cback )\
/ self.cp**2
# Calculate the NUMBER OF ECLIPSES required to observe a given SNR as a function of the spectral res
self.nSNR = self.wantsnr**2 * ( (1+1./self.nout) * self.tdur * self.cs \
+ 1./self.nout * self.tdur * self.cp \
+ (1+1./self.nout)*self.tdur*self.cback ) \
/ (self.tdur * self.cp)**2
return
def plot_spectrum(self, SNR_threshold = 0.0, Nsig = None, ax0 = None,
err_kws = {"fmt" : ".", "c" : "k", "alpha" : 1},
plot_kws = {"lw" : 1.0, "c" : "C4", "alpha" : 0.5},
draw_box = True):
"""
Plot noised emission spectrum.
Parameters
----------
SNR_threshold : float
Threshold SNR below which do not plot
Nsig : float
Number of standard deviations about median observed points to set
yaxis limits
ax0 : `matplotlib.axes`
Optional axis to provide
err_kws : dic
Keyword arguments for `errorbar`
plot_kws : dic
Keyword arguments for `plot`
draw_box : bool
Draw important quantities in a box?
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
m = [self.SNRn > SNR_threshold]
scale = 1e6
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel(r"Eclipse Depth $(F_p / F_{\star})$ [ppm]")
else:
ax = ax0
#ax.plot(lam, scale*RpRs2, alpha = 1.0, ls = "steps-mid")
ax.errorbar(self.lam[m], scale*self.obs[m], yerr=scale*self.sig[m], zorder = 100, **err_kws)
#ax.set_yscale("log")
# Set ylim
if Nsig is not None:
mederr = scale*np.median(self.sig)
medy = scale*np.median(self.obs)
ax.set_ylim([medy - Nsig*mederr, medy + Nsig*mederr])
ylims = ax.get_ylim()
xlims = ax.get_xlim()
ax.plot(self.lamhr, scale*self.FpFshr, **plot_kws)
ax.set_ylim(ylims)
ax.set_xlim(xlims)
if draw_box:
text = "%i eclipses \n %i m \n %i\%% throughput" %(self.ntran, self.telescope.diameter, 100*self.telescope.throughput)
ax.text(0.02, 0.975, text, transform=ax.transAxes, ha = "left", va = "top",
bbox=dict(boxstyle="square", fc="w", ec="k", alpha=0.9), zorder=101)
#ax.legend()
if ax0 is None:
return fig, ax
else:
return
def plot_SNRn(self, ax0 = None, plot_kws = {"ls" : "steps-mid"}):
"""
Plot the S/N on the Eclipse Depth as a function of wavelength.
Parameters
----------
ax0 : `matplotlib.axes`
Optional axis to provide
plot_kws : dic
Keyword arguments for `plot`
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
else:
ax = ax0
ax.plot(self.lam, self.SNRn, **plot_kws)
#ax.set_yscale("log")
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("S/N on Eclipse Depth")
#ax.legend()
if ax0 is None:
return fig, ax
else:
return
def plot_ntran_to_wantsnr(self, ax0 = None,
plot_kws = {"ls" : "steps-mid", "alpha" : 1.0}):
"""
Plot the number of eclipses to get a SNR on the eclipse depth as
a function of wavelength.
Parameters
----------
ax0 : `matplotlib.axes`
Optional axis to provide
plot_kws : dic
Keyword arguments for `plot`
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("Eclipses to S/N = %i on Eclipse Depth" %self.wantsnr)
ax.set_yscale("log")
else:
ax = ax0
ax.plot(self.lam, self.nSNR, **plot_kws)
if ax0 is None:
return fig, ax
else:
return
def plot_time_to_wantsnr(self, ax0 = None, plot_kws = {"ls" : "steps-mid", "alpha" : 1.0}):
"""
Plot the time to get a SNR on the eclipse depth as
a function of wavelength.
Parameters
----------
ax0 : `matplotlib.axes`
Optional axis to provide
plot_kws : dic
Keyword arguments for `plot`
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("Time to S/N = %i on Eclipse Depth [s]" %self.wantsnr)
ax.set_yscale("log")
else:
ax = ax0
ax.plot(self.lam, self.tSNR, **plot_kws)
if ax0 is None:
return fig, ax
else:
return
def plot_count_rates(self, ax0 = None):
"""
Plot the photon count rate for all sources.
Parameters
----------
ax0 : `matplotlib.axes`
Optional axis to provide
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("Photons / s")
ax.set_yscale("log")
else:
ax = ax0
ax.plot(self.lam, self.cp, label = "Planet", ls = "dashed")
ax.plot(self.lam, self.cs, label = "Star")
ax.plot(self.lam, self.cback, label = "Total Bkg")
ax.plot(self.lam, self.cz, label = "SS Zodi")
ax.plot(self.lam, self.cez, label = "Exo-Zodi")
ax.plot(self.lam, self.cth, label = "Thermal Bkg")
ax.plot(self.lam, self.cD, label = "Dark")
ax.plot(self.lam, self.cR, label = "Read")
if ax0 is None:
leg = ax.legend(fontsize = 14, ncol = 2)
return fig, ax
else:
return
class TransitNoise(object):
"""
Simulate exoplanet transit transmission spectroscopy with a next-generation
telescope.
Parameters
----------
telescope : Telescope
Initialized object containing ``Telescope`` parameters
planet : Planet
Initialized object containing ``Planet`` parameters
star : Star
Initialized object containing ``Star`` parameters
tdur : float
Transit duration [s]
ntran : float
Number of transits
nout : float
Number of out-of-transit transit durations to observe
wantsnr : float, optional
Desired signal-to-noise ratio in each pixel
FIX_OWA : bool, optional
Set to fix OWA at ``OWA*lammin/D``, as would occur if lenslet array is
limiting the OWA
COMPUTE_LAM : bool, optional
Set to compute lo-res wavelength grid, otherwise the grid input as
variable ``lam`` is used
SILENT : bool, optional
Set to suppress print statements
NIR : bool, optional
Re-adjusts pixel size in NIR, as would occur if a second instrument
was designed to handle the NIR
THERMAL : bool, optional
Set to compute thermal photon counts due to telescope temperature
GROUND : bool, optional
Set to simulate ground-based observations through atmosphere
vod : bool, optional
"Valley of Death" red QE parameterization from Robinson et al. (2016)
"""
def __init__(self, tdur = 3432., # TRAPPIST-1e
telescope = Telescope(),
planet = Planet(),
star = Star(),
ntran = 1,
nout = 1,
wantsnr = 1000.0,
NIR = True,
THERMAL = True,
GROUND = False,
vod = False,
IMAGE = False):
self.telescope = telescope
self.planet = planet
self.star = star
self.tdur = tdur
self.ntran = ntran
self.nout = nout
self.wantsnr = wantsnr
self.NIR = NIR
self.THERMAL = THERMAL
self.GROUND = GROUND
self.vod = vod
self.IMAGE = IMAGE
self._computed = False
return
def run_count_rates(self, lamhr = None, tdhr = None, Fshr = None):
"""
Calculate the photon count rates and signal to noise on a
transmission spectrum observation
Parameters
----------
lamhr : numpy.ndarray
Wavelength [$\mu$m]
tdhr : numpy.ndarray
Transit Depth $(Rp/Rs)^2$
Fshr : numpy.ndarray
Flux density incident at the planet's TOA [W/m$^2$/$\mu$]
Calling ``run_count_rates()`` creates the following attributes for
the ``TransitNoise`` instance:
Attributes
----------
lamhr : array
Wavelength [$\mu$m]
tdhr : array
Transit Depth $(Rp/Rs)^2$
Fshr : array
Flux density incident at the planet's TOA [W/m$^2$/$\mu$]
cs : array
Stellar photon count rate [photons/s]
cback : array
Background photon count rate [photons/s]
cz : array
Zodi photon count rate [photons/s]
cez : array
Exo-zodi photon count rate [photons/s]
cth : array
Thermal photon count rate [photons/s]
cD : array
Dark current photon count rate [photons/s]
cR : array
Read noise photon count rate [photons/s]
cmiss : array
Occulted stellar photon count rate [photons/s]
SNR1 : array
S/N for one transit
SNRn : array
S/N for ``ntran`` transits
tSNR : array
Exposure time to ``wantsnr`` [s]
nSNR : array
Number of transits to ``wantsnr``
lam : array
Observed wavelength grid [$\mu$m]
dlam : array
Observed wavelength grid widths [$\mu$m]
RpRs2 : array
Low-res transit depth
"""
self.lamhr = lamhr
self.tdhr = tdhr
self.Fshr = Fshr
if self.telescope.A_collect is None:
diam_collect = self.telescope.diameter
else:
diam_collect = 2. * (self.telescope.A_collect / np.pi)**0.5
# Set the convolution function
convolution_function = downbin_spec
# Does the telescope object already have a wavelength grid?
if (self.telescope.lam is None) or (self.telescope.dlam is None):
# Create wavelength grid
lam, dlam = construct_lam(self.telescope.lammin,
self.telescope.lammax,
self.telescope.resolution)
else:
# Use existing grids
lam = self.telescope.lam
dlam = self.telescope.dlam
# Set Quantum Efficiency
q = set_quantum_efficiency(lam,
self.telescope.qe,
NIR=self.NIR,
vod=self.vod)
# Set Dark current and Read noise
De = set_dark_current(lam,
self.telescope.darkcurrent,
self.telescope.lammax,
self.telescope.Tdet,
NIR=self.NIR)
Re = set_read_noise(lam,
self.telescope.readnoise,
NIR=self.NIR)
# Set Angular size of lenslet
theta = set_lenslet(lam,
self.telescope.lammin,
diam_collect,
self.telescope.X,
NIR=self.NIR)
# Set throughput
#sep = r/d*np.sin(alpha*np.pi/180.)*np.pi/180./3600. # separation in radians
#T = set_throughput(lam, Tput, diam, sep, IWA, OWA, lammin, FIX_OWA=FIX_OWA, SILENT=SILENT)
T = self.telescope.throughput * np.ones_like(lam)
# Apply wavelength-dependent throuput, if needed
if self.telescope.Tput_lam is not None:
# Bin input throughput curve to native res
Tlam = np.interp(lam, self.telescope.Tput_lam[0], self.telescope.Tput_lam[1])
# Multiply into regular throughput
T = T * Tlam
# Apply wavelength-dependent quantum efficiency, if needed
if self.telescope.qe_lam is not None:
# Bin input QE curve to native res
qlam = np.interp(lam, self.telescope.qe_lam[0], self.telescope.qe_lam[1])
# Multiply into regular QE
q = q * qlam
# Modify throughput by atmospheric transmission if GROUND-based
if self.GROUND:
# Use SMART calc
Tatmos = set_atmos_throughput(lam, dlam, convolution_function)
# Multiply telescope throughput by atmospheric throughput
T = T * Tatmos
# Degrade transit and stellar spectrum
RpRs2 = convolution_function(tdhr,lamhr,lam,dlam=dlam)
# Calculate intensity of the star [W/m^2/um/sr]
if Fshr is None:
# Using a blackbody
Bstar = planck(self.star.Teff, lam)
else:
# Using provided TOA stellar flux
Fslr = convolution_function(Fshr, lamhr, lam, dlam=dlam)
Bstar = Fslr / ( np.pi*(self.star.Rs*u.Rsun.in_units(u.km)/\
(self.planet.a*u.AU.in_units(u.km)))**2. )
# Solid angle in steradians
omega_star = np.pi*(self.star.Rs*u.Rsun.in_units(u.km)/\
(self.planet.distance*u.pc.in_units(u.km)))**2.
omega_planet = np.pi*(self.planet.Rp*u.Rearth.in_units(u.km)/\
(self.planet.distance*u.pc.in_units(u.km)))**2.
# Fluxes at earth [W/m^2/um]
Fs = Bstar * omega_star
#Fback = jwst_background(lam)
Fstar_miss = Fs * RpRs2
# Fraction of planetary signal in Airy pattern
fpa = 1.0 # No fringe pattern here --> all of stellar psf falls on CCD
########## Calculate Photon Count Rates ##########
# Stellar photon count rate
cs = cstar(q, fpa, T, lam, dlam, Fs, diam_collect)
# Missing photon count rate (is this a thing? it is now!)
cmiss = Fstar_miss*dlam*(lam*1e-6)/(h*c)*T*(np.pi * (0.5*diam_collect)**2)
# Solar System Zodi count rate
cz = czodi(q, self.telescope.X, T, lam, dlam,
diam_collect, self.planet.MzV)
# Exo-Zodi count rate
cez = cezodi(q, self.telescope.X, T, lam, dlam, diam_collect,
self.planet.a,
Fstar(lam, self.star.Teff, self.star.Rs, 1., AU=True),
self.planet.Nez, self.planet.MezV)
# Dark current count rate
cD = cdark(De, self.telescope.X, lam,
diam_collect, theta,
self.telescope.DNHpix, IMAGE=self.IMAGE)
# Read noise count rate
cR = cread(Re, self.telescope.X, lam, diam_collect,
theta, self.telescope.DNHpix, self.telescope.Dtmax,
IMAGE=self.IMAGE)
# Thermal background count rate
if self.THERMAL:
# telescope internal thermal count rate
cth = ctherm(q, self.telescope.X, T, lam, dlam,
diam_collect, self.telescope.Tsys,
self.telescope.emissivity)
else:
cth = np.zeros_like(cs)
# Additional background from sky for ground-based observations
if self.GROUND:
if self.GROUND == "ESO":
# Use ESO SKCALC
wl_sky, Isky = get_sky_flux()
# Convolve to instrument resolution
Itherm = convolution_function(Isky, wl_sky, lam, dlam=dlam)
else:
# Get SMART computed surface intensity due to sky background
Itherm = get_thermal_ground_intensity(lam, dlam, convolution_function)
# Compute Earth thermal photon count rate
cthe = ctherm_earth(q, self.telescope.X, T, lam, dlam,
diam_collect, Itherm)
# Add earth thermal photon counts to telescope thermal counts
cth = cth + cthe
# Calculate background photon count rate
cback = cz + cez + cth + cD + cR
# Save count rates as attributes
self.cs = cs
self.cback = cback
self.cz = cz
self.cez = cez
self.cth = cth
self.cD = cD
self.cR = cR
self.cmiss = cmiss
# Flip the switch
self._computed = True
########## Calculate SNR-like Quantities ##########
# Count STELLAR photons per transit
Nstar = self.tdur * 1 * cs
# Count BACKGROUND photons per transit
Nback = self.tdur * 1 * cback
# Calculate SNR on missing stellar photons in one transit
# This formula assumes a homogeneous stellar disk (i.e. no limb darkening),
# and comes from standard error propigation on the missing photons due to the
# planet occulting the star calculation in terms of observables
SNR1 = (Nstar * RpRs2) / np.sqrt((1 + 1./self.nout - RpRs2) * Nstar + (1 + 1./self.nout) * Nback)
# Calculate SNR on missing stellar photons in ntran transits
SNRn = np.sqrt(self.ntran) * SNR1
# Calculate the SECONDS required to observe a given SNR as a function of the spectral res
tSNR = self.wantsnr**2 * ((1 + 1./self.nout - RpRs2) * cs + (1 + 1./self.nout) * cback) / (cs * RpRs2)**2
# Calculate the NUMBER OF TRANSITS required to observe a given SNR as a function of the spectral res
nSNR = self.wantsnr**2 * ((1 + 1./self.nout - RpRs2) * self.tdur * cs + (1 + 1./self.nout) * self.tdur * cback) / (self.tdur * cs * RpRs2)**2
# Save SNR quantities as attributes
self.SNR1 = SNR1
self.SNRn = SNRn
self.tSNR = tSNR
self.nSNR = nSNR
# Save additional stuff
self.lam = lam
self.dlam = dlam
self.RpRs2 = RpRs2
# Create fake data
self.make_fake_data()
return
def make_fake_data(self):
"""
Make a fake dataset by sampling from a Gaussian.
Attributes
----------
SNRn : array
S/N in ``ntran`` transits
obs : array
Observed transit depth with noise
sig : array
Observed uncertainties on transit depth
"""
# Ensure that simulation has been run
assert self._computed
# Calculate SNR on missing stellar photons in ntran transits
self.SNRn = np.sqrt(self.ntran) * self.SNR1
# Generate synthetic observations
self.sig = self.RpRs2 / self.SNRn
self.obs = random_draw(self.RpRs2, self.sig)
def recalc_wantsnr(self, wantsnr = None):
"""
Recalculate the time and number of transits required to achieve a
user specified SNR via `wantsnr`.
Attributes
----------
tSNR : array
Exposure time to ``wantsnr`` [s]
nSNR : array
Number of transits to ``wantsnr``
"""
assert self._computed
if wantsnr is not None:
self.wantsnr = wantsnr
# Calculate the SECONDS required to observe a given SNR as a function of the spectral res
self.tSNR = self.wantsnr**2 * ((1 + 1./self.nout - self.RpRs2) \
* self.cs + (1 + 1./self.nout) \
* self.cback) / (self.cs * self.RpRs2)**2
# Calculate the NUMBER OF TRANSITS required to observe a given SNR as a function of the spectral res
self.nSNR = self.wantsnr**2 * ((1 + 1./self.nout - self.RpRs2) \
* self.tdur * self.cs + (1 + 1./self.nout) \
* self.tdur * self.cback) / (self.tdur * self.cs * self.RpRs2)**2
return
def plot_spectrum(self, SNR_threshold = 1.0, Nsig = 6.0, ax0 = None,
err_kws = {"fmt" : ".", "c" : "k", "alpha" : 1},
plot_kws = {"lw" : 1.0, "c" : "C4", "alpha" : 0.5},
draw_box = True):
"""
Plot noised transmission spectrum.
Parameters
----------
SNR_threshold : float
Threshold SNR below which do not plot
Nsig : float
Number of standard deviations about median observed points to set
yaxis limits
ax0 : `matplotlib.axes`
Optional axis to provide
err_kws : dic
Keyword arguments for `errorbar`
plot_kws : dic
Keyword arguments for `plot`
draw_box : bool
Draw important quantities in a box?
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
m = [self.SNRn > SNR_threshold]
scale = 1e6
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("Transit Depth $(R_p / R_{\star})^2$ [ppm]")
else:
ax = ax0
#ax.plot(lam, scale*RpRs2, alpha = 1.0, ls = "steps-mid")
ax.errorbar(self.lam[m], scale*self.obs[m], yerr=scale*self.sig[m], zorder = 100, **err_kws)
#ax.set_yscale("log")
# Set ylim
mederr = scale*np.median(self.sig)
medy = scale*np.median(self.obs)
ax.set_ylim([medy - Nsig*mederr, medy + Nsig*mederr])
ylims = ax.get_ylim()
xlims = ax.get_xlim()
ax.plot(self.lamhr, scale*self.tdhr, **plot_kws)
ax.set_ylim(ylims)
ax.set_xlim(xlims)
if draw_box:
text = "%i transits \n %i m \n %i\%% throughput" %(self.ntran, self.telescope.diameter, 100*self.telescope.throughput)
ax.text(0.02, 0.975, text, transform=ax.transAxes, ha = "left", va = "top",
bbox=dict(boxstyle="square", fc="w", ec="k", alpha=0.9), zorder=101)
#ax.legend()
if ax0 is None:
return fig, ax
else:
return
def plot_SNRn(self, ax0 = None, plot_kws = {"ls" : "steps-mid"}):
"""
Plot the S/N on the Transit Depth as a function of wavelength.
Parameters
----------
ax0 : `matplotlib.axes`
Optional axis to provide
plot_kws : dic
Keyword arguments for `plot`
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
else:
ax = ax0
ax.plot(self.lam, self.SNRn, **plot_kws)
#ax.set_yscale("log")
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("S/N on Transit Depth")
#ax.legend()
if ax0 is None:
return fig, ax
else:
return
def plot_ntran_to_wantsnr(self, ax0 = None,
plot_kws = {"ls" : "steps-mid", "alpha" : 1.0}):
"""
Plot the number of transits to get a SNR on the transit depth as
a function of wavelength.
Parameters
----------
ax0 : `matplotlib.axes`
Optional axis to provide
plot_kws : dic
Keyword arguments for `plot`
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("Transits to S/N = %i on Transit Depth" %self.wantsnr)
ax.set_yscale("log")
else:
ax = ax0
ax.plot(self.lam, self.nSNR, **plot_kws)
if ax0 is None:
return fig, ax
else:
return
def plot_time_to_wantsnr(self, ax0 = None, plot_kws = {"ls" : "steps-mid", "alpha" : 1.0}):
"""
Plot the time to get a SNR on the transit depth as
a function of wavelength.
Parameters
----------
ax0 : `matplotlib.axes`
Optional axis to provide
plot_kws : dic
Keyword arguments for `plot`
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("Time to S/N = %i on Transit Depth [s]" %self.wantsnr)
ax.set_yscale("log")
else:
ax = ax0
ax.plot(self.lam, self.tSNR, **plot_kws)
if ax0 is None:
return fig, ax
else:
return
def plot_count_rates(self, ax0 = None):
"""
Plot the photon count rate for all sources.
Parameters
----------
ax0 : `matplotlib.axes`
Optional axis to provide
Returns
-------
fig : `matplotlib.figure.Figure`
Returns a figure if `ax0` is `None`
ax : `matplotlib.axes`
Returns an axis if `ax0` is `None`
Note
----
Only returns `fig` and `ax` is ``ax0 is None``
"""
if ax0 is None:
# Create Plot
fig, ax = plt.subplots(figsize = (10,8))
ax.set_xlabel(r"Wavelength [$\mu$m]")
ax.set_ylabel("Photons / s")
ax.set_yscale("log")
else:
ax = ax0
ax.plot(self.lam, self.cmiss, label = "Occulted", ls = "dashed")
ax.plot(self.lam, self.cs, label = "Star")
ax.plot(self.lam, self.cback, label = "Total Bkg")
ax.plot(self.lam, self.cz, label = "SS Zodi")
ax.plot(self.lam, self.cez, label = "Exo-Zodi")
ax.plot(self.lam, self.cth, label = "Thermal Bkg")
ax.plot(self.lam, self.cD, label = "Dark")
ax.plot(self.lam, self.cR, label = "Read")
if ax0 is None:
leg = ax.legend(fontsize = 14, ncol = 2)
return fig, ax
else:
return
def get_earth_trans_spectrum():
'''
Get the transmission spectrum of the Earth around the Sun.
Returns
-------
lam : `numpy.ndarray`
Wavelength grid [um]
tdepth : `numpy.ndarray`
Transit depth (Rp/Rs)^2
fplan : `numpy.ndarray`
TOA planet flux [W/m^2/um]
fstar : `numpy.ndarray`
Stellar flux at planet [W/m^2/um]
'''
# Read in transit data
here = os.path.join(os.path.dirname(__file__))
plus = "planets/earth_avg_hitran2012_300_100000cm.trnst"
data = np.loadtxt(os.path.join(here, plus))
# Parse
lam = data[:,0]
tdepth = data[:,3]
# Read in flux data
plus = "planets/earth_avg_hitran2012_300_100000cm_toa.rad"
data = np.loadtxt(os.path.join(here, plus))
# Parse
fplan = data[:,3]
fstar = data[:,2]
return lam, tdepth, fplan, fstar
| 33.522929
| 159
| 0.53474
| 5,455
| 45,323
| 4.386618
| 0.100458
| 0.041289
| 0.018806
| 0.018388
| 0.883489
| 0.874462
| 0.858832
| 0.837728
| 0.834134
| 0.80906
| 0
| 0.014968
| 0.36615
| 45,323
| 1,351
| 160
| 33.547742
| 0.817982
| 0.386404
| 0
| 0.821154
| 0
| 0
| 0.041062
| 0.004908
| 0
| 0
| 0
| 0
| 0.007692
| 1
| 0.036538
| false
| 0
| 0.019231
| 0
| 0.111538
| 0.001923
| 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
|
5aa4cf7f53cfbf62bd246840806e79cfca651c93
| 91
|
py
|
Python
|
tests/utils/__init__.py
|
id23cat/DMC-compute-nodes
|
de295b97c0832eb83a7f4c29cb34b517b9ded1bd
|
[
"Apache-2.0"
] | null | null | null |
tests/utils/__init__.py
|
id23cat/DMC-compute-nodes
|
de295b97c0832eb83a7f4c29cb34b517b9ded1bd
|
[
"Apache-2.0"
] | null | null | null |
tests/utils/__init__.py
|
id23cat/DMC-compute-nodes
|
de295b97c0832eb83a7f4c29cb34b517b9ded1bd
|
[
"Apache-2.0"
] | 1
|
2021-06-15T14:46:41.000Z
|
2021-06-15T14:46:41.000Z
|
from tests.utils.timed_dict import *
from tests.utils.error_context_handler_mixin import *
| 30.333333
| 53
| 0.846154
| 14
| 91
| 5.214286
| 0.714286
| 0.246575
| 0.383562
| 0
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| 0.087912
| 91
| 2
| 54
| 45.5
| 0.879518
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| 0
| true
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| null | 1
| 1
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| 0
|
0
| 7
|
5af9a223bc397bb5c33ea38ddef6a8781c576498
| 31,879
|
py
|
Python
|
test/rlai/runners/trainer_test.py
|
MatthewGerber/rlai
|
f390433c3adc285e1e9cc113deed7009b2e6dd5a
|
[
"MIT"
] | 9
|
2021-05-09T22:30:42.000Z
|
2021-12-27T19:42:56.000Z
|
test/rlai/runners/trainer_test.py
|
MatthewGerber/rlai
|
f390433c3adc285e1e9cc113deed7009b2e6dd5a
|
[
"MIT"
] | 13
|
2020-11-18T03:30:39.000Z
|
2021-12-12T04:19:16.000Z
|
test/rlai/runners/trainer_test.py
|
MatthewGerber/rlai
|
f390433c3adc285e1e9cc113deed7009b2e6dd5a
|
[
"MIT"
] | 1
|
2021-06-24T16:48:59.000Z
|
2021-06-24T16:48:59.000Z
|
import os
import pickle
import shlex
import tempfile
from typing import Any, Dict, Tuple
import pytest
import rlai.q_S_A.function_approximation.models
from rlai.policies.tabular import TabularPolicy
from rlai.runners.trainer import run
from test.rlai.utils import start_virtual_display_if_headless
def test_continuous_state_discretization():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --continuous-state-discretization-resolution 0.1 --gamma 1 --environment rlai.environments.openai_gym.Gym --gym-id CartPole-v1 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --n-steps 10 --num-improvements 3 --num-episodes-per-improvement 5 --alpha 0.1 --epsilon 0.01 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True --num-improvements-per-checkpoint 3 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_continuous_state_discretization.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_continuous_state_discretization.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_trajectory_sampling_planning():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --planning-environment rlai.environments.mdp.TrajectorySamplingMdpPlanningEnvironment --num-planning-improvements-per-direct-improvement 10 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 10 --num-episodes-per-improvement 5 --epsilon 0.01 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True --num-improvements-per-checkpoint 10 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_trajectory_sampling_planning.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_trajectory_sampling_planning.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_prioritized_sweeping_planning_low_threshold():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --planning-environment rlai.environments.mdp.PrioritizedSweepingMdpPlanningEnvironment --num-planning-improvements-per-direct-improvement 10 --priority-theta -1 --T-planning 50 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 10 --num-episodes-per-improvement 5 --epsilon 0.01 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True --num-improvements-per-checkpoint 10 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_prioritized_sweeping_planning_low_threshold.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_prioritized_sweeping_planning_low_threshold.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_prioritized_sweeping_planning_high_threshold():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --planning-environment rlai.environments.mdp.PrioritizedSweepingMdpPlanningEnvironment --num-planning-improvements-per-direct-improvement 10 --priority-theta -10 --T-planning 50 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 10 --num-episodes-per-improvement 1 --epsilon 0.01 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True --num-improvements-per-checkpoint 10 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_prioritized_sweeping_planning_high_threshold.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_prioritized_sweeping_planning_high_threshold.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_q_learning_with_patsy_formula():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --T 25 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 5 --num-episodes-per-improvement 5 --epsilon 0.05 --q-S-A rlai.q_S_A.function_approximation.estimators.ApproximateStateActionValueEstimator --function-approximation-model rlai.q_S_A.function_approximation.models.sklearn.SKLearnSGD --verbose 1 --feature-extractor rlai.q_S_A.function_approximation.models.feature_extraction.StateActionIdentityFeatureExtractor --formula "C(s, levels={list(range(16))}):C(a, levels={list(range(4))})" --make-final-policy-greedy True --num-improvements-per-checkpoint 5 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_q_learning_with_patsy_formula.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_q_learning_with_patsy_formula.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_q_learning_with_state_action_interaction_feature_extractor():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --T 25 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 5 --num-episodes-per-improvement 50 --epsilon 0.05 --q-S-A rlai.q_S_A.function_approximation.estimators.ApproximateStateActionValueEstimator --function-approximation-model rlai.q_S_A.function_approximation.models.sklearn.SKLearnSGD --feature-extractor rlai.environments.gridworld.GridworldFeatureExtractor --make-final-policy-greedy True --num-improvements-per-checkpoint 5 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_q_learning_with_state_action_interaction_feature_extractor.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_q_learning_with_state_action_interaction_feature_extractor.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_sarsa_with_model_plots():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --T 25 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode SARSA --num-improvements 10 --num-episodes-per-improvement 50 --epsilon 0.05 --q-S-A rlai.q_S_A.function_approximation.estimators.ApproximateStateActionValueEstimator --plot-model --plot-model-bins 10 --function-approximation-model rlai.q_S_A.function_approximation.models.sklearn.SKLearnSGD --feature-extractor rlai.environments.gridworld.GridworldFeatureExtractor --make-final-policy-greedy True --num-improvements-per-checkpoint 5 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_sarsa_with_model_plots.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_sarsa_with_model_plots.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_continuous_action_discretization():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --continuous-state-discretization-resolution 0.005 --gamma 0.95 --environment rlai.environments.openai_gym.Gym --gym-id MountainCarContinuous-v0 --T 20 --continuous-action-discretization-resolution 0.1 --render-every-nth-episode 2 --video-directory {tempfile.TemporaryDirectory().name} --force --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode SARSA --num-improvements 2 --num-episodes-per-improvement 1 --epsilon 0.01 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True --num-improvements-per-plot 2 --num-improvements-per-checkpoint 2 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_continuous_action_discretization.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_continuous_action_discretization.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_gym_cartpole_function_approximation():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 0.95 --environment rlai.environments.openai_gym.Gym --gym-id CartPole-v1 --render-every-nth-episode 2 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode SARSA --num-improvements 2 --num-episodes-per-improvement 2 --num-updates-per-improvement 1 --epsilon 0.2 --q-S-A rlai.q_S_A.function_approximation.estimators.ApproximateStateActionValueEstimator --function-approximation-model rlai.q_S_A.function_approximation.models.sklearn.SKLearnSGD --loss squared_loss --sgd-alpha 0.0 --learning-rate constant --eta0 0.001 --feature-extractor rlai.environments.openai_gym.CartpoleFeatureExtractor --make-final-policy-greedy True --num-improvements-per-plot 2 --num-improvements-per-checkpoint 2 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_gym_cartpole_function_approximation.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_gym_cartpole_function_approximation.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_gym_cartpole_tabular():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --continuous-state-discretization-resolution 0.005 --gamma 0.95 --environment rlai.environments.openai_gym.Gym --gym-id CartPole-v1 --render-every-nth-episode 2 --train-function rlai.gpi.monte_carlo.iteration.iterate_value_q_pi --num-improvements 2 --num-episodes-per-improvement 2 --update-upon-every-visit True --epsilon 0.2 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True --num-improvements-per-plot 2 --num-improvements-per-checkpoint 2 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_gym_cartpole_tabular.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_gym_cartpole_tabular.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_gym_cartpole_function_approximation_plot_model():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 0.95 --environment rlai.environments.openai_gym.Gym --gym-id CartPole-v1 --render-every-nth-episode 2 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode SARSA --num-improvements 2 --num-episodes-per-improvement 2 --num-updates-per-improvement 1 --epsilon 0.2 --q-S-A rlai.q_S_A.function_approximation.estimators.ApproximateStateActionValueEstimator --plot-model --plot-model-bins 10 --function-approximation-model rlai.q_S_A.function_approximation.models.sklearn.SKLearnSGD --loss squared_loss --sgd-alpha 0.0 --learning-rate constant --eta0 0.001 --feature-extractor rlai.environments.openai_gym.CartpoleFeatureExtractor --make-final-policy-greedy True --num-improvements-per-plot 2 --num-improvements-per-checkpoint 2 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_gym_cartpole_function_approximation_plot_model.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_gym_cartpole_function_approximation_plot_model.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_gym_continuous_mountain_car():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 0.99 --environment rlai.environments.openai_gym.Gym --gym-id MountainCarContinuous-v0 --plot-environment --T 1000 --train-function rlai.policy_gradient.monte_carlo.reinforce.improve --num-episodes 2 --plot-state-value True --v-S rlai.v_S.function_approximation.estimators.ApproximateStateValueEstimator --feature-extractor rlai.environments.openai_gym.ContinuousMountainCarFeatureExtractor --function-approximation-model rlai.models.sklearn.SKLearnSGD --loss squared_loss --sgd-alpha 0.0 --learning-rate constant --eta0 0.01 --policy rlai.policies.parameterized.continuous_action.ContinuousActionBetaDistributionPolicy --policy-feature-extractor rlai.environments.openai_gym.ContinuousMountainCarFeatureExtractor --plot-policy --alpha 0.01 --update-upon-every-visit True --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --num-episodes-per-checkpoint 1 --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name} --log DEBUG'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_gym_continuous_mountain_car.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_gym_continuous_mountain_car.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_gridworld_plot_model_pdf():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --T 25 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode SARSA --num-improvements 10 --num-episodes-per-improvement 50 --epsilon 0.05 --q-S-A rlai.q_S_A.function_approximation.estimators.ApproximateStateActionValueEstimator --plot-model --function-approximation-model rlai.q_S_A.function_approximation.models.sklearn.SKLearnSGD --feature-extractor rlai.environments.gridworld.GridworldFeatureExtractor --make-final-policy-greedy True --num-improvements-per-checkpoint 5 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name} --pdf-save-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_gridworld_plot_model_pdf.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_gridworld_plot_model_pdf.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_scale_learning_rate_with_logging():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --T 25 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 5 --num-episodes-per-improvement 50 --epsilon 0.05 --q-S-A rlai.q_S_A.function_approximation.estimators.ApproximateStateActionValueEstimator --function-approximation-model rlai.q_S_A.function_approximation.models.sklearn.SKLearnSGD --scale-eta0-for-y --feature-extractor rlai.environments.gridworld.GridworldFeatureExtractor --make-final-policy-greedy True --num-improvements-per-checkpoint 5 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name} --log INFO'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_scale_learning_rate_with_logging.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_scale_learning_rate_with_logging.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_policy_gradient_reinforce_beta_with_baseline():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 0.99 --environment rlai.environments.openai_gym.Gym --gym-id LunarLanderContinuous-v2 --render-every-nth-episode 2 --plot-environment --T 2000 --train-function rlai.policy_gradient.monte_carlo.reinforce.improve --num-episodes 4 --v-S rlai.v_S.function_approximation.estimators.ApproximateStateValueEstimator --feature-extractor rlai.environments.openai_gym.ContinuousFeatureExtractor --function-approximation-model rlai.models.sklearn.SKLearnSGD --loss squared_loss --sgd-alpha 0.0 --learning-rate constant --eta0 0.00001 --policy rlai.policies.parameterized.continuous_action.ContinuousActionBetaDistributionPolicy --policy-feature-extractor rlai.environments.openai_gym.ContinuousFeatureExtractor --plot-policy --alpha 0.00001 --update-upon-every-visit True --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name} --log DEBUG'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_policy_gradient_reinforce_beta_with_baseline.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_policy_gradient_reinforce_beta_with_baseline.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_policy_gradient_reinforce_normal_with_baseline():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 0.99 --environment rlai.environments.openai_gym.Gym --gym-id LunarLanderContinuous-v2 --render-every-nth-episode 2 --steps-per-second 1000 --plot-environment --T 2000 --train-function rlai.policy_gradient.monte_carlo.reinforce.improve --num-episodes 4 --v-S rlai.v_S.function_approximation.estimators.ApproximateStateValueEstimator --feature-extractor rlai.environments.openai_gym.ContinuousFeatureExtractor --function-approximation-model rlai.models.sklearn.SKLearnSGD --loss squared_loss --sgd-alpha 0.0 --learning-rate constant --eta0 0.00001 --policy rlai.policies.parameterized.continuous_action.ContinuousActionNormalDistributionPolicy --policy-feature-extractor rlai.environments.openai_gym.ContinuousFeatureExtractor --plot-policy --alpha 0.00001 --update-upon-every-visit True --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_policy_gradient_reinforce_normal_with_baseline.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_policy_gradient_reinforce_normal_with_baseline.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_policy_gradient_reinforce_softmax_action_preferences_with_baseline():
start_virtual_display_if_headless()
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --train-function rlai.policy_gradient.monte_carlo.reinforce.improve --num-episodes 10 --v-S rlai.v_S.function_approximation.estimators.ApproximateStateValueEstimator --feature-extractor rlai.environments.gridworld.GridworldStateFeatureExtractor --function-approximation-model rlai.models.sklearn.SKLearnSGD --loss squared_loss --sgd-alpha 0.0 --learning-rate constant --eta0 0.001 --policy rlai.policies.parameterized.discrete_action.SoftMaxInActionPreferencesPolicy --policy-feature-extractor rlai.environments.gridworld.GridworldFeatureExtractor --alpha 0.001 --update-upon-every-visit False --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
checkpoint, agent = load_checkpoint_and_agent(checkpoint_path, agent_path)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_policy_gradient_reinforce_softmax_action_preferences_with_baseline.pickle', 'wb') as f:
# pickle.dump((checkpoint, agent), f)
with open(f'{os.path.dirname(__file__)}/fixtures/test_policy_gradient_reinforce_softmax_action_preferences_with_baseline.pickle', 'rb') as f:
checkpoint_fixture, agent_fixture = pickle.load(f)
assert_run(
checkpoint,
agent,
checkpoint_fixture,
agent_fixture
)
def test_missing_arguments():
run(shlex.split('--agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 10 --num-episodes-per-improvement 5 --epsilon 0.01 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True'))
def test_unparsed_arguments():
with pytest.raises(ValueError, match='Unparsed arguments'):
run(shlex.split('--agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 10 --num-episodes-per-improvement 5 --epsilon 0.01 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True --XXXX'))
def test_help():
with pytest.raises(ValueError, match='No training function specified. Cannot train.'):
run(shlex.split('--agent rlai.agents.mdp.StochasticMdpAgent --help'))
def test_resume():
checkpoint_path, agent_path = run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode Q_LEARNING --num-improvements 10 --num-episodes-per-improvement 5 --epsilon 0.01 --q-S-A rlai.q_S_A.tabular.TabularStateActionValueEstimator --make-final-policy-greedy True --num-improvements-per-checkpoint 10 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
_, resumed_agent_path = run(shlex.split(f'--resume --random-seed 12345 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --num-improvements 10 --checkpoint-path {checkpoint_path} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
with open(resumed_agent_path, 'rb') as f:
agent = pickle.load(f)
# uncomment the following line and run test to update fixture
# with open(f'{os.path.dirname(__file__)}/fixtures/test_resume.pickle', 'wb') as file:
# pickle.dump(agent, file)
with open(f'{os.path.dirname(__file__)}/fixtures/test_resume.pickle', 'rb') as file:
agent_fixture = pickle.load(file)
assert agent.pi == agent_fixture.pi
def test_too_many_coefficients_for_plot_model():
old_vals = (
rlai.q_S_A.function_approximation.models.MAX_PLOT_COEFFICIENTS,
rlai.q_S_A.function_approximation.models.MAX_PLOT_ACTIONS
)
rlai.q_S_A.function_approximation.models.MAX_PLOT_COEFFICIENTS = 2
rlai.q_S_A.function_approximation.models.MAX_PLOT_ACTIONS = 2
run(shlex.split(f'--random-seed 12345 --agent rlai.agents.mdp.StochasticMdpAgent --gamma 1 --environment rlai.environments.gridworld.Gridworld --id example_4_1 --T 25 --train-function rlai.gpi.temporal_difference.iteration.iterate_value_q_pi --mode SARSA --num-improvements 10 --num-episodes-per-improvement 50 --epsilon 0.05 --q-S-A rlai.q_S_A.function_approximation.estimators.ApproximateStateActionValueEstimator --plot-model --plot-model-bins 10 --function-approximation-model rlai.q_S_A.function_approximation.models.sklearn.SKLearnSGD --feature-extractor rlai.environments.gridworld.GridworldFeatureExtractor --make-final-policy-greedy True --num-improvements-per-checkpoint 5 --checkpoint-path {tempfile.NamedTemporaryFile(delete=False).name} --save-agent-path {tempfile.NamedTemporaryFile(delete=False).name}'))
(
rlai.q_S_A.function_approximation.models.MAX_PLOT_COEFFICIENTS,
rlai.q_S_A.function_approximation.models.MAX_PLOT_ACTIONS
) = old_vals
def assert_run(
checkpoint: Dict,
agent: Any,
checkpoint_fixture: Dict,
agent_fixture: Any
):
"""
Assert test run.
:param checkpoint: Checkpoint.
:param agent: Agent.
:param checkpoint_fixture: Checkpoint fixture.
:param agent_fixture: Agent fixture.
"""
if isinstance(agent.pi, TabularPolicy):
assert checkpoint['q_S_A'] == checkpoint_fixture['q_S_A']
assert agent.pi == agent_fixture.pi
else:
assert agent.pi == agent_fixture.pi
def load_checkpoint_and_agent(
checkpoint_path: str,
agent_path: str
) -> Tuple[Dict, Any]:
"""
Load a checkpoint and agent from paths.
:param checkpoint_path: Checkpoint path.
:param agent_path: Agent path.
:return: 2-tuple of checkpoint dictionary and agent object.
"""
if checkpoint_path is None:
checkpoint = None
else:
with open(checkpoint_path, 'rb') as f:
checkpoint = pickle.load(f)
with open(agent_path, 'rb') as f:
agent = pickle.load(f)
return checkpoint, agent
| 63.251984
| 1,074
| 0.770288
| 4,165
| 31,879
| 5.663625
| 0.059544
| 0.023274
| 0.006613
| 0.056467
| 0.927678
| 0.916275
| 0.907838
| 0.892535
| 0.886388
| 0.881089
| 0
| 0.015653
| 0.116221
| 31,879
| 503
| 1,075
| 63.377734
| 0.821609
| 0.129239
| 0
| 0.554717
| 0
| 0.083019
| 0.650342
| 0.448475
| 0
| 0
| 0
| 0
| 0.083019
| 1
| 0.090566
| false
| 0
| 0.037736
| 0
| 0.132075
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
8523e9a38ecf8efa9f5c1122024f14a1d91b1876
| 339
|
py
|
Python
|
RecoTracker/TkSeedingLayers/python/TTRHBuilderWithoutAngle4MixedTriplets_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 852
|
2015-01-11T21:03:51.000Z
|
2022-03-25T21:14:00.000Z
|
RecoTracker/TkSeedingLayers/python/TTRHBuilderWithoutAngle4MixedTriplets_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 30,371
|
2015-01-02T00:14:40.000Z
|
2022-03-31T23:26:05.000Z
|
RecoTracker/TkSeedingLayers/python/TTRHBuilderWithoutAngle4MixedTriplets_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 3,240
|
2015-01-02T05:53:18.000Z
|
2022-03-31T17:24:21.000Z
|
import FWCore.ParameterSet.Config as cms
import RecoTracker.TransientTrackingRecHit.TransientTrackingRecHitBuilder_cfi
myTTRHBuilderWithoutAngle4MixedTriplets = RecoTracker.TransientTrackingRecHit.TransientTrackingRecHitBuilder_cfi.ttrhbwr.clone(
StripCPE = 'Fake',
ComponentName = 'TTRHBuilderWithoutAngle4MixedTriplets'
)
| 42.375
| 127
| 0.855457
| 22
| 339
| 13.090909
| 0.772727
| 0.236111
| 0.444444
| 0.465278
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006494
| 0.091445
| 339
| 7
| 128
| 48.428571
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0.120944
| 0.109145
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 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
| 0
| 0
|
0
| 7
|
51cc73bc3c91e5873f821266201c3c8b5399ad97
| 137,508
|
py
|
Python
|
Hello_world.py
|
Palmen98/MicroPythonOTA
|
df7a6c47fae989a3ef4a6b82feddabeb7e336496
|
[
"MIT"
] | null | null | null |
Hello_world.py
|
Palmen98/MicroPythonOTA
|
df7a6c47fae989a3ef4a6b82feddabeb7e336496
|
[
"MIT"
] | null | null | null |
Hello_world.py
|
Palmen98/MicroPythonOTA
|
df7a6c47fae989a3ef4a6b82feddabeb7e336496
|
[
"MIT"
] | null | null | null |
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| 20.996793
| 20
| 0.714286
| 19,644
| 137,508
| 5
| 0.000153
| 0.666667
| 1
| 1.33313
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0.095238
| 137,508
| 6,548
| 21
| 21
| 0.789474
| 0
| 0
| 1
| 0
| 0
| 0.52381
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 1
| 1
| 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
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 12
|
51d0b91f2fce7855545b73a4e40cb448a3cd983b
| 2,530
|
py
|
Python
|
python/cp2_code/tests_cp2_server.py
|
ntpdrop/ieeesp2021
|
084ac380774351cb032e9c1f48c5c6f7b58372fa
|
[
"MIT"
] | null | null | null |
python/cp2_code/tests_cp2_server.py
|
ntpdrop/ieeesp2021
|
084ac380774351cb032e9c1f48c5c6f7b58372fa
|
[
"MIT"
] | null | null | null |
python/cp2_code/tests_cp2_server.py
|
ntpdrop/ieeesp2021
|
084ac380774351cb032e9c1f48c5c6f7b58372fa
|
[
"MIT"
] | null | null | null |
import unittest
from cp2_common_secret import CP2_ZERO_BITS, CP2_ONE_BITS
from cp2_server import CP2Server
class CP2ServerTests(unittest.TestCase):
def test_set_current_stratum_is_first_0_value_set_accordingly(self):
# Arrange
server = CP2Server('', '')
server.payload_bits = '0'
# Act
server.set_current_stratum()
# Assert
self.assertEqual(CP2_ZERO_BITS[0], server.current_stratum)
def test_set_current_stratum_is_first_1_value_set_accordingly(self):
# Arrange
server = CP2Server('', '')
server.payload_bits = '1'
# Act
server.set_current_stratum()
# Assert
self.assertEqual(CP2_ONE_BITS[0], server.current_stratum)
def test_set_current_stratum_overflow_value_set_accordingly(self):
# Arrange
server = CP2Server('', '')
server.payload_bits = '011'
# Act
server.set_current_stratum()
server.set_current_stratum()
server.set_current_stratum()
server.set_current_stratum()
# Assert
self.assertEqual(CP2_ZERO_BITS[0], server.current_stratum)
def test_set_current_stratum_zero_toogle_set_accordingly(self):
# Arrange
server = CP2Server('', '')
server.payload_bits = '00'
# Act
server.set_current_stratum()
server.set_current_stratum()
# Assert
self.assertEqual(CP2_ZERO_BITS[1], server.current_stratum)
def test_set_current_stratum_one_toogle_set_accordingly(self):
# Arrange
server = CP2Server('', '')
server.payload_bits = '11'
# Act
server.set_current_stratum()
server.set_current_stratum()
# Assert
self.assertEqual(CP2_ONE_BITS[1], server.current_stratum)
def test_set_current_stratum_one_different_set_accordingly(self):
# Arrange
server = CP2Server('', '')
server.payload_bits = '01'
# Act
server.set_current_stratum()
server.set_current_stratum()
# Assert
self.assertEqual(CP2_ONE_BITS[0], server.current_stratum)
def test_set_current_stratum_zero_different_set_accordingly(self):
# Arrange
server = CP2Server('', '')
server.payload_bits = '10'
# Act
server.set_current_stratum()
server.set_current_stratum()
# Assert
self.assertEqual(CP2_ZERO_BITS[0], server.current_stratum)
if __name__ == '__main__':
unittest.main()
| 26.354167
| 72
| 0.649407
| 283
| 2,530
| 5.367491
| 0.14841
| 0.258065
| 0.235023
| 0.211982
| 0.889401
| 0.889401
| 0.889401
| 0.864384
| 0.864384
| 0.85846
| 0
| 0.022424
| 0.259684
| 2,530
| 95
| 73
| 26.631579
| 0.788574
| 0.052174
| 0
| 0.541667
| 0
| 0
| 0.008838
| 0
| 0
| 0
| 0
| 0
| 0.145833
| 1
| 0.145833
| false
| 0
| 0.0625
| 0
| 0.229167
| 0
| 0
| 0
| 0
| null | 1
| 1
| 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
| 9
|
a405328398fcd8cc194394783f9a4e87a9bbb28a
| 3,015
|
py
|
Python
|
oxe-api/test/resource/workforce/test_add_workforce.py
|
CybersecurityLuxembourg/openxeco
|
8d4e5578bde6a07f5d6d569b16b4de224abf7bf0
|
[
"BSD-2-Clause"
] | null | null | null |
oxe-api/test/resource/workforce/test_add_workforce.py
|
CybersecurityLuxembourg/openxeco
|
8d4e5578bde6a07f5d6d569b16b4de224abf7bf0
|
[
"BSD-2-Clause"
] | null | null | null |
oxe-api/test/resource/workforce/test_add_workforce.py
|
CybersecurityLuxembourg/openxeco
|
8d4e5578bde6a07f5d6d569b16b4de224abf7bf0
|
[
"BSD-2-Clause"
] | null | null | null |
from test.BaseCase import BaseCase
class TestAddWorkforce(BaseCase):
@BaseCase.login
@BaseCase.grant_access("/workforce/add_workforce")
def test_ok(self, token):
self.db.insert({"name": "Newspaper"}, self.db.tables["Source"])
self.db.insert({"id": 1, "name": "Company1"}, self.db.tables["Company"])
payload = {
"company": 1,
"workforce": 15,
"date": "2020-01-01",
"is_estimated": True,
"source": "Newspaper",
}
response = self.application.post('/workforce/add_workforce',
headers=self.get_standard_post_header(token),
json=payload)
self.assertEqual(200, response.status_code)
self.assertEqual(self.db.get_count(self.db.tables["Workforce"]), 1)
@BaseCase.login
@BaseCase.grant_access("/workforce/add_workforce")
def test_ko_missing_company(self, token):
self.db.insert({"name": "Newspaper"}, self.db.tables["Source"])
payload = {
"company": 1,
"workforce": 15,
"date": "2020-01-01",
"is_estimated": True,
"source": "Newspaper",
}
response = self.application.post('/workforce/add_workforce',
headers=self.get_standard_post_header(token),
json=payload)
self.assertEqual(422, response.status_code)
self.assertEqual("422 Provided company not existing", response.status)
@BaseCase.login
@BaseCase.grant_access("/workforce/add_workforce")
def test_ko_missing_source(self, token):
self.db.insert({"id": 1, "name": "Company1"}, self.db.tables["Company"])
payload = {
"company": 1,
"workforce": 15,
"date": "2020-01-01",
"is_estimated": True,
"source": "Newspaper",
}
response = self.application.post('/workforce/add_workforce',
headers=self.get_standard_post_header(token),
json=payload)
self.assertEqual(422, response.status_code)
self.assertEqual("422 Provided source not existing", response.status)
@BaseCase.login
@BaseCase.grant_access("/workforce/add_workforce")
def test_ko_wrong_date_format(self, token):
payload = {
"company": 1,
"workforce": 15,
"date": "202a-01-01",
"is_estimated": True,
"source": "Newspaper",
}
response = self.application.post('/workforce/add_workforce',
headers=self.get_standard_post_header(token),
json=payload)
self.assertEqual(422, response.status_code)
self.assertEqual("422 Provided date does not have the right format (expected: YYYY-mm-dd)", response.status)
| 35.892857
| 116
| 0.549917
| 297
| 3,015
| 5.434343
| 0.212121
| 0.037175
| 0.104089
| 0.064436
| 0.86803
| 0.842007
| 0.82342
| 0.82342
| 0.82342
| 0.82342
| 0
| 0.033857
| 0.324046
| 3,015
| 83
| 117
| 36.325301
| 0.758096
| 0
| 0
| 0.757576
| 0
| 0
| 0.21393
| 0.063682
| 0
| 0
| 0
| 0
| 0.121212
| 1
| 0.060606
| false
| 0
| 0.015152
| 0
| 0.090909
| 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
|
cfe18b6dbeb8a30d29736a43eca5136d6a41b126
| 94
|
py
|
Python
|
summarization/model/__init__.py
|
houshengyuan/MAN
|
03912e80b21e0fc40c36515b6893d4244b82e6b6
|
[
"MIT"
] | 8
|
2021-06-03T08:55:05.000Z
|
2022-03-28T19:50:27.000Z
|
summarization/model/__init__.py
|
houshengyuan/MAN
|
03912e80b21e0fc40c36515b6893d4244b82e6b6
|
[
"MIT"
] | 1
|
2022-01-15T10:07:20.000Z
|
2022-01-15T10:07:20.000Z
|
summarization/model/__init__.py
|
houshengyuan/MAN
|
03912e80b21e0fc40c36515b6893d4244b82e6b6
|
[
"MIT"
] | 3
|
2021-06-12T03:11:36.000Z
|
2021-09-18T12:38:29.000Z
|
from . import masked_s2s
from . import man
from . import translation
from . import masked_lm2
| 18.8
| 25
| 0.787234
| 14
| 94
| 5.142857
| 0.5
| 0.555556
| 0.444444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025641
| 0.170213
| 94
| 4
| 26
| 23.5
| 0.897436
| 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
|
5c4dffc1082cc37a87c0020f233cf563ab3cfd78
| 3,665
|
py
|
Python
|
electrical_systems_model/core/power.py
|
kyleoliver22/electrical-systems-model
|
41b0e4e14bb7733b6cba54212dc667095c8ff98b
|
[
"MIT"
] | null | null | null |
electrical_systems_model/core/power.py
|
kyleoliver22/electrical-systems-model
|
41b0e4e14bb7733b6cba54212dc667095c8ff98b
|
[
"MIT"
] | null | null | null |
electrical_systems_model/core/power.py
|
kyleoliver22/electrical-systems-model
|
41b0e4e14bb7733b6cba54212dc667095c8ff98b
|
[
"MIT"
] | 1
|
2021-08-09T21:01:23.000Z
|
2021-08-09T21:01:23.000Z
|
import copy
from abc import ABC, abstractmethod
import numpy
class PowerInterface(ABC):
@abstractmethod
def add(self, power):
pass
@abstractmethod
def apply_efficiency_loss(self, efficiency):
pass
def copy(self):
return copy.copy(self)
class SinglePhaseElectricalPower(PowerInterface):
# TODO: refactor to include phase switch to eliminate repeating ourselves
# this would include phase (int) in arguments for creation
# and would require additional handling in __init__, add, and resistance_loss methods
def __init__(self, power, voltage, frequency, power_factor):
self.voltage = voltage
self.frequency = frequency
self.power_factor = power_factor
phase_quadrant = power_factor / abs(power_factor)
real_power = power * power_factor / phase_quadrant
imag_power = numpy.sqrt(power**2 - real_power**2) * phase_quadrant
self.power = complex(real_power, imag_power)
self.current = abs(self.power) / self.voltage
def add(self, power):
self.power = self.power + power.power
self.power_factor = self.power.real / abs(self.power)
self.current = abs(self.power) / (numpy.sqrt(3) * self.voltage)
def apply_efficiency_loss(self, efficiency):
self.power = self.power / efficiency
def apply_resistance_loss(self, resistance):
self.current = abs(self.power) / (numpy.sqrt(3) * self.voltage)
current_phase = self.current
loss_phase = current_phase**2 * resistance
power_loss = loss_phase
self.power = self.power + power_loss
class ThreePhaseElectricalPower(PowerInterface):
# TODO: refactor to include phase switch to eliminate repeating ourselves
# this would include phase (int) in arguments for creation
# and would require additional handling in __init__, add, and resistance_loss methods
def __init__(self, power, voltage, frequency, power_factor):
self.voltage = voltage
self.frequency = frequency
self.power_factor = power_factor
phase_quadrant = power_factor / abs(power_factor)
real_power = power * power_factor / phase_quadrant
imag_power = numpy.sqrt(power**2 - real_power**2) * phase_quadrant
self.power = complex(real_power, imag_power)
self.current = abs(self.power) / (numpy.sqrt(3) * self.voltage)
def add(self, power):
self.power = self.power + power.power
self.power_factor = self.power.real / abs(self.power)
self.current = abs(self.power) / (numpy.sqrt(3) * self.voltage)
def apply_efficiency_loss(self, efficiency):
self.power = self.power / efficiency
def apply_resistance_loss(self, resistance):
self.current = abs(self.power) / (numpy.sqrt(3) * self.voltage)
current_phase = self.current / numpy.sqrt(3)
loss_phase = current_phase**2 * resistance
power_loss = 3 * loss_phase
self.power = self.power + power_loss
class DirectElectricalPower(PowerInterface):
# TODO: implement this class
def __init__(self, power, voltage):
self.power = power
self.voltage = voltage
self.current = self.power / self.voltage
def add(self, power):
pass
def apply_efficiency_loss(self, efficiency):
self.power = self.power / efficiency
class MechanicalPower(PowerInterface):
# TODO: implement this class
def __init__(self, power, rpm):
self.power = power
self.rpm = rpm
def add(self, power):
pass
def apply_efficiency_loss(self, efficiency):
self.power = self.power / efficiency
| 34.904762
| 89
| 0.677217
| 450
| 3,665
| 5.333333
| 0.128889
| 0.165
| 0.075833
| 0.075
| 0.87
| 0.859167
| 0.844167
| 0.844167
| 0.801667
| 0.724167
| 0
| 0.00463
| 0.233834
| 3,665
| 104
| 90
| 35.240385
| 0.850071
| 0.130696
| 0
| 0.739726
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009615
| 0
| 1
| 0.232877
| false
| 0.054795
| 0.041096
| 0.013699
| 0.356164
| 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
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 9
|
7a3e855309503b00ebe190a9a5cc967a7f76a968
| 26,682
|
py
|
Python
|
src/models/sed_models.py
|
Sarajvega/kaggle-birdsong-recognition
|
cbe1c8b59d03a1ac210439fef6045ce4e57235dd
|
[
"MIT"
] | 137
|
2020-09-17T16:36:28.000Z
|
2022-03-23T23:54:09.000Z
|
src/models/sed_models.py
|
Sarajvega/kaggle-birdsong-recognition
|
cbe1c8b59d03a1ac210439fef6045ce4e57235dd
|
[
"MIT"
] | 3
|
2020-09-18T07:42:37.000Z
|
2021-07-19T22:37:38.000Z
|
src/models/sed_models.py
|
Sarajvega/kaggle-birdsong-recognition
|
cbe1c8b59d03a1ac210439fef6045ce4e57235dd
|
[
"MIT"
] | 38
|
2020-09-20T07:24:07.000Z
|
2022-03-14T03:06:18.000Z
|
'''
The MIT License
Copyright (c) 2018-2020 Qiuqiang Kong
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.models as models
from augmentations.mixup import do_mixup
def init_layer(layer):
nn.init.xavier_uniform_(layer.weight)
if hasattr(layer, "bias"):
if layer.bias is not None:
layer.bias.data.fill_(0.)
def init_bn(bn):
bn.bias.data.fill_(0.)
bn.weight.data.fill_(1.0)
def interpolate(x: torch.Tensor, ratio: int):
"""Interpolate data in time domain. This is used to compensate the
resolution reduction in downsampling of a CNN.
Args:
x: (batch_size, time_steps, classes_num)
ratio: int, ratio to interpolate
Returns:
upsampled: (batch_size, time_steps * ratio, classes_num)
"""
(batch_size, time_steps, classes_num) = x.shape
upsampled = x[:, :, None, :].repeat(1, 1, ratio, 1)
upsampled = upsampled.reshape(batch_size, time_steps * ratio, classes_num)
return upsampled
def pad_framewise_output(framewise_output: torch.Tensor, frames_num: int):
"""Pad framewise_output to the same length as input frames. The pad value
is the same as the value of the last frame.
Args:
framewise_output: (batch_size, frames_num, classes_num)
frames_num: int, number of frames to pad
Outputs:
output: (batch_size, frames_num, classes_num)
"""
pad = framewise_output[:, -1:, :].repeat(
1, frames_num - framewise_output.shape[1], 1)
"""tensor for padding"""
output = torch.cat((framewise_output, pad), dim=1)
"""(batch_size, frames_num, classes_num)"""
return output
class ConvBlock(nn.Module):
def __init__(self, in_channels: int, out_channels: int):
super().__init__()
self.conv1 = nn.Conv2d(
in_channels=in_channels,
out_channels=out_channels,
kernel_size=(3, 3),
stride=(1, 1),
padding=(1, 1),
bias=False)
self.conv2 = nn.Conv2d(
in_channels=out_channels,
out_channels=out_channels,
kernel_size=(3, 3),
stride=(1, 1),
padding=(1, 1),
bias=False)
self.bn1 = nn.BatchNorm2d(out_channels)
self.bn2 = nn.BatchNorm2d(out_channels)
self.init_weight()
def init_weight(self):
init_layer(self.conv1)
init_layer(self.conv2)
init_bn(self.bn1)
init_bn(self.bn2)
def forward(self, input, pool_size=(2, 2), pool_type='avg'):
x = input
x = F.relu_(self.bn1(self.conv1(x)))
x = F.relu_(self.bn2(self.conv2(x)))
if pool_type == 'max':
x = F.max_pool2d(x, kernel_size=pool_size)
elif pool_type == 'avg':
x = F.avg_pool2d(x, kernel_size=pool_size)
elif pool_type == 'avg+max':
x1 = F.avg_pool2d(x, kernel_size=pool_size)
x2 = F.max_pool2d(x, kernel_size=pool_size)
x = x1 + x2
else:
raise Exception('Incorrect argument!')
return x
class AttBlock(nn.Module):
def __init__(self,
in_features: int,
out_features: int,
activation="linear",
temperature=1.0):
super().__init__()
self.activation = activation
self.temperature = temperature
self.att = nn.Conv1d(
in_channels=in_features,
out_channels=out_features,
kernel_size=1,
stride=1,
padding=0,
bias=True)
self.cla = nn.Conv1d(
in_channels=in_features,
out_channels=out_features,
kernel_size=1,
stride=1,
padding=0,
bias=True)
self.bn_att = nn.BatchNorm1d(out_features)
self.init_weights()
def init_weights(self):
init_layer(self.att)
init_layer(self.cla)
init_bn(self.bn_att)
def forward(self, x):
# x: (n_samples, n_in, n_time)
norm_att = torch.softmax(torch.tanh(self.att(x)), dim=-1)
cla = self.nonlinear_transform(self.cla(x))
x = torch.sum(norm_att * cla, dim=2)
return x, norm_att, cla
def nonlinear_transform(self, x):
if self.activation == 'linear':
return x
elif self.activation == 'sigmoid':
return torch.sigmoid(x)
from helpers.sed_audio_utils import *
class PANNsCNN14Att(nn.Module):
def __init__(self, sample_rate: int, window_size: int, hop_size: int,
mel_bins: int, fmin: int, fmax: int, classes_num: int, apply_aug: bool):
super().__init__()
window = 'hann'
center = True
pad_mode = 'reflect'
ref = 1.0
amin = 1e-10
top_db = None
self.interpolate_ratio = 32 # Downsampled ratio
self.apply_aug = apply_aug
# Spectrogram extractor
self.spectrogram_extractor = Spectrogram(
n_fft=window_size,
hop_length=hop_size,
win_length=window_size,
window=window,
center=center,
pad_mode=pad_mode,
freeze_parameters=True)
# Logmel feature extractor
self.logmel_extractor = LogmelFilterBank(
sr=sample_rate,
n_fft=window_size,
n_mels=mel_bins,
fmin=fmin,
fmax=fmax,
ref=ref,
amin=amin,
top_db=top_db,
freeze_parameters=True)
# Spec augmenter
self.spec_augmenter = SpecAugmentation(
time_drop_width=64,
time_stripes_num=2,
freq_drop_width=8,
freq_stripes_num=2)
self.bn0 = nn.BatchNorm2d(mel_bins)
self.conv_block1 = ConvBlock(in_channels=1, out_channels=64)
self.conv_block2 = ConvBlock(in_channels=64, out_channels=128)
self.conv_block3 = ConvBlock(in_channels=128, out_channels=256)
self.conv_block4 = ConvBlock(in_channels=256, out_channels=512)
self.conv_block5 = ConvBlock(in_channels=512, out_channels=1024)
# self.conv_block6 = ConvBlock(in_channels=1024, out_channels=2048)
self.fc1 = nn.Linear(1024, 1024, bias=True)
self.att_block = AttBlock(1024, classes_num, activation='sigmoid')
self.init_weight()
def init_weight(self):
init_bn(self.bn0)
init_layer(self.fc1)
def cnn_feature_extractor(self, x):
x = self.conv_block1(x, pool_size=(2, 2), pool_type='avg')
x = F.dropout(x, p=0.2, training=self.training)
x = self.conv_block2(x, pool_size=(2, 2), pool_type='avg')
x = F.dropout(x, p=0.2, training=self.training)
x = self.conv_block3(x, pool_size=(2, 2), pool_type='avg')
x = F.dropout(x, p=0.2, training=self.training)
x = self.conv_block4(x, pool_size=(2, 2), pool_type='avg')
x = F.dropout(x, p=0.2, training=self.training)
x = self.conv_block5(x, pool_size=(2, 2), pool_type='avg')
x = F.dropout(x, p=0.2, training=self.training)
# x = self.conv_block6(x, pool_size=(1, 1), pool_type='avg')
# x = F.dropout(x, p=0.2, training=self.training)
return x
def preprocess(self, input_x, mixup_lambda=None):
x = self.spectrogram_extractor(input_x) # (batch_size, 1, time_steps, freq_bins)
x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins)
frames_num = x.shape[2]
x = x.transpose(1, 3)
x = self.bn0(x)
x = x.transpose(1, 3)
if self.training and self.apply_aug:
x = self.spec_augmenter(x)
# Mixup on spectrogram
if self.training and self.apply_aug and mixup_lambda is not None:
x = do_mixup(x, mixup_lambda)
return x, frames_num
def forward(self, input_data):
input_x, mixup_lambda = input_data
"""
Input: (batch_size, data_length)"""
b, c, s = input_x.shape
input_x = input_x.reshape(b*c, s)
x, frames_num = self.preprocess(input_x, mixup_lambda=mixup_lambda)
if mixup_lambda is not None:
b = (b*c)//2
c = 1
# Output shape (batch size, channels, time, frequency)
x = self.cnn_feature_extractor(x)
# Aggregate in frequency axis
x = torch.mean(x, dim=3)
x1 = F.max_pool1d(x, kernel_size=3, stride=1, padding=1)
x2 = F.avg_pool1d(x, kernel_size=3, stride=1, padding=1)
x = x1 + x2
x = F.dropout(x, p=0.5, training=self.training)
x = x.transpose(1, 2)
x = F.relu_(self.fc1(x))
x = x.transpose(1, 2)
x = F.dropout(x, p=0.5, training=self.training)
(clipwise_output, norm_att, segmentwise_output) = self.att_block(x)
segmentwise_output = segmentwise_output.transpose(1, 2)
# Get framewise output
framewise_output = interpolate(segmentwise_output,
self.interpolate_ratio)
framewise_output = pad_framewise_output(framewise_output, frames_num)
frame_shape = framewise_output.shape
clip_shape = clipwise_output.shape
output_dict = {
'framewise_output': framewise_output.reshape(b, c, frame_shape[1],frame_shape[2]),
'clipwise_output': clipwise_output.reshape(b, c, clip_shape[1]),
}
return output_dict
class PANNsDense121Att(nn.Module):
def __init__(self, sample_rate: int, window_size: int, hop_size: int,
mel_bins: int, fmin: int, fmax: int, classes_num: int, apply_aug: bool, top_db=None):
super().__init__()
window = 'hann'
center = True
pad_mode = 'reflect'
ref = 1.0
amin = 1e-10
self.interpolate_ratio = 32 # Downsampled ratio
self.apply_aug = apply_aug
# Spectrogram extractor
self.spectrogram_extractor = Spectrogram(
n_fft=window_size,
hop_length=hop_size,
win_length=window_size,
window=window,
center=center,
pad_mode=pad_mode,
freeze_parameters=True)
# Logmel feature extractor
self.logmel_extractor = LogmelFilterBank(
sr=sample_rate,
n_fft=window_size,
n_mels=mel_bins,
fmin=fmin,
fmax=fmax,
ref=ref,
amin=amin,
top_db=top_db,
freeze_parameters=True)
# Spec augmenter
self.spec_augmenter = SpecAugmentation(
time_drop_width=64,
time_stripes_num=2,
freq_drop_width=8,
freq_stripes_num=2)
self.bn0 = nn.BatchNorm2d(mel_bins)
self.fc1 = nn.Linear(1024, 1024, bias=True)
self.att_block = AttBlock(1024, classes_num, activation='sigmoid')
self.densenet_features = models.densenet121(pretrained=True).features
self.init_weight()
def init_weight(self):
init_bn(self.bn0)
init_layer(self.fc1)
def cnn_feature_extractor(self, x):
x = self.densenet_features(x)
return x
def preprocess(self, input_x, mixup_lambda=None):
x = self.spectrogram_extractor(input_x) # (batch_size, 1, time_steps, freq_bins)
x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins)
frames_num = x.shape[2]
x = x.transpose(1, 3)
x = self.bn0(x)
x = x.transpose(1, 3)
if self.training and self.apply_aug:
x = self.spec_augmenter(x)
# Mixup on spectrogram
if self.training and self.apply_aug and mixup_lambda is not None:
x = do_mixup(x, mixup_lambda)
return x, frames_num
def forward(self, input_data):
input_x, mixup_lambda = input_data
"""
Input: (batch_size, data_length)"""
b, c, s = input_x.shape
input_x = input_x.reshape(b*c, s)
x, frames_num = self.preprocess(input_x, mixup_lambda=mixup_lambda)
if mixup_lambda is not None:
b = (b*c)//2
c = 1
# Output shape (batch size, channels, time, frequency)
x = x.expand(x.shape[0], 3, x.shape[2], x.shape[3])
x = self.cnn_feature_extractor(x)
# Aggregate in frequency axis
x = torch.mean(x, dim=3)
x1 = F.max_pool1d(x, kernel_size=3, stride=1, padding=1)
x2 = F.avg_pool1d(x, kernel_size=3, stride=1, padding=1)
x = x1 + x2
x = F.dropout(x, p=0.5, training=self.training)
x = x.transpose(1, 2)
x = F.relu_(self.fc1(x))
x = x.transpose(1, 2)
x = F.dropout(x, p=0.5, training=self.training)
(clipwise_output, norm_att, segmentwise_output) = self.att_block(x)
segmentwise_output = segmentwise_output.transpose(1, 2)
# Get framewise output
framewise_output = interpolate(segmentwise_output,
self.interpolate_ratio)
framewise_output = pad_framewise_output(framewise_output, frames_num)
frame_shape = framewise_output.shape
clip_shape = clipwise_output.shape
output_dict = {
'framewise_output': framewise_output.reshape(b, c, frame_shape[1],frame_shape[2]),
'clipwise_output': clipwise_output.reshape(b, c, clip_shape[1]),
}
return output_dict
class PANNsDense161Att(nn.Module):
def __init__(self, sample_rate: int, window_size: int, hop_size: int,
mel_bins: int, fmin: int, fmax: int, classes_num: int, apply_aug: bool, top_db=None):
super().__init__()
window = 'hann'
center = True
pad_mode = 'reflect'
ref = 1.0
amin = 1e-10
self.interpolate_ratio = 32 # Downsampled ratio
self.apply_aug = apply_aug
# Spectrogram extractor
self.spectrogram_extractor = Spectrogram(
n_fft=window_size,
hop_length=hop_size,
win_length=window_size,
window=window,
center=center,
pad_mode=pad_mode,
freeze_parameters=True)
# Logmel feature extractor
self.logmel_extractor = LogmelFilterBank(
sr=sample_rate,
n_fft=window_size,
n_mels=mel_bins,
fmin=fmin,
fmax=fmax,
ref=ref,
amin=amin,
top_db=top_db,
freeze_parameters=True)
# Spec augmenter
self.spec_augmenter = SpecAugmentation(
time_drop_width=64,
time_stripes_num=2,
freq_drop_width=8,
freq_stripes_num=2)
self.bn0 = nn.BatchNorm2d(mel_bins)
self.fc1 = nn.Linear(2208, 2048, bias=True)
self.att_block = AttBlock(2048, classes_num, activation='sigmoid')
self.init_weight()
self.densenet_features = models.densenet161(pretrained=True).features
def init_weight(self):
init_bn(self.bn0)
init_layer(self.fc1)
def cnn_feature_extractor(self, x):
x = self.densenet_features(x)
return x
def preprocess(self, input_x, mixup_lambda=None):
x = self.spectrogram_extractor(input_x) # (batch_size, 1, time_steps, freq_bins)
x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins)
frames_num = x.shape[2]
x = x.transpose(1, 3)
x = self.bn0(x)
x = x.transpose(1, 3)
if self.training and self.apply_aug:
x = self.spec_augmenter(x)
# Mixup on spectrogram
if self.training and self.apply_aug and mixup_lambda is not None:
x = do_mixup(x, mixup_lambda)
return x, frames_num
def forward(self, input_data):
input_x, mixup_lambda = input_data
"""
Input: (batch_size, data_length)"""
b, c, s = input_x.shape
input_x = input_x.reshape(b*c, s)
x, frames_num = self.preprocess(input_x, mixup_lambda=mixup_lambda)
if mixup_lambda is not None:
b = (b*c)//2
c = 1
# Output shape (batch size, channels, time, frequency)
x = x.expand(x.shape[0], 3, x.shape[2], x.shape[3])
x = self.cnn_feature_extractor(x)
# Aggregate in frequency axis
x = torch.mean(x, dim=3)
x1 = F.max_pool1d(x, kernel_size=3, stride=1, padding=1)
x2 = F.avg_pool1d(x, kernel_size=3, stride=1, padding=1)
x = x1 + x2
x = F.dropout(x, p=0.5, training=self.training)
x = x.transpose(1, 2)
x = F.relu_(self.fc1(x))
x = x.transpose(1, 2)
x = F.dropout(x, p=0.5, training=self.training)
(clipwise_output, norm_att, segmentwise_output) = self.att_block(x)
segmentwise_output = segmentwise_output.transpose(1, 2)
# Get framewise output
framewise_output = interpolate(segmentwise_output,
self.interpolate_ratio)
framewise_output = pad_framewise_output(framewise_output, frames_num)
frame_shape = framewise_output.shape
clip_shape = clipwise_output.shape
output_dict = {
'framewise_output': framewise_output.reshape(b, c, frame_shape[1],frame_shape[2]),
'clipwise_output': clipwise_output.reshape(b, c, clip_shape[1]),
}
return output_dict
class PANNsDense169Att(nn.Module):
def __init__(self, sample_rate: int, window_size: int, hop_size: int,
mel_bins: int, fmin: int, fmax: int, classes_num: int, apply_aug: bool, top_db=None):
super().__init__()
window = 'hann'
center = True
pad_mode = 'reflect'
ref = 1.0
amin = 1e-10
self.interpolate_ratio = 32 # Downsampled ratio
self.apply_aug = apply_aug
# Spectrogram extractor
self.spectrogram_extractor = Spectrogram(
n_fft=window_size,
hop_length=hop_size,
win_length=window_size,
window=window,
center=center,
pad_mode=pad_mode,
freeze_parameters=True)
# Logmel feature extractor
self.logmel_extractor = LogmelFilterBank(
sr=sample_rate,
n_fft=window_size,
n_mels=mel_bins,
fmin=fmin,
fmax=fmax,
ref=ref,
amin=amin,
top_db=top_db,
freeze_parameters=True)
# Spec augmenter
self.spec_augmenter = SpecAugmentation(
time_drop_width=64,
time_stripes_num=2,
freq_drop_width=8,
freq_stripes_num=2)
self.bn0 = nn.BatchNorm2d(mel_bins)
self.fc1 = nn.Linear(1664, 1024, bias=True)
self.att_block = AttBlock(1024, classes_num, activation='sigmoid')
self.init_weight()
self.densenet_features = models.densenet169(pretrained=True).features
def init_weight(self):
init_bn(self.bn0)
init_layer(self.fc1)
def cnn_feature_extractor(self, x):
x = self.densenet_features(x)
return x
def preprocess(self, input_x, mixup_lambda=None):
x = self.spectrogram_extractor(input_x) # (batch_size, 1, time_steps, freq_bins)
x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins)
frames_num = x.shape[2]
x = x.transpose(1, 3)
x = self.bn0(x)
x = x.transpose(1, 3)
if self.training and self.apply_aug:
x = self.spec_augmenter(x)
# Mixup on spectrogram
if self.training and self.apply_aug and mixup_lambda is not None:
x = do_mixup(x, mixup_lambda)
return x, frames_num
def forward(self, input_data):
input_x, mixup_lambda = input_data
"""
Input: (batch_size, data_length)"""
b, c, s = input_x.shape
input_x = input_x.reshape(b*c, s)
x, frames_num = self.preprocess(input_x, mixup_lambda=mixup_lambda)
if mixup_lambda is not None:
b = (b*c)//2
c = 1
# Output shape (batch size, channels, time, frequency)
x = x.expand(x.shape[0], 3, x.shape[2], x.shape[3])
x = self.cnn_feature_extractor(x)
# Aggregate in frequency axis
x = torch.mean(x, dim=3)
x1 = F.max_pool1d(x, kernel_size=3, stride=1, padding=1)
x2 = F.avg_pool1d(x, kernel_size=3, stride=1, padding=1)
x = x1 + x2
x = F.dropout(x, p=0.5, training=self.training)
x = x.transpose(1, 2)
x = F.relu_(self.fc1(x))
x = x.transpose(1, 2)
x = F.dropout(x, p=0.5, training=self.training)
(clipwise_output, norm_att, segmentwise_output) = self.att_block(x)
segmentwise_output = segmentwise_output.transpose(1, 2)
# Get framewise output
framewise_output = interpolate(segmentwise_output,
self.interpolate_ratio)
framewise_output = pad_framewise_output(framewise_output, frames_num)
frame_shape = framewise_output.shape
clip_shape = clipwise_output.shape
output_dict = {
'framewise_output': framewise_output.reshape(b, c, frame_shape[1],frame_shape[2]),
'clipwise_output': clipwise_output.reshape(b, c, clip_shape[1]),
}
return output_dict
class PANNsDense201Att(nn.Module):
def __init__(self, sample_rate: int, window_size: int, hop_size: int,
mel_bins: int, fmin: int, fmax: int, classes_num: int, apply_aug: bool, top_db=None):
super().__init__()
window = 'hann'
center = True
pad_mode = 'reflect'
ref = 1.0
amin = 1e-10
self.interpolate_ratio = 32 # Downsampled ratio
self.apply_aug = apply_aug
# Spectrogram extractor
self.spectrogram_extractor = Spectrogram(
n_fft=window_size,
hop_length=hop_size,
win_length=window_size,
window=window,
center=center,
pad_mode=pad_mode,
freeze_parameters=True)
# Logmel feature extractor
self.logmel_extractor = LogmelFilterBank(
sr=sample_rate,
n_fft=window_size,
n_mels=mel_bins,
fmin=fmin,
fmax=fmax,
ref=ref,
amin=amin,
top_db=top_db,
freeze_parameters=True)
# Spec augmenter
self.spec_augmenter = SpecAugmentation(
time_drop_width=64,
time_stripes_num=2,
freq_drop_width=8,
freq_stripes_num=2)
self.bn0 = nn.BatchNorm2d(mel_bins)
self.fc1 = nn.Linear(1920, 1024, bias=True)
self.att_block = AttBlock(1024, classes_num, activation='sigmoid')
self.init_weight()
self.densenet_features = models.densenet201(pretrained=True).features
def init_weight(self):
init_bn(self.bn0)
init_layer(self.fc1)
def cnn_feature_extractor(self, x):
x = self.densenet_features(x)
return x
def preprocess(self, input_x, mixup_lambda=None):
x = self.spectrogram_extractor(input_x) # (batch_size, 1, time_steps, freq_bins)
x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins)
frames_num = x.shape[2]
x = x.transpose(1, 3)
x = self.bn0(x)
x = x.transpose(1, 3)
if self.training and self.apply_aug:
x = self.spec_augmenter(x)
# Mixup on spectrogram
if self.training and self.apply_aug and mixup_lambda is not None:
x = do_mixup(x, mixup_lambda)
return x, frames_num
def forward(self, input_data):
input_x, mixup_lambda = input_data
"""
Input: (batch_size, data_length)"""
b, c, s = input_x.shape
input_x = input_x.reshape(b*c, s)
x, frames_num = self.preprocess(input_x, mixup_lambda=mixup_lambda)
if mixup_lambda is not None:
b = (b*c)//2
c = 1
# Output shape (batch size, channels, time, frequency)
x = x.expand(x.shape[0], 3, x.shape[2], x.shape[3])
x = self.cnn_feature_extractor(x)
# Aggregate in frequency axis
x = torch.mean(x, dim=3)
x1 = F.max_pool1d(x, kernel_size=3, stride=1, padding=1)
x2 = F.avg_pool1d(x, kernel_size=3, stride=1, padding=1)
x = x1 + x2
x = F.dropout(x, p=0.5, training=self.training)
x = x.transpose(1, 2)
x = F.relu_(self.fc1(x))
x = x.transpose(1, 2)
x = F.dropout(x, p=0.5, training=self.training)
(clipwise_output, norm_att, segmentwise_output) = self.att_block(x)
segmentwise_output = segmentwise_output.transpose(1, 2)
# Get framewise output
framewise_output = interpolate(segmentwise_output,
self.interpolate_ratio)
framewise_output = pad_framewise_output(framewise_output, frames_num)
frame_shape = framewise_output.shape
clip_shape = clipwise_output.shape
output_dict = {
'framewise_output': framewise_output.reshape(b, c, frame_shape[1],frame_shape[2]),
'clipwise_output': clipwise_output.reshape(b, c, clip_shape[1]),
}
return output_dict
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0
| 7
|
7aa9f57d880a2ffff952fbb527af7f16f40a5a2e
| 63,703
|
py
|
Python
|
cFSPlib/python_api_client/swagger_client/api/resources__admin_only_api.py
|
cloudFPGA/cFSP
|
f6d93ff8eddb774711064e59e4dc4f931d803d5f
|
[
"Apache-2.0"
] | 2
|
2022-01-31T10:19:13.000Z
|
2022-02-15T06:07:04.000Z
|
cFSPlib/python_api_client/swagger_client/api/resources__admin_only_api.py
|
cloudFPGA/cFSP
|
f6d93ff8eddb774711064e59e4dc4f931d803d5f
|
[
"Apache-2.0"
] | 1
|
2022-01-24T16:16:52.000Z
|
2022-01-25T19:21:52.000Z
|
cFSPlib/python_api_client/swagger_client/api/resources__admin_only_api.py
|
cloudFPGA/cFSP
|
f6d93ff8eddb774711064e59e4dc4f931d803d5f
|
[
"Apache-2.0"
] | null | null | null |
# coding: utf-8
"""
cloudFPGA Resource Manager API
No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501
OpenAPI spec version: 0.8
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from swagger_client.api_client import ApiClient
class ResourcesAdminOnlyApi(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):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def cf_manager_rest_api_delete_resource(self, username, password, resource_id, **kwargs): # noqa: E501
"""Remove a resource # noqa: E501
Please Note, after the deletion of a resource, the freed resource-id will be assigned again for new resources. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_delete_resource(username, password, resource_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_delete_resource_with_http_info(username, password, resource_id, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_delete_resource_with_http_info(username, password, resource_id, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_delete_resource_with_http_info(self, username, password, resource_id, **kwargs): # noqa: E501
"""Remove a resource # noqa: E501
Please Note, after the deletion of a resource, the freed resource-id will be assigned again for new resources. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_delete_resource_with_http_info(username, password, resource_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'resource_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_delete_resource" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_delete_resource`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_delete_resource`") # noqa: E501
# verify the required parameter 'resource_id' is set
if ('resource_id' not in params or
params['resource_id'] is None):
raise ValueError("Missing the required parameter `resource_id` when calling `cf_manager_rest_api_delete_resource`") # noqa: E501
collection_formats = {}
path_params = {}
if 'resource_id' in params:
path_params['resource_id'] = params['resource_id'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/{resource_id}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_get_available_resources(self, username, password, status, **kwargs): # noqa: E501
"""Get all cloudFPGA resources in state `{status}` # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_available_resources(username, password, status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str status: Status of the requested resources (required)
:param int limit:
:return: list[Resource]
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_get_available_resources_with_http_info(username, password, status, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_get_available_resources_with_http_info(username, password, status, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_get_available_resources_with_http_info(self, username, password, status, **kwargs): # noqa: E501
"""Get all cloudFPGA resources in state `{status}` # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_available_resources_with_http_info(username, password, status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str status: Status of the requested resources (required)
:param int limit:
:return: list[Resource]
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'status', 'limit'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_get_available_resources" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_get_available_resources`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_get_available_resources`") # noqa: E501
# verify the required parameter 'status' is set
if ('status' not in params or
params['status'] is None):
raise ValueError("Missing the required parameter `status` when calling `cf_manager_rest_api_get_available_resources`") # noqa: E501
collection_formats = {}
path_params = {}
if 'status' in params:
path_params['status'] = params['status'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
if 'limit' in params:
query_params.append(('limit', params['limit'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/status/{status}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='list[Resource]', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_get_resources(self, username, password, **kwargs): # noqa: E501
"""Get all cloudFPGA resources # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_resources(username, password, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param int limit:
:return: list[Resource]
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_get_resources_with_http_info(username, password, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_get_resources_with_http_info(username, password, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_get_resources_with_http_info(self, username, password, **kwargs): # noqa: E501
"""Get all cloudFPGA resources # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_resources_with_http_info(username, password, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param int limit:
:return: list[Resource]
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'limit'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_get_resources" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_get_resources`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_get_resources`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
if 'limit' in params:
query_params.append(('limit', params['limit'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='list[Resource]', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_get_resources_of_sled_status(self, username, password, sled_ip, **kwargs): # noqa: E501
"""Get status of **all resources** from a specific sled # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_resources_of_sled_status(username, password, sled_ip, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str sled_ip: The ip address of a SM (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_get_resources_of_sled_status_with_http_info(username, password, sled_ip, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_get_resources_of_sled_status_with_http_info(username, password, sled_ip, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_get_resources_of_sled_status_with_http_info(self, username, password, sled_ip, **kwargs): # noqa: E501
"""Get status of **all resources** from a specific sled # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_resources_of_sled_status_with_http_info(username, password, sled_ip, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str sled_ip: The ip address of a SM (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'sled_ip'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_get_resources_of_sled_status" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_get_resources_of_sled_status`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_get_resources_of_sled_status`") # noqa: E501
# verify the required parameter 'sled_ip' is set
if ('sled_ip' not in params or
params['sled_ip'] is None):
raise ValueError("Missing the required parameter `sled_ip` when calling `cf_manager_rest_api_get_resources_of_sled_status`") # noqa: E501
collection_formats = {}
path_params = {}
if 'sled_ip' in params:
path_params['sled_ip'] = params['sled_ip'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/sled/{sled_ip}/status/', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_get_resources_of_sled_status_in_state(self, username, password, sled_ip, status, **kwargs): # noqa: E501
"""Get status of **all resources** from a specific sled in a specific `{status}` # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_resources_of_sled_status_in_state(username, password, sled_ip, status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str sled_ip: The ip address of a SM (required)
:param str status: Status of the requested resources (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_get_resources_of_sled_status_in_state_with_http_info(username, password, sled_ip, status, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_get_resources_of_sled_status_in_state_with_http_info(username, password, sled_ip, status, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_get_resources_of_sled_status_in_state_with_http_info(self, username, password, sled_ip, status, **kwargs): # noqa: E501
"""Get status of **all resources** from a specific sled in a specific `{status}` # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_resources_of_sled_status_in_state_with_http_info(username, password, sled_ip, status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str sled_ip: The ip address of a SM (required)
:param str status: Status of the requested resources (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'sled_ip', 'status'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_get_resources_of_sled_status_in_state" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_get_resources_of_sled_status_in_state`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_get_resources_of_sled_status_in_state`") # noqa: E501
# verify the required parameter 'sled_ip' is set
if ('sled_ip' not in params or
params['sled_ip'] is None):
raise ValueError("Missing the required parameter `sled_ip` when calling `cf_manager_rest_api_get_resources_of_sled_status_in_state`") # noqa: E501
# verify the required parameter 'status' is set
if ('status' not in params or
params['status'] is None):
raise ValueError("Missing the required parameter `status` when calling `cf_manager_rest_api_get_resources_of_sled_status_in_state`") # noqa: E501
collection_formats = {}
path_params = {}
if 'sled_ip' in params:
path_params['sled_ip'] = params['sled_ip'] # noqa: E501
if 'status' in params:
path_params['status'] = params['status'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/sled/{sled_ip}/{status}/', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_get_single_resource(self, username, password, resource_id, **kwargs): # noqa: E501
"""Get details of one resource # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_single_resource(username, password, resource_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:return: Resource
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_get_single_resource_with_http_info(username, password, resource_id, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_get_single_resource_with_http_info(username, password, resource_id, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_get_single_resource_with_http_info(self, username, password, resource_id, **kwargs): # noqa: E501
"""Get details of one resource # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_single_resource_with_http_info(username, password, resource_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:return: Resource
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'resource_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_get_single_resource" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_get_single_resource`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_get_single_resource`") # noqa: E501
# verify the required parameter 'resource_id' is set
if ('resource_id' not in params or
params['resource_id'] is None):
raise ValueError("Missing the required parameter `resource_id` when calling `cf_manager_rest_api_get_single_resource`") # noqa: E501
collection_formats = {}
path_params = {}
if 'resource_id' in params:
path_params['resource_id'] = params['resource_id'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/{resource_id}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Resource', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_get_single_resource_status(self, username, password, resource_id, **kwargs): # noqa: E501
"""Get status of one resource # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_single_resource_status(username, password, resource_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:return: InlineResponse2005
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_get_single_resource_status_with_http_info(username, password, resource_id, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_get_single_resource_status_with_http_info(username, password, resource_id, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_get_single_resource_status_with_http_info(self, username, password, resource_id, **kwargs): # noqa: E501
"""Get status of one resource # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_get_single_resource_status_with_http_info(username, password, resource_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:return: InlineResponse2005
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'resource_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_get_single_resource_status" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_get_single_resource_status`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_get_single_resource_status`") # noqa: E501
# verify the required parameter 'resource_id' is set
if ('resource_id' not in params or
params['resource_id'] is None):
raise ValueError("Missing the required parameter `resource_id` when calling `cf_manager_rest_api_get_single_resource_status`") # noqa: E501
collection_formats = {}
path_params = {}
if 'resource_id' in params:
path_params['resource_id'] = params['resource_id'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/{resource_id}/status/', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='InlineResponse2005', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_post_resources(self, username, password, **kwargs): # noqa: E501
"""Create a cloudFPGA resource # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_post_resources(username, password, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param Resource body:
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_post_resources_with_http_info(username, password, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_post_resources_with_http_info(username, password, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_post_resources_with_http_info(self, username, password, **kwargs): # noqa: E501
"""Create a cloudFPGA resource # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_post_resources_with_http_info(username, password, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param Resource body:
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'body'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_post_resources" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_post_resources`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_post_resources`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_put_resource(self, username, password, resource_id, **kwargs): # noqa: E501
"""Update a resource # noqa: E501
Only the properties to update must be part of the `resource_data` field. All not mentioned properties will stay the same. It is not possible to change the `state` with this API call. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_put_resource(username, password, resource_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:param Resource body:
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_put_resource_with_http_info(username, password, resource_id, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_put_resource_with_http_info(username, password, resource_id, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_put_resource_with_http_info(self, username, password, resource_id, **kwargs): # noqa: E501
"""Update a resource # noqa: E501
Only the properties to update must be part of the `resource_data` field. All not mentioned properties will stay the same. It is not possible to change the `state` with this API call. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_put_resource_with_http_info(username, password, resource_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:param Resource body:
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'resource_id', 'body'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_put_resource" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_put_resource`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_put_resource`") # noqa: E501
# verify the required parameter 'resource_id' is set
if ('resource_id' not in params or
params['resource_id'] is None):
raise ValueError("Missing the required parameter `resource_id` when calling `cf_manager_rest_api_put_resource`") # noqa: E501
collection_formats = {}
path_params = {}
if 'resource_id' in params:
path_params['resource_id'] = params['resource_id'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/{resource_id}', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_put_resource_status(self, username, password, resource_id, new_status, **kwargs): # noqa: E501
"""Update status of a resource # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_put_resource_status(username, password, resource_id, new_status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:param str new_status: New status of the resource (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_put_resource_status_with_http_info(username, password, resource_id, new_status, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_put_resource_status_with_http_info(username, password, resource_id, new_status, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_put_resource_status_with_http_info(self, username, password, resource_id, new_status, **kwargs): # noqa: E501
"""Update status of a resource # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_put_resource_status_with_http_info(username, password, resource_id, new_status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str resource_id: cloudFPGA resource unique identifier (required)
:param str new_status: New status of the resource (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'resource_id', 'new_status'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_put_resource_status" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_put_resource_status`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_put_resource_status`") # noqa: E501
# verify the required parameter 'resource_id' is set
if ('resource_id' not in params or
params['resource_id'] is None):
raise ValueError("Missing the required parameter `resource_id` when calling `cf_manager_rest_api_put_resource_status`") # noqa: E501
# verify the required parameter 'new_status' is set
if ('new_status' not in params or
params['new_status'] is None):
raise ValueError("Missing the required parameter `new_status` when calling `cf_manager_rest_api_put_resource_status`") # noqa: E501
collection_formats = {}
path_params = {}
if 'resource_id' in params:
path_params['resource_id'] = params['resource_id'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
if 'new_status' in params:
query_params.append(('new_status', params['new_status'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/{resource_id}/status/', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_put_resources_of_sled_status(self, username, password, sled_ip, new_status, **kwargs): # noqa: E501
"""Update status of **all resources** from a specific sled # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_put_resources_of_sled_status(username, password, sled_ip, new_status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str sled_ip: The ip address of a SM (required)
:param str new_status: New status of the resource (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_put_resources_of_sled_status_with_http_info(username, password, sled_ip, new_status, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_put_resources_of_sled_status_with_http_info(username, password, sled_ip, new_status, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_put_resources_of_sled_status_with_http_info(self, username, password, sled_ip, new_status, **kwargs): # noqa: E501
"""Update status of **all resources** from a specific sled # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_put_resources_of_sled_status_with_http_info(username, password, sled_ip, new_status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str sled_ip: The ip address of a SM (required)
:param str new_status: New status of the resource (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'sled_ip', 'new_status'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_put_resources_of_sled_status" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_put_resources_of_sled_status`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_put_resources_of_sled_status`") # noqa: E501
# verify the required parameter 'sled_ip' is set
if ('sled_ip' not in params or
params['sled_ip'] is None):
raise ValueError("Missing the required parameter `sled_ip` when calling `cf_manager_rest_api_put_resources_of_sled_status`") # noqa: E501
# verify the required parameter 'new_status' is set
if ('new_status' not in params or
params['new_status'] is None):
raise ValueError("Missing the required parameter `new_status` when calling `cf_manager_rest_api_put_resources_of_sled_status`") # noqa: E501
collection_formats = {}
path_params = {}
if 'sled_ip' in params:
path_params['sled_ip'] = params['sled_ip'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
if 'new_status' in params:
query_params.append(('new_status', params['new_status'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/sled/{sled_ip}/status/', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cf_manager_rest_api_put_resources_of_sled_status_in_state(self, username, password, sled_ip, status, new_status, **kwargs): # noqa: E501
"""Update status of **all resources** from a specific sled in a specific `{status}` # noqa: E501
For example, if this method is called with `PUT /resources/sled/1.2.3.4/AVAILABLE`, then only all `AVAILABLE` resources of Sled `1.2.3.4` are put to to the `new_status`. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_put_resources_of_sled_status_in_state(username, password, sled_ip, status, new_status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str sled_ip: The ip address of a SM (required)
:param str status: Status of the resources that should be updated (required)
:param str new_status: New status of the resources (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cf_manager_rest_api_put_resources_of_sled_status_in_state_with_http_info(username, password, sled_ip, status, new_status, **kwargs) # noqa: E501
else:
(data) = self.cf_manager_rest_api_put_resources_of_sled_status_in_state_with_http_info(username, password, sled_ip, status, new_status, **kwargs) # noqa: E501
return data
def cf_manager_rest_api_put_resources_of_sled_status_in_state_with_http_info(self, username, password, sled_ip, status, new_status, **kwargs): # noqa: E501
"""Update status of **all resources** from a specific sled in a specific `{status}` # noqa: E501
For example, if this method is called with `PUT /resources/sled/1.2.3.4/AVAILABLE`, then only all `AVAILABLE` resources of Sled `1.2.3.4` are put to to the `new_status`. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cf_manager_rest_api_put_resources_of_sled_status_in_state_with_http_info(username, password, sled_ip, status, new_status, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str username: OpenStack username (required)
:param str password: OpenStack password (required)
:param str sled_ip: The ip address of a SM (required)
:param str status: Status of the resources that should be updated (required)
:param str new_status: New status of the resources (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['username', 'password', 'sled_ip', 'status', 'new_status'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cf_manager_rest_api_put_resources_of_sled_status_in_state" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'username' is set
if ('username' not in params or
params['username'] is None):
raise ValueError("Missing the required parameter `username` when calling `cf_manager_rest_api_put_resources_of_sled_status_in_state`") # noqa: E501
# verify the required parameter 'password' is set
if ('password' not in params or
params['password'] is None):
raise ValueError("Missing the required parameter `password` when calling `cf_manager_rest_api_put_resources_of_sled_status_in_state`") # noqa: E501
# verify the required parameter 'sled_ip' is set
if ('sled_ip' not in params or
params['sled_ip'] is None):
raise ValueError("Missing the required parameter `sled_ip` when calling `cf_manager_rest_api_put_resources_of_sled_status_in_state`") # noqa: E501
# verify the required parameter 'status' is set
if ('status' not in params or
params['status'] is None):
raise ValueError("Missing the required parameter `status` when calling `cf_manager_rest_api_put_resources_of_sled_status_in_state`") # noqa: E501
# verify the required parameter 'new_status' is set
if ('new_status' not in params or
params['new_status'] is None):
raise ValueError("Missing the required parameter `new_status` when calling `cf_manager_rest_api_put_resources_of_sled_status_in_state`") # noqa: E501
collection_formats = {}
path_params = {}
if 'sled_ip' in params:
path_params['sled_ip'] = params['sled_ip'] # noqa: E501
if 'status' in params:
path_params['status'] = params['status'] # noqa: E501
query_params = []
if 'username' in params:
query_params.append(('username', params['username'])) # noqa: E501
if 'password' in params:
query_params.append(('password', params['password'])) # noqa: E501
if 'new_status' in params:
query_params.append(('new_status', params['new_status'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/resources/sled/{sled_ip}/{status}/', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
| 46.703079
| 205
| 0.639216
| 7,639
| 63,703
| 5.056421
| 0.026181
| 0.042044
| 0.041397
| 0.05095
| 0.987081
| 0.987081
| 0.986822
| 0.981955
| 0.981334
| 0.980712
| 0
| 0.013948
| 0.274069
| 63,703
| 1,363
| 206
| 46.737344
| 0.821317
| 0.328933
| 0
| 0.812827
| 1
| 0
| 0.242198
| 0.085365
| 0
| 0
| 0
| 0
| 0
| 1
| 0.032723
| false
| 0.157068
| 0.005236
| 0
| 0.086387
| 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
|
7aaf0195e171caf26796067e2d71e5a9be540eb6
| 2,175
|
py
|
Python
|
asciipug.py
|
FelixMaxwell/termdoggo
|
48d3e2081a2e3722064b8e9944414ede213cee52
|
[
"MIT"
] | null | null | null |
asciipug.py
|
FelixMaxwell/termdoggo
|
48d3e2081a2e3722064b8e9944414ede213cee52
|
[
"MIT"
] | null | null | null |
asciipug.py
|
FelixMaxwell/termdoggo
|
48d3e2081a2e3722064b8e9944414ede213cee52
|
[
"MIT"
] | null | null | null |
#Eyes & Ears
print (" ")
print (" ///////// /////////////// ")
print (" \ ///|||||||||||||||||||||||||||||||||||||||||||||// / ")
print (" \ // // / ")
print (" \ // // / ")
print (" \ // // / ")
print (" \ // // / ")
print (" \ // // / ")
print (" \ /// $$$$$$$$$$ $$$$$$$$$$ /// / ")
print (" \ //// $$$#########$$ $$$#########$$ /// / ")
print (" \ //// $$$############$$$ $$############$$ /// / ")
print (" \/ $$$############$$ $$############$$ \/ ")
print (" \ $$$#########$$ $$$#########$$ / ")
print (" \ / ")
print (" \ / ")
#Nose
print (" \ / (@@@@@@@) \ / ")
print (" \ / ( @@;@@@@;@@ ) \ / ")
print (" \ \ ( @@@;@@@@;@@@ ) / / ")
#Mouth - Used to display different emotions
print (" \ \ /\ / / ")
print (" \ \ / \ / / ")
print (" \ \____________/ \__________/ / ")
print (" \ / ")
print (" \ _________________________________________ / ")
| 72.5
| 93
| 0.103448
| 32
| 2,175
| 5.0625
| 0.3125
| 1.234568
| 1.574074
| 1.728395
| 0.617284
| 0.462963
| 0.462963
| 0.462963
| 0.462963
| 0.462963
| 0
| 0
| 0.689195
| 2,175
| 29
| 94
| 75
| 0.239645
| 0.026207
| 0
| 0.434783
| 0
| 0
| 0.877956
| 0.043046
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 8
|
8906676461b409afb175ea729826e1261088afd0
| 48
|
py
|
Python
|
src/stackedwaterfalls/__init__.py
|
askprash/stackedwaterfall
|
e85e8226230c65e4e61a60077f53b75b1c7a3909
|
[
"MIT"
] | 7
|
2021-11-17T06:01:57.000Z
|
2022-03-28T22:08:07.000Z
|
src/stackedwaterfalls/__init__.py
|
askprash/stackedwaterfall
|
e85e8226230c65e4e61a60077f53b75b1c7a3909
|
[
"MIT"
] | 1
|
2021-11-17T16:47:22.000Z
|
2021-11-17T16:47:22.000Z
|
src/stackedwaterfalls/__init__.py
|
askprash/stackedwaterfall
|
e85e8226230c65e4e61a60077f53b75b1c7a3909
|
[
"MIT"
] | null | null | null |
from .stackedwaterfalls import StackedWaterfalls
| 48
| 48
| 0.916667
| 4
| 48
| 11
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.0625
| 48
| 1
| 48
| 48
| 0.977778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
8f4cf5289539f8124c91c74df996c9a3ac461b18
| 4,139
|
py
|
Python
|
photoplaces/photoplaces_web/migrations/0011_auto_20150119_0826.py
|
joonamo/photoplaces
|
2223f62459e5141ce5bb5325ad83e5975f1545c7
|
[
"MIT"
] | null | null | null |
photoplaces/photoplaces_web/migrations/0011_auto_20150119_0826.py
|
joonamo/photoplaces
|
2223f62459e5141ce5bb5325ad83e5975f1545c7
|
[
"MIT"
] | null | null | null |
photoplaces/photoplaces_web/migrations/0011_auto_20150119_0826.py
|
joonamo/photoplaces
|
2223f62459e5141ce5bb5325ad83e5975f1545c7
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('photoplaces_web', '0010_auto_20150119_0805'),
]
operations = [
migrations.RemoveField(
model_name='photocluster',
name='points_month_1',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_10',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_11',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_12',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_2',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_3',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_4',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_5',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_6',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_7',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_8',
),
migrations.RemoveField(
model_name='photocluster',
name='points_month_9',
),
migrations.AddField(
model_name='photocluster',
name='points_month_10_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_11_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_12_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_1_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_2_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_3_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_4_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_5_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_6_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_7_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_8_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
migrations.AddField(
model_name='photocluster',
name='points_month_9_relative',
field=models.FloatField(default=0),
preserve_default=True,
),
]
| 30.659259
| 55
| 0.556415
| 350
| 4,139
| 6.28
| 0.134286
| 0.098271
| 0.229299
| 0.272975
| 0.925387
| 0.925387
| 0.925387
| 0.911738
| 0.575978
| 0.5505
| 0
| 0.021723
| 0.343803
| 4,139
| 134
| 56
| 30.88806
| 0.787555
| 0.005074
| 0
| 0.75
| 0
| 0
| 0.188533
| 0.073372
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.015625
| 0
| 0.039063
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 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
|
56cfd28a732f502bb211c1af917e75170251c5da
| 41,105
|
py
|
Python
|
organize.py
|
acic2017/Butterfly-SDM
|
4b3cfe132a22d195ca3730f4fdd78c71fc958505
|
[
"MIT"
] | 1
|
2017-12-04T05:02:34.000Z
|
2017-12-04T05:02:34.000Z
|
organize.py
|
acic2017/Butterfly-SDM
|
4b3cfe132a22d195ca3730f4fdd78c71fc958505
|
[
"MIT"
] | 1
|
2017-12-05T07:22:54.000Z
|
2017-12-05T07:22:54.000Z
|
organize.py
|
acic2017/Butterfly-SDM
|
4b3cfe132a22d195ca3730f4fdd78c71fc958505
|
[
"MIT"
] | 3
|
2017-12-01T03:55:10.000Z
|
2018-12-14T23:42:08.000Z
|
'''
ISTA 422 Final Project
Team Name: Monarch 2.0
Code Author: Phillip Johnson
Purpose of script:
This Python script is used to clean and organize data from iNaturalist Gbif dump
and eButterfly Database dump and integrate it into a singular file in a format needed
to run the R Species Distribution Model program. For additional information about specific
functionality of this code, please see additional comments included in the code below.
'''
#import csv utilizes the Python library that specializes in CSV manipulation and file writing.
#import os utilizes the Python library that specializes in functions such as directory creation.
#import string utilizes the Python library that specializes in string manipulation.
import csv
import string
import os
'''
Global Variables:
This predetermines items that will been to be reference throughout the different functions
without having to explicitely return them from each function.
'''
year_keys=[]
month_list=['01','02','03','04','05','06','07','08','09','10','11','12','all']
data_dict={}
'''
Function get_iNat:
This function opens and reads data from iNaturalist, in the form of the Gbif data dump. Once
open, it traverses the file, creating a dictionary association of each entry by scientificName,
year, month, latitude, and longitude. While accomplishing this, it also does not transcribe
any data that is not marked as 'Research Grade' or any data that is missing information in the areas
needed. This function returns None, but rather fills the data_dict global variable.
This code is optimized to pull out ONLY butterfly and moth observations from this file, but having a
requirement of the 'order' in the dataset to be Lepidoptera.
If you would prefer to pull ALL observations for the purpose of cleaning and analysis. Please remove
the portion (row['order'] == 'Lepidoptera' and) from line 48 and 73.
'''
def get_iNat(filename):
with open(filename, encoding='utf8') as csvfile:
reader = csv.DictReader(csvfile)
data_keys=data_dict.keys()
for row in reader:
if row['order'] == 'Lepidoptera' and row['scientificName'] not in data_keys and row['datasetName'] == 'iNaturalist research-grade observations':
data_dict[row['scientificName']]= {}
'''
organizing dictionary input into format {{year}, {month}, [lat, long]}
'''
if row['eventDate'][4]=='-':
data_dict[row['scientificName']][row['eventDate'][0:4]]={}
data_dict[row['scientificName']][row['eventDate'][0:4]]['01']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['02']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['03']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['04']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['05']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['06']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['07']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['08']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['09']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['10']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['11']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['12']=[]
#format is Latitude, longitude
data_dict[row['scientificName']][row['eventDate'][0:4]][row['eventDate'][5:7]].append([row['decimalLatitude'],row['decimalLongitude']])
elif row['order'] == 'Lepidoptera' and row['datasetName'] == 'iNaturalist research-grade observations':
'''
This gets rid of all non research grade observations
'''
if len(row['eventDate'])>0 and row['eventDate'][4]=='-':
year_key = data_dict[row['scientificName']].keys()
if row['eventDate'][0:4]not in year_key:
year_keys.append([row['eventDate'][0:4]])
data_dict[row['scientificName']][row['eventDate'][0:4]]={}
data_dict[row['scientificName']][row['eventDate'][0:4]]['01']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['02']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['03']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['04']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['05']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['06']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['07']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['08']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['09']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['10']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['11']=[]
data_dict[row['scientificName']][row['eventDate'][0:4]]['12']=[]
'''
Checking that entries have Lat/long coords, not transcribing entries if they do not.
'''
if len(row['decimalLatitude']) > 1 or len(row['decimalLongitude']) > 1:
data_dict[row['scientificName']][row['eventDate'][0:4]][row['eventDate'][5:7]].append([row['decimalLatitude'],row['decimalLongitude']])
else:
if len(row['decimalLatitude']) > 1 or len(row['decimalLongitude']) > 1:
data_dict[row['scientificName']][row['eventDate'][0:4]][row['eventDate'][5:7]].append([row['decimalLatitude'],row['decimalLongitude']])
'''
Function get_eButterfly:
This function opens and reads data from a csv file created from the eButterfly sql data dump
(this datadump is partially cleaned and extracted via a seperate script). Once open, it traverses
the file, creating a dictionary association of each entry by scientificName
(in this files case, it is labeled latin_name), year, month, latitude, and longitude. While
accomplishing this, it also does not transcribe any data that is missing information in the areas
needed. This function returns None, but rather fills/augments the data_dict global variable.
'''
def get_eButterfly(filename):
with open(filename, encoding='utf8') as csvfile:
reader = csv.DictReader(csvfile)
data_keys=data_dict.keys()
for row in reader:
#row['ColumnID'] = total_rows['ColumnID'].astype(str)
if row['latin_name'] not in data_keys:
data_dict[row['latin_name']]= {}
'''
organizing dictionary input into format {{year}, {month}, [lat, long]}
'''
if len(row['year_created'])==4:
data_dict[row['latin_name']][row['year_created']]={}
data_dict[row['latin_name']][row['year_created']]['01']=[]
data_dict[row['latin_name']][row['year_created']]['02']=[]
data_dict[row['latin_name']][row['year_created']]['03']=[]
data_dict[row['latin_name']][row['year_created']]['04']=[]
data_dict[row['latin_name']][row['year_created']]['05']=[]
data_dict[row['latin_name']][row['year_created']]['06']=[]
data_dict[row['latin_name']][row['year_created']]['07']=[]
data_dict[row['latin_name']][row['year_created']]['08']=[]
data_dict[row['latin_name']][row['year_created']]['09']=[]
data_dict[row['latin_name']][row['year_created']]['10']=[]
data_dict[row['latin_name']][row['year_created']]['11']=[]
data_dict[row['latin_name']][row['year_created']]['12']=[]
#cleaning month formatting vvv
if len(row['month_created']) == 1:
row['month_created']='0' + row['month_created']
#format is Latitude, longitude
data_dict[row['latin_name']][row['year_created']][row['month_created']].append([row['latitude'],row['longitude']])
else :
year_key = data_dict[row['latin_name']].keys()
if row['year_created'] not in year_key:
year_keys.append([row['year_created']])
data_dict[row['latin_name']][row['year_created']]={}
data_dict[row['latin_name']][row['year_created']]['01']=[]
data_dict[row['latin_name']][row['year_created']]['02']=[]
data_dict[row['latin_name']][row['year_created']]['03']=[]
data_dict[row['latin_name']][row['year_created']]['04']=[]
data_dict[row['latin_name']][row['year_created']]['05']=[]
data_dict[row['latin_name']][row['year_created']]['06']=[]
data_dict[row['latin_name']][row['year_created']]['07']=[]
data_dict[row['latin_name']][row['year_created']]['08']=[]
data_dict[row['latin_name']][row['year_created']]['09']=[]
data_dict[row['latin_name']][row['year_created']]['10']=[]
data_dict[row['latin_name']][row['year_created']]['11']=[]
data_dict[row['latin_name']][row['year_created']]['12']=[]
#cleaning month formatting vvv
if len(row['month_created']) == 1:
row['month_created']='0' + row['month_created']
'''
Checking that entries have Lat/long coords, not transcribing entries if they do not.
'''
if len(row['latitude']) > 1 or len(row['longitude']) > 1:
data_dict[row['latin_name']][row['year_created']][row['month_created']].append([row['latitude'],row['longitude']])
else:
if len(row['month_created']) == 1:
row['month_created']='0' + row['month_created']
if len(row['latitude']) > 1 or len(row['longitude']) > 1:
data_dict[row['latin_name']][row['year_created']][row['month_created']].append([row['latitude'],row['longitude']])
'''
Runs get_iNat function and organizes/cleans observations.csv file from the Gbif Datadump (iNaturalist)
Currently the iNaturalist function is commented out for faster running. To include the full dataset,
please remove the '#' from lines 190,191, and 192.
'''
#print('Beginning cleaning of iNaturalist Data')
#get_iNat('observations.csv')
#print('Cleaning of iNaturalist Data Complete')
print('Beginning cleaning of eButterfly Data')
#Runs get_eButterfly function and organizes/cleans eb_butterflies_new.csv file from the eButterfly Datadump.
get_eButterfly('eb_butterflies_new.csv')
print('Processing Complete, beginning file creation and integration of data sources')
''' Writing data in format needed to new TXT file for SDM format
***************************************************************************************************
If preferred format is TXT and not CSV please uncomment out this function.
To do this, please move contents from below "print('data_for_sdm.txt created successfully')"
to directly under the astrics line below.
***************************************************************************************************
with open('data_for_sdm.txt','w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientificName','year','month','latitude','longitude'])
for id in data_dict:
for year in data_dict[id]:
for month in data_dict[id][year]:
for coords in data_dict[id][year][month]:
for m in range(len(coords)):
coords[m]=coords[m].strip()
coords[m]=coords[m].replace('N' ,'')
coords[m]=coords[m].replace('+' ,'')
coords[m]=coords[m].replace(' ' ,'.',1)
coords[m]=coords[m].replace('\\' ,'')
coords[m]=coords[m].replace("'" ,'.')
coords[m]=coords[m].replace('"' ,'.')
coords[m]=coords[m].replace("′" ,'.')
coords[m]=coords[m].replace('″' ,'.')
coords[m]=coords[m].replace(';' ,'.')
coords[m]=coords[m].replace(',' ,'')
coords[m]=coords[m].replace('_' ,'')
coords[m]=coords[m].replace('>' ,'.')
coords[m]=coords[m].replace(':' ,'.')
if len(coords[m])>1:
coords[m]=coords[m].replace('°' ,'')
for n in range(len(coords[m])):
if coords[m][n].isalpha():
coords[m]=coords[m].replace(coords[m][n] ,' ')
decimal_counter=0
for o in range(len(coords[m])):
if o <= len(coords[m]):
if coords[m][o]=='.':
decimal_counter+=1
if decimal_counter > 1:
coords[m][o]
coords[m]=coords[m][0:o]+coords[m][o+1:]+' '
decimal_counter-=1
for p in range(len(coords[m])):
if coords[m][p]=='-' and p!=0:
coords[m][p]
coords[m]=coords[m][0:p]+coords[m][p+1:]+' '
coords[m]=coords[m].replace(' ' ,'')
csvwriter.writerow([id,year, month,coords[0], coords[-1]])
print('data_for_sdm.txt created successfully')
'''
'''
This portion of code takes the filled global variable data_dict and creates a
csv file which will be used by the Species Distribution Model (SDM) as well
as allowing easier user viewing if further or seperate analysis is needed on
the combined, cleaned datasets. This code also cleans the Latitude and Longitude
inputs from the files, and cleans/organizes them into a uniform format.
'''
#Format of CSV is scientificName, year, month, latitude, longitude
with open('data_for_sdm.csv','w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientificName','year','month','latitude','longitude'])
for id in data_dict:
for year in data_dict[id]:
for month in data_dict[id][year]:
for coords in data_dict[id][year][month]:
for m in range(len(coords)):
#The below code cleans common errors noticed for the latitude/longitude entries.
#This includes ensuring a singular format after cleaning.
coords[m]=coords[m].strip()
coords[m]=coords[m].replace('N' ,'')
coords[m]=coords[m].replace('+' ,'')
coords[m]=coords[m].replace(' ' ,'.',1)
coords[m]=coords[m].replace('\\' ,'')
coords[m]=coords[m].replace("'" ,'.')
coords[m]=coords[m].replace('"' ,'.')
coords[m]=coords[m].replace("′" ,'.')
coords[m]=coords[m].replace('″' ,'.')
coords[m]=coords[m].replace(';' ,'.')
coords[m]=coords[m].replace(',' ,'')
coords[m]=coords[m].replace('_' ,'')
coords[m]=coords[m].replace('>' ,'.')
coords[m]=coords[m].replace(':' ,'.')
if len(coords[m])>1:
coords[m]=coords[m].replace('°' ,'')
for n in range(len(coords[m])):
if coords[m][n].isalpha():
coords[m]=coords[m].replace(coords[m][n] ,' ')
decimal_counter=0
for o in range(len(coords[m])):
if o <= len(coords[m]):
if coords[m][o]=='.':
decimal_counter+=1
if decimal_counter > 1:
coords[m][o]
coords[m]=coords[m][0:o]+coords[m][o+1:]+' '
decimal_counter-=1
for p in range(len(coords[m])):
if coords[m][p]=='-' and p!=0:
coords[m][p]
coords[m]=coords[m][0:p]+coords[m][p+1:]+' '
coords[m]=coords[m].replace(' ' ,'')
csvwriter.writerow([id,year, month,coords[0], coords[-1]])
print('data_for_sdm.csv created successfully. This is useful for visualizing the data in a clean excel form')
'''
This portion of code seperates each Species into their own files, containing all
of the data for that species in the format scientificName, year, month, latitude,
longitude. When this code finishes running there will be a singular csv for each
and every species. This code has a threshold requirement of 13 total observations
for the species to be considered, have a folder created and a csv written. This
portion also write individual files for each species for each month, containing
all observations for that species for all years during that month, if the observations
for that month are above the threshold of 13. All written files will be contained
within a folder named the species scientificName.
Update** This code now includes a filter, so that only species and/or observations from
North America will be included in the output. This was implemented due to the bounding
boxes in the Run_SDM.R script as to now cause errors for points out of bounds.
'''
print('Beginning species specific csv file creation.')
species=list(data_dict.keys())
with open('species_list.csv','w', encoding='utf-8') as csv_file:
#Creates a species list, to show a total listing of all species
#in the combined dataset, prior to the observations_threshold
#or North American filter.
csvwriter_species = csv.writer( csv_file, delimiter=',' )
for each in species:
if len(each)<3 :
del each
else:
csvwriter_species.writerow([each])
for i in range(len(species)):
nameset=species[i]
naming=nameset.split()
#cleans Species Name and joins it by an '_' to prepare
#for folder/file creation.
for j in range(len(naming)):
naming[j]=naming[j].strip('"')
for char in naming[j]:
if char in " ?.!/;:":
naming[j] = naming[j].replace(char,'')
join_name='_'.join(naming)
filename = str(join_name )
if len(filename)>4:
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
if not os.path.exists(filename) :
os.makedirs(filename)
file_output =os.path.join(filename , 'all')
os.makedirs(file_output)
file_output =os.path.join(filename , 'jan')
os.makedirs(file_output)
file_output =os.path.join(filename , 'feb')
os.makedirs(file_output)
file_output =os.path.join(filename , 'mar')
os.makedirs(file_output)
file_output =os.path.join(filename , 'apr')
os.makedirs(file_output)
file_output =os.path.join(filename , 'may')
os.makedirs(file_output)
file_output =os.path.join(filename , 'jun')
os.makedirs(file_output)
file_output =os.path.join(filename , 'jul')
os.makedirs(file_output)
file_output =os.path.join(filename , 'aug')
os.makedirs(file_output)
file_output =os.path.join(filename , 'sep')
os.makedirs(file_output)
file_output =os.path.join(filename , 'oct')
os.makedirs(file_output)
file_output =os.path.join(filename , 'nov')
os.makedirs(file_output)
file_output =os.path.join(filename , 'dec')
os.makedirs(file_output)
file_output =os.path.join(filename ,'all', filename +'_all.csv')
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold=0
observations_threshold=len(data_dict[nameset]) + len(data_dict[nameset][year]) + len(data_dict[nameset][year][month])
if observations_threshold >= 13:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
observations_threshold=0
file_output =filename + '\\' + 'jan\\' + filename +'_jan.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '01':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '01':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'feb\\' +filename +'_feb.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '02':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '02':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'mar\\' +filename +'_mar.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '03':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '03':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'apr\\' +filename +'_apr.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '04':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '04':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'may\\' + filename +'_may.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '05':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '05':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'jun\\' +filename +'_jun.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '06':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '06':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'jul\\' +filename +'_jul.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '07':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '07':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'aug\\' +filename +'_aug.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '08':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '08':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'sep\\' +filename +'_sep.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '09':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '09':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'oct\\' +filename +'_oct.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '10':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '10':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'nov\\' +filename +'_nov.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '11':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '11':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
file_output =filename + '\\' + 'dec\\' +filename +'_dec.csv'
observations_threshold=0
for years in data_dict[nameset]:
for months in data_dict[nameset][years]:
if months == '12':
for coords in data_dict[nameset][years][months]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
observations_threshold+=1
if observations_threshold >= 13:
with open(file_output,'w', encoding='utf-8') as csv_file:
csvwriter = csv.writer(csv_file, delimiter=',' )
csvwriter.writerow(['scientific_name','year','month','latitude','longitude'])
for year in data_dict[nameset]:
for month in data_dict[nameset][year]:
if month == '12':
for coords in data_dict[nameset][year][month]:
coords[0]=coords[0].replace('°' ,'')
coords[-1]=coords[-1].replace('°' ,'')
if len(coords[0]) >1 and coords[0][-1]=='.' :
coords[0]=coords[0][0:-1]
if len(coords[-1]) >1 and coords[-1][-1]=='.' :
coords[-1]=coords[-1][0:-1]
if len(coords[0]) >1 and ',' not in coords[0] and float(coords[0]) >= 15 and float(coords[0]) <= 75:
if float(coords[-1])>= -165 and float(coords[-1]) <= -52:
csvwriter.writerow([nameset, year, month,coords[0], coords[-1]])
print('Individual species csv file creation complete.')
| 49.524096
| 148
| 0.578251
| 5,658
| 41,105
| 4.133439
| 0.066101
| 0.082311
| 0.036773
| 0.056698
| 0.810407
| 0.795485
| 0.795485
| 0.77449
| 0.771069
| 0.76906
| 0
| 0.04219
| 0.22732
| 41,105
| 829
| 149
| 49.583836
| 0.692264
| 0.038049
| 0
| 0.771987
| 0
| 0
| 0.110952
| 0.000672
| 0
| 0
| 0
| 0
| 0
| 1
| 0.003257
| false
| 0
| 0.004886
| 0
| 0.008143
| 0.008143
| 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
|
56d691d887e229dcedaa5e5447a2c9dc94e4c5df
| 4,849
|
py
|
Python
|
jauth/migrations/0001_initial.py
|
kajala/django-jauth
|
9a3681d4d0f030a167649ec6cb7ab5f79a71d00c
|
[
"MIT"
] | null | null | null |
jauth/migrations/0001_initial.py
|
kajala/django-jauth
|
9a3681d4d0f030a167649ec6cb7ab5f79a71d00c
|
[
"MIT"
] | null | null | null |
jauth/migrations/0001_initial.py
|
kajala/django-jauth
|
9a3681d4d0f030a167649ec6cb7ab5f79a71d00c
|
[
"MIT"
] | null | null | null |
# Generated by Django 2.2.3 on 2019-07-15 17:13
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name="GoogleUser",
fields=[
("id", models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
("ext_user_id", models.CharField(db_index=True, max_length=32, unique=True)),
("me", django.contrib.postgres.fields.jsonb.JSONField(blank=True, default=dict)),
(
"user",
models.ForeignKey(
blank=True,
default=None,
null=True,
on_delete=django.db.models.deletion.CASCADE,
to=settings.AUTH_USER_MODEL,
),
),
],
options={
"abstract": False,
},
),
migrations.CreateModel(
name="GoogleAccessToken",
fields=[
("id", models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
("access_token", models.CharField(max_length=255)),
("expire_time", models.DateTimeField(db_index=True)),
(
"ext_user",
models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name="+", to="jauth.GoogleUser"),
),
],
options={
"abstract": False,
},
),
migrations.CreateModel(
name="FacebookUser",
fields=[
("id", models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
("ext_user_id", models.CharField(db_index=True, max_length=32, unique=True)),
("me", django.contrib.postgres.fields.jsonb.JSONField(blank=True, default=dict)),
(
"user",
models.ForeignKey(
blank=True,
default=None,
null=True,
on_delete=django.db.models.deletion.CASCADE,
to=settings.AUTH_USER_MODEL,
),
),
],
options={
"abstract": False,
},
),
migrations.CreateModel(
name="FacebookAccessToken",
fields=[
("id", models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
("access_token", models.CharField(max_length=255)),
("expire_time", models.DateTimeField(db_index=True)),
(
"ext_user",
models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name="+", to="jauth.FacebookUser"),
),
],
options={
"abstract": False,
},
),
migrations.CreateModel(
name="AccountKitUser",
fields=[
("id", models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
("ext_user_id", models.CharField(db_index=True, max_length=32, unique=True)),
("me", django.contrib.postgres.fields.jsonb.JSONField(blank=True, default=dict)),
(
"user",
models.ForeignKey(
blank=True,
default=None,
null=True,
on_delete=django.db.models.deletion.CASCADE,
to=settings.AUTH_USER_MODEL,
),
),
],
options={
"abstract": False,
},
),
migrations.CreateModel(
name="AccountKitAccessToken",
fields=[
("id", models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
("access_token", models.CharField(max_length=255)),
("expire_time", models.DateTimeField(db_index=True)),
(
"ext_user",
models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name="+", to="jauth.AccountKitUser"),
),
],
options={
"abstract": False,
},
),
]
| 38.181102
| 128
| 0.487317
| 406
| 4,849
| 5.665025
| 0.194581
| 0.031304
| 0.042609
| 0.066957
| 0.817391
| 0.803478
| 0.764348
| 0.764348
| 0.764348
| 0.764348
| 0
| 0.010263
| 0.397195
| 4,849
| 126
| 129
| 38.484127
| 0.776599
| 0.00928
| 0
| 0.731092
| 1
| 0
| 0.076218
| 0.004373
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.033613
| 0
| 0.067227
| 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
|
8567228e4682d060ee565e06f4fe460b3c836577
| 13,482
|
py
|
Python
|
tests/st/param_name/test_parameter.py
|
zhz44/mindspore
|
6044d34074c8505dd4b02c0a05419cbc32a43f86
|
[
"Apache-2.0"
] | 1
|
2022-02-23T09:13:43.000Z
|
2022-02-23T09:13:43.000Z
|
tests/st/param_name/test_parameter.py
|
zhz44/mindspore
|
6044d34074c8505dd4b02c0a05419cbc32a43f86
|
[
"Apache-2.0"
] | null | null | null |
tests/st/param_name/test_parameter.py
|
zhz44/mindspore
|
6044d34074c8505dd4b02c0a05419cbc32a43f86
|
[
"Apache-2.0"
] | null | null | null |
# Copyright 2022 Huawei Technologies Co., Ltd
#
# 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 pytest
import mindspore as ms
from mindspore.nn import Cell
from mindspore.common.parameter import Parameter
from mindspore.common import ParameterTuple
from mindspore import Tensor, context
context.set_context(mode=context.GRAPH_MODE)
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_1_1():
"""
Feature: Check the names of parameters and the names of inputs of construct.
Description: If the name of the input of construct is same as the parameters, add suffix to the name of the input.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.param_b = Parameter(Tensor([2], ms.float32), name="name_b")
def construct(self, name_a):
return self.param_a + self.param_b - name_a
net = ParamNet()
res = net(Tensor([3], ms.float32))
assert res == 0
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_1_2():
"""
Feature: Check the names of parameters and the names of inputs of construct.
Description: If the name of the input of construct is same as the parameters, add suffix to the name of the input.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.param_b = ParameterTuple((Parameter(Tensor([2], ms.float32), name="name_b"), self.param_a))
def construct(self, name_b):
return self.param_a + self.param_b[0] - name_b
net = ParamNet()
res = net(Tensor([3], ms.float32))
assert res == 0
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_2_1():
"""
Feature: Check the names of parameters.
Description: If parameters in init have same name, an exception will be thrown.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.param_b = Parameter(Tensor([2], ms.float32), name="name_a")
def construct(self):
return self.param_a + self.param_b
with pytest.raises(ValueError, match="its name 'name_a' already exists."):
net = ParamNet()
res = net()
assert res == 3
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_2_2():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.res1 = ParameterTuple((Parameter(Tensor([2], ms.float32)), self.param_a))
self.param_a = Parameter(Tensor([3], ms.float32), name="name_a")
self.res2 = self.res1[0] + self.param_a
def construct(self):
return self.param_a + self.res1[0] + self.res2
with pytest.raises(ValueError, match="its name 'name_a' already exists."):
net = ParamNet()
res = net()
assert res == 10
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_3():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32))
self.param_b = Parameter(Tensor([2], ms.float32))
def construct(self):
return self.param_a + self.param_b
net = ParamNet()
res = net()
assert res == 3
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_4():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.res1 = ParameterTuple((Parameter(Tensor([2], ms.float32), name="name_a"),
Parameter(Tensor([4], ms.float32), name="name_a")))
def construct(self):
return self.res1[0] + self.res1[1]
with pytest.raises(ValueError, match="its name 'name_a' already exists."):
net = ParamNet()
res = net()
assert res == 6
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_5_1():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.res1 = ParameterTuple((Parameter(Tensor([2], ms.float32)), Parameter(Tensor([4], ms.float32))))
def construct(self):
return self.res1[0] + self.res1[1]
with pytest.raises(ValueError, match="its name 'Parameter' already exists."):
net = ParamNet()
res = net()
assert res == 6
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_5_2():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.res1 = ParameterTuple((Parameter(Tensor([2], ms.float32)), self.param_a))
self.param_a = Parameter(Tensor([3], ms.float32), name="name_b")
self.res2 = self.res1[0] + self.param_a
def construct(self):
return self.param_a + self.res1[0] + self.res2
net = ParamNet()
res = net()
assert res == 10
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_list_tuple_no_name():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_tuple = (Parameter(Tensor([5], ms.float32)), Parameter(Tensor([6], ms.float32)))
self.param_list = [Parameter(Tensor([7], ms.float32)), Parameter(Tensor([8], ms.float32))]
def construct(self):
return self.param_tuple[0] + self.param_tuple[1] + self.param_list[0] + self.param_list[1]
net = ParamNet()
res = net()
assert res == 26
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_in_tuple():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.param_b = Parameter(Tensor([2], ms.float32), name="name_b")
self.param_tuple = ParameterTuple((self.param_a, self.param_b))
def construct(self):
return self.param_a + self.param_b + self.param_tuple[0] + self.param_tuple[1]
net = ParamNet()
res = net()
assert res == 6
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_parameter_tuple_1():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.param_tuple = ParameterTuple((Parameter(Tensor([5], ms.float32), name="name_a"),
Parameter(Tensor([5], ms.float32), name="name_b")))
def construct(self):
return self.param_a + self.param_tuple[0] + self.param_tuple[1]
with pytest.raises(ValueError, match="its name 'name_a' already exists."):
net = ParamNet()
res = net()
assert res == 11
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_parameter_parameter_tuple_2():
"""
Feature: Check the names of parameters.
Description: Check the name of parameter in init.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.param_tuple = ParameterTuple((self.param_a, self.param_a, self.param_a))
def construct(self):
return self.param_a + self.param_tuple[0] + self.param_tuple[1] + self.param_tuple[2]
net = ParamNet()
res = net()
assert res == 4
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_parameter():
"""
Feature: Check the names of parameters.
Description: If parameter in list or tuple is not given a name, will give it a unique name.
Expectation: No exception.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_a = Parameter(Tensor([1], ms.float32), name="name_a")
self.param_b = Parameter(Tensor([2], ms.float32), name="name_b")
self.param_c = Parameter(Tensor([3], ms.float32))
self.param_d = Parameter(Tensor([4], ms.float32))
self.param_tuple = (Parameter(Tensor([5], ms.float32)),
Parameter(Tensor([6], ms.float32)))
self.param_list = [Parameter(Tensor([5], ms.float32)),
Parameter(Tensor([6], ms.float32))]
def construct(self, x):
res1 = self.param_a + self.param_b + self.param_c + self.param_d
res1 = res1 - self.param_list[0] + self.param_list[1] + x
res2 = self.param_list[0] + self.param_list[1]
return res1, res2
net = ParamNet()
x = Tensor([10], ms.float32)
output1, output2 = net(x)
output1_expect = Tensor(21, ms.float32)
output2_expect = Tensor(11, ms.float32)
assert output1 == output1_expect
assert output2 == output2_expect
@pytest.mark.level1
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_parameter_same_name_between_tuple_or_list():
"""
Feature: Check the names of parameters between tuple or list.
Description: If the same name exists between tuple and list, an exception will be thrown.
Expectation: Get the expected exception report.
"""
class ParamNet(Cell):
def __init__(self):
super(ParamNet, self).__init__()
self.param_tuple = (Parameter(Tensor([1], ms.float32), name="name_a"),
Parameter(Tensor([2], ms.float32)))
self.param_list = [Parameter(Tensor([3], ms.float32), name="name_a"),
Parameter(Tensor([4], ms.float32))]
def construct(self, x):
res = self.param_tuple[0] + self.param_tuple[1] + self.param_list[0] + self.param_listp[1] + x
return res
with pytest.raises(ValueError, match="its name 'name_a' already exists."):
net = ParamNet()
x = Tensor([10], ms.float32)
output = net(x)
output_expect = Tensor(20, ms.float32)
assert output == output_expect
| 34.747423
| 118
| 0.649013
| 1,761
| 13,482
| 4.758092
| 0.091993
| 0.081633
| 0.036997
| 0.074472
| 0.854159
| 0.848073
| 0.829932
| 0.804273
| 0.756415
| 0.749612
| 0
| 0.027532
| 0.229491
| 13,482
| 387
| 119
| 34.837209
| 0.779072
| 0.195668
| 0
| 0.707317
| 0
| 0
| 0.03169
| 0
| 0
| 0
| 0
| 0
| 0.060976
| 1
| 0.170732
| false
| 0
| 0.02439
| 0.04878
| 0.308943
| 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
|
8579bd8a35d7bb7e9c2054943d5165e00be45b53
| 1,099
|
py
|
Python
|
tests/highlevel/inchannel-conflict.py
|
sjdv1982/seamless
|
1b814341e74a56333c163f10e6f6ceab508b7df9
|
[
"MIT"
] | 15
|
2017-06-07T12:49:12.000Z
|
2020-07-25T18:06:04.000Z
|
tests/highlevel/inchannel-conflict.py
|
sjdv1982/seamless
|
1b814341e74a56333c163f10e6f6ceab508b7df9
|
[
"MIT"
] | 110
|
2016-06-21T23:20:44.000Z
|
2022-02-24T16:15:22.000Z
|
tests/highlevel/inchannel-conflict.py
|
sjdv1982/seamless
|
1b814341e74a56333c163f10e6f6ceab508b7df9
|
[
"MIT"
] | 6
|
2016-06-21T11:19:22.000Z
|
2019-01-21T13:45:39.000Z
|
from seamless.highlevel import Context, Cell
ctx = Context()
ctx.a = Cell("int").set(10)
ctx.c = Cell("int").set(30)
ctx.s = Cell()
ctx.translate()
ctx.s.a = ctx.a
ctx.s.c = ctx.c
ctx.ss = ctx.s
ctx.ss.celltype = "plain"
ctx.compute()
print(ctx.s.value)
print(ctx.ss.value)
ctx.s.set("NOT TO BE PRINTED")
ctx.compute()
print(ctx.s.value)
print(ctx.ss.value)
print(ctx.s.exception)
print("")
ctx.s = "NOT TO BE PRINTED 2"
ctx.s.a = ctx.a
ctx.s.c = ctx.c
ctx.compute()
print(ctx.s.value)
print(ctx.ss.value)
print(ctx.s.exception)
print("")
ctx.s.set({})
ctx.compute()
print(ctx.s.value)
print(ctx.ss.value)
print(ctx.s.exception)
print("")
ctx.b = Cell("int").set(999)
ctx.s.b = ctx.b
ctx.compute()
print(ctx.s.value)
print(ctx.ss.value)
print(ctx.s.exception)
print("")
ctx.b = None
ctx.compute()
print(ctx.s.value)
print(ctx.ss.value)
print(ctx.s.exception)
print("")
ctx.d = 123
#ctx.d.celltype = "int" ###
ctx.s.d = ctx.d
ctx.compute()
print(ctx.s.value)
print(ctx.ss.value)
print(ctx.s.exception)
print("")
ctx.d = None
ctx.compute()
print(ctx.s.value)
print(ctx.ss.value)
print(ctx.s.exception)
| 18.627119
| 44
| 0.683348
| 213
| 1,099
| 3.525822
| 0.150235
| 0.308921
| 0.203728
| 0.191744
| 0.71771
| 0.71771
| 0.71771
| 0.71771
| 0.71771
| 0.71771
| 0
| 0.011078
| 0.096451
| 1,099
| 59
| 45
| 18.627119
| 0.745217
| 0.020018
| 0
| 0.706897
| 0
| 0
| 0.046598
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.017241
| 0
| 0.017241
| 0.5
| 0
| 0
| 0
| null | 1
| 1
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 10
|
a46098d928333c780582aec75af79ba65e303377
| 9,142
|
py
|
Python
|
cowinvacc/app.py
|
anajikadam17/cowinvacc
|
e2d242409dc93f4237ae90c2daa7b658eb14d895
|
[
"MIT"
] | null | null | null |
cowinvacc/app.py
|
anajikadam17/cowinvacc
|
e2d242409dc93f4237ae90c2daa7b658eb14d895
|
[
"MIT"
] | null | null | null |
cowinvacc/app.py
|
anajikadam17/cowinvacc
|
e2d242409dc93f4237ae90c2daa7b658eb14d895
|
[
"MIT"
] | null | null | null |
import requests
import datetime
import json
import pandas as pd
from cowinvacc.getData import requests_url
class CowinAPIsData():
def States_dict(self):
data = {}
url = "https://cdn-api.co-vin.in/api/v2/admin/location/states"
state_name = requests_url(url)
for i in state_name['states']:
data.update({i['state_id']:i['state_name']})
return data
def States_df(self):
data = {}
url = "https://cdn-api.co-vin.in/api/v2/admin/location/states"
state_name = requests_url(url)
for i in state_name['states']:
data.update({i['state_id']:i['state_name']})
df = pd.DataFrame(list(zip(list(data.keys()), list(data.values()))), columns = ['state_id', 'state_name'])
return df
def States_list(self):
data = {}
url = "https://cdn-api.co-vin.in/api/v2/admin/location/states"
state_name = requests_url(url)
for i in state_name['states']:
data.update({i['state_id']:i['state_name']})
lst = list(data.values())
return lst
def Districts_df(self):
data = {}
data1 = []
for state_code in range(1,40):
url = "https://cdn-api.co-vin.in/api/v2/admin/location/districts/{}".format(state_code)
json_data = requests_url(url)
for i in json_data["districts"]:
data.update({i['district_id']:i['district_name']})
data1.append(state_code)
df = pd.DataFrame(list(zip(list(data.keys()), data1, list(data.values()))), columns = ['district_id', 'state_code', 'district_name'])
df.sort_values('district_id', ignore_index = True, inplace = True)
return df
def Districts_dict(self):
data = {}
for state_code in range(1,40):
url = "https://cdn-api.co-vin.in/api/v2/admin/location/districts/{}".format(state_code)
json_data = requests_url(url)
for i in json_data["districts"]:
data.update({i['district_id']:i['district_name']})
return data
def Districts_list(self):
data = {}
for state_code in range(1,40):
url = "https://cdn-api.co-vin.in/api/v2/admin/location/districts/{}".format(state_code)
json_data = requests_url(url)
for i in json_data["districts"]:
data.update({i['district_id']:i['district_name']})
lst = list(data.values())
return lst
def districts_id(self, distr):
ldist = distr.lower()
dist_data = CowinAPIsData.Districts_dict(self)
result = "District NOT found, search using Districts_list()."
for i in list(dist_data.values()):
if ldist in i.lower():
key_dist = list(dist_data.keys())[list(dist_data.values()).index(i)]
result = "District Code for {} is {}".format(i, key_dist)
return result
def centersBydistId(self, district_id, numdays=5):
df = pd.DataFrame(columns = ['date', 'center_id', 'name', 'address',
'state_name', 'district_name', 'block_name', 'pincode',
'from1', 'to', 'fee_type', 'available_capacity', 'min_age_limit', 'vaccine', 'slots'])
base = datetime.datetime.today()
date_list = [base + datetime.timedelta(days=x) for x in range(numdays)]
date_str = [x.strftime("%d-%m-%Y") for x in date_list]
for INP_DATE in date_str:
URL = "https://cdn-api.co-vin.in/api/v2/appointment/sessions/public/calendarByDistrict?district_id={}&date={}".format(district_id, INP_DATE)
#print(URL)
json_data = requests_url(URL)
if type(json_data)==dict:
if json_data["centers"]:
for center in json_data["centers"]:
date = center['sessions'][0]['date']
center_id = center['center_id']
name = center['name']
address = center['address']
state_name = center['state_name']
district_name = center['district_name']
block_name = center['block_name']
pincode = center['pincode']
from1 = center['from']
to = center['to']
fee_type = center['fee_type']
available_capacity = center['sessions'][0]['available_capacity']
min_age_limit = center['sessions'][0]['min_age_limit']
vaccine = center['sessions'][0]['vaccine']
slots = center['sessions'][0]['slots']
df.loc[len(df)] = [date, center_id, name, address,state_name, district_name, block_name, pincode,
from1, to, fee_type, available_capacity, min_age_limit, vaccine, slots]
else:
#print("No available slots on {}".format(INP_DATE))
date = INP_DATE
center_id = 'NA'
name = 'NA'
address = 'NA'
state_name = 'NA'
district_name = 'NA'
block_name = 'NA'
pincode = 'NA'
from1 = 'NA'
to = 'NA'
fee_type = 'NA'
available_capacity = 'NA'
min_age_limit = 'NA'
vaccine = 'NA'
slots = 'NA'
df.loc[len(df)] = [date, center_id, name, address,
state_name, district_name, block_name, pincode,
from1, to, fee_type, available_capacity, min_age_limit, vaccine, slots]
return df
def centersByPinCode(self, POST_CODE, numdays=5):
POST_CODE = str(POST_CODE)
df = pd.DataFrame(columns = ['date', 'center_id', 'name', 'address',
'state_name', 'district_name', 'block_name', 'pincode',
'from1', 'to', 'fee_type', 'available_capacity', 'min_age_limit', 'vaccine', 'slots'])
base = datetime.datetime.today()
date_list = [base + datetime.timedelta(days=x) for x in range(numdays)]
date_str = [x.strftime("%d-%m-%Y") for x in date_list]
for INP_DATE in date_str:
URL = "https://cdn-api.co-vin.in/api/v2/appointment/sessions/public/calendarByPin?pincode={}&date={}".format(POST_CODE, INP_DATE)
#print(URL)
json_data = requests_url(URL)
if type(json_data)==dict:
if json_data["centers"]:
for center in json_data["centers"]:
date = center['sessions'][0]['date']
center_id = center['center_id']
name = center['name']
address = center['address']
state_name = center['state_name']
district_name = center['district_name']
block_name = center['block_name']
pincode = center['pincode']
from1 = center['from']
to = center['to']
fee_type = center['fee_type']
available_capacity = center['sessions'][0]['available_capacity']
min_age_limit = center['sessions'][0]['min_age_limit']
vaccine = center['sessions'][0]['vaccine']
slots = center['sessions'][0]['slots']
df.loc[len(df)] = [date, center_id, name, address,state_name, district_name, block_name, pincode,
from1, to, fee_type, available_capacity, min_age_limit, vaccine, slots]
else:
#print("No available slots on {}".format(INP_DATE))
date = INP_DATE
center_id = 'NA'
name = 'NA'
address = 'NA'
state_name = 'NA'
district_name = 'NA'
block_name = 'NA'
pincode = 'NA'
from1 = 'NA'
to = 'NA'
fee_type = 'NA'
available_capacity = 'NA'
min_age_limit = 'NA'
vaccine = 'NA'
slots = 'NA'
df.loc[len(df)] = [date, center_id, name, address,
state_name, district_name, block_name, pincode,
from1, to, fee_type, available_capacity, min_age_limit, vaccine, slots]
return df
| 45.71
| 153
| 0.489061
| 967
| 9,142
| 4.427094
| 0.11789
| 0.046251
| 0.030834
| 0.026162
| 0.808456
| 0.808456
| 0.808456
| 0.808456
| 0.793506
| 0.775753
| 0
| 0.00752
| 0.389083
| 9,142
| 199
| 154
| 45.939698
| 0.758997
| 0.013126
| 0
| 0.815476
| 0
| 0.047619
| 0.17162
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.053571
| false
| 0
| 0.029762
| 0
| 0.142857
| 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
|
f109ef8a01bd636010e4919561f8d657e41d3830
| 22,328
|
py
|
Python
|
tests/test_items.py
|
fastly/fastly-blocklist
|
a286c547e3bf020c66a04b214d49164a570c362a
|
[
"MIT"
] | 4
|
2020-02-11T17:21:45.000Z
|
2021-06-15T14:19:54.000Z
|
tests/test_items.py
|
fastly/fastly-blocklist
|
a286c547e3bf020c66a04b214d49164a570c362a
|
[
"MIT"
] | null | null | null |
tests/test_items.py
|
fastly/fastly-blocklist
|
a286c547e3bf020c66a04b214d49164a570c362a
|
[
"MIT"
] | 5
|
2020-02-25T15:16:26.000Z
|
2022-03-29T19:30:50.000Z
|
'''
Test managing list items with lib Items()
'''
import unittest
import os
import argparse
import time
from lib import Environment, Lists, Items
class ItemTests(unittest.TestCase):
'''
Test managing list items with Items()
'''
def setUp(self):
with open('tests.apikey', 'w') as file_apikey:
file_apikey.write('fastly_token: APIKEY')
self.args = argparse.Namespace(
init=True,
apikey='tests.apikey',
config='tests.blocklist',
service=['SERVICEID'],
log='',
block='',
force=False,
verbose=False
)
def tearDown(self):
try:
os.remove('tests.apikey')
os.remove('tests.blocklist')
os.remove('tests.items')
except BaseException:
pass
def test_add_item_bad(self):
'''
try to add an item where no args.item or args.file provided
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'var'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = 'var.whatever'
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = []
self.args.file = None
# create a new config file
env = Environment(self.args)
Lists(self.args, env)
with self.assertRaisesRegex(
SystemExit,
"add requires list items"
):
Items(self.args, env)
def test_add_geo(self):
'''
try to add a valid new item to geo list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'geo'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['US']
self.args.file = None
# create a new config file
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.assertEqual(
env.config['lists'][0]['items'][0]['US'],
'fastly-blocklist'
)
def test_add_geo_file(self):
'''
try to add a valid new item to geo list from args.file
'''
with open('tests.items', 'w') as file_items:
file_items.writelines(['US', '\n', 'RU'])
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'geo'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = []
self.args.file = 'tests.items'
# create a new config file
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.assertEqual(
len(env.config['lists'][0]['items']),
2
)
def test_add_geo_bad(self):
'''
try to add an invalid new item to geo list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'geo'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['United States of America']
self.args.file = None
# create a new config file
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
def test_add_geo_file_bad(self):
'''
try to add itemss to geo list from args.file that doesn't exist
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'geo'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = []
self.args.file = 'tests.items'
# create new environment
env = Environment(self.args)
Lists(self.args, env)
with self.assertRaisesRegex(
SystemExit,
"could not read items from file"
):
Items(self.args, env)
def test_add_geo_duplicate(self):
'''
try to add a duplicate item to geo list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'geo'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['US']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.init = False
self.args.new = False
Items(self.args, env)
self.assertEqual(
len(env.config['lists'][0]['items']),
1
)
def test_add_block_v4(self):
'''
try to add a valid IPv4 item to block list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['!10.0.0.0/8']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.assertEqual(
env.config['lists'][0]['items'][0],
'!10.0.0.0/8'
)
def test_add_block_v6(self):
'''
try to add a valid new IPv6 item to block list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['2a04:4e42:0010:0000:0000:0000:0000:0313']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.assertEqual(
env.config['lists'][0]['items'][0],
'2a04:4e42:10::313/128'
)
def test_add_block_bad(self):
'''
try to add an invalid new item to block list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['867-5309']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
def test_add_block_duplicate(self):
'''
try to add a duplicate item to block list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['!10.0.0.0/8']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.init = False
self.args.new = False
Items(self.args, env)
self.assertEqual(
len(env.config['lists'][0]['items']),
1
)
def test_add_temp(self):
'''
try to add a valid new item to temp list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'temp'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = 600
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['10.0.0.1']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
expiration_time = int(time.time()) + self.args.block_length
Items(self.args, env)
self.assertTrue(env.config['lists'][0]['items'][0]['10.0.0.1'])
self.assertEqual(
env.config['lists'][0]['items'][0]['10.0.0.1'],
expiration_time
)
def test_add_temp_bad(self):
'''
try to add an invalid new item to temp list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'temp'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = 600
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['867-5309']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
def test_add_var(self):
'''
try to add a valid new item to var list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'var'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = 'var.whatever'
self.args.block_length = 600
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['ABC']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.assertEqual(
env.config['lists'][0]['items'][0]['ABC'],
'fastly-blocklist'
)
def test_add_combo(self):
'''
try to add a valid new combo list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['LIST1', 'LIST2']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = None
self.args.variable = None
self.args.block_length = 600
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['!10.0.0.0/8']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.list = ['COMBO']
self.args.type = 'combo'
self.args.item = ['LIST1', 'LIST2']
Lists(self.args, env)
Items(self.args, env)
self.assertEqual(
len(env.config['lists'][2]['items']),
2
)
def test_add_combo_bad(self):
'''
try to add an invalid new combo list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['LIST1', 'LIST2']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = None
self.args.variable = None
self.args.block_length = 600
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['!10.0.0.0/8']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.list = ['COMBO']
self.args.type = 'combo'
self.args.item = ['CALM', 'DOWN']
Lists(self.args, env)
Items(self.args, env)
self.assertFalse(env.config['lists'][2]['items'])
def test_remove_item_bad(self):
'''
try to remove item when no args.item or args.file provided
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = False
self.args.remove = True
self.args.clean = False
self.args.removeall = False
self.args.item = []
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
with self.assertRaisesRegex(
SystemExit,
"remove requires list items"
):
Items(self.args, env)
def test_remove_geo(self):
'''
try to remove item from geo list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'geo'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['US']
self.args.file = None
# create a new config file
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.add = False
self.args.remove = True
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
def test_remove_geo_bad(self):
'''
try to remove item that doesn't exist from geo list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'geo'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['US']
self.args.file = None
# create a new config file
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.add = False
self.args.remove = True
self.args.item = ['United States of America']
Items(self.args, env)
self.assertTrue(env.config['lists'][0]['items'])
def test_remove_block(self):
'''
try to remove item from block list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['!10.0.0.0/8']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.add = False
self.args.remove = True
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
def test_remove_block_bad(self):
'''
try to remove item that doesn't exist from block list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['!10.0.0.0/8']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.add = False
self.args.remove = True
self.args.item = ['127.0.0.1']
Items(self.args, env)
self.assertTrue(env.config['lists'][0]['items'])
def test_clean(self):
'''
try to clean expired items from all temp lists
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'temp'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = 600
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['10.0.0.1']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
force_expiration_time = int(time.time()) - self.args.block_length
env.config['lists'][0]['items'][0]['10.0.0.1'] = force_expiration_time
self.args.add = False
self.args.list = []
self.args.clean = True
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
def test_clean_list(self):
'''
try to clean expired items from a specific temp list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'temp'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = 600
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['10.0.0.1']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
force_expiration_time = int(time.time()) - self.args.block_length
env.config['lists'][0]['items'][0]['10.0.0.1'] = force_expiration_time
self.args.add = False
self.args.clean = True
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
def test_removeall(self):
'''
try to remove all items from all lists
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['!10.0.0.1/8']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.add = False
self.args.list = []
self.args.removeall = True
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
def test_removeall_list(self):
'''
try to remove all items from a specific list
'''
self.args.new = True
self.args.delete = False
self.args.list = ['a_new_list']
self.args.type = 'block'
self.args.action = 'block'
self.args.match = 'exact'
self.args.variable = None
self.args.block_length = None
self.args.add = True
self.args.remove = False
self.args.clean = False
self.args.removeall = False
self.args.item = ['!10.0.0.1/8']
self.args.file = None
# create a new environment
env = Environment(self.args)
Lists(self.args, env)
Items(self.args, env)
self.args.add = False
self.args.removeall = True
Items(self.args, env)
self.assertFalse(env.config['lists'][0]['items'])
if __name__ == '__main__':
unittest.main()
| 27.163017
| 78
| 0.542279
| 2,795
| 22,328
| 4.276565
| 0.048658
| 0.305865
| 0.115285
| 0.049527
| 0.932904
| 0.91751
| 0.906802
| 0.890488
| 0.884715
| 0.863382
| 0
| 0.014824
| 0.335319
| 22,328
| 821
| 79
| 27.196102
| 0.79058
| 0.079273
| 0
| 0.851658
| 0
| 0
| 0.072144
| 0.003006
| 0
| 0
| 0
| 0
| 0.04363
| 1
| 0.045375
| false
| 0.001745
| 0.008726
| 0
| 0.055846
| 0
| 0
| 0
| 0
| null | 1
| 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
| 8
|
74b2e2b74df7b92be04eea8fabd1d614fcaad781
| 378
|
py
|
Python
|
mock_master/models.py
|
kpekepoh/django-aww
|
f18dc11474b856bd70bb8dbc3acf39be6ea881d0
|
[
"MIT"
] | null | null | null |
mock_master/models.py
|
kpekepoh/django-aww
|
f18dc11474b856bd70bb8dbc3acf39be6ea881d0
|
[
"MIT"
] | 7
|
2015-01-19T07:25:33.000Z
|
2015-01-20T02:04:34.000Z
|
mock_master/models.py
|
kpekepoh/django-aww
|
f18dc11474b856bd70bb8dbc3acf39be6ea881d0
|
[
"MIT"
] | null | null | null |
from django.db import models
class One(models.Model):
name = models.CharField(max_length=100)
class Two(models.Model):
name = models.CharField(max_length=100)
number = models.IntegerField(null=True, blank=True, default=0)
class Three(models.Model):
name = models.CharField(max_length=100)
number = models.IntegerField(null=True, blank=True, default=0)
| 23.625
| 66
| 0.732804
| 53
| 378
| 5.169811
| 0.415094
| 0.120438
| 0.164234
| 0.229927
| 0.817518
| 0.817518
| 0.817518
| 0.817518
| 0.664234
| 0.664234
| 0
| 0.034056
| 0.145503
| 378
| 15
| 67
| 25.2
| 0.814241
| 0
| 0
| 0.555556
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.111111
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 7
|
74d9eaeae4fd24f507aa23368bd29f8c2e8b671c
| 115
|
py
|
Python
|
montepython/likelihoods/cosmic_clocks_2017/__init__.py
|
ClaudioNahmad/montepython-kauyumari
|
adae25120f4cdf3719b356c790ba5c0193964265
|
[
"MIT"
] | null | null | null |
montepython/likelihoods/cosmic_clocks_2017/__init__.py
|
ClaudioNahmad/montepython-kauyumari
|
adae25120f4cdf3719b356c790ba5c0193964265
|
[
"MIT"
] | null | null | null |
montepython/likelihoods/cosmic_clocks_2017/__init__.py
|
ClaudioNahmad/montepython-kauyumari
|
adae25120f4cdf3719b356c790ba5c0193964265
|
[
"MIT"
] | null | null | null |
from montepython.likelihood_class import Likelihood_clocks
class cosmic_clocks_2017(Likelihood_clocks):
pass
| 19.166667
| 58
| 0.852174
| 14
| 115
| 6.642857
| 0.642857
| 0.344086
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.039216
| 0.113043
| 115
| 5
| 59
| 23
| 0.872549
| 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
| 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
| 1
| 1
| 0
| 1
| 0
|
0
| 7
|
2d0e59d023e99be0048e1b6ae35b8ae5d32b3d19
| 98
|
py
|
Python
|
pytik/__init__.py
|
thengo1/pytok
|
7ff35cba2acf751651796ef3e3025d4252839093
|
[
"MIT"
] | 1
|
2020-11-30T18:23:08.000Z
|
2020-11-30T18:23:08.000Z
|
pytik/__init__.py
|
thengo1/pytik
|
7ff35cba2acf751651796ef3e3025d4252839093
|
[
"MIT"
] | 13
|
2020-11-30T17:46:24.000Z
|
2020-12-14T06:06:37.000Z
|
pytik/__init__.py
|
thengo1/pytok
|
7ff35cba2acf751651796ef3e3025d4252839093
|
[
"MIT"
] | null | null | null |
from pytik.tiktok import TikTok
from pytik.tiktok import extract
from pytik.tiktok import request
| 24.5
| 32
| 0.846939
| 15
| 98
| 5.533333
| 0.4
| 0.325301
| 0.542169
| 0.759036
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.122449
| 98
| 3
| 33
| 32.666667
| 0.965116
| 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
|
2d13ac90034bf14e11a4bf0cd444833993403b24
| 2,922
|
py
|
Python
|
tests/test_build_tools.py
|
practicalci/practci
|
47d0600918762373992da0ba067dbb84a3e4d633
|
[
"BSD-3-Clause"
] | null | null | null |
tests/test_build_tools.py
|
practicalci/practci
|
47d0600918762373992da0ba067dbb84a3e4d633
|
[
"BSD-3-Clause"
] | null | null | null |
tests/test_build_tools.py
|
practicalci/practci
|
47d0600918762373992da0ba067dbb84a3e4d633
|
[
"BSD-3-Clause"
] | null | null | null |
import os
import shutil
import unittest
from practci import build_tools
from practci.build_tools import BuildToolType, BuildTarget, BuildType
from practci import toolchains
from tests.project_templates import cmake as cmake_template
class TestBuildTool(unittest.TestCase):
def test_get_build_tool(self):
build_tool = build_tools.get_build_tool(BuildToolType.CMAKE)
self.assertIsNotNone(build_tool)
def test_build_setup_cmake(self):
build_tool = build_tools.get_build_tool(BuildToolType.CMAKE)
template_project_root_dir = os.path.dirname(cmake_template.__file__)
toolchain = toolchains.get_tool_chain('native/identity', template_project_root_dir)
build_tool.setup(project_root_dir=template_project_root_dir, toolchain=toolchain, build_type=BuildType.DEBUG,
)
build_dir = os.path.join(template_project_root_dir, 'build')
self.assertTrue(os.path.exists(build_dir))
self.assertTrue(os.path.isdir(build_dir))
shutil.rmtree(build_dir)
def test_build_purge_cmake(self):
build_tool = build_tools.get_build_tool(BuildToolType.CMAKE)
template_project_root_dir = os.path.dirname(cmake_template.__file__)
toolchain = toolchains.get_tool_chain('native/identity', template_project_root_dir)
build_dir = os.path.join(template_project_root_dir, 'build')
install_dir = os.path.join(template_project_root_dir, 'install')
build_tool.setup(project_root_dir=template_project_root_dir, toolchain=toolchain, build_type=BuildType.DEBUG)
self.assertTrue(os.path.exists(build_dir))
self.assertTrue(os.path.exists(install_dir))
build_tool.purge(project_root_dir=template_project_root_dir, toolchain=toolchain)
build_dir = os.path.join(template_project_root_dir, 'build', toolchain.get_name())
install_dir = os.path.join(template_project_root_dir, 'install', toolchain.get_name())
self.assertFalse(os.path.exists(build_dir))
self.assertFalse(os.path.exists(install_dir))
def test_build_purge__all_cmake(self):
build_tool = build_tools.get_build_tool(BuildToolType.CMAKE)
template_project_root_dir = os.path.dirname(cmake_template.__file__)
toolchain = toolchains.get_tool_chain('native/identity', template_project_root_dir)
build_dir = os.path.join(template_project_root_dir, 'build')
install_dir = os.path.join(template_project_root_dir, 'install')
build_tool.setup(project_root_dir=template_project_root_dir, toolchain=toolchain, build_type=BuildType.DEBUG)
self.assertTrue(os.path.exists(build_dir))
self.assertTrue(os.path.exists(install_dir))
build_tool.purge_all(project_root_dir=template_project_root_dir)
self.assertFalse(os.path.exists(build_dir))
self.assertFalse(os.path.exists(install_dir))
| 35.634146
| 117
| 0.749829
| 385
| 2,922
| 5.303896
| 0.127273
| 0.123898
| 0.157689
| 0.193928
| 0.821254
| 0.803134
| 0.803134
| 0.785504
| 0.785504
| 0.785504
| 0
| 0
| 0.161191
| 2,922
| 81
| 118
| 36.074074
| 0.833129
| 0
| 0
| 0.553191
| 0
| 0
| 0.029442
| 0
| 0
| 0
| 0
| 0
| 0.234043
| 1
| 0.085106
| false
| 0
| 0.148936
| 0
| 0.255319
| 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
|
2d25245b283bb208dc833a10465d26514bd905c1
| 112
|
py
|
Python
|
line_bot/models/__init__.py
|
Ukyo-m/HairSalon-Reserve-LineBot
|
f58b70c78254dac1d0bdc2739a21536dba59d4ba
|
[
"Unlicense"
] | 2
|
2021-09-26T17:17:42.000Z
|
2021-09-26T17:17:45.000Z
|
line_bot/models/__init__.py
|
Ukyo-m/HairSalon-Reserve-LineBot
|
f58b70c78254dac1d0bdc2739a21536dba59d4ba
|
[
"Unlicense"
] | null | null | null |
line_bot/models/__init__.py
|
Ukyo-m/HairSalon-Reserve-LineBot
|
f58b70c78254dac1d0bdc2739a21536dba59d4ba
|
[
"Unlicense"
] | null | null | null |
from line_bot.models.user import *
from line_bot.models.staff import *
from line_bot.models.reservation import *
| 37.333333
| 41
| 0.821429
| 18
| 112
| 4.944444
| 0.444444
| 0.269663
| 0.370787
| 0.573034
| 0.516854
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.098214
| 112
| 3
| 41
| 37.333333
| 0.881188
| 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
|
741055412558ce5389bb87bcd7a92b6c21500477
| 409,475
|
py
|
Python
|
data/election88.py
|
davmre/autoreparam
|
c25340f272209278d336627cca42e139c0e4c961
|
[
"Apache-2.0"
] | 32
|
2019-06-10T16:51:14.000Z
|
2022-03-08T14:14:25.000Z
|
data/election88.py
|
davmre/autoreparam
|
c25340f272209278d336627cca42e139c0e4c961
|
[
"Apache-2.0"
] | null | null | null |
data/election88.py
|
davmre/autoreparam
|
c25340f272209278d336627cca42e139c0e4c961
|
[
"Apache-2.0"
] | 3
|
2019-06-11T16:36:40.000Z
|
2019-10-03T02:25:41.000Z
|
data = {
"N": 11566,
"y": [1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0,
1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1,
0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1,
1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0,
1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0,
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1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0,
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1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1,
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1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1,
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1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1,
0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0,
1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1,
1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1,
0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1,
0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0,
1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1,
0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1,
0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1,
0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1,
1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0,
1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1,
1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0,
0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1,
1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1,
0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1,
0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0,
0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1,
0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1,
1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0,
1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1,
1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1,
0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0,
0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1,
1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1,
0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1,
0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0,
1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1,
0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0,
0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0,
1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0,
1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1,
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1,
0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1,
0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0,
0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0,
0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1,
1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0,
0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0,
0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1,
1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0,
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0,
0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0,
1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1,
1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1,
0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0,
1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1,
1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0,
0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1,
1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0,
0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1,
0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1,
1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1,
0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1,
1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0,
1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0,
0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1,
0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0,
1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1,
1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0,
1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1,
1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1,
0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1,
0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1,
1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1,
0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0,
0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1,
1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0,
1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1,
1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1,
0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0,
0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1,
0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0,
0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1,
0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1,
1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1,
1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0,
0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1,
0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1,
0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1,
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1,
0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1,
0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0,
0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0,
0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1,
1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0,
0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0,
0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1,
1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0,
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0,
0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0,
1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1,
1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1,
0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0,
1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1,
1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0,
0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1,
1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0,
0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1,
0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1,
1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1,
0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1,
1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0,
1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0,
0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1,
0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0,
1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1,
1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0,
0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0,
1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0,
1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1,
1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1,
1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0,
1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1,
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1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1,
0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1,
1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1,
1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1,
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1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1,
1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0,
0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0,
0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1,
1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1,
0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1,
0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1,
0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1,
1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1,
1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1,
1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1,
1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1,
0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1,
0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1,
0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0,
1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0,
0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1,
0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1,
0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1,
0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1,
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0,
0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1,
1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0,
0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1,
0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1,
1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1,
1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0,
0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1,
0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1,
1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1,
0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0,
1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1,
1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0,
1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0,
1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0,
1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0,
1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0,
1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1,
0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1,
0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1,
0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0,
1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1,
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1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1,
1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0,
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0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1,
0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1,
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0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1,
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1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1,
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1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1,
1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1,
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1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1,
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1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1,
1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1,
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0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1,
1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1,
1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0,
0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0,
0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1,
0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0,
0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1,
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1,
0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0,
1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1,
0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0,
1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0,
0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1,
0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0,
0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1,
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0,
0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1,
0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1,
1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1,
1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1,
1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1,
0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0,
0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0,
0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1,
1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0,
1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0,
0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1,
0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0,
1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1,
1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,
1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0,
0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0,
1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0,
1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0,
0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0,
1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0,
0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,
0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1,
1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1,
1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1,
1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0,
1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1,
1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1,
0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1,
1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0,
1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1,
1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1,
1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1,
0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1,
1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1,
1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1,
0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1,
1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1,
1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1,
1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1,
1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0,
0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1,
0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1,
0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0,
0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1,
1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0,
0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1,
0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1,
1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1,
1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0,
1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1,
1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1,
1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1,
1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0,
1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1,
0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0,
0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0,
1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1,
0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1,
0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0,
0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1,
0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0,
1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,
1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1,
1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1,
1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1,
1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0,
1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1,
1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1,
1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1,
1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1,
1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1,
1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0,
1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1,
0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0,
0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1,
1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0,
1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0,
1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0,
0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1,
1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1,
0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0,
0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1,
0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0,
0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1,
1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0,
1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1,
1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1,
1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1,
0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
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0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1,
0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1,
1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,
1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1,
1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1,
1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0,
0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1,
1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1,
1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0,
0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1,
0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1,
1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1,
1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1,
0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0,
1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0,
0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0,
1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1,
0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,
0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0,
0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0,
1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1,
1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1,
1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1,
0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,
1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0,
1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1,
1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1,
0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1,
1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1,
0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1,
1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1,
1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0,
0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1,
1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1,
1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1,
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0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0,
1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1,
1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1,
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1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1,
0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0,
0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0,
0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1,
0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1,
1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0,
1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0,
1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0,
0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1,
0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1,
1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1,
1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1,
0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1,
1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1,
1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0,
1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1,
1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1,
1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1,
0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1,
1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0,
1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0,
0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1,
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1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0,
1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0,
0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1,
1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0,
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1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1,
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0,
0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0,
1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0,
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0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0,
0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0,
0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1,
1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1,
1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1,
1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1,
1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0,
0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1,
0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1,
0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0,
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0,
1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1,
0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1,
0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0,
0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0,
1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0,
1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1,
0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1,
1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0,
1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1,
1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0,
1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0,
1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0,
1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1,
0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0,
0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1,
1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1,
1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1,
1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1,
1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1,
0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0,
1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1,
1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1,
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1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1,
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1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1,
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1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1,
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1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1,
1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1,
0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0,
0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1,
1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1,
1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1,
1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1,
0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1,
0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1,
0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0,
1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0,
0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0,
1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1,
0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0,
1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1,
0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0,
0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1,
1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1,
0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0,
1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1,
0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1,
1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0,
0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1,
0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1,
1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0,
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1,
1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0,
0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0,
1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0,
1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0,
1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1,
0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1,
1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0,
1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0,
1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1,
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1,
0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1,
1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0,
1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1,
1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1,
0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1,
1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0,
1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0,
0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1,
1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1,
1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0,
0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1,
1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0,
0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1,
1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1,
0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0,
1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1,
0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1,
1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0,
0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0,
1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1,
0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1,
1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1,
0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1,
0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0,
0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1,
0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1,
0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1,
1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1,
0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1,
1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1,
1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0,
0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1,
0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1,
0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0,
0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0,
1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0,
1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1,
1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1,
1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1,
1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0,
0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1,
1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0,
1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1,
0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1,
1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1,
1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1,
1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1,
1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1,
1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1,
1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0,
1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1,
1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0,
1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1,
1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1,
1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1,
1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0,
1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1,
1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0,
1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1,
0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1,
0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0,
0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1,
0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1,
0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0,
1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0,
1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1,
1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0,
0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0,
1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0,
0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0,
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0,
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1,
1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1,
0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1,
0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1,
0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1,
1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0,
1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1,
0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1,
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1,
1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0,
0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1,
0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0,
1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1,
0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1,
0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0,
0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1,
1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0,
0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0,
1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1,
1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1,
1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0,
1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1,
1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0,
0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1,
0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0,
0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0,
1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0,
0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1,
0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1,
0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0,
0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0,
1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0,
0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1,
1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1,
0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1,
0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1,
1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0,
1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1,
1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1,
0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1,
1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1,
0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0,
1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0,
0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1,
0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0,
0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1,
0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0,
1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1,
1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1,
1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0,
1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0,
0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1,
1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1,
0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0,
1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1,
0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1,
1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0,
1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0,
1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1,
1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0,
0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1,
1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0,
1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0,
1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1,
0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0,
1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0,
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0,
1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0,
1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0,
0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1,
0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0,
1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1,
0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1,
1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0,
1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0,
1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1,
0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0,
1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0,
1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1,
1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1,
1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0,
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1,
1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0,
1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0,
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0,
0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1,
1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0,
1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0,
1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0,
0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1,
0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0,
1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1,
1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0,
0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1,
1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1,
1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1,
1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1,
0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0,
1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1,
1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1,
1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1,
0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1,
1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0,
1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1,
1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1,
0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0,
0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1,
0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0,
0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1,
1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0,
0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1,
0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1,
1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0,
0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0,
1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1,
0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1,
1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1,
1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1,
1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1,
1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1,
1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0,
0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0,
0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1,
0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0,
1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1,
1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0,
1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0,
1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1,
0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0,
1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0,
1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0,
0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1,
1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1,
1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0,
1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1,
1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1,
1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1,
0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1,
1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0,
0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1,
1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1,
0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1,
1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0,
1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,
0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0,
1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1,
0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0,
0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1,
0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1,
1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0,
1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1,
1, 1, 0, 1, 0, 1, 1, 1, 0, 1],
"age": [2, 3, 1, 2, 1, 2, 3, 2, 2, 3, 1, 1, 3, 3, 2, 3, 3, 2,
2, 2, 4, 2, 4, 2, 2, 4, 2, 2, 2, 3, 3, 3, 4, 2, 4, 3,
2, 2, 3, 3, 1, 3, 1, 2, 1, 2, 3, 3, 1, 3, 1, 1, 2, 2,
2, 3, 2, 2, 1, 4, 4, 2, 2, 2, 1, 3, 2, 4, 4, 2, 2, 3,
3, 1, 1, 2, 3, 2, 3, 1, 2, 1, 1, 3, 2, 2, 4, 4, 3, 3,
1, 3, 2, 3, 2, 1, 1, 2, 2, 3, 1, 1, 1, 3, 2, 3, 3, 1,
2, 1, 3, 1, 2, 4, 3, 3, 1, 2, 1, 1, 1, 4, 1, 2, 1, 2,
2, 2, 1, 4, 1, 3, 3, 2, 2, 4, 1, 3, 3, 4, 1, 2, 2, 3,
2, 2, 3, 3, 1, 2, 2, 2, 3, 2, 3, 1, 1, 2, 2, 2, 3, 2,
3, 2, 4, 2, 3, 2, 1, 1, 1, 4, 4, 2, 1, 2, 2, 4, 3, 2,
3, 1, 2, 4, 3, 2, 1, 3, 3, 2, 2, 1, 2, 2, 3, 3, 3, 1,
4, 2, 2, 3, 4, 3, 2, 2, 3, 3, 2, 2, 3, 1, 1, 1, 2, 1,
3, 3, 4, 2, 1, 1, 1, 3, 3, 1, 3, 2, 1, 2, 1, 2, 3, 4,
3, 3, 3, 4, 3, 1, 4, 3, 4, 3, 4, 3, 2, 3, 3, 1, 4, 3,
2, 1, 4, 4, 3, 2, 3, 1, 1, 4, 3, 3, 3, 4, 1, 1, 1, 1,
2, 1, 3, 3, 2, 2, 4, 3, 2, 2, 2, 2, 4, 3, 2, 1, 1, 4,
2, 2, 3, 2, 2, 3, 2, 3, 2, 1, 1, 4, 4, 2, 2, 2, 1, 3,
1, 3, 3, 2, 1, 1, 2, 3, 4, 1, 1, 2, 2, 2, 3, 2, 2, 3,
1, 4, 3, 1, 2, 3, 2, 3, 1, 3, 1, 2, 2, 2, 1, 1, 3, 1,
3, 2, 2, 2, 2, 1, 2, 2, 3, 2, 4, 2, 1, 3, 1, 2, 2, 4,
4, 4, 2, 2, 2, 1, 2, 1, 4, 1, 3, 3, 2, 3, 3, 2, 4, 2,
2, 2, 4, 1, 1, 3, 2, 2, 4, 3, 4, 2, 2, 1, 1, 3, 2, 2,
2, 3, 2, 2, 3, 3, 2, 2, 3, 2, 3, 2, 1, 2, 2, 3, 3, 1,
3, 2, 1, 1, 1, 3, 2, 3, 4, 3, 2, 3, 2, 2, 1, 2, 1, 2,
2, 3, 2, 3, 1, 2, 2, 2, 3, 4, 2, 4, 3, 4, 2, 3, 4, 1,
2, 1, 2, 4, 3, 2, 3, 4, 2, 2, 3, 3, 4, 2, 2, 2, 1, 3,
2, 4, 1, 4, 4, 1, 3, 1, 3, 2, 2, 3, 1, 3, 1, 2, 1, 3,
4, 2, 1, 1, 3, 2, 1, 2, 1, 3, 2, 4, 3, 3, 2, 2, 3, 4,
1, 2, 2, 4, 2, 3, 1, 3, 2, 1, 2, 2, 1, 3, 2, 3, 2, 3,
2, 2, 1, 3, 2, 3, 3, 2, 2, 1, 1, 3, 4, 3, 3, 2, 3, 2,
2, 3, 3, 2, 2, 2, 2, 2, 3, 3, 2, 2, 1, 4, 2, 3, 2, 2,
2, 2, 1, 2, 3, 1, 3, 2, 2, 4, 3, 3, 2, 1, 3, 1, 3, 3,
2, 3, 1, 2, 2, 4, 2, 1, 3, 3, 3, 3, 3, 2, 2, 2, 3, 2,
2, 4, 2, 3, 3, 3, 2, 1, 1, 4, 3, 3, 2, 3, 2, 4, 4, 1,
4, 1, 2, 2, 3, 3, 3, 3, 4, 2, 1, 4, 1, 3, 2, 2, 3, 1,
2, 4, 2, 3, 2, 1, 1, 3, 1, 1, 3, 1, 3, 3, 4, 1, 3, 1,
2, 3, 2, 1, 2, 1, 4, 3, 2, 2, 3, 2, 1, 2, 3, 2, 3, 2,
3, 1, 2, 3, 2, 1, 1, 3, 4, 1, 3, 3, 2, 1, 4, 3, 2, 3,
4, 2, 1, 4, 1, 3, 2, 2, 3, 4, 2, 2, 1, 2, 3, 3, 3, 2,
3, 3, 4, 1, 2, 2, 1, 2, 4, 2, 2, 3, 4, 3, 3, 2, 3, 2,
1, 4, 2, 4, 2, 1, 1, 2, 1, 3, 1, 4, 2, 2, 2, 2, 2, 1,
3, 2, 1, 1, 3, 2, 1, 1, 4, 2, 3, 2, 3, 2, 1, 2, 2, 3,
1, 1, 2, 2, 3, 2, 1, 1, 3, 2, 4, 3, 2, 2, 3, 3, 3, 4,
4, 3, 2, 3, 2, 3, 4, 1, 1, 2, 2, 4, 2, 1, 4, 1, 2, 3,
4, 2, 3, 3, 3, 4, 1, 2, 2, 2, 2, 4, 2, 1, 3, 1, 3, 1,
2, 1, 2, 1, 3, 2, 2, 1, 3, 4, 2, 1, 3, 2, 4, 2, 1, 3,
1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 2, 2, 2, 1, 2, 3, 1, 2,
3, 1, 1, 2, 3, 2, 2, 4, 4, 3, 2, 3, 3, 3, 3, 3, 1, 1,
1, 3, 2, 2, 3, 4, 4, 3, 1, 3, 4, 1, 1, 3, 4, 2, 1, 2,
2, 1, 2, 1, 4, 1, 2, 2, 3, 3, 3, 4, 2, 1, 1, 4, 2, 1,
3, 4, 4, 2, 4, 3, 4, 4, 2, 3, 2, 4, 2, 4, 3, 3, 3, 4,
1, 2, 2, 2, 4, 2, 4, 2, 1, 3, 2, 2, 2, 4, 3, 3, 2, 4,
2, 4, 2, 4, 2, 4, 2, 1, 3, 4, 3, 4, 3, 2, 4, 2, 2, 3,
3, 3, 4, 2, 3, 3, 2, 1, 2, 4, 3, 3, 3, 2, 4, 4, 3, 2,
2, 2, 2, 3, 2, 1, 1, 1, 2, 2, 2, 1, 1, 2, 2, 4, 1, 1,
2, 3, 2, 1, 2, 4, 3, 2, 1, 2, 3, 4, 1, 3, 3, 2, 1, 2,
1, 3, 3, 4, 3, 1, 2, 1, 3, 1, 4, 1, 2, 2, 1, 3, 1, 3,
2, 3, 2, 3, 2, 2, 2, 2, 3, 2, 2, 1, 2, 3, 2, 4, 2, 1,
1, 4, 3, 1, 3, 3, 3, 2, 4, 4, 3, 3, 4, 2, 1, 2, 3, 3,
2, 2, 2, 2, 3, 1, 4, 2, 4, 3, 3, 4, 4, 3, 3, 2, 4, 2,
4, 3, 4, 4, 3, 2, 3, 1, 4, 1, 4, 2, 1, 3, 4, 2, 1, 2,
1, 1, 1, 2, 2, 2, 1, 4, 1, 1, 4, 3, 1, 2, 2, 3, 2, 2,
2, 1, 2, 2, 2, 4, 3, 3, 1, 3, 1, 4, 4, 3, 3, 3, 1, 1,
4, 2, 4, 1, 4, 3, 1, 2, 1, 2, 3, 3, 3, 1, 1, 3, 3, 1,
2, 4, 1, 3, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 3, 3, 4, 4,
4, 3, 4, 1, 2, 2, 1, 3, 3, 1, 4, 3, 2, 3, 1, 2, 3, 4,
2, 1, 4, 2, 4, 3, 1, 2, 1, 2, 3, 4, 2, 2, 2, 1, 1, 4,
2, 2, 3, 3, 4, 3, 1, 1, 2, 4, 2, 1, 2, 2, 3, 2, 1, 2,
2, 2, 4, 3, 1, 1, 2, 1, 1, 1, 2, 1, 3, 1, 3, 1, 1, 1,
1, 1, 1, 1, 3, 2, 2, 3, 3, 3, 3, 2, 1, 3, 2, 3, 4, 4,
2, 2, 1, 4, 1, 4, 2, 1, 2, 2, 3, 3, 1, 2, 3, 2, 3, 1,
2, 1, 4, 2, 2, 2, 2, 3, 1, 1, 3, 2, 3, 2, 3, 2, 2, 2,
3, 4, 2, 2, 1, 1, 2, 3, 2, 2, 2, 2, 3, 3, 4, 3, 3, 2,
1, 3, 1, 1, 2, 1, 4, 4, 3, 2, 1, 2, 1, 4, 2, 3, 1, 2,
1, 1, 1, 4, 2, 2, 1, 1, 2, 1, 3, 2, 2, 1, 2, 2, 3, 2,
1, 3, 2, 2, 1, 3, 1, 2, 3, 2, 3, 1, 3, 1, 1, 1, 4, 2,
2, 2, 2, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 3, 2, 3, 1, 2,
2, 3, 3, 2, 4, 1, 1, 2, 1, 4, 3, 2, 2, 2, 3, 2, 2, 2,
4, 3, 3, 1, 3, 3, 2, 3, 4, 1, 1, 1, 3, 4, 3, 2, 4, 4,
2, 2, 1, 4, 3, 4, 3, 3, 3, 3, 2, 2, 3, 3, 2, 3, 4, 2,
3, 3, 2, 2, 3, 4, 2, 1, 4, 2, 1, 4, 2, 2, 2, 1, 2, 2,
1, 2, 3, 4, 2, 2, 3, 3, 4, 2, 2, 2, 1, 3, 2, 4, 1, 4,
4, 1, 3, 1, 3, 2, 2, 3, 1, 3, 1, 2, 1, 3, 4, 2, 1, 1,
3, 2, 1, 2, 1, 3, 2, 4, 3, 3, 2, 2, 3, 4, 1, 2, 2, 4,
2, 3, 1, 3, 2, 1, 2, 2, 1, 3, 2, 3, 2, 3, 2, 2, 1, 3,
2, 3, 3, 2, 2, 1, 1, 3, 4, 3, 3, 2, 3, 2, 2, 3, 3, 2,
2, 2, 2, 2, 3, 3, 2, 2, 1, 4, 2, 3, 2, 2, 2, 2, 1, 2,
3, 1, 3, 2, 2, 4, 3, 3, 2, 1, 3, 1, 3, 3, 2, 3, 1, 2,
2, 4, 2, 1, 3, 3, 3, 3, 3, 2, 2, 2, 3, 2, 2, 4, 2, 3,
3, 3, 2, 1, 1, 4, 3, 3, 2, 3, 2, 4, 4, 1, 4, 1, 2, 2,
3, 3, 3, 3, 4, 2, 1, 4, 1, 3, 2, 2, 3, 1, 2, 4, 2, 3,
2, 1, 1, 3, 1, 1, 3, 1, 3, 3, 4, 1, 3, 1, 2, 3, 2, 1,
2, 1, 4, 3, 2, 2, 3, 2, 1, 2, 3, 2, 3, 2, 3, 1, 2, 3,
2, 1, 1, 3, 4, 1, 3, 3, 2, 1, 4, 3, 2, 3, 4, 2, 1, 4,
1, 3, 2, 2, 3, 4, 2, 2, 1, 2, 3, 3, 3, 2, 3, 3, 4, 1,
2, 2, 1, 2, 4, 2, 2, 3, 4, 3, 3, 2, 3, 2, 1, 4, 2, 4,
2, 1, 1, 2, 1, 3, 1, 4, 2, 2, 2, 2, 2, 1, 3, 2, 1, 1,
3, 2, 1, 1, 4, 2, 3, 2, 3, 2, 1, 2, 2, 3, 1, 1, 2, 2,
3, 2, 1, 1, 3, 2, 4, 3, 2, 2, 3, 3, 3, 4, 4, 3, 2, 3,
2, 3, 4, 1, 1, 2, 2, 4, 2, 1, 4, 1, 2, 3, 4, 2, 3, 3,
3, 4, 1, 2, 2, 2, 2, 4, 2, 1, 3, 1, 3, 1, 2, 1, 2, 1,
3, 2, 2, 1, 3, 4, 2, 1, 3, 2, 4, 2, 1, 3, 1, 2, 1, 1,
2, 2, 1, 1, 2, 2, 2, 2, 2, 1, 2, 3, 1, 2, 4, 4, 2, 4,
3, 4, 4, 2, 3, 2, 4, 2, 4, 3, 3, 3, 4, 1, 2, 2, 2, 4,
2, 4, 2, 1, 3, 2, 2, 2, 4, 3, 3, 2, 4, 2, 4, 2, 4, 2,
4, 2, 1, 3, 4, 3, 4, 3, 2, 4, 2, 2, 3, 3, 3, 4, 2, 3,
3, 2, 1, 2, 4, 3, 3, 3, 2, 4, 4, 3, 2, 2, 2, 2, 3, 2,
1, 1, 1, 2, 2, 2, 1, 1, 2, 2, 4, 1, 1, 2, 3, 2, 1, 2,
4, 3, 2, 1, 2, 3, 4, 1, 3, 3, 2, 1, 2, 1, 3, 3, 4, 3,
1, 2, 1, 3, 1, 4, 1, 2, 2, 1, 3, 1, 3, 2, 3, 2, 3, 2,
2, 2, 2, 3, 2, 2, 1, 2, 3, 2, 4, 2, 1, 1, 4, 3, 1, 3,
3, 3, 2, 4, 4, 3, 3, 4, 2, 1, 2, 3, 3, 2, 2, 2, 2, 3,
1, 4, 2, 4, 3, 3, 4, 4, 3, 3, 2, 4, 2, 4, 3, 4, 4, 3,
2, 3, 1, 4, 1, 4, 2, 1, 3, 4, 2, 1, 2, 1, 1, 1, 2, 2,
2, 1, 4, 1, 1, 4, 3, 1, 2, 2, 3, 2, 2, 2, 1, 2, 2, 2,
4, 3, 3, 1, 3, 1, 4, 4, 3, 3, 3, 1, 1, 4, 2, 4, 1, 4,
3, 1, 2, 1, 2, 3, 3, 3, 1, 1, 3, 3, 1, 2, 4, 1, 3, 1,
1, 1, 1, 1, 1, 1, 3, 1, 1, 3, 3, 4, 4, 4, 3, 4, 1, 2,
2, 1, 3, 3, 1, 4, 3, 2, 3, 1, 2, 3, 4, 2, 1, 4, 2, 4,
3, 1, 2, 1, 2, 3, 4, 2, 2, 2, 1, 1, 4, 2, 2, 3, 3, 4,
3, 1, 1, 2, 4, 2, 1, 2, 2, 3, 2, 1, 2, 2, 2, 4, 3, 1,
1, 2, 1, 1, 1, 2, 1, 3, 1, 3, 1, 1, 1, 1, 1, 1, 1, 3,
2, 2, 3, 3, 3, 3, 2, 1, 3, 2, 3, 4, 4, 2, 2, 1, 4, 1,
4, 2, 1, 2, 2, 3, 3, 1, 2, 3, 2, 3, 1, 2, 1, 4, 2, 2,
2, 2, 3, 1, 1, 3, 2, 3, 2, 3, 2, 2, 2, 3, 4, 2, 2, 1,
1, 2, 3, 2, 2, 2, 2, 3, 3, 4, 3, 3, 2, 1, 3, 1, 1, 2,
1, 4, 4, 3, 2, 1, 2, 1, 4, 2, 3, 1, 2, 1, 1, 1, 4, 2,
2, 1, 1, 2, 1, 3, 2, 2, 1, 2, 2, 3, 2, 1, 3, 2, 2, 1,
3, 1, 2, 3, 2, 3, 1, 3, 1, 1, 1, 4, 2, 2, 2, 2, 2, 2,
1, 2, 2, 1, 1, 1, 2, 2, 3, 2, 3, 1, 2, 2, 3, 3, 2, 4,
1, 1, 2, 1, 4, 3, 2, 2, 2, 3, 2, 2, 2, 4, 3, 3, 1, 3,
3, 2, 3, 4, 1, 1, 1, 3, 4, 3, 2, 4, 4, 2, 2, 1, 4, 3,
4, 3, 3, 3, 3, 2, 2, 3, 3, 2, 3, 4, 2, 3, 3, 2, 2, 3,
4, 2, 1, 4, 2, 1, 4, 2, 2, 2, 1, 2, 2, 1, 2, 2, 4, 1,
2, 3, 2, 2, 1, 1, 2, 4, 2, 2, 2, 3, 2, 4, 4, 1, 1, 4,
2, 3, 2, 3, 3, 1, 3, 3, 2, 1, 2, 1, 3, 2, 3, 3, 1, 2,
4, 2, 4, 3, 4, 3, 2, 2, 1, 2, 3, 2, 1, 2, 2, 1, 2, 1,
4, 3, 3, 4, 3, 2, 1, 2, 3, 3, 3, 2, 1, 3, 2, 3, 2, 2,
3, 2, 3, 3, 1, 4, 2, 4, 4, 3, 3, 2, 2, 4, 3, 2, 3, 4,
3, 2, 4, 4, 1, 3, 4, 3, 2, 4, 3, 3, 3, 4, 4, 3, 3, 4,
1, 3, 3, 1, 3, 1, 2, 2, 2, 3, 2, 1, 4, 2, 2, 2, 1, 2,
3, 4, 1, 1, 2, 2, 2, 2, 1, 3, 3, 2, 2, 3, 4, 3, 3, 2,
3, 3, 1, 2, 4, 4, 2, 3, 4, 2, 4, 2, 1, 2, 2, 3, 4, 3,
4, 3, 3, 1, 3, 4, 1, 1, 1, 2, 2, 1, 1, 4, 2, 1, 2, 2,
3, 3, 2, 2, 4, 1, 2, 1, 2, 2, 3, 2, 3, 2, 1, 3, 2, 3,
2, 1, 3, 4, 2, 3, 3, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 4,
2, 2, 3, 1, 3, 1, 2, 2, 4, 1, 2, 2, 2, 3, 4, 2, 2, 3,
2, 1, 2, 2, 2, 1, 2, 3, 1, 1, 2, 3, 1, 3, 1, 4, 4, 3,
3, 3, 2, 3, 2, 1, 3, 2, 3, 3, 2, 3, 4, 1, 4, 1, 3, 4,
4, 3, 3, 2, 1, 2, 3, 3, 2, 1, 1, 2, 4, 3, 3, 1, 4, 2,
3, 4, 1, 4, 3, 3, 3, 1, 2, 3, 2, 4, 2, 4, 4, 4, 2, 3,
3, 4, 2, 2, 3, 3, 2, 1, 1, 4, 2, 2, 2, 2, 3, 2, 2, 1,
1, 2, 2, 4, 2, 3, 3, 4, 1, 4, 4, 2, 1, 2, 2, 2, 2, 3,
3, 2, 1, 4, 4, 2, 4, 2, 3, 1, 4, 3, 3, 3, 4, 4, 4, 1,
4, 1, 1, 3, 4, 1, 3, 2, 1, 2, 4, 1, 4, 1, 2, 2, 1, 1,
2, 1, 2, 2, 3, 1, 3, 2, 3, 1, 4, 1, 3, 2, 2, 2, 2, 3,
3, 1, 1, 3, 3, 3, 1, 2, 2, 3, 3, 4, 3, 2, 3, 2, 2, 4,
4, 3, 1, 4, 2, 4, 3, 4, 1, 2, 1, 3, 4, 2, 4, 3, 3, 2,
1, 2, 1, 1, 2, 4, 3, 4, 2, 1, 2, 4, 2, 4, 2, 4, 2, 1,
3, 4, 3, 4, 3, 2, 4, 2, 2, 3, 3, 3, 4, 2, 3, 3, 2, 1,
2, 4, 3, 3, 3, 2, 4, 4, 3, 2, 2, 2, 2, 3, 2, 1, 1, 1,
2, 2, 2, 1, 1, 2, 2, 4, 1, 1, 2, 3, 2, 1, 2, 4, 3, 2,
1, 2, 3, 4, 1, 3, 3, 2, 1, 2, 1, 3, 3, 4, 3, 1, 2, 1,
3, 1, 4, 1, 2, 2, 1, 3, 1, 3, 2, 3, 2, 3, 2, 2, 2, 2,
3, 2, 2, 1, 2, 3, 2, 4, 2, 1, 1, 4, 3, 1, 3, 3, 3, 2,
4, 4, 3, 3, 4, 2, 1, 2, 3, 3, 2, 2, 2, 2, 3, 1, 4, 2,
4, 3, 3, 4, 4, 3, 3, 2, 4, 2, 4, 3, 4, 4, 3, 2, 3, 1,
4, 1, 4, 2, 1, 3, 4, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 4,
1, 1, 4, 3, 1, 2, 2, 3, 2, 2, 2, 1, 2, 2, 2, 4, 3, 3,
1, 3, 1, 4, 4, 3, 3, 3, 1, 1, 4, 2, 4, 1, 4, 3, 1, 2,
1, 2, 3, 3, 3, 1, 1, 3, 3, 1, 2, 4, 1, 3, 1, 1, 1, 1,
1, 1, 1, 3, 1, 1, 3, 3, 4, 4, 4, 3, 4, 1, 2, 2, 1, 3,
3, 1, 4, 3, 2, 3, 1, 2, 3, 4, 2, 1, 4, 2, 4, 3, 1, 2,
1, 2, 3, 4, 2, 2, 2, 1, 1, 4, 2, 2, 3, 3, 4, 3, 1, 1,
2, 4, 2, 1, 2, 2, 3, 2, 1, 2, 2, 2, 4, 3, 1, 1, 2, 1,
1, 1, 2, 1, 3, 1, 3, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2, 3,
3, 3, 3, 2, 1, 3, 2, 3, 4, 4, 2, 2, 1, 4, 1, 4, 2, 1,
2, 2, 3, 3, 1, 2, 3, 2, 3, 1, 2, 1, 4, 2, 2, 2, 2, 3,
1, 1, 3, 2, 3, 2, 3, 2, 2, 2, 3, 4, 2, 2, 1, 1, 2, 3,
2, 2, 2, 2, 3, 3, 4, 3, 3, 2, 1, 3, 1, 1, 2, 1, 4, 4,
3, 2, 1, 2, 1, 4, 2, 3, 1, 2, 1, 1, 1, 4, 2, 2, 1, 1,
2, 1, 3, 2, 2, 1, 2, 2, 3, 2, 1, 3, 2, 2, 1, 3, 1, 2,
3, 2, 3, 1, 3, 1, 1, 1, 4, 2, 2, 2, 2, 2, 2, 1, 2, 2,
1, 1, 1, 2, 2, 3, 2, 3, 1, 2, 2, 3, 3, 2, 4, 1, 1, 2,
1, 4, 3, 2, 2, 2, 3, 2, 2, 2, 4, 3, 3, 1, 3, 3, 2, 3,
4, 1, 1, 1, 3, 4, 3, 2, 4, 4, 2, 2, 1, 4, 3, 4, 3, 3,
3, 3, 2, 2, 3, 3, 2, 3, 4, 2, 3, 3, 2, 2, 3, 4, 2, 1,
4, 2, 1, 4, 2, 2, 2, 1, 2, 2, 1, 2, 2, 4, 1, 2, 3, 2,
2, 1, 1, 2, 4, 2, 2, 2, 3, 2, 4, 4, 1, 1, 4, 2, 3, 2,
3, 3, 1, 3, 3, 2, 1, 2, 1, 3, 2, 3, 3, 1, 2, 4, 2, 4,
3, 4, 3, 2, 2, 1, 2, 3, 2, 1, 2, 2, 1, 2, 1, 4, 3, 3,
4, 3, 2, 1, 2, 3, 3, 3, 2, 1, 3, 2, 3, 2, 2, 3, 2, 3,
3, 1, 4, 2, 4, 4, 3, 3, 2, 2, 4, 3, 2, 3, 4, 3, 2, 4,
4, 1, 3, 4, 3, 2, 4, 3, 3, 3, 4, 4, 3, 3, 4, 1, 3, 3,
1, 3, 1, 2, 2, 2, 3, 2, 1, 4, 2, 2, 2, 1, 2, 3, 4, 1,
1, 2, 2, 2, 2, 1, 3, 3, 2, 2, 3, 4, 3, 3, 2, 3, 3, 1,
2, 4, 4, 2, 3, 4, 2, 4, 2, 1, 2, 2, 3, 4, 3, 4, 3, 3,
1, 3, 4, 1, 1, 1, 2, 2, 1, 1, 4, 2, 1, 2, 2, 3, 3, 2,
2, 4, 1, 2, 1, 2, 2, 3, 2, 3, 2, 1, 3, 2, 3, 2, 1, 3,
4, 2, 3, 3, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 4, 2, 2, 3,
1, 3, 1, 2, 2, 4, 1, 2, 2, 2, 3, 4, 2, 2, 3, 2, 1, 2,
2, 2, 1, 2, 3, 1, 1, 2, 3, 1, 3, 1, 4, 4, 3, 3, 3, 2,
3, 2, 1, 3, 2, 3, 3, 2, 3, 4, 1, 4, 1, 3, 4, 4, 3, 3,
2, 1, 2, 3, 3, 2, 1, 1, 2, 4, 3, 3, 1, 4, 2, 3, 4, 1,
4, 3, 3, 3, 1, 2, 3, 2, 4, 2, 4, 4, 4, 2, 3, 3, 4, 2,
2, 3, 3, 2, 1, 1, 4, 2, 2, 2, 2, 3, 2, 2, 1, 1, 2, 2,
4, 2, 3, 3, 4, 1, 4, 4, 2, 1, 2, 2, 2, 2, 3, 3, 2, 1,
4, 4, 2, 4, 2, 3, 1, 4, 3, 3, 3, 4, 4, 4, 1, 4, 1, 1,
3, 4, 1, 3, 2, 1, 2, 4, 1, 4, 1, 2, 2, 1, 1, 2, 1, 2,
2, 3, 1, 3, 2, 3, 1, 4, 1, 3, 2, 2, 2, 2, 3, 3, 1, 1,
3, 3, 3, 1, 2, 2, 3, 3, 4, 3, 2, 3, 2, 2, 4, 4, 3, 1,
4, 2, 4, 3, 4, 1, 2, 1, 3, 4, 2, 4, 3, 3, 2, 1, 2, 1,
1, 2, 4, 3, 4, 2, 1, 2, 1, 3, 2, 1, 1, 2, 1, 4, 2, 3,
2, 2, 2, 4, 1, 2, 2, 4, 4, 2, 3, 1, 3, 2, 2, 2, 2, 4,
2, 3, 4, 2, 3, 4, 3, 3, 3, 2, 2, 2, 1, 1, 1, 2, 2, 2,
3, 2, 2, 4, 1, 1, 3, 4, 2, 3, 1, 2, 2, 3, 1, 4, 2, 2,
4, 2, 1, 1, 2, 1, 3, 3, 3, 2, 2, 3, 4, 2, 4, 2, 3, 4,
2, 2, 3, 2, 2, 3, 4, 1, 3, 2, 1, 2, 2, 2, 2, 2, 2, 2,
4, 4, 3, 3, 3, 3, 2, 4, 1, 3, 4, 3, 1, 4, 3, 2, 1, 2,
2, 2, 2, 2, 4, 1, 2, 1, 3, 3, 4, 1, 3, 1, 3, 3, 3, 2,
2, 4, 2, 3, 2, 2, 2, 3, 1, 3, 3, 2, 1, 4, 2, 4, 2, 3,
2, 3, 3, 3, 3, 1, 3, 3, 4, 3, 4, 3, 4, 4, 3, 1, 4, 2,
3, 1, 1, 3, 1, 1, 2, 1, 2, 2, 2, 1, 4, 3, 2, 2, 3, 4,
3, 4, 1, 2, 3, 3, 2, 3, 4, 1, 2, 1, 2, 3, 1, 1, 4, 2,
4, 1, 3, 1, 3, 3, 1, 3, 4, 1, 3, 1, 1, 1, 1, 4, 1, 3,
3, 1, 2, 1, 2, 2, 3, 2, 4, 2, 1, 2, 2, 1, 3, 3, 3, 4,
4, 2, 1, 2, 2, 3, 2, 3, 3, 2, 4, 4, 3, 3, 3, 2, 2, 2,
1, 3, 2, 2, 3, 3, 4, 2, 2, 3, 2, 2, 4, 2, 3, 3, 4, 2,
4, 1, 3, 1, 2, 4, 4, 3, 3, 4, 2, 2, 2, 1, 1, 2, 1, 1,
4, 3, 2, 3, 2, 3, 3, 3, 2, 2, 2, 3, 3, 4, 4, 3, 3, 3,
1, 4, 4, 2, 1, 2, 2, 1, 3, 3, 4, 2, 4, 3, 3, 1, 2, 2,
2, 2, 3, 4, 2, 1, 2, 2, 4, 1, 3, 4, 2, 3, 2, 3, 3, 3,
2, 2, 2, 2, 2, 2, 2, 3, 3, 1, 2, 2, 1, 4, 3, 2, 3, 4,
4, 1, 1, 2, 2, 1, 4, 2, 3, 2, 2, 4, 3, 2, 2, 2, 1, 3,
4, 3, 2, 1, 2, 4, 1, 2, 3, 1, 1, 1, 2, 2, 4, 2, 2, 3,
2, 3, 1, 3, 2, 2, 2, 2, 2, 2, 2, 1, 3, 3, 3, 4, 1, 2,
4, 1, 2, 2, 1, 3, 2, 3, 1, 1, 2, 1, 2, 2, 4, 3, 4, 3,
2, 2, 4, 4, 3, 1, 3, 3, 3, 2, 2, 2, 4, 3, 4, 2, 2, 1,
2, 3, 1, 4, 3, 2, 2, 1, 4, 4, 2, 4, 2, 4, 1, 2, 3, 2,
2, 1, 1, 2, 4, 2, 2, 2, 3, 2, 4, 4, 1, 1, 4, 2, 3, 2,
3, 3, 1, 3, 3, 2, 1, 2, 1, 3, 2, 3, 3, 1, 2, 4, 2, 4,
3, 4, 3, 2, 2, 1, 2, 3, 2, 1, 2, 2, 1, 2, 1, 4, 3, 3,
4, 3, 2, 1, 2, 3, 3, 3, 2, 1, 3, 2, 3, 2, 2, 3, 2, 3,
3, 1, 4, 2, 4, 4, 3, 3, 2, 2, 4, 3, 2, 3, 4, 3, 2, 4,
4, 1, 3, 4, 3, 2, 4, 3, 3, 3, 4, 4, 3, 3, 4, 1, 3, 3,
1, 3, 1, 2, 2, 2, 3, 2, 1, 4, 2, 2, 2, 1, 2, 3, 4, 1,
1, 2, 2, 2, 2, 1, 3, 3, 2, 2, 3, 4, 3, 3, 2, 3, 3, 1,
2, 4, 4, 2, 3, 4, 2, 4, 2, 1, 2, 2, 3, 4, 3, 4, 3, 3,
1, 3, 4, 1, 1, 1, 2, 2, 1, 1, 4, 2, 1, 2, 2, 3, 3, 2,
2, 4, 1, 2, 1, 2, 2, 3, 2, 3, 2, 1, 3, 2, 3, 2, 1, 3,
4, 2, 3, 3, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 4, 2, 2, 3,
1, 3, 1, 2, 2, 4, 1, 2, 2, 2, 3, 4, 2, 2, 3, 2, 1, 2,
2, 2, 1, 2, 3, 1, 1, 2, 3, 1, 3, 1, 4, 4, 3, 3, 3, 2,
3, 2, 1, 3, 2, 3, 3, 2, 3, 4, 1, 4, 1, 3, 4, 4, 3, 3,
2, 1, 2, 3, 3, 2, 1, 1, 2, 4, 3, 3, 1, 4, 2, 3, 4, 1,
4, 3, 3, 3, 1, 2, 3, 2, 4, 2, 4, 4, 4, 2, 3, 3, 4, 2,
2, 3, 3, 2, 1, 1, 4, 2, 2, 2, 2, 3, 2, 2, 1, 1, 2, 2,
4, 2, 3, 3, 4, 1, 4, 4, 2, 1, 2, 2, 2, 2, 3, 3, 2, 1,
4, 4, 2, 4, 2, 3, 1, 4, 3, 3, 3, 4, 4, 4, 1, 4, 1, 1,
3, 4, 1, 3, 2, 1, 2, 4, 1, 4, 1, 2, 2, 1, 1, 2, 1, 2,
2, 3, 1, 3, 2, 3, 1, 4, 1, 3, 2, 2, 2, 2, 3, 3, 1, 1,
3, 3, 3, 1, 2, 2, 3, 3, 4, 3, 2, 3, 2, 2, 4, 4, 3, 1,
4, 2, 4, 3, 4, 1, 2, 1, 3, 4, 2, 4, 3, 3, 2, 1, 2, 1,
1, 2, 4, 3, 4, 2, 1, 2, 1, 3, 2, 1, 1, 2, 1, 4, 2, 3,
2, 2, 2, 4, 1, 2, 2, 4, 4, 2, 3, 1, 3, 2, 2, 2, 2, 4,
2, 3, 4, 2, 3, 4, 3, 3, 3, 2, 2, 2, 1, 1, 1, 2, 2, 2,
3, 2, 2, 4, 1, 1, 3, 4, 2, 3, 1, 2, 2, 3, 1, 4, 2, 2,
4, 2, 1, 1, 2, 4, 1, 3, 3, 3, 2, 2, 3, 4, 2, 4, 2, 3,
4, 2, 2, 3, 2, 2, 3, 4, 1, 3, 2, 1, 2, 2, 2, 2, 2, 2,
2, 4, 4, 3, 3, 3, 3, 2, 4, 1, 3, 4, 3, 1, 4, 3, 2, 1,
2, 2, 2, 2, 2, 4, 1, 2, 1, 3, 3, 4, 1, 3, 1, 3, 3, 3,
2, 2, 4, 2, 3, 2, 2, 2, 3, 1, 3, 3, 2, 1, 4, 2, 4, 2,
3, 2, 3, 3, 3, 3, 1, 3, 3, 4, 3, 4, 3, 4, 4, 3, 1, 4,
2, 3, 1, 1, 3, 1, 1, 2, 1, 2, 2, 2, 1, 4, 3, 2, 2, 3,
4, 3, 4, 1, 2, 3, 3, 2, 3, 4, 1, 2, 1, 2, 3, 1, 1, 4,
2, 4, 1, 3, 1, 3, 3, 1, 3, 4, 1, 3, 1, 1, 1, 1, 4, 1,
3, 3, 1, 2, 1, 2, 2, 3, 2, 4, 2, 1, 2, 2, 1, 3, 3, 3,
4, 4, 2, 1, 2, 2, 3, 2, 3, 3, 2, 4, 4, 3, 3, 3, 2, 2,
2, 1, 3, 2, 2, 3, 3, 4, 2, 2, 3, 2, 2, 4, 2, 3, 3, 4,
2, 4, 1, 3, 1, 2, 4, 4, 3, 3, 4, 2, 2, 2, 1, 1, 2, 1,
1, 4, 3, 4, 2, 3, 2, 3, 3, 3, 2, 2, 2, 3, 3, 4, 4, 3,
3, 3, 1, 4, 4, 2, 1, 2, 2, 1, 3, 3, 4, 2, 4, 3, 3, 1,
2, 2, 2, 2, 3, 2, 4, 2, 1, 2, 2, 4, 1, 3, 4, 2, 3, 2,
3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 3, 3, 1, 2, 2, 1, 4, 3,
2, 3, 4, 4, 1, 1, 2, 2, 1, 4, 2, 3, 2, 2, 4, 3, 2, 2,
2, 1, 3, 4, 3, 2, 1, 2, 4, 1, 2, 3, 1, 1, 1, 2, 2, 4,
2, 2, 3, 2, 3, 1, 3, 2, 2, 2, 2, 2, 2, 2, 1, 3, 3, 3,
4, 1, 2, 4, 1, 2, 2, 1, 3, 2, 3, 1, 1, 2, 1, 2, 2, 4,
3, 4, 3, 2, 2, 4, 4, 3, 1, 3, 3, 3, 2, 2, 2, 4, 3, 4,
2, 2, 1, 2, 3, 1, 4, 3, 2, 2, 1, 4, 4, 2, 4, 2, 3, 1,
2, 2, 2, 2, 1, 4, 3, 4, 2, 3, 4, 2, 4, 1, 1, 1, 2, 3,
1, 1, 2, 4, 2, 2, 2, 4, 4, 2, 4, 3, 4, 2, 3, 2, 1, 4,
4, 3, 3, 1, 3, 4, 1, 4, 2, 3, 4, 2, 2, 2, 2, 2, 3, 3,
3, 3, 3, 3, 2, 3, 1, 2, 1, 4, 1, 3, 2, 3, 1, 1, 4, 2,
1, 2, 4, 2, 3, 4, 1, 2, 1, 4, 2, 3, 1, 3, 2, 3, 3, 4,
3, 4, 3, 3, 4, 2, 1, 3, 1, 3, 3, 2, 4, 3, 4, 3, 3, 3,
2, 3, 3, 2, 4, 2, 2, 1, 3, 2, 4, 4, 3, 1, 2, 4, 2, 3,
4, 2, 1, 4, 1, 1, 2, 3, 3, 2, 3, 3, 1, 2, 3, 1, 2, 2,
3, 2, 4, 2, 1, 4, 2, 1, 1, 3, 4, 4, 2, 3, 2, 2, 4, 3,
3, 2, 3, 4, 2, 2, 4, 2, 4, 2, 4, 1, 4, 2, 2, 2, 3, 1,
2, 1, 2, 3, 2, 4, 2, 4, 3, 1, 4, 3, 2, 4, 2, 3, 3, 2,
2, 2, 3, 4, 3, 1, 3, 2, 4, 1, 2, 2, 2, 3, 4, 3, 4, 2,
3, 2, 2, 2, 2, 1, 3, 1, 2, 1, 2, 2, 4, 2, 3, 2, 4, 3,
4, 3, 3, 3, 2, 2, 2, 1, 2, 1, 2, 1, 2, 4, 2, 4, 1, 1,
2, 3, 1, 4, 2, 3, 2, 2, 4, 2, 2, 3, 3, 1, 3, 1, 2, 3,
3, 2, 3, 1, 2, 3, 3, 3, 3, 3, 2, 3, 4, 2, 3, 2, 4, 3,
3, 2, 2, 2, 1, 1, 1, 3, 2, 3, 1, 1, 3, 3, 1, 2, 3, 3,
3, 2, 2, 2, 3, 4, 4, 2, 3, 3, 1, 3, 3, 3, 3, 2, 4, 1,
3, 2, 1, 2, 1, 2, 2, 2, 3, 2, 2, 3, 3, 4, 3, 4, 3, 3,
2, 3, 3, 2, 1, 2, 4, 3, 3, 4, 1, 3, 2, 2, 1, 2, 4, 1,
3, 3, 4, 4, 4, 2, 4, 1, 3, 3, 3, 1, 2, 1, 2, 2, 1, 2,
4, 4, 3, 4, 3, 2, 3, 3, 1, 1, 3, 3, 3, 3, 4, 1, 4, 3,
3, 3, 2, 3, 2, 2, 2, 2, 3, 2, 2, 4, 1, 3, 2, 1, 4, 2,
2, 3, 1, 4, 1, 2, 4, 1, 3, 2, 4, 1, 2, 3, 4, 2, 3, 1,
2, 2, 3, 4, 3, 2, 2, 3, 2, 2, 2, 2, 1, 2, 2, 4, 1, 1,
2, 1, 4, 2, 3, 1, 2, 1, 3, 4, 1, 1, 3, 3, 1, 2, 3, 4,
1, 3, 2, 3, 3, 2, 3, 2, 2, 2, 2, 4, 2, 2, 3, 2, 2, 3,
2, 3, 2, 3, 1, 4, 2, 2, 1, 4, 1, 3, 2, 3, 1, 2, 2, 2,
2, 1, 4, 3, 4, 2, 3, 4, 2, 4, 1, 1, 1, 2, 3, 1, 1, 2,
4, 2, 2, 2, 4, 4, 2, 4, 3, 4, 2, 3, 2, 1, 4, 4, 3, 3,
1, 3, 4, 1, 4, 2, 3, 4, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3,
3, 2, 3, 1, 2, 1, 4, 1, 3, 2, 3, 1, 1, 4, 2, 1, 2, 4,
2, 3, 4, 1, 2, 1, 4, 2, 3, 1, 3, 2, 3, 3, 4, 3, 4, 3,
3, 4, 2, 1, 3, 1, 3, 3, 2, 4, 3, 4, 3, 3, 3, 2, 3, 3,
2, 4, 2, 2, 1, 3, 2, 4, 4, 3, 1, 2, 4, 2, 3, 4, 2, 1,
4, 1, 1, 2, 3, 3, 2, 3, 3, 1, 2, 3, 1, 2, 2, 3, 2, 4,
2, 1, 4, 2, 1, 1, 3, 4, 4, 2, 3, 2, 2, 4, 3, 3, 2, 3,
4, 2, 2, 4, 2, 4, 2, 4, 1, 4, 2, 2, 2, 3, 1, 2, 1, 2,
3, 2, 4, 2, 4, 3, 1, 4, 3, 2, 4, 2, 3, 3, 2, 2, 2, 3,
4, 3, 1, 3, 2, 4, 1, 2, 2, 2, 3, 4, 3, 4, 2, 3, 2, 2,
2, 2, 1, 3, 1, 2, 1, 2, 2, 4, 2, 3, 2, 4, 3, 4, 3, 3,
3, 2, 2, 2, 1, 2, 1, 2, 1, 2, 4, 2, 4, 1, 1, 2, 3, 1,
4, 2, 3, 2, 2, 4, 2, 2, 3, 3, 1, 3, 1, 2, 3, 3, 2, 3,
1, 2, 3, 3, 3, 3, 3, 2, 3, 4, 2, 3, 2, 4, 3, 3, 2, 2,
2, 1, 1, 1, 3, 2, 3, 1, 1, 3, 3, 1, 2, 3, 3, 3, 2, 2,
2, 3, 4, 4, 2, 3, 3, 1, 3, 3, 3, 3, 2, 4, 1, 3, 2, 1,
2, 1, 2, 2, 2, 3, 2, 2, 3, 3, 4, 3, 4, 3, 3, 2, 3, 3,
2, 1, 2, 4, 3, 3, 4, 1, 3, 2, 2, 1, 2, 4, 1, 3, 3, 4,
4, 4, 2, 4, 1, 3, 3, 3, 1, 2, 1, 2, 2, 1, 2, 4, 4, 3,
4, 3, 2, 3, 3, 1, 1, 3, 3, 3, 3, 4, 1, 4, 3, 3, 3, 2,
3, 2, 2, 2, 2, 3, 2, 2, 4, 1, 3, 2, 1, 4, 2, 2, 3, 1,
4, 1, 2, 4, 1, 3, 2, 4, 1, 2, 3, 4, 2, 3, 1, 2, 2, 3,
4, 3, 2, 2, 3, 2, 2, 2, 2, 1, 2, 2, 4, 1, 1, 2, 1, 4,
2, 3, 1, 2, 1, 3, 4, 1, 1, 3, 3, 1, 2, 3, 4, 1, 3, 2,
3, 3, 2, 3, 2, 2, 2, 2, 4, 2, 2, 3, 2, 2, 3, 2, 3, 2,
3, 1, 4, 2, 2, 1, 4, 1, 3, 3, 2, 4, 3, 4, 2, 1, 3, 2,
2, 4, 2, 2, 4, 2, 1, 4, 3, 1, 3, 3, 1, 4, 1, 2, 2, 4,
4, 3, 1, 3, 3, 3, 2, 2, 2, 3, 1, 4, 1, 3, 3, 3, 3, 1,
4, 2, 4, 3, 4, 3, 2, 2, 4, 3, 1, 2, 2, 1, 4, 1, 3, 3,
3, 1, 2, 1, 4, 1, 1, 3, 4, 3, 1, 1, 2, 3, 3, 2, 2, 3,
2, 3, 2, 3, 3, 3, 2, 4, 2, 1, 1, 4, 2, 3, 4, 4, 2, 2,
4, 3, 2, 3, 3, 3, 3, 4, 2, 1, 2, 3, 2, 4, 2, 2, 3, 2,
2, 1, 2, 2, 2, 2, 2, 1, 3, 2, 4, 1, 3, 3, 2, 2, 3, 2,
3, 2, 4, 2, 3, 1, 3, 4, 3, 1, 1, 3, 2, 3, 3, 2, 4, 4,
3, 2, 2, 1, 3, 4, 1, 2, 4, 2, 3, 3, 3, 4, 2, 1, 1, 4,
4, 2, 4, 1, 1, 4, 2, 4, 4, 2, 2, 3, 1, 3, 4, 3, 4, 1,
1, 3, 1, 3, 2, 3, 1, 4, 1, 3, 1, 4, 3, 2, 1, 1, 3, 2,
1, 3, 1, 3, 2, 3, 3, 1, 2, 2, 2, 4, 2, 1, 2, 3, 4, 4,
3, 2, 2, 3, 4, 3, 3, 1, 2, 4, 3, 2, 1, 1, 4, 1, 1, 1,
2, 4, 2, 1, 2, 2, 2, 2, 2, 2, 4, 1, 1, 3, 1, 2, 3, 3,
1, 2, 2, 1, 2, 3, 2, 1, 3, 4, 1, 3, 4, 1, 2, 2, 1, 1,
2, 3, 1, 2, 4, 4, 3, 2, 2, 1, 1, 3, 1, 3, 2, 2, 4, 2,
2, 2, 3, 4, 2, 2, 2, 1, 3, 1, 2, 4, 2, 1, 1, 1, 2, 4,
2, 4, 3, 4, 2, 3, 3, 4, 4, 1, 1, 3, 2, 2, 4, 3, 3, 4,
4, 1, 4, 1, 4, 2, 1, 1, 1, 1, 4, 2, 4, 1, 1, 1, 3, 2,
1, 2, 4, 3, 1, 3, 4, 1, 1, 4, 3, 1, 2, 4, 1, 2, 2, 2,
3, 4, 1, 3, 1, 1, 1, 1, 3, 3, 2, 4, 2, 3, 4, 1, 2, 3,
2, 3, 2, 2, 4, 1, 1, 2, 3, 3, 2, 3, 4, 3, 2, 1, 3, 2,
4, 1, 3, 2, 1, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 3, 2, 1,
2, 1, 1, 1, 2, 2, 1, 4, 1, 2, 2, 3, 1, 2, 2, 2, 3, 3,
1, 1, 3, 4, 1, 1, 1, 2, 4, 1, 3, 1, 4, 3, 1, 1, 2, 3,
2, 3, 1, 2, 3, 2, 1, 3, 4, 2, 1, 2, 3, 2, 2, 2, 1, 3,
3, 3, 2, 1, 1, 1, 2, 4, 3, 1, 4, 1, 3, 3, 2, 4, 1, 2,
2, 1, 2, 2, 3, 2, 2, 1, 1, 2, 2, 4, 2, 3, 1, 4, 3, 4,
1, 2, 2, 2, 4, 3, 3, 2, 1, 2, 1, 3, 3, 3, 2, 4, 3, 2,
1, 2, 3, 4, 2, 3, 3, 2, 3, 1, 1, 3, 2, 4, 3, 4, 3, 2,
2, 2, 4, 3, 2, 4, 1, 1, 1, 3, 3, 3, 3, 2, 1, 2, 1, 1,
2, 3, 2, 4, 1, 1, 4, 1, 4, 2, 1, 1, 4, 2, 1, 2, 2, 2,
1, 2, 2, 2, 4, 4, 4, 2, 1, 2, 1, 2, 1, 1, 2, 3, 2, 2,
1, 2, 1, 1, 3, 3, 4, 1, 2, 2, 2, 3, 2, 1, 2, 3, 1, 3,
2, 4, 3, 1, 3, 2, 3, 3, 2, 2, 2, 1, 3, 1, 3, 2, 3, 2,
2, 2, 2, 4, 3, 3, 2, 2, 1, 2, 1, 2, 2, 3, 2, 2, 4, 3,
1, 2, 1, 3, 3, 4, 2, 1, 4, 2, 2, 1, 2, 1, 4, 2, 1, 2,
4, 4, 1, 4, 4, 2, 1, 2, 4, 1, 2, 1, 2, 2, 4, 2, 2, 2,
4, 2, 1, 1, 4, 3, 4, 3, 3, 1, 1, 2, 2, 3, 2, 3, 2, 2,
1, 4, 1, 4, 2, 2, 3, 1, 2, 2, 2, 2, 3, 4, 3, 2, 2, 3,
3, 2, 4, 2, 2, 4, 1, 3, 1, 4, 2, 2, 2, 1, 4, 3, 3, 3,
3, 1, 2, 3, 2, 2, 2, 3, 3, 2, 2, 2, 2, 3, 1, 3, 2, 3,
2, 3, 2, 2, 4, 4, 1, 1, 3, 2, 2, 2, 4, 1, 4, 4, 4, 2,
2, 1, 4, 1, 4, 4, 3, 2, 1, 3, 1, 3, 3, 2, 4, 1, 1, 2,
4, 2, 3, 3, 2, 3, 3, 2, 3, 4, 2, 3, 4, 3, 3, 3, 1, 2,
1, 2, 3, 3, 1, 1, 3, 4, 2, 1, 1, 2, 2, 3, 3, 3, 2, 2,
3, 3, 2, 4, 3, 2, 3, 3, 2, 2, 2, 2, 4, 2, 4, 3, 1, 3,
2, 1, 2, 4, 1, 2, 4, 2, 3, 3, 4, 2, 3, 2, 3, 1, 2, 1,
3, 1, 4, 4, 2, 3, 1, 4, 1, 3, 2, 2, 3, 2, 1, 2, 2, 4,
4, 1, 1, 1, 4, 4, 3, 2, 2, 1, 1, 1, 1, 1, 3, 1, 3, 1,
2, 3, 2, 1, 2, 3, 3, 2, 2, 2, 3, 2, 2, 4, 2, 3, 1, 2,
4, 2, 1, 2, 1, 4, 2, 2, 2, 4, 2, 2, 2, 3, 1, 2, 1, 3,
2, 4, 2, 1, 4, 1, 2, 2, 2, 4, 2, 2, 3, 2, 2, 1, 1, 3,
3, 3, 2, 2, 1, 1, 4, 4, 3, 1, 2, 4, 2, 3, 4, 2, 4, 3,
2, 1, 1, 2, 1, 1, 4, 1, 2, 1, 3, 1, 3, 1, 1, 2, 3, 4,
2, 2, 1, 2, 1, 4, 4, 2, 2, 4, 2, 2, 3, 3, 1, 1, 4, 1,
2, 2, 4, 2, 3, 3, 2, 3, 3, 1, 1, 2, 3, 4, 3, 3, 2, 3,
2, 2, 1, 3, 1, 2, 2, 3, 2, 2, 2, 2, 1, 2, 1, 4, 3, 1,
3, 4, 4, 1, 1, 2, 2, 2, 1, 3, 2, 1, 3, 2, 1, 2, 1, 1,
2, 2, 4, 1, 2, 1, 2, 2, 4, 2, 4, 2, 2, 1, 1, 1, 2, 2,
2, 2, 2, 2, 2, 3, 2, 2, 4, 2, 1, 2, 2, 2, 4, 2, 2, 1,
1, 4, 3, 2, 3, 2, 2, 2, 2, 2, 4, 2, 2, 4, 2, 2, 2, 2,
3, 2, 3, 2, 3, 1, 3, 2, 1, 1, 2, 4, 2, 2, 3, 2, 2, 4,
2, 1, 1, 1, 2, 1, 3, 2, 3, 3, 2, 2, 2, 3, 2, 3, 2, 2,
3, 3, 3, 2, 4, 4, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 3, 2,
4, 3, 3, 2, 1, 1, 2, 2, 2, 1, 1, 4, 4, 1, 1, 2, 1, 3,
3, 1, 2, 1, 3, 3, 3, 2, 3, 1, 3, 1, 2, 3, 1, 1, 2, 1,
2, 3, 3, 1, 1, 2, 2, 1, 4, 3, 1, 2, 3, 3, 2, 3, 3, 3,
2, 2, 3, 4, 4, 1, 4, 1, 2, 4, 2, 1, 4, 4, 3, 1, 1, 3,
1, 3, 3, 2, 3, 3, 4, 2, 4, 3, 1, 3, 4, 3, 4, 2, 4, 2,
4, 4, 2, 4, 2, 4, 3, 4, 2, 4, 2, 4, 2, 2, 1, 3, 1, 1,
4, 2, 4, 4, 2, 4, 4, 2, 1, 4, 3, 2, 2, 1, 3, 4, 3, 3,
3, 4, 3, 4, 4, 2, 4, 3, 2, 2, 4, 2, 3, 1, 4, 4, 4, 4,
1, 2, 3, 2, 3, 4, 3, 2, 3, 3, 4, 2, 1, 1, 4, 2, 3, 2,
3, 2, 2, 1, 3, 2, 4, 2, 1, 1, 2, 4, 1, 1, 1, 2, 4, 3,
2, 4, 2, 2, 2, 1, 2, 1, 3, 2, 4, 1, 3, 2, 1, 2, 2, 3,
2, 2, 2, 2, 2, 2, 2, 3, 2, 1, 2, 1, 1, 1, 2, 2, 1, 4,
1, 2, 2, 3, 1, 2, 2, 2, 3, 3, 1, 1, 3, 4, 1, 1, 1, 2,
4, 1, 3, 1, 4, 3, 1, 1, 2, 3, 2, 3, 1, 2, 3, 2, 1, 3,
4, 2, 1, 2, 3, 2, 2, 2, 1, 3, 3, 3, 2, 1, 1, 1, 2, 4,
3, 1, 4, 1, 3, 3, 2, 4, 1, 2, 2, 1, 2, 2, 3, 2, 2, 1,
1, 2, 2, 4, 2, 3, 1, 4, 3, 4, 1, 2, 2, 2, 4, 3, 3, 2,
1, 2, 1, 3, 3, 3, 2, 4, 3, 2, 1, 2, 3, 4, 2, 3, 3, 2,
3, 1, 1, 3, 2, 4, 3, 4, 3, 2, 2, 2, 4, 3, 2, 4, 1, 1,
1, 3, 3, 3, 3, 2, 1, 2, 1, 1, 2, 3, 2, 4, 1, 1, 4, 1,
4, 2, 1, 1, 4, 2, 1, 2, 2, 2, 1, 2, 2, 2, 4, 4, 4, 2,
1, 2, 1, 2, 1, 1, 2, 3, 2, 2, 1, 2, 1, 1, 3, 3, 4, 1,
2, 2, 2, 3, 2, 1, 2, 3, 1, 3, 2, 4, 3, 1, 3, 2, 3, 3,
2, 2, 2, 1, 3, 1, 3, 2, 3, 2, 2, 2, 2, 4, 3, 3, 2, 2,
1, 2, 1, 2, 2, 3, 2, 2, 4, 3, 1, 2, 1, 3, 3, 4, 2, 1,
4, 2, 2, 1, 2, 1, 4, 2, 1, 2, 4, 4, 1, 4, 4, 2, 1, 2,
4, 1, 2, 1, 2, 2, 4, 2, 2, 2, 4, 2, 1, 1, 4, 3, 4, 3,
3, 1, 1, 2, 2, 3, 2, 3, 2, 2, 1, 4, 1, 4, 2, 2, 3, 1,
2, 2, 2, 2, 3, 4, 3, 2, 2, 3, 3, 2, 4, 2, 2, 4, 1, 3,
1, 4, 2, 2, 2, 1, 4, 3, 3, 3, 3, 1, 2, 3, 2, 2, 2, 3,
3, 2, 2, 2, 2, 3, 1, 3, 2, 3, 2, 3, 2, 2, 4, 4, 1, 1,
3, 2, 2, 2, 4, 1, 4, 4, 4, 2, 2, 1, 4, 1, 4, 4, 3, 2,
1, 3, 1, 3, 3, 2, 4, 1, 1, 2, 4, 2, 3, 3, 2, 3, 3, 2,
3, 4, 2, 3, 4, 3, 3, 3, 1, 2, 1, 2, 3, 3, 1, 1, 3, 4,
2, 1, 1, 2, 2, 3, 3, 3, 2, 2, 3, 3, 2, 4, 3, 2, 3, 3,
2, 2, 2, 2, 4, 2, 4, 3, 1, 3, 2, 1, 2, 4, 1, 2, 4, 2,
3, 3, 4, 2, 3, 2, 3, 1, 2, 1, 3, 1, 4, 4, 2, 3, 1, 4,
1, 3, 2, 2, 3, 2, 1, 2, 2, 4, 4, 1, 1, 1, 4, 4, 3, 2,
2, 1, 1, 1, 1, 1, 3, 1, 3, 1, 2, 3, 2, 1, 2, 3, 3, 2,
2, 2, 3, 2, 2, 4, 2, 3, 1, 2, 4, 2, 1, 2, 1, 4, 2, 2,
2, 4, 2, 2, 2, 3, 1, 2, 1, 3, 2, 4, 2, 1, 4, 1, 2, 2,
2, 4, 2, 2, 3, 2, 2, 1, 1, 3, 3, 3, 2, 2, 1, 1, 4, 4,
3, 1, 2, 4, 2, 3, 4, 2, 4, 3, 2, 1, 1, 2, 1, 1, 4, 1,
2, 1, 3, 1, 3, 1, 1, 2, 3, 4, 2, 2, 1, 2, 1, 4, 4, 2,
2, 4, 2, 2, 3, 3, 1, 1, 4, 1, 2, 2, 4, 2, 3, 3, 2, 3,
3, 1, 1, 2, 3, 4, 3, 3, 2, 3, 2, 2, 1, 3, 1, 2, 2, 3,
2, 2, 2, 2, 1, 2, 1, 4, 3, 1, 3, 4, 4, 1, 1, 2, 2, 2,
1, 3, 2, 1, 3, 2, 1, 2, 1, 1, 2, 2, 4, 1, 2, 1, 2, 2,
4, 2, 4, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2,
4, 2, 1, 2, 2, 2, 4, 2, 2, 1, 1, 4, 3, 2, 3, 2, 2, 2,
2, 2, 4, 2, 2, 4, 2, 2, 2, 2, 3, 2, 3, 2, 3, 1, 3, 2,
1, 1, 2, 4, 2, 2, 3, 2, 2, 4, 2, 1, 1, 1, 2, 1, 3, 2,
3, 3, 2, 2, 2, 3, 2, 3, 2, 2, 3, 3, 3, 2, 4, 4, 2, 1,
2, 2, 2, 2, 1, 1, 1, 1, 3, 2, 4, 3, 3, 2, 1, 1, 2, 2,
2, 1, 1, 4, 4, 1, 1, 2, 1, 3, 3, 1, 2, 1, 3, 3, 3, 2,
3, 1, 3, 1, 2, 3, 1, 1, 2, 1, 2, 3, 3, 1, 1, 2, 2, 1,
4, 3, 1, 2, 3, 3, 2, 3, 3, 3, 2, 2, 3, 4, 4, 1, 4, 1,
2, 4, 2, 1, 4, 4, 3, 1, 1, 3, 1, 3, 3, 2, 3, 3, 4, 2,
4, 3, 1, 3, 4, 3, 4, 2, 4, 2, 4, 4, 2, 4, 2, 4, 3, 4,
2, 4, 2, 4, 2, 2, 1, 3, 1, 1, 4, 2, 4, 4, 2, 4, 4, 2,
1, 4, 3, 2, 2, 1, 3, 4, 3, 3, 3, 4, 3, 4, 4, 2, 4, 3,
2, 2, 4, 2, 3, 1, 4, 4, 4, 4, 1, 2, 3, 2, 3, 4, 3, 2,
3, 3, 4, 2, 1, 1, 4, 2, 3, 2, 3, 2, 2, 1, 3, 2, 4, 2,
1, 1, 2, 4, 1, 1, 1, 2, 4, 3, 2, 4, 2, 2, 2, 1, 1, 2,
4, 1, 2, 4, 2, 4, 3, 3, 2, 4, 2, 2, 2, 4, 4, 1, 2, 4,
1, 3, 2, 2, 3, 1, 3, 4, 2, 3, 4, 2, 2, 1, 2, 4, 3, 3,
3, 2, 3, 1, 1, 2, 1, 2, 3, 2, 2, 3, 1, 3, 2, 1, 2, 2,
2, 1, 2, 4, 4, 2, 2, 2, 2, 2, 3, 1, 1, 2, 3, 1, 1, 2,
2, 3, 2, 3, 2, 2, 4, 1, 3, 3, 1, 1, 1, 4, 1, 1, 1, 3,
3, 1, 2, 2, 2, 3, 4, 2, 3, 4, 1, 1, 2, 2, 2, 1, 3, 3,
2, 3, 1, 4, 1, 2, 1, 4, 1, 3, 2, 2, 2, 2, 4, 1, 3, 2,
2, 4, 2, 2, 3, 4, 4, 2, 2, 4, 3, 2, 3, 1, 1, 4, 1, 1,
3, 1, 3, 1, 4, 2, 3, 2, 2, 2, 1, 2, 1, 3, 2, 1, 1, 3,
1, 1, 2, 1, 3, 2, 2, 3, 3, 1, 3, 2, 3, 4, 3, 2, 3, 4,
2, 1, 3, 2, 3, 1, 2, 2, 3, 2, 2, 4, 3, 4, 4, 2, 3, 3,
1, 3, 2, 2, 2, 2, 1, 2, 2, 3, 4, 2, 1, 1, 2, 1, 1, 3,
2, 3, 1, 2, 2, 1, 3, 3, 2, 2, 1, 2, 3, 1, 2, 4, 3, 1,
2, 1, 4, 3, 1, 1, 2, 2, 3, 3, 2, 3, 2, 2, 1, 1, 1, 3,
2, 2, 3, 1, 1, 1, 3, 3, 2, 2, 1, 1, 1, 3, 2, 1, 4, 3,
2, 1, 2, 3, 3, 1, 3, 1, 2, 1, 3, 2, 1, 2, 3, 4, 2, 3,
2, 3, 1, 4, 4, 1, 2, 4, 1, 2, 3, 3, 2, 2, 1, 2, 2, 1,
1, 1, 1, 3, 3, 1, 2, 2, 4, 4, 2, 1, 2, 1, 4, 4, 2, 4,
2, 3, 2, 2, 3, 1, 4, 2, 2, 3, 3, 2, 2, 1, 3, 2, 2, 3,
3, 3, 3, 2, 3, 2, 4, 2, 2, 2, 1, 2, 3, 2, 2, 1, 1, 1,
2, 2, 3, 1, 1, 3, 3, 3, 3, 1, 1, 2, 3, 1, 2, 2, 4, 2,
3, 2, 1, 1, 3, 2, 2, 2, 2, 2, 4, 1, 3, 2, 1, 1, 3, 4,
2, 2, 4, 3, 4, 1, 2, 3, 3, 2, 3, 4, 2, 4, 2, 3, 1, 1,
1, 4, 2, 2, 4, 3, 1, 3, 1, 2, 2, 1, 3, 2, 4, 2, 3, 2,
2, 2, 4, 1, 1, 1, 1, 2, 2, 2, 3, 4, 2, 1, 2, 1, 1, 3,
2, 2, 1, 4, 3, 1, 3, 2, 2, 2, 1, 2, 2, 2, 1, 3, 3, 3,
2, 1, 2, 4, 2, 2, 1, 2, 3, 1, 1, 2, 2, 1, 2, 1, 2, 3,
2, 2, 1, 2, 1, 2, 1, 4, 2, 1, 2, 2, 3, 1, 1, 1, 1, 2,
1, 2, 1, 2, 2, 3, 4, 4, 3, 3, 1, 2, 3, 3, 3, 3, 2, 2,
3, 1, 2, 1, 3, 2, 2, 4, 1, 3, 2, 2, 3, 3, 2, 2, 3, 4,
2, 3, 1, 2, 1, 2, 3, 1, 3, 2, 2, 3, 1, 2, 2, 1, 2, 4,
2, 2, 2, 4, 2, 1, 1, 1, 2, 2, 2, 2, 2, 4, 2, 3, 1, 3,
1, 2, 2, 2, 2, 1, 3, 2, 2, 2, 2, 2, 3, 3, 3, 3, 1, 1,
4, 4, 2, 3, 4, 3, 2, 3, 1, 2, 3, 4, 1, 2, 2, 2, 2, 3,
1, 1, 3, 4, 2, 2, 1, 1, 1, 4, 2, 1, 4, 2, 3, 1, 1, 4,
4, 3, 2, 4, 2, 3, 2, 3, 3, 4, 2, 3, 1, 1, 4, 4, 3, 2,
3, 4, 1, 4, 1, 3, 1, 3, 3, 2, 1, 4, 4, 3, 3, 2, 1, 3,
1, 2, 1, 2, 2, 2, 4, 2, 3, 2, 3, 3, 3, 4, 1, 1, 2, 4,
3, 2, 3, 3, 3, 2, 3, 3, 1, 2, 2, 4, 2, 4, 2, 2, 2, 2,
2, 1, 4, 2, 2, 1, 2, 3, 2, 1, 2, 1, 2, 2, 1, 3, 2, 2,
4, 3, 1, 3, 1, 3, 1, 4, 3, 3, 1, 2, 2, 1, 4, 2, 2, 1,
1, 3, 1, 1, 2, 2, 3, 1, 2, 2, 2, 3, 3, 3, 3, 1, 3, 4,
1, 2, 1, 2, 3, 2, 3, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 4,
1, 3, 2, 3, 3, 2, 2, 4, 3, 3, 3, 3, 2, 3, 1, 2, 3, 1,
1, 2, 1, 2, 3, 1, 2, 2, 1, 3, 3, 1, 2, 1, 1, 1, 1, 2,
2, 3, 2, 3, 3, 2, 3, 1, 2, 2, 2, 3, 1, 1, 2, 2, 2, 1,
1, 4, 4, 1, 2, 3, 3, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2,
2, 2, 3, 2, 3, 1, 2, 4, 2, 1, 2, 2, 2, 1, 2, 1, 1, 2,
2, 3, 1, 3, 2, 2, 2, 2, 1, 2, 2, 1, 3, 3, 4, 2, 4, 2,
1, 4, 2, 2, 1, 3, 2, 3, 2, 2, 2, 4, 2, 1, 1, 2, 2, 2,
1, 1, 4, 3, 1, 2, 3, 2, 1, 1, 2, 3, 3, 4, 3, 2, 1, 2,
4, 1, 4, 3, 3, 4, 4, 2, 2, 3, 1, 1, 2, 2, 4, 3, 2, 4,
2, 4, 1, 3, 3, 2, 4, 1, 3, 2, 3, 2, 1, 2, 4, 4, 2, 2,
2, 1, 1, 3, 3, 2, 3, 3, 3, 4, 4, 3, 3, 3, 2, 4, 2, 4,
3, 4, 2, 4, 4, 1, 4, 3, 3, 3, 2, 4, 3, 4, 2, 3, 2, 3,
4, 3, 3, 3, 1, 2, 4, 2, 3, 2, 2, 2, 4, 1, 2, 4, 2, 4,
3, 3, 2, 4, 2, 2, 2, 4, 4, 1, 2, 4, 1, 3, 2, 2, 3, 1,
3, 4, 2, 3, 4, 2, 2, 1, 2, 4, 3, 3, 3, 2, 3, 1, 1, 2,
1, 2, 3, 2, 2, 3, 1, 3, 2, 1, 2, 2, 2, 1, 2, 4, 4, 2,
2, 2, 2, 2, 3, 1, 1, 2, 3, 1, 1, 2, 2, 3, 2, 3, 2, 2,
4, 1, 3, 3, 1, 1, 1, 4, 1, 1, 1, 3, 3, 1, 2, 2, 2, 3,
4, 2, 3, 4, 1, 1, 2, 2, 2, 1, 3, 3, 2, 3, 1, 4, 1, 2,
1, 4, 1, 3, 2, 2, 2, 2, 4, 1, 3, 2, 2, 4, 2, 2, 3, 4,
4, 2, 2, 4, 3, 2, 3, 1, 1, 4, 1, 1, 3, 1, 3, 1, 4, 2,
3, 2, 2, 2, 1, 2, 1, 3, 2, 1, 1, 3, 1, 1, 2, 1, 3, 2,
2, 3, 3, 1, 3, 2, 3, 4, 3, 2, 3, 4, 2, 1, 3, 2, 3, 1,
2, 2, 3, 2, 2, 4, 3, 4, 4, 2, 3, 3, 1, 3, 2, 2, 2, 2,
1, 2, 2, 3, 4, 2, 1, 1, 2, 1, 1, 3, 2, 3, 1, 2, 2, 1,
3, 3, 2, 2, 1, 2, 3, 1, 2, 4, 3, 1, 2, 1, 4, 3, 1, 1,
2, 2, 3, 3, 2, 3, 2, 2, 1, 1, 1, 3, 2, 2, 3, 1, 1, 1,
3, 3, 2, 2, 1, 1, 1, 3, 2, 1, 4, 3, 2, 1, 2, 3, 3, 1,
3, 1, 2, 1, 3, 2, 1, 2, 3, 4, 2, 3, 2, 3, 1, 4, 4, 1,
2, 4, 1, 2, 3, 3, 2, 2, 1, 2, 2, 1, 1, 1, 1, 3, 3, 1,
2, 2, 4, 4, 2, 1, 2, 1, 4, 4, 2, 4, 2, 3, 2, 2, 3, 1,
4, 2, 2, 3, 3, 2, 2, 1, 3, 2, 2, 3, 3, 3, 3, 2, 3, 2,
4, 2, 2, 2, 1, 2, 3, 2, 2, 1, 1, 1, 2, 2, 3, 1, 1, 3,
3, 3, 3, 1, 1, 2, 3, 1, 2, 2, 4, 2, 3, 2, 1, 1, 3, 2,
2, 2, 2, 2, 4, 1, 3, 2, 1, 1, 3, 4, 2, 2, 4, 3, 4, 1,
2, 3, 3, 2, 3, 4, 2, 4, 2, 3, 1, 1, 1, 4, 2, 2, 4, 3,
1, 3, 1, 2, 2, 1, 3, 2, 4, 2, 3, 2, 2, 2, 4, 1, 1, 1,
1, 2, 2, 2, 3, 4, 2, 1, 2, 1, 1, 3, 2, 2, 1, 4, 3, 1,
3, 2, 2, 2, 1, 2, 2, 2, 1, 3, 3, 3, 2, 1, 2, 4, 2, 2,
1, 2, 3, 1, 1, 2, 2, 1, 2, 1, 2, 3, 2, 2, 1, 2, 1, 2,
1, 4, 2, 1, 2, 2, 3, 1, 1, 1, 1, 2, 1, 2, 1, 2, 2, 3,
4, 4, 3, 3, 1, 2, 3, 3, 3, 3, 2, 2, 3, 1, 2, 1, 3, 2,
2, 4, 1, 3, 2, 2, 3, 3, 2, 2, 3, 4, 2, 3, 1, 2, 1, 2,
3, 1, 3, 2, 2, 3, 1, 2, 2, 1, 2, 4, 2, 2, 2, 4, 2, 1,
1, 1, 2, 2, 2, 2, 2, 4, 2, 3, 1, 3, 1, 2, 2, 2, 2, 1,
3, 2, 2, 2, 2, 2, 3, 3, 3, 3, 1, 1, 4, 4, 2, 3, 4, 3,
2, 3, 1, 2, 3, 4, 1, 2, 2, 2, 2, 3, 1, 1, 3, 4, 2, 2,
1, 1, 1, 4, 2, 1, 4, 2, 3, 1, 1, 4, 4, 3, 2, 4, 2, 3,
2, 3, 3, 4, 2, 3, 1, 1, 4, 4, 3, 2, 3, 4, 1, 4, 1, 3,
1, 3, 3, 2, 1, 4, 4, 3, 3, 2, 1, 3, 1, 2, 1, 2, 2, 2,
4, 2, 3, 2, 3, 3, 3, 4, 1, 1, 2, 4, 3, 2, 3, 3, 3, 2,
3, 3, 1, 2, 2, 4, 2, 4, 2, 2, 2, 2, 2, 1, 4, 2, 2, 1,
2, 3, 2, 1, 2, 1, 2, 2, 1, 3, 2, 2, 4, 3, 1, 3, 1, 3,
1, 4, 3, 3, 1, 2, 2, 1, 4, 2, 2, 1, 1, 3, 1, 1, 2, 2,
3, 1, 2, 2, 2, 3, 3, 3, 3, 1, 3, 4, 1, 2, 1, 2, 3, 2,
3, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 4, 1, 3, 2, 3, 3, 2,
2, 4, 3, 3, 3, 3, 2, 3, 1, 2, 3, 1, 1, 2, 1, 2, 3, 1,
2, 2, 1, 3, 3, 1, 2, 1, 1, 1, 1, 2, 2, 3, 2, 3, 3, 2,
3, 1, 2, 2, 2, 3, 1, 1, 2, 2, 2, 1, 1, 4, 4, 1, 2, 3,
3, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 3, 1,
2, 4, 2, 1, 2, 2, 2, 1, 2, 1, 1, 2, 2, 3, 1, 3, 2, 2,
2, 2, 1, 2, 2, 1, 3, 3, 4, 2, 4, 2, 1, 4, 2, 2, 1, 3,
2, 3, 2, 2, 2, 4, 2, 1, 1, 2, 2, 2, 1, 1, 4, 3, 1, 2,
3, 2, 1, 1, 2, 3, 3, 4, 3, 2, 1, 2, 4, 1, 4, 3, 3, 4,
4, 2, 2, 3, 1, 1, 2, 2, 4, 3, 2, 4, 2, 4, 1, 3, 3, 2,
4, 1, 3, 2, 3, 2, 1, 2, 4, 4, 2, 2, 2, 1, 1, 3, 3, 2,
3, 3, 3, 4, 4, 3, 3, 3, 2, 4, 2, 4, 3, 4, 2, 4, 4, 1,
4, 3, 3, 3, 2, 4, 3, 4, 2, 3, 2, 3, 4, 3, 3, 3, 1, 2,
4, 2, 3, 2, 2, 2, 2, 2, 2, 1, 3, 4, 4, 1, 2, 3, 3, 2,
2, 2, 1, 2, 4, 2, 1, 2, 2, 1, 1, 1, 1, 3, 2, 1, 2, 4,
1, 1, 3, 2, 3, 4, 2, 1, 3, 4, 2, 2, 2, 4, 2, 4, 4, 3,
3, 2, 4, 3, 1, 3, 2, 2, 4, 2, 2, 3, 4, 1, 2, 4, 3, 1,
1, 2, 3, 3, 1, 4, 4, 3, 3, 3, 2, 4, 2, 3, 3, 1, 2, 2,
2, 4, 2, 1, 2, 2, 4, 2, 2, 1, 2, 2, 3, 2, 2, 2, 1, 3,
3, 3, 3, 2, 1, 1, 4, 1, 3, 3, 1, 4, 3, 4, 4, 4, 2, 2,
3, 2, 2, 4, 3, 4, 1, 1, 2, 2, 2, 3, 4, 1, 2, 2, 3, 1,
2, 2, 4, 3, 2, 2, 2, 4, 2, 3, 1, 1, 4, 1, 1, 1, 1, 3,
4, 3, 2, 2, 3, 2, 1, 4, 2, 1, 3, 2, 1, 1, 4, 3, 1, 2,
3, 4, 1, 3, 4, 3, 4, 3, 2, 3, 4, 2, 3, 4, 2, 1, 1, 2,
4, 1, 4, 2, 1, 1, 2, 1, 3, 1, 3, 3, 2, 2, 2, 1, 2, 1,
3, 4, 2, 2, 2, 1, 3, 4, 1, 1, 2, 2, 3, 3, 1, 2, 2, 1,
4, 3, 1, 2, 2, 1, 3, 2, 2, 3, 1, 3, 1, 3, 3, 3, 1, 2,
3, 2, 2, 4, 4, 2, 3, 2, 2, 1, 3, 1, 1, 1, 4, 1, 1, 1,
2, 1, 3, 4, 2, 1, 1, 2, 3, 2, 4, 3, 2, 2, 2, 4, 3, 2,
1, 3, 3, 2, 2, 2, 1, 4, 1, 2, 2, 1, 2, 3, 2, 1, 2, 2,
2, 4, 4, 3, 2, 2, 3, 4, 3, 1, 2, 1, 2, 1, 1, 3, 1, 2,
4, 1, 2, 2, 2, 1, 1, 2, 2, 4, 4, 1, 1, 2, 3, 3, 1, 3,
2, 2, 3, 2, 1, 1, 1, 3, 2, 3, 3, 2, 4, 3, 4, 2, 2, 3,
2, 3, 2, 3, 4, 2, 3, 3, 1, 3, 2, 3, 2, 1, 3, 1, 1, 4,
2, 1, 2, 1, 1, 2, 2, 4, 2, 2, 3, 1, 2, 2, 1, 2, 1, 2,
4, 2, 2, 1, 1, 3, 2, 2, 2, 1, 3, 2, 1, 1, 2, 4, 4, 1,
1, 3, 2, 2, 2, 3, 2, 3, 1, 3, 1, 2, 3, 3, 1, 1, 4, 4,
2, 1, 2, 3, 4, 2, 3, 3, 4, 1, 3, 1, 2, 2, 2, 2, 1, 3,
2, 3, 1, 2, 2, 4, 2, 2, 1, 1, 2, 1, 1, 4, 3, 1, 2, 2,
1, 1, 3, 2, 2, 4, 4, 4, 3, 4, 1, 2, 3, 2, 2, 2, 3, 3,
1, 2, 4, 2, 1, 3, 2, 3, 1, 2, 2, 2, 2, 3, 2, 4, 3, 1,
3, 3, 4, 3, 3, 4, 4, 2, 3, 2, 2, 4, 4, 3, 4, 4, 4, 2,
2, 4, 3, 3, 2, 2, 3, 4, 2, 2, 1, 2, 4, 2, 1, 1, 2, 3,
4, 2, 2, 2, 1, 3, 4, 1, 2, 1, 3, 3, 1, 2, 3, 2, 2, 4,
4, 1, 2, 4, 2, 3, 2, 3, 2, 3, 1, 4, 4, 3, 4, 2, 1, 1,
3, 4, 4, 2, 4, 2, 4, 4, 4, 2, 2, 1, 3, 2, 2, 2, 2, 4,
2, 4, 1, 2, 3, 1, 2, 3, 2, 2, 2, 2, 1, 2, 2, 4, 1, 1,
1, 1, 1, 3, 3, 2, 2, 1, 4, 2, 2, 2, 2, 2, 1, 3, 3, 1,
2, 2, 1, 4, 1, 4, 1, 3, 2, 2, 4, 2, 4, 4, 2, 2, 1, 1,
3, 1, 1, 2, 3, 1, 3, 2, 2, 2, 2, 3, 2, 2, 2, 3, 1, 2,
1, 3, 2, 4, 2, 2, 1, 4, 2, 4, 3, 1, 1, 3, 1, 1, 4, 4,
3, 4, 4, 1, 3, 3, 1, 1, 2, 3, 2, 2, 2, 3, 3, 4, 2, 4,
2, 3, 4, 3, 4, 3, 1, 3, 2, 2, 2, 1, 2, 3, 2, 2, 2, 2,
1, 1, 2, 3, 2, 4, 1, 1, 4, 2, 2, 1, 4, 1, 1, 4, 4, 2,
2, 1, 2, 2, 3, 1, 3, 3, 4, 3, 4, 3, 4, 3, 3, 3, 2, 2,
4, 3, 4, 3, 2, 1, 1, 2, 2, 2, 1, 4, 2, 3, 2, 2, 4, 1,
1, 3, 2, 4, 1, 2, 1, 2, 2, 4, 2, 1, 3, 1, 1, 1, 1, 3,
1, 1, 3, 1, 3, 4, 3, 3, 1, 3, 1, 1, 3, 3, 2, 2, 3, 2,
1, 1, 2, 3, 1, 1, 4, 4, 1, 3, 2, 3, 2, 1, 1, 2, 1, 4,
2, 2, 2, 2, 1, 4, 2, 4, 3, 1, 2, 3, 2, 2, 2, 2, 3, 3,
1, 2, 4, 3, 3, 1, 2, 1, 3, 2, 4, 1, 1, 2, 2, 2, 2, 2,
2, 2, 1, 3, 3, 2, 2, 2, 4, 2, 3, 1, 2, 2, 1, 1, 2, 2,
2, 2, 4, 2, 4, 2, 1, 1, 1, 3, 3, 2, 3, 2, 2, 4, 2, 1,
2, 3, 1, 2, 2, 3, 2, 2, 2, 2, 1, 2, 1, 4, 4, 3, 1, 2,
3, 3, 3, 2, 2, 2, 2, 2, 3, 3, 2, 2, 2, 3, 3, 4, 1, 3,
2, 3, 2, 1, 2, 2, 4, 1, 1, 2, 3, 2, 2, 2, 2, 2, 3, 1,
3, 1, 1, 1, 2, 1, 1, 2, 2, 3, 3, 2, 3, 1, 2, 2, 2, 1,
3, 2, 3, 1, 3, 1, 2, 2, 4, 1, 2, 2, 3, 3, 3, 2, 3, 2,
3, 3, 1, 4, 2, 3, 2, 2, 2, 4, 2, 3, 2, 3, 3, 4, 2, 4,
1, 3, 1, 1, 1, 2, 3, 1, 2, 3],
"state": [7, 33, 20, 31, 18, 31, 40, 33, 22, 22, 33, 22, 39, 33,
31, 33, 10, 33, 40, 33, 39, 31, 33, 41, 33, 15, 22, 39,
22, 7, 33, 22, 10, 31, 19, 22, 33, 43, 14, 1, 14, 16,
10, 21, 33, 25, 39, 36, 49, 1, 34, 36, 47, 34, 23, 10,
24, 19, 43, 23, 50, 4, 34, 14, 14, 15, 50, 25, 10, 16,
50, 44, 15, 10, 24, 18, 16, 16, 36, 43, 18, 48, 17, 50,
36, 43, 43, 10, 36, 32, 36, 28, 21, 43, 34, 3, 23, 15,
45, 1, 27, 47, 19, 28, 36, 5, 14, 5, 36, 14, 47, 23,
5, 21, 1, 23, 6, 45, 44, 3, 13, 36, 50, 1, 21, 5,
5, 10, 10, 5, 10, 35, 14, 48, 23, 3, 23, 10, 21, 32,
5, 23, 43, 18, 48, 8, 48, 23, 21, 5, 15, 5, 1, 44,
6, 5, 24, 17, 5, 6, 25, 5, 51, 16, 25, 49, 19, 5,
5, 48, 21, 10, 18, 21, 47, 14, 36, 41, 33, 5, 16, 10,
11, 36, 33, 39, 1, 36, 22, 31, 33, 44, 14, 44, 3, 39,
36, 7, 39, 31, 7, 10, 49, 22, 33, 39, 22, 7, 33, 16,
5, 33, 39, 44, 33, 10, 33, 43, 23, 39, 33, 39, 20, 33,
50, 39, 33, 7, 34, 33, 22, 4, 39, 36, 31, 17, 19, 23,
23, 38, 33, 1, 33, 31, 40, 39, 39, 31, 23, 14, 44, 22,
23, 18, 47, 36, 7, 22, 33, 39, 45, 50, 33, 39, 26, 14,
7, 17, 10, 22, 14, 31, 33, 50, 48, 44, 42, 39, 1, 22,
15, 22, 33, 43, 14, 31, 26, 23, 50, 50, 39, 35, 15, 44,
26, 19, 15, 39, 25, 31, 26, 22, 50, 14, 15, 14, 36, 47,
23, 23, 15, 15, 34, 17, 24, 50, 14, 15, 26, 31, 44, 23,
4, 14, 37, 17, 36, 7, 23, 23, 17, 41, 17, 5, 24, 14,
23, 14, 36, 21, 34, 22, 14, 14, 36, 44, 10, 47, 44, 11,
1, 50, 16, 26, 1, 14, 36, 44, 14, 10, 42, 26, 21, 37,
18, 44, 14, 15, 19, 49, 17, 19, 19, 14, 36, 16, 42, 23,
25, 17, 43, 4, 11, 11, 44, 49, 18, 1, 24, 4, 25, 49,
14, 32, 36, 44, 44, 11, 43, 18, 14, 50, 44, 19, 5, 44,
5, 3, 44, 25, 1, 18, 44, 5, 6, 26, 6, 50, 38, 24,
1, 25, 5, 5, 48, 5, 5, 45, 5, 48, 5, 5, 6, 5,
5, 5, 5, 5, 5, 5, 48, 5, 3, 6, 5, 5, 32, 13,
38, 5, 45, 48, 5, 5, 5, 48, 21, 8, 43, 25, 10, 36,
47, 1, 32, 11, 5, 5, 48, 6, 5, 10, 22, 25, 10, 20,
10, 31, 39, 44, 11, 33, 22, 34, 22, 39, 34, 22, 31, 31,
50, 31, 28, 44, 22, 23, 33, 18, 33, 44, 22, 44, 39, 43,
7, 10, 22, 44, 33, 21, 36, 17, 33, 25, 34, 22, 40, 22,
43, 34, 33, 33, 39, 11, 49, 36, 47, 10, 23, 33, 10, 34,
47, 39, 43, 43, 39, 47, 14, 33, 41, 1, 33, 33, 41, 21,
36, 39, 25, 19, 49, 36, 36, 22, 47, 50, 37, 39, 44, 11,
35, 39, 14, 31, 23, 43, 43, 43, 14, 50, 43, 33, 7, 44,
21, 36, 21, 44, 23, 23, 21, 41, 36, 23, 7, 50, 26, 43,
11, 10, 14, 36, 44, 11, 43, 10, 14, 24, 18, 34, 41, 26,
26, 23, 36, 23, 16, 39, 10, 44, 41, 36, 7, 50, 26, 33,
11, 43, 44, 1, 10, 41, 15, 23, 24, 23, 14, 26, 15, 42,
49, 43, 34, 42, 8, 33, 25, 1, 36, 35, 24, 11, 50, 39,
36, 14, 3, 49, 44, 14, 31, 14, 23, 5, 21, 26, 14, 28,
15, 7, 14, 47, 20, 5, 7, 34, 36, 14, 21, 16, 14, 33,
5, 48, 39, 33, 36, 26, 23, 21, 44, 42, 1, 3, 10, 5,
26, 5, 19, 14, 3, 48, 19, 48, 15, 5, 45, 36, 5, 23,
4, 51, 5, 44, 45, 3, 5, 23, 5, 5, 15, 45, 5, 3,
5, 36, 27, 5, 48, 5, 24, 5, 5, 38, 33, 47, 31, 17,
39, 5, 32, 10, 5, 5, 43, 24, 3, 5, 31, 11, 33, 5,
39, 38, 44, 5, 48, 36, 5, 10, 28, 14, 39, 41, 36, 38,
44, 14, 28, 47, 23, 24, 44, 23, 44, 1, 10, 48, 26, 15,
24, 4, 44, 36, 10, 3, 10, 14, 44, 44, 26, 25, 24, 28,
3, 15, 44, 14, 19, 1, 14, 5, 48, 32, 5, 6, 5, 5,
5, 5, 5, 5, 5, 6, 38, 5, 5, 5, 5, 13, 48, 5,
5, 5, 3, 5, 5, 5, 5, 5, 3, 5, 5, 5, 48, 5,
5, 5, 5, 48, 5, 5, 48, 5, 5, 5, 48, 48, 5, 5,
27, 5, 5, 5, 5, 5, 25, 5, 33, 11, 14, 10, 31, 5,
36, 47, 37, 25, 25, 8, 24, 31, 44, 43, 36, 38, 44, 34,
5, 31, 41, 10, 39, 1, 21, 36, 48, 23, 5, 5, 34, 5,
33, 11, 33, 10, 48, 33, 44, 5, 32, 16, 24, 39, 20, 21,
26, 22, 44, 6, 22, 3, 11, 5, 43, 25, 23, 28, 33, 10,
39, 33, 34, 39, 26, 10, 10, 36, 23, 21, 11, 34, 23, 31,
36, 23, 5, 14, 25, 26, 26, 15, 33, 14, 10, 33, 10, 33,
33, 47, 11, 34, 10, 39, 31, 40, 31, 22, 7, 43, 25, 10,
39, 44, 51, 36, 14, 15, 15, 50, 39, 39, 31, 33, 49, 22,
23, 14, 33, 22, 39, 14, 23, 33, 21, 26, 11, 15, 33, 11,
33, 36, 25, 24, 50, 33, 34, 33, 23, 33, 31, 36, 26, 33,
50, 31, 10, 50, 50, 31, 33, 10, 44, 22, 14, 11, 36, 47,
37, 24, 18, 39, 50, 23, 36, 26, 43, 39, 39, 16, 36, 33,
23, 30, 15, 24, 15, 50, 10, 39, 33, 36, 36, 18, 44, 4,
28, 41, 39, 10, 25, 10, 10, 22, 10, 14, 40, 21, 34, 33,
14, 8, 19, 20, 35, 4, 10, 21, 18, 14, 47, 36, 22, 31,
14, 50, 31, 11, 8, 33, 44, 50, 14, 43, 33, 34, 28, 24,
31, 33, 31, 49, 15, 14, 39, 37, 15, 50, 31, 39, 44, 44,
31, 34, 10, 10, 31, 34, 36, 44, 14, 47, 21, 22, 26, 49,
14, 15, 23, 7, 41, 7, 36, 21, 22, 44, 23, 15, 36, 49,
42, 18, 23, 28, 16, 33, 35, 37, 44, 1, 10, 43, 34, 21,
8, 26, 24, 34, 50, 34, 14, 25, 18, 26, 33, 23, 44, 5,
25, 39, 36, 40, 36, 19, 43, 11, 10, 49, 16, 34, 41, 44,
49, 50, 47, 28, 33, 50, 26, 36, 15, 19, 26, 26, 39, 1,
50, 21, 14, 10, 5, 41, 10, 15, 15, 21, 23, 7, 31, 50,
41, 50, 43, 33, 34, 33, 44, 1, 43, 50, 50, 21, 34, 36,
39, 18, 14, 24, 50, 24, 23, 47, 24, 11, 50, 10, 1, 41,
33, 17, 10, 36, 18, 44, 17, 33, 4, 15, 10, 21, 22, 14,
44, 36, 20, 34, 21, 18, 1, 50, 47, 22, 41, 31, 21, 44,
43, 34, 11, 18, 36, 4, 36, 47, 18, 36, 33, 15, 44, 5,
41, 19, 11, 47, 44, 36, 23, 10, 41, 31, 33, 48, 28, 43,
17, 28, 19, 43, 44, 23, 10, 25, 37, 14, 21, 4, 44, 26,
1, 26, 50, 43, 43, 15, 16, 14, 26, 28, 23, 44, 45, 10,
43, 5, 14, 19, 18, 16, 48, 5, 43, 5, 48, 5, 44, 14,
5, 48, 6, 14, 5, 5, 5, 19, 43, 44, 5, 5, 48, 48,
5, 48, 48, 5, 6, 5, 32, 48, 48, 45, 45, 5, 5, 32,
5, 5, 5, 5, 5, 5, 5, 3, 38, 5, 5, 38, 5, 6,
48, 38, 5, 5, 48, 5, 5, 5, 5, 5, 5, 45, 38, 5,
48, 5, 5, 48, 38, 3, 5, 48, 5, 5, 48, 29, 5, 5,
5, 5, 5, 39, 21, 11, 1, 15, 13, 28, 44, 47, 24, 21,
23, 31, 14, 39, 44, 10, 44, 17, 47, 39, 39, 44, 10, 43,
10, 47, 19, 4, 11, 11, 34, 47, 5, 34, 5, 5, 5, 3,
13, 22, 50, 26, 5, 24, 19, 5, 27, 5, 44, 37, 41, 41,
47, 14, 29, 15, 3, 5, 37, 39, 5, 39, 44, 17, 5, 11,
37, 48, 10, 24, 21, 8, 43, 25, 10, 36, 47, 1, 32, 11,
5, 5, 48, 6, 5, 10, 22, 25, 10, 20, 10, 31, 39, 44,
11, 33, 22, 34, 22, 39, 34, 22, 31, 31, 50, 31, 28, 44,
22, 23, 33, 18, 33, 44, 22, 44, 39, 43, 7, 10, 22, 44,
33, 21, 36, 17, 33, 25, 34, 22, 40, 22, 43, 34, 33, 33,
39, 11, 49, 36, 47, 10, 23, 33, 10, 34, 47, 39, 43, 43,
39, 47, 14, 33, 41, 1, 33, 33, 41, 21, 36, 39, 25, 19,
49, 36, 36, 22, 47, 50, 37, 39, 44, 11, 35, 39, 14, 31,
23, 43, 43, 43, 14, 50, 43, 33, 7, 44, 21, 36, 21, 44,
23, 23, 21, 41, 36, 23, 7, 50, 26, 43, 11, 10, 14, 36,
44, 11, 43, 10, 14, 24, 18, 34, 41, 26, 26, 23, 36, 23,
16, 39, 10, 44, 41, 36, 7, 50, 26, 33, 11, 43, 44, 1,
10, 41, 15, 23, 24, 23, 14, 26, 15, 42, 49, 43, 34, 42,
8, 33, 25, 1, 36, 35, 24, 11, 50, 39, 36, 14, 3, 49,
44, 14, 31, 14, 23, 5, 21, 26, 14, 28, 15, 7, 14, 47,
20, 5, 7, 34, 36, 14, 21, 16, 14, 33, 5, 48, 39, 33,
36, 26, 23, 21, 44, 42, 1, 3, 10, 5, 26, 5, 19, 14,
3, 48, 19, 48, 15, 5, 45, 36, 5, 23, 4, 51, 5, 44,
45, 3, 5, 23, 5, 5, 15, 45, 5, 3, 5, 36, 27, 5,
48, 5, 24, 5, 5, 38, 33, 47, 31, 17, 39, 5, 32, 10,
5, 5, 43, 24, 3, 5, 31, 11, 33, 5, 39, 38, 44, 5,
48, 36, 5, 10, 28, 14, 39, 41, 36, 38, 44, 14, 28, 47,
23, 24, 44, 23, 44, 1, 10, 48, 26, 15, 24, 4, 44, 36,
10, 3, 10, 14, 44, 44, 26, 25, 24, 28, 3, 15, 44, 14,
19, 1, 14, 5, 48, 32, 5, 6, 5, 5, 5, 5, 5, 5,
5, 6, 38, 5, 5, 5, 5, 13, 48, 5, 5, 5, 3, 5,
5, 5, 5, 5, 3, 5, 5, 5, 48, 5, 5, 5, 5, 48,
5, 5, 48, 5, 5, 5, 48, 48, 5, 5, 27, 5, 5, 5,
5, 5, 3, 11, 5, 43, 25, 23, 28, 33, 10, 39, 33, 34,
39, 26, 10, 10, 36, 23, 21, 11, 34, 23, 31, 36, 23, 5,
14, 25, 26, 26, 15, 33, 14, 10, 33, 10, 33, 33, 47, 11,
34, 10, 39, 31, 40, 31, 22, 7, 43, 25, 10, 39, 44, 51,
36, 14, 15, 15, 50, 39, 39, 31, 33, 49, 22, 23, 14, 33,
22, 39, 14, 23, 33, 21, 26, 11, 15, 33, 11, 33, 36, 25,
24, 50, 33, 34, 33, 23, 33, 31, 36, 26, 33, 50, 31, 10,
50, 50, 31, 33, 10, 44, 22, 14, 11, 36, 47, 37, 24, 18,
39, 50, 23, 36, 26, 43, 39, 39, 16, 36, 33, 23, 30, 15,
24, 15, 50, 10, 39, 33, 36, 36, 18, 44, 4, 28, 41, 39,
10, 25, 10, 10, 22, 10, 14, 40, 21, 34, 33, 14, 8, 19,
20, 35, 4, 10, 21, 18, 14, 47, 36, 22, 31, 14, 50, 31,
11, 8, 33, 44, 50, 14, 43, 33, 34, 28, 24, 31, 33, 31,
49, 15, 14, 39, 37, 15, 50, 31, 39, 44, 44, 31, 34, 10,
10, 31, 34, 36, 44, 14, 47, 21, 22, 26, 49, 14, 15, 23,
7, 41, 7, 36, 21, 22, 44, 23, 15, 36, 49, 42, 18, 23,
28, 16, 33, 35, 37, 44, 1, 10, 43, 34, 21, 8, 26, 24,
34, 50, 34, 14, 25, 18, 26, 33, 23, 44, 5, 25, 39, 36,
40, 36, 19, 43, 11, 10, 49, 16, 34, 41, 44, 49, 50, 47,
28, 33, 50, 26, 36, 15, 19, 26, 26, 39, 1, 50, 21, 14,
10, 5, 41, 10, 15, 15, 21, 23, 7, 31, 50, 41, 50, 43,
33, 34, 33, 44, 1, 43, 50, 50, 21, 34, 36, 39, 18, 14,
24, 50, 24, 23, 47, 24, 11, 50, 10, 1, 41, 33, 17, 10,
36, 18, 44, 17, 33, 4, 15, 10, 21, 22, 14, 44, 36, 20,
34, 21, 18, 1, 50, 47, 22, 41, 31, 21, 44, 43, 34, 11,
18, 36, 4, 36, 47, 18, 36, 33, 15, 44, 5, 41, 19, 11,
47, 44, 36, 23, 10, 41, 31, 33, 48, 28, 43, 17, 28, 19,
43, 44, 23, 10, 25, 37, 14, 21, 4, 44, 26, 1, 26, 50,
43, 43, 15, 16, 14, 26, 28, 23, 44, 45, 10, 43, 5, 14,
19, 18, 16, 48, 5, 43, 5, 48, 5, 44, 14, 5, 48, 6,
14, 5, 5, 5, 19, 43, 44, 5, 5, 48, 48, 5, 48, 48,
5, 6, 5, 32, 48, 48, 45, 45, 5, 5, 32, 5, 5, 5,
5, 5, 5, 5, 3, 38, 5, 5, 38, 5, 6, 48, 38, 5,
5, 48, 5, 5, 5, 5, 5, 5, 45, 38, 5, 48, 5, 5,
48, 38, 3, 5, 48, 5, 5, 48, 29, 5, 5, 5, 5, 5,
39, 21, 11, 1, 15, 13, 28, 44, 47, 24, 21, 23, 31, 14,
39, 44, 10, 44, 17, 47, 39, 39, 44, 10, 43, 10, 47, 19,
4, 11, 11, 34, 47, 5, 34, 5, 5, 5, 3, 13, 22, 50,
26, 5, 24, 19, 5, 27, 5, 44, 37, 41, 41, 47, 14, 29,
15, 3, 5, 37, 39, 5, 39, 44, 17, 5, 11, 37, 48, 10,
24, 6, 14, 40, 23, 39, 35, 33, 10, 45, 39, 22, 44, 39,
40, 10, 21, 33, 5, 15, 47, 41, 33, 22, 18, 34, 34, 7,
39, 22, 39, 33, 36, 22, 34, 39, 5, 39, 33, 31, 21, 34,
15, 33, 31, 33, 21, 14, 36, 15, 36, 23, 31, 22, 10, 22,
22, 15, 15, 15, 31, 22, 41, 33, 31, 22, 33, 36, 40, 22,
22, 33, 10, 21, 21, 33, 39, 23, 23, 34, 33, 23, 47, 50,
5, 47, 44, 23, 7, 10, 11, 10, 26, 5, 15, 26, 36, 23,
7, 5, 10, 7, 23, 33, 42, 10, 48, 33, 33, 14, 15, 14,
41, 11, 14, 39, 14, 14, 5, 39, 39, 36, 20, 39, 21, 28,
50, 40, 7, 7, 19, 44, 4, 19, 14, 5, 10, 24, 37, 44,
1, 44, 44, 44, 10, 37, 19, 10, 37, 19, 32, 33, 3, 14,
33, 33, 37, 43, 14, 50, 16, 17, 26, 42, 24, 14, 23, 24,
35, 21, 47, 5, 10, 17, 10, 15, 17, 50, 33, 6, 5, 36,
43, 44, 16, 10, 31, 46, 34, 15, 33, 15, 32, 3, 33, 33,
17, 50, 41, 44, 22, 10, 31, 47, 24, 6, 22, 21, 14, 47,
33, 33, 41, 36, 47, 32, 10, 31, 36, 23, 43, 36, 43, 10,
49, 33, 7, 24, 26, 33, 45, 3, 14, 44, 47, 11, 33, 24,
15, 28, 10, 47, 47, 31, 3, 14, 42, 26, 21, 26, 31, 39,
47, 31, 40, 30, 32, 26, 50, 13, 26, 17, 49, 36, 23, 10,
19, 3, 22, 1, 11, 47, 33, 14, 24, 11, 39, 25, 38, 44,
43, 13, 44, 45, 19, 24, 5, 26, 34, 14, 24, 38, 23, 39,
36, 14, 6, 26, 6, 19, 36, 22, 36, 36, 7, 39, 39, 24,
14, 26, 14, 23, 50, 39, 49, 25, 11, 50, 5, 22, 44, 36,
10, 47, 39, 39, 47, 47, 21, 18, 18, 45, 1, 10, 37, 14,
50, 50, 10, 39, 24, 34, 41, 9, 10, 11, 35, 35, 16, 50,
17, 25, 42, 15, 33, 14, 16, 23, 14, 6, 3, 10, 10, 41,
47, 42, 32, 6, 5, 44, 5, 5, 5, 5, 5, 5, 5, 5,
5, 38, 5, 5, 5, 5, 38, 5, 5, 5, 48, 48, 5, 38,
48, 5, 5, 5, 5, 5, 5, 5, 25, 48, 5, 48, 5, 38,
5, 5, 5, 5, 1, 44, 44, 5, 5, 5, 48, 3, 6, 5,
6, 3, 25, 48, 5, 5, 5, 5, 5, 5, 5, 48, 27, 5,
48, 5, 5, 5, 5, 5, 5, 5, 5, 29, 5, 5, 5, 33,
33, 47, 11, 34, 10, 39, 31, 40, 31, 22, 7, 43, 25, 10,
39, 44, 51, 36, 14, 15, 15, 50, 39, 39, 31, 33, 49, 22,
23, 14, 33, 22, 39, 14, 23, 33, 21, 26, 11, 15, 33, 11,
33, 36, 25, 24, 50, 33, 34, 33, 23, 33, 31, 36, 26, 33,
50, 31, 10, 50, 50, 31, 33, 10, 44, 22, 14, 11, 36, 47,
37, 24, 18, 39, 50, 23, 36, 26, 43, 39, 39, 16, 36, 33,
23, 30, 15, 24, 15, 50, 10, 39, 33, 36, 36, 18, 44, 4,
28, 41, 39, 10, 25, 10, 10, 22, 10, 14, 40, 21, 34, 33,
14, 8, 19, 20, 35, 4, 10, 21, 18, 14, 47, 36, 22, 31,
14, 50, 31, 11, 8, 33, 44, 50, 14, 43, 33, 34, 28, 24,
31, 33, 31, 49, 15, 14, 39, 37, 15, 50, 31, 39, 44, 44,
31, 34, 10, 10, 31, 34, 36, 44, 14, 47, 21, 22, 26, 49,
14, 15, 23, 7, 41, 7, 36, 21, 22, 44, 23, 15, 36, 49,
42, 18, 23, 28, 16, 33, 35, 37, 44, 1, 10, 43, 34, 21,
8, 26, 24, 34, 50, 34, 14, 25, 18, 26, 33, 23, 44, 5,
25, 39, 36, 40, 36, 19, 43, 11, 10, 49, 16, 34, 41, 44,
49, 50, 47, 28, 33, 50, 26, 36, 15, 19, 26, 26, 39, 1,
50, 21, 14, 10, 5, 41, 10, 15, 15, 21, 23, 7, 31, 50,
41, 50, 43, 33, 34, 33, 44, 1, 43, 50, 50, 21, 34, 36,
39, 18, 14, 24, 50, 24, 23, 47, 24, 11, 50, 10, 1, 41,
33, 17, 10, 36, 18, 44, 17, 33, 4, 15, 10, 21, 22, 14,
44, 36, 20, 34, 21, 18, 1, 50, 47, 22, 41, 31, 21, 44,
43, 34, 11, 18, 36, 4, 36, 47, 18, 36, 33, 15, 44, 5,
41, 19, 11, 47, 44, 36, 23, 10, 41, 31, 33, 48, 28, 43,
17, 28, 19, 43, 44, 23, 10, 25, 37, 14, 21, 4, 44, 26,
1, 26, 50, 43, 43, 15, 16, 14, 26, 28, 23, 44, 45, 10,
43, 5, 14, 19, 18, 16, 48, 5, 43, 5, 48, 5, 44, 14,
5, 48, 6, 14, 5, 5, 5, 19, 43, 44, 5, 5, 48, 48,
5, 48, 48, 5, 6, 5, 32, 48, 48, 45, 45, 5, 5, 32,
5, 5, 5, 5, 5, 5, 5, 3, 38, 5, 5, 38, 5, 6,
48, 38, 5, 5, 48, 5, 5, 5, 5, 5, 5, 45, 38, 5,
48, 5, 5, 48, 38, 3, 5, 48, 5, 5, 48, 29, 5, 5,
5, 5, 5, 39, 21, 11, 1, 15, 13, 28, 44, 47, 24, 21,
23, 31, 14, 39, 44, 10, 44, 17, 47, 39, 39, 44, 10, 43,
10, 47, 19, 4, 11, 11, 34, 47, 5, 34, 5, 5, 5, 3,
13, 22, 50, 26, 5, 24, 19, 5, 27, 5, 44, 37, 41, 41,
47, 14, 29, 15, 3, 5, 37, 39, 5, 39, 44, 17, 5, 11,
37, 48, 10, 24, 6, 14, 40, 23, 39, 35, 33, 10, 45, 39,
22, 44, 39, 40, 10, 21, 33, 5, 15, 47, 41, 33, 22, 18,
34, 34, 7, 39, 22, 39, 33, 36, 22, 34, 39, 5, 39, 33,
31, 21, 34, 15, 33, 31, 33, 21, 14, 36, 15, 36, 23, 31,
22, 10, 22, 22, 15, 15, 15, 31, 22, 41, 33, 31, 22, 33,
36, 40, 22, 22, 33, 10, 21, 21, 33, 39, 23, 23, 34, 33,
23, 47, 50, 5, 47, 44, 23, 7, 10, 11, 10, 26, 5, 15,
26, 36, 23, 7, 5, 10, 7, 23, 33, 42, 10, 48, 33, 33,
14, 15, 14, 41, 11, 14, 39, 14, 14, 5, 39, 39, 36, 20,
39, 21, 28, 50, 40, 7, 7, 19, 44, 4, 19, 14, 5, 10,
24, 37, 44, 1, 44, 44, 44, 10, 37, 19, 10, 37, 19, 32,
33, 3, 14, 33, 33, 37, 43, 14, 50, 16, 17, 26, 42, 24,
14, 23, 24, 35, 21, 47, 5, 10, 17, 10, 15, 17, 50, 33,
6, 5, 36, 43, 44, 16, 10, 31, 46, 34, 15, 33, 15, 32,
3, 33, 33, 17, 50, 41, 44, 22, 10, 31, 47, 24, 6, 22,
21, 14, 47, 33, 33, 41, 36, 47, 32, 10, 31, 36, 23, 43,
36, 43, 10, 49, 33, 7, 24, 26, 33, 45, 3, 14, 44, 47,
11, 33, 24, 15, 28, 10, 47, 47, 31, 3, 14, 42, 26, 21,
26, 31, 39, 47, 31, 40, 30, 32, 26, 50, 13, 26, 17, 49,
36, 23, 10, 19, 3, 22, 1, 11, 47, 33, 14, 24, 11, 39,
25, 38, 44, 43, 13, 44, 45, 19, 24, 5, 26, 34, 14, 24,
38, 23, 39, 36, 14, 6, 26, 6, 19, 36, 22, 36, 36, 7,
39, 39, 24, 14, 26, 14, 23, 50, 39, 49, 25, 11, 50, 5,
22, 44, 36, 10, 47, 39, 39, 47, 47, 21, 18, 18, 45, 1,
10, 37, 14, 50, 50, 10, 39, 24, 34, 41, 9, 10, 11, 35,
35, 16, 50, 17, 25, 42, 15, 33, 14, 16, 23, 14, 6, 3,
10, 10, 41, 47, 42, 32, 6, 5, 44, 5, 5, 5, 5, 5,
5, 5, 5, 5, 38, 5, 5, 5, 5, 38, 5, 5, 5, 48,
48, 5, 38, 48, 5, 5, 5, 5, 5, 5, 5, 25, 48, 5,
48, 5, 38, 5, 5, 5, 5, 1, 44, 44, 5, 5, 5, 48,
3, 6, 5, 6, 3, 25, 48, 5, 5, 5, 5, 5, 5, 5,
48, 27, 5, 48, 5, 5, 5, 5, 5, 5, 5, 5, 29, 5,
5, 5, 1, 1, 39, 43, 43, 25, 1, 44, 44, 39, 46, 33,
33, 39, 5, 32, 5, 5, 5, 5, 37, 49, 34, 10, 10, 10,
11, 41, 28, 44, 32, 5, 32, 28, 13, 48, 26, 6, 25, 44,
39, 34, 39, 10, 22, 37, 24, 50, 50, 16, 36, 42, 24, 31,
33, 25, 44, 14, 34, 41, 21, 37, 44, 5, 39, 26, 26, 14,
50, 44, 49, 10, 42, 10, 1, 31, 39, 40, 33, 47, 48, 5,
31, 36, 23, 36, 15, 33, 39, 26, 6, 10, 43, 34, 11, 18,
41, 7, 22, 23, 36, 36, 36, 22, 40, 10, 18, 48, 44, 44,
25, 4, 25, 34, 47, 11, 42, 41, 21, 33, 39, 10, 33, 23,
44, 34, 18, 10, 23, 43, 14, 10, 39, 5, 5, 5, 5, 5,
44, 10, 33, 10, 11, 18, 24, 21, 37, 1, 47, 26, 3, 39,
47, 36, 20, 14, 23, 29, 25, 5, 18, 41, 44, 33, 5, 39,
23, 39, 17, 1, 15, 44, 25, 47, 44, 43, 21, 33, 36, 5,
44, 19, 20, 23, 23, 15, 36, 47, 39, 31, 33, 47, 22, 10,
22, 15, 24, 17, 17, 34, 33, 6, 23, 23, 36, 31, 39, 30,
31, 31, 31, 39, 31, 23, 22, 14, 23, 23, 15, 15, 23, 6,
22, 16, 47, 26, 22, 33, 20, 36, 23, 19, 22, 7, 14, 22,
33, 11, 41, 19, 21, 49, 23, 48, 15, 22, 10, 22, 23, 36,
16, 10, 39, 13, 28, 17, 26, 15, 31, 31, 25, 25, 10, 44,
31, 11, 22, 3, 41, 25, 14, 14, 14, 21, 36, 43, 37, 21,
4, 48, 5, 6, 5, 5, 5, 44, 19, 45, 3, 5, 44, 45,
4, 44, 25, 50, 22, 19, 11, 34, 44, 4, 1, 44, 44, 33,
33, 40, 33, 5, 23, 44, 37, 33, 1, 14, 5, 44, 50, 34,
26, 14, 16, 14, 44, 21, 36, 18, 39, 21, 44, 10, 22, 50,
48, 6, 24, 28, 38, 31, 44, 19, 50, 26, 17, 44, 14, 1,
10, 44, 44, 44, 5, 5, 48, 38, 14, 5, 26, 4, 47, 44,
43, 34, 16, 41, 44, 44, 39, 23, 36, 31, 22, 26, 31, 49,
26, 26, 18, 9, 39, 10, 33, 44, 25, 39, 32, 50, 21, 34,
33, 14, 26, 10, 11, 10, 34, 11, 43, 31, 50, 33, 31, 14,
18, 28, 18, 21, 14, 34, 16, 44, 44, 37, 5, 5, 13, 5,
27, 6, 35, 50, 24, 39, 39, 15, 48, 38, 33, 48, 27, 48,
38, 48, 48, 15, 5, 5, 5, 38, 5, 5, 48, 5, 5, 48,
23, 15, 26, 48, 5, 38, 48, 5, 5, 38, 48, 48, 48, 5,
48, 29, 5, 48, 5, 5, 5, 48, 5, 5, 5, 43, 6, 14,
40, 23, 39, 35, 33, 10, 45, 39, 22, 44, 39, 40, 10, 21,
33, 5, 15, 47, 41, 33, 22, 18, 34, 34, 7, 39, 22, 39,
33, 36, 22, 34, 39, 5, 39, 33, 31, 21, 34, 15, 33, 31,
33, 21, 14, 36, 15, 36, 23, 31, 22, 10, 22, 22, 15, 15,
15, 31, 22, 41, 33, 31, 22, 33, 36, 40, 22, 22, 33, 10,
21, 21, 33, 39, 23, 23, 34, 33, 23, 47, 50, 5, 47, 44,
23, 7, 10, 11, 10, 26, 5, 15, 26, 36, 23, 7, 5, 10,
7, 23, 33, 42, 10, 48, 33, 33, 14, 15, 14, 41, 11, 14,
39, 14, 14, 5, 39, 39, 36, 20, 39, 21, 28, 50, 40, 7,
7, 19, 44, 4, 19, 14, 5, 10, 24, 37, 44, 1, 44, 44,
44, 10, 37, 19, 10, 37, 19, 32, 33, 3, 14, 33, 33, 37,
43, 14, 50, 16, 17, 26, 42, 24, 14, 23, 24, 35, 21, 47,
5, 10, 17, 10, 15, 17, 50, 33, 6, 5, 36, 43, 44, 16,
10, 31, 46, 34, 15, 33, 15, 32, 3, 33, 33, 17, 50, 41,
44, 22, 10, 31, 47, 24, 6, 22, 21, 14, 47, 33, 33, 41,
36, 47, 32, 10, 31, 36, 23, 43, 36, 43, 10, 49, 33, 7,
24, 26, 33, 45, 3, 14, 44, 47, 11, 33, 24, 15, 28, 10,
47, 47, 31, 3, 14, 42, 26, 21, 26, 31, 39, 47, 31, 40,
30, 32, 26, 50, 13, 26, 17, 49, 36, 23, 10, 19, 3, 22,
1, 11, 47, 33, 14, 24, 11, 39, 25, 38, 44, 43, 13, 44,
45, 19, 24, 5, 26, 34, 14, 24, 38, 23, 39, 36, 14, 6,
26, 6, 19, 36, 22, 36, 36, 7, 39, 39, 24, 14, 26, 14,
23, 50, 39, 49, 25, 11, 50, 5, 22, 44, 36, 10, 47, 39,
39, 47, 47, 21, 18, 18, 45, 1, 10, 37, 14, 50, 50, 10,
39, 24, 34, 41, 9, 10, 11, 35, 35, 16, 50, 17, 25, 42,
15, 33, 14, 16, 23, 14, 6, 3, 10, 10, 41, 47, 42, 32,
6, 5, 44, 5, 5, 5, 5, 5, 5, 5, 5, 5, 38, 5,
5, 5, 5, 38, 5, 5, 5, 48, 48, 5, 38, 48, 5, 5,
5, 5, 5, 5, 5, 25, 48, 5, 48, 5, 38, 5, 5, 5,
5, 1, 44, 44, 5, 5, 5, 48, 3, 6, 5, 6, 3, 25,
48, 5, 5, 5, 5, 5, 5, 5, 48, 27, 5, 48, 5, 5,
5, 5, 5, 5, 5, 5, 29, 5, 5, 5, 1, 1, 39, 43,
43, 25, 1, 44, 44, 39, 46, 33, 33, 39, 5, 32, 5, 5,
5, 5, 37, 49, 34, 10, 10, 10, 11, 41, 28, 44, 32, 5,
32, 28, 13, 48, 26, 6, 25, 44, 39, 34, 39, 10, 22, 37,
24, 50, 50, 16, 36, 42, 24, 31, 33, 25, 44, 14, 34, 41,
21, 37, 44, 5, 39, 26, 26, 14, 50, 50, 44, 49, 10, 42,
10, 1, 31, 39, 40, 33, 47, 48, 5, 31, 36, 23, 36, 15,
33, 39, 26, 6, 10, 43, 34, 11, 18, 41, 7, 22, 23, 36,
36, 36, 22, 40, 10, 18, 48, 44, 44, 25, 4, 25, 34, 47,
11, 42, 41, 21, 33, 39, 10, 33, 23, 44, 34, 18, 10, 23,
43, 14, 10, 39, 5, 5, 5, 5, 5, 44, 10, 33, 10, 11,
18, 24, 21, 37, 1, 47, 26, 3, 39, 47, 36, 20, 14, 23,
29, 25, 5, 18, 41, 44, 33, 5, 39, 23, 39, 17, 1, 15,
44, 25, 47, 44, 43, 21, 33, 36, 5, 44, 19, 20, 23, 23,
15, 36, 47, 39, 31, 33, 47, 22, 10, 22, 15, 24, 17, 17,
34, 33, 6, 23, 23, 36, 31, 39, 30, 31, 31, 31, 39, 31,
23, 22, 14, 23, 23, 15, 15, 23, 6, 22, 16, 47, 26, 22,
33, 20, 36, 23, 19, 22, 7, 14, 22, 33, 11, 41, 19, 21,
49, 23, 48, 15, 22, 10, 22, 23, 36, 16, 10, 39, 13, 28,
17, 26, 15, 31, 31, 25, 25, 10, 44, 31, 11, 22, 3, 41,
25, 14, 14, 14, 21, 36, 43, 37, 21, 4, 48, 5, 6, 5,
5, 5, 44, 19, 45, 3, 5, 44, 45, 4, 44, 25, 50, 22,
19, 11, 34, 49, 44, 4, 1, 44, 44, 33, 33, 40, 33, 5,
23, 44, 37, 33, 1, 14, 5, 44, 50, 34, 26, 14, 16, 14,
44, 21, 36, 18, 39, 21, 44, 10, 22, 50, 48, 6, 24, 14,
28, 38, 31, 44, 19, 50, 26, 17, 44, 14, 1, 10, 44, 44,
44, 5, 5, 48, 38, 14, 5, 26, 4, 47, 44, 43, 34, 16,
41, 44, 44, 39, 23, 36, 31, 22, 26, 31, 49, 26, 26, 18,
9, 39, 10, 33, 44, 25, 39, 32, 50, 21, 34, 33, 14, 26,
10, 11, 10, 34, 11, 43, 31, 50, 33, 31, 14, 18, 28, 18,
21, 14, 34, 16, 44, 44, 37, 5, 5, 13, 5, 27, 6, 35,
50, 24, 39, 39, 15, 48, 38, 33, 48, 27, 48, 38, 48, 48,
15, 5, 5, 5, 38, 5, 5, 48, 5, 5, 48, 23, 15, 26,
48, 5, 38, 48, 5, 5, 38, 48, 48, 48, 5, 48, 29, 5,
48, 5, 5, 5, 48, 5, 5, 5, 43, 22, 22, 46, 33, 33,
31, 6, 23, 43, 18, 43, 23, 18, 36, 15, 36, 18, 44, 43,
47, 34, 23, 34, 25, 11, 43, 14, 25, 36, 21, 5, 10, 10,
38, 47, 5, 34, 5, 10, 43, 21, 33, 15, 36, 7, 25, 5,
33, 31, 33, 33, 43, 11, 43, 44, 33, 39, 8, 7, 33, 36,
31, 36, 22, 33, 3, 33, 39, 21, 11, 10, 18, 47, 34, 44,
10, 10, 47, 23, 11, 47, 10, 43, 47, 34, 36, 42, 23, 23,
23, 10, 10, 3, 19, 5, 14, 18, 38, 35, 21, 21, 47, 11,
11, 31, 10, 15, 15, 33, 33, 31, 33, 22, 22, 31, 10, 41,
41, 36, 15, 17, 22, 39, 20, 23, 33, 33, 33, 23, 24, 23,
23, 36, 23, 23, 50, 28, 33, 26, 33, 33, 36, 36, 15, 14,
22, 26, 21, 36, 33, 36, 14, 1, 11, 23, 50, 31, 4, 33,
28, 44, 39, 19, 19, 37, 43, 44, 44, 25, 19, 25, 15, 37,
47, 33, 4, 50, 14, 16, 44, 44, 26, 25, 50, 21, 50, 26,
14, 22, 43, 37, 36, 44, 47, 37, 10, 10, 18, 34, 39, 33,
36, 36, 23, 36, 11, 33, 47, 22, 30, 33, 44, 33, 33, 14,
5, 36, 36, 25, 44, 33, 34, 31, 31, 31, 33, 39, 33, 28,
33, 33, 33, 33, 39, 22, 36, 7, 39, 39, 33, 44, 15, 33,
14, 23, 23, 23, 23, 23, 43, 40, 33, 10, 10, 25, 31, 1,
50, 47, 18, 5, 44, 5, 34, 11, 43, 49, 20, 50, 50, 4,
47, 44, 42, 24, 28, 23, 22, 24, 34, 44, 39, 7, 22, 33,
44, 1, 37, 10, 4, 15, 44, 44, 25, 33, 7, 35, 15, 21,
35, 14, 44, 1, 31, 18, 33, 15, 11, 35, 43, 1, 39, 50,
44, 22, 33, 5, 44, 5, 44, 32, 43, 45, 44, 44, 44, 10,
25, 39, 33, 44, 34, 24, 28, 40, 31, 33, 25, 44, 24, 24,
43, 25, 39, 8, 24, 15, 26, 10, 44, 44, 39, 36, 14, 50,
19, 33, 33, 33, 36, 17, 14, 4, 44, 44, 28, 24, 50, 44,
26, 31, 35, 17, 17, 14, 45, 3, 5, 48, 44, 32, 33, 5,
3, 6, 36, 26, 14, 4, 15, 23, 23, 5, 17, 11, 18, 44,
41, 5, 28, 24, 5, 26, 33, 42, 34, 14, 34, 33, 19, 48,
3, 5, 3, 48, 48, 5, 48, 5, 5, 16, 5, 48, 5, 5,
5, 5, 5, 32, 5, 32, 32, 5, 45, 6, 5, 5, 5, 38,
6, 44, 50, 27, 15, 5, 5, 38, 5, 38, 5, 38, 5, 5,
50, 24, 3, 5, 5, 5, 24, 6, 5, 3, 16, 5, 5, 48,
38, 5, 29, 31, 5, 5, 48, 27, 48, 6, 25, 5, 29, 5,
48, 5, 48, 32, 31, 5, 47, 5, 33, 5, 33, 5, 5, 33,
5, 5, 5, 5, 43, 35, 22, 22, 46, 33, 33, 31, 6, 23,
43, 18, 43, 23, 18, 36, 15, 36, 18, 44, 43, 47, 34, 23,
34, 25, 11, 43, 14, 25, 36, 21, 5, 10, 10, 38, 47, 5,
34, 5, 10, 43, 21, 33, 15, 36, 7, 25, 5, 33, 31, 33,
33, 43, 11, 43, 44, 33, 39, 8, 7, 33, 36, 31, 36, 22,
33, 3, 33, 39, 21, 11, 10, 18, 47, 34, 44, 10, 10, 47,
23, 11, 47, 10, 43, 47, 34, 36, 42, 23, 23, 23, 10, 10,
3, 19, 5, 14, 18, 38, 35, 21, 21, 47, 11, 11, 31, 10,
15, 15, 33, 33, 31, 33, 22, 22, 31, 10, 41, 41, 36, 15,
17, 22, 39, 20, 23, 33, 33, 33, 23, 24, 23, 23, 36, 23,
23, 50, 28, 33, 26, 33, 33, 36, 36, 15, 14, 22, 26, 21,
36, 33, 36, 14, 1, 11, 23, 50, 31, 4, 33, 28, 44, 39,
19, 19, 37, 43, 44, 44, 25, 19, 25, 15, 37, 47, 33, 4,
50, 14, 16, 44, 44, 26, 25, 50, 21, 50, 26, 14, 22, 43,
37, 36, 44, 47, 37, 10, 10, 18, 34, 39, 33, 36, 36, 23,
36, 11, 33, 47, 22, 30, 33, 44, 33, 33, 14, 5, 36, 36,
25, 44, 33, 34, 31, 31, 31, 33, 39, 33, 28, 33, 33, 33,
33, 39, 22, 36, 7, 39, 39, 33, 44, 15, 33, 14, 23, 23,
23, 23, 23, 43, 40, 33, 10, 10, 25, 31, 1, 50, 47, 18,
5, 44, 5, 34, 11, 43, 49, 20, 50, 50, 4, 47, 44, 42,
24, 28, 23, 22, 24, 34, 44, 39, 7, 22, 33, 44, 1, 37,
10, 4, 15, 44, 44, 25, 33, 7, 35, 15, 21, 35, 14, 44,
1, 31, 18, 33, 15, 11, 35, 43, 1, 39, 50, 44, 22, 33,
5, 44, 5, 44, 32, 43, 45, 44, 44, 44, 10, 25, 39, 33,
44, 34, 24, 28, 40, 31, 33, 25, 44, 24, 24, 43, 25, 39,
8, 24, 15, 26, 10, 44, 44, 39, 36, 14, 50, 19, 33, 33,
33, 36, 17, 14, 4, 44, 44, 28, 24, 50, 44, 26, 31, 35,
17, 17, 14, 45, 3, 5, 48, 44, 32, 33, 5, 3, 6, 36,
26, 14, 4, 15, 23, 23, 5, 17, 11, 18, 44, 41, 5, 28,
24, 5, 26, 33, 42, 34, 14, 34, 33, 19, 48, 3, 5, 3,
48, 48, 5, 48, 5, 5, 16, 5, 48, 5, 5, 5, 5, 5,
32, 5, 32, 32, 5, 45, 6, 5, 5, 5, 38, 6, 44, 50,
27, 15, 5, 5, 38, 5, 38, 5, 38, 5, 5, 50, 24, 3,
5, 5, 5, 24, 6, 5, 3, 16, 5, 5, 48, 38, 5, 29,
31, 5, 5, 48, 27, 48, 6, 25, 5, 29, 5, 48, 5, 48,
32, 31, 5, 47, 5, 33, 5, 33, 5, 5, 33, 5, 5, 5,
5, 43, 35, 31, 33, 39, 31, 40, 22, 22, 33, 33, 39, 33,
39, 33, 39, 33, 31, 39, 31, 39, 39, 39, 31, 39, 31, 23,
7, 33, 39, 31, 7, 39, 33, 31, 22, 39, 36, 31, 31, 33,
22, 17, 7, 39, 33, 30, 31, 22, 7, 39, 36, 26, 14, 39,
31, 39, 33, 42, 22, 33, 33, 33, 36, 50, 33, 24, 39, 33,
22, 40, 26, 36, 23, 23, 23, 39, 22, 33, 33, 42, 50, 33,
23, 22, 36, 14, 15, 15, 15, 14, 50, 36, 26, 14, 24, 33,
14, 24, 50, 33, 16, 17, 15, 36, 14, 50, 14, 36, 36, 14,
24, 15, 14, 26, 35, 1, 44, 50, 14, 50, 9, 16, 33, 42,
47, 25, 7, 16, 16, 23, 23, 26, 24, 50, 44, 23, 17, 23,
41, 42, 25, 37, 18, 50, 11, 47, 26, 41, 23, 36, 23, 44,
10, 15, 10, 36, 41, 36, 14, 44, 36, 50, 49, 34, 41, 42,
21, 26, 10, 47, 14, 41, 37, 47, 50, 47, 19, 43, 47, 36,
19, 10, 43, 8, 50, 34, 50, 18, 18, 24, 1, 10, 11, 43,
49, 47, 1, 41, 47, 1, 44, 10, 43, 15, 10, 24, 41, 10,
10, 43, 10, 10, 11, 43, 21, 44, 43, 44, 19, 10, 11, 11,
43, 10, 41, 11, 25, 50, 34, 10, 1, 41, 34, 21, 44, 36,
10, 37, 47, 44, 47, 44, 21, 11, 44, 10, 38, 10, 15, 44,
5, 32, 49, 21, 10, 1, 10, 1, 5, 11, 47, 47, 6, 43,
5, 43, 4, 37, 10, 10, 4, 5, 6, 21, 5, 38, 34, 37,
25, 18, 5, 5, 5, 32, 5, 3, 43, 5, 5, 48, 3, 34,
25, 5, 19, 5, 5, 5, 5, 5, 27, 45, 5, 38, 14, 19,
42, 11, 10, 38, 5, 50, 15, 14, 26, 10, 38, 48, 45, 10,
5, 25, 6, 5, 3, 43, 43, 5, 44, 44, 38, 48, 3, 5,
3, 5, 25, 38, 45, 45, 5, 44, 5, 48, 48, 5, 3, 6,
5, 36, 32, 51, 38, 5, 27, 3, 6, 25, 51, 44, 45, 5,
5, 48, 5, 5, 5, 5, 27, 5, 5, 3, 5, 5, 3, 5,
5, 11, 38, 48, 5, 38, 5, 5, 5, 5, 38, 32, 13, 5,
6, 5, 48, 5, 6, 13, 5, 38, 48, 5, 5, 5, 34, 33,
39, 22, 33, 22, 33, 33, 33, 43, 33, 21, 33, 10, 33, 43,
33, 22, 44, 39, 47, 33, 44, 37, 44, 24, 18, 33, 1, 18,
33, 36, 49, 10, 36, 15, 36, 34, 44, 34, 21, 31, 23, 23,
44, 11, 26, 43, 43, 36, 41, 44, 17, 4, 4, 10, 37, 26,
44, 14, 18, 47, 16, 37, 23, 15, 34, 19, 34, 5, 48, 50,
43, 10, 44, 36, 1, 5, 5, 41, 47, 5, 41, 48, 14, 27,
3, 15, 41, 27, 23, 43, 43, 9, 5, 23, 43, 24, 21, 10,
16, 21, 5, 5, 25, 26, 24, 14, 23, 44, 5, 5, 47, 5,
5, 5, 3, 25, 5, 48, 5, 5, 5, 38, 25, 3, 5, 51,
44, 5, 11, 10, 5, 5, 5, 5, 10, 44, 33, 11, 11, 39,
44, 49, 44, 4, 39, 14, 11, 44, 16, 41, 15, 31, 34, 26,
47, 39, 3, 39, 5, 34, 20, 40, 31, 10, 33, 30, 10, 33,
31, 11, 33, 33, 4, 44, 5, 3, 34, 39, 33, 18, 7, 6,
22, 33, 31, 33, 10, 40, 39, 36, 44, 11, 27, 10, 18, 33,
26, 39, 47, 44, 24, 33, 47, 21, 5, 39, 18, 47, 34, 11,
4, 50, 44, 13, 26, 14, 19, 26, 50, 36, 24, 24, 5, 14,
15, 50, 34, 10, 17, 24, 44, 5, 21, 50, 25, 43, 39, 23,
5, 19, 25, 49, 25, 6, 6, 10, 23, 26, 1, 39, 23, 34,
36, 50, 36, 5, 44, 10, 23, 10, 39, 7, 43, 15, 5, 33,
34, 36, 14, 23, 18, 37, 43, 20, 14, 26, 1, 50, 33, 31,
14, 48, 47, 47, 7, 23, 6, 13, 31, 24, 34, 34, 23, 39,
5, 26, 14, 39, 47, 42, 23, 50, 11, 18, 17, 39, 33, 16,
50, 24, 50, 23, 36, 24, 26, 22, 36, 18, 39, 26, 14, 10,
5, 39, 44, 36, 14, 15, 36, 14, 23, 41, 33, 23, 10, 45,
6, 15, 14, 5, 44, 36, 10, 31, 48, 5, 14, 39, 5, 33,
47, 26, 36, 44, 5, 36, 5, 4, 44, 22, 24, 4, 25, 39,
32, 15, 11, 44, 22, 25, 11, 14, 31, 48, 32, 33, 3, 48,
10, 11, 23, 8, 33, 5, 10, 23, 44, 22, 3, 19, 5, 26,
10, 36, 40, 5, 16, 23, 44, 38, 44, 43, 37, 15, 36, 48,
36, 5, 4, 11, 5, 44, 5, 44, 36, 36, 25, 47, 44, 36,
50, 33, 10, 1, 22, 22, 21, 44, 5, 36, 17, 1, 44, 17,
31, 18, 34, 44, 44, 39, 11, 48, 41, 24, 26, 26, 10, 5,
39, 15, 5, 33, 33, 39, 33, 7, 39, 39, 22, 33, 31, 31,
46, 31, 22, 33, 33, 21, 21, 31, 33, 39, 39, 21, 33, 21,
34, 31, 11, 39, 10, 34, 47, 21, 34, 39, 10, 49, 41, 21,
10, 36, 25, 15, 19, 11, 26, 24, 4, 23, 7, 36, 24, 50,
23, 21, 14, 10, 19, 14, 24, 14, 26, 44, 44, 15, 23, 19,
18, 23, 44, 5, 23, 14, 10, 43, 44, 45, 5, 42, 5, 23,
48, 28, 37, 22, 43, 5, 24, 5, 5, 48, 23, 18, 5, 38,
34, 41, 32, 6, 36, 44, 19, 16, 39, 38, 5, 5, 33, 24,
48, 24, 36, 47, 44, 51, 21, 23, 37, 5, 44, 33, 39, 3,
39, 5, 14, 36, 38, 36, 44, 10, 34, 34, 6, 5, 10, 41,
39, 6, 33, 43, 11, 6, 14, 43, 39, 5, 36, 28, 50, 7,
18, 5, 15, 36, 5, 27, 50, 14, 21, 5, 36, 21, 11, 10,
25, 39, 14, 5, 24, 48, 11, 50, 10, 5, 5, 44, 39, 5,
36, 3, 34, 22, 7, 49, 3, 33, 39, 16, 23, 48, 5, 11,
47, 20, 5, 21, 5, 36, 23, 22, 36, 17, 33, 31, 10, 48,
48, 10, 33, 10, 44, 5, 19, 6, 4, 48, 37, 48, 11, 10,
50, 3, 3, 44, 31, 47, 4, 39, 21, 16, 14, 7, 36, 36,
22, 22, 44, 14, 36, 26, 33, 50, 26, 19, 15, 10, 10, 33,
5, 23, 26, 33, 33, 23, 41, 36, 34, 10, 32, 23, 41, 10,
5, 26, 39, 22, 10, 15, 41, 23, 21, 33, 10, 10, 47, 36,
8, 30, 44, 22, 11, 39, 33, 10, 44, 31, 36, 48, 15, 31,
7, 44, 34, 34, 10, 28, 44, 39, 39, 41, 34, 39, 44, 21,
1, 33, 10, 44, 22, 25, 10, 22, 24, 23, 23, 44, 30, 50,
23, 40, 44, 10, 48, 10, 26, 44, 8, 50, 10, 15, 5, 7,
47, 10, 22, 5, 24, 15, 31, 10, 26, 36, 35, 50, 5, 5,
14, 5, 21, 39, 18, 16, 10, 24, 26, 33, 5, 50, 50, 50,
5, 39, 4, 39, 44, 16, 35, 44, 22, 50, 44, 40, 16, 33,
30, 24, 31, 43, 19, 17, 25, 22, 14, 31, 43, 35, 7, 18,
44, 23, 18, 5, 47, 1, 36, 23, 4, 18, 41, 50, 10, 48,
31, 21, 5, 34, 5, 22, 14, 25, 50, 5, 44, 43, 48, 5,
39, 44, 5, 5, 5, 10, 36, 34, 28, 10, 21, 5, 5, 14,
48, 10, 31, 39, 31, 15, 43, 5, 48, 31, 10, 44, 34, 22,
44, 43, 50, 4, 43, 44, 17, 39, 19, 10, 43, 43, 21, 10,
34, 34, 18, 14, 14, 33, 44, 14, 23, 36, 5, 10, 31, 10,
5, 44, 5, 31, 1, 39, 10, 50, 44, 48, 33, 36, 31, 39,
16, 44, 47, 34, 47, 5, 29, 5, 39, 44, 11, 6, 1, 34,
8, 6, 3, 5, 5, 4, 33, 31, 21, 10, 34, 33, 39, 22,
33, 22, 33, 33, 33, 43, 33, 21, 33, 10, 33, 43, 33, 22,
44, 39, 47, 33, 44, 37, 44, 24, 18, 33, 1, 18, 33, 36,
49, 10, 36, 15, 36, 34, 44, 34, 21, 31, 23, 23, 44, 11,
26, 43, 43, 36, 41, 44, 17, 4, 4, 10, 37, 26, 44, 14,
18, 47, 16, 37, 23, 15, 34, 19, 34, 5, 48, 50, 43, 10,
44, 36, 1, 5, 5, 41, 47, 5, 41, 48, 14, 27, 3, 15,
41, 27, 23, 43, 43, 9, 5, 23, 43, 24, 21, 10, 16, 21,
5, 5, 25, 26, 24, 14, 23, 44, 5, 5, 47, 5, 5, 5,
3, 25, 5, 48, 5, 5, 5, 38, 25, 3, 5, 51, 44, 5,
11, 10, 5, 5, 5, 5, 10, 44, 33, 11, 11, 39, 44, 49,
44, 4, 39, 14, 11, 44, 16, 41, 15, 31, 34, 26, 47, 39,
3, 39, 5, 34, 20, 40, 31, 10, 33, 30, 10, 33, 31, 11,
33, 33, 4, 44, 5, 3, 34, 39, 33, 18, 7, 6, 22, 33,
31, 33, 10, 40, 39, 36, 44, 11, 27, 10, 18, 33, 26, 39,
47, 44, 24, 33, 47, 21, 5, 39, 18, 47, 34, 11, 4, 50,
44, 13, 26, 14, 19, 26, 50, 36, 24, 24, 5, 14, 15, 50,
34, 10, 17, 24, 44, 5, 21, 50, 25, 43, 39, 23, 5, 19,
25, 49, 25, 6, 6, 10, 23, 26, 1, 39, 23, 34, 36, 50,
36, 5, 44, 10, 23, 10, 39, 7, 43, 15, 5, 33, 34, 36,
14, 23, 18, 37, 43, 20, 14, 26, 1, 50, 33, 31, 14, 48,
47, 47, 7, 23, 6, 13, 31, 24, 34, 34, 23, 39, 5, 26,
14, 39, 47, 42, 23, 50, 11, 18, 17, 39, 33, 16, 50, 24,
50, 23, 36, 24, 26, 22, 36, 18, 39, 26, 14, 10, 5, 39,
44, 36, 14, 15, 36, 14, 23, 41, 33, 23, 10, 45, 6, 15,
14, 5, 44, 36, 10, 31, 48, 5, 14, 39, 5, 33, 47, 26,
36, 44, 5, 36, 5, 4, 44, 22, 24, 4, 25, 39, 32, 15,
11, 44, 22, 25, 11, 14, 31, 48, 32, 33, 3, 48, 10, 11,
23, 8, 33, 5, 10, 23, 44, 22, 3, 19, 5, 26, 10, 36,
40, 5, 16, 23, 44, 38, 44, 43, 37, 15, 36, 48, 36, 5,
4, 11, 5, 44, 5, 44, 36, 36, 25, 47, 44, 36, 50, 33,
10, 1, 22, 22, 21, 44, 5, 36, 17, 1, 44, 17, 31, 18,
34, 44, 44, 39, 11, 48, 41, 24, 26, 26, 10, 5, 39, 15,
5, 33, 33, 39, 33, 7, 39, 39, 22, 33, 31, 31, 46, 31,
22, 33, 33, 21, 21, 31, 33, 39, 39, 21, 33, 21, 34, 31,
11, 39, 10, 34, 47, 21, 34, 39, 10, 49, 41, 21, 10, 36,
25, 15, 19, 11, 26, 24, 4, 23, 7, 36, 24, 50, 23, 21,
14, 10, 19, 14, 24, 14, 26, 44, 44, 15, 23, 19, 18, 23,
44, 5, 23, 14, 10, 43, 44, 45, 5, 42, 5, 23, 48, 28,
37, 22, 43, 5, 24, 5, 5, 48, 23, 18, 5, 38, 34, 41,
32, 6, 36, 44, 19, 16, 39, 38, 5, 5, 33, 24, 48, 24,
36, 47, 44, 51, 21, 23, 37, 5, 44, 33, 39, 3, 39, 5,
14, 36, 38, 36, 44, 10, 34, 34, 6, 5, 10, 41, 39, 6,
33, 43, 11, 6, 14, 43, 39, 5, 36, 28, 50, 7, 18, 5,
15, 36, 5, 27, 50, 14, 21, 5, 36, 21, 11, 10, 25, 39,
14, 5, 24, 48, 11, 50, 10, 5, 5, 44, 39, 5, 36, 3,
34, 22, 7, 49, 3, 33, 39, 16, 23, 48, 5, 11, 47, 20,
5, 21, 5, 36, 23, 22, 36, 17, 33, 31, 10, 48, 48, 10,
33, 10, 44, 5, 19, 6, 4, 48, 37, 48, 11, 10, 50, 3,
3, 44, 31, 47, 4, 39, 21, 16, 14, 7, 36, 36, 22, 22,
44, 14, 36, 26, 33, 50, 26, 19, 15, 10, 10, 33, 5, 23,
26, 33, 33, 23, 41, 36, 34, 10, 32, 23, 41, 10, 5, 26,
39, 22, 10, 15, 41, 23, 21, 33, 10, 10, 47, 36, 8, 30,
44, 22, 11, 39, 33, 10, 44, 31, 36, 48, 15, 31, 7, 44,
34, 34, 10, 28, 44, 39, 39, 41, 34, 39, 44, 21, 1, 33,
10, 44, 22, 25, 10, 22, 24, 23, 23, 44, 30, 50, 23, 40,
44, 10, 48, 10, 26, 44, 8, 50, 10, 15, 5, 7, 47, 10,
22, 5, 24, 15, 31, 10, 26, 36, 35, 50, 5, 5, 14, 5,
21, 39, 18, 16, 10, 24, 26, 33, 5, 50, 50, 50, 5, 39,
4, 39, 44, 16, 35, 44, 22, 50, 44, 40, 16, 33, 30, 24,
31, 43, 19, 17, 25, 22, 14, 31, 43, 35, 7, 18, 44, 23,
18, 5, 47, 1, 36, 23, 4, 18, 41, 50, 10, 48, 31, 21,
5, 34, 5, 22, 14, 25, 50, 5, 44, 43, 48, 5, 39, 44,
5, 5, 5, 10, 36, 34, 28, 10, 21, 5, 5, 14, 48, 10,
31, 39, 31, 15, 43, 5, 48, 31, 10, 44, 34, 22, 44, 43,
50, 4, 43, 44, 17, 39, 19, 10, 43, 43, 21, 10, 34, 34,
18, 14, 14, 33, 44, 14, 23, 36, 5, 10, 31, 10, 5, 44,
5, 31, 1, 39, 10, 50, 44, 48, 33, 36, 31, 39, 16, 44,
47, 34, 47, 5, 29, 5, 39, 44, 11, 6, 1, 34, 8, 6,
3, 5, 5, 4, 33, 31, 21, 10, 7, 39, 31, 7, 33, 33,
39, 20, 33, 40, 31, 33, 33, 31, 22, 31, 39, 31, 33, 33,
7, 39, 33, 33, 22, 31, 31, 31, 22, 33, 44, 22, 39, 33,
10, 31, 4, 31, 44, 14, 41, 22, 10, 41, 39, 41, 19, 14,
47, 37, 22, 31, 11, 36, 24, 19, 7, 25, 9, 47, 17, 26,
49, 14, 18, 21, 37, 41, 11, 43, 14, 33, 25, 49, 19, 25,
44, 43, 47, 14, 19, 17, 34, 11, 44, 24, 10, 10, 14, 36,
41, 11, 44, 11, 10, 44, 14, 50, 44, 21, 21, 43, 18, 23,
26, 47, 19, 10, 34, 44, 10, 15, 25, 23, 44, 34, 34, 44,
47, 49, 18, 10, 23, 10, 24, 44, 14, 49, 10, 43, 3, 13,
44, 14, 44, 36, 25, 49, 47, 48, 10, 16, 41, 44, 36, 24,
48, 36, 14, 10, 28, 5, 24, 8, 5, 23, 28, 35, 5, 3,
10, 48, 28, 44, 23, 14, 26, 23, 18, 17, 14, 23, 5, 14,
5, 5, 14, 5, 32, 36, 5, 48, 17, 48, 48, 5, 5, 5,
32, 38, 36, 5, 50, 5, 32, 5, 48, 5, 5, 45, 45, 5,
44, 5, 22, 31, 31, 43, 10, 5, 36, 5, 33, 36, 5, 14,
41, 48, 5, 23, 33, 50, 36, 36, 33, 47, 40, 14, 36, 5,
22, 5, 38, 40, 3, 50, 45, 24, 36, 16, 20, 44, 32, 50,
3, 23, 24, 22, 6, 31, 47, 24, 21, 49, 23, 6, 31, 48,
17, 37, 36, 36, 5, 33, 43, 19, 26, 43, 19, 31, 10, 39,
43, 22, 23, 11, 14, 41, 34, 14, 49, 10, 23, 22, 50, 33,
43, 4, 36, 11, 23, 10, 22, 39, 22, 37, 14, 14, 24, 39,
23, 10, 11, 23, 39, 11, 22, 47, 22, 33, 14, 26, 28, 23,
31, 42, 31, 44, 34, 11, 14, 33, 43, 15, 15, 31, 22, 26,
1, 49, 14, 33, 33, 31, 47, 36, 33, 33, 30, 22, 44, 25,
33, 23, 23, 41, 24, 40, 44, 22, 24, 46, 31, 33, 44, 36,
34, 41, 19, 31, 19, 47, 31, 40, 41, 10, 14, 22, 31, 10,
44, 39, 49, 11, 33, 10, 11, 34, 34, 26, 23, 33, 21, 47,
11, 47, 17, 22, 33, 10, 44, 33, 25, 23, 19, 21, 49, 41,
49, 33, 39, 11, 39, 10, 10, 21, 44, 44, 33, 44, 18, 44,
43, 33, 44, 34, 31, 5, 34, 31, 14, 18, 22, 43, 6, 14,
31, 39, 10, 34, 10, 39, 15, 22, 44, 14, 10, 44, 47, 18,
44, 40, 37, 36, 18, 39, 33, 43, 24, 10, 36, 14, 10, 10,
11, 10, 33, 39, 17, 26, 47, 10, 50, 11, 18, 50, 33, 28,
43, 24, 19, 31, 33, 26, 23, 14, 43, 44, 18, 4, 14, 26,
1, 45, 17, 44, 25, 3, 44, 5, 43, 25, 3, 50, 44, 43,
50, 5, 6, 5, 5, 5, 5, 48, 48, 51, 5, 32, 5, 5,
5, 5, 5, 5, 48, 38, 48, 33, 33, 39, 39, 33, 22, 33,
33, 33, 33, 33, 33, 33, 39, 7, 40, 33, 22, 33, 31, 50,
33, 23, 31, 39, 33, 15, 26, 33, 31, 39, 36, 36, 36, 40,
33, 39, 39, 50, 50, 36, 7, 17, 36, 50, 36, 22, 33, 50,
14, 23, 40, 17, 36, 22, 17, 39, 26, 19, 14, 36, 50, 14,
24, 50, 33, 24, 23, 15, 28, 36, 47, 33, 10, 43, 50, 36,
36, 39, 10, 47, 36, 26, 47, 18, 34, 33, 23, 14, 16, 25,
10, 4, 44, 49, 44, 49, 28, 33, 33, 10, 44, 24, 26, 11,
19, 9, 10, 50, 44, 44, 44, 39, 44, 47, 34, 44, 14, 34,
43, 50, 18, 34, 28, 44, 1, 47, 47, 10, 1, 18, 5, 44,
6, 4, 5, 44, 6, 10, 44, 3, 5, 11, 1, 10, 34, 32,
32, 5, 11, 38, 37, 24, 41, 32, 5, 5, 49, 50, 48, 1,
25, 43, 5, 48, 5, 5, 11, 3, 5, 5, 37, 29, 18, 6,
5, 16, 47, 44, 7, 5, 21, 44, 33, 38, 5, 10, 44, 3,
39, 5, 36, 33, 23, 34, 38, 15, 34, 23, 39, 33, 36, 37,
33, 48, 23, 34, 23, 14, 7, 39, 23, 44, 11, 10, 10, 17,
21, 17, 23, 14, 25, 8, 10, 10, 5, 33, 22, 10, 19, 3,
47, 38, 18, 41, 50, 32, 47, 25, 13, 23, 36, 44, 33, 22,
11, 48, 15, 6, 36, 11, 5, 44, 5, 14, 33, 5, 47, 6,
36, 44, 10, 33, 49, 39, 37, 43, 24, 19, 18, 26, 24, 33,
39, 33, 34, 47, 33, 3, 11, 5, 41, 43, 33, 22, 31, 43,
10, 43, 11, 6, 33, 19, 30, 41, 36, 39, 20, 34, 14, 6,
14, 48, 5, 43, 11, 23, 31, 22, 5, 5, 10, 44, 39, 33,
41, 23, 47, 39, 18, 39, 33, 41, 47, 5, 3, 35, 33, 18,
5, 10, 10, 1, 36, 44, 44, 38, 33, 5, 44, 48, 41, 33,
16, 5, 44, 10, 39, 10, 33, 10, 1, 41, 31, 43, 43, 36,
33, 15, 44, 36, 10, 40, 43, 5, 5, 1, 40, 10, 14, 48,
39, 31, 49, 44, 11, 36, 14, 10, 5, 33, 14, 22, 33, 7,
23, 11, 33, 36, 22, 14, 23, 11, 44, 36, 31, 36, 33, 33,
5, 21, 31, 23, 20, 44, 38, 7, 6, 5, 1, 5, 44, 39,
31, 22, 31, 16, 10, 6, 37, 14, 5, 48, 37, 36, 21, 5,
5, 21, 5, 44, 38, 14, 10, 5, 10, 22, 22, 39, 34, 33,
39, 10, 33, 44, 25, 5, 48, 10, 36, 40, 3, 3, 36, 5,
34, 10, 19, 5, 24, 28, 1, 43, 38, 5, 5, 39, 33, 44,
34, 10, 47, 47, 5, 44, 19, 18, 36, 36, 18, 36, 10, 17,
39, 39, 11, 39, 31, 7, 33, 33, 39, 20, 33, 40, 31, 33,
33, 31, 22, 31, 39, 31, 33, 33, 7, 39, 33, 33, 22, 31,
31, 31, 22, 33, 44, 22, 39, 33, 10, 31, 4, 31, 44, 14,
41, 22, 10, 41, 39, 41, 19, 14, 47, 37, 22, 31, 11, 36,
24, 19, 7, 25, 9, 47, 17, 26, 49, 14, 18, 21, 37, 41,
11, 43, 14, 33, 25, 49, 19, 25, 44, 43, 47, 14, 19, 17,
34, 11, 44, 24, 10, 10, 14, 36, 41, 11, 44, 11, 10, 44,
14, 50, 44, 21, 21, 43, 18, 23, 26, 47, 19, 10, 34, 44,
10, 15, 25, 23, 44, 34, 34, 44, 47, 49, 18, 10, 23, 10,
24, 44, 14, 49, 10, 43, 3, 13, 44, 14, 44, 36, 25, 49,
47, 48, 10, 16, 41, 44, 36, 24, 48, 36, 14, 10, 28, 5,
24, 8, 5, 23, 28, 35, 5, 3, 10, 48, 28, 44, 23, 14,
26, 23, 18, 17, 14, 23, 5, 14, 5, 5, 14, 5, 32, 36,
5, 48, 17, 48, 48, 5, 5, 5, 32, 38, 36, 5, 50, 5,
32, 5, 48, 5, 5, 45, 45, 5, 44, 5, 22, 31, 31, 43,
10, 5, 36, 5, 33, 36, 5, 14, 41, 48, 5, 23, 33, 50,
36, 36, 33, 47, 40, 14, 36, 5, 22, 5, 38, 40, 3, 50,
45, 24, 36, 16, 20, 44, 32, 50, 3, 23, 24, 22, 6, 31,
47, 24, 21, 49, 23, 6, 31, 48, 17, 37, 36, 36, 5, 33,
43, 19, 26, 43, 19, 31, 10, 39, 43, 22, 23, 11, 14, 41,
34, 14, 49, 10, 23, 22, 50, 33, 43, 4, 36, 11, 23, 10,
22, 39, 22, 37, 14, 14, 24, 39, 23, 10, 11, 23, 39, 11,
22, 47, 22, 33, 14, 26, 28, 23, 31, 42, 31, 44, 34, 11,
14, 33, 43, 15, 15, 31, 22, 26, 1, 49, 14, 33, 33, 31,
47, 36, 33, 33, 30, 22, 44, 25, 33, 23, 23, 41, 24, 40,
44, 22, 24, 46, 31, 33, 44, 36, 34, 41, 19, 31, 19, 47,
31, 40, 41, 10, 14, 22, 31, 10, 44, 39, 49, 11, 33, 10,
11, 34, 34, 26, 23, 33, 21, 47, 11, 47, 17, 22, 33, 10,
44, 33, 25, 23, 19, 21, 49, 41, 49, 33, 39, 11, 39, 10,
10, 21, 44, 44, 33, 44, 18, 44, 43, 33, 44, 34, 31, 5,
34, 31, 14, 18, 22, 43, 6, 14, 31, 39, 10, 34, 10, 39,
15, 22, 44, 14, 10, 44, 47, 18, 44, 40, 37, 36, 18, 39,
33, 43, 24, 10, 36, 14, 10, 10, 11, 10, 33, 39, 17, 26,
47, 10, 50, 11, 18, 50, 33, 28, 43, 24, 19, 31, 33, 26,
23, 14, 43, 44, 18, 4, 14, 26, 1, 45, 17, 44, 25, 3,
44, 5, 43, 25, 3, 50, 44, 43, 50, 5, 6, 5, 5, 5,
5, 48, 48, 51, 5, 32, 5, 5, 5, 5, 5, 5, 48, 38,
48, 33, 33, 39, 39, 33, 22, 33, 33, 33, 33, 33, 33, 33,
39, 7, 40, 33, 22, 33, 31, 50, 33, 23, 31, 39, 33, 15,
26, 33, 31, 39, 36, 36, 36, 40, 33, 39, 39, 50, 50, 36,
7, 17, 36, 50, 36, 22, 33, 50, 14, 23, 40, 17, 36, 22,
17, 39, 26, 19, 14, 36, 50, 14, 24, 50, 33, 24, 23, 15,
28, 36, 47, 33, 10, 43, 50, 36, 36, 39, 10, 47, 36, 26,
47, 18, 34, 33, 23, 14, 16, 25, 10, 4, 44, 49, 44, 49,
28, 33, 33, 10, 44, 24, 26, 11, 19, 9, 10, 50, 44, 44,
44, 39, 44, 47, 34, 44, 14, 34, 43, 50, 18, 34, 28, 44,
1, 47, 47, 10, 1, 18, 5, 44, 6, 4, 5, 44, 6, 10,
44, 3, 5, 11, 1, 10, 34, 32, 32, 5, 11, 38, 37, 24,
41, 32, 5, 5, 49, 50, 48, 1, 25, 43, 5, 48, 5, 5,
11, 3, 5, 5, 37, 29, 18, 6, 5, 16, 47, 44, 7, 5,
21, 44, 33, 38, 5, 10, 44, 3, 39, 5, 36, 33, 23, 34,
38, 15, 34, 23, 39, 33, 36, 37, 33, 48, 23, 34, 23, 14,
7, 39, 23, 44, 11, 10, 10, 17, 21, 17, 23, 14, 25, 8,
10, 10, 5, 33, 22, 10, 19, 3, 47, 38, 18, 41, 50, 32,
47, 25, 13, 23, 36, 44, 33, 22, 11, 48, 15, 6, 36, 11,
5, 44, 5, 14, 33, 5, 47, 6, 36, 44, 10, 33, 49, 39,
37, 43, 24, 19, 18, 26, 24, 33, 39, 33, 34, 47, 33, 3,
11, 5, 41, 43, 33, 22, 31, 43, 10, 43, 11, 6, 33, 19,
30, 41, 36, 39, 20, 34, 14, 6, 14, 48, 5, 43, 11, 23,
31, 22, 5, 5, 10, 44, 39, 33, 41, 23, 47, 39, 18, 39,
33, 41, 47, 5, 3, 35, 33, 18, 5, 10, 10, 1, 36, 44,
44, 38, 33, 5, 44, 48, 41, 33, 16, 5, 44, 10, 39, 10,
33, 10, 1, 41, 31, 43, 43, 36, 33, 15, 44, 36, 10, 40,
43, 5, 5, 1, 40, 10, 14, 48, 39, 31, 49, 44, 11, 36,
14, 10, 5, 33, 14, 22, 33, 7, 23, 11, 33, 36, 22, 14,
23, 11, 44, 36, 31, 36, 33, 33, 5, 21, 31, 23, 20, 44,
38, 7, 6, 5, 1, 5, 44, 39, 31, 22, 31, 16, 10, 6,
37, 14, 5, 48, 37, 36, 21, 5, 5, 21, 5, 44, 38, 14,
10, 5, 10, 22, 22, 39, 34, 33, 39, 10, 33, 44, 25, 5,
48, 10, 36, 40, 3, 3, 36, 5, 34, 10, 19, 5, 24, 28,
1, 43, 38, 5, 5, 39, 33, 44, 34, 10, 47, 47, 5, 44,
19, 18, 36, 36, 18, 36, 10, 17, 39, 39, 11, 48, 48, 13,
5, 23, 36, 10, 33, 50, 43, 23, 36, 11, 50, 24, 22, 14,
17, 33, 15, 35, 19, 33, 5, 50, 5, 10, 14, 26, 36, 14,
49, 31, 39, 44, 21, 10, 1, 10, 47, 10, 43, 11, 10, 1,
33, 10, 21, 1, 44, 21, 47, 34, 33, 47, 39, 18, 47, 44,
41, 47, 26, 10, 44, 10, 43, 49, 47, 41, 18, 10, 42, 22,
47, 21, 7, 41, 10, 21, 31, 11, 17, 34, 11, 44, 41, 21,
26, 33, 31, 33, 4, 33, 50, 31, 16, 10, 48, 33, 31, 33,
25, 4, 33, 24, 36, 47, 7, 33, 33, 10, 50, 49, 37, 33,
39, 47, 33, 33, 44, 5, 36, 39, 44, 24, 10, 41, 33, 33,
21, 33, 50, 36, 33, 16, 39, 47, 44, 22, 26, 22, 10, 49,
50, 35, 22, 11, 36, 31, 1, 36, 36, 24, 50, 31, 10, 31,
14, 23, 28, 22, 22, 23, 23, 14, 28, 44, 7, 33, 37, 15,
36, 19, 16, 33, 5, 5, 48, 36, 5, 41, 23, 45, 44, 36,
3, 5, 5, 3, 32, 14, 1, 45, 50, 26, 47, 9, 5, 33,
44, 3, 23, 28, 26, 3, 5, 47, 24, 23, 5, 5, 16, 48,
36, 39, 48, 10, 33, 10, 10, 23, 1, 27, 15, 23, 36, 15,
6, 5, 39, 33, 45, 5, 5, 6, 14, 50, 36, 5, 33, 25,
5, 6, 8, 43, 31, 22, 33, 24, 21, 5, 41, 48, 10, 5,
49, 5, 44, 5, 44, 11, 39, 33, 15, 24, 24, 20, 44, 33,
32, 5, 33, 44, 23, 33, 38, 5, 17, 19, 34, 16, 1, 37,
39, 31, 16, 36, 39, 19, 18, 41, 39, 23, 7, 48, 34, 33,
4, 7, 33, 14, 10, 44, 48, 14, 5, 13, 43, 39, 32, 47,
36, 33, 30, 18, 33, 26, 5, 5, 22, 20, 23, 14, 14, 47,
36, 36, 25, 44, 14, 39, 33, 38, 16, 48, 50, 39, 33, 50,
34, 23, 26, 6, 15, 14, 31, 10, 11, 36, 33, 26, 36, 5,
10, 3, 42, 10, 15, 41, 28, 22, 3, 36, 21, 43, 39, 8,
5, 16, 24, 34, 36, 10, 24, 48, 5, 24, 6, 33, 10, 3,
5, 35, 15, 5, 5, 27, 49, 26, 5, 48, 28, 5, 5, 17,
48, 14, 48, 33, 28, 5, 5, 48, 5, 5, 42, 5, 5, 48,
50, 5, 5, 32, 5, 48, 5, 32, 3, 32, 11, 1, 44, 1,
15, 15, 34, 48, 39, 17, 36, 14, 15, 44, 10, 5, 31, 36,
14, 33, 19, 36, 10, 7, 43, 44, 32, 44, 44, 11, 5, 10,
5, 5, 5, 23, 21, 23, 5, 14, 34, 31, 31, 5, 17, 5,
39, 10, 1, 22, 33, 28, 39, 7, 1, 43, 36, 35, 3, 10,
48, 33, 48, 14, 15, 44, 39, 15, 44, 19, 33, 5, 44, 44,
23, 5, 5, 25, 33, 5, 44, 25, 10, 25, 44, 38, 50, 5,
36, 15, 48, 10, 49, 5, 3, 34, 50, 44, 14, 25, 5, 47,
39, 39, 34, 44, 44, 20, 32, 44, 48, 47, 47, 11, 44, 4,
20, 33, 39, 39, 31, 20, 33, 31, 33, 33, 39, 33, 39, 33,
39, 31, 39, 31, 22, 7, 33, 10, 33, 33, 39, 33, 39, 46,
33, 33, 17, 33, 39, 18, 31, 31, 7, 39, 39, 33, 33, 10,
36, 31, 39, 24, 7, 24, 39, 47, 14, 23, 42, 24, 23, 50,
39, 36, 23, 39, 7, 34, 33, 23, 23, 24, 10, 14, 44, 36,
31, 14, 14, 34, 34, 36, 50, 39, 24, 23, 26, 50, 11, 17,
26, 36, 23, 14, 15, 10, 7, 23, 50, 36, 11, 50, 10, 1,
14, 1, 10, 37, 44, 16, 26, 8, 21, 23, 14, 36, 34, 33,
36, 26, 44, 36, 10, 10, 10, 14, 50, 18, 34, 14, 50, 33,
39, 47, 25, 10, 11, 19, 44, 21, 50, 44, 43, 23, 23, 44,
10, 44, 15, 10, 26, 15, 10, 44, 44, 11, 23, 34, 43, 44,
43, 23, 18, 33, 23, 36, 25, 49, 19, 35, 4, 36, 36, 19,
39, 44, 43, 23, 19, 23, 25, 43, 47, 24, 23, 44, 21, 19,
27, 44, 47, 5, 10, 44, 16, 23, 5, 48, 10, 7, 5, 10,
5, 44, 24, 17, 14, 48, 6, 45, 10, 18, 36, 5, 48, 23,
17, 6, 5, 24, 3, 16, 8, 5, 10, 21, 32, 5, 44, 5,
10, 32, 5, 49, 15, 50, 5, 11, 1, 50, 36, 48, 3, 32,
33, 10, 48, 38, 6, 18, 39, 38, 33, 32, 5, 33, 4, 15,
23, 5, 24, 23, 39, 50, 26, 23, 8, 29, 44, 18, 44, 16,
15, 50, 33, 47, 36, 33, 47, 44, 6, 31, 14, 5, 31, 47,
44, 3, 5, 11, 5, 38, 26, 36, 6, 5, 31, 10, 31, 33,
5, 23, 33, 20, 15, 26, 5, 48, 11, 43, 33, 7, 20, 39,
49, 29, 39, 5, 3, 16, 48, 5, 22, 7, 41, 10, 7, 10,
36, 33, 39, 31, 50, 26, 23, 31, 49, 26, 44, 50, 20, 47,
5, 10, 5, 39, 23, 50, 22, 14, 20, 47, 44, 1, 11, 5,
23, 43, 39, 44, 47, 34, 23, 47, 15, 33, 39, 32, 5, 33,
19, 37, 11, 23, 18, 10, 5, 5, 49, 23, 45, 48, 15, 42,
39, 21, 10, 10, 19, 7, 39, 33, 36, 37, 17, 17, 33, 37,
3, 10, 21, 34, 14, 15, 22, 28, 36, 21, 1, 39, 44, 34,
21, 6, 21, 17, 39, 14, 36, 36, 5, 14, 36, 5, 24, 25,
44, 14, 14, 3, 15, 5, 1, 1, 44, 25, 16, 14, 27, 25,
48, 50, 4, 14, 26, 19, 26, 1, 25, 43, 44, 50, 3, 24,
44, 1, 14, 5, 5, 45, 51, 5, 45, 48, 5, 3, 27, 5,
38, 5, 5, 5, 5, 5, 5, 32, 5, 6, 29, 5, 3, 5,
5, 5],
"age_edu": [6, 12, 2, 7, 3, 8, 9, 8, 8, 12, 4, 4, 10, 10,
8, 10, 11, 7, 8, 7, 13, 8, 13, 7, 8, 16, 6, 6,
7, 12, 12, 12, 13, 8, 13, 10, 8, 7, 10, 10, 1, 10,
1, 8, 4, 8, 10, 10, 4, 9, 2, 3, 8, 7, 7, 12,
6, 7, 2, 13, 13, 7, 7, 8, 4, 12, 6, 14, 16, 8,
6, 10, 12, 1, 2, 8, 10, 8, 10, 3, 7, 3, 3, 10,
8, 5, 16, 15, 11, 9, 2, 11, 8, 12, 6, 2, 2, 8,
5, 11, 2, 3, 3, 10, 6, 12, 12, 4, 8, 3, 9, 3,
7, 14, 10, 10, 3, 6, 2, 2, 3, 14, 4, 6, 4, 8,
8, 8, 3, 14, 4, 9, 12, 6, 6, 14, 2, 11, 12, 14,
4, 8, 7, 12, 8, 8, 12, 10, 3, 7, 6, 7, 11, 6,
11, 2, 4, 8, 7, 8, 10, 7, 9, 7, 13, 5, 11, 7,
1, 2, 2, 14, 13, 8, 4, 6, 6, 14, 10, 8, 11, 2,
6, 14, 12, 6, 2, 9, 10, 6, 7, 2, 6, 7, 11, 11,
12, 2, 15, 6, 6, 10, 14, 11, 6, 6, 11, 12, 8, 7,
11, 4, 4, 4, 8, 2, 10, 12, 14, 7, 1, 3, 4, 12,
12, 2, 10, 6, 2, 8, 2, 6, 10, 14, 12, 10, 11, 16,
11, 4, 13, 12, 15, 11, 14, 10, 8, 12, 10, 3, 14, 10,
7, 3, 13, 14, 10, 6, 12, 3, 2, 14, 11, 12, 11, 15,
4, 2, 4, 2, 6, 4, 9, 9, 8, 6, 15, 10, 6, 8,
6, 6, 16, 10, 7, 4, 3, 15, 8, 7, 9, 7, 7, 12,
8, 9, 6, 4, 2, 14, 16, 8, 7, 7, 2, 12, 2, 9,
12, 6, 3, 4, 7, 12, 14, 2, 2, 8, 6, 8, 11, 6,
6, 12, 2, 15, 10, 4, 8, 11, 6, 10, 4, 9, 2, 8,
7, 8, 3, 2, 11, 4, 11, 6, 8, 8, 8, 1, 7, 6,
10, 5, 15, 8, 3, 10, 4, 6, 6, 14, 13, 13, 5, 6,
6, 4, 7, 4, 16, 4, 10, 10, 7, 11, 12, 8, 13, 7,
5, 5, 13, 2, 3, 12, 8, 8, 14, 11, 14, 8, 7, 2,
2, 10, 7, 6, 8, 11, 5, 7, 10, 10, 8, 8, 10, 8,
12, 7, 3, 8, 7, 10, 10, 2, 12, 6, 4, 3, 4, 10,
8, 10, 14, 11, 5, 11, 8, 8, 4, 8, 3, 7, 7, 10,
8, 11, 3, 8, 6, 5, 10, 16, 8, 14, 12, 13, 5, 11,
14, 4, 8, 3, 8, 16, 9, 7, 12, 15, 7, 7, 11, 10,
14, 8, 7, 6, 3, 9, 7, 14, 3, 14, 13, 3, 10, 4,
11, 7, 6, 12, 3, 12, 3, 7, 4, 10, 14, 6, 2, 3,
10, 8, 1, 8, 2, 9, 8, 13, 11, 10, 7, 8, 10, 14,
2, 8, 8, 13, 8, 11, 4, 12, 7, 3, 5, 5, 3, 10,
7, 10, 7, 9, 8, 7, 3, 10, 6, 10, 10, 6, 6, 2,
2, 12, 15, 9, 10, 8, 10, 6, 5, 9, 12, 8, 7, 7,
6, 8, 10, 12, 8, 6, 2, 14, 7, 11, 7, 7, 7, 6,
2, 8, 10, 2, 10, 8, 8, 14, 9, 12, 7, 3, 12, 3,
10, 10, 8, 11, 2, 6, 6, 13, 8, 3, 12, 10, 12, 10,
10, 8, 8, 8, 9, 6, 6, 14, 8, 12, 9, 10, 6, 2,
2, 13, 11, 10, 7, 9, 8, 15, 15, 2, 14, 4, 7, 7,
9, 10, 11, 12, 16, 8, 1, 14, 3, 9, 7, 6, 10, 4,
6, 16, 5, 10, 6, 4, 4, 10, 3, 3, 10, 4, 10, 12,
15, 4, 10, 3, 8, 10, 7, 2, 8, 4, 13, 11, 7, 8,
9, 7, 3, 7, 10, 7, 10, 5, 12, 3, 6, 10, 6, 3,
3, 10, 13, 2, 10, 10, 8, 4, 14, 11, 6, 9, 14, 5,
3, 14, 3, 10, 7, 8, 10, 14, 7, 8, 3, 6, 10, 10,
10, 8, 11, 11, 16, 2, 6, 6, 1, 7, 14, 6, 7, 12,
16, 12, 11, 8, 10, 8, 2, 13, 5, 13, 8, 4, 4, 6,
2, 10, 1, 14, 8, 8, 8, 6, 8, 2, 11, 7, 2, 2,
12, 6, 2, 2, 13, 8, 12, 8, 10, 8, 2, 8, 7, 10,
4, 4, 6, 6, 12, 7, 3, 3, 12, 8, 16, 12, 6, 6,
10, 10, 10, 14, 15, 12, 6, 10, 6, 12, 14, 1, 4, 8,
7, 15, 6, 4, 14, 4, 6, 11, 15, 5, 12, 12, 10, 14,
2, 8, 7, 7, 6, 13, 7, 3, 10, 3, 12, 3, 5, 2,
8, 4, 12, 7, 6, 3, 12, 14, 6, 1, 10, 7, 16, 6,
2, 11, 2, 6, 3, 2, 8, 6, 3, 2, 7, 7, 7, 8,
6, 2, 6, 12, 3, 6, 9, 2, 3, 6, 12, 7, 6, 15,
14, 9, 8, 9, 10, 12, 11, 11, 2, 2, 2, 9, 6, 7,
9, 13, 14, 9, 4, 10, 15, 4, 1, 9, 13, 5, 2, 6,
5, 1, 8, 4, 13, 4, 7, 8, 11, 11, 11, 14, 8, 4,
4, 16, 8, 3, 10, 14, 16, 8, 13, 12, 16, 15, 7, 10,
8, 16, 6, 14, 10, 10, 11, 14, 2, 7, 7, 7, 13, 8,
16, 7, 3, 10, 5, 6, 6, 13, 10, 11, 7, 14, 6, 13,
7, 16, 8, 14, 6, 3, 9, 13, 11, 15, 10, 8, 13, 8,
5, 11, 10, 10, 15, 7, 10, 12, 5, 2, 7, 14, 10, 9,
10, 7, 14, 14, 12, 8, 8, 6, 6, 11, 8, 3, 4, 2,
6, 8, 7, 2, 2, 6, 8, 14, 3, 3, 8, 11, 8, 2,
7, 15, 11, 6, 2, 7, 9, 14, 2, 10, 9, 8, 2, 7,
4, 12, 12, 14, 10, 1, 6, 2, 12, 2, 14, 4, 5, 7,
3, 9, 3, 12, 6, 11, 6, 10, 8, 8, 8, 6, 10, 6,
6, 1, 8, 9, 7, 15, 7, 3, 3, 13, 10, 2, 12, 11,
10, 8, 16, 13, 10, 9, 15, 8, 4, 8, 12, 10, 6, 6,
8, 7, 12, 2, 14, 8, 13, 10, 12, 13, 14, 11, 12, 8,
13, 7, 14, 11, 14, 16, 10, 7, 11, 3, 15, 2, 15, 6,
3, 12, 14, 7, 2, 6, 4, 2, 1, 8, 5, 8, 2, 13,
2, 4, 13, 10, 4, 7, 6, 12, 7, 7, 6, 2, 7, 5,
6, 14, 11, 10, 4, 11, 4, 15, 13, 11, 12, 9, 3, 2,
15, 7, 15, 2, 14, 12, 4, 6, 4, 6, 10, 10, 10, 4,
4, 11, 12, 3, 7, 13, 2, 11, 2, 2, 3, 3, 2, 3,
3, 12, 2, 3, 11, 11, 16, 14, 15, 10, 15, 3, 7, 5,
3, 11, 12, 2, 14, 9, 8, 10, 2, 6, 10, 13, 7, 3,
13, 6, 13, 12, 3, 5, 3, 6, 10, 16, 8, 8, 7, 2,
3, 13, 7, 6, 10, 10, 13, 10, 2, 1, 8, 14, 6, 2,
6, 6, 10, 6, 2, 7, 8, 5, 14, 12, 4, 1, 6, 3,
2, 3, 6, 1, 11, 4, 9, 3, 2, 4, 3, 3, 2, 3,
10, 8, 6, 10, 10, 9, 9, 7, 4, 11, 7, 10, 14, 15,
8, 7, 3, 15, 2, 13, 7, 2, 8, 8, 12, 10, 3, 7,
11, 8, 10, 2, 6, 3, 14, 6, 7, 8, 6, 10, 2, 4,
12, 8, 12, 6, 12, 7, 7, 8, 10, 15, 8, 7, 2, 3,
8, 12, 8, 8, 7, 6, 9, 10, 13, 12, 11, 8, 3, 10,
2, 4, 6, 4, 14, 15, 11, 8, 3, 8, 3, 14, 8, 12,
2, 7, 3, 3, 4, 14, 6, 8, 3, 2, 8, 4, 10, 6,
7, 2, 7, 8, 12, 7, 4, 12, 5, 7, 3, 11, 3, 8,
12, 8, 12, 2, 10, 4, 4, 2, 14, 8, 7, 8, 7, 7,
7, 1, 7, 7, 4, 4, 4, 7, 8, 10, 7, 11, 2, 8,
6, 12, 12, 7, 15, 4, 2, 8, 3, 14, 9, 8, 7, 8,
10, 6, 6, 8, 16, 11, 12, 2, 9, 10, 8, 10, 16, 2,
3, 2, 10, 14, 10, 7, 14, 16, 8, 5, 2, 14, 10, 16,
11, 10, 12, 9, 7, 6, 10, 11, 8, 12, 13, 8, 10, 9,
8, 5, 9, 13, 6, 3, 13, 6, 2, 14, 8, 5, 5, 2,
6, 6, 2, 6, 12, 15, 7, 7, 11, 10, 14, 8, 7, 6,
3, 9, 7, 14, 3, 14, 13, 3, 10, 4, 11, 7, 6, 12,
3, 12, 3, 7, 4, 10, 14, 6, 2, 3, 10, 8, 1, 8,
2, 9, 8, 13, 11, 10, 7, 8, 10, 14, 2, 8, 8, 13,
8, 11, 4, 12, 7, 3, 5, 5, 3, 10, 7, 10, 7, 9,
8, 7, 3, 10, 6, 10, 10, 6, 6, 2, 2, 12, 15, 9,
10, 8, 10, 6, 5, 9, 12, 8, 7, 7, 6, 8, 10, 12,
8, 6, 2, 14, 7, 11, 7, 7, 7, 6, 2, 8, 10, 2,
10, 8, 8, 14, 9, 12, 7, 3, 12, 3, 10, 10, 8, 11,
2, 6, 6, 13, 8, 3, 12, 10, 12, 10, 10, 8, 8, 8,
9, 6, 6, 14, 8, 12, 9, 10, 6, 2, 2, 13, 11, 10,
7, 9, 8, 15, 15, 2, 14, 4, 7, 7, 9, 10, 11, 12,
16, 8, 1, 14, 3, 9, 7, 6, 10, 4, 6, 16, 5, 10,
6, 4, 4, 10, 3, 3, 10, 4, 10, 12, 15, 4, 10, 3,
8, 10, 7, 2, 8, 4, 13, 11, 7, 8, 9, 7, 3, 7,
10, 7, 10, 5, 12, 3, 6, 10, 6, 3, 3, 10, 13, 2,
10, 10, 8, 4, 14, 11, 6, 9, 14, 5, 3, 14, 3, 10,
7, 8, 10, 14, 7, 8, 3, 6, 10, 10, 10, 8, 11, 11,
16, 2, 6, 6, 1, 7, 14, 6, 7, 12, 16, 12, 11, 8,
10, 8, 2, 13, 5, 13, 8, 4, 4, 6, 2, 10, 1, 14,
8, 8, 8, 6, 8, 2, 11, 7, 2, 2, 12, 6, 2, 2,
13, 8, 12, 8, 10, 8, 2, 8, 7, 10, 4, 4, 6, 6,
12, 7, 3, 3, 12, 8, 16, 12, 6, 6, 10, 10, 10, 14,
15, 12, 6, 10, 6, 12, 14, 1, 4, 8, 7, 15, 6, 4,
14, 4, 6, 11, 15, 5, 12, 12, 10, 14, 2, 8, 7, 7,
6, 13, 7, 3, 10, 3, 12, 3, 5, 2, 8, 4, 12, 7,
6, 3, 12, 14, 6, 1, 10, 7, 16, 6, 2, 11, 2, 6,
3, 2, 8, 6, 3, 2, 7, 7, 7, 8, 6, 2, 6, 12,
3, 6, 14, 16, 8, 13, 12, 16, 15, 7, 10, 8, 16, 6,
14, 10, 10, 11, 14, 2, 7, 7, 7, 13, 8, 16, 7, 3,
10, 5, 6, 6, 13, 10, 11, 7, 14, 6, 13, 7, 16, 8,
14, 6, 3, 9, 13, 11, 15, 10, 8, 13, 8, 5, 11, 10,
10, 15, 7, 10, 12, 5, 2, 7, 14, 10, 9, 10, 7, 14,
14, 12, 8, 8, 6, 6, 11, 8, 3, 4, 2, 6, 8, 7,
2, 2, 6, 8, 14, 3, 3, 8, 11, 8, 2, 7, 15, 11,
6, 2, 7, 9, 14, 2, 10, 9, 8, 2, 7, 4, 12, 12,
14, 10, 1, 6, 2, 12, 2, 14, 4, 5, 7, 3, 9, 3,
12, 6, 11, 6, 10, 8, 8, 8, 6, 10, 6, 6, 1, 8,
9, 7, 15, 7, 3, 3, 13, 10, 2, 12, 11, 10, 8, 16,
13, 10, 9, 15, 8, 4, 8, 12, 10, 6, 6, 8, 7, 12,
2, 14, 8, 13, 10, 12, 13, 14, 11, 12, 8, 13, 7, 14,
11, 14, 16, 10, 7, 11, 3, 15, 2, 15, 6, 3, 12, 14,
7, 2, 6, 4, 2, 1, 8, 5, 8, 2, 13, 2, 4, 13,
10, 4, 7, 6, 12, 7, 7, 6, 2, 7, 5, 6, 14, 11,
10, 4, 11, 4, 15, 13, 11, 12, 9, 3, 2, 15, 7, 15,
2, 14, 12, 4, 6, 4, 6, 10, 10, 10, 4, 4, 11, 12,
3, 7, 13, 2, 11, 2, 2, 3, 3, 2, 3, 3, 12, 2,
3, 11, 11, 16, 14, 15, 10, 15, 3, 7, 5, 3, 11, 12,
2, 14, 9, 8, 10, 2, 6, 10, 13, 7, 3, 13, 6, 13,
12, 3, 5, 3, 6, 10, 16, 8, 8, 7, 2, 3, 13, 7,
6, 10, 10, 13, 10, 2, 1, 8, 14, 6, 2, 6, 6, 10,
6, 2, 7, 8, 5, 14, 12, 4, 1, 6, 3, 2, 3, 6,
1, 11, 4, 9, 3, 2, 4, 3, 3, 2, 3, 10, 8, 6,
10, 10, 9, 9, 7, 4, 11, 7, 10, 14, 15, 8, 7, 3,
15, 2, 13, 7, 2, 8, 8, 12, 10, 3, 7, 11, 8, 10,
2, 6, 3, 14, 6, 7, 8, 6, 10, 2, 4, 12, 8, 12,
6, 12, 7, 7, 8, 10, 15, 8, 7, 2, 3, 8, 12, 8,
8, 7, 6, 9, 10, 13, 12, 11, 8, 3, 10, 2, 4, 6,
4, 14, 15, 11, 8, 3, 8, 3, 14, 8, 12, 2, 7, 3,
3, 4, 14, 6, 8, 3, 2, 8, 4, 10, 6, 7, 2, 7,
8, 12, 7, 4, 12, 5, 7, 3, 11, 3, 8, 12, 8, 12,
2, 10, 4, 4, 2, 14, 8, 7, 8, 7, 7, 7, 1, 7,
7, 4, 4, 4, 7, 8, 10, 7, 11, 2, 8, 6, 12, 12,
7, 15, 4, 2, 8, 3, 14, 9, 8, 7, 8, 10, 6, 6,
8, 16, 11, 12, 2, 9, 10, 8, 10, 16, 2, 3, 2, 10,
14, 10, 7, 14, 16, 8, 5, 2, 14, 10, 16, 11, 10, 12,
9, 7, 6, 10, 11, 8, 12, 13, 8, 10, 9, 8, 5, 9,
13, 6, 3, 13, 6, 2, 14, 8, 5, 5, 2, 6, 6, 2,
6, 7, 14, 2, 7, 10, 6, 7, 4, 3, 7, 14, 5, 5,
7, 9, 7, 14, 15, 4, 4, 15, 8, 9, 7, 11, 11, 2,
10, 10, 7, 4, 6, 4, 10, 6, 11, 11, 2, 8, 13, 6,
14, 12, 14, 9, 8, 8, 2, 7, 11, 8, 2, 7, 7, 3,
6, 2, 16, 12, 10, 13, 11, 7, 2, 7, 10, 10, 12, 8,
4, 9, 7, 9, 7, 8, 11, 7, 10, 10, 2, 14, 8, 14,
16, 11, 10, 8, 6, 14, 10, 7, 12, 16, 10, 6, 14, 14,
3, 11, 16, 11, 8, 13, 11, 12, 10, 15, 14, 11, 9, 14,
3, 10, 9, 3, 10, 4, 8, 6, 8, 12, 8, 4, 14, 7,
6, 8, 3, 8, 11, 16, 2, 2, 7, 8, 6, 7, 2, 10,
11, 8, 7, 12, 13, 10, 12, 8, 12, 10, 3, 8, 16, 16,
6, 12, 13, 6, 14, 7, 4, 8, 8, 11, 16, 10, 13, 12,
10, 3, 10, 16, 4, 2, 4, 8, 6, 1, 4, 15, 8, 1,
7, 7, 11, 10, 7, 7, 13, 2, 7, 2, 6, 7, 9, 8,
10, 6, 3, 12, 6, 12, 7, 3, 10, 15, 8, 12, 9, 2,
7, 8, 7, 6, 7, 7, 8, 8, 10, 15, 6, 8, 12, 4,
11, 1, 8, 8, 16, 4, 8, 6, 8, 10, 15, 7, 8, 12,
6, 4, 7, 8, 8, 4, 7, 10, 4, 2, 6, 11, 4, 11,
3, 14, 13, 9, 12, 10, 7, 12, 8, 4, 10, 5, 12, 11,
6, 12, 16, 2, 13, 3, 9, 14, 14, 12, 10, 7, 2, 7,
9, 12, 7, 2, 2, 8, 14, 10, 12, 2, 16, 7, 11, 14,
2, 14, 9, 11, 11, 2, 7, 12, 6, 15, 6, 16, 14, 13,
7, 10, 10, 15, 8, 8, 10, 11, 8, 4, 2, 16, 8, 8,
6, 7, 12, 7, 8, 3, 2, 7, 6, 15, 7, 10, 11, 15,
2, 14, 16, 5, 3, 6, 8, 6, 7, 12, 11, 8, 2, 14,
16, 7, 14, 7, 11, 3, 15, 11, 11, 10, 16, 15, 15, 4,
14, 3, 3, 11, 16, 1, 12, 7, 3, 8, 15, 2, 15, 4,
8, 8, 4, 3, 8, 4, 8, 6, 11, 3, 11, 7, 10, 3,
15, 2, 12, 7, 6, 8, 8, 10, 10, 2, 1, 12, 9, 10,
3, 8, 6, 12, 10, 15, 11, 8, 11, 7, 7, 15, 16, 12,
3, 14, 8, 15, 12, 14, 4, 7, 2, 10, 14, 6, 14, 12,
11, 7, 2, 8, 2, 4, 8, 16, 11, 15, 7, 3, 8, 13,
7, 16, 8, 14, 6, 3, 9, 13, 11, 15, 10, 8, 13, 8,
5, 11, 10, 10, 15, 7, 10, 12, 5, 2, 7, 14, 10, 9,
10, 7, 14, 14, 12, 8, 8, 6, 6, 11, 8, 3, 4, 2,
6, 8, 7, 2, 2, 6, 8, 14, 3, 3, 8, 11, 8, 2,
7, 15, 11, 6, 2, 7, 9, 14, 2, 10, 9, 8, 2, 7,
4, 12, 12, 14, 10, 1, 6, 2, 12, 2, 14, 4, 5, 7,
3, 9, 3, 12, 6, 11, 6, 10, 8, 8, 8, 6, 10, 6,
6, 1, 8, 9, 7, 15, 7, 3, 3, 13, 10, 2, 12, 11,
10, 8, 16, 13, 10, 9, 15, 8, 4, 8, 12, 10, 6, 6,
8, 7, 12, 2, 14, 8, 13, 10, 12, 13, 14, 11, 12, 8,
13, 7, 14, 11, 14, 16, 10, 7, 11, 3, 15, 2, 15, 6,
3, 12, 14, 7, 2, 6, 4, 2, 1, 8, 5, 8, 2, 13,
2, 4, 13, 10, 4, 7, 6, 12, 7, 7, 6, 2, 7, 5,
6, 14, 11, 10, 4, 11, 4, 15, 13, 11, 12, 9, 3, 2,
15, 7, 15, 2, 14, 12, 4, 6, 4, 6, 10, 10, 10, 4,
4, 11, 12, 3, 7, 13, 2, 11, 2, 2, 3, 3, 2, 3,
3, 12, 2, 3, 11, 11, 16, 14, 15, 10, 15, 3, 7, 5,
3, 11, 12, 2, 14, 9, 8, 10, 2, 6, 10, 13, 7, 3,
13, 6, 13, 12, 3, 5, 3, 6, 10, 16, 8, 8, 7, 2,
3, 13, 7, 6, 10, 10, 13, 10, 2, 1, 8, 14, 6, 2,
6, 6, 10, 6, 2, 7, 8, 5, 14, 12, 4, 1, 6, 3,
2, 3, 6, 1, 11, 4, 9, 3, 2, 4, 3, 3, 2, 3,
10, 8, 6, 10, 10, 9, 9, 7, 4, 11, 7, 10, 14, 15,
8, 7, 3, 15, 2, 13, 7, 2, 8, 8, 12, 10, 3, 7,
11, 8, 10, 2, 6, 3, 14, 6, 7, 8, 6, 10, 2, 4,
12, 8, 12, 6, 12, 7, 7, 8, 10, 15, 8, 7, 2, 3,
8, 12, 8, 8, 7, 6, 9, 10, 13, 12, 11, 8, 3, 10,
2, 4, 6, 4, 14, 15, 11, 8, 3, 8, 3, 14, 8, 12,
2, 7, 3, 3, 4, 14, 6, 8, 3, 2, 8, 4, 10, 6,
7, 2, 7, 8, 12, 7, 4, 12, 5, 7, 3, 11, 3, 8,
12, 8, 12, 2, 10, 4, 4, 2, 14, 8, 7, 8, 7, 7,
7, 1, 7, 7, 4, 4, 4, 7, 8, 10, 7, 11, 2, 8,
6, 12, 12, 7, 15, 4, 2, 8, 3, 14, 9, 8, 7, 8,
10, 6, 6, 8, 16, 11, 12, 2, 9, 10, 8, 10, 16, 2,
3, 2, 10, 14, 10, 7, 14, 16, 8, 5, 2, 14, 10, 16,
11, 10, 12, 9, 7, 6, 10, 11, 8, 12, 13, 8, 10, 9,
8, 5, 9, 13, 6, 3, 13, 6, 2, 14, 8, 5, 5, 2,
6, 6, 2, 6, 7, 14, 2, 7, 10, 6, 7, 4, 3, 7,
14, 5, 5, 7, 9, 7, 14, 15, 4, 4, 15, 8, 9, 7,
11, 11, 2, 10, 10, 7, 4, 6, 4, 10, 6, 11, 11, 2,
8, 13, 6, 14, 12, 14, 9, 8, 8, 2, 7, 11, 8, 2,
7, 7, 3, 6, 2, 16, 12, 10, 13, 11, 7, 2, 7, 10,
10, 12, 8, 4, 9, 7, 9, 7, 8, 11, 7, 10, 10, 2,
14, 8, 14, 16, 11, 10, 8, 6, 14, 10, 7, 12, 16, 10,
6, 14, 14, 3, 11, 16, 11, 8, 13, 11, 12, 10, 15, 14,
11, 9, 14, 3, 10, 9, 3, 10, 4, 8, 6, 8, 12, 8,
4, 14, 7, 6, 8, 3, 8, 11, 16, 2, 2, 7, 8, 6,
7, 2, 10, 11, 8, 7, 12, 13, 10, 12, 8, 12, 10, 3,
8, 16, 16, 6, 12, 13, 6, 14, 7, 4, 8, 8, 11, 16,
10, 13, 12, 10, 3, 10, 16, 4, 2, 4, 8, 6, 1, 4,
15, 8, 1, 7, 7, 11, 10, 7, 7, 13, 2, 7, 2, 6,
7, 9, 8, 10, 6, 3, 12, 6, 12, 7, 3, 10, 15, 8,
12, 9, 2, 7, 8, 7, 6, 7, 7, 8, 8, 10, 15, 6,
8, 12, 4, 11, 1, 8, 8, 16, 4, 8, 6, 8, 10, 15,
7, 8, 12, 6, 4, 7, 8, 8, 4, 7, 10, 4, 2, 6,
11, 4, 11, 3, 14, 13, 9, 12, 10, 7, 12, 8, 4, 10,
5, 12, 11, 6, 12, 16, 2, 13, 3, 9, 14, 14, 12, 10,
7, 2, 7, 9, 12, 7, 2, 2, 8, 14, 10, 12, 2, 16,
7, 11, 14, 2, 14, 9, 11, 11, 2, 7, 12, 6, 15, 6,
16, 14, 13, 7, 10, 10, 15, 8, 8, 10, 11, 8, 4, 2,
16, 8, 8, 6, 7, 12, 7, 8, 3, 2, 7, 6, 15, 7,
10, 11, 15, 2, 14, 16, 5, 3, 6, 8, 6, 7, 12, 11,
8, 2, 14, 16, 7, 14, 7, 11, 3, 15, 11, 11, 10, 16,
15, 15, 4, 14, 3, 3, 11, 16, 1, 12, 7, 3, 8, 15,
2, 15, 4, 8, 8, 4, 3, 8, 4, 8, 6, 11, 3, 11,
7, 10, 3, 15, 2, 12, 7, 6, 8, 8, 10, 10, 2, 1,
12, 9, 10, 3, 8, 6, 12, 10, 15, 11, 8, 11, 7, 7,
15, 16, 12, 3, 14, 8, 15, 12, 14, 4, 7, 2, 10, 14,
6, 14, 12, 11, 7, 2, 8, 2, 4, 8, 16, 11, 15, 7,
3, 8, 1, 9, 6, 2, 3, 5, 1, 13, 7, 10, 6, 6,
8, 15, 2, 7, 8, 15, 16, 8, 12, 3, 11, 8, 6, 8,
6, 16, 7, 12, 13, 8, 9, 15, 9, 11, 10, 8, 5, 7,
4, 1, 4, 7, 8, 8, 9, 6, 6, 15, 3, 3, 10, 15,
8, 10, 3, 8, 6, 9, 2, 14, 7, 8, 16, 6, 2, 4,
6, 1, 11, 12, 12, 7, 7, 9, 13, 6, 16, 7, 9, 13,
8, 6, 10, 5, 6, 10, 14, 2, 10, 5, 3, 6, 5, 6,
6, 8, 8, 6, 16, 15, 12, 12, 12, 10, 8, 15, 3, 11,
13, 10, 1, 14, 11, 7, 2, 7, 6, 6, 8, 8, 13, 3,
5, 2, 10, 10, 15, 2, 10, 1, 11, 9, 10, 8, 7, 13,
6, 11, 8, 8, 8, 9, 2, 10, 12, 6, 3, 15, 7, 13,
8, 12, 6, 10, 11, 9, 11, 2, 9, 12, 16, 9, 13, 12,
16, 15, 10, 2, 15, 6, 10, 3, 3, 9, 2, 2, 8, 2,
6, 8, 7, 2, 16, 12, 7, 8, 11, 13, 11, 16, 2, 8,
10, 11, 6, 10, 15, 2, 6, 2, 8, 10, 3, 2, 15, 8,
15, 2, 9, 3, 12, 10, 4, 12, 13, 3, 10, 1, 2, 3,
1, 13, 2, 10, 10, 4, 7, 2, 8, 6, 12, 8, 14, 8,
4, 6, 5, 2, 10, 10, 11, 15, 14, 7, 2, 7, 6, 12,
7, 12, 12, 7, 14, 13, 9, 11, 10, 8, 8, 7, 4, 12,
7, 6, 10, 10, 16, 8, 8, 9, 7, 8, 13, 6, 10, 10,
14, 8, 15, 3, 10, 3, 7, 14, 14, 11, 10, 15, 6, 7,
7, 3, 3, 7, 3, 2, 13, 10, 6, 10, 8, 9, 12, 12,
6, 8, 8, 11, 12, 13, 15, 12, 10, 9, 3, 16, 14, 8,
4, 7, 8, 3, 11, 9, 14, 7, 13, 11, 9, 3, 8, 8,
8, 8, 11, 15, 8, 3, 7, 7, 14, 3, 10, 15, 7, 11,
7, 12, 12, 12, 6, 7, 6, 8, 6, 6, 6, 11, 11, 4,
6, 8, 2, 13, 10, 6, 11, 14, 15, 4, 2, 6, 8, 3,
14, 6, 12, 8, 8, 14, 12, 6, 6, 8, 3, 11, 14, 10,
8, 2, 8, 15, 2, 7, 10, 2, 4, 3, 7, 8, 15, 8,
7, 10, 8, 11, 2, 10, 6, 8, 6, 6, 8, 8, 8, 4,
11, 11, 9, 13, 3, 8, 13, 3, 7, 8, 3, 12, 7, 11,
3, 2, 7, 3, 7, 8, 16, 10, 14, 11, 8, 6, 13, 15,
10, 2, 10, 11, 10, 8, 7, 8, 16, 12, 16, 8, 7, 2,
8, 10, 3, 13, 11, 8, 7, 2, 14, 14, 6, 13, 7, 14,
2, 7, 10, 6, 7, 4, 3, 7, 14, 5, 5, 7, 9, 7,
14, 15, 4, 4, 15, 8, 9, 7, 11, 11, 2, 10, 10, 7,
4, 6, 4, 10, 6, 11, 11, 2, 8, 13, 6, 14, 12, 14,
9, 8, 8, 2, 7, 11, 8, 2, 7, 7, 3, 6, 2, 16,
12, 10, 13, 11, 7, 2, 7, 10, 10, 12, 8, 4, 9, 7,
9, 7, 8, 11, 7, 10, 10, 2, 14, 8, 14, 16, 11, 10,
8, 6, 14, 10, 7, 12, 16, 10, 6, 14, 14, 3, 11, 16,
11, 8, 13, 11, 12, 10, 15, 14, 11, 9, 14, 3, 10, 9,
3, 10, 4, 8, 6, 8, 12, 8, 4, 14, 7, 6, 8, 3,
8, 11, 16, 2, 2, 7, 8, 6, 7, 2, 10, 11, 8, 7,
12, 13, 10, 12, 8, 12, 10, 3, 8, 16, 16, 6, 12, 13,
6, 14, 7, 4, 8, 8, 11, 16, 10, 13, 12, 10, 3, 10,
16, 4, 2, 4, 8, 6, 1, 4, 15, 8, 1, 7, 7, 11,
10, 7, 7, 13, 2, 7, 2, 6, 7, 9, 8, 10, 6, 3,
12, 6, 12, 7, 3, 10, 15, 8, 12, 9, 2, 7, 8, 7,
6, 7, 7, 8, 8, 10, 15, 6, 8, 12, 4, 11, 1, 8,
8, 16, 4, 8, 6, 8, 10, 15, 7, 8, 12, 6, 4, 7,
8, 8, 4, 7, 10, 4, 2, 6, 11, 4, 11, 3, 14, 13,
9, 12, 10, 7, 12, 8, 4, 10, 5, 12, 11, 6, 12, 16,
2, 13, 3, 9, 14, 14, 12, 10, 7, 2, 7, 9, 12, 7,
2, 2, 8, 14, 10, 12, 2, 16, 7, 11, 14, 2, 14, 9,
11, 11, 2, 7, 12, 6, 15, 6, 16, 14, 13, 7, 10, 10,
15, 8, 8, 10, 11, 8, 4, 2, 16, 8, 8, 6, 7, 12,
7, 8, 3, 2, 7, 6, 15, 7, 10, 11, 15, 2, 14, 16,
5, 3, 6, 8, 6, 7, 12, 11, 8, 2, 14, 16, 7, 14,
7, 11, 3, 15, 11, 11, 10, 16, 15, 15, 4, 14, 3, 3,
11, 16, 1, 12, 7, 3, 8, 15, 2, 15, 4, 8, 8, 4,
3, 8, 4, 8, 6, 11, 3, 11, 7, 10, 3, 15, 2, 12,
7, 6, 8, 8, 10, 10, 2, 1, 12, 9, 10, 3, 8, 6,
12, 10, 15, 11, 8, 11, 7, 7, 15, 16, 12, 3, 14, 8,
15, 12, 14, 4, 7, 2, 10, 14, 6, 14, 12, 11, 7, 2,
8, 2, 4, 8, 16, 11, 15, 7, 3, 8, 1, 9, 6, 2,
3, 5, 1, 13, 7, 10, 6, 6, 8, 15, 2, 7, 8, 15,
16, 8, 12, 3, 11, 8, 6, 8, 6, 16, 7, 12, 13, 8,
9, 15, 9, 11, 10, 8, 5, 7, 4, 1, 4, 7, 8, 8,
9, 6, 6, 15, 3, 3, 10, 15, 8, 10, 3, 8, 6, 9,
2, 14, 7, 8, 16, 6, 2, 4, 6, 14, 1, 11, 12, 12,
7, 7, 9, 13, 6, 16, 7, 9, 13, 8, 6, 10, 5, 6,
10, 14, 2, 10, 5, 3, 6, 5, 6, 6, 8, 8, 6, 16,
15, 12, 12, 12, 10, 8, 15, 3, 11, 13, 10, 1, 14, 11,
7, 2, 7, 6, 6, 8, 8, 13, 3, 5, 2, 10, 10, 15,
2, 10, 1, 11, 9, 10, 8, 7, 13, 6, 11, 8, 8, 8,
9, 2, 10, 12, 6, 3, 15, 7, 13, 8, 12, 6, 10, 11,
9, 11, 2, 9, 12, 16, 9, 13, 12, 16, 15, 10, 2, 15,
6, 10, 3, 3, 9, 2, 2, 8, 2, 6, 8, 7, 2, 16,
12, 7, 8, 11, 13, 11, 16, 2, 8, 10, 11, 6, 10, 15,
2, 6, 2, 8, 10, 3, 2, 15, 8, 15, 2, 9, 3, 12,
10, 4, 12, 13, 3, 10, 1, 2, 3, 1, 13, 2, 10, 10,
4, 7, 2, 8, 6, 12, 8, 14, 8, 4, 6, 5, 2, 10,
10, 11, 15, 14, 7, 2, 7, 6, 12, 7, 12, 12, 7, 14,
13, 9, 11, 10, 8, 8, 7, 4, 12, 7, 6, 10, 10, 16,
8, 8, 9, 7, 8, 13, 6, 10, 10, 14, 8, 15, 3, 10,
3, 7, 14, 14, 11, 10, 15, 6, 7, 7, 3, 3, 7, 3,
2, 13, 10, 14, 6, 10, 8, 9, 12, 12, 6, 8, 8, 11,
12, 13, 15, 12, 10, 9, 3, 16, 14, 8, 4, 7, 8, 3,
11, 9, 14, 7, 13, 11, 9, 3, 8, 8, 8, 8, 11, 7,
15, 8, 3, 7, 7, 14, 3, 10, 15, 7, 11, 7, 12, 12,
12, 6, 7, 6, 8, 6, 6, 6, 11, 11, 4, 6, 8, 2,
13, 10, 6, 11, 14, 15, 4, 2, 6, 8, 3, 14, 6, 12,
8, 8, 14, 12, 6, 6, 8, 3, 11, 14, 10, 8, 2, 8,
15, 2, 7, 10, 2, 4, 3, 7, 8, 15, 8, 7, 10, 8,
11, 2, 10, 6, 8, 6, 6, 8, 8, 8, 4, 11, 11, 9,
13, 3, 8, 13, 3, 7, 8, 3, 12, 7, 11, 3, 2, 7,
3, 7, 8, 16, 10, 14, 11, 8, 6, 13, 15, 10, 2, 10,
11, 10, 8, 7, 8, 16, 12, 16, 8, 7, 2, 8, 10, 3,
13, 11, 8, 7, 2, 14, 14, 6, 13, 8, 9, 2, 8, 7,
6, 8, 2, 16, 10, 15, 7, 12, 15, 5, 16, 1, 4, 1,
8, 10, 3, 2, 6, 15, 6, 8, 6, 14, 13, 6, 13, 10,
13, 6, 12, 6, 4, 15, 14, 11, 9, 3, 10, 13, 3, 15,
6, 10, 14, 5, 8, 6, 7, 6, 12, 11, 9, 10, 10, 10,
6, 12, 4, 8, 2, 16, 4, 12, 6, 12, 2, 4, 15, 8,
4, 7, 14, 8, 11, 16, 4, 7, 3, 14, 7, 10, 2, 12,
8, 10, 10, 14, 12, 14, 11, 9, 16, 6, 3, 9, 4, 10,
10, 8, 16, 10, 14, 12, 12, 11, 8, 10, 10, 6, 14, 5,
6, 3, 10, 6, 14, 14, 9, 2, 6, 14, 8, 11, 14, 6,
2, 16, 2, 3, 7, 10, 10, 8, 12, 9, 3, 7, 12, 3,
8, 6, 12, 7, 16, 6, 3, 14, 6, 3, 2, 12, 14, 14,
7, 10, 6, 8, 13, 11, 10, 8, 11, 14, 8, 7, 14, 5,
15, 8, 13, 3, 16, 6, 8, 7, 10, 2, 8, 2, 6, 11,
7, 14, 6, 13, 9, 4, 15, 11, 8, 13, 6, 11, 10, 8,
8, 6, 11, 13, 9, 3, 10, 8, 13, 4, 7, 8, 8, 11,
15, 12, 14, 8, 10, 7, 7, 7, 8, 2, 10, 3, 8, 2,
8, 7, 14, 8, 12, 6, 14, 10, 13, 11, 11, 9, 6, 7,
6, 2, 6, 2, 8, 4, 5, 14, 6, 15, 3, 4, 6, 10,
4, 14, 5, 12, 6, 8, 13, 8, 6, 10, 9, 4, 12, 2,
7, 10, 10, 6, 12, 4, 7, 12, 9, 10, 10, 10, 8, 12,
14, 7, 12, 8, 14, 11, 10, 6, 5, 6, 3, 3, 4, 12,
8, 9, 4, 2, 11, 12, 3, 6, 11, 11, 10, 7, 8, 6,
12, 16, 16, 7, 11, 12, 4, 12, 10, 12, 10, 7, 16, 3,
9, 6, 3, 7, 2, 8, 7, 7, 12, 6, 5, 10, 12, 14,
9, 15, 9, 12, 6, 12, 10, 7, 2, 6, 14, 10, 11, 15,
3, 10, 7, 8, 2, 7, 14, 3, 10, 9, 15, 13, 13, 5,
13, 2, 11, 9, 11, 4, 8, 2, 7, 7, 2, 6, 14, 14,
11, 14, 12, 7, 12, 9, 2, 3, 12, 12, 10, 10, 14, 3,
14, 10, 12, 10, 7, 10, 6, 8, 7, 7, 10, 8, 8, 15,
3, 11, 7, 1, 14, 6, 7, 12, 4, 15, 2, 6, 14, 3,
11, 8, 13, 2, 8, 10, 14, 8, 10, 3, 6, 8, 10, 14,
11, 7, 6, 12, 6, 8, 8, 7, 2, 7, 8, 14, 3, 3,
6, 3, 16, 8, 9, 2, 7, 3, 12, 15, 4, 3, 9, 10,
2, 7, 10, 14, 2, 12, 8, 10, 10, 7, 12, 7, 6, 8,
8, 16, 6, 6, 9, 7, 8, 10, 8, 12, 7, 12, 3, 14,
8, 8, 2, 15, 2, 11, 8, 9, 2, 8, 7, 6, 8, 2,
16, 10, 15, 7, 12, 15, 5, 16, 1, 4, 1, 8, 10, 3,
2, 6, 15, 6, 8, 6, 14, 13, 6, 13, 10, 13, 6, 12,
6, 4, 15, 14, 11, 9, 3, 10, 13, 3, 15, 6, 10, 14,
5, 8, 6, 7, 6, 12, 11, 9, 10, 10, 10, 6, 12, 4,
8, 2, 16, 4, 12, 6, 12, 2, 4, 15, 8, 4, 7, 14,
8, 11, 16, 4, 7, 3, 14, 7, 10, 2, 12, 8, 10, 10,
14, 12, 14, 11, 9, 16, 6, 3, 9, 4, 10, 10, 8, 16,
10, 14, 12, 12, 11, 8, 10, 10, 6, 14, 5, 6, 3, 10,
6, 14, 14, 9, 2, 6, 14, 8, 11, 14, 6, 2, 16, 2,
3, 7, 10, 10, 8, 12, 9, 3, 7, 12, 3, 8, 6, 12,
7, 16, 6, 3, 14, 6, 3, 2, 12, 14, 14, 7, 10, 6,
8, 13, 11, 10, 8, 11, 14, 8, 7, 14, 5, 15, 8, 13,
3, 16, 6, 8, 7, 10, 2, 8, 2, 6, 11, 7, 14, 6,
13, 9, 4, 15, 11, 8, 13, 6, 11, 10, 8, 8, 6, 11,
13, 9, 3, 10, 8, 13, 4, 7, 8, 8, 11, 15, 12, 14,
8, 10, 7, 7, 7, 8, 2, 10, 3, 8, 2, 8, 7, 14,
8, 12, 6, 14, 10, 13, 11, 11, 9, 6, 7, 6, 2, 6,
2, 8, 4, 5, 14, 6, 15, 3, 4, 6, 10, 4, 14, 5,
12, 6, 8, 13, 8, 6, 10, 9, 4, 12, 2, 7, 10, 10,
6, 12, 4, 7, 12, 9, 10, 10, 10, 8, 12, 14, 7, 12,
8, 14, 11, 10, 6, 5, 6, 3, 3, 4, 12, 8, 9, 4,
2, 11, 12, 3, 6, 11, 11, 10, 7, 8, 6, 12, 16, 16,
7, 11, 12, 4, 12, 10, 12, 10, 7, 16, 3, 9, 6, 3,
7, 2, 8, 7, 7, 12, 6, 5, 10, 12, 14, 9, 15, 9,
12, 6, 12, 10, 7, 2, 6, 14, 10, 11, 15, 3, 10, 7,
8, 2, 7, 14, 3, 10, 9, 15, 13, 13, 5, 13, 2, 11,
9, 11, 4, 8, 2, 7, 7, 2, 6, 14, 14, 11, 14, 12,
7, 12, 9, 2, 3, 12, 12, 10, 10, 14, 3, 14, 10, 12,
10, 7, 10, 6, 8, 7, 7, 10, 8, 8, 15, 3, 11, 7,
1, 14, 6, 7, 12, 4, 15, 2, 6, 14, 3, 11, 8, 13,
2, 8, 10, 14, 8, 10, 3, 6, 8, 10, 14, 11, 7, 6,
12, 6, 8, 8, 7, 2, 7, 8, 14, 3, 3, 6, 3, 16,
8, 9, 2, 7, 3, 12, 15, 4, 3, 9, 10, 2, 7, 10,
14, 2, 12, 8, 10, 10, 7, 12, 7, 6, 8, 8, 16, 6,
6, 9, 7, 8, 10, 8, 12, 7, 12, 3, 14, 8, 8, 2,
15, 2, 11, 12, 7, 13, 10, 14, 7, 4, 10, 8, 6, 16,
7, 6, 15, 8, 2, 14, 11, 1, 9, 12, 2, 15, 2, 6,
7, 16, 14, 9, 2, 10, 10, 12, 7, 7, 7, 10, 4, 14,
4, 12, 12, 10, 10, 4, 16, 8, 13, 10, 16, 10, 6, 8,
15, 11, 4, 8, 8, 4, 14, 3, 12, 10, 12, 2, 8, 2,
13, 3, 3, 10, 13, 10, 3, 4, 8, 10, 9, 6, 8, 11,
5, 12, 6, 10, 10, 11, 6, 16, 6, 2, 2, 13, 6, 10,
14, 15, 7, 6, 14, 12, 6, 10, 10, 12, 11, 13, 7, 2,
8, 10, 6, 16, 8, 5, 11, 7, 6, 3, 8, 6, 5, 6,
6, 3, 12, 7, 14, 3, 10, 9, 7, 8, 10, 6, 12, 7,
15, 6, 10, 2, 11, 14, 10, 1, 2, 10, 5, 10, 11, 6,
16, 14, 12, 6, 6, 2, 11, 13, 2, 7, 14, 8, 12, 10,
12, 14, 6, 2, 1, 13, 13, 6, 13, 3, 2, 13, 8, 14,
16, 7, 6, 12, 3, 12, 14, 9, 14, 2, 3, 12, 1, 12,
8, 9, 2, 16, 2, 12, 1, 14, 10, 6, 3, 4, 12, 8,
3, 9, 4, 10, 6, 10, 10, 2, 8, 7, 8, 14, 8, 3,
8, 10, 16, 14, 12, 7, 7, 12, 14, 10, 10, 3, 7, 14,
10, 7, 2, 1, 16, 4, 2, 2, 6, 14, 7, 3, 6, 6,
7, 6, 8, 8, 13, 4, 2, 10, 2, 7, 11, 12, 2, 6,
6, 2, 6, 12, 7, 4, 9, 14, 4, 10, 14, 2, 8, 8,
1, 4, 8, 12, 1, 8, 14, 15, 9, 8, 8, 2, 4, 10,
3, 12, 6, 8, 14, 8, 8, 8, 11, 15, 8, 7, 8, 2,
11, 2, 8, 15, 7, 3, 2, 3, 7, 16, 8, 13, 11, 14,
7, 12, 12, 15, 15, 2, 2, 12, 8, 7, 14, 10, 9, 14,
13, 4, 13, 2, 14, 8, 2, 2, 3, 4, 13, 7, 15, 3,
2, 2, 11, 8, 1, 7, 15, 9, 2, 9, 13, 2, 2, 14,
11, 4, 8, 16, 1, 8, 5, 7, 12, 15, 3, 12, 3, 3,
2, 2, 10, 12, 7, 16, 6, 10, 14, 4, 7, 10, 7, 10,
7, 6, 13, 2, 3, 8, 11, 10, 8, 9, 13, 11, 7, 4,
10, 7, 14, 2, 10, 6, 2, 7, 7, 10, 6, 6, 7, 8,
7, 7, 8, 12, 6, 2, 6, 2, 4, 4, 6, 7, 3, 13,
4, 6, 5, 11, 2, 5, 8, 6, 10, 9, 2, 4, 10, 14,
2, 2, 4, 6, 15, 3, 10, 3, 16, 10, 1, 4, 7, 9,
6, 9, 2, 6, 11, 6, 3, 10, 14, 6, 2, 8, 10, 8,
8, 6, 2, 12, 11, 12, 7, 4, 2, 1, 8, 15, 12, 2,
14, 1, 12, 11, 7, 15, 3, 8, 6, 3, 5, 5, 10, 6,
6, 1, 4, 8, 6, 13, 6, 11, 3, 16, 11, 14, 3, 8,
7, 6, 15, 9, 11, 7, 4, 8, 4, 10, 10, 10, 8, 14,
10, 5, 3, 7, 12, 14, 6, 12, 9, 7, 11, 2, 2, 10,
6, 15, 12, 14, 10, 7, 8, 8, 14, 11, 6, 13, 3, 3,
2, 10, 10, 11, 12, 7, 4, 6, 4, 3, 8, 10, 8, 15,
3, 3, 15, 4, 13, 8, 2, 2, 14, 6, 1, 8, 8, 8,
4, 7, 7, 8, 15, 14, 13, 8, 2, 8, 4, 7, 2, 3,
6, 11, 8, 7, 2, 6, 4, 2, 12, 10, 13, 4, 8, 5,
8, 9, 7, 2, 8, 10, 2, 9, 6, 13, 12, 3, 10, 8,
11, 12, 6, 8, 6, 4, 11, 1, 12, 6, 11, 6, 8, 8,
6, 13, 10, 10, 7, 6, 3, 7, 3, 8, 6, 11, 7, 6,
15, 11, 3, 8, 1, 11, 11, 14, 7, 4, 16, 6, 5, 2,
8, 2, 14, 7, 2, 6, 13, 16, 2, 15, 16, 7, 2, 6,
14, 3, 6, 3, 8, 7, 15, 7, 8, 7, 14, 6, 3, 3,
16, 11, 15, 9, 12, 4, 2, 6, 6, 11, 7, 10, 8, 8,
2, 13, 2, 14, 6, 8, 9, 3, 8, 7, 6, 8, 12, 14,
12, 8, 5, 10, 10, 6, 14, 7, 8, 13, 4, 10, 4, 16,
8, 8, 8, 2, 14, 10, 10, 12, 9, 1, 6, 10, 7, 8,
8, 12, 11, 7, 8, 6, 8, 10, 4, 9, 8, 12, 6, 10,
8, 5, 14, 15, 2, 2, 10, 8, 6, 6, 14, 4, 14, 15,
15, 7, 6, 4, 14, 4, 14, 14, 12, 5, 3, 11, 2, 10,
10, 7, 14, 4, 2, 6, 14, 8, 10, 9, 6, 10, 9, 7,
12, 13, 6, 10, 14, 10, 10, 12, 3, 6, 2, 6, 11, 11,
3, 4, 12, 13, 8, 4, 4, 7, 8, 10, 10, 11, 5, 6,
9, 11, 6, 13, 9, 6, 11, 11, 8, 6, 7, 6, 16, 7,
16, 10, 2, 10, 7, 2, 7, 16, 1, 6, 13, 8, 10, 12,
13, 8, 10, 8, 11, 4, 6, 3, 12, 4, 14, 16, 8, 10,
2, 13, 2, 10, 6, 6, 10, 8, 4, 8, 8, 13, 14, 2,
3, 3, 16, 16, 10, 8, 6, 3, 4, 2, 2, 2, 10, 2,
11, 3, 8, 10, 6, 2, 7, 10, 10, 6, 6, 7, 9, 8,
8, 14, 7, 10, 2, 6, 15, 6, 2, 5, 3, 14, 6, 7,
8, 15, 8, 7, 7, 12, 3, 6, 3, 10, 7, 16, 7, 1,
14, 2, 8, 6, 7, 15, 8, 7, 10, 8, 6, 3, 4, 10,
12, 10, 6, 7, 4, 3, 13, 15, 11, 4, 7, 16, 8, 10,
15, 8, 16, 10, 6, 1, 2, 7, 3, 3, 13, 3, 8, 4,
9, 4, 10, 2, 3, 8, 9, 14, 7, 7, 3, 8, 2, 16,
13, 6, 8, 14, 7, 8, 10, 10, 2, 2, 16, 3, 6, 6,
16, 6, 11, 12, 6, 11, 10, 3, 2, 7, 11, 13, 12, 11,
6, 12, 6, 6, 4, 10, 2, 7, 6, 10, 8, 8, 8, 6,
2, 8, 4, 15, 12, 3, 12, 16, 13, 2, 2, 6, 6, 8,
3, 10, 6, 1, 10, 8, 2, 8, 2, 4, 8, 8, 13, 2,
6, 4, 8, 6, 15, 7, 14, 8, 7, 3, 3, 4, 7, 8,
8, 8, 7, 8, 7, 10, 8, 6, 14, 6, 3, 7, 6, 8,
13, 8, 8, 2, 1, 15, 10, 8, 10, 8, 8, 6, 6, 6,
13, 6, 6, 16, 8, 5, 7, 6, 11, 8, 9, 8, 12, 3,
12, 7, 2, 2, 8, 13, 8, 8, 10, 8, 6, 14, 6, 2,
3, 3, 8, 2, 12, 8, 10, 10, 8, 6, 7, 9, 6, 10,
8, 6, 11, 12, 12, 6, 14, 15, 7, 2, 6, 8, 6, 6,
4, 2, 2, 2, 9, 6, 13, 11, 9, 5, 4, 3, 8, 6,
6, 2, 4, 16, 14, 4, 2, 6, 4, 9, 10, 2, 8, 4,
11, 10, 12, 8, 9, 2, 10, 3, 5, 10, 4, 3, 6, 1,
6, 12, 10, 2, 4, 6, 7, 1, 14, 12, 3, 7, 10, 10,
8, 9, 9, 10, 8, 7, 10, 15, 14, 2, 13, 2, 8, 16,
8, 4, 14, 15, 11, 3, 2, 12, 3, 9, 9, 6, 11, 10,
14, 6, 14, 10, 3, 12, 13, 10, 14, 8, 16, 6, 14, 16,
6, 16, 8, 15, 11, 16, 7, 13, 6, 16, 6, 6, 2, 11,
3, 3, 13, 6, 13, 13, 7, 15, 13, 6, 3, 13, 9, 8,
5, 2, 11, 15, 10, 12, 9, 15, 9, 16, 16, 7, 16, 10,
8, 7, 14, 8, 12, 2, 14, 15, 15, 14, 2, 5, 9, 8,
10, 13, 10, 7, 9, 10, 14, 7, 4, 2, 14, 5, 9, 6,
9, 5, 8, 2, 10, 6, 13, 7, 1, 1, 8, 14, 2, 3,
2, 6, 16, 9, 8, 13, 7, 8, 6, 2, 7, 4, 10, 7,
14, 2, 10, 6, 2, 7, 7, 10, 6, 6, 7, 8, 7, 7,
8, 12, 6, 2, 6, 2, 4, 4, 6, 7, 3, 13, 4, 6,
5, 11, 2, 5, 8, 6, 10, 9, 2, 4, 10, 14, 2, 2,
4, 6, 15, 3, 10, 3, 16, 10, 1, 4, 7, 9, 6, 9,
2, 6, 11, 6, 3, 10, 14, 6, 2, 8, 10, 8, 8, 6,
2, 12, 11, 12, 7, 4, 2, 1, 8, 15, 12, 2, 14, 1,
12, 11, 7, 15, 3, 8, 6, 3, 5, 5, 10, 6, 6, 1,
4, 8, 6, 13, 6, 11, 3, 16, 11, 14, 3, 8, 7, 6,
15, 9, 11, 7, 4, 8, 4, 10, 10, 10, 8, 14, 10, 5,
3, 7, 12, 14, 6, 12, 9, 7, 11, 2, 2, 10, 6, 15,
12, 14, 10, 7, 8, 8, 14, 11, 6, 13, 3, 3, 2, 10,
10, 11, 12, 7, 4, 6, 4, 3, 8, 10, 8, 15, 3, 3,
15, 4, 13, 8, 2, 2, 14, 6, 1, 8, 8, 8, 4, 7,
7, 8, 15, 14, 13, 8, 2, 8, 4, 7, 2, 3, 6, 11,
8, 7, 2, 6, 4, 2, 12, 10, 13, 4, 8, 5, 8, 9,
7, 2, 8, 10, 2, 9, 6, 13, 12, 3, 10, 8, 11, 12,
6, 8, 6, 4, 11, 1, 12, 6, 11, 6, 8, 8, 6, 13,
10, 10, 7, 6, 3, 7, 3, 8, 6, 11, 7, 6, 15, 11,
3, 8, 1, 11, 11, 14, 7, 4, 16, 6, 5, 2, 8, 2,
14, 7, 2, 6, 13, 16, 2, 15, 16, 7, 2, 6, 14, 3,
6, 3, 8, 7, 15, 7, 8, 7, 14, 6, 3, 3, 16, 11,
15, 9, 12, 4, 2, 6, 6, 11, 7, 10, 8, 8, 2, 13,
2, 14, 6, 8, 9, 3, 8, 7, 6, 8, 12, 14, 12, 8,
5, 10, 10, 6, 14, 7, 8, 13, 4, 10, 4, 16, 8, 8,
8, 2, 14, 10, 10, 12, 9, 1, 6, 10, 7, 8, 8, 12,
11, 7, 8, 6, 8, 10, 4, 9, 8, 12, 6, 10, 8, 5,
14, 15, 2, 2, 10, 8, 6, 6, 14, 4, 14, 15, 15, 7,
6, 4, 14, 4, 14, 14, 12, 5, 3, 11, 2, 10, 10, 7,
14, 4, 2, 6, 14, 8, 10, 9, 6, 10, 9, 7, 12, 13,
6, 10, 14, 10, 10, 12, 3, 6, 2, 6, 11, 11, 3, 4,
12, 13, 8, 4, 4, 7, 8, 10, 10, 11, 5, 6, 9, 11,
6, 13, 9, 6, 11, 11, 8, 6, 7, 6, 16, 7, 16, 10,
2, 10, 7, 2, 7, 16, 1, 6, 13, 8, 10, 12, 13, 8,
10, 8, 11, 4, 6, 3, 12, 4, 14, 16, 8, 10, 2, 13,
2, 10, 6, 6, 10, 8, 4, 8, 8, 13, 14, 2, 3, 3,
16, 16, 10, 8, 6, 3, 4, 2, 2, 2, 10, 2, 11, 3,
8, 10, 6, 2, 7, 10, 10, 6, 6, 7, 9, 8, 8, 14,
7, 10, 2, 6, 15, 6, 2, 5, 3, 14, 6, 7, 8, 15,
8, 7, 7, 12, 3, 6, 3, 10, 7, 16, 7, 1, 14, 2,
8, 6, 7, 15, 8, 7, 10, 8, 6, 3, 4, 10, 12, 10,
6, 7, 4, 3, 13, 15, 11, 4, 7, 16, 8, 10, 15, 8,
16, 10, 6, 1, 2, 7, 3, 3, 13, 3, 8, 4, 9, 4,
10, 2, 3, 8, 9, 14, 7, 7, 3, 8, 2, 16, 13, 6,
8, 14, 7, 8, 10, 10, 2, 2, 16, 3, 6, 6, 16, 6,
11, 12, 6, 11, 10, 3, 2, 7, 11, 13, 12, 11, 6, 12,
6, 6, 4, 10, 2, 7, 6, 10, 8, 8, 8, 6, 2, 8,
4, 15, 12, 3, 12, 16, 13, 2, 2, 6, 6, 8, 3, 10,
6, 1, 10, 8, 2, 8, 2, 4, 8, 8, 13, 2, 6, 4,
8, 6, 15, 7, 14, 8, 7, 3, 3, 4, 7, 8, 8, 8,
7, 8, 7, 10, 8, 6, 14, 6, 3, 7, 6, 8, 13, 8,
8, 2, 1, 15, 10, 8, 10, 8, 8, 6, 6, 6, 13, 6,
6, 16, 8, 5, 7, 6, 11, 8, 9, 8, 12, 3, 12, 7,
2, 2, 8, 13, 8, 8, 10, 8, 6, 14, 6, 2, 3, 3,
8, 2, 12, 8, 10, 10, 8, 6, 7, 9, 6, 10, 8, 6,
11, 12, 12, 6, 14, 15, 7, 2, 6, 8, 6, 6, 4, 2,
2, 2, 9, 6, 13, 11, 9, 5, 4, 3, 8, 6, 6, 2,
4, 16, 14, 4, 2, 6, 4, 9, 10, 2, 8, 4, 11, 10,
12, 8, 9, 2, 10, 3, 5, 10, 4, 3, 6, 1, 6, 12,
10, 2, 4, 6, 7, 1, 14, 12, 3, 7, 10, 10, 8, 9,
9, 10, 8, 7, 10, 15, 14, 2, 13, 2, 8, 16, 8, 4,
14, 15, 11, 3, 2, 12, 3, 9, 9, 6, 11, 10, 14, 6,
14, 10, 3, 12, 13, 10, 14, 8, 16, 6, 14, 16, 6, 16,
8, 15, 11, 16, 7, 13, 6, 16, 6, 6, 2, 11, 3, 3,
13, 6, 13, 13, 7, 15, 13, 6, 3, 13, 9, 8, 5, 2,
11, 15, 10, 12, 9, 15, 9, 16, 16, 7, 16, 10, 8, 7,
14, 8, 12, 2, 14, 15, 15, 14, 2, 5, 9, 8, 10, 13,
10, 7, 9, 10, 14, 7, 4, 2, 14, 5, 9, 6, 9, 5,
8, 2, 10, 6, 13, 7, 1, 1, 8, 14, 2, 3, 2, 6,
16, 9, 8, 13, 7, 8, 6, 2, 3, 8, 14, 3, 6, 16,
6, 14, 12, 9, 8, 15, 8, 8, 8, 14, 13, 2, 7, 15,
2, 10, 8, 8, 12, 2, 12, 15, 5, 10, 13, 7, 8, 3,
6, 13, 10, 10, 12, 6, 12, 4, 1, 8, 3, 8, 10, 6,
8, 9, 4, 9, 7, 3, 6, 6, 7, 4, 8, 13, 13, 6,
6, 8, 7, 8, 12, 2, 3, 7, 12, 2, 2, 7, 8, 10,
8, 9, 7, 6, 14, 1, 9, 10, 4, 4, 2, 16, 2, 3,
2, 9, 11, 2, 7, 8, 8, 11, 14, 6, 12, 14, 2, 2,
6, 5, 7, 2, 12, 10, 6, 12, 3, 14, 3, 6, 1, 13,
3, 9, 5, 5, 6, 6, 13, 1, 12, 6, 6, 14, 7, 8,
12, 16, 16, 6, 8, 13, 12, 6, 12, 4, 3, 16, 3, 3,
9, 3, 11, 3, 13, 8, 10, 6, 7, 6, 2, 8, 3, 9,
8, 2, 4, 12, 3, 2, 6, 4, 10, 6, 7, 12, 10, 2,
10, 7, 11, 15, 12, 7, 11, 14, 8, 3, 11, 8, 11, 2,
7, 8, 10, 8, 7, 14, 10, 14, 15, 7, 12, 12, 3, 10,
8, 7, 8, 6, 4, 7, 8, 10, 15, 6, 1, 2, 7, 4,
2, 11, 8, 12, 4, 8, 6, 2, 12, 11, 7, 8, 2, 6,
12, 2, 6, 13, 10, 4, 8, 2, 14, 10, 4, 4, 7, 6,
10, 10, 7, 12, 7, 8, 3, 3, 3, 10, 6, 8, 10, 3,
3, 3, 10, 12, 8, 8, 3, 2, 4, 10, 7, 3, 14, 12,
8, 2, 8, 10, 9, 2, 11, 2, 7, 1, 12, 6, 4, 6,
10, 14, 6, 9, 6, 11, 3, 16, 15, 3, 7, 14, 3, 6,
11, 11, 8, 7, 2, 6, 8, 2, 2, 2, 1, 10, 11, 2,
8, 7, 14, 13, 7, 3, 6, 2, 16, 13, 7, 14, 8, 10,
5, 6, 10, 2, 14, 8, 8, 11, 9, 7, 6, 2, 12, 7,
8, 10, 10, 12, 11, 6, 10, 6, 13, 6, 7, 7, 2, 7,
10, 8, 6, 4, 2, 2, 6, 8, 10, 4, 4, 10, 12, 10,
11, 2, 1, 6, 12, 3, 7, 6, 13, 7, 10, 8, 3, 4,
12, 6, 7, 8, 8, 5, 14, 4, 10, 6, 2, 2, 10, 14,
6, 8, 16, 10, 14, 2, 6, 10, 12, 8, 10, 16, 6, 16,
8, 12, 2, 2, 3, 14, 8, 5, 13, 10, 4, 10, 4, 8,
7, 2, 12, 5, 14, 7, 10, 7, 8, 7, 14, 4, 3, 3,
3, 7, 7, 6, 11, 14, 6, 3, 6, 1, 4, 10, 8, 8,
2, 13, 11, 2, 10, 8, 6, 7, 3, 8, 6, 6, 2, 12,
10, 10, 7, 4, 7, 15, 7, 7, 4, 6, 9, 2, 2, 8,
6, 4, 6, 4, 5, 11, 6, 8, 4, 6, 4, 8, 2, 14,
6, 4, 6, 8, 11, 2, 4, 1, 4, 7, 4, 8, 2, 8,
8, 12, 16, 13, 12, 10, 2, 6, 10, 10, 11, 11, 8, 8,
12, 2, 6, 4, 9, 8, 8, 13, 2, 12, 7, 7, 12, 11,
8, 7, 10, 14, 7, 10, 2, 7, 2, 6, 10, 3, 10, 8,
8, 10, 2, 6, 8, 2, 6, 13, 7, 8, 6, 16, 8, 4,
2, 4, 5, 7, 6, 8, 7, 14, 8, 10, 4, 10, 2, 6,
6, 6, 6, 2, 9, 6, 8, 8, 6, 8, 10, 12, 10, 9,
2, 3, 15, 16, 8, 11, 14, 10, 6, 12, 3, 6, 10, 13,
4, 8, 7, 6, 8, 11, 3, 1, 10, 16, 8, 6, 2, 1,
4, 14, 6, 3, 16, 7, 10, 2, 2, 14, 14, 10, 8, 14,
8, 10, 6, 10, 10, 15, 8, 12, 3, 3, 16, 13, 11, 6,
11, 14, 2, 16, 3, 10, 4, 10, 11, 8, 3, 14, 14, 10,
12, 6, 3, 9, 2, 7, 2, 8, 8, 8, 13, 6, 9, 7,
11, 11, 9, 14, 2, 3, 5, 16, 12, 8, 10, 10, 10, 8,
9, 9, 3, 5, 8, 13, 6, 14, 8, 7, 8, 7, 8, 3,
15, 7, 6, 2, 6, 10, 8, 2, 6, 2, 6, 8, 3, 9,
8, 8, 16, 9, 4, 10, 4, 10, 4, 16, 9, 10, 3, 6,
6, 4, 14, 8, 8, 4, 2, 10, 4, 3, 7, 7, 10, 4,
8, 6, 8, 10, 10, 12, 10, 4, 9, 13, 4, 8, 1, 7,
12, 6, 10, 3, 7, 7, 2, 8, 6, 7, 6, 6, 4, 15,
4, 10, 8, 12, 11, 8, 6, 14, 10, 9, 11, 11, 6, 11,
3, 6, 9, 2, 2, 8, 4, 6, 9, 2, 7, 7, 4, 11,
10, 2, 6, 3, 3, 4, 2, 6, 6, 10, 6, 10, 10, 8,
12, 3, 6, 7, 7, 12, 2, 4, 6, 8, 7, 3, 4, 14,
15, 4, 8, 11, 10, 2, 3, 8, 3, 5, 6, 8, 7, 8,
7, 7, 7, 8, 12, 8, 10, 1, 8, 14, 7, 2, 7, 8,
6, 2, 7, 3, 2, 8, 8, 10, 2, 9, 8, 6, 5, 7,
1, 6, 6, 2, 10, 11, 13, 8, 15, 7, 3, 14, 8, 7,
2, 12, 7, 11, 6, 8, 5, 14, 8, 4, 4, 6, 6, 8,
2, 2, 14, 11, 1, 6, 11, 5, 3, 2, 7, 11, 11, 16,
12, 6, 4, 7, 16, 3, 13, 10, 12, 13, 14, 7, 6, 12,
2, 4, 8, 8, 13, 12, 5, 14, 6, 14, 3, 11, 10, 7,
13, 3, 12, 6, 10, 6, 4, 6, 13, 14, 8, 6, 6, 2,
4, 10, 12, 6, 9, 10, 12, 14, 13, 11, 11, 11, 6, 14,
8, 13, 10, 13, 7, 13, 13, 2, 13, 12, 12, 10, 8, 13,
10, 15, 8, 10, 7, 11, 15, 9, 10, 10, 2, 8, 13, 8,
10, 7, 6, 8, 14, 3, 6, 16, 6, 14, 12, 9, 8, 15,
8, 8, 8, 14, 13, 2, 7, 15, 2, 10, 8, 8, 12, 2,
12, 15, 5, 10, 13, 7, 8, 3, 6, 13, 10, 10, 12, 6,
12, 4, 1, 8, 3, 8, 10, 6, 8, 9, 4, 9, 7, 3,
6, 6, 7, 4, 8, 13, 13, 6, 6, 8, 7, 8, 12, 2,
3, 7, 12, 2, 2, 7, 8, 10, 8, 9, 7, 6, 14, 1,
9, 10, 4, 4, 2, 16, 2, 3, 2, 9, 11, 2, 7, 8,
8, 11, 14, 6, 12, 14, 2, 2, 6, 5, 7, 2, 12, 10,
6, 12, 3, 14, 3, 6, 1, 13, 3, 9, 5, 5, 6, 6,
13, 1, 12, 6, 6, 14, 7, 8, 12, 16, 16, 6, 8, 13,
12, 6, 12, 4, 3, 16, 3, 3, 9, 3, 11, 3, 13, 8,
10, 6, 7, 6, 2, 8, 3, 9, 8, 2, 4, 12, 3, 2,
6, 4, 10, 6, 7, 12, 10, 2, 10, 7, 11, 15, 12, 7,
11, 14, 8, 3, 11, 8, 11, 2, 7, 8, 10, 8, 7, 14,
10, 14, 15, 7, 12, 12, 3, 10, 8, 7, 8, 6, 4, 7,
8, 10, 15, 6, 1, 2, 7, 4, 2, 11, 8, 12, 4, 8,
6, 2, 12, 11, 7, 8, 2, 6, 12, 2, 6, 13, 10, 4,
8, 2, 14, 10, 4, 4, 7, 6, 10, 10, 7, 12, 7, 8,
3, 3, 3, 10, 6, 8, 10, 3, 3, 3, 10, 12, 8, 8,
3, 2, 4, 10, 7, 3, 14, 12, 8, 2, 8, 10, 9, 2,
11, 2, 7, 1, 12, 6, 4, 6, 10, 14, 6, 9, 6, 11,
3, 16, 15, 3, 7, 14, 3, 6, 11, 11, 8, 7, 2, 6,
8, 2, 2, 2, 1, 10, 11, 2, 8, 7, 14, 13, 7, 3,
6, 2, 16, 13, 7, 14, 8, 10, 5, 6, 10, 2, 14, 8,
8, 11, 9, 7, 6, 2, 12, 7, 8, 10, 10, 12, 11, 6,
10, 6, 13, 6, 7, 7, 2, 7, 10, 8, 6, 4, 2, 2,
6, 8, 10, 4, 4, 10, 12, 10, 11, 2, 1, 6, 12, 3,
7, 6, 13, 7, 10, 8, 3, 4, 12, 6, 7, 8, 8, 5,
14, 4, 10, 6, 2, 2, 10, 14, 6, 8, 16, 10, 14, 2,
6, 10, 12, 8, 10, 16, 6, 16, 8, 12, 2, 2, 3, 14,
8, 5, 13, 10, 4, 10, 4, 8, 7, 2, 12, 5, 14, 7,
10, 7, 8, 7, 14, 4, 3, 3, 3, 7, 7, 6, 11, 14,
6, 3, 6, 1, 4, 10, 8, 8, 2, 13, 11, 2, 10, 8,
6, 7, 3, 8, 6, 6, 2, 12, 10, 10, 7, 4, 7, 15,
7, 7, 4, 6, 9, 2, 2, 8, 6, 4, 6, 4, 5, 11,
6, 8, 4, 6, 4, 8, 2, 14, 6, 4, 6, 8, 11, 2,
4, 1, 4, 7, 4, 8, 2, 8, 8, 12, 16, 13, 12, 10,
2, 6, 10, 10, 11, 11, 8, 8, 12, 2, 6, 4, 9, 8,
8, 13, 2, 12, 7, 7, 12, 11, 8, 7, 10, 14, 7, 10,
2, 7, 2, 6, 10, 3, 10, 8, 8, 10, 2, 6, 8, 2,
6, 13, 7, 8, 6, 16, 8, 4, 2, 4, 5, 7, 6, 8,
7, 14, 8, 10, 4, 10, 2, 6, 6, 6, 6, 2, 9, 6,
8, 8, 6, 8, 10, 12, 10, 9, 2, 3, 15, 16, 8, 11,
14, 10, 6, 12, 3, 6, 10, 13, 4, 8, 7, 6, 8, 11,
3, 1, 10, 16, 8, 6, 2, 1, 4, 14, 6, 3, 16, 7,
10, 2, 2, 14, 14, 10, 8, 14, 8, 10, 6, 10, 10, 15,
8, 12, 3, 3, 16, 13, 11, 6, 11, 14, 2, 16, 3, 10,
4, 10, 11, 8, 3, 14, 14, 10, 12, 6, 3, 9, 2, 7,
2, 8, 8, 8, 13, 6, 9, 7, 11, 11, 9, 14, 2, 3,
5, 16, 12, 8, 10, 10, 10, 8, 9, 9, 3, 5, 8, 13,
6, 14, 8, 7, 8, 7, 8, 3, 15, 7, 6, 2, 6, 10,
8, 2, 6, 2, 6, 8, 3, 9, 8, 8, 16, 9, 4, 10,
4, 10, 4, 16, 9, 10, 3, 6, 6, 4, 14, 8, 8, 4,
2, 10, 4, 3, 7, 7, 10, 4, 8, 6, 8, 10, 10, 12,
10, 4, 9, 13, 4, 8, 1, 7, 12, 6, 10, 3, 7, 7,
2, 8, 6, 7, 6, 6, 4, 15, 4, 10, 8, 12, 11, 8,
6, 14, 10, 9, 11, 11, 6, 11, 3, 6, 9, 2, 2, 8,
4, 6, 9, 2, 7, 7, 4, 11, 10, 2, 6, 3, 3, 4,
2, 6, 6, 10, 6, 10, 10, 8, 12, 3, 6, 7, 7, 12,
2, 4, 6, 8, 7, 3, 4, 14, 15, 4, 8, 11, 10, 2,
3, 8, 3, 5, 6, 8, 7, 8, 7, 7, 7, 8, 12, 8,
10, 1, 8, 14, 7, 2, 7, 8, 6, 2, 7, 3, 2, 8,
8, 10, 2, 9, 8, 6, 5, 7, 1, 6, 6, 2, 10, 11,
13, 8, 15, 7, 3, 14, 8, 7, 2, 12, 7, 11, 6, 8,
5, 14, 8, 4, 4, 6, 6, 8, 2, 2, 14, 11, 1, 6,
11, 5, 3, 2, 7, 11, 11, 16, 12, 6, 4, 7, 16, 3,
13, 10, 12, 13, 14, 7, 6, 12, 2, 4, 8, 8, 13, 12,
5, 14, 6, 14, 3, 11, 10, 7, 13, 3, 12, 6, 10, 6,
4, 6, 13, 14, 8, 6, 6, 2, 4, 10, 12, 6, 9, 10,
12, 14, 13, 11, 11, 11, 6, 14, 8, 13, 10, 13, 7, 13,
13, 2, 13, 12, 12, 10, 8, 13, 10, 15, 8, 10, 7, 11,
15, 9, 10, 10, 2, 8, 13, 8, 10, 7, 6, 6, 7, 8,
8, 2, 11, 16, 14, 2, 8, 10, 10, 8, 8, 6, 4, 8,
14, 8, 1, 6, 8, 3, 2, 3, 3, 10, 6, 2, 7, 16,
4, 2, 10, 7, 12, 16, 6, 2, 12, 14, 5, 6, 8, 13,
6, 14, 13, 9, 10, 8, 16, 9, 4, 10, 8, 5, 15, 8,
8, 12, 14, 4, 7, 15, 10, 2, 3, 6, 12, 10, 4, 13,
16, 10, 11, 9, 6, 14, 8, 11, 12, 1, 7, 6, 8, 13,
6, 3, 6, 8, 13, 8, 5, 4, 7, 8, 10, 8, 8, 7,
4, 11, 9, 10, 10, 8, 4, 2, 15, 2, 11, 9, 1, 14,
10, 13, 14, 14, 5, 7, 9, 8, 8, 15, 12, 15, 2, 2,
7, 6, 7, 10, 16, 1, 5, 8, 12, 4, 6, 8, 14, 10,
8, 8, 6, 14, 6, 10, 3, 2, 13, 1, 2, 2, 1, 10,
16, 10, 8, 8, 11, 7, 2, 16, 8, 2, 10, 6, 2, 3,
13, 10, 4, 5, 11, 15, 2, 9, 13, 10, 14, 10, 6, 12,
14, 7, 10, 15, 8, 4, 4, 8, 15, 2, 15, 7, 2, 4,
6, 2, 11, 3, 10, 12, 8, 7, 6, 1, 8, 4, 11, 16,
8, 8, 6, 4, 9, 15, 2, 2, 6, 7, 10, 10, 4, 6,
8, 1, 13, 10, 4, 8, 6, 2, 11, 6, 7, 10, 4, 12,
4, 10, 10, 11, 2, 8, 11, 7, 8, 16, 13, 6, 12, 7,
6, 3, 9, 2, 3, 4, 14, 3, 1, 3, 8, 2, 12, 13,
5, 1, 2, 8, 10, 8, 16, 12, 6, 6, 5, 14, 12, 6,
3, 12, 11, 5, 8, 6, 2, 16, 4, 6, 8, 2, 7, 12,
6, 4, 8, 6, 7, 16, 15, 12, 8, 6, 12, 14, 10, 3,
6, 4, 6, 3, 2, 11, 2, 8, 15, 4, 8, 7, 6, 4,
2, 7, 8, 13, 14, 2, 4, 6, 9, 11, 2, 10, 6, 6,
10, 7, 2, 4, 3, 12, 8, 11, 10, 7, 16, 10, 13, 7,
6, 12, 6, 10, 8, 12, 14, 8, 10, 12, 2, 10, 6, 11,
6, 2, 10, 3, 2, 14, 8, 4, 8, 2, 2, 5, 8, 16,
8, 7, 12, 4, 5, 6, 2, 8, 4, 7, 14, 7, 8, 3,
3, 10, 6, 8, 8, 2, 10, 7, 2, 3, 6, 13, 13, 3,
2, 11, 8, 8, 8, 10, 6, 12, 4, 12, 3, 6, 10, 11,
2, 3, 13, 14, 8, 2, 7, 9, 14, 5, 12, 10, 13, 4,
10, 3, 7, 6, 8, 8, 2, 9, 6, 10, 4, 6, 6, 16,
6, 6, 2, 3, 5, 2, 1, 13, 9, 2, 6, 5, 4, 1,
12, 8, 7, 14, 13, 13, 10, 16, 2, 6, 12, 7, 7, 7,
12, 12, 2, 7, 13, 6, 4, 12, 8, 11, 2, 6, 7, 8,
8, 12, 7, 13, 10, 2, 9, 10, 15, 9, 12, 13, 15, 6,
9, 7, 8, 16, 14, 11, 14, 14, 15, 8, 5, 16, 12, 11,
6, 8, 12, 16, 7, 5, 3, 5, 15, 5, 1, 2, 6, 12,
15, 6, 6, 8, 2, 10, 16, 3, 7, 2, 10, 9, 2, 8,
10, 8, 7, 14, 13, 1, 6, 15, 6, 9, 6, 10, 7, 9,
2, 16, 16, 10, 16, 6, 2, 3, 11, 13, 13, 8, 15, 7,
14, 13, 15, 8, 8, 2, 12, 7, 8, 7, 6, 15, 8, 14,
2, 8, 10, 3, 6, 11, 8, 6, 6, 8, 3, 8, 6, 13,
2, 3, 4, 2, 2, 10, 11, 6, 8, 2, 14, 7, 5, 7,
6, 6, 2, 12, 9, 3, 7, 7, 2, 14, 3, 14, 2, 10,
8, 7, 15, 6, 14, 15, 7, 6, 2, 4, 10, 2, 2, 6,
10, 3, 12, 7, 8, 7, 7, 10, 6, 6, 6, 10, 3, 8,
3, 11, 6, 15, 8, 8, 3, 16, 6, 15, 9, 2, 2, 10,
2, 3, 13, 13, 10, 15, 15, 2, 11, 10, 2, 2, 7, 10,
8, 7, 6, 10, 10, 14, 7, 14, 8, 12, 15, 10, 15, 10,
4, 10, 6, 6, 6, 2, 7, 12, 7, 7, 8, 7, 2, 3,
6, 10, 6, 15, 2, 3, 16, 7, 8, 3, 15, 2, 2, 14,
14, 6, 6, 2, 7, 7, 11, 3, 10, 9, 15, 10, 14, 12,
13, 10, 11, 11, 6, 6, 14, 12, 13, 10, 6, 1, 4, 8,
8, 7, 2, 16, 6, 10, 7, 8, 13, 1, 4, 12, 6, 16,
1, 6, 1, 6, 8, 16, 6, 2, 9, 1, 1, 2, 2, 10,
4, 4, 12, 4, 10, 16, 10, 12, 3, 11, 3, 2, 12, 10,
6, 7, 11, 7, 4, 3, 8, 10, 3, 3, 13, 13, 2, 12,
7, 11, 7, 3, 2, 6, 2, 14, 7, 7, 8, 7, 2, 14,
7, 14, 11, 2, 6, 10, 7, 7, 6, 8, 11, 10, 2, 6,
13, 11, 9, 3, 7, 2, 11, 6, 14, 4, 3, 8, 7, 7,
6, 6, 8, 6, 2, 12, 12, 7, 7, 6, 16, 7, 10, 4,
7, 6, 1, 3, 8, 8, 7, 6, 13, 6, 13, 6, 2, 3,
3, 10, 10, 6, 9, 8, 7, 15, 6, 3, 8, 10, 2, 5,
7, 12, 6, 6, 5, 8, 2, 8, 2, 13, 14, 10, 2, 6,
11, 11, 12, 6, 6, 8, 6, 7, 12, 11, 8, 8, 6, 12,
10, 13, 3, 10, 8, 9, 8, 3, 7, 8, 16, 3, 4, 6,
11, 7, 8, 6, 8, 6, 12, 2, 10, 2, 3, 3, 8, 4,
3, 7, 7, 10, 10, 6, 10, 2, 8, 6, 8, 4, 11, 8,
11, 1, 10, 1, 8, 6, 13, 2, 8, 5, 10, 11, 10, 8,
12, 6, 11, 10, 2, 15, 7, 11, 6, 7, 8, 16, 6, 10,
8, 12, 9, 14, 7, 16, 4, 10, 4, 3, 4, 7, 10, 3,
6, 11],
"region_full": [1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1,
1, 1, 1, 1, 1, 3, 1, 2, 1, 1, 1, 1, 1, 1, 3, 1, 3, 1,
1, 3, 2, 3, 2, 2, 3, 1, 1, 3, 1, 2, 1, 3, 3, 2, 3, 3,
2, 3, 2, 3, 3, 2, 2, 3, 3, 2, 2, 2, 2, 3, 3, 2, 2, 3,
2, 3, 2, 3, 2, 2, 2, 3, 3, 4, 2, 2, 2, 3, 3, 3, 2, 4,
2, 2, 1, 3, 3, 4, 2, 2, 4, 3, 4, 3, 3, 2, 2, 4, 2, 4,
2, 2, 3, 2, 4, 1, 3, 2, 4, 4, 3, 4, 4, 2, 2, 3, 1, 4,
4, 3, 3, 4, 3, 2, 2, 4, 2, 4, 2, 3, 1, 4, 4, 2, 3, 3,
4, 1, 4, 2, 1, 4, 2, 4, 3, 3, 4, 4, 2, 2, 4, 4, 3, 4,
4, 2, 3, 1, 3, 4, 4, 4, 1, 3, 3, 1, 3, 2, 2, 3, 1, 4,
2, 3, 3, 2, 1, 1, 3, 2, 1, 1, 1, 3, 2, 3, 4, 1, 2, 1,
1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 2, 4, 1, 1, 3, 1, 3,
1, 3, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 3, 1, 1, 3, 1, 2,
1, 2, 3, 2, 2, 4, 1, 3, 1, 1, 1, 1, 1, 1, 2, 2, 3, 1,
2, 3, 3, 2, 1, 1, 1, 1, 4, 2, 1, 1, 2, 2, 1, 2, 3, 1,
2, 1, 1, 2, 4, 3, 2, 1, 3, 1, 2, 1, 1, 3, 2, 1, 2, 2,
2, 2, 1, 2, 2, 3, 2, 3, 2, 1, 3, 1, 2, 1, 2, 2, 2, 2,
2, 3, 2, 2, 2, 2, 3, 2, 2, 2, 2, 2, 2, 1, 3, 2, 3, 2,
3, 2, 2, 1, 2, 2, 2, 3, 2, 4, 2, 2, 2, 2, 2, 1, 3, 1,
2, 2, 2, 3, 3, 3, 3, 3, 3, 2, 2, 2, 3, 2, 2, 3, 2, 3,
2, 2, 1, 3, 3, 3, 2, 2, 3, 1, 2, 3, 3, 2, 2, 2, 2, 2,
3, 2, 3, 3, 3, 3, 3, 1, 3, 3, 2, 3, 3, 1, 2, 4, 2, 3,
3, 3, 3, 3, 2, 2, 3, 3, 4, 3, 4, 4, 3, 3, 3, 3, 3, 4,
4, 2, 4, 2, 4, 2, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 1, 1, 3, 3, 3, 2, 3, 3, 4, 3, 4, 4,
4, 4, 4, 3, 1, 3, 3, 1, 3, 1, 1, 3, 3, 1, 1, 3, 1, 1,
3, 1, 1, 1, 2, 1, 2, 3, 1, 2, 1, 3, 1, 3, 1, 3, 1, 3,
1, 3, 1, 3, 1, 1, 2, 2, 1, 3, 3, 1, 1, 1, 3, 3, 1, 1,
1, 3, 1, 2, 3, 3, 2, 1, 3, 3, 3, 1, 3, 3, 1, 3, 2, 1,
3, 3, 1, 1, 3, 1, 2, 1, 3, 3, 1, 2, 2, 1, 3, 2, 3, 1,
3, 3, 2, 1, 2, 1, 2, 3, 3, 3, 2, 2, 3, 1, 1, 3, 1, 2,
1, 3, 2, 2, 1, 3, 2, 2, 1, 2, 2, 3, 3, 3, 2, 2, 3, 3,
3, 3, 2, 2, 3, 3, 3, 2, 2, 2, 2, 2, 2, 1, 3, 3, 3, 2,
1, 2, 2, 1, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2,
1, 3, 3, 2, 1, 1, 3, 3, 2, 2, 2, 3, 2, 1, 2, 2, 4, 1,
3, 2, 1, 2, 2, 4, 1, 2, 2, 2, 2, 1, 2, 3, 1, 4, 1, 3,
2, 2, 1, 2, 2, 1, 4, 4, 1, 1, 2, 2, 2, 1, 3, 2, 3, 4,
3, 4, 2, 4, 3, 2, 4, 4, 3, 4, 2, 4, 4, 2, 4, 2, 3, 4,
4, 3, 4, 4, 4, 2, 4, 4, 2, 4, 4, 4, 4, 2, 4, 4, 4, 4,
2, 4, 4, 4, 1, 3, 1, 2, 1, 4, 4, 3, 4, 4, 3, 2, 4, 4,
1, 3, 1, 4, 1, 4, 3, 4, 4, 2, 4, 3, 2, 2, 1, 3, 2, 4,
3, 2, 2, 3, 2, 2, 3, 2, 3, 3, 3, 4, 2, 2, 2, 3, 3, 2,
3, 4, 3, 2, 3, 3, 2, 3, 2, 2, 4, 2, 3, 2, 3, 3, 2, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
3, 4, 1, 3, 2, 3, 1, 4, 2, 3, 3, 3, 3, 1, 2, 1, 3, 3,
2, 4, 3, 3, 4, 1, 3, 3, 1, 3, 1, 2, 4, 2, 4, 4, 3, 4,
1, 3, 1, 3, 4, 1, 3, 4, 4, 2, 2, 1, 1, 1, 2, 1, 3, 4,
1, 4, 3, 4, 3, 3, 2, 2, 1, 3, 1, 1, 3, 1, 2, 3, 3, 2,
2, 1, 3, 3, 2, 1, 2, 2, 4, 2, 3, 2, 2, 2, 1, 2, 3, 1,
3, 1, 1, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 3, 3, 3, 1, 3,
4, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2,
2, 1, 1, 2, 3, 2, 1, 3, 1, 2, 3, 2, 2, 1, 3, 1, 2, 1,
1, 2, 2, 1, 2, 1, 3, 2, 2, 1, 1, 3, 3, 1, 2, 3, 2, 3,
3, 2, 3, 1, 2, 2, 2, 2, 3, 1, 1, 2, 2, 1, 2, 1, 2, 2,
2, 2, 3, 1, 1, 2, 2, 3, 3, 3, 2, 3, 1, 3, 3, 3, 3, 1,
3, 2, 1, 1, 3, 1, 2, 1, 3, 1, 2, 3, 3, 1, 3, 2, 3, 2,
1, 1, 2, 2, 1, 3, 1, 1, 3, 2, 2, 3, 1, 3, 2, 2, 1, 1,
1, 1, 2, 2, 1, 3, 2, 2, 1, 1, 3, 3, 1, 3, 3, 3, 1, 3,
2, 3, 2, 3, 1, 1, 2, 1, 2, 2, 2, 1, 3, 1, 2, 1, 1, 3,
2, 2, 2, 1, 2, 3, 2, 2, 2, 1, 2, 3, 3, 3, 3, 3, 3, 1,
1, 2, 2, 3, 2, 3, 2, 3, 3, 2, 1, 2, 3, 4, 3, 1, 2, 1,
2, 3, 3, 3, 3, 1, 2, 3, 3, 3, 1, 2, 3, 2, 1, 2, 2, 2,
2, 3, 2, 2, 1, 3, 2, 1, 2, 3, 4, 3, 3, 2, 2, 1, 2, 1,
1, 2, 3, 2, 3, 1, 3, 1, 3, 3, 3, 2, 2, 1, 3, 2, 1, 3,
2, 2, 2, 2, 2, 3, 2, 3, 2, 3, 3, 3, 1, 2, 3, 2, 3, 3,
2, 1, 3, 2, 3, 1, 1, 2, 3, 2, 1, 3, 1, 3, 3, 2, 3, 1,
3, 1, 1, 3, 3, 3, 3, 3, 2, 3, 2, 3, 3, 2, 1, 2, 3, 4,
3, 3, 3, 3, 3, 2, 2, 3, 3, 1, 1, 4, 2, 3, 2, 2, 3, 3,
3, 2, 3, 3, 3, 2, 1, 3, 3, 2, 3, 2, 2, 3, 3, 2, 2, 2,
2, 2, 2, 3, 4, 3, 3, 4, 2, 3, 3, 2, 4, 4, 3, 4, 4, 4,
3, 2, 4, 4, 4, 2, 4, 4, 4, 3, 3, 3, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 1, 1, 3, 3, 2, 4, 2, 3, 3, 2, 1, 2, 1, 2, 1,
3, 3, 3, 2, 3, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
4, 3, 4, 4, 4, 4, 4, 1, 2, 2, 4, 2, 3, 4, 4, 4, 3, 3,
3, 3, 3, 2, 4, 2, 4, 4, 3, 1, 4, 1, 3, 2, 4, 3, 3, 4,
3, 2, 1, 1, 3, 3, 3, 2, 3, 3, 4, 3, 4, 4, 4, 4, 4, 3,
1, 3, 3, 1, 3, 1, 1, 3, 3, 1, 1, 3, 1, 1, 3, 1, 1, 1,
2, 1, 2, 3, 1, 2, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3, 1, 3,
1, 1, 2, 2, 1, 3, 3, 1, 1, 1, 3, 3, 1, 1, 1, 3, 1, 2,
3, 3, 2, 1, 3, 3, 3, 1, 3, 3, 1, 3, 2, 1, 3, 3, 1, 1,
3, 1, 2, 1, 3, 3, 1, 2, 2, 1, 3, 2, 3, 1, 3, 3, 2, 1,
2, 1, 2, 3, 3, 3, 2, 2, 3, 1, 1, 3, 1, 2, 1, 3, 2, 2,
1, 3, 2, 2, 1, 2, 2, 3, 3, 3, 2, 2, 3, 3, 3, 3, 2, 2,
3, 3, 3, 2, 2, 2, 2, 2, 2, 1, 3, 3, 3, 2, 1, 2, 2, 1,
3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 1, 3, 3, 2,
1, 1, 3, 3, 2, 2, 2, 3, 2, 1, 2, 2, 4, 1, 3, 2, 1, 2,
2, 4, 1, 2, 2, 2, 2, 1, 2, 3, 1, 4, 1, 3, 2, 2, 1, 2,
2, 1, 4, 4, 1, 1, 2, 2, 2, 1, 3, 2, 3, 4, 3, 4, 2, 4,
3, 2, 4, 4, 3, 4, 2, 4, 4, 2, 4, 2, 3, 4, 4, 3, 4, 4,
4, 2, 4, 4, 2, 4, 4, 4, 4, 2, 4, 4, 4, 4, 2, 4, 4, 4,
1, 3, 1, 2, 1, 4, 4, 3, 4, 4, 3, 2, 4, 4, 1, 3, 1, 4,
1, 4, 3, 4, 4, 2, 4, 3, 2, 2, 1, 3, 2, 4, 3, 2, 2, 3,
2, 2, 3, 2, 3, 3, 3, 4, 2, 2, 2, 3, 3, 2, 3, 4, 3, 2,
3, 3, 2, 3, 2, 2, 4, 2, 3, 2, 3, 3, 2, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 3,
3, 2, 2, 1, 3, 1, 1, 3, 1, 2, 3, 3, 2, 2, 1, 3, 3, 2,
1, 2, 2, 4, 2, 3, 2, 2, 2, 1, 2, 3, 1, 3, 1, 1, 3, 3,
3, 3, 1, 1, 1, 1, 1, 1, 3, 3, 3, 1, 3, 4, 2, 2, 2, 2,
2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 3,
2, 1, 3, 1, 2, 3, 2, 2, 1, 3, 1, 2, 1, 1, 2, 2, 1, 2,
1, 3, 2, 2, 1, 1, 3, 3, 1, 2, 3, 2, 3, 3, 2, 3, 1, 2,
2, 2, 2, 3, 1, 1, 2, 2, 1, 2, 1, 2, 2, 2, 2, 3, 1, 1,
2, 2, 3, 3, 3, 2, 3, 1, 3, 3, 3, 3, 1, 3, 2, 1, 1, 3,
1, 2, 1, 3, 1, 2, 3, 3, 1, 3, 2, 3, 2, 1, 1, 2, 2, 1,
3, 1, 1, 3, 2, 2, 3, 1, 3, 2, 2, 1, 1, 1, 1, 2, 2, 1,
3, 2, 2, 1, 1, 3, 3, 1, 3, 3, 3, 1, 3, 2, 3, 2, 3, 1,
1, 2, 1, 2, 2, 2, 1, 3, 1, 2, 1, 1, 3, 2, 2, 2, 1, 2,
3, 2, 2, 2, 1, 2, 3, 3, 3, 3, 3, 3, 1, 1, 2, 2, 3, 2,
3, 2, 3, 3, 2, 1, 2, 3, 4, 3, 1, 2, 1, 2, 3, 3, 3, 3,
1, 2, 3, 3, 3, 1, 2, 3, 2, 1, 2, 2, 2, 2, 3, 2, 2, 1,
3, 2, 1, 2, 3, 4, 3, 3, 2, 2, 1, 2, 1, 1, 2, 3, 2, 3,
1, 3, 1, 3, 3, 3, 2, 2, 1, 3, 2, 1, 3, 2, 2, 2, 2, 2,
3, 2, 3, 2, 3, 3, 3, 1, 2, 3, 2, 3, 3, 2, 1, 3, 2, 3,
1, 1, 2, 3, 2, 1, 3, 1, 3, 3, 2, 3, 1, 3, 1, 1, 3, 3,
3, 3, 3, 2, 3, 2, 3, 3, 2, 1, 2, 3, 4, 3, 3, 3, 3, 3,
2, 2, 3, 3, 1, 1, 4, 2, 3, 2, 2, 3, 3, 3, 2, 3, 3, 3,
2, 1, 3, 3, 2, 3, 2, 2, 3, 3, 2, 2, 2, 2, 2, 2, 3, 4,
3, 3, 4, 2, 3, 3, 2, 4, 4, 3, 4, 4, 4, 3, 2, 4, 4, 4,
2, 4, 4, 4, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1,
3, 3, 2, 4, 2, 3, 3, 2, 1, 2, 1, 2, 1, 3, 3, 3, 2, 3,
1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 4, 4, 4,
4, 4, 1, 2, 2, 4, 2, 3, 4, 4, 4, 3, 3, 3, 3, 3, 2, 4,
2, 4, 4, 3, 1, 4, 1, 3, 2, 4, 3, 3, 4, 3, 2, 4, 2, 1,
2, 1, 2, 1, 3, 4, 1, 1, 3, 1, 1, 3, 1, 1, 4, 2, 3, 3,
1, 1, 3, 3, 3, 1, 1, 1, 1, 1, 2, 1, 3, 1, 4, 1, 1, 1,
1, 3, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 3, 1, 1, 2,
2, 2, 1, 1, 3, 1, 1, 1, 1, 2, 1, 1, 1, 1, 3, 1, 1, 1,
1, 2, 2, 3, 1, 2, 3, 2, 4, 3, 3, 2, 1, 3, 3, 3, 2, 4,
2, 2, 2, 2, 1, 4, 3, 1, 2, 1, 2, 3, 4, 1, 1, 2, 2, 2,
3, 3, 2, 1, 2, 2, 4, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1,
3, 3, 3, 3, 2, 4, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 4, 1, 4, 2, 1, 1, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 1, 3, 4, 3, 2, 3, 2, 2, 2, 1, 4, 4, 2, 3, 3,
2, 3, 1, 1, 3, 2, 1, 2, 4, 4, 1, 1, 2, 2, 3, 3, 1, 3,
1, 3, 2, 4, 1, 1, 2, 3, 1, 1, 3, 2, 3, 4, 3, 1, 2, 2,
3, 2, 3, 3, 1, 1, 1, 2, 2, 1, 4, 4, 2, 3, 3, 3, 1, 2,
2, 2, 3, 3, 3, 1, 4, 2, 2, 2, 1, 2, 1, 1, 3, 1, 1, 1,
4, 2, 2, 4, 2, 2, 1, 2, 2, 3, 3, 4, 1, 3, 3, 3, 1, 2,
2, 3, 1, 3, 4, 3, 3, 4, 3, 4, 3, 2, 4, 2, 3, 2, 2, 4,
2, 1, 2, 2, 4, 2, 4, 3, 2, 1, 2, 2, 1, 1, 1, 2, 2, 2,
2, 2, 2, 1, 1, 3, 3, 2, 4, 1, 3, 2, 3, 3, 1, 1, 3, 3,
1, 3, 3, 4, 3, 3, 3, 2, 2, 2, 3, 1, 2, 3, 3, 5, 3, 3,
2, 2, 2, 2, 2, 3, 2, 2, 1, 2, 2, 2, 2, 4, 4, 3, 3, 3,
3, 2, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 4, 4, 4, 4, 4,
4, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 3, 3, 3, 3, 1,
1, 1, 1, 1, 1, 3, 3, 3, 1, 3, 4, 2, 2, 2, 2, 2, 1, 1,
1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 3, 2, 1, 3,
1, 2, 3, 2, 2, 1, 3, 1, 2, 1, 1, 2, 2, 1, 2, 1, 3, 2,
2, 1, 1, 3, 3, 1, 2, 3, 2, 3, 3, 2, 3, 1, 2, 2, 2, 2,
3, 1, 1, 2, 2, 1, 2, 1, 2, 2, 2, 2, 3, 1, 1, 2, 2, 3,
3, 3, 2, 3, 1, 3, 3, 3, 3, 1, 3, 2, 1, 1, 3, 1, 2, 1,
3, 1, 2, 3, 3, 1, 3, 2, 3, 2, 1, 1, 2, 2, 1, 3, 1, 1,
3, 2, 2, 3, 1, 3, 2, 2, 1, 1, 1, 1, 2, 2, 1, 3, 2, 2,
1, 1, 3, 3, 1, 3, 3, 3, 1, 3, 2, 3, 2, 3, 1, 1, 2, 1,
2, 2, 2, 1, 3, 1, 2, 1, 1, 3, 2, 2, 2, 1, 2, 3, 2, 2,
2, 1, 2, 3, 3, 3, 3, 3, 3, 1, 1, 2, 2, 3, 2, 3, 2, 3,
3, 2, 1, 2, 3, 4, 3, 1, 2, 1, 2, 3, 3, 3, 3, 1, 2, 3,
3, 3, 1, 2, 3, 2, 1, 2, 2, 2, 2, 3, 2, 2, 1, 3, 2, 1,
2, 3, 4, 3, 3, 2, 2, 1, 2, 1, 1, 2, 3, 2, 3, 1, 3, 1,
3, 3, 3, 2, 2, 1, 3, 2, 1, 3, 2, 2, 2, 2, 2, 3, 2, 3,
2, 3, 3, 3, 1, 2, 3, 2, 3, 3, 2, 1, 3, 2, 3, 1, 1, 2,
3, 2, 1, 3, 1, 3, 3, 2, 3, 1, 3, 1, 1, 3, 3, 3, 3, 3,
2, 3, 2, 3, 3, 2, 1, 2, 3, 4, 3, 3, 3, 3, 3, 2, 2, 3,
3, 1, 1, 4, 2, 3, 2, 2, 3, 3, 3, 2, 3, 3, 3, 2, 1, 3,
3, 2, 3, 2, 2, 3, 3, 2, 2, 2, 2, 2, 2, 3, 4, 3, 3, 4,
2, 3, 3, 2, 4, 4, 3, 4, 4, 4, 3, 2, 4, 4, 4, 2, 4, 4,
4, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 3, 3, 2,
4, 2, 3, 3, 2, 1, 2, 1, 2, 1, 3, 3, 3, 2, 3, 1, 1, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 4, 4, 4, 4, 4, 1,
2, 2, 4, 2, 3, 4, 4, 4, 3, 3, 3, 3, 3, 2, 4, 2, 4, 4,
3, 1, 4, 1, 3, 2, 4, 3, 3, 4, 3, 2, 4, 2, 1, 2, 1, 2,
1, 3, 4, 1, 1, 3, 1, 1, 3, 1, 1, 4, 2, 3, 3, 1, 1, 3,
3, 3, 1, 1, 1, 1, 1, 2, 1, 3, 1, 4, 1, 1, 1, 1, 3, 2,
1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 3, 1, 1, 2, 2, 2, 1,
1, 3, 1, 1, 1, 1, 2, 1, 1, 1, 1, 3, 1, 1, 1, 1, 2, 2,
3, 1, 2, 3, 2, 4, 3, 3, 2, 1, 3, 3, 3, 2, 4, 2, 2, 2,
2, 1, 4, 3, 1, 2, 1, 2, 3, 4, 1, 1, 2, 2, 2, 3, 3, 2,
1, 2, 2, 4, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 3, 3, 3,
3, 2, 4, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4,
1, 4, 2, 1, 1, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 3, 4, 3, 2, 3, 2, 2, 2, 1, 4, 4, 2, 3, 3, 2, 3, 1,
1, 3, 2, 1, 2, 4, 4, 1, 1, 2, 2, 3, 3, 1, 3, 1, 3, 2,
4, 1, 1, 2, 3, 1, 1, 3, 2, 3, 4, 3, 1, 2, 2, 3, 2, 3,
3, 1, 1, 1, 2, 2, 1, 4, 4, 2, 3, 3, 3, 1, 2, 2, 2, 3,
3, 3, 1, 4, 2, 2, 2, 1, 2, 1, 1, 3, 1, 1, 1, 4, 2, 2,
4, 2, 2, 1, 2, 2, 3, 3, 4, 1, 3, 3, 3, 1, 2, 2, 3, 1,
3, 4, 3, 3, 4, 3, 4, 3, 2, 4, 2, 3, 2, 2, 4, 2, 1, 2,
2, 4, 2, 4, 3, 2, 1, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2,
1, 1, 3, 3, 2, 4, 1, 3, 2, 3, 3, 1, 1, 3, 3, 1, 3, 3,
4, 3, 3, 3, 2, 2, 2, 3, 1, 2, 3, 3, 5, 3, 3, 2, 2, 2,
2, 2, 3, 2, 2, 1, 2, 2, 2, 2, 4, 4, 3, 3, 3, 3, 2, 4,
4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4,
4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4,
4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 1, 3, 3, 3, 3, 3, 3, 1,
1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 3, 1, 3, 3, 3, 3, 3, 3,
2, 3, 4, 4, 4, 2, 4, 4, 2, 4, 3, 3, 1, 3, 1, 3, 1, 3,
2, 2, 2, 2, 2, 2, 2, 1, 1, 3, 3, 2, 3, 3, 1, 3, 3, 4,
1, 2, 2, 2, 2, 3, 1, 3, 2, 3, 3, 1, 1, 1, 1, 3, 4, 4,
1, 2, 2, 2, 2, 1, 1, 2, 4, 3, 3, 3, 3, 3, 3, 1, 1, 2,
2, 2, 2, 1, 1, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3,
1, 1, 1, 3, 1, 2, 3, 3, 3, 3, 2, 3, 2, 3, 1, 4, 4, 4,
4, 4, 3, 3, 1, 3, 3, 3, 2, 1, 3, 3, 3, 2, 4, 1, 3, 2,
1, 2, 2, 4, 3, 4, 3, 3, 3, 1, 4, 1, 2, 1, 2, 3, 2, 3,
3, 3, 3, 3, 1, 1, 2, 4, 3, 3, 1, 2, 2, 2, 2, 3, 1, 1,
1, 3, 1, 3, 1, 2, 2, 2, 2, 3, 1, 4, 2, 2, 2, 1, 1, 1,
1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 4, 1, 2, 3, 2,
1, 1, 1, 2, 2, 3, 1, 1, 2, 1, 1, 3, 3, 3, 1, 1, 2, 4,
2, 1, 3, 1, 2, 2, 2, 3, 1, 4, 2, 2, 2, 2, 1, 1, 3, 3,
3, 3, 1, 3, 1, 4, 3, 3, 2, 2, 2, 1, 2, 3, 3, 1, 3, 4,
4, 4, 4, 4, 4, 3, 3, 4, 4, 4, 3, 4, 3, 3, 3, 2, 1, 3,
3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 4, 2, 3, 3, 1, 3, 2,
4, 3, 2, 3, 2, 2, 2, 2, 3, 1, 2, 3, 1, 1, 3, 3, 1, 2,
4, 4, 2, 2, 4, 1, 3, 3, 2, 2, 2, 3, 2, 3, 3, 3, 3, 3,
4, 4, 4, 4, 2, 4, 2, 3, 3, 3, 3, 3, 2, 3, 3, 3, 1, 2,
2, 1, 1, 2, 1, 1, 2, 2, 3, 5, 1, 3, 1, 3, 3, 1, 4, 2,
1, 3, 1, 2, 2, 3, 3, 3, 3, 3, 3, 1, 2, 1, 1, 2, 3, 2,
3, 1, 2, 3, 2, 3, 3, 3, 4, 4, 4, 4, 4, 4, 2, 2, 2, 1,
1, 2, 4, 4, 1, 4, 4, 4, 4, 4, 4, 2, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 2, 1, 2, 1, 2,
1, 3, 4, 1, 1, 3, 1, 1, 3, 1, 1, 4, 2, 3, 3, 1, 1, 3,
3, 3, 1, 1, 1, 1, 1, 2, 1, 3, 1, 4, 1, 1, 1, 1, 3, 2,
1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 3, 1, 1, 2, 2, 2, 1,
1, 3, 1, 1, 1, 1, 2, 1, 1, 1, 1, 3, 1, 1, 1, 1, 2, 2,
3, 1, 2, 3, 2, 4, 3, 3, 2, 1, 3, 3, 3, 2, 4, 2, 2, 2,
2, 1, 4, 3, 1, 2, 1, 2, 3, 4, 1, 1, 2, 2, 2, 3, 3, 2,
1, 2, 2, 4, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 3, 3, 3,
3, 2, 4, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4,
1, 4, 2, 1, 1, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 3, 4, 3, 2, 3, 2, 2, 2, 1, 4, 4, 2, 3, 3, 2, 3, 1,
1, 3, 2, 1, 2, 4, 4, 1, 1, 2, 2, 3, 3, 1, 3, 1, 3, 2,
4, 1, 1, 2, 3, 1, 1, 3, 2, 3, 4, 3, 1, 2, 2, 3, 2, 3,
3, 1, 1, 1, 2, 2, 1, 4, 4, 2, 3, 3, 3, 1, 2, 2, 2, 3,
3, 3, 1, 4, 2, 2, 2, 1, 2, 1, 1, 3, 1, 1, 1, 4, 2, 2,
4, 2, 2, 1, 2, 2, 3, 3, 4, 1, 3, 3, 3, 1, 2, 2, 3, 1,
3, 4, 3, 3, 4, 3, 4, 3, 2, 4, 2, 3, 2, 2, 4, 2, 1, 2,
2, 4, 2, 4, 3, 2, 1, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2,
1, 1, 3, 3, 2, 4, 1, 3, 2, 3, 3, 1, 1, 3, 3, 1, 3, 3,
4, 3, 3, 3, 2, 2, 2, 3, 1, 2, 3, 3, 5, 3, 3, 2, 2, 2,
2, 2, 3, 2, 2, 1, 2, 2, 2, 2, 4, 4, 3, 3, 3, 3, 2, 4,
4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4,
4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4,
4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 1, 3, 3, 3, 3, 3, 3, 1,
1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 3, 1, 3, 3, 3, 3, 3, 3,
2, 3, 4, 4, 4, 2, 4, 4, 2, 4, 3, 3, 1, 3, 1, 3, 1, 3,
2, 2, 2, 2, 2, 2, 2, 1, 1, 3, 3, 2, 3, 3, 1, 3, 3, 4,
1, 2, 2, 2, 2, 2, 3, 1, 3, 2, 3, 3, 1, 1, 1, 1, 3, 4,
4, 1, 2, 2, 2, 2, 1, 1, 2, 4, 3, 3, 3, 3, 3, 3, 1, 1,
2, 2, 2, 2, 1, 1, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 2,
3, 1, 1, 1, 3, 1, 2, 3, 3, 3, 3, 2, 3, 2, 3, 1, 4, 4,
4, 4, 4, 3, 3, 1, 3, 3, 3, 2, 1, 3, 3, 3, 2, 4, 1, 3,
2, 1, 2, 2, 4, 3, 4, 3, 3, 3, 1, 4, 1, 2, 1, 2, 3, 2,
3, 3, 3, 3, 3, 1, 1, 2, 4, 3, 3, 1, 2, 2, 2, 2, 3, 1,
1, 1, 3, 1, 3, 1, 2, 2, 2, 2, 3, 1, 4, 2, 2, 2, 1, 1,
1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 4, 1, 2, 3,
2, 1, 1, 1, 2, 2, 3, 1, 1, 2, 1, 1, 3, 3, 3, 1, 1, 2,
4, 2, 1, 3, 1, 2, 2, 2, 3, 1, 4, 2, 2, 2, 2, 1, 1, 3,
3, 3, 3, 1, 3, 1, 4, 3, 3, 2, 2, 2, 1, 2, 3, 3, 1, 3,
4, 4, 4, 4, 4, 4, 3, 3, 4, 4, 4, 3, 4, 3, 3, 3, 2, 1,
3, 3, 3, 1, 3, 3, 3, 3, 3, 1, 1, 1, 1, 4, 2, 3, 3, 1,
3, 2, 4, 3, 2, 3, 2, 2, 2, 2, 3, 1, 2, 3, 1, 1, 3, 3,
1, 2, 4, 4, 2, 2, 2, 4, 1, 3, 3, 2, 2, 2, 3, 2, 3, 3,
3, 3, 3, 4, 4, 4, 4, 2, 4, 2, 3, 3, 3, 3, 3, 2, 3, 3,
3, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 3, 5, 1, 3, 1, 3, 3,
1, 4, 2, 1, 3, 1, 2, 2, 3, 3, 3, 3, 3, 3, 1, 2, 1, 1,
2, 3, 2, 3, 1, 2, 3, 2, 3, 3, 3, 4, 4, 4, 4, 4, 4, 2,
2, 2, 1, 1, 2, 4, 4, 1, 4, 4, 4, 4, 4, 4, 2, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 1, 1, 1,
1, 1, 1, 4, 2, 3, 3, 3, 2, 3, 2, 2, 2, 3, 3, 3, 3, 3,
2, 3, 3, 3, 3, 2, 3, 2, 1, 4, 3, 3, 4, 3, 4, 3, 4, 3,
3, 1, 1, 2, 2, 1, 3, 4, 1, 1, 1, 1, 3, 3, 3, 3, 1, 1,
1, 1, 1, 2, 1, 2, 1, 1, 4, 1, 1, 1, 3, 3, 3, 3, 3, 3,
3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 3, 3, 4,
3, 4, 2, 3, 4, 2, 1, 1, 3, 3, 3, 1, 3, 2, 2, 1, 1, 1,
1, 1, 1, 1, 3, 3, 3, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2,
2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2,
1, 2, 1, 2, 2, 3, 3, 2, 2, 1, 3, 1, 2, 3, 1, 3, 3, 3,
3, 3, 3, 3, 3, 3, 2, 3, 3, 1, 3, 2, 2, 2, 3, 3, 2, 3,
2, 1, 2, 2, 2, 1, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 1, 1,
2, 2, 2, 2, 3, 1, 3, 1, 1, 1, 3, 1, 1, 2, 4, 2, 2, 3,
3, 1, 3, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1,
1, 1, 1, 3, 2, 1, 2, 2, 2, 2, 2, 2, 3, 1, 1, 3, 3, 3,
1, 3, 2, 3, 3, 4, 3, 4, 3, 3, 3, 1, 1, 2, 2, 3, 3, 3,
2, 2, 2, 2, 1, 2, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3, 3, 2,
3, 3, 3, 1, 1, 2, 2, 1, 2, 2, 3, 3, 1, 3, 1, 2, 3, 2,
3, 3, 1, 2, 3, 1, 1, 4, 3, 4, 3, 4, 3, 4, 3, 3, 3, 3,
3, 1, 1, 3, 3, 2, 2, 1, 1, 1, 3, 3, 2, 2, 3, 3, 1, 1,
2, 2, 2, 3, 3, 3, 1, 2, 2, 2, 3, 1, 1, 1, 2, 2, 2, 3,
3, 3, 2, 2, 2, 3, 2, 1, 2, 2, 2, 2, 4, 4, 4, 4, 3, 4,
1, 4, 4, 4, 2, 2, 2, 3, 2, 2, 2, 4, 2, 3, 3, 3, 3, 4,
2, 2, 4, 2, 1, 2, 3, 2, 3, 1, 3, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 3, 2, 4, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4,
2, 2, 4, 4, 4, 4, 2, 4, 4, 4, 2, 4, 4, 4, 4, 4, 4, 1,
4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 1, 4, 3, 4,
1, 4, 1, 4, 4, 1, 4, 4, 4, 4, 3, 2, 1, 1, 1, 1, 1, 1,
4, 2, 3, 3, 3, 2, 3, 2, 2, 2, 3, 3, 3, 3, 3, 2, 3, 3,
3, 3, 2, 3, 2, 1, 4, 3, 3, 4, 3, 4, 3, 4, 3, 3, 1, 1,
2, 2, 1, 3, 4, 1, 1, 1, 1, 3, 3, 3, 3, 1, 1, 1, 1, 1,
2, 1, 2, 1, 1, 4, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3,
2, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 3, 3, 4, 3, 4, 2,
3, 4, 2, 1, 1, 3, 3, 3, 1, 3, 2, 2, 1, 1, 1, 1, 1, 1,
1, 3, 3, 3, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 2,
2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 1, 2, 1,
2, 2, 3, 3, 2, 2, 1, 3, 1, 2, 3, 1, 3, 3, 3, 3, 3, 3,
3, 3, 3, 2, 3, 3, 1, 3, 2, 2, 2, 3, 3, 2, 3, 2, 1, 2,
2, 2, 1, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 1, 1, 2, 2, 2,
2, 3, 1, 3, 1, 1, 1, 3, 1, 1, 2, 4, 2, 2, 3, 3, 1, 3,
1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1,
3, 2, 1, 2, 2, 2, 2, 2, 2, 3, 1, 1, 3, 3, 3, 1, 3, 2,
3, 3, 4, 3, 4, 3, 3, 3, 1, 1, 2, 2, 3, 3, 3, 2, 2, 2,
2, 1, 2, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3, 3, 2, 3, 3, 3,
1, 1, 2, 2, 1, 2, 2, 3, 3, 1, 3, 1, 2, 3, 2, 3, 3, 1,
2, 3, 1, 1, 4, 3, 4, 3, 4, 3, 4, 3, 3, 3, 3, 3, 1, 1,
3, 3, 2, 2, 1, 1, 1, 3, 3, 2, 2, 3, 3, 1, 1, 2, 2, 2,
3, 3, 3, 1, 2, 2, 2, 3, 1, 1, 1, 2, 2, 2, 3, 3, 3, 2,
2, 2, 3, 2, 1, 2, 2, 2, 2, 4, 4, 4, 4, 3, 4, 1, 4, 4,
4, 2, 2, 2, 3, 2, 2, 2, 4, 2, 3, 3, 3, 3, 4, 2, 2, 4,
2, 1, 2, 3, 2, 3, 1, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 3, 2, 4, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 2, 2, 4,
4, 4, 4, 2, 4, 4, 4, 2, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4,
4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 1, 4, 3, 4, 1, 4, 1,
4, 4, 1, 4, 4, 4, 4, 3, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1,
1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2,
1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 1,
2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 2,
2, 2, 5, 2, 1, 2, 3, 3, 1, 2, 2, 2, 2, 2, 2, 2, 3, 2,
2, 2, 3, 2, 3, 3, 3, 2, 3, 3, 2, 3, 2, 2, 2, 3, 3, 2,
3, 2, 3, 2, 2, 3, 2, 2, 1, 3, 3, 2, 1, 2, 3, 3, 2, 3,
3, 3, 2, 3, 3, 3, 3, 2, 3, 3, 3, 1, 2, 3, 2, 3, 3, 2,
3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 2, 3, 3,
3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 2, 3, 3, 3, 3, 3, 1, 3, 2, 3, 3, 3, 3, 3, 3, 1, 3,
3, 3, 4, 3, 2, 3, 4, 4, 1, 1, 3, 3, 3, 3, 4, 3, 3, 3,
4, 3, 4, 3, 3, 3, 3, 3, 3, 4, 4, 1, 4, 4, 3, 3, 3, 3,
4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4, 3, 3, 4, 3, 4, 4, 4,
4, 4, 4, 4, 4, 4, 2, 3, 2, 3, 3, 4, 4, 2, 2, 2, 2, 3,
4, 4, 4, 3, 4, 3, 4, 4, 4, 3, 3, 4, 3, 3, 4, 4, 4, 4,
4, 4, 3, 4, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 2, 4, 4,
4, 4, 4, 4, 4, 3, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 1, 1, 1,
1, 1, 1, 1, 1, 3, 1, 1, 1, 3, 1, 3, 1, 1, 3, 1, 3, 1,
3, 3, 3, 2, 3, 1, 3, 3, 1, 2, 1, 3, 2, 2, 2, 3, 3, 3,
1, 1, 2, 2, 3, 3, 2, 3, 3, 2, 3, 3, 2, 3, 3, 3, 3, 2,
3, 2, 3, 3, 2, 3, 2, 2, 3, 3, 3, 4, 4, 2, 3, 3, 3, 2,
3, 4, 4, 3, 3, 4, 3, 4, 2, 4, 4, 2, 3, 4, 2, 3, 3, 5,
4, 2, 3, 2, 1, 3, 2, 1, 4, 4, 3, 2, 2, 2, 2, 3, 4, 4,
3, 4, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 3, 4,
3, 3, 4, 4, 4, 4, 3, 3, 1, 3, 3, 1, 3, 1, 3, 3, 1, 2,
3, 3, 2, 3, 2, 1, 3, 2, 3, 1, 4, 1, 4, 3, 1, 1, 1, 3,
1, 1, 3, 1, 1, 3, 1, 1, 3, 3, 4, 4, 3, 1, 1, 3, 1, 4,
1, 1, 1, 1, 3, 1, 1, 2, 3, 3, 4, 3, 3, 1, 2, 1, 3, 3,
2, 1, 3, 1, 4, 1, 3, 3, 3, 3, 3, 2, 3, 4, 2, 2, 3, 2,
2, 2, 2, 2, 4, 2, 2, 2, 3, 3, 2, 2, 3, 4, 1, 2, 3, 3,
1, 2, 4, 3, 3, 1, 3, 4, 4, 3, 2, 2, 3, 1, 2, 3, 2, 2,
2, 4, 3, 3, 2, 3, 1, 1, 3, 2, 4, 1, 3, 2, 2, 2, 3, 3,
3, 1, 2, 2, 3, 2, 1, 1, 2, 4, 3, 3, 1, 2, 4, 4, 1, 2,
3, 3, 2, 1, 4, 2, 2, 1, 3, 2, 2, 2, 3, 3, 2, 1, 1, 2,
2, 2, 2, 2, 2, 2, 2, 1, 2, 3, 1, 2, 2, 3, 4, 1, 3, 2,
2, 2, 2, 2, 2, 3, 1, 2, 3, 4, 4, 2, 2, 4, 3, 2, 3, 1,
4, 4, 2, 1, 4, 1, 3, 2, 2, 3, 4, 2, 4, 3, 3, 1, 2, 3,
3, 1, 4, 2, 3, 3, 1, 3, 3, 2, 1, 4, 4, 1, 4, 4, 3, 3,
2, 1, 1, 4, 3, 2, 3, 1, 4, 3, 4, 2, 3, 2, 1, 4, 2, 2,
3, 4, 3, 3, 3, 2, 2, 4, 2, 4, 3, 3, 4, 3, 4, 3, 2, 2,
3, 3, 3, 2, 2, 1, 3, 3, 1, 1, 1, 3, 4, 2, 2, 3, 3, 2,
1, 3, 3, 3, 3, 1, 3, 4, 3, 2, 2, 2, 3, 4, 1, 2, 4, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 3, 1, 3, 1, 3, 3, 3, 1, 3, 1, 3, 1,
3, 1, 3, 2, 3, 2, 3, 3, 2, 2, 3, 2, 1, 2, 2, 2, 2, 1,
2, 3, 3, 2, 2, 2, 2, 3, 3, 2, 2, 3, 3, 2, 3, 4, 2, 2,
3, 3, 3, 4, 4, 2, 4, 2, 4, 2, 3, 1, 3, 4, 2, 4, 4, 4,
2, 3, 4, 4, 3, 3, 4, 4, 2, 3, 3, 2, 1, 4, 4, 4, 1, 2,
4, 2, 2, 3, 3, 4, 1, 2, 3, 4, 3, 1, 1, 4, 1, 4, 2, 2,
4, 2, 3, 3, 3, 3, 4, 4, 3, 3, 1, 4, 1, 3, 3, 4, 2, 3,
1, 4, 2, 2, 2, 1, 3, 4, 2, 2, 4, 4, 2, 2, 1, 4, 2, 1,
3, 3, 3, 1, 2, 4, 2, 4, 3, 2, 3, 4, 4, 3, 1, 4, 2, 4,
3, 1, 1, 1, 4, 1, 1, 2, 2, 4, 4, 3, 3, 1, 4, 1, 4, 2,
2, 1, 2, 2, 1, 1, 3, 4, 4, 3, 1, 3, 3, 4, 3, 4, 3, 4,
3, 4, 3, 3, 2, 4, 4, 3, 1, 3, 3, 1, 1, 2, 2, 1, 2, 2,
1, 1, 3, 2, 2, 2, 1, 2, 2, 3, 2, 3, 3, 1, 4, 2, 2, 1,
1, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 2, 1, 1, 3, 2, 3, 2,
1, 1, 3, 3, 3, 2, 1, 1, 3, 1, 3, 1, 1, 3, 3, 1, 2, 4,
2, 1, 1, 3, 3, 3, 3, 2, 3, 1, 1, 3, 3, 1, 3, 1, 3, 1,
3, 3, 1, 3, 3, 1, 2, 2, 2, 3, 1, 2, 2, 1, 3, 3, 4, 3,
2, 3, 1, 2, 3, 2, 4, 1, 3, 3, 1, 4, 2, 2, 1, 3, 2, 2,
2, 2, 4, 4, 2, 4, 1, 1, 3, 2, 3, 2, 2, 1, 4, 2, 2, 2,
4, 1, 3, 1, 3, 2, 2, 3, 1, 2, 3, 1, 2, 1, 1, 2, 1, 3,
3, 2, 3, 1, 2, 1, 3, 2, 1, 3, 3, 2, 3, 4, 3, 3, 2, 2,
3, 3, 3, 2, 3, 4, 1, 1, 4, 3, 4, 1, 2, 3, 2, 4, 3, 3,
4, 4, 1, 3, 4, 4, 4, 3, 2, 3, 2, 3, 1, 4, 4, 2, 4, 3,
1, 1, 1, 2, 3, 4, 4, 1, 3, 3, 3, 1, 3, 3, 2, 3, 3, 3,
2, 1, 3, 3, 3, 3, 1, 3, 3, 3, 3, 2, 2, 1, 3, 2, 2, 2,
4, 3, 1, 3, 4, 3, 4, 1, 3, 1, 3, 2, 3, 4, 1, 2, 1, 1,
2, 3, 3, 3, 3, 4, 4, 4, 1, 3, 3, 4, 3, 3, 1, 4, 4, 4,
4, 3, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1,
1, 3, 1, 3, 1, 1, 3, 1, 3, 1, 3, 3, 3, 2, 3, 1, 3, 3,
1, 2, 1, 3, 2, 2, 2, 3, 3, 3, 1, 1, 2, 2, 3, 3, 2, 3,
3, 2, 3, 3, 2, 3, 3, 3, 3, 2, 3, 2, 3, 3, 2, 3, 2, 2,
3, 3, 3, 4, 4, 2, 3, 3, 3, 2, 3, 4, 4, 3, 3, 4, 3, 4,
2, 4, 4, 2, 3, 4, 2, 3, 3, 5, 4, 2, 3, 2, 1, 3, 2, 1,
4, 4, 3, 2, 2, 2, 2, 3, 4, 4, 3, 4, 4, 4, 4, 3, 4, 4,
4, 4, 4, 4, 3, 4, 4, 4, 3, 4, 3, 3, 4, 4, 4, 4, 3, 3,
1, 3, 3, 1, 3, 1, 3, 3, 1, 2, 3, 3, 2, 3, 2, 1, 3, 2,
3, 1, 4, 1, 4, 3, 1, 1, 1, 3, 1, 1, 3, 1, 1, 3, 1, 1,
3, 3, 4, 4, 3, 1, 1, 3, 1, 4, 1, 1, 1, 1, 3, 1, 1, 2,
3, 3, 4, 3, 3, 1, 2, 1, 3, 3, 2, 1, 3, 1, 4, 1, 3, 3,
3, 3, 3, 2, 3, 4, 2, 2, 3, 2, 2, 2, 2, 2, 4, 2, 2, 2,
3, 3, 2, 2, 3, 4, 1, 2, 3, 3, 1, 2, 4, 3, 3, 1, 3, 4,
4, 3, 2, 2, 3, 1, 2, 3, 2, 2, 2, 4, 3, 3, 2, 3, 1, 1,
3, 2, 4, 1, 3, 2, 2, 2, 3, 3, 3, 1, 2, 2, 3, 2, 1, 1,
2, 4, 3, 3, 1, 2, 4, 4, 1, 2, 3, 3, 2, 1, 4, 2, 2, 1,
3, 2, 2, 2, 3, 3, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1,
2, 3, 1, 2, 2, 3, 4, 1, 3, 2, 2, 2, 2, 2, 2, 3, 1, 2,
3, 4, 4, 2, 2, 4, 3, 2, 3, 1, 4, 4, 2, 1, 4, 1, 3, 2,
2, 3, 4, 2, 4, 3, 3, 1, 2, 3, 3, 1, 4, 2, 3, 3, 1, 3,
3, 2, 1, 4, 4, 1, 4, 4, 3, 3, 2, 1, 1, 4, 3, 2, 3, 1,
4, 3, 4, 2, 3, 2, 1, 4, 2, 2, 3, 4, 3, 3, 3, 2, 2, 4,
2, 4, 3, 3, 4, 3, 4, 3, 2, 2, 3, 3, 3, 2, 2, 1, 3, 3,
1, 1, 1, 3, 4, 2, 2, 3, 3, 2, 1, 3, 3, 3, 3, 1, 3, 4,
3, 2, 2, 2, 3, 4, 1, 2, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1,
3, 1, 3, 3, 3, 1, 3, 1, 3, 1, 3, 1, 3, 2, 3, 2, 3, 3,
2, 2, 3, 2, 1, 2, 2, 2, 2, 1, 2, 3, 3, 2, 2, 2, 2, 3,
3, 2, 2, 3, 3, 2, 3, 4, 2, 2, 3, 3, 3, 4, 4, 2, 4, 2,
4, 2, 3, 1, 3, 4, 2, 4, 4, 4, 2, 3, 4, 4, 3, 3, 4, 4,
2, 3, 3, 2, 1, 4, 4, 4, 1, 2, 4, 2, 2, 3, 3, 4, 1, 2,
3, 4, 3, 1, 1, 4, 1, 4, 2, 2, 4, 2, 3, 3, 3, 3, 4, 4,
3, 3, 1, 4, 1, 3, 3, 4, 2, 3, 1, 4, 2, 2, 2, 1, 3, 4,
2, 2, 4, 4, 2, 2, 1, 4, 2, 1, 3, 3, 3, 1, 2, 4, 2, 4,
3, 2, 3, 4, 4, 3, 1, 4, 2, 4, 3, 1, 1, 1, 4, 1, 1, 2,
2, 4, 4, 3, 3, 1, 4, 1, 4, 2, 2, 1, 2, 2, 1, 1, 3, 4,
4, 3, 1, 3, 3, 4, 3, 4, 3, 4, 3, 4, 3, 3, 2, 4, 4, 3,
1, 3, 3, 1, 1, 2, 2, 1, 2, 2, 1, 1, 3, 2, 2, 2, 1, 2,
2, 3, 2, 3, 3, 1, 4, 2, 2, 1, 1, 2, 3, 2, 3, 3, 4, 2,
3, 3, 4, 2, 1, 1, 3, 2, 3, 2, 1, 1, 3, 3, 3, 2, 1, 1,
3, 1, 3, 1, 1, 3, 3, 1, 2, 4, 2, 1, 1, 3, 3, 3, 3, 2,
3, 1, 1, 3, 3, 1, 3, 1, 3, 1, 3, 3, 1, 3, 3, 1, 2, 2,
2, 3, 1, 2, 2, 1, 3, 3, 4, 3, 2, 3, 1, 2, 3, 2, 4, 1,
3, 3, 1, 4, 2, 2, 1, 3, 2, 2, 2, 2, 4, 4, 2, 4, 1, 1,
3, 2, 3, 2, 2, 1, 4, 2, 2, 2, 4, 1, 3, 1, 3, 2, 2, 3,
1, 2, 3, 1, 2, 1, 1, 2, 1, 3, 3, 2, 3, 1, 2, 1, 3, 2,
1, 3, 3, 2, 3, 4, 3, 3, 2, 2, 3, 3, 3, 2, 3, 4, 1, 1,
4, 3, 4, 1, 2, 3, 2, 4, 3, 3, 4, 4, 1, 3, 4, 4, 4, 3,
2, 3, 2, 3, 1, 4, 4, 2, 4, 3, 1, 1, 1, 2, 3, 4, 4, 1,
3, 3, 3, 1, 3, 3, 2, 3, 3, 3, 2, 1, 3, 3, 3, 3, 1, 3,
3, 3, 3, 2, 2, 1, 3, 2, 2, 2, 4, 3, 1, 3, 4, 3, 4, 1,
3, 1, 3, 2, 3, 4, 1, 2, 1, 1, 2, 3, 3, 3, 3, 4, 4, 4,
1, 3, 3, 4, 3, 3, 1, 4, 4, 4, 4, 3, 1, 1, 1, 3, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 3, 1, 3, 1,
3, 2, 3, 1, 3, 3, 1, 3, 3, 2, 3, 3, 1, 1, 3, 2, 2, 3,
1, 3, 5, 3, 2, 2, 1, 2, 3, 1, 3, 3, 3, 3, 2, 1, 3, 1,
3, 3, 3, 3, 3, 2, 3, 2, 3, 3, 3, 2, 3, 3, 2, 2, 3, 3,
3, 3, 3, 3, 2, 2, 3, 1, 1, 3, 3, 2, 2, 3, 3, 3, 3, 3,
3, 2, 3, 2, 3, 3, 3, 3, 3, 1, 3, 3, 2, 3, 2, 3, 2, 1,
3, 3, 4, 4, 3, 2, 3, 2, 3, 1, 3, 4, 3, 2, 3, 3, 2, 2,
4, 2, 2, 3, 2, 4, 2, 1, 4, 2, 2, 2, 4, 4, 3, 4, 2, 3,
2, 2, 2, 2, 3, 2, 2, 2, 4, 2, 4, 4, 2, 4, 4, 2, 4, 4,
2, 4, 4, 4, 4, 4, 4, 4, 2, 4, 2, 4, 4, 4, 4, 4, 4, 4,
4, 4, 3, 4, 1, 1, 1, 3, 3, 4, 2, 4, 1, 2, 4, 2, 3, 4,
4, 2, 1, 2, 2, 2, 1, 3, 1, 2, 2, 4, 1, 4, 4, 1, 4, 2,
4, 2, 2, 2, 1, 3, 4, 2, 4, 2, 2, 1, 4, 1, 3, 2, 1, 1,
2, 4, 1, 4, 2, 3, 2, 2, 4, 1, 3, 3, 2, 3, 3, 1, 3, 1,
3, 1, 2, 3, 2, 3, 3, 2, 1, 3, 2, 1, 2, 1, 3, 3, 2, 3,
2, 3, 1, 1, 1, 3, 2, 2, 2, 1, 2, 3, 3, 2, 1, 3, 1, 3,
1, 1, 2, 2, 2, 2, 1, 2, 1, 3, 3, 3, 2, 1, 3, 2, 2, 1,
1, 2, 3, 1, 2, 1, 1, 1, 3, 2, 1, 1, 1, 1, 3, 3, 1, 2,
2, 3, 2, 1, 3, 1, 2, 1, 1, 1, 3, 2, 3, 3, 3, 1, 3, 3,
1, 1, 3, 3, 2, 1, 1, 3, 3, 1, 1, 3, 1, 3, 3, 3, 3, 2,
2, 1, 1, 3, 3, 3, 2, 1, 1, 3, 3, 1, 3, 2, 3, 1, 1, 3,
1, 1, 1, 3, 1, 3, 3, 1, 3, 3, 1, 3, 3, 3, 3, 1, 3, 3,
1, 4, 3, 1, 2, 3, 1, 3, 4, 2, 1, 1, 3, 3, 3, 1, 2, 1,
3, 2, 3, 3, 3, 3, 3, 1, 3, 2, 3, 1, 1, 3, 2, 3, 2, 2,
3, 3, 3, 3, 1, 1, 2, 2, 3, 3, 2, 3, 3, 2, 1, 2, 3, 2,
3, 1, 1, 2, 2, 2, 3, 3, 3, 3, 2, 2, 3, 4, 2, 3, 3, 4,
3, 4, 3, 3, 4, 2, 3, 3, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1,
1, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 2,
2, 2, 2, 1, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 3, 2, 2,
2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 3, 1, 3, 3, 2, 2, 2, 1,
3, 3, 2, 2, 3, 3, 3, 1, 2, 2, 2, 3, 3, 3, 3, 1, 3, 1,
2, 1, 1, 3, 3, 2, 2, 3, 3, 5, 3, 2, 3, 3, 3, 1, 3, 3,
3, 3, 2, 3, 3, 2, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 4, 3,
4, 3, 4, 3, 4, 3, 3, 4, 4, 3, 3, 3, 3, 4, 4, 4, 3, 4,
3, 2, 3, 4, 4, 4, 1, 2, 4, 3, 3, 3, 4, 4, 4, 4, 3, 4,
4, 4, 3, 4, 3, 4, 4, 2, 3, 3, 1, 4, 1, 3, 1, 4, 4, 3,
3, 4, 1, 4, 2, 1, 2, 3, 4, 2, 3, 2, 1, 1, 2, 3, 1, 4,
2, 3, 2, 2, 1, 1, 2, 3, 3, 3, 3, 2, 1, 2, 2, 2, 3, 1,
3, 3, 4, 1, 1, 3, 3, 4, 3, 4, 3, 3, 2, 4, 3, 3, 4, 2,
2, 3, 1, 1, 3, 4, 2, 4, 2, 3, 4, 3, 4, 2, 1, 4, 3, 4,
2, 3, 3, 1, 1, 1, 3, 3, 2, 3, 3, 2, 2, 1, 1, 1, 3, 3,
1, 4, 3, 4, 3, 3, 1, 1, 1, 3, 3, 3, 3, 4, 1, 3, 1, 3,
2, 1, 1, 3, 2, 4, 2, 4, 4, 3, 3, 2, 1, 1, 4, 4, 3, 3,
1, 1, 3, 2, 3, 1, 3, 1, 1, 3, 3, 4, 4, 2, 1, 3, 4, 3,
3, 3, 2, 3, 3, 4, 1, 4, 3, 4, 3, 1, 2, 4, 3, 3, 1, 3,
1, 3, 3, 3, 1, 3, 3, 2, 1, 2, 3, 2, 3, 1, 3, 4, 4, 3,
1, 3, 2, 4, 1, 1, 1, 3, 3, 2, 2, 3, 4, 1, 2, 1, 1, 1,
2, 3, 1, 2, 1, 2, 2, 3, 3, 2, 1, 2, 1, 1, 4, 1, 1, 2,
1, 3, 4, 1, 4, 4, 3, 4, 3, 1, 1, 1, 1, 2, 3, 4, 3, 2,
4, 4, 3, 2, 1, 4, 4, 1, 4, 3, 4, 2, 3, 4, 3, 1, 1, 1,
3, 1, 1, 3, 1, 3, 3, 4, 4, 3, 2, 1, 4, 4, 2, 4, 3, 3,
3, 4, 2, 2, 3, 3, 4, 4, 4, 1, 1, 3, 3, 3, 3, 3, 4, 3,
3, 3, 2, 2, 3, 2, 3, 2, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 3, 1, 1, 1, 3, 1, 3, 1, 3, 2, 3, 1, 3, 3,
1, 3, 3, 2, 3, 3, 1, 1, 3, 2, 2, 3, 1, 3, 5, 3, 2, 2,
1, 2, 3, 1, 3, 3, 3, 3, 2, 1, 3, 1, 3, 3, 3, 3, 3, 2,
3, 2, 3, 3, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 3, 2, 2,
3, 1, 1, 3, 3, 2, 2, 3, 3, 3, 3, 3, 3, 2, 3, 2, 3, 3,
3, 3, 3, 1, 3, 3, 2, 3, 2, 3, 2, 1, 3, 3, 4, 4, 3, 2,
3, 2, 3, 1, 3, 4, 3, 2, 3, 3, 2, 2, 4, 2, 2, 3, 2, 4,
2, 1, 4, 2, 2, 2, 4, 4, 3, 4, 2, 3, 2, 2, 2, 2, 3, 2,
2, 2, 4, 2, 4, 4, 2, 4, 4, 2, 4, 4, 2, 4, 4, 4, 4, 4,
4, 4, 2, 4, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 1, 1,
1, 3, 3, 4, 2, 4, 1, 2, 4, 2, 3, 4, 4, 2, 1, 2, 2, 2,
1, 3, 1, 2, 2, 4, 1, 4, 4, 1, 4, 2, 4, 2, 2, 2, 1, 3,
4, 2, 4, 2, 2, 1, 4, 1, 3, 2, 1, 1, 2, 4, 1, 4, 2, 3,
2, 2, 4, 1, 3, 3, 2, 3, 3, 1, 3, 1, 3, 1, 2, 3, 2, 3,
3, 2, 1, 3, 2, 1, 2, 1, 3, 3, 2, 3, 2, 3, 1, 1, 1, 3,
2, 2, 2, 1, 2, 3, 3, 2, 1, 3, 1, 3, 1, 1, 2, 2, 2, 2,
1, 2, 1, 3, 3, 3, 2, 1, 3, 2, 2, 1, 1, 2, 3, 1, 2, 1,
1, 1, 3, 2, 1, 1, 1, 1, 3, 3, 1, 2, 2, 3, 2, 1, 3, 1,
2, 1, 1, 1, 3, 2, 3, 3, 3, 1, 3, 3, 1, 1, 3, 3, 2, 1,
1, 3, 3, 1, 1, 3, 1, 3, 3, 3, 3, 2, 2, 1, 1, 3, 3, 3,
2, 1, 1, 3, 3, 1, 3, 2, 3, 1, 1, 3, 1, 1, 1, 3, 1, 3,
3, 1, 3, 3, 1, 3, 3, 3, 3, 1, 3, 3, 1, 4, 3, 1, 2, 3,
1, 3, 4, 2, 1, 1, 3, 3, 3, 1, 2, 1, 3, 2, 3, 3, 3, 3,
3, 1, 3, 2, 3, 1, 1, 3, 2, 3, 2, 2, 3, 3, 3, 3, 1, 1,
2, 2, 3, 3, 2, 3, 3, 2, 1, 2, 3, 2, 3, 1, 1, 2, 2, 2,
3, 3, 3, 3, 2, 2, 3, 4, 2, 3, 3, 4, 3, 4, 3, 3, 4, 2,
3, 3, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1,
2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2,
2, 2, 1, 2, 2, 1, 2, 1, 2, 3, 2, 2, 2, 2, 2, 2, 1, 2,
2, 2, 2, 2, 3, 1, 3, 3, 2, 2, 2, 1, 3, 3, 2, 2, 3, 3,
3, 1, 2, 2, 2, 3, 3, 3, 3, 1, 3, 1, 2, 1, 1, 3, 3, 2,
2, 3, 3, 5, 3, 2, 3, 3, 3, 1, 3, 3, 3, 3, 2, 3, 3, 2,
3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 4, 3, 4, 3, 4, 3, 4, 3,
3, 4, 4, 3, 3, 3, 3, 4, 4, 4, 3, 4, 3, 2, 3, 4, 4, 4,
1, 2, 4, 3, 3, 3, 4, 4, 4, 4, 3, 4, 4, 4, 3, 4, 3, 4,
4, 2, 3, 3, 1, 4, 1, 3, 1, 4, 4, 3, 3, 4, 1, 4, 2, 1,
2, 3, 4, 2, 3, 2, 1, 1, 2, 3, 1, 4, 2, 3, 2, 2, 1, 1,
2, 3, 3, 3, 3, 2, 1, 2, 2, 2, 3, 1, 3, 3, 4, 1, 1, 3,
3, 4, 3, 4, 3, 3, 2, 4, 3, 3, 4, 2, 2, 3, 1, 1, 3, 4,
2, 4, 2, 3, 4, 3, 4, 2, 1, 4, 3, 4, 2, 3, 3, 1, 1, 1,
3, 3, 2, 3, 3, 2, 2, 1, 1, 1, 3, 3, 1, 4, 3, 4, 3, 3,
1, 1, 1, 3, 3, 3, 3, 4, 1, 3, 1, 3, 2, 1, 1, 3, 2, 4,
2, 4, 4, 3, 3, 2, 1, 1, 4, 4, 3, 3, 1, 1, 3, 2, 3, 1,
3, 1, 1, 3, 3, 4, 4, 2, 1, 3, 4, 3, 3, 3, 2, 3, 3, 4,
1, 4, 3, 4, 3, 1, 2, 4, 3, 3, 1, 3, 1, 3, 3, 3, 1, 3,
3, 2, 1, 2, 3, 2, 3, 1, 3, 4, 4, 3, 1, 3, 2, 4, 1, 1,
1, 3, 3, 2, 2, 3, 4, 1, 2, 1, 1, 1, 2, 3, 1, 2, 1, 2,
2, 3, 3, 2, 1, 2, 1, 1, 4, 1, 1, 2, 1, 3, 4, 1, 4, 4,
3, 4, 3, 1, 1, 1, 1, 2, 3, 4, 3, 2, 4, 4, 3, 2, 1, 4,
4, 1, 4, 3, 4, 2, 3, 4, 3, 1, 1, 1, 3, 1, 1, 3, 1, 3,
3, 4, 4, 3, 2, 1, 4, 4, 2, 4, 3, 3, 3, 4, 2, 2, 3, 3,
4, 4, 4, 1, 1, 3, 3, 3, 3, 3, 4, 3, 3, 3, 2, 2, 3, 2,
3, 2, 1, 1, 3, 4, 4, 4, 4, 2, 2, 3, 1, 2, 3, 2, 2, 3,
2, 2, 1, 2, 2, 1, 2, 2, 3, 1, 4, 2, 4, 3, 2, 2, 2, 2,
1, 1, 1, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 1, 3,
3, 1, 3, 3, 1, 3, 1, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 1,
3, 3, 3, 3, 2, 1, 3, 1, 1, 3, 3, 1, 1, 3, 2, 3, 3, 3,
3, 1, 2, 1, 1, 1, 3, 1, 2, 1, 2, 3, 4, 1, 1, 1, 3, 3,
1, 2, 2, 3, 1, 1, 1, 3, 2, 1, 3, 1, 1, 3, 1, 1, 3, 4,
2, 1, 3, 2, 3, 3, 1, 1, 1, 1, 2, 2, 1, 2, 1, 3, 3, 1,
2, 1, 3, 1, 2, 2, 1, 3, 2, 1, 3, 2, 2, 2, 2, 1, 3, 1,
2, 2, 2, 1, 1, 2, 2, 2, 2, 3, 1, 1, 3, 2, 2, 3, 2, 1,
4, 4, 4, 2, 4, 3, 2, 4, 3, 2, 4, 4, 4, 4, 4, 2, 3, 4,
2, 2, 3, 5, 4, 1, 3, 4, 2, 2, 2, 4, 4, 3, 2, 2, 4, 4,
2, 4, 2, 1, 4, 3, 1, 3, 3, 2, 3, 4, 2, 2, 2, 2, 4, 4,
1, 1, 4, 4, 4, 4, 2, 2, 2, 4, 1, 3, 4, 4, 1, 3, 1, 1,
1, 2, 1, 4, 3, 4, 3, 4, 1, 4, 3, 4, 3, 3, 1, 1, 2, 2,
2, 1, 3, 1, 4, 4, 1, 3, 2, 1, 4, 4, 2, 3, 3, 2, 3, 3,
1, 1, 2, 2, 1, 3, 3, 3, 1, 2, 1, 4, 3, 1, 3, 1, 1, 2,
3, 3, 4, 2, 4, 4, 3, 1, 4, 3, 2, 1, 1, 3, 1, 2, 4, 4,
1, 1, 2, 2, 2, 3, 2, 2, 3, 3, 2, 1, 1, 4, 2, 4, 2, 1,
1, 2, 3, 2, 2, 4, 2, 2, 1, 3, 3, 2, 1, 2, 2, 4, 3, 4,
2, 3, 2, 3, 2, 1, 4, 2, 1, 3, 1, 1, 4, 2, 2, 3, 2, 3,
2, 4, 4, 2, 4, 1, 3, 4, 4, 2, 2, 4, 4, 4, 1, 2, 4, 4,
2, 4, 4, 2, 4, 2, 4, 1, 2, 4, 4, 4, 4, 4, 2, 4, 4, 4,
2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 2, 2, 3, 4,
1, 2, 2, 2, 2, 3, 3, 4, 1, 2, 2, 1, 3, 2, 3, 1, 3, 3,
4, 3, 3, 3, 4, 3, 4, 4, 4, 2, 1, 2, 4, 2, 3, 1, 1, 4,
2, 4, 1, 3, 3, 1, 1, 2, 1, 1, 3, 3, 2, 2, 4, 3, 4, 1,
4, 2, 2, 3, 1, 2, 3, 3, 1, 4, 3, 3, 2, 4, 4, 3, 1, 4,
3, 3, 3, 3, 3, 4, 2, 4, 2, 2, 4, 3, 1, 4, 4, 3, 2, 3,
2, 3, 4, 3, 1, 1, 3, 3, 3, 1, 4, 3, 4, 3, 3, 3, 3, 3,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 3, 1, 1,
1, 1, 1, 1, 1, 3, 2, 1, 1, 2, 1, 2, 1, 3, 2, 2, 2, 2,
2, 2, 1, 2, 2, 1, 1, 3, 1, 2, 2, 2, 3, 2, 3, 2, 1, 2,
2, 3, 3, 2, 2, 1, 2, 2, 2, 2, 3, 2, 2, 2, 2, 2, 2, 3,
1, 2, 2, 2, 3, 2, 3, 3, 2, 3, 3, 3, 3, 2, 2, 1, 1, 2,
2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 3, 2, 2, 3, 3, 2, 2, 1,
1, 3, 3, 3, 3, 3, 3, 1, 2, 3, 3, 2, 2, 3, 3, 3, 2, 3,
2, 2, 3, 3, 3, 3, 2, 3, 3, 3, 3, 2, 3, 1, 2, 2, 3, 1,
3, 2, 3, 2, 2, 3, 1, 3, 3, 2, 3, 2, 3, 3, 3, 2, 2, 3,
1, 3, 4, 3, 3, 4, 3, 3, 2, 2, 4, 4, 3, 1, 4, 3, 4, 3,
2, 2, 2, 4, 4, 4, 3, 3, 2, 4, 4, 2, 2, 4, 4, 2, 4, 2,
1, 4, 3, 1, 4, 4, 3, 4, 3, 4, 4, 1, 2, 2, 4, 3, 3, 2,
2, 4, 4, 4, 1, 3, 4, 4, 4, 3, 1, 4, 1, 4, 4, 1, 3, 2,
2, 4, 2, 2, 1, 2, 2, 2, 1, 4, 3, 3, 3, 2, 2, 2, 1, 3,
2, 1, 3, 3, 4, 1, 2, 4, 1, 3, 3, 4, 4, 3, 4, 4, 2, 2,
4, 4, 1, 3, 1, 1, 4, 2, 1, 1, 2, 2, 4, 4, 3, 3, 1, 1,
1, 1, 1, 4, 1, 4, 4, 2, 4, 4, 1, 1, 3, 3, 1, 3, 2, 1,
1, 1, 2, 2, 2, 1, 1, 2, 3, 2, 1, 3, 4, 3, 4, 1, 2, 2,
1, 2, 1, 3, 3, 3, 3, 4, 2, 3, 1, 3, 3, 3, 2, 3, 2, 1,
1, 4, 4, 1, 3, 3, 3, 2, 3, 3, 4, 4, 1, 2, 4, 4, 2, 2,
1, 1, 3, 3, 3, 1, 1, 1, 2, 3, 2, 2, 1, 3, 4, 3, 1, 3,
2, 2, 1, 2, 2, 1, 3, 1, 3, 3, 1, 4, 1, 2, 1, 2, 2, 2,
4, 2, 2, 4, 2, 3, 3, 2, 2, 4, 2, 4, 3, 3, 3, 3, 2, 2,
4, 3, 4, 2, 3, 2, 2, 3, 2, 3, 3, 3, 3, 2, 4, 2, 3, 3,
2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 4, 4],
"edu": [2, 4, 2, 3, 3, 4, 1, 4, 4, 4, 4, 4, 2, 2, 4, 2, 3, 3,
4, 3, 1, 4, 1, 3, 4, 4, 2, 2, 3, 4, 4, 4, 1, 4, 1, 2,
4, 3, 2, 2, 1, 2, 1, 4, 4, 4, 2, 2, 4, 1, 2, 3, 4, 3,
3, 4, 2, 3, 2, 1, 1, 3, 3, 4, 4, 4, 2, 2, 4, 4, 2, 2,
4, 1, 2, 4, 2, 4, 2, 3, 3, 3, 3, 2, 4, 1, 4, 3, 3, 1,
2, 3, 4, 4, 2, 2, 2, 4, 1, 3, 2, 3, 3, 2, 2, 4, 4, 4,
4, 3, 1, 3, 3, 2, 2, 2, 3, 2, 2, 2, 3, 2, 4, 2, 4, 4,
4, 4, 3, 2, 4, 1, 4, 2, 2, 2, 2, 3, 4, 2, 4, 4, 3, 4,
4, 4, 4, 2, 3, 3, 2, 3, 3, 2, 3, 2, 4, 4, 3, 4, 2, 3,
1, 3, 1, 1, 3, 3, 1, 2, 2, 2, 1, 4, 4, 2, 2, 2, 2, 4,
3, 2, 2, 2, 4, 2, 2, 1, 2, 2, 3, 2, 2, 3, 3, 3, 4, 2,
3, 2, 2, 2, 2, 3, 2, 2, 3, 4, 4, 3, 3, 4, 4, 4, 4, 2,
2, 4, 2, 3, 1, 3, 4, 4, 4, 2, 2, 2, 2, 4, 2, 2, 2, 2,
4, 2, 3, 4, 3, 4, 1, 4, 3, 3, 2, 2, 4, 4, 2, 3, 2, 2,
3, 3, 1, 2, 2, 2, 4, 3, 2, 2, 3, 4, 3, 3, 4, 2, 4, 2,
2, 4, 1, 1, 4, 2, 3, 2, 2, 4, 2, 2, 4, 2, 3, 4, 3, 3,
4, 3, 1, 3, 3, 4, 4, 1, 2, 4, 2, 2, 4, 4, 3, 3, 2, 4,
2, 1, 4, 2, 3, 4, 3, 4, 2, 2, 2, 4, 2, 4, 3, 2, 2, 4,
2, 3, 2, 4, 4, 3, 2, 2, 4, 1, 2, 4, 3, 4, 3, 2, 3, 4,
3, 2, 4, 4, 4, 1, 3, 2, 2, 1, 3, 4, 3, 2, 4, 2, 2, 2,
1, 1, 1, 2, 2, 4, 3, 4, 4, 4, 2, 2, 3, 3, 4, 4, 1, 3,
1, 1, 1, 2, 3, 4, 4, 4, 2, 3, 2, 4, 3, 2, 2, 2, 3, 2,
4, 3, 1, 3, 2, 2, 4, 4, 2, 4, 4, 3, 3, 4, 3, 2, 2, 2,
4, 2, 4, 3, 4, 2, 4, 2, 2, 3, 1, 3, 4, 4, 4, 4, 3, 3,
3, 2, 4, 3, 3, 4, 2, 1, 2, 4, 4, 2, 4, 1, 1, 3, 2, 4,
4, 3, 4, 4, 1, 3, 4, 3, 3, 3, 3, 2, 2, 4, 3, 2, 3, 1,
3, 2, 3, 2, 1, 3, 2, 4, 3, 3, 2, 4, 3, 4, 3, 3, 4, 2,
2, 2, 2, 3, 2, 4, 1, 4, 2, 1, 4, 1, 3, 2, 3, 4, 2, 2,
2, 4, 4, 1, 4, 3, 4, 4, 3, 3, 1, 1, 3, 2, 3, 2, 3, 1,
4, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 4, 3, 1, 2, 4, 2, 2,
1, 1, 4, 4, 3, 3, 2, 4, 2, 4, 4, 2, 2, 2, 3, 3, 3, 3,
3, 2, 2, 4, 2, 2, 2, 4, 4, 2, 1, 4, 3, 3, 4, 3, 2, 2,
4, 3, 2, 2, 2, 1, 4, 3, 4, 2, 4, 2, 2, 4, 4, 4, 1, 2,
2, 2, 4, 4, 1, 2, 2, 2, 2, 1, 3, 2, 3, 1, 4, 3, 3, 2,
2, 4, 3, 3, 1, 2, 3, 4, 4, 4, 1, 2, 3, 1, 3, 2, 2, 4,
2, 4, 1, 2, 2, 4, 4, 2, 3, 3, 2, 4, 2, 4, 3, 4, 2, 3,
4, 2, 3, 2, 4, 4, 1, 3, 3, 4, 1, 3, 3, 3, 2, 3, 2, 1,
4, 3, 2, 2, 2, 3, 3, 2, 1, 2, 2, 2, 4, 4, 2, 3, 2, 1,
2, 1, 3, 2, 3, 2, 3, 4, 2, 2, 3, 4, 3, 2, 2, 2, 2, 4,
3, 3, 4, 2, 2, 2, 1, 3, 2, 2, 3, 4, 4, 4, 3, 4, 2, 4,
2, 1, 1, 1, 4, 4, 4, 2, 2, 2, 1, 2, 4, 4, 4, 2, 4, 2,
3, 3, 2, 2, 4, 2, 2, 2, 1, 4, 4, 4, 2, 4, 2, 4, 3, 2,
4, 4, 2, 2, 4, 3, 3, 3, 4, 4, 4, 4, 2, 2, 2, 2, 2, 2,
3, 4, 2, 2, 2, 4, 2, 1, 4, 4, 3, 3, 2, 4, 2, 4, 2, 3,
3, 1, 4, 4, 2, 2, 2, 4, 3, 3, 2, 1, 3, 3, 2, 3, 4, 3,
1, 2, 4, 4, 4, 3, 2, 3, 4, 2, 2, 1, 2, 3, 4, 2, 2, 3,
2, 2, 3, 2, 4, 2, 3, 2, 3, 3, 3, 4, 2, 2, 2, 4, 3, 2,
1, 2, 3, 2, 4, 3, 2, 3, 2, 1, 4, 1, 2, 4, 3, 3, 2, 2,
2, 1, 2, 3, 1, 1, 2, 1, 4, 2, 3, 4, 1, 1, 1, 1, 2, 2,
1, 1, 4, 4, 1, 4, 3, 4, 3, 3, 3, 2, 4, 4, 4, 4, 4, 3,
2, 2, 4, 4, 1, 4, 4, 3, 3, 2, 4, 4, 2, 2, 2, 2, 3, 2,
2, 3, 3, 3, 1, 4, 4, 3, 3, 2, 1, 2, 2, 1, 2, 3, 3, 2,
2, 1, 3, 4, 4, 2, 2, 3, 1, 1, 3, 3, 2, 4, 1, 4, 1, 3,
2, 2, 3, 3, 2, 4, 1, 2, 3, 2, 2, 1, 2, 3, 2, 2, 4, 4,
4, 2, 2, 3, 4, 3, 4, 2, 2, 4, 3, 2, 2, 2, 4, 2, 3, 3,
4, 3, 4, 2, 3, 3, 3, 2, 2, 3, 1, 2, 2, 2, 1, 4, 2, 3,
4, 4, 4, 2, 2, 1, 2, 2, 4, 2, 2, 4, 1, 3, 3, 1, 3, 4,
2, 3, 2, 2, 4, 4, 4, 2, 2, 2, 2, 1, 4, 1, 3, 3, 3, 3,
3, 1, 2, 2, 4, 3, 2, 4, 4, 1, 2, 1, 3, 4, 4, 4, 4, 2,
2, 2, 4, 3, 4, 2, 2, 4, 1, 2, 4, 1, 2, 3, 4, 4, 1, 3,
2, 3, 2, 4, 2, 3, 3, 3, 3, 2, 3, 2, 3, 4, 2, 3, 2, 2,
4, 2, 1, 4, 1, 4, 2, 1, 2, 4, 1, 2, 4, 3, 2, 4, 3, 3,
2, 2, 3, 1, 2, 2, 3, 2, 4, 3, 4, 3, 1, 3, 4, 1, 3, 2,
3, 3, 3, 2, 2, 4, 4, 2, 4, 2, 2, 2, 2, 4, 4, 3, 4, 3,
3, 1, 2, 3, 2, 2, 3, 3, 2, 3, 3, 4, 2, 3, 3, 3, 4, 2,
3, 2, 3, 3, 3, 1, 3, 3, 4, 2, 2, 1, 4, 2, 2, 2, 2, 1,
3, 3, 1, 2, 1, 4, 3, 1, 3, 2, 2, 4, 4, 4, 3, 2, 3, 1,
3, 2, 2, 2, 1, 2, 2, 1, 4, 2, 2, 2, 2, 2, 2, 2, 2, 3,
4, 1, 2, 4, 4, 1, 2, 3, 2, 3, 2, 1, 3, 4, 1, 3, 2, 4,
3, 3, 2, 3, 2, 4, 2, 2, 2, 1, 1, 3, 4, 3, 3, 2, 2, 3,
4, 3, 3, 3, 2, 1, 3, 2, 4, 4, 4, 2, 3, 3, 3, 4, 2, 2,
2, 3, 2, 2, 3, 4, 2, 2, 2, 4, 4, 4, 4, 2, 4, 3, 3, 4,
2, 3, 4, 3, 2, 3, 4, 4, 4, 4, 3, 2, 1, 2, 1, 4, 3, 4,
3, 2, 2, 4, 2, 4, 2, 3, 3, 4, 3, 4, 3, 2, 4, 4, 2, 3,
3, 3, 4, 2, 2, 4, 3, 2, 4, 4, 2, 2, 3, 2, 3, 4, 4, 3,
4, 4, 1, 3, 3, 3, 3, 4, 4, 4, 4, 2, 2, 4, 4, 2, 2, 4,
3, 4, 3, 3, 3, 1, 3, 3, 4, 4, 4, 3, 4, 2, 3, 3, 2, 4,
2, 4, 4, 3, 3, 4, 2, 4, 3, 2, 1, 4, 3, 4, 2, 2, 2, 4,
4, 3, 4, 2, 1, 2, 4, 2, 4, 2, 3, 2, 2, 2, 2, 3, 2, 4,
4, 1, 2, 2, 2, 4, 3, 2, 4, 1, 3, 2, 2, 3, 4, 4, 1, 4,
2, 1, 4, 1, 1, 1, 2, 3, 1, 2, 2, 2, 4, 1, 1, 2, 2, 2,
2, 2, 4, 3, 3, 3, 3, 2, 2, 4, 3, 2, 3, 1, 3, 2, 3, 2,
1, 3, 2, 4, 3, 3, 2, 4, 3, 4, 3, 3, 4, 2, 2, 2, 2, 3,
2, 4, 1, 4, 2, 1, 4, 1, 3, 2, 3, 4, 2, 2, 2, 4, 4, 1,
4, 3, 4, 4, 3, 3, 1, 1, 3, 2, 3, 2, 3, 1, 4, 3, 3, 2,
2, 2, 2, 2, 2, 2, 2, 4, 3, 1, 2, 4, 2, 2, 1, 1, 4, 4,
3, 3, 2, 4, 2, 4, 4, 2, 2, 2, 3, 3, 3, 3, 3, 2, 2, 4,
2, 2, 2, 4, 4, 2, 1, 4, 3, 3, 4, 3, 2, 2, 4, 3, 2, 2,
2, 1, 4, 3, 4, 2, 4, 2, 2, 4, 4, 4, 1, 2, 2, 2, 4, 4,
1, 2, 2, 2, 2, 1, 3, 2, 3, 1, 4, 3, 3, 2, 2, 4, 3, 3,
1, 2, 3, 4, 4, 4, 1, 2, 3, 1, 3, 2, 2, 4, 2, 4, 1, 2,
2, 4, 4, 2, 3, 3, 2, 4, 2, 4, 3, 4, 2, 3, 4, 2, 3, 2,
4, 4, 1, 3, 3, 4, 1, 3, 3, 3, 2, 3, 2, 1, 4, 3, 2, 2,
2, 3, 3, 2, 1, 2, 2, 2, 4, 4, 2, 3, 2, 1, 2, 1, 3, 2,
3, 2, 3, 4, 2, 2, 3, 4, 3, 2, 2, 2, 2, 4, 3, 3, 4, 2,
2, 2, 1, 3, 2, 2, 3, 4, 4, 4, 3, 4, 2, 4, 2, 1, 1, 1,
4, 4, 4, 2, 2, 2, 1, 2, 4, 4, 4, 2, 4, 2, 3, 3, 2, 2,
4, 2, 2, 2, 1, 4, 4, 4, 2, 4, 2, 4, 3, 2, 4, 4, 2, 2,
4, 3, 3, 3, 4, 4, 4, 4, 2, 2, 2, 2, 2, 2, 3, 4, 2, 2,
2, 4, 2, 1, 4, 4, 3, 3, 2, 4, 2, 4, 2, 3, 3, 1, 4, 4,
2, 2, 2, 4, 3, 3, 2, 1, 3, 3, 2, 3, 4, 3, 1, 2, 4, 4,
4, 3, 2, 3, 4, 2, 2, 1, 2, 3, 4, 2, 2, 3, 2, 2, 3, 2,
4, 2, 3, 2, 3, 3, 3, 4, 2, 2, 2, 4, 3, 2, 2, 4, 4, 1,
4, 4, 3, 3, 2, 4, 4, 2, 2, 2, 2, 3, 2, 2, 3, 3, 3, 1,
4, 4, 3, 3, 2, 1, 2, 2, 1, 2, 3, 3, 2, 2, 1, 3, 4, 4,
2, 2, 3, 1, 1, 3, 3, 2, 4, 1, 4, 1, 3, 2, 2, 3, 3, 2,
4, 1, 2, 3, 2, 2, 1, 2, 3, 2, 2, 4, 4, 4, 2, 2, 3, 4,
3, 4, 2, 2, 4, 3, 2, 2, 2, 4, 2, 3, 3, 4, 3, 4, 2, 3,
3, 3, 2, 2, 3, 1, 2, 2, 2, 1, 4, 2, 3, 4, 4, 4, 2, 2,
1, 2, 2, 4, 2, 2, 4, 1, 3, 3, 1, 3, 4, 2, 3, 2, 2, 4,
4, 4, 2, 2, 2, 2, 1, 4, 1, 3, 3, 3, 3, 3, 1, 2, 2, 4,
3, 2, 4, 4, 1, 2, 1, 3, 4, 4, 4, 4, 2, 2, 2, 4, 3, 4,
2, 2, 4, 1, 2, 4, 1, 2, 3, 4, 4, 1, 3, 2, 3, 2, 4, 2,
3, 3, 3, 3, 2, 3, 2, 3, 4, 2, 3, 2, 2, 4, 2, 1, 4, 1,
4, 2, 1, 2, 4, 1, 2, 4, 3, 2, 4, 3, 3, 2, 2, 3, 1, 2,
2, 3, 2, 4, 3, 4, 3, 1, 3, 4, 1, 3, 2, 3, 3, 3, 2, 2,
4, 4, 2, 4, 2, 2, 2, 2, 4, 4, 3, 4, 3, 3, 1, 2, 3, 2,
2, 3, 3, 2, 3, 3, 4, 2, 3, 3, 3, 4, 2, 3, 2, 3, 3, 3,
1, 3, 3, 4, 2, 2, 1, 4, 2, 2, 2, 2, 1, 3, 3, 1, 2, 1,
4, 3, 1, 3, 2, 2, 4, 4, 4, 3, 2, 3, 1, 3, 2, 2, 2, 1,
2, 2, 1, 4, 2, 2, 2, 2, 2, 2, 2, 2, 3, 4, 1, 2, 4, 4,
1, 2, 3, 2, 3, 2, 1, 3, 4, 1, 3, 2, 4, 3, 3, 2, 3, 2,
4, 2, 2, 2, 1, 1, 3, 4, 3, 3, 2, 2, 3, 4, 3, 3, 3, 2,
1, 3, 2, 4, 4, 4, 2, 3, 3, 3, 4, 2, 2, 2, 3, 2, 2, 3,
4, 2, 2, 2, 4, 4, 4, 4, 2, 4, 3, 3, 4, 2, 3, 4, 3, 2,
3, 4, 4, 4, 4, 3, 2, 1, 2, 1, 4, 3, 4, 3, 2, 2, 4, 2,
4, 2, 3, 3, 4, 3, 4, 3, 2, 4, 4, 2, 3, 3, 3, 4, 2, 2,
4, 3, 2, 4, 4, 2, 2, 3, 2, 3, 4, 4, 3, 4, 4, 1, 3, 3,
3, 3, 4, 4, 4, 4, 2, 2, 4, 4, 2, 2, 4, 3, 4, 3, 3, 3,
1, 3, 3, 4, 4, 4, 3, 4, 2, 3, 3, 2, 4, 2, 4, 4, 3, 3,
4, 2, 4, 3, 2, 1, 4, 3, 4, 2, 2, 2, 4, 4, 3, 4, 2, 1,
2, 4, 2, 4, 2, 3, 2, 2, 2, 2, 3, 2, 4, 4, 1, 2, 2, 2,
4, 3, 2, 4, 1, 3, 2, 2, 3, 4, 4, 1, 4, 2, 1, 4, 1, 1,
1, 2, 3, 1, 2, 2, 2, 4, 1, 1, 2, 2, 2, 2, 2, 3, 2, 2,
3, 2, 2, 3, 4, 3, 3, 2, 1, 1, 3, 1, 3, 2, 3, 4, 4, 3,
4, 1, 3, 3, 3, 2, 2, 2, 3, 4, 2, 4, 2, 2, 3, 3, 2, 4,
1, 2, 2, 4, 2, 1, 4, 4, 2, 3, 3, 4, 2, 3, 3, 3, 2, 2,
4, 4, 2, 1, 3, 3, 2, 3, 2, 2, 4, 4, 4, 1, 3, 1, 3, 4,
3, 3, 2, 2, 2, 2, 4, 2, 4, 3, 2, 4, 2, 2, 2, 3, 4, 4,
2, 2, 2, 2, 3, 3, 4, 3, 4, 1, 3, 4, 2, 3, 2, 3, 1, 2,
3, 2, 1, 3, 2, 4, 4, 2, 4, 4, 4, 4, 2, 3, 2, 4, 3, 4,
3, 4, 2, 2, 3, 4, 2, 3, 2, 2, 3, 4, 3, 4, 1, 2, 4, 4,
4, 2, 3, 4, 4, 4, 2, 4, 1, 2, 2, 3, 4, 4, 4, 3, 4, 2,
1, 4, 2, 3, 2, 4, 4, 2, 4, 4, 2, 1, 4, 3, 4, 1, 3, 3,
3, 2, 3, 3, 1, 2, 3, 2, 2, 3, 1, 4, 2, 2, 3, 4, 2, 4,
3, 3, 2, 3, 4, 4, 1, 2, 3, 4, 3, 2, 3, 3, 4, 4, 2, 3,
2, 4, 4, 4, 3, 1, 4, 4, 4, 4, 4, 2, 4, 2, 3, 3, 4, 4,
2, 4, 3, 4, 4, 4, 3, 2, 4, 2, 2, 3, 4, 3, 3, 2, 1, 1,
4, 2, 3, 4, 4, 4, 2, 1, 4, 3, 2, 4, 4, 2, 1, 3, 1, 2,
2, 4, 2, 3, 2, 3, 1, 4, 3, 2, 2, 4, 2, 2, 4, 2, 4, 3,
3, 2, 2, 2, 1, 3, 3, 2, 3, 4, 2, 3, 2, 4, 2, 1, 3, 2,
2, 3, 4, 4, 2, 3, 4, 4, 2, 4, 4, 4, 2, 3, 4, 3, 4, 3,
2, 3, 2, 3, 3, 2, 3, 3, 2, 2, 4, 1, 3, 2, 4, 2, 3, 4,
3, 4, 2, 2, 4, 3, 2, 3, 3, 3, 3, 3, 3, 2, 4, 3, 3, 4,
2, 3, 3, 3, 4, 1, 4, 3, 3, 4, 3, 2, 3, 4, 4, 4, 4, 3,
4, 4, 4, 2, 3, 3, 3, 3, 2, 3, 3, 2, 4, 3, 2, 4, 4, 2,
2, 2, 1, 4, 1, 2, 3, 4, 2, 4, 2, 3, 3, 4, 3, 3, 3, 3,
4, 4, 3, 2, 4, 3, 4, 2, 4, 3, 2, 2, 2, 2, 2, 4, 3, 3,
2, 4, 2, 4, 4, 4, 3, 3, 3, 3, 4, 1, 3, 4, 4, 2, 2, 3,
1, 1, 3, 3, 2, 4, 1, 4, 1, 3, 2, 2, 3, 3, 2, 4, 1, 2,
3, 2, 2, 1, 2, 3, 2, 2, 4, 4, 4, 2, 2, 3, 4, 3, 4, 2,
2, 4, 3, 2, 2, 2, 4, 2, 3, 3, 4, 3, 4, 2, 3, 3, 3, 2,
2, 3, 1, 2, 2, 2, 1, 4, 2, 3, 4, 4, 4, 2, 2, 1, 2, 2,
4, 2, 2, 4, 1, 3, 3, 1, 3, 4, 2, 3, 2, 2, 4, 4, 4, 2,
2, 2, 2, 1, 4, 1, 3, 3, 3, 3, 3, 1, 2, 2, 4, 3, 2, 4,
4, 1, 2, 1, 3, 4, 4, 4, 4, 2, 2, 2, 4, 3, 4, 2, 2, 4,
1, 2, 4, 1, 2, 3, 4, 4, 1, 3, 2, 3, 2, 4, 2, 3, 3, 3,
3, 2, 3, 2, 3, 4, 2, 3, 2, 2, 4, 2, 1, 4, 1, 4, 2, 1,
2, 4, 1, 2, 4, 3, 2, 4, 3, 3, 2, 2, 3, 1, 2, 2, 3, 2,
4, 3, 4, 3, 1, 3, 4, 1, 3, 2, 3, 3, 3, 2, 2, 4, 4, 2,
4, 2, 2, 2, 2, 4, 4, 3, 4, 3, 3, 1, 2, 3, 2, 2, 3, 3,
2, 3, 3, 4, 2, 3, 3, 3, 4, 2, 3, 2, 3, 3, 3, 1, 3, 3,
4, 2, 2, 1, 4, 2, 2, 2, 2, 1, 3, 3, 1, 2, 1, 4, 3, 1,
3, 2, 2, 4, 4, 4, 3, 2, 3, 1, 3, 2, 2, 2, 1, 2, 2, 1,
4, 2, 2, 2, 2, 2, 2, 2, 2, 3, 4, 1, 2, 4, 4, 1, 2, 3,
2, 3, 2, 1, 3, 4, 1, 3, 2, 4, 3, 3, 2, 3, 2, 4, 2, 2,
2, 1, 1, 3, 4, 3, 3, 2, 2, 3, 4, 3, 3, 3, 2, 1, 3, 2,
4, 4, 4, 2, 3, 3, 3, 4, 2, 2, 2, 3, 2, 2, 3, 4, 2, 2,
2, 4, 4, 4, 4, 2, 4, 3, 3, 4, 2, 3, 4, 3, 2, 3, 4, 4,
4, 4, 3, 2, 1, 2, 1, 4, 3, 4, 3, 2, 2, 4, 2, 4, 2, 3,
3, 4, 3, 4, 3, 2, 4, 4, 2, 3, 3, 3, 4, 2, 2, 4, 3, 2,
4, 4, 2, 2, 3, 2, 3, 4, 4, 3, 4, 4, 1, 3, 3, 3, 3, 4,
4, 4, 4, 2, 2, 4, 4, 2, 2, 4, 3, 4, 3, 3, 3, 1, 3, 3,
4, 4, 4, 3, 4, 2, 3, 3, 2, 4, 2, 4, 4, 3, 3, 4, 2, 4,
3, 2, 1, 4, 3, 4, 2, 2, 2, 4, 4, 3, 4, 2, 1, 2, 4, 2,
4, 2, 3, 2, 2, 2, 2, 3, 2, 4, 4, 1, 2, 2, 2, 4, 3, 2,
4, 1, 3, 2, 2, 3, 4, 4, 1, 4, 2, 1, 4, 1, 1, 1, 2, 3,
1, 2, 2, 2, 4, 1, 1, 2, 2, 2, 2, 2, 3, 2, 2, 3, 2, 2,
3, 4, 3, 3, 2, 1, 1, 3, 1, 3, 2, 3, 4, 4, 3, 4, 1, 3,
3, 3, 2, 2, 2, 3, 4, 2, 4, 2, 2, 3, 3, 2, 4, 1, 2, 2,
4, 2, 1, 4, 4, 2, 3, 3, 4, 2, 3, 3, 3, 2, 2, 4, 4, 2,
1, 3, 3, 2, 3, 2, 2, 4, 4, 4, 1, 3, 1, 3, 4, 3, 3, 2,
2, 2, 2, 4, 2, 4, 3, 2, 4, 2, 2, 2, 3, 4, 4, 2, 2, 2,
2, 3, 3, 4, 3, 4, 1, 3, 4, 2, 3, 2, 3, 1, 2, 3, 2, 1,
3, 2, 4, 4, 2, 4, 4, 4, 4, 2, 3, 2, 4, 3, 4, 3, 4, 2,
2, 3, 4, 2, 3, 2, 2, 3, 4, 3, 4, 1, 2, 4, 4, 4, 2, 3,
4, 4, 4, 2, 4, 1, 2, 2, 3, 4, 4, 4, 3, 4, 2, 1, 4, 2,
3, 2, 4, 4, 2, 4, 4, 2, 1, 4, 3, 4, 1, 3, 3, 3, 2, 3,
3, 1, 2, 3, 2, 2, 3, 1, 4, 2, 2, 3, 4, 2, 4, 3, 3, 2,
3, 4, 4, 1, 2, 3, 4, 3, 2, 3, 3, 4, 4, 2, 3, 2, 4, 4,
4, 3, 1, 4, 4, 4, 4, 4, 2, 4, 2, 3, 3, 4, 4, 2, 4, 3,
4, 4, 4, 3, 2, 4, 2, 2, 3, 4, 3, 3, 2, 1, 1, 4, 2, 3,
4, 4, 4, 2, 1, 4, 3, 2, 4, 4, 2, 1, 3, 1, 2, 2, 4, 2,
3, 2, 3, 1, 4, 3, 2, 2, 4, 2, 2, 4, 2, 4, 3, 3, 2, 2,
2, 1, 3, 3, 2, 3, 4, 2, 3, 2, 4, 2, 1, 3, 2, 2, 3, 4,
4, 2, 3, 4, 4, 2, 4, 4, 4, 2, 3, 4, 3, 4, 3, 2, 3, 2,
3, 3, 2, 3, 3, 2, 2, 4, 1, 3, 2, 4, 2, 3, 4, 3, 4, 2,
2, 4, 3, 2, 3, 3, 3, 3, 3, 3, 2, 4, 3, 3, 4, 2, 3, 3,
3, 4, 1, 4, 3, 3, 4, 3, 2, 3, 4, 4, 4, 4, 3, 4, 4, 4,
2, 3, 3, 3, 3, 2, 3, 3, 2, 4, 3, 2, 4, 4, 2, 2, 2, 1,
4, 1, 2, 3, 4, 2, 4, 2, 3, 3, 4, 3, 3, 3, 3, 4, 4, 3,
2, 4, 3, 4, 2, 4, 3, 2, 2, 2, 2, 2, 4, 3, 3, 2, 4, 2,
4, 4, 4, 3, 3, 3, 3, 4, 1, 1, 2, 2, 3, 1, 1, 1, 3, 2,
2, 2, 4, 3, 2, 3, 4, 3, 4, 4, 4, 3, 3, 4, 2, 4, 2, 4,
3, 4, 1, 4, 1, 3, 1, 3, 2, 4, 1, 3, 4, 1, 4, 3, 4, 4,
1, 2, 2, 3, 3, 3, 2, 3, 4, 2, 3, 4, 2, 1, 2, 2, 3, 4,
4, 2, 2, 4, 2, 1, 3, 4, 4, 3, 3, 1, 1, 2, 4, 3, 1, 1,
4, 2, 2, 1, 2, 2, 2, 2, 2, 1, 3, 2, 1, 2, 2, 4, 4, 2,
4, 3, 4, 4, 4, 2, 4, 3, 3, 3, 1, 2, 1, 2, 3, 3, 2, 3,
2, 2, 4, 4, 1, 3, 1, 2, 2, 2, 3, 2, 2, 1, 3, 1, 2, 4,
3, 1, 2, 3, 4, 4, 4, 1, 2, 2, 4, 2, 3, 3, 3, 1, 4, 4,
2, 2, 3, 1, 3, 2, 1, 4, 4, 1, 1, 4, 4, 3, 2, 2, 3, 2,
2, 3, 3, 1, 2, 2, 4, 2, 2, 4, 3, 2, 4, 4, 3, 4, 3, 1,
3, 4, 2, 4, 2, 3, 2, 2, 3, 2, 2, 2, 4, 2, 3, 2, 3, 4,
3, 2, 1, 3, 4, 2, 4, 4, 1, 3, 2, 1, 2, 3, 1, 1, 2, 2,
2, 4, 3, 2, 4, 2, 4, 4, 2, 4, 4, 2, 1, 2, 2, 2, 3, 3,
2, 3, 2, 3, 2, 4, 3, 4, 4, 3, 2, 1, 1, 3, 2, 4, 4, 3,
4, 4, 3, 2, 2, 2, 4, 4, 4, 1, 3, 4, 1, 2, 2, 2, 2, 4,
3, 3, 2, 3, 3, 2, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 2,
1, 2, 2, 2, 4, 1, 4, 4, 2, 4, 4, 3, 4, 1, 3, 4, 2, 1,
3, 4, 2, 4, 4, 3, 4, 3, 3, 1, 2, 3, 1, 3, 1, 3, 4, 4,
4, 4, 3, 3, 4, 3, 3, 3, 2, 3, 2, 3, 3, 3, 3, 4, 4, 4,
2, 3, 2, 4, 2, 2, 2, 3, 3, 4, 2, 4, 2, 1, 2, 2, 3, 2,
3, 4, 2, 2, 4, 3, 2, 2, 4, 4, 4, 2, 4, 2, 2, 4, 3, 3,
2, 2, 4, 2, 4, 3, 2, 3, 2, 2, 4, 3, 3, 4, 3, 4, 3, 2,
4, 3, 2, 2, 2, 4, 2, 2, 4, 4, 4, 4, 3, 3, 1, 1, 3, 4,
1, 3, 3, 4, 3, 4, 3, 3, 3, 2, 3, 3, 3, 4, 4, 2, 2, 3,
4, 2, 1, 3, 2, 2, 2, 3, 2, 4, 3, 4, 4, 4, 4, 4, 3, 2,
4, 2, 3, 1, 3, 4, 3, 2, 2, 2, 2, 1, 3, 2, 2, 3, 2, 2,
3, 4, 3, 3, 2, 1, 1, 3, 1, 3, 2, 3, 4, 4, 3, 4, 1, 3,
3, 3, 2, 2, 2, 3, 4, 2, 4, 2, 2, 3, 3, 2, 4, 1, 2, 2,
4, 2, 1, 4, 4, 2, 3, 3, 4, 2, 3, 3, 3, 2, 2, 4, 4, 2,
1, 3, 3, 2, 3, 2, 2, 4, 4, 4, 1, 3, 1, 3, 4, 3, 3, 2,
2, 2, 2, 4, 2, 4, 3, 2, 4, 2, 2, 2, 3, 4, 4, 2, 2, 2,
2, 3, 3, 4, 3, 4, 1, 3, 4, 2, 3, 2, 3, 1, 2, 3, 2, 1,
3, 2, 4, 4, 2, 4, 4, 4, 4, 2, 3, 2, 4, 3, 4, 3, 4, 2,
2, 3, 4, 2, 3, 2, 2, 3, 4, 3, 4, 1, 2, 4, 4, 4, 2, 3,
4, 4, 4, 2, 4, 1, 2, 2, 3, 4, 4, 4, 3, 4, 2, 1, 4, 2,
3, 2, 4, 4, 2, 4, 4, 2, 1, 4, 3, 4, 1, 3, 3, 3, 2, 3,
3, 1, 2, 3, 2, 2, 3, 1, 4, 2, 2, 3, 4, 2, 4, 3, 3, 2,
3, 4, 4, 1, 2, 3, 4, 3, 2, 3, 3, 4, 4, 2, 3, 2, 4, 4,
4, 3, 1, 4, 4, 4, 4, 4, 2, 4, 2, 3, 3, 4, 4, 2, 4, 3,
4, 4, 4, 3, 2, 4, 2, 2, 3, 4, 3, 3, 2, 1, 1, 4, 2, 3,
4, 4, 4, 2, 1, 4, 3, 2, 4, 4, 2, 1, 3, 1, 2, 2, 4, 2,
3, 2, 3, 1, 4, 3, 2, 2, 4, 2, 2, 4, 2, 4, 3, 3, 2, 2,
2, 1, 3, 3, 2, 3, 4, 2, 3, 2, 4, 2, 1, 3, 2, 2, 3, 4,
4, 2, 3, 4, 4, 2, 4, 4, 4, 2, 3, 4, 3, 4, 3, 2, 3, 2,
3, 3, 2, 3, 3, 2, 2, 4, 1, 3, 2, 4, 2, 3, 4, 3, 4, 2,
2, 4, 3, 2, 3, 3, 3, 3, 3, 3, 2, 4, 3, 3, 4, 2, 3, 3,
3, 4, 1, 4, 3, 3, 4, 3, 2, 3, 4, 4, 4, 4, 3, 4, 4, 4,
2, 3, 3, 3, 3, 2, 3, 3, 2, 4, 3, 2, 4, 4, 2, 2, 2, 1,
4, 1, 2, 3, 4, 2, 4, 2, 3, 3, 4, 3, 3, 3, 3, 4, 4, 3,
2, 4, 3, 4, 2, 4, 3, 2, 2, 2, 2, 2, 4, 3, 3, 2, 4, 2,
4, 4, 4, 3, 3, 3, 3, 4, 1, 1, 2, 2, 3, 1, 1, 1, 3, 2,
2, 2, 4, 3, 2, 3, 4, 3, 4, 4, 4, 3, 3, 4, 2, 4, 2, 4,
3, 4, 1, 4, 1, 3, 1, 3, 2, 4, 1, 3, 4, 1, 4, 3, 4, 4,
1, 2, 2, 3, 3, 3, 2, 3, 4, 2, 3, 4, 2, 1, 2, 2, 3, 4,
4, 2, 2, 4, 2, 2, 1, 3, 4, 4, 3, 3, 1, 1, 2, 4, 3, 1,
1, 4, 2, 2, 1, 2, 2, 2, 2, 2, 1, 3, 2, 1, 2, 2, 4, 4,
2, 4, 3, 4, 4, 4, 2, 4, 3, 3, 3, 1, 2, 1, 2, 3, 3, 2,
3, 2, 2, 4, 4, 1, 3, 1, 2, 2, 2, 3, 2, 2, 1, 3, 1, 2,
4, 3, 1, 2, 3, 4, 4, 4, 1, 2, 2, 4, 2, 3, 3, 3, 1, 4,
4, 2, 2, 3, 1, 3, 2, 1, 4, 4, 1, 1, 4, 4, 3, 2, 2, 3,
2, 2, 3, 3, 1, 2, 2, 4, 2, 2, 4, 3, 2, 4, 4, 3, 4, 3,
1, 3, 4, 2, 4, 2, 3, 2, 2, 3, 2, 2, 2, 4, 2, 3, 2, 3,
4, 3, 2, 1, 3, 4, 2, 4, 4, 1, 3, 2, 1, 2, 3, 1, 1, 2,
2, 2, 4, 3, 2, 4, 2, 4, 4, 2, 4, 4, 2, 1, 2, 2, 2, 3,
3, 2, 3, 2, 3, 2, 4, 3, 4, 4, 3, 2, 1, 1, 3, 2, 4, 4,
3, 4, 4, 3, 2, 2, 2, 4, 4, 4, 1, 3, 4, 1, 2, 2, 2, 2,
4, 3, 3, 2, 3, 3, 2, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3,
2, 1, 2, 2, 2, 2, 4, 1, 4, 4, 2, 4, 4, 3, 4, 1, 3, 4,
2, 1, 3, 4, 2, 4, 4, 3, 4, 3, 3, 1, 2, 3, 1, 3, 1, 3,
4, 4, 4, 4, 3, 3, 3, 4, 3, 3, 3, 2, 3, 2, 3, 3, 3, 3,
4, 4, 4, 2, 3, 2, 4, 2, 2, 2, 3, 3, 4, 2, 4, 2, 1, 2,
2, 3, 2, 3, 4, 2, 2, 4, 3, 2, 2, 4, 4, 4, 2, 4, 2, 2,
4, 3, 3, 2, 2, 4, 2, 4, 3, 2, 3, 2, 2, 4, 3, 3, 4, 3,
4, 3, 2, 4, 3, 2, 2, 2, 4, 2, 2, 4, 4, 4, 4, 3, 3, 1,
1, 3, 4, 1, 3, 3, 4, 3, 4, 3, 3, 3, 2, 3, 3, 3, 4, 4,
2, 2, 3, 4, 2, 1, 3, 2, 2, 2, 3, 2, 4, 3, 4, 4, 4, 4,
4, 3, 2, 4, 2, 3, 1, 3, 4, 3, 2, 2, 2, 2, 1, 4, 1, 2,
4, 3, 2, 4, 2, 4, 2, 3, 3, 4, 3, 1, 4, 1, 4, 1, 4, 2,
3, 2, 2, 3, 2, 4, 2, 2, 1, 2, 1, 2, 1, 2, 4, 2, 4, 3,
2, 3, 1, 3, 2, 1, 3, 3, 2, 2, 2, 1, 4, 2, 3, 2, 4, 3,
1, 2, 2, 2, 2, 4, 4, 4, 2, 4, 4, 4, 2, 4, 2, 4, 3, 4,
4, 3, 2, 4, 3, 4, 4, 3, 3, 2, 3, 2, 2, 4, 4, 2, 2, 2,
4, 2, 3, 1, 4, 2, 3, 1, 4, 2, 2, 4, 4, 2, 2, 4, 4, 3,
4, 2, 2, 2, 2, 1, 2, 3, 2, 2, 2, 2, 1, 2, 2, 2, 4, 3,
2, 2, 2, 4, 2, 3, 3, 2, 2, 4, 4, 1, 3, 3, 4, 3, 4, 2,
4, 3, 4, 2, 3, 2, 2, 3, 2, 4, 2, 2, 3, 2, 2, 4, 1, 3,
2, 4, 3, 2, 4, 3, 2, 1, 3, 4, 1, 3, 4, 2, 4, 3, 2, 2,
4, 2, 2, 3, 3, 2, 2, 1, 1, 4, 3, 3, 4, 1, 2, 3, 2, 4,
4, 2, 3, 1, 1, 3, 2, 4, 1, 4, 3, 4, 4, 3, 3, 4, 2, 4,
2, 3, 3, 3, 4, 2, 2, 3, 4, 2, 4, 3, 2, 4, 4, 2, 2, 2,
1, 3, 3, 1, 2, 3, 2, 2, 2, 2, 4, 4, 1, 2, 2, 3, 3, 4,
2, 2, 4, 2, 1, 4, 2, 4, 1, 4, 2, 2, 1, 4, 4, 2, 3, 2,
2, 2, 4, 4, 3, 4, 1, 2, 2, 2, 4, 4, 2, 3, 4, 4, 2, 3,
2, 2, 1, 2, 3, 3, 4, 4, 4, 1, 4, 2, 3, 4, 3, 2, 3, 3,
2, 3, 4, 2, 4, 4, 4, 3, 3, 4, 4, 4, 2, 4, 2, 3, 4, 3,
1, 2, 3, 3, 2, 4, 3, 3, 4, 2, 1, 2, 4, 2, 1, 3, 1, 4,
2, 4, 2, 3, 2, 2, 2, 2, 3, 3, 3, 2, 3, 4, 2, 3, 2, 3,
2, 1, 3, 1, 1, 1, 1, 2, 3, 1, 3, 4, 4, 2, 3, 3, 2, 2,
2, 2, 3, 2, 4, 3, 4, 1, 2, 3, 4, 4, 2, 2, 2, 3, 2, 2,
4, 2, 3, 2, 2, 4, 3, 3, 2, 4, 4, 3, 3, 3, 3, 1, 2, 2,
3, 4, 4, 3, 2, 2, 2, 3, 3, 4, 1, 2, 4, 2, 2, 4, 2, 3,
2, 4, 2, 2, 3, 3, 2, 4, 2, 4, 4, 3, 2, 3, 4, 2, 3, 3,
2, 3, 4, 4, 1, 2, 3, 3, 4, 3, 4, 3, 1, 2, 2, 3, 2, 2,
2, 4, 4, 2, 2, 3, 4, 3, 2, 4, 4, 4, 2, 2, 1, 3, 4, 2,
4, 4, 3, 4, 3, 2, 4, 4, 2, 3, 2, 3, 4, 1, 2, 4, 3, 2,
4, 2, 4, 2, 3, 3, 4, 3, 1, 4, 1, 4, 1, 4, 2, 3, 2, 2,
3, 2, 4, 2, 2, 1, 2, 1, 2, 1, 2, 4, 2, 4, 3, 2, 3, 1,
3, 2, 1, 3, 3, 2, 2, 2, 1, 4, 2, 3, 2, 4, 3, 1, 2, 2,
2, 2, 4, 4, 4, 2, 4, 4, 4, 2, 4, 2, 4, 3, 4, 4, 3, 2,
4, 3, 4, 4, 3, 3, 2, 3, 2, 2, 4, 4, 2, 2, 2, 4, 2, 3,
1, 4, 2, 3, 1, 4, 2, 2, 4, 4, 2, 2, 4, 4, 3, 4, 2, 2,
2, 2, 1, 2, 3, 2, 2, 2, 2, 1, 2, 2, 2, 4, 3, 2, 2, 2,
4, 2, 3, 3, 2, 2, 4, 4, 1, 3, 3, 4, 3, 4, 2, 4, 3, 4,
2, 3, 2, 2, 3, 2, 4, 2, 2, 3, 2, 2, 4, 1, 3, 2, 4, 3,
2, 4, 3, 2, 1, 3, 4, 1, 3, 4, 2, 4, 3, 2, 2, 4, 2, 2,
3, 3, 2, 2, 1, 1, 4, 3, 3, 4, 1, 2, 3, 2, 4, 4, 2, 3,
1, 1, 3, 2, 4, 1, 4, 3, 4, 4, 3, 3, 4, 2, 4, 2, 3, 3,
3, 4, 2, 2, 3, 4, 2, 4, 3, 2, 4, 4, 2, 2, 2, 1, 3, 3,
1, 2, 3, 2, 2, 2, 2, 4, 4, 1, 2, 2, 3, 3, 4, 2, 2, 4,
2, 1, 4, 2, 4, 1, 4, 2, 2, 1, 4, 4, 2, 3, 2, 2, 2, 4,
4, 3, 4, 1, 2, 2, 2, 4, 4, 2, 3, 4, 4, 2, 3, 2, 2, 1,
2, 3, 3, 4, 4, 4, 1, 4, 2, 3, 4, 3, 2, 3, 3, 2, 3, 4,
2, 4, 4, 4, 3, 3, 4, 4, 4, 2, 4, 2, 3, 4, 3, 1, 2, 3,
3, 2, 4, 3, 3, 4, 2, 1, 2, 4, 2, 1, 3, 1, 4, 2, 4, 2,
3, 2, 2, 2, 2, 3, 3, 3, 2, 3, 4, 2, 3, 2, 3, 2, 1, 3,
1, 1, 1, 1, 2, 3, 1, 3, 4, 4, 2, 3, 3, 2, 2, 2, 2, 3,
2, 4, 3, 4, 1, 2, 3, 4, 4, 2, 2, 2, 3, 2, 2, 4, 2, 3,
2, 2, 4, 3, 3, 2, 4, 4, 3, 3, 3, 3, 1, 2, 2, 3, 4, 4,
3, 2, 2, 2, 3, 3, 4, 1, 2, 4, 2, 2, 4, 2, 3, 2, 4, 2,
2, 3, 3, 2, 4, 2, 4, 4, 3, 2, 3, 4, 2, 3, 3, 2, 3, 4,
4, 1, 2, 3, 3, 4, 3, 4, 3, 1, 2, 2, 3, 2, 2, 2, 4, 4,
2, 2, 3, 4, 3, 2, 4, 4, 4, 2, 2, 1, 3, 4, 2, 4, 4, 3,
4, 3, 2, 4, 4, 2, 3, 2, 3, 4, 3, 1, 2, 2, 3, 4, 2, 4,
2, 4, 3, 2, 3, 4, 2, 2, 3, 1, 1, 4, 2, 3, 2, 2, 3, 4,
2, 1, 2, 2, 2, 4, 3, 3, 3, 2, 4, 2, 4, 4, 4, 2, 2, 4,
4, 4, 1, 2, 4, 2, 2, 4, 3, 3, 4, 4, 4, 4, 2, 3, 4, 2,
4, 2, 4, 2, 1, 3, 3, 2, 1, 2, 3, 4, 4, 2, 1, 2, 4, 3,
1, 4, 2, 2, 2, 3, 2, 4, 2, 2, 2, 1, 2, 2, 2, 3, 3, 2,
2, 4, 2, 2, 2, 4, 3, 1, 3, 2, 4, 2, 2, 4, 4, 1, 3, 3,
2, 3, 4, 2, 1, 2, 2, 3, 4, 3, 2, 3, 2, 1, 3, 4, 2, 2,
4, 3, 3, 2, 2, 2, 3, 2, 2, 1, 2, 2, 1, 2, 3, 2, 4, 2,
4, 2, 2, 2, 3, 1, 2, 3, 2, 4, 4, 2, 4, 2, 2, 2, 1, 1,
1, 2, 1, 3, 2, 1, 4, 2, 4, 3, 2, 4, 3, 4, 2, 1, 2, 2,
3, 4, 1, 4, 4, 1, 2, 4, 2, 4, 1, 2, 2, 2, 3, 4, 4, 4,
3, 1, 4, 2, 2, 2, 2, 2, 4, 3, 4, 2, 4, 3, 4, 2, 4, 2,
4, 3, 3, 4, 2, 2, 2, 3, 3, 2, 2, 3, 2, 1, 4, 4, 2, 2,
2, 2, 3, 3, 2, 2, 3, 2, 4, 4, 1, 4, 2, 2, 2, 3, 3, 4,
2, 2, 2, 2, 2, 4, 3, 4, 1, 2, 4, 2, 2, 2, 4, 4, 1, 4,
4, 4, 1, 4, 2, 3, 1, 4, 4, 2, 4, 2, 3, 4, 2, 4, 2, 4,
4, 4, 3, 3, 4, 3, 4, 2, 3, 2, 4, 3, 3, 3, 2, 3, 3, 4,
4, 1, 3, 2, 3, 4, 4, 3, 3, 2, 2, 4, 4, 3, 2, 2, 1, 2,
1, 4, 1, 2, 2, 4, 2, 2, 3, 4, 1, 3, 3, 3, 2, 2, 3, 4,
1, 3, 3, 1, 2, 1, 1, 2, 2, 2, 3, 4, 4, 4, 1, 4, 1, 3,
4, 3, 3, 4, 3, 3, 2, 2, 2, 4, 3, 4, 2, 2, 2, 4, 3, 2,
3, 2, 3, 2, 1, 2, 3, 4, 3, 2, 4, 1, 1, 3, 3, 4, 2, 3,
2, 2, 2, 2, 2, 3, 3, 2, 2, 2, 3, 4, 3, 3, 4, 4, 2, 2,
2, 2, 4, 4, 2, 3, 3, 1, 4, 2, 1, 3, 2, 1, 4, 2, 2, 1,
2, 4, 2, 2, 2, 2, 4, 2, 3, 3, 2, 3, 4, 2, 1, 4, 3, 1,
2, 1, 2, 2, 3, 2, 3, 2, 2, 2, 2, 4, 2, 4, 4, 2, 2, 4,
3, 4, 3, 4, 2, 1, 4, 3, 4, 2, 2, 1, 4, 3, 3, 3, 3, 4,
2, 3, 1, 1, 2, 2, 2, 1, 4, 4, 2, 1, 2, 3, 3, 4, 3, 2,
3, 4, 3, 2, 3, 1, 3, 3, 4, 4, 4, 2, 2, 2, 4, 2, 2, 1,
3, 3, 4, 2, 2, 4, 1, 3, 3, 2, 2, 2, 2, 3, 4, 2, 2, 3,
4, 4, 2, 3, 2, 1, 3, 3, 2, 2, 2, 3, 4, 3, 4, 2, 4, 3,
4, 2, 4, 3, 3, 3, 3, 4, 1, 4, 2, 2, 2, 2, 1, 4, 4, 4,
4, 3, 3, 4, 3, 2, 1, 4, 2, 4, 4, 3, 2, 3, 2, 3, 4, 3,
2, 2, 4, 2, 4, 2, 1, 4, 4, 1, 4, 1, 3, 2, 4, 2, 2, 1,
2, 1, 4, 3, 2, 4, 3, 4, 2, 4, 2, 4, 3, 1, 4, 2, 3, 2,
4, 4, 2, 1, 2, 2, 3, 2, 3, 3, 3, 4, 2, 3, 3, 2, 3, 3,
3, 4, 1, 3, 3, 2, 3, 4, 4, 2, 1, 2, 4, 2, 2, 3, 2, 2,
1, 4, 2, 3, 4, 3, 2, 2, 2, 3, 2, 3, 4, 3, 3, 3, 4, 3,
2, 2, 3, 3, 4, 3, 3, 1, 4, 4, 2, 2, 2, 3, 3, 2, 4, 4,
2, 1, 2, 2, 2, 4, 1, 3, 4, 3, 2, 4, 4, 2, 4, 4, 1, 2,
2, 2, 2, 3, 4, 1, 4, 2, 4, 4, 4, 4, 4, 2, 2, 2, 2, 4,
1, 1, 2, 2, 3, 4, 4, 4, 3, 3, 4, 2, 4, 2, 4, 1, 4, 4,
2, 2, 4, 1, 2, 3, 2, 2, 2, 4, 2, 2, 2, 4, 2, 3, 3, 3,
2, 4, 2, 4, 2, 2, 4, 1, 3, 3, 2, 2, 2, 3, 2, 4, 2, 2,
2, 4, 2, 1, 2, 2, 1, 3, 4, 1, 2, 2, 2, 2, 2, 4, 3, 2,
2, 2, 3, 3, 3, 4, 4, 1, 4, 4, 4, 3, 4, 2, 2, 3, 1, 2,
1, 3, 2, 1, 1, 2, 3, 3, 4, 2, 3, 2, 4, 3, 4, 2, 2, 2,
3, 2, 3, 4, 1, 2, 1, 4, 2, 4, 1, 4, 2, 4, 3, 4, 2, 3,
4, 4, 2, 4, 4, 2, 2, 1, 2, 2, 2, 2, 2, 4, 4, 4, 4, 1,
2, 2, 3, 3, 4, 4, 2, 4, 2, 3, 4, 2, 2, 2, 2, 2, 3, 3,
4, 2, 2, 2, 3, 2, 2, 2, 2, 3, 1, 4, 4, 2, 3, 2, 2, 2,
3, 2, 2, 1, 3, 2, 2, 3, 4, 3, 4, 3, 3, 4, 3, 2, 3, 2,
3, 4, 3, 1, 2, 2, 4, 2, 3, 3, 4, 3, 2, 4, 2, 3, 4, 2,
4, 2, 2, 3, 4, 3, 1, 3, 3, 4, 3, 4, 4, 2, 3, 4, 4, 2,
2, 1, 2, 3, 3, 3, 1, 3, 4, 4, 1, 4, 2, 2, 3, 4, 1, 2,
3, 3, 3, 4, 2, 4, 1, 2, 4, 2, 3, 4, 2, 2, 2, 2, 4, 3,
2, 2, 4, 2, 3, 4, 2, 3, 2, 3, 2, 3, 3, 1, 4, 3, 2, 4,
2, 2, 4, 2, 2, 3, 2, 2, 4, 4, 4, 2, 2, 4, 4, 3, 4, 3,
4, 4, 1, 2, 2, 2, 2, 4, 3, 2, 2, 1, 2, 4, 2, 4, 2, 4,
4, 4, 1, 2, 2, 4, 4, 2, 3, 3, 2, 4, 3, 3, 3, 4, 3, 4,
4, 4, 3, 4, 3, 2, 4, 2, 2, 2, 3, 3, 2, 4, 1, 4, 4, 2,
1, 3, 2, 4, 2, 4, 4, 2, 2, 2, 1, 2, 2, 4, 4, 1, 3, 2,
3, 4, 1, 4, 4, 3, 4, 3, 2, 2, 4, 1, 4, 4, 2, 4, 2, 2,
2, 2, 3, 3, 4, 2, 4, 4, 2, 2, 4, 2, 3, 1, 2, 2, 4, 2,
3, 4, 4, 2, 2, 3, 3, 2, 2, 4, 2, 2, 4, 2, 2, 2, 1, 2,
1, 3, 1, 1, 4, 3, 4, 2, 2, 2, 4, 4, 2, 4, 2, 2, 4, 1,
2, 2, 4, 4, 3, 2, 4, 4, 1, 2, 2, 3, 1, 2, 4, 3, 2, 1,
2, 4, 2, 2, 4, 2, 3, 1, 2, 4, 3, 3, 2, 2, 4, 1, 1, 2,
4, 3, 2, 3, 2, 2, 1, 2, 4, 4, 4, 4, 2, 3, 3, 3, 2, 4,
3, 1, 1, 2, 3, 2, 2, 2, 2, 2, 3, 4, 1, 2, 2, 4, 4, 2,
2, 4, 2, 4, 4, 3, 3, 4, 3, 1, 2, 4, 2, 2, 2, 3, 3, 3,
1, 2, 1, 1, 3, 3, 1, 2, 3, 1, 1, 4, 1, 2, 3, 3, 2, 4,
1, 3, 1, 4, 4, 3, 4, 2, 4, 3, 2, 4, 4, 2, 2, 3, 3, 2,
2, 1, 1, 4, 2, 1, 2, 3, 1, 2, 2, 3, 4, 2, 2, 1, 1, 2,
1, 1, 4, 2, 2, 2, 1, 3, 1, 1, 4, 2, 2, 3, 2, 2, 4, 1,
4, 1, 3, 4, 2, 2, 3, 4, 2, 3, 2, 2, 2, 2, 2, 3, 3, 2,
2, 2, 3, 4, 3, 3, 4, 4, 2, 2, 2, 2, 4, 4, 2, 3, 3, 1,
4, 2, 1, 3, 2, 1, 4, 2, 2, 1, 2, 4, 2, 2, 2, 2, 4, 2,
3, 3, 2, 3, 4, 2, 1, 4, 3, 1, 2, 1, 2, 2, 3, 2, 3, 2,
2, 2, 2, 4, 2, 4, 4, 2, 2, 4, 3, 4, 3, 4, 2, 1, 4, 3,
4, 2, 2, 1, 4, 3, 3, 3, 3, 4, 2, 3, 1, 1, 2, 2, 2, 1,
4, 4, 2, 1, 2, 3, 3, 4, 3, 2, 3, 4, 3, 2, 3, 1, 3, 3,
4, 4, 4, 2, 2, 2, 4, 2, 2, 1, 3, 3, 4, 2, 2, 4, 1, 3,
3, 2, 2, 2, 2, 3, 4, 2, 2, 3, 4, 4, 2, 3, 2, 1, 3, 3,
2, 2, 2, 3, 4, 3, 4, 2, 4, 3, 4, 2, 4, 3, 3, 3, 3, 4,
1, 4, 2, 2, 2, 2, 1, 4, 4, 4, 4, 3, 3, 4, 3, 2, 1, 4,
2, 4, 4, 3, 2, 3, 2, 3, 4, 3, 2, 2, 4, 2, 4, 2, 1, 4,
4, 1, 4, 1, 3, 2, 4, 2, 2, 1, 2, 1, 4, 3, 2, 4, 3, 4,
2, 4, 2, 4, 3, 1, 4, 2, 3, 2, 4, 4, 2, 1, 2, 2, 3, 2,
3, 3, 3, 4, 2, 3, 3, 2, 3, 3, 3, 4, 1, 3, 3, 2, 3, 4,
4, 2, 1, 2, 4, 2, 2, 3, 2, 2, 1, 4, 2, 3, 4, 3, 2, 2,
2, 3, 2, 3, 4, 3, 3, 3, 4, 3, 2, 2, 3, 3, 4, 3, 3, 1,
4, 4, 2, 2, 2, 3, 3, 2, 4, 4, 2, 1, 2, 2, 2, 4, 1, 3,
4, 3, 2, 4, 4, 2, 4, 4, 1, 2, 2, 2, 2, 3, 4, 1, 4, 2,
4, 4, 4, 4, 4, 2, 2, 2, 2, 4, 1, 1, 2, 2, 3, 4, 4, 4,
3, 3, 4, 2, 4, 2, 4, 1, 4, 4, 2, 2, 4, 1, 2, 3, 2, 2,
2, 4, 2, 2, 2, 4, 2, 3, 3, 3, 2, 4, 2, 4, 2, 2, 4, 1,
3, 3, 2, 2, 2, 3, 2, 4, 2, 2, 2, 4, 2, 1, 2, 2, 1, 3,
4, 1, 2, 2, 2, 2, 2, 4, 3, 2, 2, 2, 3, 3, 3, 4, 4, 1,
4, 4, 4, 3, 4, 2, 2, 3, 1, 2, 1, 3, 2, 1, 1, 2, 3, 3,
4, 2, 3, 2, 4, 3, 4, 2, 2, 2, 3, 2, 3, 4, 1, 2, 1, 4,
2, 4, 1, 4, 2, 4, 3, 4, 2, 3, 4, 4, 2, 4, 4, 2, 2, 1,
2, 2, 2, 2, 2, 4, 4, 4, 4, 1, 2, 2, 3, 3, 4, 4, 2, 4,
2, 3, 4, 2, 2, 2, 2, 2, 3, 3, 4, 2, 2, 2, 3, 2, 2, 2,
2, 3, 1, 4, 4, 2, 3, 2, 2, 2, 3, 2, 2, 1, 3, 2, 2, 3,
4, 3, 4, 3, 3, 4, 3, 2, 3, 2, 3, 4, 3, 1, 2, 2, 4, 2,
3, 3, 4, 3, 2, 4, 2, 3, 4, 2, 4, 2, 2, 3, 4, 3, 1, 3,
3, 4, 3, 4, 4, 2, 3, 4, 4, 2, 2, 1, 2, 3, 3, 3, 1, 3,
4, 4, 1, 4, 2, 2, 3, 4, 1, 2, 3, 3, 3, 4, 2, 4, 1, 2,
4, 2, 3, 4, 2, 2, 2, 2, 4, 3, 2, 2, 4, 2, 3, 4, 2, 3,
2, 3, 2, 3, 3, 1, 4, 3, 2, 4, 2, 2, 4, 2, 2, 3, 2, 2,
4, 4, 4, 2, 2, 4, 4, 3, 4, 3, 4, 4, 1, 2, 2, 2, 2, 4,
3, 2, 2, 1, 2, 4, 2, 4, 2, 4, 4, 4, 1, 2, 2, 4, 4, 2,
3, 3, 2, 4, 3, 3, 3, 4, 3, 4, 4, 4, 3, 4, 3, 2, 4, 2,
2, 2, 3, 3, 2, 4, 1, 4, 4, 2, 1, 3, 2, 4, 2, 4, 4, 2,
2, 2, 1, 2, 2, 4, 4, 1, 3, 2, 3, 4, 1, 4, 4, 3, 4, 3,
2, 2, 4, 1, 4, 4, 2, 4, 2, 2, 2, 2, 3, 3, 4, 2, 4, 4,
2, 2, 4, 2, 3, 1, 2, 2, 4, 2, 3, 4, 4, 2, 2, 3, 3, 2,
2, 4, 2, 2, 4, 2, 2, 2, 1, 2, 1, 3, 1, 1, 4, 3, 4, 2,
2, 2, 4, 4, 2, 4, 2, 2, 4, 1, 2, 2, 4, 4, 3, 2, 4, 4,
1, 2, 2, 3, 1, 2, 4, 3, 2, 1, 2, 4, 2, 2, 4, 2, 3, 1,
2, 4, 3, 3, 2, 2, 4, 1, 1, 2, 4, 3, 2, 3, 2, 2, 1, 2,
4, 4, 4, 4, 2, 3, 3, 3, 2, 4, 3, 1, 1, 2, 3, 2, 2, 2,
2, 2, 3, 4, 1, 2, 2, 4, 4, 2, 2, 4, 2, 4, 4, 3, 3, 4,
3, 1, 2, 4, 2, 2, 2, 3, 3, 3, 1, 2, 1, 1, 3, 3, 1, 2,
3, 1, 1, 4, 1, 2, 3, 3, 2, 4, 1, 3, 1, 4, 4, 3, 4, 2,
4, 3, 2, 4, 4, 2, 2, 3, 3, 2, 2, 1, 1, 4, 2, 1, 2, 3,
1, 2, 2, 3, 4, 2, 2, 1, 1, 2, 1, 1, 4, 2, 2, 2, 1, 3,
1, 1, 4, 2, 2, 3, 2, 2, 4, 1, 4, 1, 3, 4, 2, 2, 3, 4,
2, 3, 2, 4, 2, 2, 4, 1, 4, 3, 4, 4, 4, 2, 1, 2, 3, 3,
2, 2, 4, 4, 4, 2, 4, 3, 1, 2, 1, 3, 4, 3, 2, 1, 2, 2,
4, 2, 4, 4, 1, 4, 3, 4, 2, 2, 4, 1, 4, 1, 3, 3, 2, 2,
3, 4, 4, 1, 1, 2, 2, 4, 3, 4, 4, 2, 3, 3, 4, 2, 2, 3,
4, 2, 4, 1, 3, 2, 2, 1, 1, 2, 4, 4, 2, 4, 2, 3, 2, 1,
3, 2, 3, 4, 4, 3, 2, 2, 4, 2, 2, 2, 2, 1, 3, 2, 4, 2,
2, 4, 3, 2, 3, 2, 1, 1, 3, 1, 1, 1, 2, 2, 1, 1, 4, 2,
2, 2, 3, 4, 4, 4, 4, 2, 4, 1, 4, 2, 4, 4, 3, 4, 3, 3,
1, 3, 3, 3, 1, 4, 2, 2, 3, 2, 2, 4, 3, 1, 4, 2, 4, 4,
3, 2, 2, 4, 2, 2, 3, 4, 2, 2, 2, 3, 3, 3, 4, 3, 3, 2,
4, 3, 3, 4, 3, 2, 3, 4, 2, 4, 3, 2, 2, 2, 3, 3, 4, 4,
3, 2, 4, 3, 4, 2, 4, 3, 4, 2, 3, 2, 1, 2, 3, 4, 2, 3,
4, 4, 4, 4, 2, 2, 4, 3, 3, 4, 2, 2, 4, 2, 2, 1, 2, 4,
4, 2, 2, 2, 4, 4, 3, 2, 2, 2, 3, 4, 3, 4, 3, 3, 3, 2,
2, 4, 2, 3, 3, 3, 2, 4, 4, 4, 3, 2, 4, 2, 3, 3, 2, 4,
4, 2, 4, 2, 1, 2, 3, 2, 3, 1, 4, 2, 4, 2, 2, 2, 2, 1,
2, 3, 3, 4, 3, 3, 3, 2, 3, 2, 3, 3, 4, 3, 2, 2, 4, 2,
2, 2, 1, 2, 3, 2, 4, 3, 2, 1, 3, 3, 2, 2, 4, 1, 3, 2,
4, 2, 1, 2, 2, 2, 2, 4, 4, 3, 1, 3, 2, 2, 4, 3, 4, 2,
2, 4, 3, 2, 2, 2, 1, 2, 3, 3, 2, 3, 2, 4, 2, 4, 2, 2,
2, 4, 2, 4, 4, 2, 4, 2, 3, 2, 1, 2, 4, 3, 3, 2, 1, 3,
2, 4, 3, 4, 4, 2, 3, 4, 4, 1, 2, 4, 2, 2, 2, 2, 2, 2,
2, 4, 4, 2, 2, 2, 2, 2, 4, 4, 2, 4, 2, 4, 4, 4, 2, 2,
3, 2, 4, 1, 1, 2, 4, 2, 4, 4, 3, 2, 4, 1, 2, 3, 2, 3,
4, 3, 2, 4, 3, 3, 3, 3, 3, 2, 3, 2, 2, 3, 2, 1, 4, 2,
4, 4, 2, 1, 3, 2, 2, 4, 2, 3, 3, 4, 2, 2, 2, 4, 2, 2,
3, 4, 3, 3, 3, 3, 4, 2, 1, 2, 2, 4, 2, 4, 2, 4, 1, 3,
2, 4, 4, 2, 4, 4, 2, 2, 2, 4, 2, 4, 3, 2, 4, 1, 4, 3,
4, 4, 2, 4, 4, 4, 4, 1, 4, 2, 2, 2, 2, 2, 3, 3, 4, 4,
4, 2, 2, 4, 1, 4, 4, 1, 2, 4, 3, 3, 4, 3, 4, 3, 2, 2,
3, 2, 2, 3, 2, 2, 2, 3, 2, 4, 4, 2, 2, 2, 4, 2, 2, 1,
3, 4, 2, 4, 4, 4, 2, 4, 1, 3, 2, 4, 3, 2, 4, 2, 4, 2,
2, 2, 2, 2, 2, 2, 1, 2, 4, 4, 2, 4, 2, 4, 2, 1, 2, 3,
3, 4, 4, 3, 2, 2, 2, 4, 3, 2, 2, 1, 4, 4, 3, 2, 4, 3,
3, 1, 2, 4, 4, 2, 2, 1, 4, 2, 2, 3, 4, 3, 2, 2, 2, 2,
2, 2, 4, 2, 4, 2, 2, 2, 2, 3, 4, 4, 3, 3, 4, 1, 3, 2,
3, 2, 2, 4, 3, 2, 4, 2, 3, 4, 3, 2, 2, 2, 4, 2, 3, 1,
2, 3, 2, 4, 4, 4, 1, 2, 1, 3, 3, 3, 1, 2, 2, 3, 1, 4,
4, 4, 2, 2, 2, 4, 1, 1, 3, 1, 4, 1, 2, 2, 4, 3, 4, 3,
4, 3, 3, 3, 2, 2, 2, 2, 4, 2, 2, 2, 2, 4, 3, 1, 4, 4,
4, 1, 4, 2, 4, 2, 4, 4, 1, 2, 3, 2, 2, 4, 2, 4, 4, 4,
2, 2, 4, 3, 3, 3, 2, 4, 4, 2, 4, 2, 2, 4, 2, 4, 1, 1,
4, 4, 1, 3, 4, 2, 2, 3, 3, 3, 2, 4, 2, 3, 2, 2, 4, 3,
4, 2, 4, 4, 3, 4, 2, 2, 2, 1, 3, 3, 2, 3, 3, 2, 1, 2,
2, 4, 4, 2, 1, 2, 3, 3, 4, 3, 2, 2, 2, 3, 3, 4, 2, 2,
2, 2, 2, 2, 2, 4, 4, 3, 2, 3, 3, 4, 2, 4, 2, 4, 3, 3,
4, 2, 3, 4, 4, 3, 2, 2, 3, 4, 3, 1, 2, 4, 3, 4, 3, 3,
3, 4, 4, 4, 2, 1, 4, 2, 3, 2, 3, 4, 2, 2, 3, 3, 2, 4,
4, 2, 2, 1, 4, 2, 1, 3, 1, 2, 2, 2, 2, 3, 1, 4, 3, 3,
3, 2, 4, 3, 2, 4, 3, 3, 2, 4, 1, 2, 4, 4, 4, 2, 2, 4,
2, 2, 2, 3, 1, 2, 3, 1, 3, 2, 3, 3, 3, 4, 4, 2, 4, 3,
4, 3, 1, 2, 4, 1, 2, 3, 2, 4, 2, 4, 4, 4, 1, 4, 1, 2,
2, 2, 3, 3, 2, 3, 1, 3, 4, 2, 2, 2, 4, 2, 1, 2, 4, 2,
2, 2, 4, 2, 4, 2, 1, 2, 4, 2, 1, 3, 3, 3, 2, 2, 4, 1,
2, 1, 3, 1, 1, 2, 1, 4, 4, 2, 4, 1, 2, 3, 4, 2, 3, 3,
3, 1, 2, 2, 2, 4, 1, 4, 2, 3, 2, 4, 2, 3, 2, 4, 2, 2,
4, 1, 4, 3, 4, 4, 4, 2, 1, 2, 3, 3, 2, 2, 4, 4, 4, 2,
4, 3, 1, 2, 1, 3, 4, 3, 2, 1, 2, 2, 4, 2, 4, 4, 1, 4,
3, 4, 2, 2, 4, 1, 4, 1, 3, 3, 2, 2, 3, 4, 4, 1, 1, 2,
2, 4, 3, 4, 4, 2, 3, 3, 4, 2, 2, 3, 4, 2, 4, 1, 3, 2,
2, 1, 1, 2, 4, 4, 2, 4, 2, 3, 2, 1, 3, 2, 3, 4, 4, 3,
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0.6146666, 0.613, 0.562, 0.4713334, 0.6463333, 0.5226667,
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"n_age": 4,
"n_edu": 4,
"n_state": 51,
"n_age_edu": 16,
"n_region_full": 5
}
| 54.918857
| 74
| 0.444926
| 115,693
| 409,475
| 1.574642
| 0.000985
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| 0.189263
| 0.211994
| 0.967279
| 0.93604
| 0.935688
| 0.902445
| 0.892856
| 0.878254
| 0
| 0.611206
| 0.272437
| 409,475
| 7,455
| 75
| 54.926224
| 0.000285
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| 0.000225
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| false
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| null | 0
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0
| 11
|
776a08626980ccfdfec67307844e648281221bc4
| 60,043
|
py
|
Python
|
snapshot_test.py
|
rwberendsen/aprilsnow
|
dbea6219928f0729a2d0000c4b3c272ee4e602e9
|
[
"MIT"
] | null | null | null |
snapshot_test.py
|
rwberendsen/aprilsnow
|
dbea6219928f0729a2d0000c4b3c272ee4e602e9
|
[
"MIT"
] | null | null | null |
snapshot_test.py
|
rwberendsen/aprilsnow
|
dbea6219928f0729a2d0000c4b3c272ee4e602e9
|
[
"MIT"
] | null | null | null |
from snowflake.connector import DictCursor, ProgrammingError
import logging
from util import run_and_fetchall, run
from test_unique_compound_key import test_unique_compound_key
from snapshot import snapshot
def _is_okay_valid_date_sequence(rows, do_zombie_check):
rows = sorted(rows, key=lambda x: x['_scd_valid_from_timestamp'])
if not len(rows):
return True
last_row = rows.pop(0)
while rows:
current_row = rows.pop(0)
if last_row['_scd_valid_to_timestamp'] is None:
if not do_zombie_check:
if last_row['_scd_deleted_timestamp'] is None:
return False
else:
return False
else:
if current_row['_scd_valid_from_timestamp'] < last_row['_scd_valid_to_timestamp']:
return False # no overlaps
if current_row['_scd_valid_from_timestamp'] > last_row['_scd_valid_to_timestamp']:
return False # no gaps, either
last_row = current_row
return True
def _is_okay_rows_are_different(rows):
rows = sorted(rows, key=lambda x: x['_scd_valid_from_timestamp'])
if not len(rows):
return True
cols_to_compare = frozenset(rows[0].keys()) - frozenset(['_scd_valid_from_timestamp', '_scd_valid_to_timestamp', '_scd_is_most_recent', '_scd_id',
'_scd_normalised_key', '_scd_deleted_timestamp', '_scd_created_timestamp', '_scd_last_modified_timestamp',
'_scd_created_by', '_scd_last_modified_by', '_scd_last_dml_action'])
last_row = rows.pop(0)
while rows:
current_row = rows.pop(0)
if all([current_row[col] == last_row[col] for col in cols_to_compare]) and last_row['_scd_deleted_timestamp'] is None:
return False
last_row = current_row
return True
def _is_okay_invariants_scd_table(rows, do_zombie_check=True):
"""Stuff that always has to hold, looking at the scd table alone. These are candidates for DBT tests on real data as well, although then, they might take a while to run."""
is_scd_id_unique = (len(frozenset([row['_scd_id'] for row in rows])) == len(rows))
if not is_scd_id_unique:
return False
is_most_recent_agrees_with_valid_to = all([
(row['_scd_is_most_recent'] and row['_scd_valid_to_timestamp'] is None) \
or \
(not row['_scd_is_most_recent'] and row['_scd_valid_to_timestamp'] is not None) for row in rows
])
if not is_most_recent_agrees_with_valid_to:
return False
most_recent_rows = [row for row in rows if row['_scd_is_most_recent']]
if not do_zombie_check:
most_recent_rows = [row for row in most_recent_rows if row['_scd_deleted_timestamp'] is None]
is_normalised_key_unique_in_most_recent_rows = (len(frozenset([row['_scd_normalised_key'] for row in most_recent_rows])) == len(most_recent_rows))
if not is_normalised_key_unique_in_most_recent_rows:
return False
is_all_non_null_valid_from = not any([row['_scd_valid_from_timestamp'] is None for row in rows])
if not is_all_non_null_valid_from:
return False
normalised_keys = frozenset([row['_scd_normalised_key'] for row in rows])
is_okay_valid_date_sequences = all([_is_okay_valid_date_sequence([row for row in rows if row['_scd_normalised_key'] == key], do_zombie_check) for key in normalised_keys])
if not is_okay_valid_date_sequences:
return False
is_okay_rows_are_different = all([_is_okay_rows_are_different([row for row in rows if row['_scd_normalised_key'] == key]) for key in normalised_keys])
if not is_okay_valid_date_sequences:
return False
is_deleted_always_later_than_valid_from = all([row['_scd_deleted_timestamp'] is None or row['_scd_deleted_timestamp'] > row['_scd_valid_from_timestamp'] for row in rows])
if not is_deleted_always_later_than_valid_from:
print('deleted from not later than valid_from')
return False
is_valid_to_always_later_than_valid_from = all([row['_scd_valid_to_timestamp'] is None or row['_scd_valid_to_timestamp'] > row['_scd_valid_from_timestamp'] for row in rows])
if not is_valid_to_always_later_than_valid_from:
print('valid_to not later than valid from')
return False
return True
def create_tables(conn, database, schema, ts_nodash_col, non_ts_nodash_columns, partition_columns=None, how_to_create='OR REPLACE'):
columns_str = ', '.join([f'{col} {type_}' for col, type_ in non_ts_nodash_columns.items()])
partition_columns_str = '' if not partition_columns else ', ' + ', '.join([f'{col} {non_ts_nodash_columns[col]} NOT NULL' for col in partition_columns])
run(conn, 'USE DATABASE IDENTIFIER(%(database)s);', params={'database': database})
run(conn, 'USE SCHEMA IDENTIFIER(%(schema)s);', params={'schema': schema})
run(conn, f'CREATE {how_to_create} TABLE tmp_in ({ts_nodash_col} VARCHAR, {columns_str});')
run(conn, f'CREATE {how_to_create} TABLE tmp_stage '
f'({ts_nodash_col} VARCHAR, {columns_str}'
', _scd_created_timestamp TIMESTAMP_NTZ NOT NULL DEFAULT SYSDATE()'
', _scd_normalised_key VARCHAR NOT NULL, _scd_created_by VARCHAR);')
run(conn, f'CREATE {how_to_create} TABLE tmp_changes '
f'({ts_nodash_col} VARCHAR, {columns_str}, _scd_normalised_key VARCHAR NOT NULL'
', _scd_id VARCHAR NOT NULL, _scd_valid_from_timestamp TIMESTAMP_NTZ NOT NULL, _scd_valid_to_timestamp TIMESTAMP_NTZ'
', _scd_deleted_timestamp TIMESTAMP_NTZ, _scd_is_most_recent BOOLEAN NOT NULL'
', _scd_last_dml_action VARCHAR, _scd_priority INT'
', _scd_created_timestamp TIMESTAMP_NTZ NOT NULL'
', _scd_last_modified_timestamp TIMESTAMP_NTZ NOT NULL'
', _scd_created_by VARCHAR, _scd_last_modified_by VARCHAR);')
run(conn, f'CREATE {how_to_create} TABLE tmp_scd '
f'({ts_nodash_col} VARCHAR, {columns_str}, _scd_normalised_key VARCHAR NOT NULL'
', _scd_id VARCHAR NOT NULL, _scd_valid_from_timestamp TIMESTAMP_NTZ NOT NULL, _scd_valid_to_timestamp TIMESTAMP_NTZ'
', _scd_deleted_timestamp TIMESTAMP_NTZ, _scd_is_most_recent BOOLEAN NOT NULL'
', _scd_last_dml_action VARCHAR'
', _scd_created_timestamp TIMESTAMP_NTZ NOT NULL'
', _scd_last_modified_timestamp TIMESTAMP_NTZ NOT NULL'
', _scd_created_by VARCHAR, _scd_last_modified_by VARCHAR);')
run(conn, f'CREATE {how_to_create} TABLE tmp_batch_metadata ({ts_nodash_col} VARCHAR NOT NULL{partition_columns_str}'
', _scd_created_timestamp TIMESTAMP_NTZ NOT NULL DEFAULT SYSDATE(), _scd_created_by VARCHAR'
', _scd_batch_metadata VARIANT);')
def is_scenario_1_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_two_rows and is_most_recent_always_true
def is_scenario_2_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce a duplicate row in the source table; only during the second step, where the changes are staged, will it be deduplicated.
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), ('20210609T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', fail_on_duplicates=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_two_rows and is_most_recent_always_true
def is_scenario_3_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# use partitions
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1},))
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_two_rows and is_most_recent_always_true
def is_scenario_4_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# use a column with values (y) that is not part of a unique key
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_two_rows and is_most_recent_always_true
def is_scenario_5_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# now in this table there are two batches worth of data
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), "
"('20210614T050000', 1, 1), ('20210614T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000')
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_three_rows and is_most_recent_not_always_true
def is_scenario_6_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce a deletion in the second batch (remember, each batch is considered to be a full load)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), "
"('20210614T050000', 1, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000')
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
is_a_deleted_row_present = any([row['_scd_deleted_timestamp'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_three_rows and is_most_recent_not_always_true and is_a_deleted_row_present
def is_scenario_7_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce a deletion in the second batch (remember, each batch is considered to be a full load)
# then, in the third batch, re-introduce a previously deleted row, without altering any of the values
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), "
"('20210614T050000', 1, 1), "
"('20210619T050000', 1, 1), ('20210619T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000')
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000')
# a third round to stage the third batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210619T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_four_rows = (len(rows) == 4)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
is_a_deleted_row_present = any([row['_scd_deleted_timestamp'] for row in rows])
is_a_deleted_invalidated_row_present = any([row['_scd_deleted_timestamp'] and not row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_four_rows and is_most_recent_not_always_true and is_a_deleted_row_present and is_a_deleted_invalidated_row_present
def is_scenario_8_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce NULL values in the values (y) and make sure it is not seen as an update (NULL = NULL evaluates to NULL in SQL)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, NULL), ('20210614T050000', 1, NULL);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000')
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_one_row and is_most_recent_always_true
def is_scenario_9_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce NULL values in the unique compound key (x) and make sure it is treated as an actual value
# (Sadly, in real life tables sometimes have no unique compound key, and we have to include columns that can be null in a "guessed" unique compound key in order to make
# rows unique in data observed so far.)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', NULL, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_one_row and is_most_recent_always_true
def is_scenario_10_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce NULL values in the unique compound key (x) and make sure it is treated as an actual value
# (Sadly, in real life tables sometimes have no unique compound key, and we have to include columns that can be null in a "guessed" unique compound key in order to make
# rows unique in data observed so far.)
# Also, add multiple rows with the same NULL compound key, and check that they are deduplicated as a single _scd_normalised_key (with an arbitrary row selected)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', NULL, 1), ('20210609T050000', NULL, 2);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', fail_on_duplicates=False)
run(conn, 'COMMIT;')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_one_row and is_most_recent_always_true
def is_scenario_11_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce NULL values in the unique compound key (x) and make sure it is treated as an actual value
# (Sadly, in real life tables sometimes have no unique compound key, and we have to include columns that can be null in a "guessed" unique compound key in order to make
# rows unique in data observed so far.)
# Also, check if we can update rows with a NULL value in a column in the compound key
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', NULL, 1), ('20210614T050000', NULL, 2);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000')
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_two_rows and is_most_recent_not_always_true
def is_scenario_12_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
# Check that partitions are handled okay, and that, if they are used, only rows in scd_table from those partitions will ever be marked for deletion
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210614T050000', 2, 2);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1},))
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210614T050000', partitions=({'x': 2},))
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
is_deleted_always_none = all([row['_scd_deleted_timestamp'] is None for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_two_rows and is_most_recent_always_true and is_deleted_always_none
def is_scenario_13_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x', 'y'))
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 3, 4), ('20210614T050000', 1, 2);")
run(conn, 'BEGIN TRANSACTION;')
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210614T050000', partitions=({'x': 1, 'y': 2},))
run(conn, 'COMMIT;')
# a second round to stage the second set of partitions for a batch dated Jun 9; however, for one of the partitions in it a newer batch exists:
is_protection_okay = False
run(conn, 'BEGIN TRANSACTION;')
try:
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1, 'y': 2}, {'x': 3, 'y': 4}))
except ValueError as e:
print('--------------')
print(e)
print('--------------')
if 'no earlier' in str(e):
is_protection_okay = True
run(conn, 'ROLLBACK;')
else:
raise
else:
run(conn, 'COMMIT;')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
is_deleted_always_none = all([row['_scd_deleted_timestamp'] is None for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_one_row and is_most_recent_always_true and is_deleted_always_none and is_protection_okay
def is_scenario_14_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', batch_metadata={'source': 'ONE_TIME_DUMP'})
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_two_rows and is_most_recent_always_true
def is_scenario_15_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# use partitions with batch metadata, this time multiple partitions
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1}, {'x': 2}), batch_metadata={'source': 'NEW_YORK_TIMES'},
run_id='my_test_run')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_three_rows and is_most_recent_always_true
def is_scenario_16_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x', 'y'))
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# use partitions, two partition columns this time
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1, 'y': 2},), batch_metadata={'source': 'WEEKLY'})
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_one_row and is_most_recent_always_true
def is_scenario_17_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't_', {'x': 'INT', 'y': 'INT'}, partition_columns=('x', 'y'))
run(conn, "INSERT INTO tmp_in (t_, x, y) VALUES ('20210609T050000', 1, 1), ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# Use lists or tuples (like we're supposed to) instead of strings that Python gladly iterates over (Python is a toy language)
# Also use a multi letter ts_nodash_col to surface a silly bug that existed once in snapshot
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', ('t_', 'x', 'y'), ('x', 'y'), 't_', '20210609T050000', partitions=({'x': 1, 'y': 2},), batch_metadata={'source': 'WEEKLY'})
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_one_row and is_most_recent_always_true
def is_scenario_18_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
# use a NOT NULL constraint in one of the columns to surface a bug we had in inserting the deletions in the changes table
create_tables(conn, database, schema, 't', {'x': 'INT NOT NULL', 'y': 'INT'})
# introduce a deletion in the second batch (remember, each batch is considered to be a full load)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), "
"('20210614T050000', 1, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000')
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
is_a_deleted_row_present = any([row['_scd_deleted_timestamp'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_three_rows and is_most_recent_not_always_true and is_a_deleted_row_present
def is_scenario_19_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
# Check that a new row is only inserted for the partition it belongs to
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210614T050000', 2, 2), ('20210629T050000', 2, 2), ('20210629T050000', 2, 3);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1},))
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210614T050000', partitions=({'x': 2},))
# a third round to stage the third batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210629T050000', partitions=({'x': 2},))
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
is_deleted_always_none = all([row['_scd_deleted_timestamp'] is None for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_three_rows and is_most_recent_always_true and is_deleted_always_none
def is_scenario_20_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
# Check that a new but unchanged row does not cause an insert of the new row + an invalidation of the old row
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210614T050000', 2, 2), ('20210629T050000', 2, 2);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210614T050000', partitions=({'x': 2},))
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210629T050000', partitions=({'x': 2},))
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
is_deleted_always_none = all([row['_scd_deleted_timestamp'] is None for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows) and is_one_row and is_most_recent_always_true and is_deleted_always_none
# ========================================== #
# Run all scenario's also without zombie check
# ========================================== #
def is_scenario_21_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_two_rows and is_most_recent_always_true
def is_scenario_22_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce a duplicate row in the source table; only during the second step, where the changes are staged, will it be deduplicated.
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), ('20210609T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', fail_on_duplicates=False, do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_two_rows and is_most_recent_always_true
def is_scenario_23_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# use partitions
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1},), do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_two_rows and is_most_recent_always_true
def is_scenario_24_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# use a column with values (y) that is not part of a unique key
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_two_rows and is_most_recent_always_true
def is_scenario_25_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# now in this table there are two batches worth of data
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), "
"('20210614T050000', 1, 1), ('20210614T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_three_rows and is_most_recent_not_always_true
def is_scenario_26_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce a deletion in the second batch (remember, each batch is considered to be a full load)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), "
"('20210614T050000', 1, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
is_a_deleted_row_present = any([row['_scd_deleted_timestamp'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_three_rows and is_most_recent_not_always_true and is_a_deleted_row_present
def is_scenario_27_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce a deletion in the second batch (remember, each batch is considered to be a full load)
# then, in the third batch, re-introduce a previously deleted row, without altering any of the values
# In other words, introduce a zombie, but without doing a zombie check. The result will be a duplicate valid row for an SCD
# I wonder if have an invariant check already that returns False
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), "
"('20210614T050000', 1, 1), "
"('20210619T050000', 1, 1), ('20210619T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000', do_zombie_check=False)
# a third round to stage the third batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210619T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_four_rows = (len(rows) == 4)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
is_a_deleted_row_present = any([row['_scd_deleted_timestamp'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_four_rows and is_most_recent_not_always_true and is_a_deleted_row_present
def is_scenario_28_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce NULL values in the values (y) and make sure it is not seen as an update (NULL = NULL evaluates to NULL in SQL)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, NULL), ('20210614T050000', 1, NULL);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_one_row and is_most_recent_always_true
def is_scenario_29_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce NULL values in the unique compound key (x) and make sure it is treated as an actual value
# (Sadly, in real life tables sometimes have no unique compound key, and we have to include columns that can be null in a "guessed" unique compound key in order to make
# rows unique in data observed so far.)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', NULL, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_one_row and is_most_recent_always_true
def is_scenario_30_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce NULL values in the unique compound key (x) and make sure it is treated as an actual value
# (Sadly, in real life tables sometimes have no unique compound key, and we have to include columns that can be null in a "guessed" unique compound key in order to make
# rows unique in data observed so far.)
# Also, add multiple rows with the same NULL compound key, and check that they are deduplicated as a single _scd_normalised_key (with an arbitrary row selected)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', NULL, 1), ('20210609T050000', NULL, 2);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', fail_on_duplicates=False, do_zombie_check=False)
run(conn, 'COMMIT;')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_one_row and is_most_recent_always_true
def is_scenario_31_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
# introduce NULL values in the unique compound key (x) and make sure it is treated as an actual value
# (Sadly, in real life tables sometimes have no unique compound key, and we have to include columns that can be null in a "guessed" unique compound key in order to make
# rows unique in data observed so far.)
# Also, check if we can update rows with a NULL value in a column in the compound key
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', NULL, 1), ('20210614T050000', NULL, 2);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_two_rows and is_most_recent_not_always_true
def is_scenario_32_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
# Check that partitions are handled okay, and that, if they are used, only rows in scd_table from those partitions will ever be marked for deletion
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210614T050000', 2, 2);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1},), do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210614T050000', partitions=({'x': 2},), do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
is_deleted_always_none = all([row['_scd_deleted_timestamp'] is None for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_two_rows and is_most_recent_always_true and is_deleted_always_none
def is_scenario_33_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x', 'y'))
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 3, 4), ('20210614T050000', 1, 2);")
run(conn, 'BEGIN TRANSACTION;')
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210614T050000', partitions=({'x': 1, 'y': 2},), do_zombie_check=False)
run(conn, 'COMMIT;')
# a second round to stage the second set of partitions for a batch dated Jun 9; however, for one of the partitions in it a newer batch exists:
is_protection_okay = False
run(conn, 'BEGIN TRANSACTION;')
try:
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1, 'y': 2}, {'x': 3, 'y': 4}), do_zombie_check=False)
except ValueError as e:
print('--------------')
print(e)
print('--------------')
if 'no earlier' in str(e):
is_protection_okay = True
run(conn, 'ROLLBACK;')
else:
raise
else:
run(conn, 'COMMIT;')
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
is_deleted_always_none = all([row['_scd_deleted_timestamp'] is None for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_one_row and is_most_recent_always_true and is_deleted_always_none and is_protection_okay
def is_scenario_34_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'})
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', batch_metadata={'source': 'ONE_TIME_DUMP'}, do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_two_rows = (len(rows) == 2)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_two_rows and is_most_recent_always_true
def is_scenario_35_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# use partitions with batch metadata, this time multiple partitions
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1}, {'x': 2}), batch_metadata={'source': 'NEW_YORK_TIMES'},
run_id='my_test_run', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_three_rows and is_most_recent_always_true
def is_scenario_36_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x', 'y'))
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# use partitions, two partition columns this time
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1, 'y': 2},), batch_metadata={'source': 'WEEKLY'}, do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_one_row and is_most_recent_always_true
def is_scenario_37_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't_', {'x': 'INT', 'y': 'INT'}, partition_columns=('x', 'y'))
run(conn, "INSERT INTO tmp_in (t_, x, y) VALUES ('20210609T050000', 1, 1), ('20210609T050000', 1, 2), ('20210609T050000', 2, 1);")
# Use lists or tuples (like we're supposed to) instead of strings that Python gladly iterates over (Python is a toy language)
# Also use a multi letter ts_nodash_col to surface a silly bug that existed once in snapshot
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', ('t_', 'x', 'y'), ('x', 'y'), 't_', '20210609T050000', partitions=({'x': 1, 'y': 2},), batch_metadata={'source': 'WEEKLY'}, do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_one_row and is_most_recent_always_true
def is_scenario_38_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
# use a NOT NULL constraint in one of the columns to surface a bug we had in inserting the deletions in the changes table
create_tables(conn, database, schema, 't', {'x': 'INT NOT NULL', 'y': 'INT'})
# introduce a deletion in the second batch (remember, each batch is considered to be a full load)
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 2), ('20210609T050000', 2, 1), "
"('20210614T050000', 1, 1);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210609T050000', do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'x', 't', '20210614T050000', do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_not_always_true = not all([row['_scd_is_most_recent'] for row in rows])
is_a_deleted_row_present = any([row['_scd_deleted_timestamp'] for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_three_rows and is_most_recent_not_always_true and is_a_deleted_row_present
def is_scenario_39_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
# Check that a new row is only inserted for the partition it belongs to
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210609T050000', 1, 1), ('20210614T050000', 2, 2), ('20210629T050000', 2, 2), ('20210629T050000', 2, 3);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210609T050000', partitions=({'x': 1},), do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210614T050000', partitions=({'x': 2},), do_zombie_check=False)
# a third round to stage the third batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210629T050000', partitions=({'x': 2},), do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_three_rows = (len(rows) == 3)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
is_deleted_always_none = all([row['_scd_deleted_timestamp'] is None for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_three_rows and is_most_recent_always_true and is_deleted_always_none
def is_scenario_40_success(database, schema, get_conn_callback) -> bool:
conn = get_conn_callback()
create_tables(conn, database, schema, 't', {'x': 'INT', 'y': 'INT'}, partition_columns=('x',))
# Check that a new but unchanged row does not cause an insert of the new row + an invalidation of the old row
run(conn, "INSERT INTO tmp_in (t, x, y) VALUES ('20210614T050000', 2, 2), ('20210629T050000', 2, 2);")
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210614T050000', partitions=({'x': 2},), do_zombie_check=False)
# a second round to stage the second batch
snapshot(conn, f'{database}.{schema}.tmp_batch_metadata', f'{database}.{schema}.tmp_in', f'{database}.{schema}.tmp_stage', f'{database}.{schema}.tmp_changes',
f'{database}.{schema}.tmp_scd', 'txy', 'xy', 't', '20210629T050000', partitions=({'x': 2},), do_zombie_check=False)
rows = run_and_fetchall(conn, 'SELECT * FROM tmp_scd')
print(rows)
is_one_row = (len(rows) == 1)
is_most_recent_always_true = all([row['_scd_is_most_recent'] for row in rows])
is_deleted_always_none = all([row['_scd_deleted_timestamp'] is None for row in rows])
conn.close()
return _is_okay_invariants_scd_table(rows, False) and is_one_row and is_most_recent_always_true and is_deleted_always_none
| 68.075964
| 191
| 0.68386
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| 0
| 0
| 0
|
0
| 7
|
77967cf4f4a640b6e2c43b11bb7b0b8c852e4fd7
| 6,865
|
py
|
Python
|
CSE250-DataStructures/PaleBlueDot/text.py
|
VikramGaru/ClassProjects
|
838ec015c34934ec5d0d94a284147df88fe72d23
|
[
"Unlicense"
] | null | null | null |
CSE250-DataStructures/PaleBlueDot/text.py
|
VikramGaru/ClassProjects
|
838ec015c34934ec5d0d94a284147df88fe72d23
|
[
"Unlicense"
] | 4
|
2016-07-25T22:01:53.000Z
|
2016-07-25T22:14:37.000Z
|
CSE250-DataStructures/PaleBlueDot/text.py
|
VikramGaru/ClassProjects
|
838ec015c34934ec5d0d94a284147df88fe72d23
|
[
"Unlicense"
] | null | null | null |
,encoding='UTF-8'
k1=Location(w,y)
md=-1
if k1 in self.cityLocations:
b=self.cityLocations[k1]
tlist=[]
print("Enter")
d=greatCircleDistance(location,Location(float(b[0][3]),float(b[0][4])))
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<d:
d=c
md=c
tlist=[a[1],a[2],a[0]]
if md>d or md==-1:
md=d
list=tlist
k2=Location(w,k.getLongitude())
if k2 in self.cityLocations:
b=self.cityLocations[k2]
tlist=[]
print("Enter")
d=greatCircleDistance(location,Location(float(b[0][3]),float(b[0][4])))
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<d:
d=c
tlist=[a[1],a[2],a[0]]
if md>d or md==-1:
md=d
list=tlist
k3=Location(k.getLatitude(),y)
if k3 in self.cityLocations:
b=self.cityLocations[k3]
tlist=[]
print("Enter")
d=greatCircleDistance(location,Location(float(b[0][3]),float(b[0][4])))
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<d:
d=c
md=c
tlist=[a[1],a[2],a[0]]
if md>d or md==-1:
md=d
list=tlist
k4=Location(w,z)
if k4 in self.cityLocations:
b=self.cityLocations[k4]
tlist=[]
print("Enter")
d=greatCircleDistance(location,Location(float(b[0][3]),float(b[0][4])))
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<d:
d=c
md=c
tlist=[a[1],a[2],a[0]]
if md>d or md==-1:
md=d
list=tlist
k5=Location(x,y)
if k5 in self.cityLocations:
b=self.cityLocations[k5]
tlist=[]
print("Enter")
d=greatCircleDistance(location,Location(float(b[0][3]),float(b[0][4])))
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<d:
d=c
md=c
tlist=[a[1],a[2],a[0]]
if md>d or md==-1:
md=d
list=tlist
k6=Location(x,z)
if k6 in self.cityLocations:
b=self.cityLocations[k6]
tlist=[]
print("Enter")
d=greatCircleDistance(location,Location(float(b[0][3]),float(b[0][4])))
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<d:
d=c
md=c
tlist=[a[1],a[2],a[0]]
if md>d or md==-1:
md=d
list=tlist
k7=Location(x,k.getLongitude())
if k7 in self.cityLocations:
b=self.cityLocations[k7]
tlist=[]
print("Enter")
d=greatCircleDistance(location,Location(float(b[0][3]),float(b[0][4])))
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<d:
d=c
md=c
tlist=[a[1],a[2],a[0]]
if md>d or md==-1:
md=d
list=tlist
k8=Location(k.getLatitude(),z)
if k8 in self.cityLocations:
b=self.cityLocations[k8]
tlist=[]
print("Enter")
d=greatCircleDistance(location,Location(float(b[0][3]),float(b[0][4])))
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<d:
d=c
md=c
tlist=[a[1],a[2],a[0]]
if md>d or md==-1:
md=d
list=tlist
if md!=-1:
break
i=i+1
#print(w)
#print(x)
#print(y)
#print(z)
#print()
w1=max(x,w)
while(w1>x):
pass
y1=max(y,z)
while(y1>z):
k1=Location(w1,y1)
print(w1,y1)
if k1 in self.cityLocations:
b=self.cityLocations[k1]
for a in b:
c=greatCircleDistance(location,Location(float(a[3]),float(a[4])))
if c<md or md==-1:
list=[a[1],a[2],a[0]]
md=c
y1=y1-1
w1=w1-1
if len(list)>0:
break
| 37.108108
| 97
| 0.301966
| 622
| 6,865
| 3.332797
| 0.078778
| 0.147612
| 0.287024
| 0.328027
| 0.837434
| 0.837434
| 0.7096
| 0.7096
| 0.7096
| 0.668114
| 0
| 0.047585
| 0.595921
| 6,865
| 185
| 98
| 37.108108
| 0.699712
| 0
| 0
| 0.732394
| 0
| 0
| 0.006596
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0.007042
| 0
| null | null | 0.06338
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 1
| 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
| 11
|
77cd68c890d47f00276c529918929d2628687174
| 13,920
|
py
|
Python
|
tests/integration/test_astore_models.py
|
pinduzera/python-sasctl
|
918849be77319482a8bbe436af96e50be7b4619d
|
[
"Apache-2.0"
] | 1
|
2021-06-15T08:22:18.000Z
|
2021-06-15T08:22:18.000Z
|
tests/integration/test_astore_models.py
|
SophiaRowland/python-sasctl
|
fa2aa24f96c1b25f5af34ba418f131a377251af5
|
[
"Apache-2.0"
] | 3
|
2019-07-12T02:09:15.000Z
|
2019-07-13T14:48:04.000Z
|
tests/integration/test_astore_models.py
|
jlwalke2/python-sasctl
|
e059647e1e35684591505be3838e8dbcfcc06ca9
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
# encoding: utf-8
#
# Copyright © 2019, SAS Institute Inc., Cary, NC, USA. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
import pytest
import six
# general additive model (gamSelect)
# clustering (fastKnn)
# svdd?
# deep neural
# bayes net
# factmac
# forecast
# text?
from sasctl.utils.astore import _get_model_properties, create_files_from_astore
BOSTON_INPUT_VARS = ('CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD', 'TAX', 'PTRATIO', 'B', 'LSTAT')
CANCER_INPUT_VARS = ('mean radius', 'mean texture', 'mean perimeter', 'mean area', 'mean smoothness', 'mean compactness',
'mean concavity', 'mean concave points', 'mean symmetry', 'mean fractal dimension', 'radius error',
'texture error', 'perimeter error', 'area error', 'smoothness error', 'compactness error', 'concavity error',
'concave points error', 'symmetry error', 'fractal dimension error', 'worst radius', 'worst texture',
'worst perimeter', 'worst area', 'worst smoothness', 'worst compactness', 'worst concavity',
'worst concave points', 'worst symmetry', 'worst fractal dimension')
IRIS_INPUT_VARS = ('SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth')
def check_input_variables(files, var_list):
assert 'inputVar.json' in files
input_vars = files['inputVar.json']
# Loop through each input variable that was used by the model
for var in input_vars:
# Ensure it was in the list of input variables for the dataset
assert var['name'] in var_list
def test_glm(cas_session, boston_dataset):
target = {
'tool': 'SAS Visual Analytics',
'targetVariable': 'Price',
'scoreCodeType': 'ds2MultiType',
'function': 'prediction',
'algorithm': 'Linear regression'
}
cas_session.loadactionset('regression')
cas_session.loadactionset('astore')
tbl = cas_session.upload(boston_dataset).casTable
tbl.regression.glm(target='Price',
inputs=list(boston_dataset.columns[:-1]),
savestate='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
# Verify properties are set
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, BOSTON_INPUT_VARS)
def test_logistic(cas_session, iris_dataset):
target = {
'tool': 'SAS Visual Analytics',
'targetVariable': 'Species',
'scoreCodeType': 'ds2MultiType',
'function': 'classification',
'algorithm': 'Logistic regression'
}
cas_session.loadactionset('regression')
cas_session.loadactionset('astore')
tbl = cas_session.upload(iris_dataset).casTable
tbl.regression.logistic(target='Species',
inputs=list(iris_dataset.columns[:-1]),
savestate='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, IRIS_INPUT_VARS)
def test_dtree_regression(cas_session, boston_dataset):
target = {
'tool': 'SAS Visual Analytics',
'targetVariable': 'Price',
'scoreCodeType': 'ds2MultiType',
'function': 'prediction',
'algorithm': 'Decision tree'
}
cas_session.loadactionset('decisiontree')
cas_session.loadactionset('astore')
tbl = cas_session.upload(boston_dataset).casTable
tbl.decisiontree.dtreetrain(target='Price',
inputs=list(boston_dataset.columns[:-1]),
casout='tree')
pytest.skip('Implement. How to get an astore?')
cas_session.decisiontree.dtreeExportModel(modelTable='tree',
casout='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, BOSTON_INPUT_VARS)
def test_forest_classification(cas_session, iris_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Species',
'scoreCodeType': 'ds2MultiType',
'function': 'classification',
'algorithm': 'Random forest'
}
cas_session.loadactionset('decisiontree')
cas_session.loadactionset('astore')
tbl = cas_session.upload(iris_dataset).casTable
tbl.decisiontree.foresttrain(target='Species',
inputs=list(iris_dataset.columns[:-1]),
saveState='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, IRIS_INPUT_VARS)
def test_forest_regression(cas_session, boston_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Price',
'scoreCodeType': 'ds2MultiType',
'function': 'prediction',
'algorithm': 'Random forest'
}
cas_session.loadactionset('decisiontree')
cas_session.loadactionset('astore')
tbl = cas_session.upload(boston_dataset).casTable
tbl.decisiontree.foresttrain(target='Price',
inputs=list(boston_dataset.columns[:-1]),
saveState='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, BOSTON_INPUT_VARS)
def test_gradboost_binary_classification(cas_session, cancer_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Type',
'scoreCodeType': 'ds2MultiType',
'function': 'classification',
'algorithm': 'Gradient boosting',
'targetLevel': 'binary'
}
cas_session.loadactionset('decisiontree')
cas_session.loadactionset('astore')
tbl = cas_session.upload(cancer_dataset).casTable
tbl.decisiontree.gbtreetrain(target='Type',
inputs=list(cancer_dataset.columns[:-1]),
savestate='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, CANCER_INPUT_VARS)
def test_gradboost_classification(cas_session, iris_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Species',
'scoreCodeType': 'ds2MultiType',
'function': 'classification',
'algorithm': 'Gradient boosting'
}
cas_session.loadactionset('decisiontree')
cas_session.loadactionset('astore')
tbl = cas_session.upload(iris_dataset).casTable
tbl.decisiontree.gbtreetrain(target='Species',
inputs=list(iris_dataset.columns[:-1]),
savestate='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, IRIS_INPUT_VARS)
def test_gradboost_regression(cas_session, boston_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Price',
'scoreCodeType': 'ds2MultiType',
'function': 'prediction',
'algorithm': 'Gradient boosting'
}
cas_session.loadactionset('decisiontree')
cas_session.loadactionset('astore')
tbl = cas_session.upload(boston_dataset).casTable
tbl.decisiontree.gbtreetrain(target='Price',
inputs=list(boston_dataset.columns[:-1]),
savestate='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, BOSTON_INPUT_VARS)
def test_neuralnet_regression(cas_session, boston_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Price',
'scoreCodeType': 'ds2MultiType',
'function': 'prediction',
'algorithm': 'Neural network'
}
cas_session.loadactionset('neuralnet')
cas_session.loadactionset('astore')
tbl = cas_session.upload(boston_dataset).casTable
tbl.neuralNet.annTrain(target='Price',
inputs=list(boston_dataset.columns[:-1]),
# modelTable='network',
arch='MLP',
hiddens=[2],
combs=['linear'],
casout='network')
# savestate='astore')
pytest.skip('Implement. How to get an astore?')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, BOSTON_INPUT_VARS)
def test_svm_classification(cas_session, cancer_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Type',
'scoreCodeType': 'ds2MultiType',
'function': 'classification',
'algorithm': 'Support vector machine',
'targetLevel': 'binary'
}
cas_session.loadactionset('svm')
cas_session.loadactionset('astore')
tbl = cas_session.upload(cancer_dataset).casTable
tbl.svm.svmTrain(target='Type',
inputs=list(cancer_dataset.columns[:-1]),
saveState='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, CANCER_INPUT_VARS)
def test_svm_regression(cas_session, boston_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Price',
'scoreCodeType': 'ds2MultiType',
'function': 'prediction',
'algorithm': 'Support vector machine'
}
cas_session.loadactionset('svm')
cas_session.loadactionset('astore')
tbl = cas_session.upload(boston_dataset).casTable
tbl.svm.svmTrain(target='Price',
inputs=list(boston_dataset.columns[:-1]),
saveState='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, BOSTON_INPUT_VARS)
def test_bayesnet_binary_classification(cas_session, cancer_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Type',
'scoreCodeType': 'ds2MultiType',
'function': 'classification',
'algorithm': 'Bayesian network',
'targetLevel': 'binary'
}
cas_session.loadactionset('bayesianNetClassifier')
cas_session.loadactionset('astore')
tbl = cas_session.upload(cancer_dataset).casTable
tbl.bayesianNetClassifier.bnet(target='Type',
inputs=list(cancer_dataset.columns[:-1]),
saveState='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, CANCER_INPUT_VARS)
def test_bayesnet_classification(cas_session, iris_dataset):
target = {
'tool': 'SAS Visual Data Mining and Machine Learning',
'targetVariable': 'Species',
'scoreCodeType': 'ds2MultiType',
'function': 'classification',
'algorithm': 'Bayesian network'
}
cas_session.loadactionset('bayesianNetClassifier')
cas_session.loadactionset('astore')
tbl = cas_session.upload(iris_dataset).casTable
tbl.bayesianNetClassifier.bnet(target='Species',
inputs=list(iris_dataset.columns[:-1]),
savestate='astore')
desc = cas_session.astore.describe(rstore='astore', epcode=True)
props = _get_model_properties(desc)
for k, v in six.iteritems(target):
assert props[k] == v
files = create_files_from_astore(cas_session.CASTable('astore'))
check_input_variables(files, IRIS_INPUT_VARS)
| 32.985782
| 130
| 0.642601
| 1,467
| 13,920
| 5.899114
| 0.132243
| 0.091287
| 0.069101
| 0.033973
| 0.836145
| 0.823203
| 0.807141
| 0.791888
| 0.770164
| 0.769009
| 0
| 0.003216
| 0.240445
| 13,920
| 421
| 131
| 33.064133
| 0.81519
| 0.032399
| 0
| 0.748252
| 0
| 0
| 0.219463
| 0.003122
| 0
| 0
| 0
| 0
| 0.052448
| 1
| 0.048951
| false
| 0
| 0.01049
| 0
| 0.059441
| 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
|
77ddec60297ab40c83938fabc44f7a917d0913d5
| 70,948
|
py
|
Python
|
Data_Sort_and_Plot_Script.py
|
MurphysLab/ADAblock
|
e6df7b027637d15a99530148dc54e8d3c5d89452
|
[
"MIT"
] | 2
|
2016-07-06T18:21:41.000Z
|
2021-03-17T16:51:29.000Z
|
Data_Sort_and_Plot_Script.py
|
MurphysLab/ADAblock
|
e6df7b027637d15a99530148dc54e8d3c5d89452
|
[
"MIT"
] | 1
|
2019-04-17T01:22:01.000Z
|
2020-05-31T04:21:59.000Z
|
Data_Sort_and_Plot_Script.py
|
MurphysLab/ADAblock
|
e6df7b027637d15a99530148dc54e8d3c5d89452
|
[
"MIT"
] | 7
|
2015-07-07T09:48:37.000Z
|
2020-05-29T06:33:36.000Z
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Data_Sort_and_Plot_Script.py
Script created by Jeffrey N. Murphy (2015); Email: jnmurphy@ualberta.ca
Provided without any warranty.
The directory locations will need to be modified, depending on the location of the input file.
The input for this script is the file produced by Data_Amalgamation_Script.py
"""
Save_Directory = "C:\\Users\\Jeffrey\\Plot Files" #Where plot files iwll be saved
CSV_file = "C:\\Users\\Jeffrey\\Summary Files\\Summary_2.csv"
#CSV_file = "/home/jeffrey/Summary Files/Summary_2.csv" #tux
CSV_directory = CSV_file[0:CSV_file.find("Summary_2.csv")]
output_filename = "Summary_5.csv"
import os
windows = "\\"
linux = "//"
filesep = os.path.sep
import csv
import numpy as np
dataset = []
dataset_index = -1
labels_old = [
"Image_Title.String","Version","Defect_Density_um",
"Total_Area_nm","correlation_length","opa_Hermans",
"LER_width_avg","LER_sigma_avg","wfft_Period_px",
"wfft_Period_nm","nm_per_pixel"
]
labels = ["Image_Number", "Image_Title.String", "Output_Folder", "Date", "Time", "Version", "nm_per_pixel", "Width_initial", "Height_initial", "Crop_1", "wfft_Period_px", "wfft_Period_nm", "Smoothing", "Smoothing_radius", "Crop_2", "Width_final", "Height_final", "Threshold.String", "Threshold", "Threshold.Auto-Local.String", "Up_Thresh", "Low_Thresh", "PA.pos_nPixels.1", "PA.pos_mean.1", "PA.pos_min.1", "PA.pos_max.1", "PA.pos_std.1", "PA.neg_nPixels.1", "PA.neg_mean.1", "PA.neg_min.1", "PA.neg_max.1", "PA.neg_std.1", "PA.nPositive.1", "PA.nNegative.1", "PA.nTotal.1", "PA.pos_nPixels.2", "PA.pos_mean.2", "PA.pos_min.2", "PA.pos_max.2", "PA.pos_std.2", "PA.neg_nPixels.2", "PA.neg_mean.2", "PA.neg_min.2", "PA.neg_max.2", "PA.neg_std.2", "PA.nPositive.2", "PA.nNegative.2", "PA.nTotal.2", "PA.SET.large_drops", "PA.SET.min_area", "PA.SET.wlsq_iterations", "PA.WLSQ.positive.0", "PA.WLSQ.positive.1", "PA.WLSQ.positive.2", "PA.WLSQ.positive.3", "PA.WLSQ.positive.4", "PA.WLSQ.positive.5", "PA.WLSQ.positive.6", "PA.WLSQ.negative.0", "PA.WLSQ.negative.1", "PA.WLSQ.negative.2", "PA.WLSQ.negative.3", "PA.WLSQ.negative.4", "PA.WLSQ.negative.5", "PA.WLSQ.negative.6", "PA.Width.positive", "PA.Width.negative", "PA.Width.proportion", "PA.Blobs.p.i.count", "PA.Blobs.p.i.area", "PA.Blobs.p.f.area", "PA.Blobs.p.f.count", "PA.Blobs.n.i.count", "PA.Blobs.n.i.area", "PA.Blobs.n.f.area", "PA.Blobs.n.f.count", "dot_max_area_pos", "pos_edge_dot_count", "pos_dot_count", "dot_max_area_neg", "neg_edge_dot_count", "neg_dot_count", "line_min_area_pos", "pos_edge_line_count", "pos_line_count", "line_min_area_neg", "neg_edge_line_count", "neg_line_count", "pos_min_area", "neg_min_area", "pos_mDist", "neg_mDist", "pos_t_defects.L", "pos_j_defects.L", "neg_t_defects.L", "neg_j_defects.L", "Skel.Coverage.Metric.pos", "Skel.Coverage.Metric.neg", "Correlation.Phase", "opa_factor", "opa_set_ds", "opa_set_ds_points", "opa_Hermans", "Array_Length_initial", "Array_Length_downsampled", "correlation_length", "correlation_length_linear", "opa_bar_R_squared", "loop_count", "P.LER_sigma_avg", "N.LER_sigma_avg", "LER_length_total_px", "LER_N_width_avg", "LER_P_width_avg", "LER_width_avg", "P.E.sigma.avg", "P.E.sigma.sigma", "P.E.sigma.min", "P.E.sigma.max", "P.E.sigma.count", "P.E.avg.avg", "P.E.avg.sigma", "P.E.avg.min", "P.E.avg.max", "P.E.avg.count", "P.E.count.avg", "P.E.count.sigma", "P.E.count.min", "P.E.count.max", "P.E.count.count", "P.E.sum.avg", "P.E.sum.sigma", "P.E.sum.min", "P.E.sum.max", "P.E.sum.count", "P.E.min.avg", "P.E.min.sigma", "P.E.min.min", "P.E.min.max", "P.E.min.count", "P.E.max.avg", "P.E.max.sigma", "P.E.max.min", "P.E.max.max", "P.E.max.count", "P.W.sigma.avg", "P.W.sigma.sigma", "P.W.sigma.min", "P.W.sigma.max", "P.W.sigma.count", "P.W.avg.avg", "P.W.avg.sigma", "P.W.avg.min", "P.W.avg.max", "P.W.avg.count", "P.W.count.avg", "P.W.count.sigma", "P.W.count.min", "P.W.count.max", "P.W.count.count", "P.W.sum.avg", "P.W.sum.sigma", "P.W.sum.min", "P.W.sum.max", "P.W.sum.count", "P.W.min.avg", "P.W.min.sigma", "P.W.min.min", "P.W.min.max", "P.W.min.count", "P.W.max.avg", "P.W.max.sigma", "P.W.max.min", "P.W.max.max", "P.W.max.count", "N.E.sigma.avg", "N.E.sigma.sigma", "N.E.sigma.min", "N.E.sigma.max", "N.E.sigma.count", "N.E.avg.avg", "N.E.avg.sigma", "N.E.avg.min", "N.E.avg.max", "N.E.avg.count", "N.E.count.avg", "N.E.count.sigma", "N.E.count.min", "N.E.count.max", "N.E.count.count", "N.E.sum.avg", "N.E.sum.sigma", "N.E.sum.min", "N.E.sum.max", "N.E.sum.count", "N.E.min.avg", "N.E.min.sigma", "N.E.min.min", "N.E.min.max", "N.E.min.count", "N.E.max.avg", "N.E.max.sigma", "N.E.max.min", "N.E.max.max", "N.E.max.count", "N.W.sigma.avg", "N.W.sigma.sigma", "N.W.sigma.min", "N.W.sigma.max", "N.W.sigma.count", "N.W.avg.avg", "N.W.avg.sigma", "N.W.avg.min", "N.W.avg.max", "N.W.avg.count", "N.W.count.avg", "N.W.count.sigma", "N.W.count.min", "N.W.count.max", "N.W.count.count", "N.W.sum.avg", "N.W.sum.sigma", "N.W.sum.min", "N.W.sum.max", "N.W.sum.count", "N.W.min.avg", "N.W.min.sigma", "N.W.min.min", "N.W.min.max", "N.W.min.count", "N.W.max.avg", "N.W.max.sigma", "N.W.max.min", "N.W.max.max", "N.W.max.count", "V.E.sigma.avg", "V.E.sigma.sigma", "V.E.sigma.min", "V.E.sigma.max", "V.E.sigma.count", "V.E.avg.avg", "V.E.avg.sigma", "V.E.avg.min", "V.E.avg.max", "V.E.avg.count", "V.E.count.avg", "V.E.count.sigma", "V.E.count.min", "V.E.count.max", "V.E.count.count", "V.E.sum.avg", "V.E.sum.sigma", "V.E.sum.min", "V.E.sum.max", "V.E.sum.count", "V.E.min.avg", "V.E.min.sigma", "V.E.min.min", "V.E.min.max", "V.E.min.count", "V.E.max.avg", "V.E.max.sigma", "V.E.max.min", "V.E.max.max", "V.E.max.count", "V.W.sigma.avg", "V.W.sigma.sigma", "V.W.sigma.min", "V.W.sigma.max", "V.W.sigma.count", "V.W.avg.avg", "V.W.avg.sigma", "V.W.avg.min", "V.W.avg.max", "V.W.avg.count", "V.W.count.avg", "V.W.count.sigma", "V.W.count.min", "V.W.count.max", "V.W.count.count", "V.W.sum.avg", "V.W.sum.sigma", "V.W.sum.min", "V.W.sum.max", "V.W.sum.count", "V.W.min.avg", "V.W.min.sigma", "V.W.min.min", "V.W.min.max", "V.W.min.count", "V.W.max.avg", "V.W.max.sigma", "V.W.max.min", "V.W.max.max", "V.W.max.count", "Skel.Dist.avg", "Skel.Dist.sigma", "Skel.Dist.min", "Skel.Dist.max", "Skel.Dist.count", "DRAW_edge_limit", "DRAW_jn_radius", "edge_limit", "PTE", "NTE", "PT", "NT", "PDE", "NDE", "PD", "ND", "PJ3", "NJ3", "PJ4", "NJ4", "PJx", "NJx", "Ptot", "Ntot", "Total_Defects", "Total_Area_px", "Total_Area_nm", "Defect_Density_nm", "Defect_Density_um"]
def clean_number(s):
if type(s) != type(''):
return True
else:
if s[0] == '-' and len(s)>1:
s = s[1:]
s = s.replace('"','')
return s.replace('.','',1).isdigit()
def clean_my_data(x_series,y_series):
x_new , y_new = [] , []
for i in range(0,len(x_series)):
if type(x_series[i]) != type('') and type(y_series[i]) != type(''):
x_new.append(x_series[i])
y_new.append(y_series[i])
return x_new , y_new
def clean_my_data_3(x_series,y_series,z_series):
x_new , y_new , z_new = [] , [] , []
for i in range(0,len(x_series)):
if type(x_series[i]) != type('') and type(y_series[i]) != type('') and type(z_series[i]) != type(''):
x_new.append(x_series[i])
y_new.append(y_series[i])
z_new.append(z_series[i])
return x_new , y_new , z_new
def clean_my_data_4(x_series,y_series,z_series, a_series):
x_new , y_new , z_new , a_new = [] , [] , [] , []
for i in range(0,len(x_series)):
if type(x_series[i]) != type('') and type(y_series[i]) != type('') and type(z_series[i]) != type('') and type(a_series[i]) != type(''):
x_new.append(x_series[i])
y_new.append(y_series[i])
z_new.append(z_series[i])
a_new.append(a_series[i])
return x_new , y_new , z_new , a_new
def clean_my_data_5(x_series,y_series,z_series, a_series, b_series):
x_new , y_new , z_new , a_new , b_new = [] , [] , [] , [] , []
for i in range(0,len(x_series)):
if type(x_series[i]) != type('') and type(y_series[i]) != type('') and type(z_series[i]) != type('') and type(a_series[i]) != type('') and type(b_series[i]) != type(''):
x_new.append(x_series[i])
y_new.append(y_series[i])
z_new.append(z_series[i])
a_new.append(a_series[i])
b_new.append(b_series[i])
return x_new , y_new , z_new , a_new , b_new
rfile = open(CSV_file,"rb")
reader = csv.reader(rfile)
temporary_data = []
for row in reader:
temp = row[0].split("\t")
for i in range(0,len(temp)):
temp[i] = temp[i].replace('"""', '"')
temp[i] = temp[i].replace('""', '"')
if clean_number(temp[i]):
temp[i] = float(temp[i].replace('"',''))
#print(clean_number(temp[1]))
#print(temp[1])
#print("\n")
temporary_data.append(temp)
rfile.close()
ofile = open(CSV_directory + output_filename, "wb")
writer = csv.writer(ofile, delimiter=',', quotechar="'", quoting=csv.QUOTE_MINIMAL) #NONNUMERIC) #quoting=csv.QUOTE_NONE)
for i in range(0,len(temporary_data)):
data = []
for j in range(0,len(temporary_data[i])):
data.append(temporary_data[i][j])
#print("\n")
writer.writerow(temporary_data[i])
#writer.writerow(data)
ofile.close()
print("DATA EXPORTED")
"""
Assembling Data
"""
''' Get BCP List '''
bcp_set = []
bcp_legend = []
bcp_row = []
bcp_datasets = []
data_labels = labels #["nm_per_pixel", "wfft_Period_px", "wfft_Period_nm", "V.W.sigma.avg", "V.W.avg.avg","V.E.sigma.avg","V.E.avg.avg","V.W.avg.sigma"]
data_label_index = []
for i in range(1,len(temporary_data)):
# 1: skip the first line with column headings
bcp = temporary_data[i][0].split(' ')
if bcp[0] not in bcp_set:
bcp_set.append(bcp[0])
bcp_datasets.append([])
bcp_row.append([])
#for k in range(0,len(data_labels)):
# bcp_datasets[len(bcp_datasets)-1].append([])
bcp_set.sort()
for i in range(0,len(bcp_set)):
bcp_legend.append(bcp_set[i].replace("-",".").replace("_","-"))
print(bcp_set)
print(bcp_datasets)
''' Find all of the relevant rows for each BCP set
No need to re-confirm that it matches the BCP '''
for i in range(0,len(bcp_set)):
values = []
for row in range(1,len(temporary_data)):
# 1: skip the first line with column headings
bcp = temporary_data[row][0].split(' ')
if bcp[0] == bcp_set[i]:
values.append(row)
bcp_row[i] = values
print(bcp_row[i])
'''Create data_label_index to avoid need to match each column'''
for k in range(0,len(data_labels)):
#print(data_labels[k])
for i in range(0,len(temporary_data[0])):
#print(temporary_data[0][i])
if data_labels[k] == temporary_data[0][i].replace('"',''):
data_label_index.append(i)
print(data_label_index)
## This would be going across the columns... why not go down the columns?
# for i in range(1,len(temporary_data)):
# # 1: skip the first line with column headings
# bcp = temporary_data[i][0].split(' ')
# for j in range(0,len(bcp_set)):
# if bcp[0] == bcp_set[j]:
# J = j
"""Collect Values and Attach as a list"""
for i in range(0,len(bcp_set)):
#print(bcp_set[i])
for m in range(0,len(data_labels)):
values = []
for k in range(0,len(bcp_row[i])):
values.append(temporary_data[bcp_row[i][k]][data_label_index[m]])
bcp_datasets[i].append(values)
#print(data_labels[m])
#print(values)
"""
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ PLOTS BELOW HERE @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
"""
"""
Plotting Data
"""
import matplotlib.pyplot as plt
# http://matplotlib.org/api/pyplot_api.html
marker_style = ["o","v","s","p","D"] #A list of several possible data markers
marker_color = ["SteelBlue","SeaGreen","GoldenRod","OrangeRed","FireBrick"]
marker_size = [9,10,9,11,9]
#axis_font = {'fontname':'Droid Sans', 'size':'18', 'color':'black', 'weight':'normal'}
font = {'family' : 'sans-serif',
'weight' : 'bold',
'size' : 27.5,
'sans-serif' : 'Arial'}
plt.rc('font', **font)
axes_style = {}
#http://stackoverflow.com/questions/3899980/how-to-change-the-font-size-on-a-matplotlib-plot
#http://matplotlib.org/users/customizing.html
# set tick width
plt.rcParams['axes.linewidth'] = 4
#X-axis
plt.rcParams['xtick.major.size'] = 12
plt.rcParams['xtick.major.width'] = 3
plt.rcParams['xtick.minor.size'] = 6
plt.rcParams['xtick.minor.width'] = 2
#Y-axis
plt.rcParams['ytick.major.size'] = 12
plt.rcParams['ytick.major.width'] = 3
plt.rcParams['ytick.minor.size'] = 6
plt.rcParams['ytick.minor.width'] = 2
#http://stackoverflow.com/questions/14705904/matplotlib-ticks-thickness
plotlegend = 0 #Set to 1 in order for legends to be turned on.
"""
PLOT 1:
X: wfft_Period_nm
Y: V.E.sigma.avg / V.W.avg.avg
"""
plot_file_1 = "1_LineEdge_StDevNorm_vs_Period"
x_axis_label = "Period (nm)"
y_axis_label = "Line Edge: St.Dev/Mean.Width (nm/nm)"
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "wfft_Period_nm"
b_label = "V.E.sigma.avg"
c_label = "V.W.avg.avg"
d_label = "nm_per_pixel"
a_data = []
b_data = []
c_data = []
d_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
y_boxplot = []
x_boxplot = []
for k in range(0,len(bcp_set)):
x_points , b_points , c_points = clean_my_data_3(a_data[k],b_data[k],c_data[k])
y_points = []
for i in range(0,len(x_points)):
x_points[i] = float(x_points[i])
y_points.append( float(b_points[i]) / float(c_points[i]) )
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.ylim([0,0.25])
plt.savefig(CSV_directory + plot_file_1 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_1 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""BOX PLOT"""
#convert x values to displacements
bp_scale_x = 5
for i in range(0,len(x_boxplot)):
x_avg = sum(x_boxplot[i])/len(x_boxplot[i])
print(x_avg)
for j in range(0,len(x_boxplot[i])):
x_boxplot[i][j] = (x_boxplot[i][j] - x_avg)/bp_scale_x + i + 1
#print(y_boxplot)
#print(x_boxplot)
plt.boxplot(y_boxplot)
plt.ylim([0,0.25])
for k in range(0,len(y_boxplot)):
plt.plot(x_boxplot[k],y_boxplot[k], marker_style[k], linestyle="none", markersize=marker_size[k]/2, label=bcp_legend[k], color=marker_color[k], alpha=0.75)
"""Boxplot Labels, etc..."""
if plotlegend: plt.legend(loc='best', numpoints=1)
x_axis_label_bp = "Grouped by Polymer"
plt.xlabel(x_axis_label_bp, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
plt.savefig(CSV_directory + "BP" + plot_file_1 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + "BP" + plot_file_1 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 2:
X: wfft_Period_nm
Y: V.W.sigma.avg / V.W.avg.avg
"""
plot_file_2 = "2_LineWidth_StDevNorm_vs_Period"
x_axis_label = "Period (nm)"
y_axis_label = "Line Width: St.Dev/Mean (nm/nm)"
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "wfft_Period_nm"
b_label = "V.W.sigma.avg"
c_label = "V.W.avg.avg"
d_label = "nm_per_pixel"
a_data = []
b_data = []
c_data = []
d_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
y_boxplot = []
x_boxplot = []
for k in range(0,len(bcp_set)):
x_points , b_points , c_points = clean_my_data_3(a_data[k],b_data[k],c_data[k])
y_points = []
for i in range(0,len(x_points)):
x_points[i] = float(x_points[i])
y_points.append( float(b_points[i]) / float(c_points[i]) )
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.ylim([0,0.25])
plt.savefig(CSV_directory + plot_file_2 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_2 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""BOX PLOT"""
#convert x values to displacements
bp_scale_x = 5
for i in range(0,len(x_boxplot)):
x_avg = sum(x_boxplot[i])/len(x_boxplot[i])
print(x_avg)
for j in range(0,len(x_boxplot[i])):
x_boxplot[i][j] = (x_boxplot[i][j] - x_avg)/bp_scale_x + i + 1
#print(y_boxplot)
#print(x_boxplot)
plt.boxplot(y_boxplot)
plt.ylim([0,0.25])
for k in range(0,len(y_boxplot)):
plt.plot(x_boxplot[k],y_boxplot[k], marker_style[k], linestyle="none", markersize=marker_size[k]/2, label=bcp_legend[k], color=marker_color[k], alpha=0.75)
"""Boxplot Labels, etc..."""
if plotlegend: plt.legend(loc='best', numpoints=1)
x_axis_label_bp = "Grouped by Polymer"
plt.xlabel(x_axis_label_bp, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
plt.savefig(CSV_directory + "BP" + plot_file_2 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + "BP" + plot_file_2 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 3:
X: wfft_Period_nm
Y: V.W.avg.avg +/- V.W.avg.sigma
"""
plot_file_3 = "3_LineWidth_vs_Period"
x_axis_label = "Period (nm)"
y_axis_label = "Line Width (nm)"
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "wfft_Period_nm"
b_label = "V.W.avg.avg"
c_label = "V.W.avg.sigma"
d_label = "nm_per_pixel"
a_data = []
b_data = []
c_data = []
d_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
y_boxplot = []
x_boxplot = []
for k in range(0,len(bcp_set)):
x_points , b_points , c_points, d_points = clean_my_data_4(a_data[k],b_data[k],c_data[k],d_data[k])
y_points = []
yerr_points = []
for i in range(0,len(x_points)):
x_points[i] = float(x_points[i])
y_points.append( float(b_points[i]) * float(d_points[i]) )
yerr_points.append( float(c_points[i]) * float(d_points[i]) )
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
plt.errorbar(x_points,y_points,yerr=yerr_points, linestyle="none", color=marker_color[k])
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.ylim([0,20])
plt.savefig(CSV_directory + plot_file_3 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_3 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""BOX PLOT"""
#convert x values to displacements
bp_scale_x = 5
for i in range(0,len(x_boxplot)):
x_avg = sum(x_boxplot[i])/len(x_boxplot[i])
print(x_avg)
for j in range(0,len(x_boxplot[i])):
x_boxplot[i][j] = (x_boxplot[i][j] - x_avg)/bp_scale_x + i + 1
#print(y_boxplot)
#print(x_boxplot)
plt.boxplot(y_boxplot)
plt.ylim([0,20])
for k in range(0,len(y_boxplot)):
plt.plot(x_boxplot[k],y_boxplot[k], marker_style[k], linestyle="none", markersize=marker_size[k]/2, label=bcp_legend[k], color=marker_color[k], alpha=0.75)
"""Boxplot Labels, etc..."""
if plotlegend: plt.legend(loc='best', numpoints=1)
x_axis_label_bp = "Grouped by Polymer"
plt.xlabel(x_axis_label_bp, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
plt.savefig(CSV_directory + "BP" + plot_file_3 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + "BP" + plot_file_3 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 4:
X: nm_per_pixel
Y: opa_Hermans
"""
plot_file_4 = "4_Hermans_vs_Resolution"
x_axis_label = "Resolution (nm/pixel)"
y_axis_label = "Herman's 2D Order Parameter (unitless)"
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "opa_Hermans"
b_label = "nm_per_pixel"
c_label = "wfft_Period_nm"
d_label = "wfft_Period_px"
a_data = []
b_data = []
c_data = []
d_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
y_boxplot = []
x_boxplot = []
for k in range(0,len(bcp_set)):
y_points , b_points, c_points = clean_my_data_3(a_data[k],b_data[k], c_data[k])
x_points = []
# yerr_points = []
for i in range(0,len(y_points)):
#x_points[i] = float(x_points[i])
x_points.append( float(b_points[i]) / float(c_points[i]) )
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.ylim([0,1])
plt.savefig(CSV_directory + plot_file_4 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_4 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 5:
X: total wire length measured
Y: opa_Hermans
"""
plot_file_5 = "5_Hermans_vs_Total_Length_nm"
x_axis_label = "Total Length of Lines (um)"
y_axis_label = "Herman's 2D Order Parameter (unitless)"
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "opa_Hermans"
b_label = "nm_per_pixel"
c_label = "wfft_Period_nm"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
for k in range(0,len(bcp_set)):
y_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(y_points)):
#x_points[i] = float(x_points[i])
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / float(c_points[i]) /1000 )
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.ylim([0,1])
plt.xscale('log')
plt.xlim([1,10000])
plt.savefig(CSV_directory + plot_file_5 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_5 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 6:
X: total wire length measured
Y: correlation_length
"""
plot_file_6 = "6_Correlation_nm_vs_Total_Length_nm"
x_axis_label = "Total Length of Lines (um)"
y_axis_label = "Correlation Length (nm)"
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "correlation_length"
b_label = "nm_per_pixel"
c_label = "wfft_Period_nm"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
for k in range(0,len(bcp_set)):
a_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
y_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(a_points)):
#x_points[i] = float(x_points[i])
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / float(c_points[i]) /1000 )
y_points.append(float(a_points[i])*float(b_points[i]))
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.yscale('log')
plt.ylim([10,2000])
plt.xscale('log')
plt.xlim([1,1000])
plt.savefig(CSV_directory + plot_file_6 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_6 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 7:
X: Image Area (um^2)
Y: correlation_length
"""
plot_file_7 = "7_Correlation_nm_vs_ImageArea_um2"
x_axis_label = "Image Area (um )" #insert superscript-2 later
y_axis_label = "Correlation Length (nm)"
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "correlation_length"
b_label = "nm_per_pixel"
c_label = "wfft_Period_nm"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
for k in range(0,len(bcp_set)):
a_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
y_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(a_points)):
#x_points[i] = float(x_points[i])
y_points.append(float(a_points[i])*float(b_points[i]))
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / 1000000 )
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.yscale('log')
plt.ylim([10,2000])
plt.xscale('log')
#plt.xlim([1,1000])
plt.savefig(CSV_directory + plot_file_7 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_7 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 8:
X: Image Area (um^2)
Y: Defect Density
"""
plot_file_8 = "8_DefectDensity_vs_ImageArea_um2"
x_axis_label = "Image Area (um )" #insert superscript 2 later
y_axis_label = "Defect Pair Density (um )" #insert superscript -2 later
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "Defect_Density_um"
b_label = "nm_per_pixel"
c_label = "wfft_Period_nm"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
for k in range(0,len(bcp_set)):
y_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(y_points)):
#x_points[i] = float(x_points[i])
stagger = (100.0 + 20.0*( float(k+1) - float(len(bcp_set))/2.0 ) / ( float(len(bcp_set))/2.0 ))/100.0
print(stagger)
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / 1000000 * stagger)
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.yscale('log')
plt.ylim([10,3000])
plt.xscale('log')
#plt.xlim([1,1000])
plt.savefig(CSV_directory + plot_file_8 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_8 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 9: (Averaged)
X: Image Area (um^2)
Y: Defect Density
"""
plot_file_9 = "9_DefectDensity_vs_ImageArea_um2"
x_axis_label = "Image Area (um )" #insert superscript 2 later
y_axis_label = "Defect Pair Density (um )" #insert superscript -2 later
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "Defect_Density_um"
b_label = "nm_per_pixel"
c_label = "wfft_Period_nm"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
yerr_points = []
for k in range(0,len(bcp_set)):
y_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(y_points)):
#x_points[i] = float(x_points[i])
stagger = (100.0 + 20.0*( float(k+1) - float(len(bcp_set))/2.0 ) / ( float(len(bcp_set))/2.0 ))/100.0
#print(stagger)
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / 1000000 * stagger)
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
# GROUP & AVERAGE
x_new = []
for i in range(0,len(x_points)):
count = 0
for j in range(0,len(x_points)):
if x_points[i] == x_points[j]:
count += 1
if x_points[i] not in x_new and count > 1:
x_new.append(x_points[i])
y_new = []
yerr_new_neg = [] #for log plots
yerr_new = []
for j in range(0,len(x_new)):
y_temp = []
for i in range(0,len(x_points)):
if x_points[i] == x_new[j]:
y_temp.append(y_points[i])
y_new.append(np.mean(y_temp))
yerr_new.append(np.std(y_temp))
if np.mean(y_temp) - np.std(y_temp) <= 0:
y_neg_std = np.mean(y_temp) - 0.01
else:
y_neg_std = np.std(y_temp)
yerr_new_neg.append(y_neg_std)
x_points = x_new
y_points = y_new
yerr_points.append(yerr_new)
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
plt.errorbar(x_points,y_points,yerr=[yerr_new_neg, yerr_new], linestyle="none", color=marker_color[k])
print(bcp_legend[k])
print(x_points)
print(yerr_points[k])
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='best', numpoints=1)
plt.yscale('log')
plt.ylim([10,3000])
plt.xscale('log')
#plt.xlim([1,1000])
plt.savefig(CSV_directory + plot_file_9 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_9 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 10: (Averaged)
X: Image Area (um^2)
Y: Defect Density
"""
plot_file_10 = "10_DefectDensity_vs_ImageArea_um2"
x_axis_label = "Image Area (um )" #insert superscript 2 later
y_axis_label = "Defect Pair Density (um )" #insert superscript -2 later
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "Defect_Density_um"
b_label = "nm_per_pixel"
c_label = "wfft_Period_nm"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
yerr_points = []
for k in range(0,len(bcp_set)):
y_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(y_points)):
#x_points[i] = float(x_points[i])
stagger = (100.0 + 20.0*( float(k+1) - float(len(bcp_set))/2.0 ) / ( float(len(bcp_set))/2.0 ))/100.0
#print(stagger)
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / 1000000 * stagger)
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
# GROUP & AVERAGE
x_new = []
for i in range(0,len(x_points)):
count = 0
for j in range(0,len(x_points)):
if x_points[i] == x_points[j]:
count += 1
if x_points[i] not in x_new and count > 1:
x_new.append(x_points[i])
x_new.sort()
y_new = []
yerr_new_neg = [] #for log plots
yerr_new = []
for j in range(0,len(x_new)):
y_temp = []
for i in range(0,len(x_points)):
if x_points[i] == x_new[j]:
y_temp.append(y_points[i])
y_new.append(np.mean(y_temp))
yerr_new.append(np.std(y_temp))
if np.mean(y_temp) - np.std(y_temp) <= 0:
y_neg_std = np.mean(y_temp) - 0.01
else:
y_neg_std = np.std(y_temp)
yerr_new_neg.append(y_neg_std)
#x_points = x_new
#y_points = y_new
yerr_points.append(yerr_new)
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.2)
plt.plot(x_new, y_new, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
plt.errorbar(x_new,y_new,yerr=[yerr_new_neg, yerr_new], linestyle="--", color=marker_color[k])
print(bcp_legend[k])
print(x_points)
print(yerr_points[k])
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='top right', numpoints=1, bbox_to_anchor=(1, 1))
plt.yscale('log')
plt.ylim([10,3000])
plt.xscale('log')
#plt.xlim([1,1000])
plt.savefig(CSV_directory + plot_file_10 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_10 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 11: (Averaged)
X: Image Area (um^2)
Y: Correlation Length
Description: Averaged with y-error bars, overlaid on semi-transparent raw datapoints.
"""
plot_file_11 = "11_CorrelationLength_vs_ImageArea_um2"
x_axis_label = "Image Area (um^2)" #insert superscript 2 later
y_axis_label = "Correlation Length (nm)" #insert superscript -2 later
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "correlation_length"
b_label = "nm_per_pixel"
c_label = "wfft_Period_nm"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
yerr_points = []
for k in range(0,len(bcp_set)):
a_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
y_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(a_points)):
#x_points[i] = float(x_points[i])
stagger = (100.0 + 20.0*( float(k+1) - float(len(bcp_set))/2.0 ) / ( float(len(bcp_set))/2.0 ))/100.0
#print(stagger)
y_points.append(float(a_points[i])*float(b_points[i]))
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / 1000000 * stagger)
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
# GROUP & AVERAGE
x_new = []
for i in range(0,len(x_points)):
count = 0
for j in range(0,len(x_points)):
if x_points[i] == x_points[j]:
count += 1
if x_points[i] not in x_new and count > 1:
x_new.append(x_points[i])
x_new.sort()
y_new = []
yerr_new_neg = [] #for log plots
yerr_new = []
for j in range(0,len(x_new)):
y_temp = []
for i in range(0,len(x_points)):
if x_points[i] == x_new[j]:
y_temp.append(y_points[i])
y_new.append(np.mean(y_temp))
yerr_new.append(np.std(y_temp))
if np.mean(y_temp) - np.std(y_temp) <= 0:
y_neg_std = np.mean(y_temp) - 0.01
else:
y_neg_std = np.std(y_temp)
yerr_new_neg.append(y_neg_std)
#x_points = x_new
#y_points = y_new
yerr_points.append(yerr_new)
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.2)
plt.plot(x_new, y_new, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
plt.errorbar(x_new,y_new,yerr=[yerr_new_neg, yerr_new], linestyle="--", color=marker_color[k])
print(bcp_legend[k])
print(x_points)
print(yerr_points[k])
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='top right', numpoints=1, bbox_to_anchor=(1, 1))
plt.yscale('log')
plt.ylim([10,3000])
plt.xscale('log')
#plt.xlim([1,1000])
plt.savefig(CSV_directory + plot_file_11 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_11 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 12: (Averaged)
X: Image Area (um^2)
Y: LER
Description: Averaged with y-error bars, overlaid on semi-transparent raw datapoints.
"""
plot_file_12 = "12_LineEdge_StDevNorm_vs_ImageArea_um2"
x_axis_label = "Image Area (um^2)" #insert superscript 2 later
y_axis_label = "Line Edge: St.Dev/Mean.Width (nm/nm)" #insert superscript -2 later
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "V.E.sigma.avg"
b_label = "nm_per_pixel"
c_label = "V.W.avg.avg"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
yerr_points = []
for k in range(0,len(bcp_set)):
a_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
y_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(a_points)):
y_points.append( float(a_points[i]) / float(c_points[i]) )
#x_points[i] = float(x_points[i])
stagger = (100.0 + 20.0*( float(k+1) - float(len(bcp_set))/2.0 ) / ( float(len(bcp_set))/2.0 ))/100.0
#print(stagger)
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / 1000000 * stagger)
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
# GROUP & AVERAGE
x_new = []
for i in range(0,len(x_points)):
count = 0
for j in range(0,len(x_points)):
if x_points[i] == x_points[j]:
count += 1
if x_points[i] not in x_new and count > 1:
x_new.append(x_points[i])
x_new.sort()
y_new = []
yerr_new_neg = [] #for log plots
yerr_new = []
for j in range(0,len(x_new)):
y_temp = []
for i in range(0,len(x_points)):
if x_points[i] == x_new[j]:
y_temp.append(y_points[i])
y_new.append(np.mean(y_temp))
yerr_new.append(np.std(y_temp))
if np.mean(y_temp) - np.std(y_temp) <= 0:
y_neg_std = np.mean(y_temp) - 0.01
else:
y_neg_std = np.std(y_temp)
yerr_new_neg.append(y_neg_std)
#x_points = x_new
#y_points = y_new
yerr_points.append(yerr_new)
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.2)
plt.plot(x_new, y_new, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
plt.errorbar(x_new,y_new,yerr=[yerr_new_neg, yerr_new], linestyle="--", color=marker_color[k])
print(bcp_legend[k])
print(x_points)
print(yerr_points[k])
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='top right', numpoints=1, bbox_to_anchor=(1, 1))
#plt.yscale('log')
plt.ylim([0.0,0.25])
plt.xscale('log')
#plt.xlim([1,1000])
plt.savefig(CSV_directory + plot_file_12 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_12 + '.svg')
#plt.show()
plt.cla()
plt.clf()
"""
PLOT 13: (Averaged)
X: Image Area (um^2)
Y: LWR/W
Description: Averaged with y-error bars, overlaid on semi-transparent raw datapoints.
"""
plot_file_13 = "13_LineWidth_StDevNorm_vs_ImageArea_um2"
x_axis_label = "Image Area (um^2)" #insert superscript 2 later
y_axis_label = "Line Edge: St.Dev/Mean.Width (nm/nm)" #insert superscript -2 later
x_points = []
y_points = []
''' Need to ensure that these labels are included in data_labels
Could just set data_labels = labels, but that slows down re-compiling the data'''
a_label = "V.W.sigma.avg"
b_label = "nm_per_pixel"
c_label = "V.W.avg.avg"
d_label = "Width_initial"
e_label = "Height_initial"
a_data = []
b_data = []
c_data = []
d_data = []
e_data = []
for i in range(0,len(data_labels)):
if a_label == data_labels[i]:
i_a = data_label_index[i]
if b_label == data_labels[i]:
i_b = data_label_index[i]
if c_label == data_labels[i]:
i_c = data_label_index[i]
if d_label == data_labels[i]:
i_d = data_label_index[i]
if e_label == data_labels[i]:
i_e = data_label_index[i]
print(data_labels)
print("i_a: " + str(i_a))
print("i_b: " + str(i_b))
print("i_c: " + str(i_c))
print("i_d: " + str(i_d))
print("i_e: " + str(i_e))
## put some error in here if it's still -1,-1
#marker_style = ["s","v","o","p","D"] #A list of several possible data markers
#marker_color = ["red","green","blue","cyan","magenta"]
#marker_size = [9,10,9,11,9]
#colors = itertools.cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k'])
## Simple case; no clean-up / filtering required
for k in range(0,len(bcp_set)):
a_values = []
b_values = []
c_values = []
d_values = []
e_values = []
for i in range(0,len(bcp_row[k])):
#print(bcp_row[k])
#print(ix)
#print(iy)
#a_values.append(float(temporary_data[bcp_row[k][i]][i_a]))
#b_values.append(float(temporary_data[bcp_row[k][i]][i_b]))
#c_values.append(float(temporary_data[bcp_row[k][i]][i_c]))
#d_values.append(float(temporary_data[bcp_row[k][i]][i_d]))
a_values.append(temporary_data[bcp_row[k][i]][i_a])
b_values.append(temporary_data[bcp_row[k][i]][i_b])
c_values.append(temporary_data[bcp_row[k][i]][i_c])
d_values.append(temporary_data[bcp_row[k][i]][i_d])
e_values.append(temporary_data[bcp_row[k][i]][i_e])
a_data.append(a_values)
b_data.append(b_values)
c_data.append(c_values)
d_data.append(d_values)
e_data.append(e_values)
y_boxplot = []
x_boxplot = []
yerr_points = []
for k in range(0,len(bcp_set)):
a_points , b_points, c_points, d_points, e_points = clean_my_data_5(a_data[k], b_data[k], c_data[k], d_data[k], e_data[k])
x_points = []
y_points = []
# a_label = "opa_Hermans"
# b_label = "nm_per_pixel"
# c_label = "wfft_Period_nm"
# d_label = "Width_initial"
# e_label = "Height_initial"
for i in range(0,len(a_points)):
y_points.append( float(a_points[i]) / float(c_points[i]) )
#x_points[i] = float(x_points[i])
stagger = (100.0 + 20.0*( float(k+1) - float(len(bcp_set))/2.0 ) / ( float(len(bcp_set))/2.0 ))/100.0
#print(stagger)
x_points.append( float(d_points[i]) * float(e_points[i]) * float(b_points[i])* float(b_points[i]) / 1000000 * stagger)
#yerr_points.append( float(c_points[i]) * float(d_points[i]) )
# GROUP & AVERAGE
x_new = []
for i in range(0,len(x_points)):
count = 0
for j in range(0,len(x_points)):
if x_points[i] == x_points[j]:
count += 1
if x_points[i] not in x_new and count > 1:
x_new.append(x_points[i])
x_new.sort()
y_new = []
yerr_new_neg = [] #for log plots
yerr_new = []
for j in range(0,len(x_new)):
y_temp = []
for i in range(0,len(x_points)):
if x_points[i] == x_new[j]:
y_temp.append(y_points[i])
y_new.append(np.mean(y_temp))
yerr_new.append(np.std(y_temp))
if np.mean(y_temp) - np.std(y_temp) <= 0:
y_neg_std = np.mean(y_temp) - 0.01
else:
y_neg_std = np.std(y_temp)
yerr_new_neg.append(y_neg_std)
#x_points = x_new
#y_points = y_new
yerr_points.append(yerr_new)
y_boxplot.append(y_points)
x_boxplot.append(x_points)
#print(x_points)
#print(y_points)
plt.plot(x_points, y_points, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.2)
plt.plot(x_new, y_new, marker_style[k], linestyle="none", markersize=marker_size[k], label=bcp_legend[k], color=marker_color[k], alpha=0.75)
plt.errorbar(x_new,y_new,yerr=[yerr_new_neg, yerr_new], linestyle="--", color=marker_color[k])
print(bcp_legend[k])
print(x_points)
print(yerr_points[k])
#axis labels
axis_font = {'fontname':'Arial', 'size':'28', 'color':'black', 'weight':'bold'}
plt.xlabel(x_axis_label, **axis_font)
#####plt.ylabel(y_axis_label, **axis_font)
if plotlegend: plt.legend(loc='top right', numpoints=1, bbox_to_anchor=(1, 1))
#plt.yscale('log')
plt.ylim([0.0,0.25])
plt.xscale('log')
#plt.xlim([1,1000])
plt.savefig(CSV_directory + plot_file_13 + '.png', bbox_inches='tight')
plt.savefig(CSV_directory + plot_file_13 + '.svg')
#plt.show()
plt.cla()
plt.clf()
| 33.045179
| 6,054
| 0.629207
| 12,165
| 70,948
| 3.41044
| 0.036991
| 0.008388
| 0.023453
| 0.052208
| 0.855814
| 0.845546
| 0.834747
| 0.827468
| 0.812259
| 0.810596
| 0
| 0.015629
| 0.181119
| 70,948
| 2,146
| 6,055
| 33.060578
| 0.698475
| 0.191506
| 0
| 0.850368
| 0
| 0
| 0.148599
| 0.011519
| 0
| 0
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| 0
| 0
| 1
| 0.004088
| false
| 0
| 0.003271
| 0
| 0.012265
| 0.080131
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
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| 0
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| 0
| 0
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| 0
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|
0
| 8
|
77f6f5594ed5a66231c8007ff7976a3f72b4d9f1
| 23,727
|
py
|
Python
|
Flat_torus_LEM.py
|
DavidLitwin/SpectralDiffusion
|
0e97b09dbc366e6b4c4d7c523d83ec0eda36579d
|
[
"MIT"
] | 2
|
2019-12-17T18:38:09.000Z
|
2019-12-18T15:08:52.000Z
|
Flat_torus_LEM.py
|
DavidLitwin/SpectralDiffusion
|
0e97b09dbc366e6b4c4d7c523d83ec0eda36579d
|
[
"MIT"
] | null | null | null |
Flat_torus_LEM.py
|
DavidLitwin/SpectralDiffusion
|
0e97b09dbc366e6b4c4d7c523d83ec0eda36579d
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Created on Thu May 2 16:46:56 2019
@author: dgbli
All landscape evolution models and figures for flat torus model with spectral
diffusion, presented at CSDMS in May 2019:
Litwin, D., C. J. Harman, T. Zaki, (2019): Implicit-spectral solution for a simple landscape evolution model. Poster. Community Surface Dynamics Modeling System Annual Meeting
"""
import numpy as np
import matplotlib.pyplot as plt
import pickle
import pandas as pd
import LEMFunctions as lf
from landlab.components import LinearDiffuser, FlowAccumulator, FastscapeEroder
from landlab.plot import imshow_grid
from landlab import RasterModelGrid, CLOSED_BOUNDARY, FIXED_VALUE_BOUNDARY
TicToc = lf.TicTocGenerator()
from matplotlib import colors as mcolors
colors = dict(mcolors.BASE_COLORS, **mcolors.CSS4_COLORS)
#%%
#np.random.seed(1)
#Nc = 50
#N = int(Nc*3)
#dx = 10
#mg = RasterModelGrid((N,N), dx)
#z = mg.add_zeros('topographic__elevation', at='node' )
#mg.status_at_node[lf.get_fixed_cells(N)] = FIXED_VALUE_BOUNDARY
#
#imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
##%% Flat torus, advective only
#
#z_orig = np.random.rand(Nc,Nc)
#z1 = np.vstack([z_orig, z_orig, z_orig])
#z_comp = np.hstack([z1, z1, z1])
#z_comp = z_comp.reshape((np.size(z_comp)))
#fixed = lf.get_fixed_cells(N)
#z_comp[fixed] = 0
#z[:] = z_comp
#
#imshow_grid(mg,'topographic__elevation')
#
#dt = 100
#T_max = 1E5
#nt = int(T_max//dt)
#D = 1E-4
#uplift_rate = 1E-3 #m/yr
#uplift_per_step = uplift_rate*dt
#m = 0.5 #Exponent on A []
#n = 1.0 #Exponent on S []
#K = 1E-11*(365*24*3600) #erosivity coefficient [yr−1]
#
#ld = LinearDiffuser(mg,linear_diffusivity=D)
#fr = FlowAccumulator(mg,'topographic__elevation',flow_director='D8')
#sp = FastscapeEroder(mg,K_sp = K,m_sp = m, n_sp=n)
#
#lf.tic()
#for i in range(nt):
# fr.run_one_step()
# sp.run_one_step(dt)
#
# z_tiled_0 = z.reshape((mg.shape))
# z_tiled_1 = lf.retile_array(z_tiled_0,Nc)
# z_tiled_1 = z_tiled_1.reshape((np.size(z_tiled_1)))
# z_tiled_1[fixed] = 0
# z[:] = z_tiled_1
#
## ld.run_one_step(dt)
# mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
#
# if i % 20 == 0:
# print ('Completed loop %d' % i)
#
#lf.toc()
#imshow_grid(mg,'topographic__elevation')
#z_array_landlab = z.reshape((mg.shape))
#
#z_center = z_array_landlab[Nc:2*Nc,Nc:2*Nc]
#plt.imshow(z_array_landlab, cmap=plt.get_cmap('copper'))
#
#%% Vary N Flat torus, landlab diffuser
a = -500
b = 500
Nc_range = [24,48,96]
results_landlab = []
for j in range(len(Nc_range)):
Nc = Nc_range[j]
N = int(Nc*3)
fixed = lf.get_fixed_cells(N)
dx = (b-a)/N
mg = RasterModelGrid((N,N), dx)
z = mg.add_zeros('topographic__elevation', at='node' )
mg.status_at_node[fixed] = FIXED_VALUE_BOUNDARY
# imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
seed = np.random.seed(1)
z_orig = np.random.rand(Nc,Nc)
z1 = np.vstack([z_orig, z_orig, z_orig])
z_comp = np.hstack([z1, z1, z1])
z_comp = z_comp.reshape((np.size(z_comp)))
z_comp[fixed] = 0
z[:] = z_comp
# imshow_grid(mg,'topographic__elevation')
dt = 100
T_max = 1E5
nt = int(T_max//dt)
D = 1E-3
uplift_rate = 1E-3 #m/yr
uplift_per_step = uplift_rate*dt
m = 0.5 #Exponent on A []
n = 1.0 #Exponent on S []
K = 3E-4 #erosivity coefficient [yr−1]
ld = LinearDiffuser(mg,linear_diffusivity=D)
fr = FlowAccumulator(mg,'topographic__elevation',flow_director='D8')
sp = FastscapeEroder(mg,K_sp = K,m_sp = m, n_sp=n)
lf.tic()
for i in range(nt):
fr.run_one_step()
sp.run_one_step(dt)
ld.run_one_step(dt)
z_tiled_0 = z.reshape((mg.shape))
z_tiled_1 = lf.retile_array(z_tiled_0,Nc)
z_tiled_1 = z_tiled_1.reshape((np.size(z_tiled_1)))
z_tiled_1[fixed] = 0
z[:] = z_tiled_1
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
if i % 20 == 0:
print ('Completed loop %d' % i)
lf.toc()
# imshow_grid(mg,'topographic__elevation')
z_array = z.reshape((mg.shape))
#
# z_center = z_array[Nc:2*Nc,Nc:2*Nc]
# plt.imshow(z_array, cmap=plt.get_cmap('copper'))
#
# pickle.dump(z_array, open('Landlab_torus_test_' + str(Nc) +'.p','wb'))
results_landlab.append(z_array)
del mg
pickle.dump(results_landlab, open('Landlab_torus_test_all_new.p','wb'))
#%% Vary N Flat torus, explicit spectral diffuser
a = -500
b = 500
Nc_range = [24,48,96]
results_exp_spectral = []
for j in range(len(Nc_range)):
Nc = Nc_range[j]
N = int(Nc*3)
fixed = lf.get_fixed_cells(N)
dx = (b-a)/N
mg = RasterModelGrid((N,N), dx)
z = mg.add_zeros('topographic__elevation', at='node' )
mg.status_at_node[fixed] = FIXED_VALUE_BOUNDARY
# imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
seed = np.random.seed(1)
z_orig = np.random.rand(Nc,Nc)
z1 = np.vstack([z_orig, z_orig, z_orig])
z_comp = np.hstack([z1, z1, z1])
z_comp = z_comp.reshape((np.size(z_comp)))
z_comp[fixed] = 0
z[:] = z_comp
# imshow_grid(mg,'topographic__elevation')
dt = 100
T_max = 1E5
nt = int(T_max//dt)
D = 1E-3
uplift_rate = 1E-3 #m/yr
uplift_per_step = uplift_rate*dt
m = 0.5 #Exponent on A []
n = 1.0 #Exponent on S []
K = 3E-4 #erosivity coefficient [yr−1]
ld = LinearDiffuser(mg,linear_diffusivity=D)
fr = FlowAccumulator(mg,'topographic__elevation',flow_director='D8')
sp = FastscapeEroder(mg,K_sp = K,m_sp = m, n_sp=n)
A = lf.Spectral_Diffuser(z_orig,D,dt,dx,dx,'explicit')
lf.tic()
for i in range(nt):
fr.run_one_step()
sp.run_one_step(dt)
z_tiled_0 = z.reshape((mg.shape))
z_center = z_tiled_0[Nc:2*Nc,Nc:2*Nc]
z_center_1 = lf.Spectral_Diffuser_one_step(z_center,A)
z_tiled_1 = lf.tile_array(z_center_1)
z_tiled_1 = z_tiled_1.reshape((np.size(z_tiled_1)))
z_tiled_1[fixed] = 0
z[:] = z_tiled_1
# ld.run_one_step(dt)
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
if i % 20 == 0:
print ('Completed loop %d' % i)
lf.toc()
# imshow_grid(mg,'topographic__elevation')
z_array = z.reshape((mg.shape))
# pickle.dump(z_array, open('Landlab_exp_spectral_torus_test_' + str(Nc) +'.p','wb'))
results_exp_spectral.append(z_array)
del mg
pickle.dump(results_exp_spectral, open('Landlab_exp_spectral_torus_test_all_new.p','wb'))
#%% Vary N Flat torus, implicit spectral diffuser
a = -500
b = 500
Nc_range = [24,48,96]
results_imp_spectral = []
for j in range(len(Nc_range)):
Nc = Nc_range[j]
N = int(Nc*3)
fixed = lf.get_fixed_cells(N)
dx = (b-a)/N
mg = RasterModelGrid((N,N), dx)
z = mg.add_zeros('topographic__elevation', at='node' )
mg.status_at_node[fixed] = FIXED_VALUE_BOUNDARY
# imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
seed = np.random.seed(1)
z_orig = np.random.rand(Nc,Nc)
z1 = np.vstack([z_orig, z_orig, z_orig])
z_comp = np.hstack([z1, z1, z1])
z_comp = z_comp.reshape((np.size(z_comp)))
z_comp[fixed] = 0
z[:] = z_comp
# imshow_grid(mg,'topographic__elevation')
dt = 100
T_max = 1E5
nt = int(T_max//dt)
D = 1E-3
uplift_rate = 1E-3 #m/yr
uplift_per_step = uplift_rate*dt
m = 0.5 #Exponent on A []
n = 1.0 #Exponent on S []
K = 3E-4 #erosivity coefficient [yr−1]
ld = LinearDiffuser(mg,linear_diffusivity=D)
fr = FlowAccumulator(mg,'topographic__elevation',flow_director='D8')
sp = FastscapeEroder(mg,K_sp = K,m_sp = m, n_sp=n)
A = lf.Spectral_Diffuser(z_orig,D,dt,dx,dx,'implicit')
lf.tic()
for i in range(nt):
fr.run_one_step()
sp.run_one_step(dt)
z_tiled_0 = z.reshape((mg.shape))
z_center = z_tiled_0[Nc:2*Nc,Nc:2*Nc]
z_center_1 = lf.Spectral_Diffuser_one_step(z_center,A)
z_tiled_1 = lf.tile_array(z_center_1)
z_tiled_1 = z_tiled_1.reshape((np.size(z_tiled_1)))
z_tiled_1[fixed] = 0
z[:] = z_tiled_1
# ld.run_one_step(dt)
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
if i % 20 == 0:
print ('Completed loop %d' % i)
lf.toc()
# imshow_grid(mg,'topographic__elevation')
z_array = z.reshape((mg.shape))
# pickle.dump(z_array, open('Landlab_imp_spectral_torus_test_' + str(Nc) +'.p','wb'))
results_imp_spectral.append(z_array)
del mg
pickle.dump(results_imp_spectral, open('Landlab_imp_spectral_torus_test_all_new.p','wb'))
#%% Vary dt Flat torus, landlab diffuser
a = -500
b = 500
Nc = 64
N = int(Nc*3)
fixed = lf.get_fixed_cells(N)
dx = (b-a)/N
dt_range = [10,50,100,500,1000,2000]
results_landlab = []
for j in range(len(dt_range)):
mg = RasterModelGrid((N,N), dx)
z = mg.add_zeros('topographic__elevation', at='node' )
mg.status_at_node[fixed] = FIXED_VALUE_BOUNDARY
# imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
seed = np.random.seed(1)
z_orig = np.random.rand(Nc,Nc)
z1 = np.vstack([z_orig, z_orig, z_orig])
z_comp = np.hstack([z1, z1, z1])
z_comp = z_comp.reshape((np.size(z_comp)))
z_comp[fixed] = 0
z[:] = z_comp
# imshow_grid(mg,'topographic__elevation')
dt = dt_range[j]
T_max = 1E5
nt = int(T_max//dt)
D = 1E-3
uplift_rate = 1E-3 #m/yr
uplift_per_step = uplift_rate*dt
m = 0.5 #Exponent on A []
n = 1.0 #Exponent on S []
K = 3E-4 #erosivity coefficient [yr−1]
ld = LinearDiffuser(mg,linear_diffusivity=D)
fr = FlowAccumulator(mg,'topographic__elevation',flow_director='D8')
sp = FastscapeEroder(mg,K_sp = K,m_sp = m, n_sp=n)
lf.tic()
for i in range(nt):
fr.run_one_step()
sp.run_one_step(dt)
ld.run_one_step(dt)
z_tiled_0 = z.reshape((mg.shape))
z_tiled_1 = lf.retile_array(z_tiled_0,Nc)
z_tiled_1 = z_tiled_1.reshape((np.size(z_tiled_1)))
z_tiled_1[fixed] = 0
z[:] = z_tiled_1
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
if i % 100 == 0:
print ('Completed loop %d' % i)
lf.toc()
# imshow_grid(mg,'topographic__elevation')
z_array = z.reshape((mg.shape))
#
# z_center = z_array[Nc:2*Nc,Nc:2*Nc]
# plt.imshow(z_array, cmap=plt.get_cmap('copper'))
#
# pickle.dump(z_array, open('Landlab_torus_test_' + str(Nc) +'.p','wb'))
results_landlab.append(z_array)
del mg
pickle.dump(results_landlab, open('Landlab_torus_test_dt_all.p','wb'))
#%% Vary dt Flat torus, explicit spectral diffuser
a = -500
b = 500
Nc = 64
N = int(Nc*3)
fixed = lf.get_fixed_cells(N)
dx = (b-a)/N
dt_range = [10,50,100,500,1000,2000]
results_exp_spectral = []
for j in range(len(dt_range)):
mg = RasterModelGrid((N,N), dx)
z = mg.add_zeros('topographic__elevation', at='node' )
mg.status_at_node[fixed] = FIXED_VALUE_BOUNDARY
# imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
seed = np.random.seed(1)
z_orig = np.random.rand(Nc,Nc)
z1 = np.vstack([z_orig, z_orig, z_orig])
z_comp = np.hstack([z1, z1, z1])
z_comp = z_comp.reshape((np.size(z_comp)))
z_comp[fixed] = 0
z[:] = z_comp
# imshow_grid(mg,'topographic__elevation')
dt = dt_range[j]
T_max = 1E5
nt = int(T_max//dt)
D = 1E-3
uplift_rate = 1E-3 #m/yr
uplift_per_step = uplift_rate*dt
m = 0.5 #Exponent on A []
n = 1.0 #Exponent on S []
K = 3E-4 #erosivity coefficient [yr−1]
ld = LinearDiffuser(mg,linear_diffusivity=D)
fr = FlowAccumulator(mg,'topographic__elevation',flow_director='D8')
sp = FastscapeEroder(mg,K_sp = K,m_sp = m, n_sp=n)
A = lf.Spectral_Diffuser(z_orig,D,dt,dx,dx,'explicit')
lf.tic()
for i in range(nt):
fr.run_one_step()
sp.run_one_step(dt)
z_tiled_0 = z.reshape((mg.shape))
z_center = z_tiled_0[Nc:2*Nc,Nc:2*Nc]
z_center_1 = lf.Spectral_Diffuser_one_step(z_center,A)
z_tiled_1 = lf.tile_array(z_center_1)
z_tiled_1 = z_tiled_1.reshape((np.size(z_tiled_1)))
z_tiled_1[fixed] = 0
z[:] = z_tiled_1
# ld.run_one_step(dt)
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
if i % 100 == 0:
print ('Completed loop %d' % i)
lf.toc()
# imshow_grid(mg,'topographic__elevation')
z_array = z.reshape((mg.shape))
# pickle.dump(z_array, open('Landlab_exp_spectral_torus_test_' + str(Nc) +'.p','wb'))
results_exp_spectral.append(z_array)
del mg
pickle.dump(results_exp_spectral, open('Landlab_exp_spectral_torus_test_dt_all.p','wb'))
#%% Vary dt, Flat torus, implicit spectral diffuser
a = -500
b = 500
Nc = 64
N = int(Nc*3)
fixed = lf.get_fixed_cells(N)
dx = (b-a)/N
dt_range = [10,50,100,500,1000,2000]
results_imp_spectral = []
for j in range(len(dt_range)):
mg = RasterModelGrid((N,N), dx)
z = mg.add_zeros('topographic__elevation', at='node' )
mg.status_at_node[fixed] = FIXED_VALUE_BOUNDARY
# imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
seed = np.random.seed(1)
z_orig = np.random.rand(Nc,Nc)
z1 = np.vstack([z_orig, z_orig, z_orig])
z_comp = np.hstack([z1, z1, z1])
z_comp = z_comp.reshape((np.size(z_comp)))
z_comp[fixed] = 0
z[:] = z_comp
# imshow_grid(mg,'topographic__elevation')
dt = dt_range[j]
T_max = 1E5
nt = int(T_max//dt)
D = 1E-3
uplift_rate = 1E-3 #m/yr
uplift_per_step = uplift_rate*dt
m = 0.5 #Exponent on A []
n = 1.0 #Exponent on S []
K = 3E-4 #erosivity coefficient [yr−1]
ld = LinearDiffuser(mg,linear_diffusivity=D)
fr = FlowAccumulator(mg,'topographic__elevation',flow_director='D8')
sp = FastscapeEroder(mg,K_sp = K,m_sp = m, n_sp=n)
A = lf.Spectral_Diffuser(z_orig,D,dt,dx,dx,'implicit')
lf.tic()
for i in range(nt):
fr.run_one_step()
sp.run_one_step(dt)
z_tiled_0 = z.reshape((mg.shape))
z_center = z_tiled_0[Nc:2*Nc,Nc:2*Nc]
z_center_1 = lf.Spectral_Diffuser_one_step(z_center,A)
z_tiled_1 = lf.tile_array(z_center_1)
z_tiled_1 = z_tiled_1.reshape((np.size(z_tiled_1)))
z_tiled_1[fixed] = 0
z[:] = z_tiled_1
# ld.run_one_step(dt)
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
if i % 100 == 0:
print ('Completed loop %d' % i)
lf.toc()
# imshow_grid(mg,'topographic__elevation')
z_array = z.reshape((mg.shape))
# pickle.dump(z_array, open('Landlab_imp_spectral_torus_test_' + str(Nc) +'.p','wb'))
results_imp_spectral.append(z_array)
del mg
pickle.dump(results_imp_spectral, open('Landlab_imp_spectral_torus_test_dt_all.p','wb'))
#%% flat torus, spectral diffuser, 3 point BCs:
a = -500
b = 500
Nc = 128
N = int(Nc*3)
dx = (b-a)/N
mg = RasterModelGrid((N,N), dx)
z = mg.add_zeros('topographic__elevation', at='node' )
fixed = lf.get_fixed_cells_3(N)
mg.status_at_node[fixed] = FIXED_VALUE_BOUNDARY
#imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
seed = np.random.seed(1)
z_orig = np.random.rand(Nc,Nc)
z1 = np.vstack([z_orig, z_orig, z_orig])
z_comp = np.hstack([z1, z1, z1])
z_comp = z_comp.reshape((np.size(z_comp)))
z_comp[fixed] = 0
z[:] = z_comp
dt = 100
T_max = 1E5
nt = int(T_max//dt)
D = 1E-3
uplift_rate = 1E-3 #m/yr
uplift_per_step = uplift_rate*dt
m = 0.5 #Exponent on A []
n = 1.0 #Exponent on S []
K = 3E-4 #erosivity coefficient [yr−1]
fr = FlowAccumulator(mg,'topographic__elevation',flow_director='D8')
sp = FastscapeEroder(mg,K_sp = K,m_sp = m, n_sp=n)
A = lf.Spectral_Diffuser(z_orig,D,dt,dx,dx,'implicit')
lf.tic()
for i in range(nt):
fr.run_one_step()
sp.run_one_step(dt)
z_tiled_0 = z.reshape((mg.shape))
z_center = z_tiled_0[Nc:2*Nc,Nc:2*Nc]
z_center_1 = lf.Spectral_Diffuser_one_step(z_center,A)
z_tiled_1 = lf.tile_array(z_center_1)
z_tiled_1 = z_tiled_1.reshape((np.size(z_tiled_1)))
z_tiled_1[fixed] = 0 #boundary condition
z[:] = z_tiled_1
# ld.run_one_step(dt)
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
if i % 20 == 0:
print ('Completed loop %d' % i)
lf.toc()
imshow_grid(mg,'topographic__elevation')
z_array_3_bcs = z.reshape((mg.shape))
pickle.dump(z_array_3_bcs, open('Landlab_imp_spectral_3bcs_2' + str(Nc) +'.p','wb'))
#%%
#
#plt.figure()
#plt.imshow(results_imp_spectral[2])
#plt.title('Implicit Spectral Diffuser')
#plt.colorbar()
#
#plt.figure()
#plt.imshow(results_landlab[0])
#plt.title('Landlab Diffuser')
#plt.colorbar()
#
#%% Figure comparing landlab, explicit spectral, implicit spectral
#find max and min
all_images = results_landlab+results_exp_spectral+results_imp_spectral
max_all = 0
for array in all_images:
max1 = np.max(array)
if max1>max_all:
max_all = max1
fig, axs = plt.subplots(nrows=3, ncols=3,figsize=[10,10])
plt.tight_layout()
for i in range(0,3):
im1 = axs[i,0].imshow(all_images[i*2], vmin=0, vmax=max_all, extent=[0,1000,0,1000])
im2 = axs[i,1].imshow(all_images[i*2+6], vmin=0, vmax=max_all, extent=[0,1000,0,1000])
im3 = axs[i,2].imshow(all_images[i*2+12], vmin=0, vmax=max_all, extent=[0,1000,0,1000])
axs[0,0].xaxis.set_ticklabels([])
axs[0,1].axes.yaxis.set_ticklabels([])
axs[0,1].axes.xaxis.set_ticklabels([])
axs[0,2].axes.yaxis.set_ticklabels([])
axs[0,2].axes.xaxis.set_ticklabels([])
axs[1,0].xaxis.set_ticklabels([])
axs[1,1].axes.yaxis.set_ticklabels([])
axs[1,1].axes.xaxis.set_ticklabels([])
axs[1,2].axes.yaxis.set_ticklabels([])
axs[1,2].axes.xaxis.set_ticklabels([])
axs[2,1].axes.yaxis.set_ticklabels([])
axs[2,2].axes.yaxis.set_ticklabels([])
axs[2,1].set_xlabel('Distance (m)')
axs[1,0].set_ylabel('Distance (m)')
fig.subplots_adjust(right=0.8,left=0.3,bottom=0.3,wspace=0.05,hspace=0.1)
cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7])
cb = fig.colorbar(im1, cax=cbar_ax)
cb.set_label('Elevation (m)')
#%% Mean elevation plot: change dt
results_imp_spectral = pickle.load(open('Landlab_imp_spectral_torus_test_dt_all.p',"rb"))
results_exp_spectral = pickle.load(open('Landlab_exp_spectral_torus_test_dt_all.p',"rb"))
results_landlab = pickle.load(open('Landlab_torus_test_dt_all.p',"rb"))
all_images = results_landlab+results_exp_spectral+results_imp_spectral
dt_range = [10,50,100,500,1000,2000]
mean_elevations = np.zeros(len(all_images))
for i in range(len(all_images)):
mean_elevations[i] = np.mean(all_images[i],axis=None)
mean_elevations = np.reshape(mean_elevations,(6,3),'F')
dt_range_plt = np.flip(dt_range)
mean_elevations_plt = np.flipud(mean_elevations)
plt.figure(figsize=[6,4])
plt.plot(dt_range_plt,mean_elevations_plt[:,0],color=colors['burlywood'],label='Landlab')
plt.plot(dt_range_plt,mean_elevations_plt[:,1],color=colors['orchid'],label='Explicit Spectral')
plt.plot(dt_range_plt,mean_elevations_plt[:,2],color=colors['mediumslateblue'],label='Implicit Spectral')
plt.xticks(dt_range_plt)
plt.xlabel('Timestep [yr]')
plt.ylabel('Mean Elevation [m]')
plt.xscale('log')
plt.legend(frameon = False)
plt.tight_layout()
#%% mean elevation plot: change N
#results_imp_spectral = pickle.load(open('Landlab_imp_spectral_torus_test_all_new.p',"rb"))
#results_exp_spectral = pickle.load(open('Landlab_exp_spectral_torus_test_all_new.p',"rb"))
#results_landlab = pickle.load(open('Landlab_torus_test_all_new.p',"rb"))
results_imp_spectral_1 = pickle.load(open('Landlab_imp_spectral_torus_test_all.p',"rb"))
results_exp_spectral_1 = pickle.load(open('Landlab_exp_spectral_torus_test_all.p',"rb"))
results_landlab_1 = pickle.load(open('Landlab_torus_test_all.p',"rb"))
results_N = [24,48,96]
results_N_1 = [32,64,128]
results_N_all = results_N + results_N_1
results_imp_spectral_all = results_imp_spectral+results_imp_spectral_1
results_exp_spectral_all = results_exp_spectral+results_exp_spectral_1
results_landlab_all = results_landlab+results_landlab_1
all_images = results_landlab_all+results_exp_spectral_all+results_imp_spectral_all
mean_elevations = np.zeros(len(all_images))
for i in range(len(all_images)):
mean_elevations[i] = np.mean(all_images[i],axis=None)
mean_elevations = np.reshape(mean_elevations,(6,3),'F')
index_sorted = np.argsort(np.array(results_N_all))
for j in range(3):
mean_elevations[:,j] = mean_elevations[index_sorted,j]
results_N_all_sort = np.sort(np.array(results_N_all))
plt.figure(figsize=[6,4])
plt.plot(results_N_all_sort,mean_elevations[:,0],color=colors['burlywood'],label='Landlab')
plt.plot(results_N_all_sort,mean_elevations[:,1],color=colors['orchid'],label='Explicit Spectral')
plt.plot(results_N_all_sort,mean_elevations[:,2],color=colors['mediumslateblue'],label='Implicit Spectral')
plt.xticks(results_N_all_sort)
plt.xlabel('Number of grid cells N')
plt.ylabel('Mean Elevation [m]')
#plt.xscale('log')
plt.legend(frameon = False)
plt.tight_layout()
#
##%%
#
#
#eta0 = pickle.load(open('Landlab_imp_spectral_switch_bcs_2_0.p',"rb"))
#eta1 = pickle.load(open('Landlab_imp_spectral_switch_bcs_2_50.p',"rb"))
#eta2 = pickle.load(open('Landlab_imp_spectral_switch_bcs_2_100.p',"rb"))
#eta3 = pickle.load(open('Landlab_imp_spectral_switch_bcs_2_150.p',"rb"))
#eta4 = pickle.load(open('Landlab_imp_spectral_switch_bcs_2_200.p',"rb"))
#
##plt.figure()
##plt.imshow(eta0)
#
##find max and min
#all_images = [eta0,eta1,eta2,eta3,eta4]
#max_all = 0
#for array in all_images:
# max1 = np.max(array)
# if max1>max_all:
# max_all = max1
##
##fig, axs = plt.subplots(nrows=1, ncols=5)
##fig.tight_layout()
##for i in range(0,5):
## im1 = axs[i].imshow(all_images[i], vmin=0, vmax=max_all)
##
##fig.subplots_adjust(right=0.8)
##cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7])
##fig.colorbar(im1, cax=cbar_ax)
#
#
#for i in range(0,5):
# fig,ax = plt.subplots()
# im = ax.imshow(all_images[i], vmin=0, vmax=max_all)
# cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7])
# fig.colorbar(im1, cax=cbar_ax)
# plt.savefig('Drainage_capture_'+str(i)+'.png')
#
#%% voronoi polygons
from scipy.spatial import Voronoi, voronoi_plot_2d
Nc = 128
N = Nc*3
a = -500
b = 500
dx = (b-a)/N
n_array = np.zeros((N**2))
point_nums = lf.get_fixed_cells_3(N)
n_array[point_nums] = 1
n_array = n_array.reshape((N,N)).T
indices = np.where(n_array==1)
x = dx*indices[0].reshape((len(indices[0]),1))
y = dx*indices[1].reshape((len(indices[0]),1))
pairs = np.concatenate((x,y),axis=1)
vor = Voronoi(pairs)
poly = voronoi_plot_2d(vor)
plt.imshow(z_array_3_bcs,origin='lower',extent=[0,1000,0,1000])
fig = plt.gcf()
fig.set_size_inches(10.5,10.5)
plt.show()
plt.xlim(0,1000)
plt.ylim(0,1000)
plt.savefig('Voronoi_3bcs.png', bbox_inches = 'tight', pad_inches = 0)
#plt.figure()
#imshow_grid(mg, mg.status_at_node, color_for_closed='blue')
| 29.621723
| 176
| 0.652253
| 3,941
| 23,727
| 3.657194
| 0.078153
| 0.026643
| 0.023312
| 0.011656
| 0.851731
| 0.825644
| 0.790051
| 0.778048
| 0.752793
| 0.708874
| 0
| 0.039537
| 0.195178
| 23,727
| 800
| 177
| 29.65875
| 0.714809
| 0.257681
| 0
| 0.786957
| 0
| 0
| 0.08698
| 0.056239
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.021739
| 0
| 0.021739
| 0.015217
| 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
|
7add48b51ec7fa8a84f50b5f27904c00c16c2c3b
| 7,890
|
py
|
Python
|
controllers/parseDh.py
|
srangar/Dheliver
|
97f00a6b7fb26aa42cc120872700f4fc47041661
|
[
"MIT"
] | 1
|
2020-08-26T06:41:26.000Z
|
2020-08-26T06:41:26.000Z
|
controllers/parseDh.py
|
akpatnam25/Dheliver
|
cf52f978334572084e265f91b8435e4269dc21b3
|
[
"MIT"
] | null | null | null |
controllers/parseDh.py
|
akpatnam25/Dheliver
|
cf52f978334572084e265f91b8435e4269dc21b3
|
[
"MIT"
] | null | null | null |
def getCowellBreakFast():
f = open('cowellBreakfast.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha():
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
words.remove('breakfast')
return dict(menu=words)
def getCowellLunch():
f = open('cowellLunch.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getCowellDinner():
f = open('cowellDinner.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getCowellLateNight():
f = open('cowellLateNight.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getMerillBreakfast():
f = open('merillBreakfast.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getMerillLunch():
f = open('merillLunch.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getMerillDinner():
f = open('merillDinner.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getMerillLateNight():
f = open('merillLateNight.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getPorterBreakfast():
f = open('porterBreakfast.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getPorterLunch():
f = open('porterLunch.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getPorterDinner():
f = open('porterDinner.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getPorterLateNight():
f = open('porterLateNight.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getRccBreakfast():
f = open('rccBreakfast.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getRccLunch():
f = open('rccLunch.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getRccDinner():
f = open('rccDinner.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getRccLateNight():
f = open('rccLateNight.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getTenBreakfast():
f = open('tenBreakfast.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getTenLunch():
f = open('tenLunch.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getTenDinner():
f = open('tenDinner.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
def getTenLateNight():
f = open('tenLateNight.txt','r')
message = f.read()
strMessage = str(message)
finalStr = ""
for i in range(len(strMessage)-3):
if strMessage[i].isalpha() :
finalStr += strMessage[i]
else:
finalStr += " "
words = finalStr.split(" ")
words[0] = words[0].replace(" ", "")
return dict(menu=words)
| 26.565657
| 40
| 0.537643
| 843
| 7,890
| 5.032028
| 0.080664
| 0.103725
| 0.051862
| 0.056577
| 0.843234
| 0.838048
| 0.838048
| 0.838048
| 0.838048
| 0.838048
| 0
| 0.010817
| 0.296958
| 7,890
| 296
| 41
| 26.655405
| 0.753921
| 0
| 0
| 0.842912
| 0
| 0
| 0.059569
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.076628
| false
| 0
| 0
| 0
| 0.153257
| 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
|
7ae5340e407629f57b0dee45518910178ad4a665
| 115
|
py
|
Python
|
bot/helpers/utils/__init__.py
|
Propheci/ruko-zara-sabar-karo
|
a8cf0660619eceade7a86caa0a480cc2deec2047
|
[
"MIT"
] | 2
|
2022-01-17T12:29:49.000Z
|
2022-02-17T13:37:54.000Z
|
bot/helpers/utils/__init__.py
|
akshettrj/request-tracker
|
a8cf0660619eceade7a86caa0a480cc2deec2047
|
[
"MIT"
] | null | null | null |
bot/helpers/utils/__init__.py
|
akshettrj/request-tracker
|
a8cf0660619eceade7a86caa0a480cc2deec2047
|
[
"MIT"
] | null | null | null |
from bot.helpers.utils.telegram import *
from bot.helpers.utils.time import *
from bot.helpers.utils.misc import *
| 28.75
| 40
| 0.791304
| 18
| 115
| 5.055556
| 0.444444
| 0.230769
| 0.461538
| 0.626374
| 0.549451
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.104348
| 115
| 3
| 41
| 38.333333
| 0.883495
| 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
|
7af4b231f1fd81b21b92731a8546b0c87ae957e4
| 60
|
py
|
Python
|
package/modA/modAX/x.py
|
BekoBou/PEP328Import
|
1f295e1ee5087403966d00e61d43939e69df7dfe
|
[
"MIT"
] | null | null | null |
package/modA/modAX/x.py
|
BekoBou/PEP328Import
|
1f295e1ee5087403966d00e61d43939e69df7dfe
|
[
"MIT"
] | null | null | null |
package/modA/modAX/x.py
|
BekoBou/PEP328Import
|
1f295e1ee5087403966d00e61d43939e69df7dfe
|
[
"MIT"
] | null | null | null |
from ...e import ANSWER
def say_answer():
return ANSWER
| 15
| 23
| 0.7
| 9
| 60
| 4.555556
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 60
| 4
| 24
| 15
| 0.854167
| 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
|
bb41209597607823c967e74f25865d840f2e5803
| 32
|
py
|
Python
|
cb1521_script.py
|
danspinelli/example-open-source-repo-2021
|
a4d8fba5c0c7a7c9d736da156f2560234c3f22de
|
[
"MIT"
] | null | null | null |
cb1521_script.py
|
danspinelli/example-open-source-repo-2021
|
a4d8fba5c0c7a7c9d736da156f2560234c3f22de
|
[
"MIT"
] | null | null | null |
cb1521_script.py
|
danspinelli/example-open-source-repo-2021
|
a4d8fba5c0c7a7c9d736da156f2560234c3f22de
|
[
"MIT"
] | null | null | null |
print("Hello hello hello hello")
| 32
| 32
| 0.78125
| 5
| 32
| 5
| 0.4
| 1.2
| 1.2
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.09375
| 32
| 1
| 32
| 32
| 0.862069
| 0
| 0
| 0
| 0
| 0
| 0.69697
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 8
|
246cfee2c64b375a6fc3a7b2358db8f4c3084e84
| 7,437
|
py
|
Python
|
tests/test_fair.py
|
utkarshmttl/fairsearch-fair-python
|
a92a3d6a94e8050a1216d7f5d1157d4882d4d584
|
[
"Apache-2.0"
] | 11
|
2019-08-13T05:53:48.000Z
|
2022-02-26T19:51:03.000Z
|
tests/test_fair.py
|
utkarshmttl/fairsearch-fair-python
|
a92a3d6a94e8050a1216d7f5d1157d4882d4d584
|
[
"Apache-2.0"
] | 1
|
2020-05-13T20:17:14.000Z
|
2020-05-13T20:17:14.000Z
|
tests/test_fair.py
|
utkarshmttl/fairsearch-fair-python
|
a92a3d6a94e8050a1216d7f5d1157d4882d4d584
|
[
"Apache-2.0"
] | 5
|
2020-05-08T15:21:56.000Z
|
2021-11-09T13:54:52.000Z
|
import pytest
from fairsearchcore import fair
from fairsearchcore import models
@pytest.mark.parametrize("k, p, alpha, ranking",(
(20, 0.25, 0.1, [models.FairScoreDoc(20,20,False),models.FairScoreDoc(19,19,True),
models.FairScoreDoc(18,18,False),models.FairScoreDoc(17,17,False),
models.FairScoreDoc(16,16,False),models.FairScoreDoc(15,15,False),
models.FairScoreDoc(14,14,False),models.FairScoreDoc(13,13,True),
models.FairScoreDoc(12,12,False),models.FairScoreDoc(11,11,True),
models.FairScoreDoc(10,10,False),models.FairScoreDoc(9,9,False),
models.FairScoreDoc(8,8,True),models.FairScoreDoc(7,7,False),
models.FairScoreDoc(6,6,False),models.FairScoreDoc(5,5,True),
models.FairScoreDoc(4,4,True),models.FairScoreDoc(3,3,False),
models.FairScoreDoc(2,2,False),models.FairScoreDoc(1,1,False)]),
(20, 0.3, 0.1, [models.FairScoreDoc(20,20,False),models.FairScoreDoc(19,19,True),
models.FairScoreDoc(18,18,False),models.FairScoreDoc(17,17,True),
models.FairScoreDoc(16,16,True),models.FairScoreDoc(15,15,False),
models.FairScoreDoc(14,14,False),models.FairScoreDoc(13,13,True),
models.FairScoreDoc(12,12,False),models.FairScoreDoc(11,11,True),
models.FairScoreDoc(10,10,False),models.FairScoreDoc(9,9,False),
models.FairScoreDoc(8,8,True),models.FairScoreDoc(7,7,False),
models.FairScoreDoc(6,6,False),models.FairScoreDoc(5,5,True),
models.FairScoreDoc(4,4,True),models.FairScoreDoc(3,3,False),
models.FairScoreDoc(2,2,False),models.FairScoreDoc(1,1,False)]),
))
def test_is_fair(k, p, alpha, ranking):
f = fair.Fair(k, p, alpha)
assert len(ranking) == k
assert f.is_fair(ranking)
@pytest.mark.parametrize("k, p, alpha, result",(
(10, 0.2, 0.15, [0, 0, 0, 0, 0, 0, 0, 0, 1, 1]),
(20, 0.25, 0.1, [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3]),
(30, 0.3, 0.05, [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5])
))
def test_create_unadjusted_mtable(k, p, alpha, result):
f = fair.Fair(k, p, alpha)
mtable = f.create_unadjusted_mtable()
assert mtable == result
@pytest.mark.parametrize("k, p, alpha, result",(
(10, 0.2, 0.15, [0, 0, 0, 0, 0, 0, 0, 0, 1, 1]),
(20, 0.25, 0.1, [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2]),
(30, 0.3, 0.05, [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 4])
))
def test_create_adjusted_mtable(k, p, alpha, result):
f = fair.Fair(k, p, alpha)
mtable = f.create_adjusted_mtable()
assert mtable == result
@pytest.mark.parametrize("k, p, alpha, result",(
(10, 0.2, 0.15, 0.15),
(20, 0.25, 0.1, 0.07812500000000001),
(30, 0.3, 0.15, 0.0796875)
))
def test_adjust_alpha(k, p, alpha, result):
f = fair.Fair(k, p, alpha)
adjusted_alpha = f.adjust_alpha()
assert abs(adjusted_alpha - result) < 0.0001 # they should be same to the 5th decimal
@pytest.mark.parametrize("k, p, alpha, result",(
(10, 0.2, 0.15, 0.13421772800000065),
(20, 0.25, 0.1, 0.10515247355215251),
(30, 0.3, 0.05, 0.04877730797178359)
))
def test_compute_fail_probability(k, p, alpha, result):
f = fair.Fair(k, p, alpha)
adjusted_mtable = f.create_adjusted_mtable()
prob = f.compute_fail_probability(adjusted_mtable)
assert abs(prob - result) < 0.0001 # they should be same to the 5th decimal
@pytest.mark.parametrize("k, p, alpha",(
(10, 0.2, 0.15),
(20, 0.25, 0.1),
(30, 0.3, 0.05)
))
def test_mtable_generation(k, p, alpha):
f = fair.Fair(k, p, alpha)
# create an adjusted mtable with alpha unadjusted
mtable = f.create_adjusted_mtable()
# get alpha adjusted
alpha_adjusted = f.adjust_alpha()
# create a new unadjusted mtable with the new alpha
f_adjusted = fair.Fair(k, p, alpha_adjusted)
mtable_adjusted = f_adjusted.create_unadjusted_mtable()
assert mtable == mtable_adjusted # they should be same to the 5th decimal
@pytest.mark.parametrize("k, p, alpha, ranking",(
(20, 0.25, 0.1, [models.FairScoreDoc(20, 20, False), models.FairScoreDoc(19, 19, False),
models.FairScoreDoc(18, 18, False), models.FairScoreDoc(17, 17, False),
models.FairScoreDoc(16, 16, False), models.FairScoreDoc(15, 15, False),
models.FairScoreDoc(14, 14, False), models.FairScoreDoc(13, 13, False),
models.FairScoreDoc(12, 12, False), models.FairScoreDoc(11, 11, False),
models.FairScoreDoc(10, 10, False), models.FairScoreDoc(9, 9, False),
models.FairScoreDoc(8, 8, False), models.FairScoreDoc(7, 7, False),
models.FairScoreDoc(6, 6, False), models.FairScoreDoc(5, 5, True),
models.FairScoreDoc(4, 4, True), models.FairScoreDoc(3, 3, True),
models.FairScoreDoc(2, 2, True), models.FairScoreDoc(1, 1, True)]),
(20, 0.3, 0.1, [models.FairScoreDoc(20,20,False),models.FairScoreDoc(19,19,False),
models.FairScoreDoc(18,18,False),models.FairScoreDoc(17,17,False),
models.FairScoreDoc(16,16,False),models.FairScoreDoc(15,15,False),
models.FairScoreDoc(14,14,False),models.FairScoreDoc(13,13,False),
models.FairScoreDoc(12,12,False),models.FairScoreDoc(11,11,True),
models.FairScoreDoc(10,10,True),models.FairScoreDoc(9,9,False),
models.FairScoreDoc(8,8,True),models.FairScoreDoc(7,7,False),
models.FairScoreDoc(6,6,False),models.FairScoreDoc(5,5,True),
models.FairScoreDoc(4,4,True),models.FairScoreDoc(3,3,True),
models.FairScoreDoc(2,2,True),models.FairScoreDoc(1,1,True)]),
))
def test_re_rank(k, p, alpha, ranking):
f = fair.Fair(k, p, alpha)
re_ranked = f.re_rank(ranking)
# input should not be fair
assert not f.is_fair(ranking)
# check length
assert len(ranking) == len(re_ranked)
# check content
assert set([r.id for r in ranking]) == set([r.id for r in re_ranked])
# output should be fair
assert f.is_fair(re_ranked)
| 50.591837
| 119
| 0.528573
| 966
| 7,437
| 4.018634
| 0.093168
| 0.370943
| 0.302164
| 0.032973
| 0.789799
| 0.761206
| 0.746522
| 0.732612
| 0.730294
| 0.730294
| 0
| 0.119887
| 0.332661
| 7,437
| 146
| 120
| 50.938356
| 0.662301
| 0.04128
| 0
| 0.53271
| 0
| 0
| 0.01784
| 0
| 0
| 0
| 0
| 0
| 0.102804
| 1
| 0.065421
| false
| 0
| 0.028037
| 0
| 0.093458
| 0
| 0
| 0
| 0
| null | 1
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
248ded6f5eb82fd36ea9140d814cd647eafb3f2b
| 61
|
py
|
Python
|
rmnplugin/localconstants.py
|
nichuguen/led-matrix-rpi
|
0837e8cd36faced3c8e6fd0249e53e9190d4b6a2
|
[
"BSD-Source-Code"
] | null | null | null |
rmnplugin/localconstants.py
|
nichuguen/led-matrix-rpi
|
0837e8cd36faced3c8e6fd0249e53e9190d4b6a2
|
[
"BSD-Source-Code"
] | null | null | null |
rmnplugin/localconstants.py
|
nichuguen/led-matrix-rpi
|
0837e8cd36faced3c8e6fd0249e53e9190d4b6a2
|
[
"BSD-Source-Code"
] | null | null | null |
list_ips = ['http://192.168.0.101', 'http://192.168.0.102']
| 20.333333
| 59
| 0.590164
| 12
| 61
| 2.916667
| 0.666667
| 0.4
| 0.571429
| 0.628571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.357143
| 0.081967
| 61
| 2
| 60
| 30.5
| 0.267857
| 0
| 0
| 0
| 0
| 0
| 0.666667
| 0
| 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
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
70272e533f933e6b67311ed879464df50e2a991b
| 112,031
|
py
|
Python
|
great_international/migrations/0033_add_homepage_fields_to_apppage.py
|
uktrade/directory-cms
|
8c8d13ce29ea74ddce7a40f3dd29c8847145d549
|
[
"MIT"
] | 6
|
2018-03-20T11:19:07.000Z
|
2021-10-05T07:53:11.000Z
|
great_international/migrations/0033_add_homepage_fields_to_apppage.py
|
uktrade/directory-cms
|
8c8d13ce29ea74ddce7a40f3dd29c8847145d549
|
[
"MIT"
] | 802
|
2018-02-05T14:16:13.000Z
|
2022-02-10T10:59:21.000Z
|
great_international/migrations/0033_add_homepage_fields_to_apppage.py
|
uktrade/directory-cms
|
8c8d13ce29ea74ddce7a40f3dd29c8847145d549
|
[
"MIT"
] | 6
|
2019-01-22T13:19:37.000Z
|
2019-07-01T10:35:26.000Z
|
# -*- coding: utf-8 -*-
# Generated by Django 1.11.20 on 2019-05-29 10:21
from __future__ import unicode_literals
import core.model_fields
import core.validators
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('wagtailcore', '0040_page_draft_title'),
('wagtailimages', '0021_image_file_hash'),
('great_international', '0032_investinternationalhomepage_how_we_help_icon_six'),
]
operations = [
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading',
field=models.TextField(blank=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading_ar',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading_de',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading_en_gb',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading_es',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading_fr',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading_ja',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading_pt',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_heading_zh_hans',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_one_image_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading',
field=models.TextField(blank=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading_ar',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading_de',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading_en_gb',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading_es',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading_fr',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading_ja',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading_pt',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_heading_zh_hans',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_three_image_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading',
field=models.TextField(blank=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading_ar',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading_de',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading_en_gb',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading_es',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading_fr',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading_ja',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading_pt',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_heading_zh_hans',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_link_two_image_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary',
field=models.TextField(blank=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary_ar',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary_de',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary_en_gb',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary_es',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary_fr',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary_ja',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary_pt',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_summary_zh_hans',
field=models.TextField(blank=True, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title',
field=models.CharField(blank=True, max_length=255),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title_ar',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title_de',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title_en_gb',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title_es',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title_fr',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title_ja',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title_pt',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='featured_links_title_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link',
field=models.CharField(blank=True, max_length=255),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link_ar',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link_de',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link_en_gb',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link_es',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link_fr',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link_ja',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link_pt',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_link_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text_ar',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text_de',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text_en_gb',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text_es',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text_fr',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text_ja',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text_pt',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_cta_text_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_image_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle',
field=models.CharField(blank=True, max_length=255),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle_ar',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle_de',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle_en_gb',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle_es',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle_fr',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle_ja',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle_pt',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_subtitle_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title',
field=models.CharField(default='', max_length=255),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title_ar',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title_de',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title_en_gb',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title_es',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title_fr',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title_ja',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title_pt',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='hero_title_zh_hans',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content',
field=core.model_fields.MarkdownField(blank=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content_ar',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content_de',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content_en_gb',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content_es',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content_fr',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content_ja',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content_pt',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_content_zh_hans',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_image_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title',
field=models.CharField(default='', max_length=255),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title_ar',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title_de',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title_en_gb',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title_es',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title_fr',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title_ja',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title_pt',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='invest_title_zh_hans',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title',
field=models.CharField(default='', max_length=255),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title_ar',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title_de',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title_en_gb',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title_es',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title_fr',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title_ja',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title_pt',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='news_title_zh_hans',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_one_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_three_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='related_page_two_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailcore.Page'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading',
field=models.CharField(blank=True, max_length=255, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading_ar',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading_de',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading_en_gb',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading_es',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading_fr',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading_ja',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading_pt',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_heading_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight title'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body',
field=models.TextField(blank=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body_ar',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body_de',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body_en_gb',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body_es',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body_fr',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body_ja',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body_pt',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_body_zh_hans',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 5 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading',
field=models.CharField(blank=True, max_length=255, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading_ar',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading_de',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading_en_gb',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading_es',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading_fr',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading_ja',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading_pt',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_heading_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 5 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_five_icon_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 5 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body',
field=models.TextField(blank=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body_ar',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body_de',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body_en_gb',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body_es',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body_fr',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body_ja',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body_pt',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_body_zh_hans',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 4 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading',
field=models.CharField(blank=True, max_length=255, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading_ar',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading_de',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading_en_gb',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading_es',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading_fr',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading_ja',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading_pt',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_heading_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 4 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_four_icon_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 4 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body',
field=models.TextField(blank=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body_ar',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body_de',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body_en_gb',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body_es',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body_fr',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body_ja',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body_pt',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_body_zh_hans',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 1 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading',
field=models.CharField(blank=True, max_length=255, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading_ar',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading_de',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading_en_gb',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading_es',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading_fr',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading_ja',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading_pt',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_heading_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 1 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_one_icon_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 1 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body',
field=models.TextField(blank=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body_ar',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body_de',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body_en_gb',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body_es',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body_fr',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body_ja',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body_pt',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_body_zh_hans',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 6 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading',
field=models.CharField(blank=True, max_length=255, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading_ar',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading_de',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading_en_gb',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading_es',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading_fr',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading_ja',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading_pt',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_heading_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 6 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_six_icon_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 6 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body',
field=models.TextField(blank=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body_ar',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body_de',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body_en_gb',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body_es',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body_fr',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body_ja',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body_pt',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_body_zh_hans',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 3 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading',
field=models.CharField(blank=True, max_length=255, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading_ar',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading_de',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading_en_gb',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading_es',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading_fr',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading_ja',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading_pt',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_heading_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 3 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_three_icon_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 3 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body',
field=models.TextField(blank=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body_ar',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body_de',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body_en_gb',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body_es',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body_fr',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body_ja',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body_pt',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_body_zh_hans',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight 2 body'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading',
field=models.CharField(blank=True, max_length=255, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading_ar',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading_de',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading_en_gb',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading_es',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading_fr',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading_ja',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading_pt',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_heading_zh_hans',
field=models.CharField(blank=True, max_length=255, null=True, verbose_name='Features highlight 2 heading'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_subsection_two_icon_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image', verbose_name='Features highlight 2 icon'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser',
field=models.TextField(blank=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser_ar',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser_de',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser_en_gb',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser_es',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser_fr',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser_ja',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser_pt',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='section_two_teaser_zh_hans',
field=models.TextField(blank=True, null=True, verbose_name='Features highlight summary'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text',
field=models.CharField(default='', max_length=255),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text_ar',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text_de',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text_en_gb',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text_es',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text_fr',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text_ja',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text_pt',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='study_in_uk_cta_text_zh_hans',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text',
field=models.CharField(default='', max_length=255),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text_ar',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text_de',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text_en_gb',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text_es',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text_fr',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text_ja',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text_pt',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_call_to_action_text_zh_hans',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description',
field=core.model_fields.MarkdownField(default='', validators=[core.validators.slug_hyperlinks]),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description_ar',
field=core.model_fields.MarkdownField(null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description_de',
field=core.model_fields.MarkdownField(null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description_en_gb',
field=core.model_fields.MarkdownField(null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description_es',
field=core.model_fields.MarkdownField(null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description_fr',
field=core.model_fields.MarkdownField(null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description_ja',
field=core.model_fields.MarkdownField(null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description_pt',
field=core.model_fields.MarkdownField(null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_description_zh_hans',
field=core.model_fields.MarkdownField(null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_image_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link',
field=models.URLField(default=''),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link_ar',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link_de',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link_en_gb',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link_es',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link_fr',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link_ja',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link_pt',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_link_zh_hans',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title',
field=models.CharField(default='', max_length=255),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title_ar',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title_de',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title_en_gb',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title_es',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title_fr',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title_ja',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title_pt',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='tariffs_title_zh_hans',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content',
field=core.model_fields.MarkdownField(blank=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content_ar',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content_de',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content_en_gb',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content_es',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content_fr',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content_ja',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content_pt',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_content_zh_hans',
field=core.model_fields.MarkdownField(blank=True, null=True, validators=[core.validators.slug_hyperlinks]),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image_ar',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image_de',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image_en_gb',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image_es',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image_fr',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image_ja',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image_pt',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_image_zh_hans',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image'),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title',
field=models.CharField(default='', max_length=255),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title_ar',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title_de',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title_en_gb',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title_es',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title_fr',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title_ja',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title_pt',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='trade_title_zh_hans',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text',
field=models.CharField(default='', max_length=255),
preserve_default=False,
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text_ar',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text_de',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text_en_gb',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text_es',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text_fr',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text_ja',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text_pt',
field=models.CharField(max_length=255, null=True),
),
migrations.AddField(
model_name='greatinternationalapp',
name='visit_uk_cta_text_zh_hans',
field=models.CharField(max_length=255, null=True),
),
]
| 49.114862
| 191
| 0.643286
| 11,490
| 112,031
| 6.010009
| 0.010705
| 0.117298
| 0.149881
| 0.175947
| 0.99415
| 0.992977
| 0.992803
| 0.992658
| 0.991717
| 0.990428
| 0
| 0.008344
| 0.245807
| 112,031
| 2,280
| 192
| 49.136404
| 0.808943
| 0.000616
| 0
| 0.789265
| 1
| 0
| 0.257237
| 0.168035
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.0022
| 0
| 0.00352
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
569699be119652314d6bd81b8572564ac5760e8e
| 74,572
|
py
|
Python
|
src/devcenter/azext_devcenter/manual/_params.py
|
tbyfield/azure-cli-extensions
|
e7e5f37fdcea3afb5c4aecb61fa72eac72c2128e
|
[
"MIT"
] | null | null | null |
src/devcenter/azext_devcenter/manual/_params.py
|
tbyfield/azure-cli-extensions
|
e7e5f37fdcea3afb5c4aecb61fa72eac72c2128e
|
[
"MIT"
] | null | null | null |
src/devcenter/azext_devcenter/manual/_params.py
|
tbyfield/azure-cli-extensions
|
e7e5f37fdcea3afb5c4aecb61fa72eac72c2128e
|
[
"MIT"
] | 1
|
2022-02-14T21:43:29.000Z
|
2022-02-14T21:43:29.000Z
|
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# --------------------------------------------------------------------------------------------
# pylint: disable=line-too-long
from knack.arguments import CLIArgumentType
from azure.cli.core.commands.parameters import (
tags_type,
get_enum_type,
resource_group_name_type,
get_location_type
)
from azure.cli.core.commands.validators import (
get_default_location_from_resource_group,
validate_file_or_dict
)
from azext_devcenter.action import (
AddParameters,
AddGitHub,
AddImageReference,
AddSku
)
def load_arguments(self, _):
from azure.cli.core.commands.parameters import tags_type
with self.argument_context('devcenter dev project list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('filter_', options_list=['--filter'], type=str, help='An OData $filter clause to apply to the '
'operation.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter dev project show') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--name', '-n', '--project-name'], type=str, help='The DevCenter '
'Project upon which to execute operations.')
with self.argument_context('devcenter dev pool list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('filter_', options_list=['--filter'], type=str, help='An OData $filter clause to apply to the '
'operation.')
c.argument('project_name', options_list=['--project-name', '--project',], type=str, help='The DevCenter Project upon which to execute operations.')
with self.argument_context('devcenter dev pool show') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project',], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('pool_name', options_list=['--name', '-n', '--pool-name'], type=str, help='The name of a pool of '
'Dev Boxes.')
with self.argument_context('devcenter dev schedule list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('filter_', options_list=['--filter'], type=str, help='An OData $filter clause to apply to the '
'operation.')
c.argument('project_name', options_list=['--project-name', '--project',], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='The name of a pool of Dev Boxes.')
with self.argument_context('devcenter dev schedule show') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project',], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='The name of a pool of Dev Boxes.')
c.argument('schedule_name', options_list=['--name', '-n', '--schedule-name'], type=str, help='The name of a '
'schedule.')
with self.argument_context('devcenter dev dev-box list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('filter_', options_list=['--filter'], type=str, help='An OData $filter clause to apply to the '
'operation.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('project_name', options_list=['--project-name', '--project',], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
with self.argument_context('devcenter dev dev-box show') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('dev_box_name', options_list=['--name', '-n', '--dev-box-name'], type=str, help='The name of a Dev '
'Box.')
with self.argument_context('devcenter dev dev-box create') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('dev_box_name', options_list=['--name', '-n', '--dev-box-name'], type=str, help='The name of a Dev '
'Box.')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='The name of the Dev Box pool this machine belongs to.')
with self.argument_context('devcenter dev dev-box delete') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('dev_box_name', options_list=['--name', '-n', '--dev-box-name'], type=str, help='The name of a Dev '
'Box.')
with self.argument_context('devcenter dev dev-box get-remote-connection') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('dev_box_name', options_list=['--name', '-n', '--dev-box-name'], type=str, help='The name of a Dev '
'Box.')
with self.argument_context('devcenter dev dev-box start') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('dev_box_name', options_list=['--name', '-n', '--dev-box-name'], type=str, help='The name of a Dev '
'Box.')
with self.argument_context('devcenter dev dev-box stop') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('dev_box_name', options_list=['--name', '-n', '--dev-box-name'], type=str, help='The name of a Dev '
'Box.')
with self.argument_context('devcenter dev dev-box wait') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('dev_box_name', options_list=['--name', '-n', '--dev-box-name'], type=str, help='The name of a Dev '
'Box.')
with self.argument_context('devcenter dev environment list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
with self.argument_context('devcenter dev environment show') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', options_list=['--name', '-n', '--environment-name'], type=str, help='The name '
'of the environment.')
with self.argument_context('devcenter dev environment create') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', options_list=['--name', '-n', '--environment-name'], type=str, help='The name '
'of the environment.')
c.argument('description', type=str, help='Description of the Environment.')
c.argument('catalog_name', type=str, help='Name of the catalog.')
c.argument('catalog_item_name', type=str, help='Name of the catalog item.')
c.argument('parameters', type=validate_file_or_dict, help='Parameters object for the deploy action Expected '
'value: json-string/json-file/@json-file.')
c.argument('scheduled_tasks', type=validate_file_or_dict, help='Set of supported scheduled tasks to help '
'manage cost. Expected value: json-string/json-file/@json-file.')
c.argument('tags', tags_type)
c.argument('environment_type', type=str, help='Environment type.')
c.argument('owner', type=str, help='Identifier of the owner of this Environment.')
with self.argument_context('devcenter dev environment update') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', options_list=['--name', '-n', '--environment-name'], type=str, help='The name '
'of the environment.')
c.argument('description', type=str, help='Description of the Environment.')
c.argument('catalog_name', type=str, help='Name of the catalog.')
c.argument('catalog_item_name', type=str, help='Name of the catalog item.')
c.argument('parameters', type=validate_file_or_dict, help='Parameters object for the deploy action Expected '
'value: json-string/json-file/@json-file.')
c.argument('scheduled_tasks', type=validate_file_or_dict, help='Set of supported scheduled tasks to help '
'manage cost. Expected value: json-string/json-file/@json-file.')
c.argument('tags', tags_type)
with self.argument_context('devcenter dev environment delete') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', options_list=['--name', '-n', '--environment-name'], type=str, help='The name '
'of the environment.')
with self.argument_context('devcenter dev environment list-by-project') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
with self.argument_context('devcenter dev environment wait') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', options_list=['--name', '-n', '--environment-name'], type=str, help='The name '
'of the environment.')
with self.argument_context('devcenter dev action list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', type=str, help='The name of the environment.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter dev action show') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', type=str, help='The name of the environment.')
c.argument('action_id', type=str, help='The unique id of the action.')
with self.argument_context('devcenter dev action create') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', type=str, help='The name of the environment.')
c.argument('action_id', type=str, help='The Catalog Item action id to execute')
c.argument('parameters', type=validate_file_or_dict, help='Parameters object for the Action Expected value: '
'json-string/json-file/@json-file.')
with self.argument_context('devcenter dev action wait') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', type=str, help='The name of the environment.')
c.argument('action_id', type=str, help='The unique id of the action.')
with self.argument_context('devcenter dev artifact list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('user_id', type=str, help='The id of the user. If value is \'me\', the identity is taken from the '
'authentication context')
c.argument('environment_name', type=str, help='The name of the environment.')
c.argument('artifact_path', type=str, help='The path of the artifact.')
with self.argument_context('devcenter dev catalog-item list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter dev catalog-item show') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('catalog_item_id', type=str, help='The unique id of the catalog item.')
with self.argument_context('devcenter dev catalog-item-version list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('catalog_item_id', type=str, help='The unique id of the catalog item.')
with self.argument_context('devcenter dev catalog-item-version show') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('catalog_item_id', type=str, help='The unique id of the catalog item.')
c.argument('version', type=str, help='The version of the catalog item.')
with self.argument_context('devcenter dev environment-type list') as c:
c.argument('dev_center', options_list=['--dev-center', '-dc'], type=str, help='The DevCenter to operate on.')
c.argument('dev_center_dns_suffix', type=str, help='The DNS suffix used as the base for all devcenter '
'requests.')
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The DevCenter Project upon which to execute operations.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
#control plane
with self.argument_context('devcenter admin dev-center list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin dev-center show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--name', '-n', '--dev-center-name'], type=str, help='The name of '
'the devcenter.', id_part='name')
with self.argument_context('devcenter admin dev-center create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--name', '-n', '--dev-center-name'], type=str, help='The name of '
'the devcenter.')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('identity_type', arg_type=get_enum_type(['SystemAssigned', 'UserAssigned',
'SystemAssigned, UserAssigned', 'None']),
help='The type of identity used for the resource. The type \'SystemAssigned, UserAssigned\' '
'includes both an implicitly created identity and a user assigned identity. The type \'None\' will '
'remove any identities from the resource.', required=False, arg_group='Identity')
c.argument('user_assigned_identity', type=str, help='The user identity '
'associated with the resource. The user identity references will be an ARM resource id '
'in the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microso'
'ft.ManagedIdentity/userAssignedIdentities/{identityName}\'. ', arg_group='Identity')
with self.argument_context('devcenter admin dev-center update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--name', '-n', '--dev-center-name'], type=str, help='The name of '
'the devcenter.', id_part='name')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('identity_type', arg_type=get_enum_type(['SystemAssigned', 'UserAssigned',
'SystemAssigned, UserAssigned', 'None']),
help='The type of identity used for the resource. The type \'SystemAssigned, UserAssigned\' '
'includes both an implicitly created identity and a user assigned identity. The type \'None\' will '
'remove any identities from the resource.', required=False, arg_group='Identity')
c.argument('user_assigned_identities', type=validate_file_or_dict, help='The list of user identities '
'associated with the resource. The user identity dictionary key references will be ARM resource ids '
'in the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microso'
'ft.ManagedIdentity/userAssignedIdentities/{identityName}\'. Expected value: '
'json-string/json-file/@json-file.', arg_group='Identity')
with self.argument_context('devcenter admin dev-center delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--name', '-n', '--dev-center-name'], type=str, help='The name of '
'the devcenter.', id_part='name')
with self.argument_context('devcenter admin dev-center wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--name', '-n', '--dev-center-name'], type=str, help='The name of '
'the devcenter.', id_part='name')
with self.argument_context('devcenter admin project list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin project show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--name', '-n', '--project-name'], type=str, help='The name of the '
'project.', id_part='name')
with self.argument_context('devcenter admin project create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--name', '-n', '--project-name'], type=str, help='The name of the '
'project.')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('dev_center_id', type=str, help='Resource Id of an associated DevCenter')
c.argument('description', type=str, help='Description of the project.')
with self.argument_context('devcenter admin project update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--name', '-n', '--project-name'], type=str, help='The name of the '
'project.', id_part='name')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('dev_center_id', type=str, help='Resource Id of an associated DevCenter')
c.argument('description', type=str, help='Description of the project.')
with self.argument_context('devcenter admin project delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--name', '-n', '--project-name'], type=str, help='The name of the '
'project.', id_part='name')
with self.argument_context('devcenter admin project wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--name', '-n', '--project-name'], type=str, help='The name of the '
'project.', id_part='name')
with self.argument_context('devcenter admin attached-network list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
with self.argument_context('devcenter admin attached-network show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('attached_network_connection_name', options_list=['--name', '-n', '--attached-network-connection-name'], type=str, help='The name of the attached NetworkConnection.',
id_part='child_name_1')
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
with self.argument_context('devcenter admin attached-network create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('attached_network_connection_name', options_list=['--name', '-n', '--attached-network-connection-name'], type=str, help='The name of the attached NetworkConnection.')
c.argument('network_connection_id', type=str, help='The resource ID of the NetworkConnection you want '
'to attach to the Dev Center.')
with self.argument_context('devcenter admin attached-network update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('attached_network_connection_name', options_list=['--name', '-n', '--attached-network-connection-name'], type=str, help='The name of the attached NetworkConnection.',
id_part='child_name_1')
c.argument('network_connection_resource_id', type=str, help='The resource ID of the NetworkConnection you want '
'to attach.')
with self.argument_context('devcenter admin attached-network delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('attached_network_connection_name', options_list=['--name', '-n', '--attached-network-connection-name'], type=str, help='The name of the attached NetworkConnection.',
id_part='child_name_1')
with self.argument_context('devcenter admin attached-network wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('attached_network_connection_name', type=str, help='The name of the attached NetworkConnection.',
id_part='child_name_1')
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
with self.argument_context('devcenter admin environment-type list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
with self.argument_context('devcenter admin environment-type show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('environment_type_name', options_list=['--name', '-n', '--environment-type-name'], type=str,
help='The name of the environment type.', id_part='child_name_1')
with self.argument_context('devcenter admin environment-type create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('environment_type_name', options_list=['--name', '-n', '--environment-type-name'], type=str,
help='The name of the environment type.')
c.argument('tags', tags_type)
c.argument('description', type=str, help='Description of the environment type.')
with self.argument_context('devcenter admin environment-type update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('environment_type_name', options_list=['--name', '-n', '--environment-type-name'], type=str,
help='The name of the environment type.', id_part='child_name_1')
c.argument('tags', tags_type)
c.argument('description', type=str, help='Description of the environment type.')
with self.argument_context('devcenter admin environment-type delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('environment_type_name', options_list=['--name', '-n', '--environment-type-name'], type=str,
help='The name of the environment type.', id_part='child_name_1')
with self.argument_context('devcenter admin environment-type wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('environment_type_name', options_list=['--name', '-n', '--environment-type-name'], type=str,
help='The name of the environment type.', id_part='child_name_1')
with self.argument_context('devcenter admin project-environment-type list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin project-environment-type show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('environment_type_name', type=str, help='The name of the environment type.',
id_part='child_name_1')
with self.argument_context('devcenter admin project-environment-type create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.')
c.argument('environment_type_name', type=str, help='The name of the environment type.')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('deployment_target_id', type=str, help='Id of a subscription that the environment type will be '
'mapped to. The environment\'s resources will be deployed into this subscription.')
c.argument('status', arg_type=get_enum_type(['Enabled', 'Disabled']), help='Defines whether this Environment '
'Type can be used in this Project.')
c.argument('creator_role_assignment', type=str, help='The role definition assigned to the environment creator '
'on backing resources.')
c.argument('user_role_assignments', type=validate_file_or_dict, help='Role Assignments created on environment '
'backing resources. This is a mapping from a user object ID to an object of role definition IDs. '
'Expected value: json-string/json-file/@json-file.')
c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['None', 'SystemAssigned', 'UserAssigned',
'SystemAssigned, UserAssigned']),
help='Type of managed service identity (where both SystemAssigned and UserAssigned types are '
'allowed).', arg_group='Identity')
c.argument('user_assigned_identities', type=validate_file_or_dict, help='The set of user assigned identities '
'associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids '
'in the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microso'
'ft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty '
'objects ({}) in requests. Expected value: json-string/json-file/@json-file.',
arg_group='Identity')
with self.argument_context('devcenter admin project-environment-type update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('environment_type_name', type=str, help='The name of the environment type.',
id_part='child_name_1')
c.argument('tags', tags_type)
c.argument('deployment_target_id', type=str, help='Id of a subscription that the environment type will be '
'mapped to. The environment\'s resources will be deployed into this subscription.')
c.argument('status', arg_type=get_enum_type(['Enabled', 'Disabled']), help='Defines whether this Environment '
'Type can be used in this Project.')
c.argument('creator_role_assignment', type=str, help='The role definition assigned to the environment creator '
'on backing resources.')
c.argument('user_role_assignments', type=validate_file_or_dict, help='Role Assignments created on environment '
'backing resources. This is a mapping from a user object ID to an object of role definition IDs. '
'Expected value: json-string/json-file/@json-file.')
c.argument('type_', options_list=['--type'], arg_type=get_enum_type(['None', 'SystemAssigned', 'UserAssigned',
'SystemAssigned, UserAssigned']),
help='Type of managed service identity (where both SystemAssigned and UserAssigned types are '
'allowed).', arg_group='Identity')
c.argument('user_assigned_identities', type=validate_file_or_dict, help='The set of user assigned identities '
'associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids '
'in the form: \'/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microso'
'ft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty '
'objects ({}) in requests. Expected value: json-string/json-file/@json-file.',
arg_group='Identity')
with self.argument_context('devcenter admin project-environment-type delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('environment_type_name', type=str, help='The name of the environment type.',
id_part='child_name_1')
with self.argument_context('devcenter admin gallery list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin gallery show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('gallery_name', options_list=['--name', '-n', '--gallery-name'], type=str, help='The name of the '
'gallery.', id_part='child_name_1')
with self.argument_context('devcenter admin gallery create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('gallery_name', options_list=['--name', '-n', '--gallery-name'], type=str, help='The name of the '
'gallery.')
c.argument('gallery_resource_id', type=str, help='The resource ID of the backing Azure Compute Gallery.')
with self.argument_context('devcenter admin gallery update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('gallery_name', options_list=['--name', '-n', '--gallery-name'], type=str, help='The name of the '
'gallery.', id_part='child_name_1')
c.argument('gallery_resource_id', type=str, help='The resource ID of the backing Azure Compute Gallery.')
c.ignore('body')
with self.argument_context('devcenter admin gallery delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('gallery_name', options_list=['--name', '-n', '--gallery-name'], type=str, help='The name of the '
'gallery.', id_part='child_name_1')
with self.argument_context('devcenter admin gallery wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('gallery_name', options_list=['--name', '-n', '--gallery-name'], type=str, help='The name of the '
'gallery.', id_part='child_name_1')
with self.argument_context('devcenter admin image list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('gallery_name', type=str, help='The name of the gallery.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin image show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('gallery_name', type=str, help='The name of the gallery.', id_part='child_name_1')
c.argument('image_name', options_list=['--name', '-n', '--image-name'], type=str,
help='The name of the image.', id_part='child_name_2')
with self.argument_context('devcenter admin image-version list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('gallery_name', type=str, help='The name of the gallery.')
c.argument('image_name', type=str, help='The name of the image.')
with self.argument_context('devcenter admin image-version show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('gallery_name', type=str, help='The name of the gallery.', id_part='child_name_1')
c.argument('image_name', type=str, help='The name of the image.', id_part='child_name_2')
c.argument('version_name', type=str, help='The version of the image.', id_part='child_name_3')
with self.argument_context('devcenter admin catalog list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin catalog show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('catalog_name', options_list=['--name', '-n', '--catalog-name'], type=str, help='The name of the '
'Catalog.', id_part='child_name_1')
with self.argument_context('devcenter admin catalog create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('catalog_name', options_list=['--name', '-n', '--catalog-name'], type=str, help='The name of the '
'Catalog.')
c.argument('git_hub', action=AddGitHub, nargs='+', help='Properties for a GitHub catalog type.')
c.argument('ado_git', action=AddGitHub, nargs='+', help='Properties for an Azure DevOps catalog type.')
with self.argument_context('devcenter admin catalog update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('catalog_name', options_list=['--name', '-n', '--catalog-name'], type=str, help='The name of the '
'Catalog.', id_part='child_name_1')
c.argument('tags', tags_type)
c.argument('git_hub', action=AddGitHub, nargs='+', help='Properties for a GitHub catalog type.')
c.argument('ado_git', action=AddGitHub, nargs='+', help='Properties for an Azure DevOps catalog type.')
with self.argument_context('devcenter admin catalog delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('catalog_name', options_list=['--name', '-n', '--catalog-name'], type=str, help='The name of the '
'Catalog.', id_part='child_name_1')
with self.argument_context('devcenter admin catalog sync') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('catalog_name', options_list=['--name', '-n', '--catalog-name'], type=str, help='The name of the '
'Catalog.', id_part='child_name_1')
with self.argument_context('devcenter admin catalog wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('catalog_name', options_list=['--name', '-n', '--catalog-name'], type=str, help='The name of the '
'Catalog.', id_part='child_name_1')
with self.argument_context('devcenter admin devbox-definition list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin devbox-definition show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('dev_box_definition_name', options_list=['--name', '-n', '--devbox-definition-name'], type=str,
help='The name of the Dev Box definition.', id_part='child_name_1')
with self.argument_context('devcenter admin devbox-definition create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.')
c.argument('dev_box_definition_name', options_list=['--name', '-n', '--dev-box-definition-name'], type=str,
help='The name of the Dev Box definition.')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('image_reference', action=AddImageReference, nargs='+', help='Image reference information.')
c.argument('sku', action=AddSku, nargs='+', help='The SKU for Dev Boxes created using this definition.')
c.argument('os_storage_type', type=str, help='The storage type used for the Operating System disk of Dev Boxes '
'created using this definition.')
with self.argument_context('devcenter admin devbox-definition update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('dev_box_definition_name', options_list=['--name', '-n', '--dev-box-definition-name'], type=str,
help='The name of the Dev Box definition.', id_part='child_name_1')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('image_reference', action=AddImageReference, nargs='+', help='Image reference information.')
c.argument('sku', action=AddSku, nargs='+', help='The SKU for Dev Boxes created using this definition.')
c.argument('os_storage_type', type=str, help='The storage type used for the Operating System disk of Dev Boxes '
'created using this definition.')
with self.argument_context('devcenter admin devbox-definition delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('dev_box_definition_name', options_list=['--name', '-n', '--devbox-definition-name'], type=str,
help='The name of the Dev Box definition.', id_part='child_name_1')
with self.argument_context('devcenter admin devbox-definition wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('dev_center_name', options_list=['--dev-center-name', '--dev-center', '-dc'], type=str, help='The name of the devcenter.', id_part='name')
c.argument('dev_box_definition_name', options_list=['--name', '-n', '--devbox-definition-name'], type=str,
help='The name of the Dev Box definition.', id_part='child_name_1')
with self.argument_context('devcenter admin sku list') as c:
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin pool list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin pool show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('pool_name', options_list=['--name', '-n', '--pool-name'], type=str, help='Name of the pool.',
id_part='child_name_1')
with self.argument_context('devcenter admin pool create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.')
c.argument('pool_name', options_list=['--name', '-n', '--pool-name'], type=str, help='Name of the pool.')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('dev_box_definition_name', options_list=['--devbox-definition-name', '-d'], type=str, help='Name of a Dev Box definition in parent Project of this Pool')
c.argument('network_connection_name', options_list=['--network-connection-name', '-nc'], type=str, help='Name of a Network Connection in parent Project of this Pool')
c.argument('local_administrator', arg_type=get_enum_type(['Disabled', 'Enabled']), help='Indicates whether '
'owners of Dev Boxes in this pool are added as local administrators on the Dev Box.')
c.argument('license_type', arg_type=get_enum_type(['Windows_client']), help='Specifies the license type indicating the caller has already acquired licenses for the Dev Boxes that will be created.')
with self.argument_context('devcenter admin pool update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('pool_name', options_list=['--name', '-n', '--pool-name'], type=str, help='Name of the pool.',
id_part='child_name_1')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('dev_box_definition_name', options_list=['--devbox-definition-name', '-d'], type=str, help='Name of a Dev Box definition in parent Project of this Pool')
c.argument('network_connection_name', options_list=['--network-connection-name', '-nc'], type=str, help='Name of a Network Connection in parent Project of this Pool')
c.argument('local_administrator', arg_type=get_enum_type(['Disabled', 'Enabled']), help='Indicates whether '
'owners of Dev Boxes in this pool are added as local administrators on the Dev Box.')
c.argument('license_type', arg_type=get_enum_type(['Windows_client']), help='Specifies the license type indicating the caller has already acquired licenses for the Dev Boxes that will be created.')
with self.argument_context('devcenter admin pool delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('pool_name', options_list=['--name', '-n', '--pool-name'], type=str, help='Name of the pool.',
id_part='child_name_1')
with self.argument_context('devcenter admin pool wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('pool_name', options_list=['--name', '-n', '--pool-name'], type=str, help='Name of the pool.',
id_part='child_name_1')
with self.argument_context('devcenter admin schedule list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='Name of the pool.')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin schedule show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='Name of the pool.', id_part='child_name_1')
c.argument('schedule_name', options_list=['--name', '-n', '--schedule-name'], type=str, help='The name of the '
'schedule that uniquely identifies it.', id_part='child_name_2')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin schedule create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='Name of the pool.')
c.argument('schedule_name', options_list=['--name', '-n', '--schedule-name'], type=str, help='The name of the '
'schedule that uniquely identifies it.')
c.argument('schedule_type', required=True, arg_type=get_enum_type(['StopDevBox']), help='The type of schedule.')
c.argument('frequency', required=True, arg_type=get_enum_type(['Daily']), help='The frequency the schedule will execute.')
c.argument('time', required=True, type=str, help='The target time to trigger the action. The format is HH:MM.')
c.argument('time_zone', required=True, type=str, help='The IANA timezone id at which the schedule should execute.')
c.argument('state', arg_type=get_enum_type(['Enabled', 'Disabled']), help='Indicates whether or not this '
'scheduled task is enabled.')
with self.argument_context('devcenter admin schedule update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='Name of the pool.', id_part='child_name_1')
c.argument('schedule_name', options_list=['--name', '-n', '--schedule-name'], type=str, help='The name of the '
'schedule that uniquely identifies it.', id_part='child_name_2')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('time', type=str, help='The target time to trigger the action. The format is HH:MM.')
c.argument('time_zone', type=str, help='The IANA timezone id at which the schedule should execute.')
c.argument('state', arg_type=get_enum_type(['Enabled', 'Disabled']), help='Indicates whether or not this '
'scheduled task is enabled.')
with self.argument_context('devcenter admin schedule delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='Name of the pool.', id_part='child_name_1')
c.argument('schedule_name', options_list=['--name', '-n', '--schedule-name'], type=str, help='The name of the '
'schedule that uniquely identifies it.', id_part='child_name_2')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin schedule wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('project_name', options_list=['--project-name', '--project'], type=str, help='The name of the project.', id_part='name')
c.argument('pool_name', options_list=['--pool-name', '--pool'], type=str, help='Name of the pool.', id_part='child_name_1')
c.argument('schedule_name', options_list=['--name', '-n', '--schedule-name'], type=str, help='The name of the '
'schedule that uniquely identifies it.', id_part='child_name_2')
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin network-connection list') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('top', type=int, help='The maximum number of resources to return from the operation. Example: '
'\'$top=10\'.')
with self.argument_context('devcenter admin network-connection show') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('network_setting_name', options_list=['--name', '-n', '--network-connection-name'], type=str,
help='Name of the Network Settings that can be applied to a Pool.', id_part='name')
with self.argument_context('devcenter admin network-connection create') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('network_setting_name', options_list=['--name', '-n', '--network-connection-name'], type=str,
help='Name of the Network Settings that can be applied to a Pool.')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('subnet_id', required=True, type=str, help='The subnet to attach Virtual Machines to')
c.argument('domain_name', type=str, help='Active Directory domain name')
c.argument('organization_unit', type=str, help='Active Directory domain Organization Unit (OU)')
c.argument('domain_username', type=str, help='The username of an Active Directory account (user or service '
'account) that has permissions to create computer objects in Active Directory. Required format: '
'admin@contoso.com.')
c.argument('domain_password', type=str, help='The password for the account used to join domain')
c.argument('networking_resource_group_name', type=str, help='The name for the managed resource group where NICs will be '
'placed.')
c.argument('domain_join_type', required=True, arg_type=get_enum_type(['HybridAzureADJoin', 'AzureADJoin']), help='AAD Join '
'type.')
with self.argument_context('devcenter admin network-connection update') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('network_setting_name', options_list=['--name', '-n', '--network-connection-name'], type=str,
help='Name of the Network Settings that can be applied to a Pool.', id_part='name')
c.argument('tags', tags_type)
c.argument('location', arg_type=get_location_type(self.cli_ctx), required=False,
validator=get_default_location_from_resource_group)
c.argument('subnet_id', type=str, help='The subnet to attach Virtual Machines to')
c.argument('domain_name', type=str, help='Active Directory domain name')
c.argument('organization_unit', type=str, help='Active Directory domain Organization Unit (OU)')
c.argument('domain_username', type=str, help='The username of an Active Directory account (user or service '
'account) that has permissions to create computer objects in Active Directory. Required format: '
'admin@contoso.com.')
c.argument('domain_password', type=str, help='The password for the account used to join domain')
with self.argument_context('devcenter admin network-connection delete') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('network_setting_name', options_list=['--name', '-n', '--network-connection-name'], type=str,
help='Name of the Network Settings that can be applied to a Pool.', id_part='name')
with self.argument_context('devcenter admin network-connection show-health-detail') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('network_setting_name', options_list=['--name', '-n', '--network-connection-name'], type=str,
help='Name of the Network Settings that can be applied to a Pool.', id_part='name')
with self.argument_context('devcenter admin network-connection run-health-check') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('network_connection_name', options_list=['--name', '-n', '--network-connection-name'], type=str,
help='Name of the Network Connection that can be applied to a Pool.', id_part='name')
with self.argument_context('devcenter admin network-connection wait') as c:
c.argument('resource_group_name', resource_group_name_type)
c.argument('network_setting_name', options_list=['--name', '-n', '--network-connection-name'], type=str,
help='Name of the Network Settings that can be applied to a Pool.', id_part='name')
| 79.079533
| 205
| 0.65483
| 10,044
| 74,572
| 4.704699
| 0.031462
| 0.091421
| 0.07356
| 0.079993
| 0.9767
| 0.975494
| 0.973124
| 0.96267
| 0.946438
| 0.943179
| 0
| 0.001656
| 0.198184
| 74,572
| 942
| 206
| 79.163482
| 0.788637
| 0.005082
| 0
| 0.782871
| 0
| 0
| 0.466395
| 0.038848
| 0
| 0
| 0
| 0
| 0
| 1
| 0.001206
| false
| 0.002413
| 0.006031
| 0
| 0.007238
| 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
|
3b7a5c9c093170b2107ba98bd793c6ce7296bff7
| 1,605
|
py
|
Python
|
tests/test_wallet/test_wallet.py
|
KarolBedkowski/marketools
|
4f4a25407916bf9077c7e264ab6e6053d893b218
|
[
"BSD-3-Clause"
] | 56
|
2020-11-29T20:34:29.000Z
|
2022-02-28T01:11:51.000Z
|
tests/test_wallet/test_wallet.py
|
KarolBedkowski/marketools
|
4f4a25407916bf9077c7e264ab6e6053d893b218
|
[
"BSD-3-Clause"
] | 21
|
2020-11-29T13:06:04.000Z
|
2020-12-20T16:46:36.000Z
|
tests/test_wallet/test_wallet.py
|
KarolBedkowski/marketools
|
4f4a25407916bf9077c7e264ab6e6053d893b218
|
[
"BSD-3-Clause"
] | 8
|
2020-12-01T15:41:05.000Z
|
2021-08-21T08:55:57.000Z
|
from marketools import Wallet
from marketools.wallet import calculate_investment_value
def test_calculate_investment_value__max():
wallet = Wallet(0.01, 3) # min recomended investment = 300
wallet.money = 10000
max_fraction = 5
expected_result = 2000
result = calculate_investment_value(wallet, max_fraction)
assert expected_result == result
def test_calculate_investment_value__low_money():
wallet = Wallet(0.01, 3) # min recomended investment = 300
wallet.money = 100
max_fraction = 5
expected_result = 0
result = calculate_investment_value(wallet, max_fraction)
assert expected_result == result
def test_calculate_investment_value__min():
wallet = Wallet(0.01, 3) # min recomended investment = 300
wallet.money = 500
max_fraction = 5
expected_result = 300
result = calculate_investment_value(wallet, max_fraction)
assert expected_result == result
def test_calculate_investment_value__invest_all():
wallet = Wallet(0.01, 3) # min recomended investment = 300
wallet.money = 2000
wallet.buy('CCC', 20, 50) # cost = 1010
max_fraction = 2
expected_result = 990
result = calculate_investment_value(wallet, max_fraction)
assert expected_result == result
def test_calculate_investment_value__no_money():
wallet = Wallet(0.01, 3) # min recomended investment = 300
wallet.money = 1010
wallet.buy('CCC', 20, 50) # cost = 1010
max_fraction = 2
expected_result = 0
result = calculate_investment_value(wallet, max_fraction)
assert expected_result == result
| 26.75
| 63
| 0.722741
| 203
| 1,605
| 5.418719
| 0.187192
| 0.19
| 0.24
| 0.118182
| 0.886364
| 0.8
| 0.8
| 0.8
| 0.8
| 0.8
| 0
| 0.068022
| 0.203115
| 1,605
| 60
| 64
| 26.75
| 0.792025
| 0.114019
| 0
| 0.615385
| 0
| 0
| 0.00424
| 0
| 0
| 0
| 0
| 0
| 0.128205
| 1
| 0.128205
| false
| 0
| 0.051282
| 0
| 0.179487
| 0
| 0
| 0
| 0
| null | 0
| 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
| 7
|
8e5b12ef11af1a04cfb680f1ac5bf206a17f877b
| 7,659
|
py
|
Python
|
instancegen/smps_instance_classes.py
|
stephenjmaher/GenStoch
|
68a8dbb0aabfb126296853712be393f670d908bc
|
[
"MIT"
] | null | null | null |
instancegen/smps_instance_classes.py
|
stephenjmaher/GenStoch
|
68a8dbb0aabfb126296853712be393f670d908bc
|
[
"MIT"
] | null | null | null |
instancegen/smps_instance_classes.py
|
stephenjmaher/GenStoch
|
68a8dbb0aabfb126296853712be393f670d908bc
|
[
"MIT"
] | null | null | null |
"""
The MIT License (MIT)
@author: Stephen J. Maher
"""
import numpy as np
from .smps_instance import Instance
class RRTailAssignInstance(Instance):
'''
SMPS output functions for the recoverable robustness tail assignment problem
'''
def writeCoefStochasticFile(self, outfile, nscenarios):
'''
writes the scenarios with coefficient stochasticity
'''
# storing the first stage RHS to compute the standard deviationi
stage = 0
secondstagecons = []
for cons in self.constraints:
if cons == self.periods[1][2]:
stage += 1
if stage == 1:
secondstagecons.append(cons)
secondstagevars = []
stage = 0
for var in self.variables:
if var == self.periods[1][1]:
stage += 1
if stage == 1:
secondstagevars.append(var)
# writing the scenarios to the STO file
weight = 1.0/float(nscenarios)
for i in range(nscenarios):
outfile.write(" SC SCEN%d ROOT %g %s 0.0\n"%(i + 1, weight, self.periods[1][0]))
for cons in secondstagecons:
if cons.startswith("RecoveryFlight"):
for var in secondstagevars:
if var.startswith("Recovery") and (var, cons) in self.coeffs and self.coeffs[var, cons] == 1:
randcoef = 1 - np.random.binomial(1, 0.01)
if randcoef == 0:
outfile.write(" %s %s %g\n"%(var, cons, randcoef))
def writeObjStochasticFile(self, outfile, nscenarios):
'''
writes the scenarios with objective stochasticity
'''
secondstagevars = []
stage = 0
for var in self.variables:
if var == self.periods[1][1]:
stage += 1
if stage == 1:
if var.startswith('Recovery'):
secondstagevars.append(var)
# writing the scenarios to the STO file
weight = 1.0/float(nscenarios)
for i in range(nscenarios):
outfile.write(" SC SCEN%d ROOT %g %s 0.0\n"%(i + 1, weight, self.periods[1][0]))
for var in secondstagevars:
if np.random.binomial(1, 0.1) == 1:
randobj = (np.random.poisson() + 1)*100
outfile.write(" %s obj %g\n"%(var, randobj))
class SSLPInstance(Instance):
'''
SMPS output functions for SSLP instances
'''
def writeStageFile(self, outfile):
'''
writes the stages file for a given core file
'''
stageconsstart = []
stagevarstart = []
# scanning all of the constraints to find the different stages
stageconsstart.append(self.constraints[0])
for cons in self.constraints[1:]:
if cons.startswith("c2"):
stageconsstart.append(cons)
break
# scanning all of the variables to find the different stages
stagevarstart.append(self.variables[0])
for var in self.variables[1:]:
if var.startswith("y_1_1"):
stagevarstart.append(var)
break
# writing the stages to the TIM file
assert len(stageconsstart) == len(stagevarstart)
for i in range(len(stageconsstart)):
outfile.write(" %s %s STAGE-%d\n"%(stagevarstart[i],
stageconsstart[i], i + 1))
def writeRhsStochasticFile(self, outfile, nscenarios):
'''
writes the scenarios with RHS stochasticity
'''
# storing the first stage RHS to compute the standard deviationi
#pdb.set_trace()
stage = 0
stagerhs = []
secondstagecons = []
for cons in self.constraints:
if cons == self.periods[1][2]:
stage += 1
if stage == 0:
stagerhs.append(self.rhs[cons])
else:
secondstagecons.append(cons)
# computing the standard deviation
stagestd = np.std(stagerhs)*2
# writing the scenarios to the STO file
weight = 1.0/float(nscenarios)
for i in range(nscenarios):
outfile.write(" SC SCEN%d ROOT %g %s\n"%(i + 1, weight, self.periods[1][0]))
for cons in secondstagecons:
# computing the RHS of the constraint from a normal distribution
#randrhs = int(np.random.normal(self.rhs[cons], stagestd))
randrhs = round(np.random.random_sample())
outfile.write(" RHS %s %g\n"%(cons, randrhs))
class NoswotInstance(Instance):
'''
SMPS output functions for the MIPLIB noswot instance
'''
def writeStageFile(self, outfile):
'''
writes the stages file for a given core file
'''
stageconsstart = []
stagevarstart = []
# scanning all of the constraints to find the different stages
stageconsstart.append(self.constraints[0])
for cons in self.constraints[1:]:
if cons.startswith("p"):
stageconsstart.append(cons)
break
# scanning all of the variables to find the different stages
stagevarstart.append(self.variables[0])
for var in self.variables[1:]:
if var.startswith("pr"):
stagevarstart.append(var)
break
# writing the stages to the TIM file
assert len(stageconsstart) == len(stagevarstart)
for i in range(len(stageconsstart)):
outfile.write(" %s %s STAGE-%d\n"%(stagevarstart[i],
stageconsstart[i], i + 1))
def writeRhsStochasticFile(self, outfile, nscenarios):
'''
writes the scenarios with RHS stochasticity
'''
# storing the first stage RHS to compute the standard deviationi
stage = 0
stagerhs = []
secondstagecons = []
for cons in self.constraints:
if cons == self.periods[1][2]:
stage += 1
if stage == 0:
stagerhs.append(self.rhs[cons])
else:
secondstagecons.append(cons)
# computing the standard deviation
stagestd = np.std(stagerhs)*2
# writing the scenarios to the STO file
weight = 1.0/float(nscenarios)
for i in range(nscenarios):
outfile.write(" SC SCEN%d ROOT %g %s\n"%(i + 1, weight, self.periods[1][0]))
#for cons in secondstagecons:
## computing the RHS of the constraint from a normal distribution
##randrhs = int(np.random.normal(self.rhs[cons], stagestd))
#randrhs = round(np.random.random_sample())
#outfile.write(" RHS %s %g\n"%(cons, randrhs))
class SnipInstance(Instance):
'''
SMPS output functions for the SNIP instances
'''
def writeStageFile(self, outfile):
'''
writes the stages file for a given core file
'''
stageconsstart = []
stagevarstart = []
# scanning all of the constraints to find the different stages
stageconsstart.append(self.constraints[0])
for cons in self.constraints[1:]:
if cons.startswith("sinkcons"):
stageconsstart.append(cons)
break
# scanning all of the variables to find the different stages
stagevarstart.append(self.variables[0])
for var in self.variables[1:]:
if var.startswith("node"):
stagevarstart.append(var)
break
# writing the stages to the TIM file
assert len(stageconsstart) == len(stagevarstart)
for i in range(len(stageconsstart)):
outfile.write(" %s %s STAGE-%d\n"%(stagevarstart[i],
stageconsstart[i], i + 1))
| 33.012931
| 116
| 0.576577
| 881
| 7,659
| 5.005675
| 0.14983
| 0.016327
| 0.018367
| 0.01746
| 0.867574
| 0.841723
| 0.819274
| 0.799773
| 0.799773
| 0.799773
| 0
| 0.016148
| 0.320799
| 7,659
| 231
| 117
| 33.155844
| 0.831603
| 0.242068
| 0
| 0.80916
| 0
| 0
| 0.077708
| 0
| 0
| 0
| 0
| 0
| 0.022901
| 1
| 0.053435
| false
| 0
| 0.015267
| 0
| 0.099237
| 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
|
8e91d15cdf011d844f26fe4d3e57e0ea38639d88
| 43,478
|
py
|
Python
|
tests/ashley/api/test_api_manage_moderators.py
|
openfun/ashley
|
33af6a46bc22c86417c200fdd84876c2c46b02ce
|
[
"MIT"
] | 6
|
2020-05-05T11:50:29.000Z
|
2021-09-19T06:01:39.000Z
|
tests/ashley/api/test_api_manage_moderators.py
|
openfun/ashley
|
33af6a46bc22c86417c200fdd84876c2c46b02ce
|
[
"MIT"
] | 93
|
2020-02-17T16:28:57.000Z
|
2022-03-18T14:06:45.000Z
|
tests/ashley/api/test_api_manage_moderators.py
|
openfun/ashley
|
33af6a46bc22c86417c200fdd84876c2c46b02ce
|
[
"MIT"
] | 1
|
2020-03-02T04:36:12.000Z
|
2020-03-02T04:36:12.000Z
|
"""Tests API to manage moderators."""
import json
from django.contrib.auth import get_user_model
from django.test import TestCase
from machina.apps.forum_permission.shortcuts import assign_perm
from ashley import SESSION_LTI_CONTEXT_ID
from ashley.defaults import _FORUM_ROLE_MODERATOR
from ashley.factories import ForumFactory, LTIContextFactory, UserFactory
User = get_user_model()
class ManageModeratorApiTest(TestCase):
"""Test the API to manage moderators."""
def test_access_basic_api_manage_moderator_list_users(self):
"""Anonymous users should not be allowed to retrieve list of users."""
response = self.client.get("/api/v1.0/users/")
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "Authentication credentials were not provided."}
)
def test_access_can_manage_moderators_moderator_list_users(self):
"""Users that can manage moderators should be able to use the API to request
list of users"""
user = UserFactory()
lti_context = LTIContextFactory(lti_consumer=user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
self.client.force_login(user, "ashley.auth.backend.LTIBackend")
response = self.client.get("/api/v1.0/users/")
# First it's forbidden
self.assertEqual(403, response.status_code)
# Add session
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
self.assertEqual(
self.client.session.get(SESSION_LTI_CONTEXT_ID), lti_context.id
)
response = self.client.get("/api/v1.0/users/")
# Still forbidden session ok but missing permission
self.assertEqual(response.status_code, 403)
assign_perm("can_manage_moderator", user, forum, True)
# Should now be authorized
response = self.client.get("/api/v1.0/users/")
self.assertEqual(response.status_code, 200)
def test_access_basic_api_manage_moderator_list_students(self):
"""Anonymous users should not be allowed to retrieve list of students."""
response = self.client.get("/api/v1.0/users/?role=student")
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "Authentication credentials were not provided."}
)
def test_access_can_manage_moderators_moderator_list_students(self):
"""Users that can manage moderators should be able to use the API to request
list of students"""
user = UserFactory()
lti_context = LTIContextFactory(lti_consumer=user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
self.client.force_login(user, "ashley.auth.backend.LTIBackend")
response = self.client.get("/api/v1.0/users/?role=student")
# First it's forbidden
self.assertEqual(403, response.status_code)
# Add session
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
self.assertEqual(
self.client.session.get(SESSION_LTI_CONTEXT_ID), lti_context.id
)
response = self.client.get("/api/v1.0/users/?role=student")
# Still forbidden session ok but missing permission
self.assertEqual(response.status_code, 403)
assign_perm("can_manage_moderator", user, forum, True)
# Should now be authorized
response = self.client.get("/api/v1.0/users/?role=student")
self.assertEqual(response.status_code, 200)
def test_access_basic_api_manage_moderator_list_moderators(self):
"""Anonymous users should not be allowed to retrieve list of moderators."""
response = self.client.get("/api/v1.0/users/?role=moderator")
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "Authentication credentials were not provided."}
)
def test_access_can_manage_moderators_list_moderators(self):
"""Users that can manage moderators should be able to use the API to request
list of moderators"""
user = UserFactory()
lti_context = LTIContextFactory(lti_consumer=user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
self.client.force_login(user, "ashley.auth.backend.LTIBackend")
response = self.client.get("/api/v1.0/users/?role=moderator")
# First it's forbidden
self.assertEqual(403, response.status_code)
# Add permission
assign_perm("can_manage_moderator", user, forum, True)
# Still forbidden, missing the session
response = self.client.get("/api/v1.0/users/?role=moderator")
self.assertEqual(403, response.status_code)
# Add session
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
self.assertEqual(
self.client.session.get(SESSION_LTI_CONTEXT_ID), lti_context.id
)
response = self.client.get("/api/v1.0/users/?role=moderator")
# Permission + session added, it should be allowed
self.assertEqual(response.status_code, 200)
def test_access_basic_api_manage_moderator_list_instructors(self):
"""Anonymous users should not be allowed to retrieve list of instructors."""
response = self.client.get("/api/v1.0/users/?role=instructor")
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "Authentication credentials were not provided."}
)
def test_access_can_manage_moderators_moderator_list_instructors(self):
"""Users that can manage moderators should be able to use the API to request
list of instructors"""
user = UserFactory()
lti_context = LTIContextFactory(lti_consumer=user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
self.client.force_login(user, "ashley.auth.backend.LTIBackend")
response = self.client.get("/api/v1.0/users/?role=instructor")
# First it's forbidden
self.assertEqual(403, response.status_code)
# Add session
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
self.assertEqual(
self.client.session.get(SESSION_LTI_CONTEXT_ID), lti_context.id
)
response = self.client.get("/api/v1.0/users/?role=instructor")
# Still forbidden session ok but missing permission
self.assertEqual(response.status_code, 403)
assign_perm("can_manage_moderator", user, forum, True)
# Should now be authorized
response = self.client.get("/api/v1.0/users/?role=instructor")
self.assertEqual(response.status_code, 200)
def test_access_basic_api_manage_moderator_list_not_moderators(self):
"""Anonymous users should not be allowed to retrieve list of non moderators."""
response = self.client.get("/api/v1.0/users/?role=!moderator")
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "Authentication credentials were not provided."}
)
def test_access_can_manage_moderators_list_non_moderators(self):
"""Users that can manage moderators should be able to use the API to request
list of users that are not moderators"""
user = UserFactory()
lti_context = LTIContextFactory(lti_consumer=user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
self.client.force_login(user, "ashley.auth.backend.LTIBackend")
response = self.client.get("/api/v1.0/users/?role=!moderator")
# First it's forbidden
self.assertEqual(403, response.status_code)
# Add permission
assign_perm("can_manage_moderator", user, forum, True)
# Still forbidden, missing the session
response = self.client.get("/api/v1.0/users/?!role=moderator")
self.assertEqual(403, response.status_code)
# Add session
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
self.assertEqual(
self.client.session.get(SESSION_LTI_CONTEXT_ID), lti_context.id
)
response = self.client.get("/api/v1.0/users/?role=!moderator")
# Permission + session added, it should be allowed
self.assertEqual(response.status_code, 200)
def test_access_api_can_manage_moderators_update_student_promote(self):
"""
Promote and revoke a user with right context, permission, group
Test to validate that update request API is working when everything
is set properly.
"""
update_user = UserFactory(public_username="Thérèse")
api_user = UserFactory(lti_consumer=update_user.lti_consumer)
lti_context = LTIContextFactory(lti_consumer=update_user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
# Assign student group to user
lti_context.sync_user_groups(update_user, ["student"])
# Check list group of the user
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
],
list(update_user.groups.values_list("name", flat=True)),
)
# Assign the permission
assign_perm("can_manage_moderator", api_user, forum, True)
# Creates the session
self.client.force_login(api_user, "ashley.auth.backend.LTIBackend")
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
# Promote user to moderator
data = {"roles": ["student", "moderator"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(content, {"success": True})
# Check group moderator is part of group of the user
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
f"{lti_context.base_group_name}:role:moderator",
],
list(update_user.groups.values_list("name", flat=True)),
)
# Then Revoke user to moderator
data = {
"roles": ["student"],
}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(content, {"success": True})
# Check group moderator is not part of users's group
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
],
list(update_user.groups.values_list("name", flat=True)),
)
def test_access_api_basic_manage_moderator_update_student(self):
"""Standard call should not be allowed to update a student."""
user = UserFactory()
data = {
"roles": ["moderator"],
}
response = self.client.post(
f"/api/v1.0/users/{user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "Authentication credentials were not provided."}
)
def test_access_api_can_manage_moderators_update_student_no_group_context(self):
"""Users that don't have a group from this context can't be promoted moderator"""
update_user = UserFactory()
api_user = UserFactory(lti_consumer=update_user.lti_consumer)
lti_context = LTIContextFactory(lti_consumer=update_user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
# Assign the permission
assign_perm("can_manage_moderator", api_user, forum, True)
# Creates the session
self.client.force_login(api_user, "ashley.auth.backend.LTIBackend")
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
# Data to promote user to moderator
data = {
"roles": ["moderator"],
}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "You do not have permission to perform this action."}
)
# Add group student and it should work
lti_context.sync_user_groups(update_user, ["student"])
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
def test_access_api_can_manage_moderators_update_student_no_group_moderator(self):
"""If moderator group doesn't exist user can be updated and group created
Case for forum created before this feature"""
update_user = UserFactory()
api_user = UserFactory(lti_consumer=update_user.lti_consumer)
lti_context = LTIContextFactory(lti_consumer=update_user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
# Add group student
lti_context.sync_user_groups(update_user, ["student"])
# Assign the permission
assign_perm("can_manage_moderator", api_user, forum, True)
# Creates the session
self.client.force_login(api_user, "ashley.auth.backend.LTIBackend")
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
# Data to promote user to moderator
data = {
"roles": ["moderator"],
}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
def test_access_api_can_manage_moderators_update_student_no_session(self):
"""Users with no session can't update user"""
update_user = UserFactory()
api_user = UserFactory(lti_consumer=update_user.lti_consumer)
lti_context = LTIContextFactory(lti_consumer=update_user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
# Assign student group to user
lti_context.sync_user_groups(update_user, ["student"])
# Assign the permission
assign_perm("can_manage_moderator", api_user, forum, True)
#
data = {
"roles": ["moderator"],
}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "Authentication credentials were not provided."}
)
# Create the session and it should work
self.client.force_login(api_user, "ashley.auth.backend.LTIBackend")
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
def _login_authorized_user_to_manage_moderators(self):
"""
Access to API has been tested in previous tests. This method is a shortcut for tests
below to retrieve a granted user for the API and the current lti_context.
"""
api_user = UserFactory()
lti_context = LTIContextFactory(lti_consumer=api_user.lti_consumer)
forum = ForumFactory()
forum.lti_contexts.add(lti_context)
# Assign the permission for API user
assign_perm("can_manage_moderator", api_user, forum, True)
# Create the session and it should work
self.client.force_login(api_user, "ashley.auth.backend.LTIBackend")
session = self.client.session
session[SESSION_LTI_CONTEXT_ID] = lti_context.id
session.save()
return api_user, lti_context
def test_access_api_can_manage_moderators_update_student_no_role(self):
"""If roles is not present or is defined to unexpected value, promote moderator is
not allowed"""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
# Creates user to update
update_user = UserFactory(lti_consumer=api_user.lti_consumer)
lti_context.sync_user_groups(update_user, ["student"])
data = {
"id": update_user.id,
}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "You do not have permission to perform this action."}
)
# Change data, add role parameter to ’whatever’
data = {"roles": ["whatever"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 403)
# Change data, add roles parameter to ’instructor’, it's not allowed
data = {"roles": ["instructor"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 403)
# Change data, add roles parameter to ’moderator’ and it should work
data = {"roles": ["moderator"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
def test_revoke_moderator_on_student(self):
"""A user that is not moderator can't be revoked"""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
# Creates user to update
update_user = UserFactory(lti_consumer=api_user.lti_consumer)
lti_context.sync_user_groups(update_user, ["student"])
data = {"roles": ["student"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "You do not have permission to perform this action."}
)
# Assign moderator group to user
lti_context.sync_user_groups(update_user, ["student", "moderator"])
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
f"{lti_context.base_group_name}:role:moderator",
],
list(update_user.groups.values_list("name", flat=True)),
)
# Revoke should now be ok
data = {"id": update_user.id, "roles": ["student"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
# Check group moderator is not part of users's group
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
],
list(update_user.groups.values_list("name", flat=True)),
)
def test_promote_on_moderator_student(self):
"""A user that is moderator can't be promoted"""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
# Assign moderator group to user
update_user = UserFactory(lti_consumer=api_user.lti_consumer)
lti_context.sync_user_groups(update_user, ["student", "moderator"])
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
f"{lti_context.base_group_name}:role:moderator",
],
list(update_user.groups.values_list("name", flat=True)),
)
# Promote shouldn't work
data = {"roles": ["moderator"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 403)
content = json.loads(response.content)
self.assertEqual(
content, {"detail": "You do not have permission to perform this action."}
)
# Revoke should work
data = {"id": update_user.id, "roles": ["student"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
],
list(update_user.groups.values_list("name", flat=True)),
)
# Now promote should work
data = {"id": update_user.id, "roles": ["moderator"]}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
f"{lti_context.base_group_name}:role:moderator",
],
list(update_user.groups.values_list("name", flat=True)),
)
def test_list_users(self):
"""Controls that the list returned by the API contains expected users"""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
user1 = UserFactory(
public_username="Thomas", lti_consumer=api_user.lti_consumer
)
user2 = UserFactory(
public_username="Aurélie", lti_consumer=api_user.lti_consumer
)
user3 = UserFactory(public_username="Abba", lti_consumer=api_user.lti_consumer)
user4 = UserFactory(
public_username="Silvio", lti_consumer=api_user.lti_consumer
)
UserFactory(public_username="Abdel", lti_consumer=api_user.lti_consumer)
lti_context.sync_user_groups(user1, ["student"])
lti_context.sync_user_groups(user2, ["student"])
lti_context.sync_user_groups(user3, ["student", "moderator"]),
lti_context.sync_user_groups(user4, ["instructor"])
# Request with no filter returns the list of users but user5 that has no roles
# list ordered by public_username
response = self.client.get("/api/v1.0/users/", content_type="application/json")
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user3.id,
"public_username": "Abba",
"roles": ["moderator", "student"],
},
{"id": user2.id, "public_username": "Aurélie", "roles": ["student"]},
{"id": user4.id, "public_username": "Silvio", "roles": ["instructor"]},
{"id": user1.id, "public_username": "Thomas", "roles": ["student"]},
],
)
response = self.client.get(
"/api/v1.0/users/?role=student", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user3.id,
"public_username": "Abba",
"roles": ["moderator", "student"],
},
{"id": user2.id, "public_username": "Aurélie", "roles": ["student"]},
{"id": user1.id, "public_username": "Thomas", "roles": ["student"]},
],
)
response = self.client.get(
"/api/v1.0/users/?role=moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user3.id,
"public_username": "Abba",
"roles": ["moderator", "student"],
},
],
)
response = self.client.get(
"/api/v1.0/users/?role=instructor", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{"id": user4.id, "public_username": "Silvio", "roles": ["instructor"]},
],
)
def test_list_moderators_with_student_groups(self):
"""Creates users with roles student and moderator, this user should be part of the
list of moderators and be part as well of the list of student group."""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
user1 = UserFactory(
public_username="Thomas", lti_consumer=api_user.lti_consumer
)
lti_context.sync_user_groups(user1, ["student", "moderator"])
# should be part of list student
response = self.client.get(
"/api/v1.0/users/?role=student", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user1.id,
"public_username": "Thomas",
"roles": ["moderator", "student"],
},
],
)
# should be part of list moderator
response = self.client.get(
"/api/v1.0/users/?role=moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user1.id,
"public_username": "Thomas",
"roles": ["moderator", "student"],
},
],
)
# should not be part of list !moderator
response = self.client.get(
"/api/v1.0/users/?role=!moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[],
)
# should be part of list of users
response = self.client.get("/api/v1.0/users/", content_type="application/json")
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user1.id,
"public_username": "Thomas",
"roles": ["moderator", "student"],
},
],
)
# should not be part of list of not moderators
response = self.client.get(
"/api/v1.0/users/?role=!moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[],
)
def test_list_moderators_with_instructor_groups(self):
"""Creates users with roles instructor and moderator, this user should be part
of the list of instructor only. Instructors are excluded from moderator list."""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
user1 = UserFactory(
public_username="Thomas", lti_consumer=api_user.lti_consumer
)
lti_context.sync_user_groups(user1, ["instructor", "moderator"])
# student list should be empty
response = self.client.get(
"/api/v1.0/users/?role=student", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[],
)
# moderator list should be empty because user1 is instructor
response = self.client.get(
"/api/v1.0/users/?role=moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[],
)
# instructor list should contain user1
response = self.client.get(
"/api/v1.0/users/?role=instructor", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user1.id,
"public_username": "Thomas",
"roles": ["instructor", "moderator"],
},
],
)
# !moderator list should not contain user1 because user1 is instructor and excluded
# from not moderators
response = self.client.get(
"/api/v1.0/users/?role=!moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[],
)
response = self.client.get("/api/v1.0/users/", content_type="application/json")
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user1.id,
"public_username": "Thomas",
"roles": ["instructor", "moderator"],
},
],
)
def test_list_users_no_moderator_if_no_group_in_context(self):
"""Controls that list of moderators only concerns users that are part of
users that have group in this context
"""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
user1 = UserFactory(
public_username="Thomas", lti_consumer=api_user.lti_consumer
)
# add group moderator
group_moderator = lti_context.get_role_group(_FORUM_ROLE_MODERATOR)
user1.groups.add(group_moderator)
user1.save()
# check user has group moderator
self.assertCountEqual(
[f"{lti_context.base_group_name}:role:moderator"],
list(user1.groups.values_list("name", flat=True)),
)
# request users that are moderator
response = self.client.get(
"/api/v1.0/users/?role=moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
# should be empty because user has no other groups from this context
self.assertEqual(content, [])
# request all users
response = self.client.get("/api/v1.0/users/", content_type="application/json")
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
# should be empty because user has no other groups from this context
self.assertEqual(
content,
[],
)
# request all users that are not moderators
response = self.client.get(
"/api/v1.0/users/?role=!moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
# should be empty because user has no other groups from this context
self.assertEqual(
content,
[],
)
def test_list_users_moderator_if_group_in_context(self):
"""Controls moderator list"""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
user1 = UserFactory(
public_username="Thomas", lti_consumer=api_user.lti_consumer
)
# add group moderator and base group of this context
lti_context.sync_user_groups(user1, ["moderator"])
# check user has group moderator
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:moderator",
],
list(user1.groups.values_list("name", flat=True)),
)
# request users that are moderator
response = self.client.get(
"/api/v1.0/users/?role=moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
# user should be in the list because user is moderator and has the base group
# from this context
self.assertEqual(
content,
[{"id": user1.id, "public_username": "Thomas", "roles": ["moderator"]}],
)
# request all users
response = self.client.get("/api/v1.0/users/", content_type="application/json")
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
# user should be in the list because user is moderator and has the base group
# from this context
self.assertEqual(
content,
[{"id": user1.id, "public_username": "Thomas", "roles": ["moderator"]}],
)
# request all users that are not moderators
response = self.client.get(
"/api/v1.0/users/?role=!moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
# should be empty because user is moderator
self.assertEqual(
content,
[],
)
def test_list_users_are_active_users(self):
"""Controls that list of users and moderators only contains active
users."""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
user1 = UserFactory(
public_username="Thomas", lti_consumer=api_user.lti_consumer
)
user2 = UserFactory(
public_username="Aurélie", lti_consumer=api_user.lti_consumer
)
user4 = UserFactory(is_active=False, lti_consumer=api_user.lti_consumer)
user3 = UserFactory(is_active=False, lti_consumer=api_user.lti_consumer)
user5 = UserFactory(public_username="Théo", lti_consumer=api_user.lti_consumer)
user6 = UserFactory(is_active=False, lti_consumer=api_user.lti_consumer)
lti_context.sync_user_groups(user1, ["student"])
lti_context.sync_user_groups(user2, ["student", "moderator"])
lti_context.sync_user_groups(user3, ["student"])
lti_context.sync_user_groups(user4, ["student", "moderator"])
lti_context.sync_user_groups(user5, ["instructor", "moderator"])
lti_context.sync_user_groups(user6, ["instructor", "moderator"])
# only active student is listed
response = self.client.get(
"/api/v1.0/users/?role=student", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user2.id,
"public_username": "Aurélie",
"roles": ["moderator", "student"],
},
{"id": user1.id, "public_username": "Thomas", "roles": ["student"]},
],
)
# only active moderator is listed
response = self.client.get(
"/api/v1.0/users/?role=moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user2.id,
"public_username": "Aurélie",
"roles": ["moderator", "student"],
}
],
)
# only active instructor is listed
response = self.client.get(
"/api/v1.0/users/?role=instructor", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[
{
"id": user5.id,
"public_username": "Théo",
"roles": ["instructor", "moderator"],
}
],
)
# only active user not moderator is listed
response = self.client.get(
"/api/v1.0/users/?role=!moderator", content_type="application/json"
)
self.assertEqual(response.status_code, 200)
content = json.loads(response.content)
self.assertEqual(
content,
[{"id": user1.id, "public_username": "Thomas", "roles": ["student"]}],
)
def test_api_can_manage_moderators_update_student_public_username_readonly(
self,
):
"""If public_username is present and changed it's not updating the user as its a
read only data"""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
# Creates user to update
update_user = UserFactory(
public_username="Théo", lti_consumer=api_user.lti_consumer
)
lti_context.sync_user_groups(update_user, ["student"])
# Check group moderator is not part of group list of the user
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
],
list(update_user.groups.values_list("name", flat=True)),
)
data = {"roles": ["moderator"], "public_username": "Salomé"}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
# Check public_username has been ignored
self.assertEqual(update_user.public_username, "Théo")
# Check group moderator is now part of user's groups
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
f"{lti_context.base_group_name}:role:moderator",
],
list(update_user.groups.values_list("name", flat=True)),
)
def test_api_can_manage_moderators_update_student_id_param_ignored(
self,
):
"""If id in body of request api is different from the id in the url is ignored.
Only the user targeted in the url is updated."""
api_user, lti_context = self._login_authorized_user_to_manage_moderators()
# Creates user to update
update_user = UserFactory(
public_username="Théo", lti_consumer=api_user.lti_consumer
)
useless_user = UserFactory(lti_consumer=api_user.lti_consumer)
lti_context.sync_user_groups(update_user, ["student"])
lti_context.sync_user_groups(useless_user, ["student"])
# Check group moderator is now part of user's groups
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
],
list(update_user.groups.values_list("name", flat=True)),
)
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
],
list(useless_user.groups.values_list("name", flat=True)),
)
# in the body we target the other user
data = {"id": useless_user.id, "roles": "moderator"}
response = self.client.put(
f"/api/v1.0/users/{update_user.id}/",
json.dumps(data),
content_type="application/json",
)
self.assertEqual(response.status_code, 200)
# Check group moderator is now part of user's groups
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
f"{lti_context.base_group_name}:role:moderator",
],
list(update_user.groups.values_list("name", flat=True)),
)
# useless_user didn't get updated and still has no moderator group
self.assertCountEqual(
[
lti_context.base_group_name,
f"{lti_context.base_group_name}:role:student",
],
list(useless_user.groups.values_list("name", flat=True)),
)
| 39.204689
| 92
| 0.605663
| 4,842
| 43,478
| 5.241636
| 0.047501
| 0.049645
| 0.044681
| 0.027305
| 0.8842
| 0.872813
| 0.856541
| 0.84279
| 0.829196
| 0.825453
| 0
| 0.012032
| 0.288905
| 43,478
| 1,108
| 93
| 39.240072
| 0.808875
| 0.135862
| 0
| 0.718458
| 0
| 0
| 0.163939
| 0.079292
| 0
| 0
| 0
| 0
| 0.142523
| 1
| 0.031542
| false
| 0
| 0.008178
| 0
| 0.042056
| 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
|
8edd354f82429ce3270b7a1eb5910e194544c99f
| 76
|
py
|
Python
|
hello-world/hello_world.py
|
ross-schlie/exercism-Python-track
|
4db690d11377377fc6f5cef6422da497272bbb31
|
[
"MIT"
] | null | null | null |
hello-world/hello_world.py
|
ross-schlie/exercism-Python-track
|
4db690d11377377fc6f5cef6422da497272bbb31
|
[
"MIT"
] | null | null | null |
hello-world/hello_world.py
|
ross-schlie/exercism-Python-track
|
4db690d11377377fc6f5cef6422da497272bbb31
|
[
"MIT"
] | null | null | null |
"""exercism hello world module."""
def hello():
return "Hello, World!"
| 15.2
| 34
| 0.631579
| 9
| 76
| 5.333333
| 0.666667
| 0.416667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.184211
| 76
| 5
| 35
| 15.2
| 0.774194
| 0.368421
| 0
| 0
| 0
| 0
| 0.302326
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 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
| 1
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
d91c9f94c3a2afc60a235549625240dd48d4a852
| 108
|
py
|
Python
|
Codewars/6kyu/rectangle-into-squares/Python/test.py
|
RevansChen/online-judge
|
ad1b07fee7bd3c49418becccda904e17505f3018
|
[
"MIT"
] | 7
|
2017-09-20T16:40:39.000Z
|
2021-08-31T18:15:08.000Z
|
Codewars/6kyu/rectangle-into-squares/Python/test.py
|
RevansChen/online-judge
|
ad1b07fee7bd3c49418becccda904e17505f3018
|
[
"MIT"
] | null | null | null |
Codewars/6kyu/rectangle-into-squares/Python/test.py
|
RevansChen/online-judge
|
ad1b07fee7bd3c49418becccda904e17505f3018
|
[
"MIT"
] | null | null | null |
# Python - 3.6.0
test.assert_equals(sqInRect(5, 5), None)
test.assert_equals(sqInRect(5, 3), [3, 2, 1, 1])
| 21.6
| 48
| 0.657407
| 21
| 108
| 3.285714
| 0.571429
| 0.289855
| 0.463768
| 0.695652
| 0.724638
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117021
| 0.12963
| 108
| 4
| 49
| 27
| 0.617021
| 0.12963
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| true
| 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
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
d96e56bfedf2691d55ac77de46c38f690bd2a2e0
| 300,616
|
py
|
Python
|
osspath-sdk/python/alibabacloud_osspath_sdk/client.py
|
aliyun/aliyun-ccp
|
5d77be2b8e35e127511cf746b7be32adcd02cebd
|
[
"Apache-2.0"
] | 35
|
2019-10-28T09:09:17.000Z
|
2021-01-21T04:50:06.000Z
|
osspath-sdk/python/alibabacloud_osspath_sdk/client.py
|
aliyun/aliyun-ccp
|
5d77be2b8e35e127511cf746b7be32adcd02cebd
|
[
"Apache-2.0"
] | 165
|
2019-11-04T11:18:31.000Z
|
2020-10-13T19:43:29.000Z
|
osspath-sdk/python/alibabacloud_osspath_sdk/client.py
|
aliyun/aliyun-ccp
|
5d77be2b8e35e127511cf746b7be32adcd02cebd
|
[
"Apache-2.0"
] | 70
|
2019-10-29T02:22:02.000Z
|
2020-11-12T06:46:44.000Z
|
# -*- coding: utf-8 -*-
# This file is auto-generated, don't edit it. Thanks.
import time
from alibabacloud_ccp_credentials.client import Client as AccessTokenCredentialClient
from alibabacloud_credentials.client import Client as CredentialClient
from alibabacloud_osspath_sdk import models as osspath_models
from alibabacloud_tea_util.client import Client as UtilClient
from Tea.exceptions import TeaException
from alibabacloud_ccp_credentials import models as access_token_credential_models
from alibabacloud_credentials import models as credential_models
from Tea.request import TeaRequest
from Tea.core import TeaCore
from Tea.response import TeaResponse
from alibabacloud_roa_util.client import Client as ROAUtilClient
from Tea.exceptions import UnretryableException
class Client(object):
"""
*
"""
def __init__(self, config, _domain_id=None, _access_token_credential=None, _endpoint=None, _protocol=None,
_nickname=None, _user_agent=None, _credential=None):
self._domain_id = _domain_id
self._access_token_credential = _access_token_credential
self._endpoint = _endpoint
self._protocol = _protocol
self._nickname = _nickname
self._user_agent = _user_agent
self._credential = _credential
if UtilClient.is_unset(config.to_map()):
raise TeaException({
"name": "ParameterMissing",
"message": "'config' can not be unset"
})
if not UtilClient.empty(config.access_token) or not UtilClient.empty(config.refresh_token):
access_config = access_token_credential_models.Config(
access_token=config.access_token,
endpoint=config.endpoint,
domain_id=config.domain_id,
client_id=config.client_id,
refresh_token=config.refresh_token,
client_secret=config.client_secret,
expire_time=config.expire_time
)
self._access_token_credential = AccessTokenCredentialClient(access_config)
if not UtilClient.empty(config.access_key_id):
if UtilClient.empty(config.type):
config.type = "access_key"
credential_config = credential_models.Config(
access_key_id=config.access_key_id,
type=config.type,
access_key_secret=config.access_key_secret,
security_token=config.security_token
)
self._credential = CredentialClient(credential_config)
self._endpoint = config.endpoint
self._protocol = config.protocol
self._user_agent = config.user_agent
self._nickname = config.nickname
self._domain_id = config.domain_id
def cancel_link(self, request, runtime):
"""
取消绑定关系，生成新用户，返回访问令牌
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/cancel_link")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.CancelLinkModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def confirm_link(self, request, runtime):
"""
确认绑定关系, 成功后返回访问令牌
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/confirm_link")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ConfirmLinkModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def change_password(self, request, runtime):
"""
修改手机登录密码，密码必须包含数字和字母，长度8-20个字符
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/default/change_password")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ChangePasswordModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def set_password(self, request, runtime):
"""
设置手机登录密码，密码必须包含数字和字母，长度8-20个字符
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/default/set_password")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 204):
return osspath_models.SetPasswordModel().from_map({
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def verify_code(self, request, runtime):
"""
校验手机短信验证码，用于重置密码时校验手机，通过校验后返回state，可通过state重新设置密码
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/default/verify_code")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.VerifyCodeModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_access_token_by_link_info(self, request, runtime):
"""
管理员通过账号信息直接获取用户的访问令牌
@tags account
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/get_access_token_by_link_info")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetAccessTokenByLinkInfoModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_captcha(self, request, runtime):
"""
获取图片验证码，用于人机校验，默认不需要
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/get_captcha")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetCaptchaModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_link_info(self, request, runtime):
"""
获取用户认证方式详情
@tags account
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/get_link_info")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetLinkInfoModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_link_info_by_user_id(self, request, runtime):
"""
获取用户的所有绑定信息
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/get_link_info_by_user_id")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetLinkInfoByUserIdModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_public_key(self, request, runtime):
"""
获取公钥，用于加密对称密钥
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/get_public_key")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetPublicKeyModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def link(self, request, runtime):
"""
绑定用户认证方式
@tags account
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error AlreadyExist {resource} has already exists. {extra_msg}
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/link")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.LinkModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def check_exist(self, request, runtime):
"""
查询手机号是否已被注册
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/mobile/check_exist")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.CheckExistModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def login(self, request, runtime):
"""
通过手机号+短信或密码登录，返回刷新令牌和访问令牌
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/mobile/login")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.LoginModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def register(self, request, runtime):
"""
通过手机号+短信验证码注册账号
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error AlreadyExist {resource} has already exists. {extra_msg}
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/mobile/register")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.RegisterModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def mobile_send_sms_code(self, request, runtime):
"""
发送短信验证码，用于登录、注册、修改密码、绑定等
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/mobile/send_sms_code")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.MobileSendSmsCodeModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def account_revoke(self, request, runtime):
"""
用户退出登录
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/revoke")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 204):
return osspath_models.AccountRevokeModel().from_map({
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def account_token(self, request, runtime):
"""
用户通过刷新令牌（refresh_token）获取访问令牌（access_token）
@tags account
@error InvalidParameterMissing The input parameter {parameter_name} is missing.
@error Forbidden User not authorized to operate on the specified APIs.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/account/token")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".auth.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.AccountTokenModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def admin_list_stores(self, request, runtime):
"""
列举Store列表
@tags admin
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error Forbidden User not authorized to operate on the specified APIs.
@error InternalError The request has been failed due to some unknown error.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/domain/list_stores")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.AdminListStoresModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_user_access_token(self, request, runtime):
"""
获取用户的accessToken
@tags admin
@error undefined undefined
@error undefined undefined
@error undefined undefined
@error undefined undefined
@error undefined undefined
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/user/get_access_token")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetUserAccessTokenModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def create_drive(self, request, runtime):
"""
支持normal和large两种drive，
large类型的drive用于文件数多的场景，不支持list操作，
当drive的文件数量大于1亿时，建议使用large类型。
@tags drive
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/drive/create")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 201):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.CreateDriveModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def delete_drive(self, request, runtime):
"""
删除指定drive_id对应的Drive
@tags drive
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/drive/delete")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 204):
return osspath_models.DeleteDriveModel().from_map({
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_drive(self, request, runtime):
"""
获取指定drive_id对应的Drive详细信息。
@tags drive
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/drive/get")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetDriveModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_default_drive(self, request, runtime):
"""
一个用户可拥有多个drive，在创建drive时通过参数指定是否为这个用户的默认drive，
每个用户只能设置一个默认drive。
@tags drive
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/drive/get_default_drive")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetDefaultDriveModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def list_drives(self, request, runtime):
"""
管理员列举指定用户的Drive
@tags drive
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/drive/list")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ListDrivesModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def list_my_drives(self, request, runtime):
"""
列举当前用户（访问令牌）的Drive
@tags drive
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/drive/list_my_drives")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ListMyDrivesModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def update_drive(self, request, runtime):
"""
更新指定drive_id的Drive信息
@tags drive
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/drive/update")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.UpdateDriveModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def complete_file(self, request, runtime):
"""
完成文件上传
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/complete")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.CompleteFileModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def copy_file(self, request, runtime):
"""
指定源文件或文件夹路径，拷贝到指定的文件夹。
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/copy")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 201):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.CopyFileModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def create_file(self, request, runtime):
"""
创建文件或者文件夹。
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error AlreadyExist {resource} has already exists. {extra_msg}
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/create")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 201):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.CreateFileModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def delete_file(self, request, runtime):
"""
指定文件或文件夹路径，删除文件或文件夹
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/delete")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 204):
return osspath_models.DeleteFileModel().from_map({
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_file(self, request, runtime):
"""
获取指定文件或文件夹路径，获取文件或文件夹信息。
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/get")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetFileModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_download_url(self, request, runtime):
"""
指定文件路径，获取文件下载地址
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/get_download_url")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetDownloadUrlModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_secure_url(self, request, runtime):
"""
指定文件路径，获取文件安全地址
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/get_secure_url")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetSecureUrlModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_upload_url(self, request, runtime):
"""
可指定分片信息，一次获取多个分片的上传地址。
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/get_upload_url")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetUploadUrlModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def list_file(self, request, runtime):
"""
指定父文件夹路径，列举文件夹下的文件或者文件夹
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/list")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ListFileModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def list_uploaded_parts(self, request, runtime):
"""
列举UploadID对应的已上传分片。
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/list_uploaded_parts")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ListUploadedPartsModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def move_file(self, request, runtime):
"""
指定源文件或文件夹路径，移动到指定的文件夹。
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/move")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.MoveFileModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def video_definition(self, request, runtime):
"""
获取视频支持的分辨率
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/video_definition")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.VideoDefinitionModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def video_license(self, request, runtime):
"""
获取视频的DRM License
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/video_license")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.VideoLicenseModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def video_m3u_8(self, request, runtime):
"""
获取视频转码后的m3u8文件
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/video_m3u8")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
byt = UtilClient.read_as_bytes(_response.body)
return osspath_models.VideoM3u8Model().from_map({
"body": byt,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def video_transcode(self, request, runtime):
"""
将mp4格式的视频文件，转为m3u8
@tags file
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/file/video_transcode")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.VideoTranscodeModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if UtilClient.equal_number(_response.status_code, 204):
return osspath_models.VideoTranscodeModel().from_map({
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def create_share(self, request, runtime):
"""
创建共享。
@tags share
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/share/create")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 201):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.CreateShareModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def delete_share(self, request, runtime):
"""
删除指定共享
@tags share
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/share/delete")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 204):
return osspath_models.DeleteShareModel().from_map({
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_share(self, request, runtime):
"""
获取共享信息。
@tags share
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/share/get")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetShareModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def list_share(self, request, runtime):
"""
列举指定用户的共享
@tags share
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/share/list")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ListShareModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def update_share(self, request, runtime):
"""
修改指定共享
@tags share
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/share/update")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.UpdateShareModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def list_storefile(self, request, runtime):
"""
列举指定store下的所有文件。
@tags store
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/osspath/store_file/list")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ListStorefileModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def create_user(self, request, runtime):
"""
创建用户，只有管理员可以调用
@tags user
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/user/create")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 201):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.CreateUserModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def delete_user(self, request, runtime):
"""
只有管理员可以调用
@tags user
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/user/delete")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 204):
return osspath_models.DeleteUserModel().from_map({
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_user(self, request, runtime):
"""
获取用户详细信息，普通用户只能获取自己的信息，管理员可以获取任意用户的信息。
@tags user
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/user/get")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.GetUserModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def list_users(self, request, runtime):
"""
只有管理员可以调用
@tags user
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/user/list")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.ListUsersModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def search_user(self, request, runtime):
"""
该接口将会根据条件查询用户，只有管理员可以调用
@tags user
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/user/search")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.SearchUserModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def update_user(self, request, runtime):
"""
用户可以修改自己的description，nick_name，avatar；
管理员在用户基础上还可修改status（可以修改任意用户）；
超级管理员在管理员基础上还可修改role（可以修改任意用户）。
@tags user
@error InvalidParameter The input parameter {parameter_name} is not valid.
@error AccessTokenInvalid AccessToken is invalid. {message}
@error ForbiddenNoPermission No Permission to access resource {resource_name}.
@error NotFound The resource {resource_name} cannot be found. Please check.
@error InternalError The request has been failed due to some unknown error.
@error ServiceUnavailable The request has failed due to a temporary failure of the server.
"""
request.validate()
runtime.validate()
_runtime = {
"timeouted": "retry",
"readTimeout": runtime.read_timeout,
"connectTimeout": runtime.connect_timeout,
"localAddr": runtime.local_addr,
"httpProxy": runtime.http_proxy,
"httpsProxy": runtime.https_proxy,
"noProxy": runtime.no_proxy,
"maxIdleConns": runtime.max_idle_conns,
"socks5Proxy": runtime.socks_5proxy,
"socks5NetWork": runtime.socks_5net_work,
"retry": {
"retryable": runtime.autoretry,
"maxAttempts": UtilClient.default_number(runtime.max_attempts, 3)
},
"backoff": {
"policy": UtilClient.default_string(runtime.backoff_policy, "no"),
"period": UtilClient.default_number(runtime.backoff_period, 1)
},
"ignoreSSL": runtime.ignore_ssl
}
_last_request = None
_last_exception = None
_now = time.time()
_retry_times = 0
while TeaCore.allow_retry(_runtime.get('retry'), _retry_times, _now):
if _retry_times > 0:
_backoff_time = TeaCore.get_backoff_time(_runtime.get('backoff'), _retry_times)
if _backoff_time > 0:
TeaCore.sleep(_backoff_time)
_retry_times = _retry_times + 1
try:
_request = TeaRequest()
accesskey_id = self.get_access_key_id()
access_key_secret = self.get_access_key_secret()
security_token = self.get_security_token()
access_token = self.get_access_token()
_request.protocol = UtilClient.default_string(self._protocol, "https")
_request.method = "POST"
_request.pathname = self.get_pathname(self._nickname, "/v2/user/update")
_request.headers = TeaCore.merge({
"user-agent": self.get_user_agent(),
"host": UtilClient.default_string(self._endpoint, "" + str(self._domain_id) + ".api.alicloudccp.com"),
"content-type": "application/json; charset=utf-8"
}, request.headers)
if not UtilClient.empty(access_token):
_request.headers["authorization"] = "Bearer " + str(access_token) + ""
elif not UtilClient.empty(accesskey_id) and not UtilClient.empty(access_key_secret):
if not UtilClient.empty(security_token):
_request.headers["x-acs-security-token"] = security_token
_request.headers["date"] = UtilClient.get_date_utcstring()
_request.headers["accept"] = "application/json"
_request.headers["x-acs-signature-method"] = "HMAC-SHA1"
_request.headers["x-acs-signature-version"] = "1.0"
string_to_sign = ROAUtilClient.get_string_to_sign(_request)
_request.headers["authorization"] = "acs " + str(accesskey_id) + ":" + str(ROAUtilClient.get_signature(string_to_sign, access_key_secret)) + ""
_request.body = UtilClient.to_jsonstring(request.body.to_map())
_last_request = _request
_response = TeaCore.do_action(_request, _runtime)
resp_map = None
obj = None
if UtilClient.equal_number(_response.status_code, 200):
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
return osspath_models.UpdateUserModel().from_map({
"body": resp_map,
"headers": _response.headers
})
if not UtilClient.empty(_response.headers.get('x-ca-error-message')):
raise TeaException({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
},
"message": _response.headers.get('x-ca-error-message')
})
obj = UtilClient.read_as_json(_response.body)
resp_map = UtilClient.assert_as_map(obj)
raise TeaException(TeaCore.merge({
"data": {
"requestId": _response.headers.get('x-ca-request-id'),
"statusCode": _response.status_code,
"statusMessage": _response.status_message
}
}, resp_map))
except Exception as e:
if TeaCore.is_retryable(e):
_last_exception = e
continue
raise e
raise UnretryableException(_last_request, _last_exception)
def get_pathname(self, nickname, path):
if UtilClient.empty(nickname):
return path
return "/" + str(nickname) + "" + str(path) + ""
def set_expire_time(self, expire_time):
if UtilClient.is_unset(self._access_token_credential):
return
self._access_token_credential.set_expire_time(expire_time)
def get_expire_time(self):
if UtilClient.is_unset(self._access_token_credential):
return ''
expire_time = self._access_token_credential.get_expire_time()
return expire_time
def set_refresh_token(self, token):
if UtilClient.is_unset(self._access_token_credential):
return
self._access_token_credential.set_refresh_token(token)
def get_refresh_token(self):
if UtilClient.is_unset(self._access_token_credential):
return ''
token = self._access_token_credential.get_refresh_token()
return token
def set_access_token(self, token):
if UtilClient.is_unset(self._access_token_credential):
return
self._access_token_credential.set_access_token(token)
def get_access_token(self):
if UtilClient.is_unset(self._access_token_credential):
return ''
token = self._access_token_credential.get_access_token()
return token
def set_user_agent(self, user_agent):
self._user_agent = user_agent
def append_user_agent(self, user_agent):
self._user_agent = "" + str(self._user_agent) + " " + str(user_agent) + ""
def get_user_agent(self):
user_agent = UtilClient.get_user_agent(self._user_agent)
return user_agent
def get_access_key_id(self):
if UtilClient.is_unset(self._credential):
return ''
access_key_id = self._credential.get_access_key_id()
return access_key_id
def get_access_key_secret(self):
if UtilClient.is_unset(self._credential):
return ''
secret = self._credential.get_access_key_secret()
return secret
def get_security_token(self):
if UtilClient.is_unset(self._credential):
return ''
token = self._credential.get_security_token()
return token
| 52.335655
| 163
| 0.559667
| 28,166
| 300,616
| 5.664347
| 0.015231
| 0.041857
| 0.030237
| 0.025247
| 0.967288
| 0.964066
| 0.962361
| 0.96233
| 0.961082
| 0.960832
| 0
| 0.004956
| 0.344849
| 300,616
| 5,743
| 164
| 52.344768
| 0.805112
| 0.073852
| 0
| 0.900722
| 1
| 0
| 0.112953
| 0.013761
| 0
| 0
| 0
| 0
| 0.01931
| 1
| 0.013068
| false
| 0.00117
| 0.002536
| 0
| 0.029842
| 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
|
d9911d0cfa7047e818c5e02dd75bb93890226e16
| 2,333
|
py
|
Python
|
Pattern Programs (1).py
|
yokesh-git/Pattern-Programs
|
82affe65cafaaeda7ad26fb06667b77b41ef9f68
|
[
"MIT"
] | null | null | null |
Pattern Programs (1).py
|
yokesh-git/Pattern-Programs
|
82affe65cafaaeda7ad26fb06667b77b41ef9f68
|
[
"MIT"
] | null | null | null |
Pattern Programs (1).py
|
yokesh-git/Pattern-Programs
|
82affe65cafaaeda7ad26fb06667b77b41ef9f68
|
[
"MIT"
] | 1
|
2020-12-24T05:06:14.000Z
|
2020-12-24T05:06:14.000Z
|
#Pyramid
'''
N = int(input())
for i in range(N):
print(' ' *(N-i-1) + (i+1)*'* ')
'''
#Inverted Pyramid
'''
N = int(input())
for i in range(N):
print(' '*i + (N-i)*'* ')
'''
#Right Angle Triangle
'''
N = int(input())
for i in range(N):
print((i+1)* '* ')
'''
#Inverted Right Angle Triangle-1
'''
N = int(input())
for i in range(N):
print(' ' * (N-i-1) + (i+1)*'*')
'''
#Inverted Right Angle Triangle-2
'''
N = int(input())
for i in range(N):
print('* '*(N-i))
'''
#Inverted Right Angle Triangle-3
'''
N = int(input())
for i in range(N):
print(i * ' ' + (N-i)*'*')
'''
#Hallow Pyramid
'''
N = int(input())
for i in range(N):
if i==0:
print(' ' * (N-i-1) + '*')
elif (i>=1) and (i<N-1):
print(' ' * (N-i-1) + '*' + i * ' ' + (i-1) * ' ' + '*')
else:
print(' ' * (N-i-1) + ((2*N)-1)*'*')
'''
#Inverted Hallow Pyramid
'''
N = int(input())
for i in range(N-1,-1,-1):
if i==0:
print(' ' * (N-i-1) + '*')
elif (i>=1) and (i<N-1):
print(' ' * (N-i-1) + '*' + i * ' ' + (i-1) * ' ' + '*')
else:
print(' ' * (N-i-1) + ((2*N)-1)*'*')
'''
#Diamond
'''
N = int(input())
for i in range(N):
print(' ' *(N-i-1) + (i+1)*'* ')
N = N-1
for i in range(N):
print(' '*i + (N-i)*' *')
'''
#Hallow Diamond
'''
N = int(input())
for i in range(N):
if i==0:
print(' ' * (N-i-1) + '*')
elif (i>=1) and (i<N-1):
print(' ' * (N-i-1) + '*' + i * ' ' + (i-1) * ' ' + '*')
N = N-1
for i in range(N-1,-1,-1):
if i==0:
print(' ' * (N-i-1) + ' *')
elif (i>=1) and (i<N-1):
print(' ' * (N-i-1) + ' *' + i * ' ' + (i-1) * ' ' + '*')
'''
#Half Hallow Diamond
'''
N = int(input())
for i in range(N):
if i==0:
print(' ' * (N-i-1) + '*')
elif (i>=1) and (i<N-1):
print(' ' * (N-i-1) + '*' + i * ' ' + (i-1) * ' ' + '*')
'''
#Half Diamond - Left
'''
N = int(input())
for i in range(N):
print((i+1)* '* ')
N = N-1
for i in range(N):
print('* '*(N-i))
'''
#Half Diamond - Right
'''
N = int(input())
for i in range(N):
print(' ' * (N-i-1) + (i+1)*'*')
N = N-1
for i in range(N):
print((i+1) * ' ' + (N-i)*'*')
'''
| 16.905797
| 66
| 0.372053
| 354
| 2,333
| 2.451977
| 0.070621
| 0.076037
| 0.145161
| 0.215438
| 0.904378
| 0.904378
| 0.853687
| 0.853687
| 0.851382
| 0.841014
| 0
| 0.038363
| 0.329619
| 2,333
| 137
| 67
| 17.029197
| 0.516624
| 0.139734
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
7966929a07fa31bbd5478a4397447f7667be4f4f
| 172
|
py
|
Python
|
backend/api/periodic_tasks.py
|
MimbleWimble-Grin/grin-testnet-deposit-withdraw
|
7943f654b0a6d79d9a31c9719366e9df55d6816c
|
[
"MIT"
] | 6
|
2021-03-11T21:02:21.000Z
|
2022-02-06T20:53:20.000Z
|
backend/api/periodic_tasks.py
|
pkariz/grin-testnet-exchange
|
b5c7a5b6322f60348e3b3db563183e2d6d2da234
|
[
"MIT"
] | 1
|
2021-03-12T12:10:19.000Z
|
2021-03-12T12:20:32.000Z
|
backend/api/periodic_tasks.py
|
MimbleWimble-Grin/grin-testnet-deposit-withdraw
|
7943f654b0a6d79d9a31c9719366e9df55d6816c
|
[
"MIT"
] | 3
|
2021-03-12T16:42:03.000Z
|
2021-04-19T07:11:33.000Z
|
from .tasks import update_deposits_and_withdrawals
def periodically_run_job():
"""This task will be run by APScheduler."""
update_deposits_and_withdrawals.send()
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0
| 8
|
798fa6fa3fb722b63d45baf40f0ad048861e1e0c
| 7,918
|
py
|
Python
|
machines/migrations/0001_initial.py
|
mkschu/greensManagerDjango
|
842f6cc0e5bc9fa5f36e5d996960900886d3370a
|
[
"Apache-2.0"
] | null | null | null |
machines/migrations/0001_initial.py
|
mkschu/greensManagerDjango
|
842f6cc0e5bc9fa5f36e5d996960900886d3370a
|
[
"Apache-2.0"
] | null | null | null |
machines/migrations/0001_initial.py
|
mkschu/greensManagerDjango
|
842f6cc0e5bc9fa5f36e5d996960900886d3370a
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.12 on 2018-04-23 21:37
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
('parts', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='FertSpreader',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('make', models.CharField(max_length=128)),
('model', models.CharField(blank=True, max_length=256, null=True)),
('ident_number', models.CharField(blank=True, max_length=16, null=True)),
('date_purchased', models.DateField()),
('in_commission', models.BooleanField(default=True)),
('capacity', models.FloatField()),
('notes', models.TextField(blank=True, null=True)),
('created_at', models.DateTimeField(auto_now_add=True)),
('updated_at', models.DateTimeField(auto_now=True)),
],
),
migrations.CreateModel(
name='Machine',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('make', models.CharField(max_length=128)),
('model', models.TextField(max_length=256)),
('year', models.IntegerField()),
('ident_number', models.CharField(blank=True, max_length=16, null=True)),
('date_purchased', models.DateField()),
('hours', models.FloatField()),
('in_commission', models.BooleanField(default=True)),
('oil_capacity', models.FloatField(blank=True, null=True)),
('hyd_oil_capacity', models.FloatField(blank=True, null=True)),
('created_at', models.DateTimeField(auto_now_add=True)),
('updated_at', models.DateTimeField(auto_now=True)),
],
),
migrations.CreateModel(
name='Aerator',
fields=[
('machine_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Machine')),
],
bases=('machines.machine',),
),
migrations.CreateModel(
name='Cart',
fields=[
('machine_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Machine')),
],
bases=('machines.machine',),
),
migrations.CreateModel(
name='Mower',
fields=[
('machine_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Machine')),
('cut_height', models.FloatField()),
],
bases=('machines.machine',),
),
migrations.CreateModel(
name='Roller',
fields=[
('machine_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Machine')),
('roll_width', models.FloatField(blank=True, null=True)),
],
bases=('machines.machine',),
),
migrations.CreateModel(
name='Sprayer',
fields=[
('machine_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Machine')),
('tank_capacity', models.IntegerField()),
],
bases=('machines.machine',),
),
migrations.CreateModel(
name='Tractor',
fields=[
('machine_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Machine')),
],
bases=('machines.machine',),
),
migrations.CreateModel(
name='TrapRake',
fields=[
('machine_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Machine')),
('plow', models.BooleanField()),
('plow_attached', models.BooleanField(default=False)),
],
bases=('machines.machine',),
),
migrations.CreateModel(
name='UtilVehicle',
fields=[
('machine_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Machine')),
('bed_size', models.FloatField(blank=True, null=True)),
],
bases=('machines.machine',),
),
migrations.AddField(
model_name='machine',
name='fuel_filter',
field=models.ManyToManyField(blank=True, related_name='_machine_fuel_filter_+', to='parts.Filter'),
),
migrations.AddField(
model_name='machine',
name='fuel_type',
field=models.ManyToManyField(blank=True, related_name='_machine_fuel_type_+', to='parts.Fuel'),
),
migrations.AddField(
model_name='machine',
name='hyd_oil_filter',
field=models.ManyToManyField(blank=True, related_name='_machine_hyd_oil_filter_+', to='parts.Filter'),
),
migrations.AddField(
model_name='machine',
name='hyd_oil_type',
field=models.ManyToManyField(blank=True, related_name='_machine_hyd_oil_type_+', to='parts.Oil'),
),
migrations.AddField(
model_name='machine',
name='oil_filter',
field=models.ManyToManyField(blank=True, related_name='_machine_oil_filter_+', to='parts.Filter'),
),
migrations.AddField(
model_name='machine',
name='oil_type',
field=models.ManyToManyField(blank=True, related_name='_machine_oil_type_+', to='parts.Oil'),
),
migrations.CreateModel(
name='FairwayMower',
fields=[
('mower_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Mower')),
],
bases=('machines.mower',),
),
migrations.CreateModel(
name='GreensMower',
fields=[
('mower_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Mower')),
],
bases=('machines.mower',),
),
migrations.CreateModel(
name='RoughMower',
fields=[
('mower_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Mower')),
],
bases=('machines.mower',),
),
migrations.CreateModel(
name='TeeMower',
fields=[
('mower_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='machines.Mower')),
],
bases=('machines.mower',),
),
]
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| 194
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0
| 7
|
79b09771841e5e4bc96cfab9c267d9f6e388f5f4
| 25,155
|
py
|
Python
|
ub/modules/diwali.py
|
parv779/javes-3.0
|
d510717b2756a65b39ff18d9f53d4adc46d8e23f
|
[
"MIT"
] | 15
|
2020-12-13T17:37:05.000Z
|
2021-06-23T00:00:49.000Z
|
ub/modules/diwali.py
|
parv779/javes-3.0
|
d510717b2756a65b39ff18d9f53d4adc46d8e23f
|
[
"MIT"
] | 2
|
2021-01-11T16:39:31.000Z
|
2021-01-25T22:35:28.000Z
|
ub/modules/diwali.py
|
parv779/javes-3.0
|
d510717b2756a65b39ff18d9f53d4adc46d8e23f
|
[
"MIT"
] | 78
|
2020-12-13T17:52:51.000Z
|
2022-03-24T03:43:09.000Z
|
#made by shivam patel
from telethon import events
import asyncio
from ub.utils import admin_cmd
from ub import bot as javes
@javes.on(admin_cmd("hdd"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0,20)
await event.edit("Happy Diwali Dosto🤗")
animation_chars = [
"""-----💜happy💜diwali💜
----💜happy💜diwali💜
---💜happy💜diwali💜
--💜happy💜diwali💜
-💜happy💜diwali💜
💜happy💜diwali💜
💜happy💜diwali💜
💜happy💜diwali💜
💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
-💖happy💖diwali💖
--💖happy💖diwali💖
---💖happy💖diwali💖
----💖happy💖diwali💖
-----💖happy💖diwali💖
-----💖happy💖diwali💖
-----💖happy💖diwali💖
----💖happy💖diwali💖
---💖happy💖diwali💖
--💖happy💖diwali💖
-💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
-💙happy💙diwali💙
--💙happy💙diwali💙
---💙happy💙diwali💙
----💙happy💙diwali💙
-----💙happy💙diwali💙
-----💙happy💙diwali💙
-----💙happy💙diwali💙
----💙happy💙diwali💙
---💙happy💙diwali💙
--💙happy💙diwali💙
-💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
❤️happy♥️diwali❤️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
-❤️happy♥️diwali♥️
--♥️happy❤️diwali♥️
---❤️happy♥️diwali❤️
----♥️happy❤️diwali♥️
-----❤️happy♥️diwali❤️
-----♥️happy❤️diwali♥️
-----❤️happy♥️diwali❤️
----♥️happy❤️diwali♥️
---♥️happy❤️diwali❤️
--♥️happy❤️diwali♥️
-♥️happy♥️diwali♥️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
-💚happy💚diwali💚
--💚happy💚diwali💚
---💚happy💚diwali💚
----💚happy💚diwali💚
-----💚happy💚diwali💚
-----💚happy💚diwali💚
-----💚happy💚diwali💚
----💚happy💚diwali💚
---💚happy💚diwali💚
--💚happy💚diwali💚
-💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
💜happy💜diwali💜
💜happy💜diwali💜
💜happy💜diwali💜
-💜happy💜diwali💜
--💜happy💜diwali💜
---💜happy💜diwali💜
----💜happy💜diwali💜
-----💜happy💜diwali💜
-----💜happy💜diwali💜
-----💜happy💜diwali💜
----💜happy💜diwali💜
---💜happy💜diwali💜
--💜happy💜diwali💜
-💜happy💜diwali💜
💜happy💜diwali💜
💜happy💜diwali💜
💜happy💜diwali💜
💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
-💖happy💖diwali💖
--💖happy💖diwali💖
---💖happy💖diwali💖
----💖happy💖diwali💖
-----💖happy💖diwali💖
-----💖happy💖diwali💖
-----💖happy💖diwali💖
----💖happy💖diwali💖
---💖happy💖diwali💖
--💖happy💖diwali💖
-💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
-💙happy💙diwali💙
--💙happy💙diwali💙
---💙happy💙diwali💙
----💙happy💙diwali💙
-----💙happy💙diwali💙
-----💙happy💙diwali💙
-----💙happy💙diwali💙
----💙happy💙diwali💙
---💙happy💙diwali💙
--💙happy💙diwali💙
-💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
❤️happy♥️diwali❤️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
-❤️happy♥️diwali♥️
--♥️happy❤️diwali♥️
---❤️happy♥️diwali❤️
----♥️happy❤️diwali♥️
-----❤️happy♥️diwali❤️
-----♥️happy❤️diwali♥️
-----❤️happy♥️diwali❤️
----♥️happy❤️diwali♥️
---♥️happy❤️diwali❤️
--♥️happy❤️diwali♥️
-♥️happy♥️diwali♥️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
-💚happy💚diwali💚
--💚happy💚diwali💚
---💚happy💚diwali💚
----💚happy💚diwali💚
-----💚happy💚diwali💚
-----💚happy💚diwali💚
-----💚happy💚diwali💚
----💚happy💚diwali💚
---💚happy💚diwali💚
--💚happy💚diwali💚
-💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
💜happy💜diwali💜
💜happy💜diwali💜
💜happy💜diwali💜
-💜happy💜diwali💜
--💜happy💜diwali💜
---💜happy💜diwali💜
----💜happy💜diwali💜
-----💜happy💜diwali💜
-----💜happy💜diwali💜
-----💜happy💜diwali💜
----💜happy💜diwali💜
---💜happy💜diwali💜
--💜happy💜diwali💜
-💜happy💜diwali💜
💜happy💜diwali💜
💜happy💜diwali💜
💜happy💜diwali💜
💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
-💖happy💖diwali💖
--💖happy💖diwali💖
---💖happy💖diwali💖
----💖happy💖diwali💖
-----💖happy💖diwali💖
-----💖happy💖diwali💖
-----💖happy💖diwali💖
----💖happy💖diwali💖
---💖happy💖diwali💖
--💖happy💖diwali💖
-💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
-💙happy💙diwali💙
--💙happy💙diwali💙
---💙happy💙diwali💙
----💙happy💙diwali💙
-----💙happy💙diwali💙
-----💙happy💙diwali💙
-----💙happy💙diwali💙
----💙happy💙diwali💙
---💙happy💙diwali💙
--💙happy💙diwali💙
-💙happy💙diwali💙
💙happy💙diwali💙""",
"""💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
-💖happy💖diwali💖
--💖happy💖diwali💖
---💖happy💖diwali💖
----💖happy💖diwali💖
-----💖happy💖diwali💖
-----💖happy💖diwali💖
-----💖happy💖diwali💖
----💖happy💖diwali💖
---💖happy💖diwali💖
--💖happy💖diwali💖
-💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
💖happy💖diwali💖
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""""💙happy💙diwali💙
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---💙happy💙diwali💙
----💙happy💙diwali💙
-----💙happy💙diwali💙
-----💙happy💙diwali💙
-----💙happy💙diwali💙
----💙happy💙diwali💙
---💙happy💙diwali💙
--💙happy💙diwali💙
-💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
💙happy💙diwali💙
-💙happy💙diwali💙
--💙happy💙diwali💙
--♥️happy❤️diwali♥️
---❤️happy♥️diwali❤️
----♥️happy❤️diwali♥️
-----❤️happy♥️diwali❤️
-----♥️happy❤️diwali♥️
-----❤️happy♥️diwali❤️
----♥️happy❤️diwali♥️
---♥️happy❤️diwali❤️
--♥️happy❤️diwali♥️
-♥️happy♥️diwali♥️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
❤️happy♥️diwali❤️
❤️happy♥️diwali♥️
❤️happy♥️diwali♥️
-❤️happy♥️diwali♥️
-💚happy💚diwali💚
--💚happy💚diwali💚
---💚happy💚diwali💚
----💚happy💚diwali💚
-----💚happy💚diwali💚
-----💚happy💚diwali💚
-----💚happy💚diwali💚
----💚happy💚diwali💚
---💚happy💚diwali💚
--💚happy💚diwali💚
-💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚
💚happy💚diwali💚""" ]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@javes.on(admin_cmd("diwali"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0,80)
await event.edit("❤Happy Diwali Dosto❤")
animation_chars = ["💖happy💖diwali💖","💙happy💙diwali💙","❤️happy♥️diwali❤️","💚happy💚diwali💚","💜happy💜diwali💜",]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 5])
@javes.on(admin_cmd("dosto"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0,22)
await event.edit("❤Dosto❤")
animation_chars = ["""💜💜 💜💜
💜💜 💜💜
💜💜 💜💜
💜💜 💜💜
💜💜💜💜💜💜💜💜💜
💜💜💜💜💜💜💜💜💜
💜💜 💜💜
💜💜 💜💜
💜💜 💜💜
💜💜 💜💜""","""ㅤㅤㅤㅤㅤ ㅤㅤㅤㅤㅤㅤㅤㅤㅤㅤㅤㅤㅤ
💙💙
💙💙💙
💙💙💙💙
💙💙 💙💙
💙💙 💙💙
💙💙 💙💙
💙💙💙💙💙💙
💙💙💙💙💙💙
💙💙 💙💙
💙💙 💙💙
💙💙 💙💙""","""💚💚💚💚💚💚💚
💚💚💚💚💚💚💚💚
💚💚 💚💚
💚💚 💚💚
💚💚💚💚💚💚💚💚
💚💚💚💚💚💚💚
💚💚
💚💚
💚💚
💚💚""","""💛💛💛💛💛💛
💛💛💛💛💛💛💛
💛💛 💛💛
💛💛 💛💛
💛💛💛💛💛💛💛
💛💛💛💛💛💛
💛💛
💛💛
💛💛
💛💛""","""💜💜 💜💜
💜💜 💜💜
💜💜 💜💜
💜💜 💜💜
💜💜💜
💜💜
💜💜
💜💜
💜💜
💜💜""","""💖💖💖💖💖💖💖
💖💖💖💖💖💖💖💖
💖💖 💖💖
💖💖 💖💖
💖💖 💖💖
💖💖 💖💖
💖💖 💖💖
💖💖 💖💖
💖💖💖💖💖💖💖💖
💖💖💖💖💖💖💖""","""💝💝💝💝💝💝
💝💝💝💝💝💝
💝💝
💝💝
💝💝
💝💝
💝💝
💝💝
💝💝💝💝💝💝
💝💝💝💝💝💝""","""💖💖 💖💖
💖💖 💖💖
💖💖 💖💖
💖💖 💖💖
💖💖 💖 💖💖
💖💖 💖💖 💖💖
💖💖 💖💖💖 💖💖
💖💖 💖💖 💖💖 💖💖
💖💖💖💖 💖💖💖💖
💖💖💖 💖💖💖""","""ㅤㅤㅤㅤㅤ ㅤㅤㅤㅤㅤㅤㅤㅤㅤㅤㅤㅤㅤ
💙💙
💙💙💙
💙💙💙💙
💙💙 💙💙
💙💙 💙💙
💙💙 💙💙
💙💙💙💙💙💙
💙💙💙💙💙💙
💙💙 💙💙
💙💙 💙💙
💙💙 💙💙""","""💘💘
💘💘
💘💘
💘💘
💘💘
💘💘
💘💘
💘💘
💘💘💘💘💘💘💘💘
💘💘💘💘💘💘💘💘""","""💝💝💝💝💝💝
💝💝💝💝💝💝
💝💝
💝💝
💝💝
💝💝
💝💝
💝💝
💝💝💝💝💝💝
💝💝💝💝💝💝""",]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
| 18.058148
| 112
| 0.577738
| 6,568
| 25,155
| 2.94458
| 0.011876
| 0.095243
| 0.111117
| 0.20636
| 0.97575
| 0.974199
| 0.974199
| 0.973371
| 0.970889
| 0.969959
| 0
| 0.00072
| 0.117193
| 25,155
| 1,392
| 113
| 18.071121
| 0.652452
| 0.000795
| 0
| 0.705479
| 0
| 0
| 0.610049
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.027397
| 0
| 0.047945
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
8dad072c88a539591cd997e5c02f572299876094
| 292,302
|
py
|
Python
|
results/n12_n25_boxplot_componentN.py
|
FreeDisciplina/FunctionalGraphStatistics
|
47a5539ceeb1d26482895157c1f0a0402fda8303
|
[
"MIT"
] | null | null | null |
results/n12_n25_boxplot_componentN.py
|
FreeDisciplina/FunctionalGraphStatistics
|
47a5539ceeb1d26482895157c1f0a0402fda8303
|
[
"MIT"
] | null | null | null |
results/n12_n25_boxplot_componentN.py
|
FreeDisciplina/FunctionalGraphStatistics
|
47a5539ceeb1d26482895157c1f0a0402fda8303
|
[
"MIT"
] | null | null | null |
import matplotlib.pyplot as plt
import numpy as np
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
n12 = [ 2.00000000000000000000, 2.00000000000000000000, 2.80735492205760410749, 2.80735492205760410749, 2.00000000000000000000, 1.00000000000000000000, 3.16992500144231236295, 1.00000000000000000000, 2.58496250072115618147, 2.32192809488736234781, 2.80735492205760410749, 2.32192809488736234781, 3.16992500144231236295, 2.58496250072115618147, 2.00000000000000000000, 2.58496250072115618147, 1.58496250072115618147, 2.58496250072115618147, 2.58496250072115618147, 2.58496250072115618147, 1.58496250072115618147, 1.58496250072115618147, 1.58496250072115618147, 2.32192809488736234781, 2.00000000000000000000, 2.32192809488736234781, 1.58496250072115618147, 3.16992500144231236295, 1.00000000000000000000, 0.00000000000000000000, 3.00000000000000000000, 1.58496250072115618147, 2.80735492205760410749, 3.00000000000000000000, 2.58496250072115618147, 1.58496250072115618147, 1.58496250072115618147, 2.32192809488736234781, 2.32192809488736234781, 1.00000000000000000000, 1.58496250072115618147, 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3.16992500144231236295, 3.45943161863729725615, 2.32192809488736234781, 3.00000000000000000000, 3.00000000000000000000, 3.16992500144231236295, 3.00000000000000000000, 2.58496250072115618147, 2.58496250072115618147, 3.58496250072115618147, 3.58496250072115618147, 3.00000000000000000000, 2.80735492205760410749, 3.90689059560851852928, 3.00000000000000000000, 2.80735492205760410749, 3.58496250072115618147, 3.16992500144231236295, 2.80735492205760410749, 2.58496250072115618147, 3.16992500144231236295, 2.00000000000000000000, 4.08746284125033940843, 1.58496250072115618147, 2.32192809488736234781, 3.00000000000000000000, 3.58496250072115618147, 2.32192809488736234781, 2.80735492205760410749, 3.58496250072115618147, 2.80735492205760410749, 3.32192809488736234781, 3.45943161863729725615, 3.80735492205760410749, 3.16992500144231236295, 2.58496250072115618147, 3.32192809488736234781, 2.58496250072115618147, 3.70043971814109216032, 2.58496250072115618147, 3.00000000000000000000, 3.32192809488736234781, 3.32192809488736234781, 2.32192809488736234781, 2.80735492205760410749, 3.32192809488736234781, 3.16992500144231236295, 3.45943161863729725615, 2.80735492205760410749, 3.16992500144231236295, 3.00000000000000000000, 3.00000000000000000000, 3.70043971814109216032, 3.16992500144231236295, 3.70043971814109216032, 3.58496250072115618147, 3.16992500144231236295, 3.58496250072115618147, 2.32192809488736234781, 3.00000000000000000000, 3.45943161863729725615, 3.00000000000000000000, 2.32192809488736234781, 2.58496250072115618147, 2.80735492205760410749, 3.45943161863729725615, 4.08746284125033940843, 3.90689059560851852928, 3.80735492205760410749, 3.16992500144231236295, 2.58496250072115618147, 3.70043971814109216032, 2.80735492205760410749, 3.70043971814109216032, 3.80735492205760410749, 3.32192809488736234781, 2.80735492205760410749, 2.58496250072115618147, 3.16992500144231236295, 3.80735492205760410749, 3.32192809488736234781, 3.80735492205760410749, 2.58496250072115618147, 2.80735492205760410749, 3.00000000000000000000, 3.58496250072115618147, 3.00000000000000000000, 2.80735492205760410749, 3.58496250072115618147, 3.16992500144231236295, 3.58496250072115618147, 2.00000000000000000000, 3.32192809488736234781, 2.32192809488736234781, 2.80735492205760410749, 2.80735492205760410749, 2.80735492205760410749, 3.45943161863729725615, 3.32192809488736234781, 3.58496250072115618147, 3.70043971814109216032, 3.16992500144231236295, 3.16992500144231236295, 2.58496250072115618147, 3.45943161863729725615, 3.32192809488736234781, 3.16992500144231236295, 2.00000000000000000000, 2.58496250072115618147, 3.00000000000000000000, 3.00000000000000000000, 3.00000000000000000000, ]
yt = [ 2.58496250072115618147, 2.70043971814109216032, 2.80735492205760410749, 2.90689059560851852928, 3.00000000000000000000, 3.08746284125033940821, 3.16992500144231236295, 3.24792751344358549383, 3.32192809488736234781, 3.39231742277876028896, 3.45943161863729725615, 3.52356195605701287229, 3.58496250072115618147, 3.64385618977472469583, ]
xt = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, ]
nlist = [ n12, n13, n14, n15, n16, n17, n18, n19, n20, n21, n22, n23, n24, n25]
# multiple box plots on one figure
fig, ax1 = plt.subplots()
bp = plt.boxplot(nlist, notch=0, sym='+', vert=1)
plt.xticks([1,2,3,4,5,6,7,8,9,10,11,12,13,14],[12,13,14,15,16,17,18,19,20,21,22,23,24,25])
for i in range(0,14):
med = bp['medians'][i]
plt.plot([np.average(med.get_xdata())], [np.average(nlist[i])], color='r', marker='*', markeredgecolor='k')
# Add a horizontal grid to the plot, but make it very light in color
# so we can use it for reading data values but not be distracting
ax1.yaxis.grid(True, linestyle='--', which='major', color='lightgrey', alpha=0.5)
# Hide these grid behind plot objects
ax1.set_axisbelow(True)
ax1.set_title('Number of component in FG of chopped AES-128 ($768$ random samplings)', fontsize=10, fontweight='bold')
ax1.set_xlabel('$\log_2(N)$')
ax1.set_ylabel('$\log_2(\#\mathrm{component})$')
the, = plt.plot(xt,yt,color='blue',label='Theoretical average value')
average_line, = plt.plot([], color='w', marker='*', markerfacecolor='red', markeredgecolor='k', markersize=8, label='Experimental average value')
plt.legend([the, average_line], ['Theoretical average value', 'Experimental average value'])
plt.savefig('n12_n25_componentN.pdf')
plt.savefig('n12_n25_componentN.png')
plt.show()
| 6,089.625
| 20,744
| 0.777124
| 21,805
| 292,302
| 10.416969
| 0.00798
| 0.14321
| 0.079809
| 0.046596
| 0.991763
| 0.988175
| 0.976099
| 0.91935
| 0.792548
| 0.496672
| 0
| 0.908521
| 0.148073
| 292,302
| 47
| 20,745
| 6,219.191489
| 0.003622
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| 1
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| 1
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| null | 0
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| 0
| 0
|
0
| 10
|
8dc9f92de6c024139626f4014c6bd1ab71108ae4
| 109
|
py
|
Python
|
tps/git_orm/models/__init__.py
|
akmohtashami/tps-web
|
9dab3ffe97c21f658be30ce2f2711dd93e4ba60f
|
[
"MIT"
] | 5
|
2019-02-26T06:10:43.000Z
|
2021-07-24T17:11:45.000Z
|
tps/git_orm/models/__init__.py
|
akmohtashami/tps-web
|
9dab3ffe97c21f658be30ce2f2711dd93e4ba60f
|
[
"MIT"
] | 3
|
2019-08-15T13:56:03.000Z
|
2021-06-10T18:43:16.000Z
|
tps/git_orm/models/__init__.py
|
jonathanirvings/tps-web
|
46519347d4fc8bdced9b5bceb6cdee5ea4e508f2
|
[
"MIT"
] | 2
|
2018-12-28T13:12:59.000Z
|
2020-12-25T18:42:13.000Z
|
from git_orm.models.base import Model
from git_orm.models.fields import *
from git_orm.models.query import Q
| 27.25
| 37
| 0.825688
| 20
| 109
| 4.35
| 0.5
| 0.241379
| 0.344828
| 0.551724
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| 109
| 3
| 38
| 36.333333
| 0.896907
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| 1
| 0
| 0
| 0
|
0
| 7
|
8dd38fa383eaa73f182383ecac41addd113750e5
| 184
|
py
|
Python
|
distributed/diagnostics/__init__.py
|
minrk/distributed
|
6da80822c75a069c14c55297cf9fc798416d3cd4
|
[
"BSD-3-Clause"
] | 1
|
2016-07-21T04:03:22.000Z
|
2016-07-21T04:03:22.000Z
|
distributed/diagnostics/__init__.py
|
minrk/distributed
|
6da80822c75a069c14c55297cf9fc798416d3cd4
|
[
"BSD-3-Clause"
] | null | null | null |
distributed/diagnostics/__init__.py
|
minrk/distributed
|
6da80822c75a069c14c55297cf9fc798416d3cd4
|
[
"BSD-3-Clause"
] | null | null | null |
from ..utils import ignoring
with ignoring(ImportError):
from .progressbar import progress
with ignoring(ImportError):
from .resource_monitor import ResourceMonitor, Occupancy
| 30.666667
| 60
| 0.804348
| 20
| 184
| 7.35
| 0.6
| 0.163265
| 0.312925
| 0.367347
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| 0
| 0
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| 0
| 0.13587
| 184
| 5
| 61
| 36.8
| 0.924528
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| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
8df01da5bd0958199832d34de129670776ef7867
| 3,071
|
py
|
Python
|
Day 1/system.py
|
RedoC-github/Gifted-Information-2021
|
90a3cd1100d2d1407083a42a2afdffe521e21f76
|
[
"MIT"
] | null | null | null |
Day 1/system.py
|
RedoC-github/Gifted-Information-2021
|
90a3cd1100d2d1407083a42a2afdffe521e21f76
|
[
"MIT"
] | null | null | null |
Day 1/system.py
|
RedoC-github/Gifted-Information-2021
|
90a3cd1100d2d1407083a42a2afdffe521e21f76
|
[
"MIT"
] | null | null | null |
from SIRmodel import SIR
import matplotlib.pyplot as plt
# STD: April 22, 2021
N = 674635
I = 687
R = 660 + 25018 + 1 # recovered + vaccination + dead
S = N - I
def simulateWithNoQuarantine():
model = SIR(S, I, R, 1, 1./30)
ds = [[], [], [], []] # [date, S, I, R]
for i in range(360):
model.update()
ds[0].append(i)
ds[1].append(model.S)
ds[2].append(model.I)
ds[3].append(model.R)
plt.title("Simulation with no quarantine")
plt.ylabel("Number of People")
plt.xlabel("Date")
plt.plot(ds[0], ds[1], label="Susceptible")
plt.plot(ds[0], ds[2], label="Infectible")
plt.plot(ds[0], ds[3], label="Recovery/Removed")
plt.legend()
plt.show()
def simulateWithLooseQuarantine():
model = SIR(S, I, R, 0.5, 1./30)
ds = [[], [], [], []] # [date, S, I, R]
for i in range(360):
model.update()
ds[0].append(i)
ds[1].append(model.S)
ds[2].append(model.I)
ds[3].append(model.R)
plt.title("Simulation with loose quarantine")
plt.ylabel("Number of People")
plt.xlabel("Date")
plt.plot(ds[0], ds[1], label="Susceptible")
plt.plot(ds[0], ds[2], label="Infectible")
plt.plot(ds[0], ds[3], label="Recovery/Removed")
plt.legend()
plt.show()
def simulateWithNormalQuarantine():
model = SIR(S, I, R, 0.2, 1./20)
ds = [[], [], [], []] # [date, S, I, R]
for i in range(360):
model.update()
ds[0].append(i)
ds[1].append(model.S)
ds[2].append(model.I)
ds[3].append(model.R)
plt.title("Simulation with normal quarantine")
plt.ylabel("Number of People")
plt.xlabel("Date")
plt.plot(ds[0], ds[1], label="Susceptible")
plt.plot(ds[0], ds[2], label="Infectible")
plt.plot(ds[0], ds[3], label="Recovery/Removed")
plt.legend()
plt.show()
def simulateWithKoreanQuarantine():
model = SIR(S, I, R, 0.1, 1./30)
ds = [[], [], [], []] # [date, S, I, R]
for i in range(360):
model.update()
ds[0].append(i)
ds[1].append(model.S)
ds[2].append(model.I)
ds[3].append(model.R)
plt.title("Simulation with hard quarantine")
plt.ylabel("Number of People")
plt.xlabel("Date")
plt.plot(ds[0], ds[1], label="Susceptible")
plt.plot(ds[0], ds[2], label="Infectible")
plt.plot(ds[0], ds[3], label="Recovery/Removed")
plt.legend()
plt.show()
def simulateWithLockdown():
model = SIR(S, I, R, 0.05, 1./30) # assume everyone stay at home.
ds = [[], [], [], []] # [date, S, I, R]
for i in range(360):
model.update()
ds[0].append(i)
ds[1].append(model.S)
ds[2].append(model.I)
ds[3].append(model.R)
plt.title("Simulation with lockdown")
plt.ylabel("Number of People")
plt.xlabel("Date")
plt.plot(ds[0], ds[1], label="Susceptible")
plt.plot(ds[0], ds[2], label="Infectible")
plt.plot(ds[0], ds[3], label="Recovery/Removed")
plt.legend()
plt.show()
| 26.938596
| 70
| 0.549007
| 455
| 3,071
| 3.705495
| 0.16044
| 0.035587
| 0.080071
| 0.088968
| 0.822657
| 0.816133
| 0.787663
| 0.787663
| 0.787663
| 0.787663
| 0
| 0.049544
| 0.250733
| 3,071
| 113
| 71
| 27.176991
| 0.683181
| 0.0521
| 0
| 0.769231
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| 0
| 0.149552
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| 0.054945
| false
| 0
| 0.021978
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| 0
| 0
|
0
| 7
|
5c12608f47f128342bf1c6072e74147ca7b51b3f
| 1,990
|
py
|
Python
|
db/models.py
|
igor-ribeiiro/help_me-bot
|
f5fe997506ca78356f2bf1b47c12cdd7889eb0dd
|
[
"MIT"
] | null | null | null |
db/models.py
|
igor-ribeiiro/help_me-bot
|
f5fe997506ca78356f2bf1b47c12cdd7889eb0dd
|
[
"MIT"
] | null | null | null |
db/models.py
|
igor-ribeiiro/help_me-bot
|
f5fe997506ca78356f2bf1b47c12cdd7889eb0dd
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, Unicode, DateTime
from datetime import datetime
Base = declarative_base()
class OfferedTraining(Base):
__tablename__ = "offeredtraining"
id = Column(Integer, primary_key=True)
id_slack = Column(Unicode(), unique=False, nullable=True)
team = Column(Unicode(), unique=False, nullable=True)
suggestion = Column(Unicode(), unique=False, nullable=True)
date = Column(DateTime(timezone=True), unique=False, nullable=True)
def __init__(self, id_slack, team, suggestion):
self.date = datetime.utcnow()
self.id_slack = id_slack
self.team = team
self.suggestion = suggestion
def __repr__(self):
return self.suggestion
# return "offered training {0} from {1}".format(self.suggestion, self.team)
class RequestedTraining(Base):
__tablename__ = "requestedtraining"
id = Column(Integer, primary_key=True)
id_slack = Column(Unicode(), unique=False, nullable=True)
team = Column(Unicode(), unique=False, nullable=True)
suggestion = Column(Unicode(), unique=False, nullable=True)
date = Column(DateTime(timezone=True), unique=False, nullable=True)
def __init__(self, id_slack, team, suggestion):
self.date = datetime.utcnow()
self.id_slack = id_slack
self.team = team
self.suggestion = suggestion
def __repr__(self):
return self.suggestion
# return "suggested training {0} from {1}".format(self.suggestion, self.team)
class User(Base):
__tablename__ = "user"
id = Column(Integer, primary_key=True)
id_slack = Column(Unicode(), unique=False, nullable=True)
team = Column(Unicode(), unique=False, nullable=True)
def __init__(self, id_slack, team):
self.id_slack = id_slack
self.team = team
def __repr__(self):
return "user {0}, team {1}".format(self.user, self.team)
| 33.166667
| 85
| 0.681407
| 239
| 1,990
| 5.451883
| 0.175732
| 0.064467
| 0.145817
| 0.176516
| 0.744436
| 0.744436
| 0.744436
| 0.744436
| 0.721412
| 0.721412
| 0
| 0.0044
| 0.200503
| 1,990
| 59
| 86
| 33.728814
| 0.814582
| 0.08593
| 0
| 0.714286
| 0
| 0
| 0.029752
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0.071429
| 0.071429
| 0.738095
| 0
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| 0
| null | 0
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| 1
| 1
| 1
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| null | 0
| 0
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| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
3096358dc5ae95221ed80eb9c6286dffbcf3ae62
| 190,737
|
py
|
Python
|
cmake-3.15.2/Tests/RunCMake/FileAPI/codemodel-v2-check.py
|
GavinMilbank/Engine
|
aa005334bd6640c78d97106a19ec3b1022cc9a62
|
[
"BSD-3-Clause"
] | null | null | null |
cmake-3.15.2/Tests/RunCMake/FileAPI/codemodel-v2-check.py
|
GavinMilbank/Engine
|
aa005334bd6640c78d97106a19ec3b1022cc9a62
|
[
"BSD-3-Clause"
] | null | null | null |
cmake-3.15.2/Tests/RunCMake/FileAPI/codemodel-v2-check.py
|
GavinMilbank/Engine
|
aa005334bd6640c78d97106a19ec3b1022cc9a62
|
[
"BSD-3-Clause"
] | null | null | null |
from check_index import *
import sys
import os
def check_objects(o, g):
assert is_list(o)
assert len(o) == 1
check_index_object(o[0], "codemodel", 2, 0, check_object_codemodel(g))
def check_backtrace(t, b, backtrace):
btg = t["backtraceGraph"]
for expected in backtrace:
assert is_int(b)
node = btg["nodes"][b]
expected_keys = ["file"]
assert matches(btg["files"][node["file"]], expected["file"])
if expected["line"] is not None:
expected_keys.append("line")
assert is_int(node["line"], expected["line"])
if expected["command"] is not None:
expected_keys.append("command")
assert is_int(node["command"])
assert is_string(btg["commands"][node["command"]], expected["command"])
if expected["hasParent"]:
expected_keys.append("parent")
assert is_int(node["parent"])
b = node["parent"]
else:
b = None
assert sorted(node.keys()) == sorted(expected_keys)
assert b is None
def check_directory(c):
def _check(actual, expected):
assert is_dict(actual)
expected_keys = ["build", "source", "projectIndex"]
assert matches(actual["build"], expected["build"])
assert is_int(actual["projectIndex"])
assert is_string(c["projects"][actual["projectIndex"]]["name"], expected["projectName"])
if expected["parentSource"] is not None:
expected_keys.append("parentIndex")
assert is_int(actual["parentIndex"])
assert matches(c["directories"][actual["parentIndex"]]["source"], expected["parentSource"])
if expected["childSources"] is not None:
expected_keys.append("childIndexes")
check_list_match(lambda a, e: matches(c["directories"][a]["source"], e),
actual["childIndexes"], expected["childSources"],
missing_exception=lambda e: "Child source: %s" % e,
extra_exception=lambda a: "Child source: %s" % a["source"])
if expected["targetIds"] is not None:
expected_keys.append("targetIndexes")
check_list_match(lambda a, e: matches(c["targets"][a]["id"], e),
actual["targetIndexes"], expected["targetIds"],
missing_exception=lambda e: "Target ID: %s" % e,
extra_exception=lambda a: "Target ID: %s" % c["targets"][a]["id"])
if expected["minimumCMakeVersion"] is not None:
expected_keys.append("minimumCMakeVersion")
assert is_dict(actual["minimumCMakeVersion"])
assert sorted(actual["minimumCMakeVersion"].keys()) == ["string"]
assert is_string(actual["minimumCMakeVersion"]["string"], expected["minimumCMakeVersion"])
if expected["hasInstallRule"] is not None:
expected_keys.append("hasInstallRule")
assert is_bool(actual["hasInstallRule"], expected["hasInstallRule"])
assert sorted(actual.keys()) == sorted(expected_keys)
return _check
def check_target_backtrace_graph(t):
btg = t["backtraceGraph"]
assert is_dict(btg)
assert sorted(btg.keys()) == ["commands", "files", "nodes"]
assert is_list(btg["commands"])
for c in btg["commands"]:
assert is_string(c)
for f in btg["files"]:
assert is_string(f)
for n in btg["nodes"]:
expected_keys = ["file"]
assert is_dict(n)
assert is_int(n["file"])
assert 0 <= n["file"] < len(btg["files"])
if "line" in n:
expected_keys.append("line")
assert is_int(n["line"])
if "command" in n:
expected_keys.append("command")
assert is_int(n["command"])
assert 0 <= n["command"] < len(btg["commands"])
if "parent" in n:
expected_keys.append("parent")
assert is_int(n["parent"])
assert 0 <= n["parent"] < len(btg["nodes"])
assert sorted(n.keys()) == sorted(expected_keys)
def check_target(c):
def _check(actual, expected):
assert is_dict(actual)
assert sorted(actual.keys()) == ["directoryIndex", "id", "jsonFile", "name", "projectIndex"]
assert is_int(actual["directoryIndex"])
assert matches(c["directories"][actual["directoryIndex"]]["source"], expected["directorySource"])
assert is_string(actual["name"], expected["name"])
assert is_string(actual["jsonFile"])
assert is_int(actual["projectIndex"])
assert is_string(c["projects"][actual["projectIndex"]]["name"], expected["projectName"])
filepath = os.path.join(reply_dir, actual["jsonFile"])
with open(filepath) as f:
obj = json.load(f)
expected_keys = ["name", "id", "type", "backtraceGraph", "paths", "sources"]
assert is_dict(obj)
assert is_string(obj["name"], expected["name"])
assert matches(obj["id"], expected["id"])
assert is_string(obj["type"], expected["type"])
check_target_backtrace_graph(obj)
assert is_dict(obj["paths"])
assert sorted(obj["paths"].keys()) == ["build", "source"]
assert matches(obj["paths"]["build"], expected["build"])
assert matches(obj["paths"]["source"], expected["source"])
def check_source(actual, expected):
assert is_dict(actual)
expected_keys = ["path"]
if expected["compileGroupLanguage"] is not None:
expected_keys.append("compileGroupIndex")
assert is_string(obj["compileGroups"][actual["compileGroupIndex"]]["language"], expected["compileGroupLanguage"])
if expected["sourceGroupName"] is not None:
expected_keys.append("sourceGroupIndex")
assert is_string(obj["sourceGroups"][actual["sourceGroupIndex"]]["name"], expected["sourceGroupName"])
if expected["isGenerated"] is not None:
expected_keys.append("isGenerated")
assert is_bool(actual["isGenerated"], expected["isGenerated"])
if expected["backtrace"] is not None:
expected_keys.append("backtrace")
check_backtrace(obj, actual["backtrace"], expected["backtrace"])
assert sorted(actual.keys()) == sorted(expected_keys)
check_list_match(lambda a, e: matches(a["path"], e["path"]), obj["sources"],
expected["sources"], check=check_source,
check_exception=lambda a, e: "Source file: %s" % a["path"],
missing_exception=lambda e: "Source file: %s" % e["path"],
extra_exception=lambda a: "Source file: %s" % a["path"])
if expected["backtrace"] is not None:
expected_keys.append("backtrace")
check_backtrace(obj, obj["backtrace"], expected["backtrace"])
if expected["folder"] is not None:
expected_keys.append("folder")
assert is_dict(obj["folder"])
assert sorted(obj["folder"].keys()) == ["name"]
assert is_string(obj["folder"]["name"], expected["folder"])
if expected["nameOnDisk"] is not None:
expected_keys.append("nameOnDisk")
assert matches(obj["nameOnDisk"], expected["nameOnDisk"])
if expected["artifacts"] is not None:
expected_keys.append("artifacts")
def check_artifact(actual, expected):
assert is_dict(actual)
assert sorted(actual.keys()) == ["path"]
check_list_match(lambda a, e: matches(a["path"], e["path"]),
obj["artifacts"], expected["artifacts"],
check=check_artifact,
check_exception=lambda a, e: "Artifact: %s" % a["path"],
missing_exception=lambda e: "Artifact: %s" % e["path"],
extra_exception=lambda a: "Artifact: %s" % a["path"])
if expected["isGeneratorProvided"] is not None:
expected_keys.append("isGeneratorProvided")
assert is_bool(obj["isGeneratorProvided"], expected["isGeneratorProvided"])
if expected["install"] is not None:
expected_keys.append("install")
assert is_dict(obj["install"])
assert sorted(obj["install"].keys()) == ["destinations", "prefix"]
assert is_dict(obj["install"]["prefix"])
assert sorted(obj["install"]["prefix"].keys()) == ["path"]
assert matches(obj["install"]["prefix"]["path"], expected["install"]["prefix"])
def check_install_destination(actual, expected):
assert is_dict(actual)
expected_keys = ["path"]
if expected["backtrace"] is not None:
expected_keys.append("backtrace")
check_backtrace(obj, actual["backtrace"], expected["backtrace"])
assert sorted(actual.keys()) == sorted(expected_keys)
check_list_match(lambda a, e: matches(a["path"], e["path"]),
obj["install"]["destinations"], expected["install"]["destinations"],
check=check_install_destination,
check_exception=lambda a, e: "Install path: %s" % a["path"],
missing_exception=lambda e: "Install path: %s" % e["path"],
extra_exception=lambda a: "Install path: %s" % a["path"])
if expected["link"] is not None:
expected_keys.append("link")
assert is_dict(obj["link"])
link_keys = ["language"]
assert is_string(obj["link"]["language"], expected["link"]["language"])
# FIXME: Properly test commandFragments
if "commandFragments" in obj["link"]:
link_keys.append("commandFragments")
assert is_list(obj["link"]["commandFragments"])
for f in obj["link"]["commandFragments"]:
assert is_dict(f)
assert sorted(f.keys()) == ["fragment", "role"]
assert is_string(f["fragment"])
assert is_string(f["role"])
assert f["role"] in ("flags", "libraries", "libraryPath", "frameworkPath")
if expected["link"]["lto"] is not None:
link_keys.append("lto")
assert is_bool(obj["link"]["lto"], expected["link"]["lto"])
# FIXME: Properly test sysroot
if "sysroot" in obj["link"]:
link_keys.append("sysroot")
assert is_string(obj["link"]["sysroot"])
assert sorted(obj["link"].keys()) == sorted(link_keys)
if expected["archive"] is not None:
expected_keys.append("archive")
assert is_dict(obj["archive"])
archive_keys = []
# FIXME: Properly test commandFragments
if "commandFragments" in obj["archive"]:
archive_keys.append("commandFragments")
assert is_list(obj["archive"]["commandFragments"])
for f in obj["archive"]["commandFragments"]:
assert is_dict(f)
assert sorted(f.keys()) == ["fragment", "role"]
assert is_string(f["fragment"])
assert is_string(f["role"])
assert f["role"] in ("flags")
if expected["archive"]["lto"] is not None:
archive_keys.append("lto")
assert is_bool(obj["archive"]["lto"], expected["archive"]["lto"])
assert sorted(obj["archive"].keys()) == sorted(archive_keys)
if expected["dependencies"] is not None:
expected_keys.append("dependencies")
def check_dependency(actual, expected):
assert is_dict(actual)
expected_keys = ["id"]
if expected["backtrace"] is not None:
expected_keys.append("backtrace")
check_backtrace(obj, actual["backtrace"], expected["backtrace"])
assert sorted(actual.keys()) == sorted(expected_keys)
check_list_match(lambda a, e: matches(a["id"], e["id"]),
obj["dependencies"], expected["dependencies"],
check=check_dependency,
check_exception=lambda a, e: "Dependency ID: %s" % a["id"],
missing_exception=lambda e: "Dependency ID: %s" % e["id"],
extra_exception=lambda a: "Dependency ID: %s" % a["id"])
if expected["sourceGroups"] is not None:
expected_keys.append("sourceGroups")
def check_source_group(actual, expected):
assert is_dict(actual)
assert sorted(actual.keys()) == ["name", "sourceIndexes"]
check_list_match(lambda a, e: matches(obj["sources"][a]["path"], e),
actual["sourceIndexes"], expected["sourcePaths"],
missing_exception=lambda e: "Source path: %s" % e,
extra_exception=lambda a: "Source path: %s" % obj["sources"][a]["path"])
check_list_match(lambda a, e: is_string(a["name"], e["name"]),
obj["sourceGroups"], expected["sourceGroups"],
check=check_source_group,
check_exception=lambda a, e: "Source group: %s" % a["name"],
missing_exception=lambda e: "Source group: %s" % e["name"],
extra_exception=lambda a: "Source group: %s" % a["name"])
if expected["compileGroups"] is not None:
expected_keys.append("compileGroups")
def check_compile_group(actual, expected):
assert is_dict(actual)
expected_keys = ["sourceIndexes", "language"]
check_list_match(lambda a, e: matches(obj["sources"][a]["path"], e),
actual["sourceIndexes"], expected["sourcePaths"],
missing_exception=lambda e: "Source path: %s" % e,
extra_exception=lambda a: "Source path: %s" % obj["sources"][a]["path"])
# FIXME: Properly test compileCommandFragments
if "compileCommandFragments" in actual:
expected_keys.append("compileCommandFragments")
assert is_list(actual["compileCommandFragments"])
for f in actual["compileCommandFragments"]:
assert is_dict(f)
assert sorted(f.keys()) == ["fragment"]
assert is_string(f["fragment"])
if expected["includes"] is not None:
expected_keys.append("includes")
def check_include(actual, expected):
assert is_dict(actual)
expected_keys = ["path"]
if expected["isSystem"] is not None:
expected_keys.append("isSystem")
assert is_bool(actual["isSystem"], expected["isSystem"])
if expected["backtrace"] is not None:
expected_keys.append("backtrace")
check_backtrace(obj, actual["backtrace"], expected["backtrace"])
assert sorted(actual.keys()) == sorted(expected_keys)
check_list_match(lambda a, e: matches(a["path"], e["path"]),
actual["includes"], expected["includes"],
check=check_include,
check_exception=lambda a, e: "Include path: %s" % a["path"],
missing_exception=lambda e: "Include path: %s" % e["path"],
extra_exception=lambda a: "Include path: %s" % a["path"])
if expected["defines"] is not None:
expected_keys.append("defines")
def check_define(actual, expected):
assert is_dict(actual)
expected_keys = ["define"]
if expected["backtrace"] is not None:
expected_keys.append("backtrace")
check_backtrace(obj, actual["backtrace"], expected["backtrace"])
assert sorted(actual.keys()) == sorted(expected_keys)
check_list_match(lambda a, e: is_string(a["define"], e["define"]),
actual["defines"], expected["defines"],
check=check_define,
check_exception=lambda a, e: "Define: %s" % a["define"],
missing_exception=lambda e: "Define: %s" % e["define"],
extra_exception=lambda a: "Define: %s" % a["define"])
# FIXME: Properly test sysroot
if "sysroot" in actual:
expected_keys.append("sysroot")
assert is_string(actual["sysroot"])
assert sorted(actual.keys()) == sorted(expected_keys)
check_list_match(lambda a, e: is_string(a["language"], e["language"]),
obj["compileGroups"], expected["compileGroups"],
check=check_compile_group,
check_exception=lambda a, e: "Compile group: %s" % a["language"],
missing_exception=lambda e: "Compile group: %s" % e["language"],
extra_exception=lambda a: "Compile group: %s" % a["language"])
assert sorted(obj.keys()) == sorted(expected_keys)
return _check
def check_project(c):
def _check(actual, expected):
assert is_dict(actual)
expected_keys = ["name", "directoryIndexes"]
check_list_match(lambda a, e: matches(c["directories"][a]["source"], e),
actual["directoryIndexes"], expected["directorySources"],
missing_exception=lambda e: "Directory source: %s" % e,
extra_exception=lambda a: "Directory source: %s" % c["directories"][a]["source"])
if expected["parentName"] is not None:
expected_keys.append("parentIndex")
assert is_int(actual["parentIndex"])
assert is_string(c["projects"][actual["parentIndex"]]["name"], expected["parentName"])
if expected["childNames"] is not None:
expected_keys.append("childIndexes")
check_list_match(lambda a, e: is_string(c["projects"][a]["name"], e),
actual["childIndexes"], expected["childNames"],
missing_exception=lambda e: "Child name: %s" % e,
extra_exception=lambda a: "Child name: %s" % c["projects"][a]["name"])
if expected["targetIds"] is not None:
expected_keys.append("targetIndexes")
check_list_match(lambda a, e: matches(c["targets"][a]["id"], e),
actual["targetIndexes"], expected["targetIds"],
missing_exception=lambda e: "Target ID: %s" % e,
extra_exception=lambda a: "Target ID: %s" % c["targets"][a]["id"])
assert sorted(actual.keys()) == sorted(expected_keys)
return _check
def gen_check_directories(c, g):
expected = [
{
"source": "^\\.$",
"build": "^\\.$",
"parentSource": None,
"childSources": [
"^alias$",
"^custom$",
"^cxx$",
"^imported$",
"^object$",
"^.*/Tests/RunCMake/FileAPIExternalSource$",
"^dir$",
],
"targetIds": [
"^ALL_BUILD::@6890427a1f51a3e7e1df$",
"^ZERO_CHECK::@6890427a1f51a3e7e1df$",
"^c_exe::@6890427a1f51a3e7e1df$",
"^c_lib::@6890427a1f51a3e7e1df$",
"^c_shared_exe::@6890427a1f51a3e7e1df$",
"^c_shared_lib::@6890427a1f51a3e7e1df$",
"^c_static_exe::@6890427a1f51a3e7e1df$",
"^c_static_lib::@6890427a1f51a3e7e1df$",
"^interface_exe::@6890427a1f51a3e7e1df$",
],
"projectName": "codemodel-v2",
"minimumCMakeVersion": "3.12",
"hasInstallRule": True,
},
{
"source": "^alias$",
"build": "^alias$",
"parentSource": "^\\.$",
"childSources": None,
"targetIds": [
"^ALL_BUILD::@53632cba2752272bb008$",
"^ZERO_CHECK::@53632cba2752272bb008$",
"^c_alias_exe::@53632cba2752272bb008$",
"^cxx_alias_exe::@53632cba2752272bb008$",
],
"projectName": "Alias",
"minimumCMakeVersion": "3.12",
"hasInstallRule": None,
},
{
"source": "^custom$",
"build": "^custom$",
"parentSource": "^\\.$",
"childSources": None,
"targetIds": [
"^ALL_BUILD::@c11385ffed57b860da63$",
"^ZERO_CHECK::@c11385ffed57b860da63$",
"^custom_exe::@c11385ffed57b860da63$",
"^custom_tgt::@c11385ffed57b860da63$",
],
"projectName": "Custom",
"minimumCMakeVersion": "3.12",
"hasInstallRule": None,
},
{
"source": "^cxx$",
"build": "^cxx$",
"parentSource": "^\\.$",
"childSources": None,
"targetIds": [
"^ALL_BUILD::@a56b12a3f5c0529fb296$",
"^ZERO_CHECK::@a56b12a3f5c0529fb296$",
"^cxx_exe::@a56b12a3f5c0529fb296$",
"^cxx_lib::@a56b12a3f5c0529fb296$",
"^cxx_shared_exe::@a56b12a3f5c0529fb296$",
"^cxx_shared_lib::@a56b12a3f5c0529fb296$",
"^cxx_static_exe::@a56b12a3f5c0529fb296$",
"^cxx_static_lib::@a56b12a3f5c0529fb296$",
],
"projectName": "Cxx",
"minimumCMakeVersion": "3.12",
"hasInstallRule": None,
},
{
"source": "^imported$",
"build": "^imported$",
"parentSource": "^\\.$",
"childSources": None,
"targetIds": [
"^ALL_BUILD::@ba7eb709d0b48779c6c8$",
"^ZERO_CHECK::@ba7eb709d0b48779c6c8$",
"^link_imported_exe::@ba7eb709d0b48779c6c8$",
"^link_imported_interface_exe::@ba7eb709d0b48779c6c8$",
"^link_imported_object_exe::@ba7eb709d0b48779c6c8$",
"^link_imported_shared_exe::@ba7eb709d0b48779c6c8$",
"^link_imported_static_exe::@ba7eb709d0b48779c6c8$",
],
"projectName": "Imported",
"minimumCMakeVersion": "3.12",
"hasInstallRule": None,
},
{
"source": "^object$",
"build": "^object$",
"parentSource": "^\\.$",
"childSources": None,
"targetIds": [
"^ALL_BUILD::@5ed5358f70faf8d8af7a$",
"^ZERO_CHECK::@5ed5358f70faf8d8af7a$",
"^c_object_exe::@5ed5358f70faf8d8af7a$",
"^c_object_lib::@5ed5358f70faf8d8af7a$",
"^cxx_object_exe::@5ed5358f70faf8d8af7a$",
"^cxx_object_lib::@5ed5358f70faf8d8af7a$",
],
"projectName": "Object",
"minimumCMakeVersion": "3.13",
"hasInstallRule": True,
},
{
"source": "^dir$",
"build": "^dir$",
"parentSource": "^\\.$",
"childSources": [
"^dir/dir$",
],
"targetIds": None,
"projectName": "codemodel-v2",
"minimumCMakeVersion": "3.12",
"hasInstallRule": None,
},
{
"source": "^dir/dir$",
"build": "^dir/dir$",
"parentSource": "^dir$",
"childSources": None,
"targetIds": None,
"projectName": "codemodel-v2",
"minimumCMakeVersion": "3.12",
"hasInstallRule": None,
},
{
"source": "^.*/Tests/RunCMake/FileAPIExternalSource$",
"build": "^.*/Tests/RunCMake/FileAPI/FileAPIExternalBuild$",
"parentSource": "^\\.$",
"childSources": None,
"targetIds": [
"^ALL_BUILD::@[0-9a-f]+$",
"^ZERO_CHECK::@[0-9a-f]+$",
"^generated_exe::@[0-9a-f]+$",
],
"projectName": "External",
"minimumCMakeVersion": "3.12",
"hasInstallRule": None,
},
]
if matches(g, "^Visual Studio "):
for e in expected:
if e["parentSource"] is not None:
e["targetIds"] = filter_list(lambda t: not matches(t, "^\\^ZERO_CHECK"), e["targetIds"])
elif g == "Xcode":
if ';' in os.environ.get("CMAKE_OSX_ARCHITECTURES", ""):
for e in expected:
e["targetIds"] = filter_list(lambda t: not matches(t, "^\\^(link_imported_object_exe)"), e["targetIds"])
else:
for e in expected:
e["targetIds"] = filter_list(lambda t: not matches(t, "^\\^(ALL_BUILD|ZERO_CHECK)"), e["targetIds"])
return expected
def check_directories(c, g):
check_list_match(lambda a, e: matches(a["source"], e["source"]), c["directories"], gen_check_directories(c, g),
check=check_directory(c),
check_exception=lambda a, e: "Directory source: %s" % a["source"],
missing_exception=lambda e: "Directory source: %s" % e["source"],
extra_exception=lambda a: "Directory source: %s" % a["source"])
def gen_check_targets(c, g, inSource):
expected = [
{
"name": "ALL_BUILD",
"id": "^ALL_BUILD::@6890427a1f51a3e7e1df$",
"directorySource": "^\\.$",
"projectName": "codemodel-v2",
"type": "UTILITY",
"isGeneratorProvided": True,
"sources": [
{
"path": "^.*/Tests/RunCMake/FileAPI/codemodel-v2-build/CMakeFiles/ALL_BUILD$",
"isGenerated": True,
"sourceGroupName": "",
"compileGroupLanguage": None,
"backtrace": [
{
"file": "^CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
{
"path": "^.*/Tests/RunCMake/FileAPI/codemodel-v2-build/CMakeFiles/ALL_BUILD\\.rule$",
"isGenerated": True,
"sourceGroupName": "CMake Rules",
"compileGroupLanguage": None,
"backtrace": [
{
"file": "^CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
],
"sourceGroups": [
{
"name": "",
"sourcePaths": [
"^.*/Tests/RunCMake/FileAPI/codemodel-v2-build/CMakeFiles/ALL_BUILD$",
],
},
{
"name": "CMake Rules",
"sourcePaths": [
"^.*/Tests/RunCMake/FileAPI/codemodel-v2-build/CMakeFiles/ALL_BUILD\\.rule$",
],
},
],
"compileGroups": None,
"backtrace": [
{
"file": "^CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
"folder": None,
"nameOnDisk": None,
"artifacts": None,
"build": "^\\.$",
"source": "^\\.$",
"install": None,
"link": None,
"archive": None,
"dependencies": [
{
"id": "^ZERO_CHECK::@6890427a1f51a3e7e1df$",
"backtrace": None,
},
{
"id": "^interface_exe::@6890427a1f51a3e7e1df$",
"backtrace": None,
},
{
"id": "^c_lib::@6890427a1f51a3e7e1df$",
"backtrace": None,
},
{
"id": "^c_exe::@6890427a1f51a3e7e1df$",
"backtrace": None,
},
{
"id": "^c_shared_lib::@6890427a1f51a3e7e1df$",
"backtrace": None,
},
{
"id": "^c_shared_exe::@6890427a1f51a3e7e1df$",
"backtrace": None,
},
{
"id": "^c_static_lib::@6890427a1f51a3e7e1df$",
"backtrace": None,
},
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"sourcePaths": [
"^.*/Tests/RunCMake/FileAPIExternalSource/empty\\.c$",
],
"includes": [
{
"path": "^.*/Tests/RunCMake/FileAPI/FileAPIExternalBuild$",
"isSystem": None,
"backtrace": None,
},
{
"path": "^.*/Tests/RunCMake/FileAPIExternalSource$",
"isSystem": True,
"backtrace": [
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": 11,
"command": "target_include_directories",
"hasParent": True,
},
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
],
"defines": [
{
"define": "EMPTY_C=1",
"backtrace": None,
},
{
"define": "SRC_DUMMY",
"backtrace": None,
},
{
"define": "GENERATED_EXE=1",
"backtrace": [
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": 12,
"command": "target_compile_definitions",
"hasParent": True,
},
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
{
"define": "TGT_DUMMY",
"backtrace": [
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": 12,
"command": "target_compile_definitions",
"hasParent": True,
},
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
],
},
{
"language": "CXX",
"sourcePaths": [
"^.*/Tests/RunCMake/FileAPI/FileAPIExternalBuild/generated\\.cxx$",
],
"includes": [
{
"path": "^.*/Tests/RunCMake/FileAPIExternalSource$",
"isSystem": True,
"backtrace": [
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": 11,
"command": "target_include_directories",
"hasParent": True,
},
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
],
"defines": [
{
"define": "GENERATED_EXE=1",
"backtrace": [
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": 12,
"command": "target_compile_definitions",
"hasParent": True,
},
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
{
"define": "TGT_DUMMY",
"backtrace": [
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": 12,
"command": "target_compile_definitions",
"hasParent": True,
},
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
],
},
],
"backtrace": [
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": 5,
"command": "add_executable",
"hasParent": True,
},
{
"file": "^.*/Tests/RunCMake/FileAPIExternalSource/CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
"folder": None,
"nameOnDisk": "^generated_exe(\\.exe)?$",
"artifacts": [
{
"path": "^.*/Tests/RunCMake/FileAPI/FileAPIExternalBuild/((Debug|Release|RelWithDebInfo|MinSizeRel)/)?generated_exe(\\.exe)?$",
"_dllExtra": False,
},
{
"path": "^.*/Tests/RunCMake/FileAPI/FileAPIExternalBuild/((Debug|Release|RelWithDebInfo|MinSizeRel)/)?generated_exe\\.pdb$",
"_dllExtra": True,
},
],
"build": "^.*/Tests/RunCMake/FileAPI/FileAPIExternalBuild$",
"source": "^.*/Tests/RunCMake/FileAPIExternalSource$",
"install": None,
"link": {
"language": "CXX",
"lto": None,
},
"archive": None,
"dependencies": [
{
"id": "^ZERO_CHECK::@[0-9a-f]+$",
"backtrace": None,
},
],
},
]
if not os.path.exists(os.path.join(reply_dir, "..", "..", "..", "..", "ipo_enabled.txt")):
for e in expected:
try:
e["link"]["lto"] = None
except TypeError: # "link" is not a dict, no problem.
pass
try:
e["archive"]["lto"] = None
except TypeError: # "archive" is not a dict, no problem.
pass
if inSource:
for e in expected:
if e["sources"] is not None:
for s in e["sources"]:
s["path"] = s["path"].replace("^.*/Tests/RunCMake/FileAPI/", "^", 1)
if e["sourceGroups"] is not None:
for g in e["sourceGroups"]:
g["sourcePaths"] = [p.replace("^.*/Tests/RunCMake/FileAPI/", "^", 1) for p in g["sourcePaths"]]
if e["compileGroups"] is not None:
for g in e["compileGroups"]:
g["sourcePaths"] = [p.replace("^.*/Tests/RunCMake/FileAPI/", "^", 1) for p in g["sourcePaths"]]
if matches(g, "^Visual Studio "):
expected = filter_list(lambda e: e["name"] not in ("ZERO_CHECK") or e["id"] == "^ZERO_CHECK::@6890427a1f51a3e7e1df$", expected)
for e in expected:
if e["type"] == "UTILITY":
if e["id"] == "^ZERO_CHECK::@6890427a1f51a3e7e1df$":
e["sources"] = [
{
"path": "^.*/Tests/RunCMake/FileAPI/codemodel-v2-build/CMakeFiles/([0-9a-f]+/)?generate\\.stamp\\.rule$",
"isGenerated": True,
"sourceGroupName": "CMake Rules",
"compileGroupLanguage": None,
"backtrace": [
{
"file": "^CMakeLists\\.txt$",
"line": None,
"command": None,
"hasParent": False,
},
],
},
]
e["sourceGroups"] = [
{
"name": "CMake Rules",
"sourcePaths": [
"^.*/Tests/RunCMake/FileAPI/codemodel-v2-build/CMakeFiles/([0-9a-f]+/)?generate\\.stamp\\.rule$",
],
},
]
elif e["name"] in ("ALL_BUILD"):
e["sources"] = []
e["sourceGroups"] = None
if e["dependencies"] is not None:
for d in e["dependencies"]:
if matches(d["id"], "^\\^ZERO_CHECK::@"):
d["id"] = "^ZERO_CHECK::@6890427a1f51a3e7e1df$"
elif g == "Xcode":
if ';' in os.environ.get("CMAKE_OSX_ARCHITECTURES", ""):
expected = filter_list(lambda e: e["name"] not in ("link_imported_object_exe"), expected)
for e in expected:
e["dependencies"] = filter_list(lambda d: not matches(d["id"], "^\\^link_imported_object_exe::@"), e["dependencies"])
if e["name"] in ("c_object_lib", "cxx_object_lib"):
e["artifacts"] = None
else:
for e in expected:
e["dependencies"] = filter_list(lambda d: not matches(d["id"], "^\\^ZERO_CHECK::@"), e["dependencies"])
expected = filter_list(lambda t: t["name"] not in ("ALL_BUILD", "ZERO_CHECK"), expected)
if sys.platform not in ("win32", "cygwin", "msys"):
for e in expected:
e["artifacts"] = filter_list(lambda a: not a["_dllExtra"], e["artifacts"])
return expected
def check_targets(c, g, inSource):
check_list_match(lambda a, e: matches(a["id"], e["id"]),
c["targets"], gen_check_targets(c, g, inSource),
check=check_target(c),
check_exception=lambda a, e: "Target ID: %s" % a["id"],
missing_exception=lambda e: "Target ID: %s" % e["id"],
extra_exception=lambda a: "Target ID: %s" % a["id"])
def gen_check_projects(c, g):
expected = [
{
"name": "codemodel-v2",
"parentName": None,
"childNames": [
"Alias",
"Custom",
"Cxx",
"Imported",
"Object",
"External",
],
"directorySources": [
"^\\.$",
"^dir$",
"^dir/dir$",
],
"targetIds": [
"^ALL_BUILD::@6890427a1f51a3e7e1df$",
"^ZERO_CHECK::@6890427a1f51a3e7e1df$",
"^interface_exe::@6890427a1f51a3e7e1df$",
"^c_lib::@6890427a1f51a3e7e1df$",
"^c_exe::@6890427a1f51a3e7e1df$",
"^c_shared_lib::@6890427a1f51a3e7e1df$",
"^c_shared_exe::@6890427a1f51a3e7e1df$",
"^c_static_lib::@6890427a1f51a3e7e1df$",
"^c_static_exe::@6890427a1f51a3e7e1df$",
],
},
{
"name": "Cxx",
"parentName": "codemodel-v2",
"childNames": None,
"directorySources": [
"^cxx$",
],
"targetIds": [
"^ALL_BUILD::@a56b12a3f5c0529fb296$",
"^ZERO_CHECK::@a56b12a3f5c0529fb296$",
"^cxx_lib::@a56b12a3f5c0529fb296$",
"^cxx_exe::@a56b12a3f5c0529fb296$",
"^cxx_shared_lib::@a56b12a3f5c0529fb296$",
"^cxx_shared_exe::@a56b12a3f5c0529fb296$",
"^cxx_static_lib::@a56b12a3f5c0529fb296$",
"^cxx_static_exe::@a56b12a3f5c0529fb296$",
],
},
{
"name": "Alias",
"parentName": "codemodel-v2",
"childNames": None,
"directorySources": [
"^alias$",
],
"targetIds": [
"^ALL_BUILD::@53632cba2752272bb008$",
"^ZERO_CHECK::@53632cba2752272bb008$",
"^c_alias_exe::@53632cba2752272bb008$",
"^cxx_alias_exe::@53632cba2752272bb008$",
],
},
{
"name": "Object",
"parentName": "codemodel-v2",
"childNames": None,
"directorySources": [
"^object$",
],
"targetIds": [
"^ALL_BUILD::@5ed5358f70faf8d8af7a$",
"^ZERO_CHECK::@5ed5358f70faf8d8af7a$",
"^c_object_lib::@5ed5358f70faf8d8af7a$",
"^c_object_exe::@5ed5358f70faf8d8af7a$",
"^cxx_object_lib::@5ed5358f70faf8d8af7a$",
"^cxx_object_exe::@5ed5358f70faf8d8af7a$",
],
},
{
"name": "Imported",
"parentName": "codemodel-v2",
"childNames": None,
"directorySources": [
"^imported$",
],
"targetIds": [
"^ALL_BUILD::@ba7eb709d0b48779c6c8$",
"^ZERO_CHECK::@ba7eb709d0b48779c6c8$",
"^link_imported_exe::@ba7eb709d0b48779c6c8$",
"^link_imported_shared_exe::@ba7eb709d0b48779c6c8$",
"^link_imported_static_exe::@ba7eb709d0b48779c6c8$",
"^link_imported_object_exe::@ba7eb709d0b48779c6c8$",
"^link_imported_interface_exe::@ba7eb709d0b48779c6c8$",
],
},
{
"name": "Custom",
"parentName": "codemodel-v2",
"childNames": None,
"directorySources": [
"^custom$",
],
"targetIds": [
"^ALL_BUILD::@c11385ffed57b860da63$",
"^ZERO_CHECK::@c11385ffed57b860da63$",
"^custom_tgt::@c11385ffed57b860da63$",
"^custom_exe::@c11385ffed57b860da63$",
],
},
{
"name": "External",
"parentName": "codemodel-v2",
"childNames": None,
"directorySources": [
"^.*/Tests/RunCMake/FileAPIExternalSource$",
],
"targetIds": [
"^ALL_BUILD::@[0-9a-f]+$",
"^ZERO_CHECK::@[0-9a-f]+$",
"^generated_exe::@[0-9a-f]+$",
],
},
]
if matches(g, "^Visual Studio "):
for e in expected:
if e["parentName"] is not None:
e["targetIds"] = filter_list(lambda t: not matches(t, "^\\^ZERO_CHECK"), e["targetIds"])
elif g == "Xcode":
if ';' in os.environ.get("CMAKE_OSX_ARCHITECTURES", ""):
for e in expected:
e["targetIds"] = filter_list(lambda t: not matches(t, "^\\^(link_imported_object_exe)"), e["targetIds"])
else:
for e in expected:
e["targetIds"] = filter_list(lambda t: not matches(t, "^\\^(ALL_BUILD|ZERO_CHECK)"), e["targetIds"])
return expected
def check_projects(c, g):
check_list_match(lambda a, e: is_string(a["name"], e["name"]), c["projects"], gen_check_projects(c, g),
check=check_project(c),
check_exception=lambda a, e: "Project name: %s" % a["name"],
missing_exception=lambda e: "Project name: %s" % e["name"],
extra_exception=lambda a: "Project name: %s" % a["name"])
def check_object_codemodel_configuration(c, g, inSource):
assert sorted(c.keys()) == ["directories", "name", "projects", "targets"]
assert is_string(c["name"])
check_directories(c, g)
check_targets(c, g, inSource)
check_projects(c, g)
def check_object_codemodel(g):
def _check(o):
assert sorted(o.keys()) == ["configurations", "kind", "paths", "version"]
# The "kind" and "version" members are handled by check_index_object.
assert is_dict(o["paths"])
assert sorted(o["paths"].keys()) == ["build", "source"]
assert matches(o["paths"]["build"], "^.*/Tests/RunCMake/FileAPI/codemodel-v2-build$")
assert matches(o["paths"]["source"], "^.*/Tests/RunCMake/FileAPI$")
inSource = os.path.dirname(o["paths"]["build"]) == o["paths"]["source"]
if matches(g, "^(Visual Studio |Xcode$)"):
assert sorted([c["name"] for c in o["configurations"]]) == ["Debug", "MinSizeRel", "RelWithDebInfo", "Release"]
else:
assert len(o["configurations"]) == 1
assert o["configurations"][0]["name"] in ("", "Debug", "Release", "RelWithDebInfo", "MinSizeRel")
for c in o["configurations"]:
check_object_codemodel_configuration(c, g, inSource)
return _check
assert is_dict(index)
assert sorted(index.keys()) == ["cmake", "objects", "reply"]
check_objects(index["objects"], index["cmake"]["generator"]["name"])
| 37.260598
| 147
| 0.339845
| 10,587
| 190,737
| 6.01653
| 0.026259
| 0.039594
| 0.051776
| 0.041462
| 0.885379
| 0.859491
| 0.813618
| 0.78145
| 0.747837
| 0.732358
| 0
| 0.031366
| 0.523957
| 190,737
| 5,118
| 148
| 37.267878
| 0.670151
| 0.002889
| 0
| 0.652017
| 0
| 0.006823
| 0.299862
| 0.130782
| 0
| 0
| 0
| 0.000195
| 0.024684
| 1
| 0.005218
| false
| 0.000401
| 0.024283
| 0
| 0.030905
| 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
|
30bb6d5917ccba684ee986b5e2d492ed14f01ac9
| 9,841
|
py
|
Python
|
test/test_pytest_plugin.py
|
fjarri/grunnur
|
5eea8ec408e431f43a59780cdf8be2f441a9ebb5
|
[
"MIT"
] | 1
|
2020-12-04T12:19:18.000Z
|
2020-12-04T12:19:18.000Z
|
test/test_pytest_plugin.py
|
fjarri/grunnur
|
5eea8ec408e431f43a59780cdf8be2f441a9ebb5
|
[
"MIT"
] | 11
|
2021-03-11T00:20:23.000Z
|
2021-03-11T01:05:54.000Z
|
test/test_pytest_plugin.py
|
fjarri/grunnur
|
5eea8ec408e431f43a59780cdf8be2f441a9ebb5
|
[
"MIT"
] | null | null | null |
import pytest
from grunnur import API, Platform, Device, Context
def run_tests(options=[]):
pytest.main([
'-v',
'--no-cov',
'-m', 'plugin_inner_test'] + options)
@pytest.mark.plugin_inner_test
def test_api_fixture(api):
assert isinstance(api, API)
def test_api(mock_backend_factory, capsys):
backend_pycuda = mock_backend_factory.mock_pycuda()
backend_pycuda.add_devices(['Device1'])
backend_pyopencl = mock_backend_factory.mock_pyopencl()
backend_pyopencl.add_platform_with_devices('Bar', ['Device2'])
run_tests(['-k', 'test_api_fixture'])
captured = capsys.readouterr()
assert 'device(cuda,0,0): nVidia CUDA, Device1' in captured.out
assert 'device(opencl,0,0): Bar, Device2' in captured.out
assert '::test_api_fixture[api(cuda)]' in captured.out
assert '::test_api_fixture[api(opencl)]' in captured.out
run_tests(['--api=cuda', '-k', 'test_api_fixture'])
captured = capsys.readouterr()
assert 'device(cuda,0,0): nVidia CUDA, Device1' in captured.out
assert 'device(opencl,0,0): Bar, Device2' not in captured.out
assert '::test_api_fixture[api(cuda)]' in captured.out
assert '::test_api_fixture[api(opencl)]' not in captured.out
run_tests(['--api=opencl', '-k', 'test_api_fixture'])
captured = capsys.readouterr()
assert 'device(cuda,0,0): nVidia CUDA, Device1' not in captured.out
assert 'device(opencl,0,0): Bar, Device2' in captured.out
assert '::test_api_fixture[api(cuda)]' not in captured.out
assert '::test_api_fixture[api(opencl)]' in captured.out
def test_no_api(mock_backend_factory, capsys):
run_tests(['-k', 'test_api_fixture'])
captured = capsys.readouterr()
assert '::test_api_fixture[no_api]' in captured.out
@pytest.mark.plugin_inner_test
def test_platform_fixture(platform):
assert isinstance(platform, Platform)
def test_platform(mock_backend_factory, capsys):
backend_pyopencl = mock_backend_factory.mock_pyopencl()
backend_pyopencl.add_platform_with_devices('Foo', ['Device1'])
backend_pyopencl.add_platform_with_devices('Bar', ['Device2'])
run_tests(['-k', 'test_platform_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
assert 'device(opencl,1,0): Bar, Device2' in captured.out
assert '::test_platform_fixture[platform(opencl,0)]' in captured.out
assert '::test_platform_fixture[platform(opencl,1)]' in captured.out
run_tests(['--platform-include-mask=Bar', '-k', 'test_platform_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' not in captured.out
assert 'device(opencl,1,0): Bar, Device2' in captured.out
assert '::test_platform_fixture[platform(opencl,0)]' not in captured.out
assert '::test_platform_fixture[platform(opencl,1)]' in captured.out
run_tests(['--platform-exclude-mask=Bar', '-k', 'test_platform_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
assert 'device(opencl,1,0): Bar, Device2' not in captured.out
assert '::test_platform_fixture[platform(opencl,0)]' in captured.out
assert '::test_platform_fixture[platform(opencl,1)]' not in captured.out
def test_no_platform(mock_backend_factory, capsys):
run_tests(['-k', 'test_platform_fixture'])
captured = capsys.readouterr()
assert '::test_platform_fixture[no_platform]' in captured.out
@pytest.mark.plugin_inner_test
def test_device_fixture(device):
assert isinstance(device, Device)
def test_device(mock_backend_factory, capsys):
backend_pyopencl = mock_backend_factory.mock_pyopencl()
backend_pyopencl.add_platform_with_devices('Foo', ['Device1', 'Device2'])
backend_pyopencl.add_platform_with_devices('Bar', ['Device2', 'Device3'])
run_tests(['-k', 'test_device_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
assert 'device(opencl,0,1): Foo, Device2' in captured.out
assert 'device(opencl,1,0): Bar, Device2' in captured.out
assert 'device(opencl,1,1): Bar, Device3' in captured.out
assert '::test_device_fixture[device(opencl,0,0)]' in captured.out
assert '::test_device_fixture[device(opencl,0,1)]' in captured.out
assert '::test_device_fixture[device(opencl,1,0)]' in captured.out
assert '::test_device_fixture[device(opencl,1,1)]' in captured.out
run_tests(['--device-include-mask=Device2', '-k', 'test_device_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' not in captured.out
assert 'device(opencl,0,1): Foo, Device2' in captured.out
assert 'device(opencl,1,0): Bar, Device2' in captured.out
assert 'device(opencl,1,1): Bar, Device3' not in captured.out
assert '::test_device_fixture[device(opencl,0,0)]' not in captured.out
assert '::test_device_fixture[device(opencl,0,1)]' in captured.out
assert '::test_device_fixture[device(opencl,1,0)]' in captured.out
assert '::test_device_fixture[device(opencl,1,1)]' not in captured.out
run_tests(['--device-exclude-mask=Device2', '-k', 'test_device_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
assert 'device(opencl,0,1): Foo, Device2' not in captured.out
assert 'device(opencl,1,0): Bar, Device2' not in captured.out
assert 'device(opencl,1,1): Bar, Device3' in captured.out
assert '::test_device_fixture[device(opencl,0,0)]' in captured.out
assert '::test_device_fixture[device(opencl,0,1)]' not in captured.out
assert '::test_device_fixture[device(opencl,1,0)]' not in captured.out
assert '::test_device_fixture[device(opencl,1,1)]' in captured.out
def test_duplicate_devices(mock_backend_factory, capsys):
backend_pyopencl = mock_backend_factory.mock_pyopencl()
backend_pyopencl.add_platform_with_devices('Foo', ['Device1', 'Device1', 'Device2'])
run_tests(['-k', 'test_device_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
assert 'device(opencl,0,1): Foo, Device1' not in captured.out
assert 'device(opencl,0,2): Foo, Device2' in captured.out
assert '::test_device_fixture[device(opencl,0,0)]' in captured.out
assert '::test_device_fixture[device(opencl,0,1)]' not in captured.out
assert '::test_device_fixture[device(opencl,0,2)]' in captured.out
run_tests(['--include-duplicate-devices', '-k', 'test_device_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
assert 'device(opencl,0,1): Foo, Device1' in captured.out
assert 'device(opencl,0,2): Foo, Device2' in captured.out
assert '::test_device_fixture[device(opencl,0,0)]' in captured.out
assert '::test_device_fixture[device(opencl,0,1)]' in captured.out
assert '::test_device_fixture[device(opencl,0,2)]' in captured.out
def test_no_device(mock_backend_factory, capsys):
run_tests(['-k', 'test_device_fixture'])
captured = capsys.readouterr()
assert 'No GPGPU devices available' in captured.out
assert '::test_device_fixture[no_device]' in captured.out
@pytest.mark.plugin_inner_test
def test_context_fixture(context):
assert isinstance(context, Context)
assert len(context.devices) == 1
def test_context(mock_backend_factory, capsys):
backend_pyopencl = mock_backend_factory.mock_pyopencl()
backend_pyopencl.add_platform_with_devices('Foo', ['Device1', 'Device2'])
run_tests(['-k', 'test_context_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
assert 'device(opencl,0,1): Foo, Device2' in captured.out
assert '::test_context_fixture[opencl,0,0]' in captured.out
assert '::test_context_fixture[opencl,0,1]' in captured.out
run_tests(['--device-include-mask=Device1', '-k', 'test_context'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
assert 'device(opencl,0,1): Foo, Device2' not in captured.out
assert '::test_context_fixture[opencl,0,0]' in captured.out
assert '::test_context_fixture[opencl,0,1]' not in captured.out
def test_no_context(mock_backend_factory, capsys):
run_tests(['-k', 'test_context_fixture'])
captured = capsys.readouterr()
assert '::test_context_fixture[no_device]' in captured.out
@pytest.mark.plugin_inner_test
def test_multi_device_context_fixture(multi_device_context):
assert isinstance(multi_device_context, Context)
assert len(multi_device_context.devices) > 1
# FIXME: decide on the exact logic in this case.
def test_multi_device_context(mock_backend_factory, capsys):
backend_pyopencl = mock_backend_factory.mock_pyopencl()
# Two of the devices have the same names to check that they will be picked up
backend_pyopencl.add_platform_with_devices('Foo', ['Device1', 'Device1', 'Device3'])
run_tests(['-k', 'test_multi_device_context_fixture'])
captured = capsys.readouterr()
assert 'device(opencl,0,0): Foo, Device1' in captured.out
# Multi-device context does not currently include all the devices used to the list
assert 'device(opencl,0,1): Foo, Device1' not in captured.out
assert 'device(opencl,0,2): Foo, Device3' in captured.out
assert '::test_multi_device_context_fixture[opencl,0,0+opencl,0,1+opencl,0,2]' in captured.out
def test_no_multi_device_context(mock_backend_factory, capsys):
backend_pyopencl = mock_backend_factory.mock_pyopencl()
backend_pyopencl.add_platform_with_devices('Foo', ['Device1'])
run_tests(['-k', 'test_multi_device_context_fixture'])
captured = capsys.readouterr()
assert '::test_multi_device_context_fixture[no_multi_device]' in captured.out
| 44.130045
| 98
| 0.726654
| 1,398
| 9,841
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0
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30bf710321b58513a4ae07b37c83ae9a7b24a547
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|
py
|
Python
|
red.py
|
bitglass-dev/eos
|
ef08b720707cfcfdf867e4e9a95fc0b33d119fc7
|
[
"MIT"
] | null | null | null |
red.py
|
bitglass-dev/eos
|
ef08b720707cfcfdf867e4e9a95fc0b33d119fc7
|
[
"MIT"
] | null | null | null |
red.py
|
bitglass-dev/eos
|
ef08b720707cfcfdf867e4e9a95fc0b33d119fc7
|
[
"MIT"
] | null | null | null |
https://portal.us.bgd4.net/admin/apiSetup/?app=githubhttps://portal.us.bgd4.net/admin/apiSetup/?app=github
https://portal.us.bgd4.net/admin/apiSetup/?app=github
lana
red
yellow
black
blue
red
| 21.333333
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0
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30c029574a785059f17d5394529cfa302b543156
| 5,448
|
py
|
Python
|
Aplicacion_Sistema_Experto/Sitio_WEB/Modulo1.py
|
HenryHdez/Sistema_Experto
|
96bbb1f99af234e39d6cec7a7c4426b4b74679d1
|
[
"MIT"
] | null | null | null |
Aplicacion_Sistema_Experto/Sitio_WEB/Modulo1.py
|
HenryHdez/Sistema_Experto
|
96bbb1f99af234e39d6cec7a7c4426b4b74679d1
|
[
"MIT"
] | 25
|
2020-08-25T19:45:40.000Z
|
2020-08-26T16:39:59.000Z
|
Aplicacion_Sistema_Experto/Sitio_WEB/Modulo1.py
|
HenryHdez/SistemaExperto
|
c9279b0d91d26d117134fc071b0df9c492434a9a
|
[
"MIT"
] | null | null | null |
import math
from Modulo2 import *
ACO2 = 0
ACO = 0
AN2 = 0
AH2O = 0
AO2 = 0
A_prom=[]
i=0.0
H=0.0
Tin=0.0
Tout=0.0
yco2=0.0
yco=0.0
yn2=0.0
yh2o=0.0
yo2=0.0
R=0.0
Tprueba=0.0
Error=0.0
contador=0
def MMO2_KG_KMOL():
#As Double
c = 12.0107
O = 15.999
H = 1.00794
N = 14.0067
CO = c+O
CO2 = c+(2*O)
N2 = 2*N
O2 = 2*O
MMO2_KG_KMOL = O2
return MMO2_KG_KMOL
def MMCO2_KG_KMOL():
#As Double
c = 12.0107
O = 15.999
H = 1.00794
N = 14.0067
CO = c + O
CO2 = c + 2 * O
N2 = 2 * N
O2 = 2 * O
MMCO2_KG_KMOL = CO2
return MMCO2_KG_KMOL
def MMN2_KG_KMOL():
#As Double
c = 12.0107
O = 15.999
H = 1.00794
N = 14.0067
CO = c + O
CO2 = c + 2 * O
N2 = 2 * N
O2 = 2 * O
MMN2_KG_KMOL = N2
return MMN2_KG_KMOL
def MMCO_KG_KMOL():
#As Double
c = 12.0107
O = 15.999
H = 1.00794
N = 14.0067
CO = c + O
CO2 = c + 2 * O
N2 = 2 * N
O2 = 2 * O
MMCO_KG_KMOL = CO
return MMCO_KG_KMOL
def MMH2O_KG_KMOL():
#As Double
O = 15.999
H = 1.00794
H2O = (2*H)+O
MMH2O_KG_KMOL = H2O
return MMH2O_KG_KMOL
def MasaMolecular(yco, yco2 , yn2 , yo2 , yh2o ):
#As Double
c = 12.0107
O = 15.999
H = 1.00794
N = 14.0067
CO = c+O
CO2 = c+(2*O)
N2 = 2*N
O2 = 2*O
H2O = (2*H)+O
MasaMolecular = (yco*CO)+(yco2*CO2)+(yn2*N2)+(yo2*O2)+(yh2o*H2O)
return MasaMolecular
def Ho(T , yco , yco2 , yn2 , yo2 , yh2o ):
#As Double
if (T + 273.15 > 1000):
CO2 = [4.63659493, 0.00274131991, -0.000000995828531, 1.60373011E-10, -9.16103468E-15, -1696.827307, -1.93534855]
CO = [3.04848583, 0.00135172818, -0.000000485794075, 7.88536486E-11, -4.69807489E-15, -972.4894446, 6.0170979]
O2 = [3.66096083, 0.000656365523, -0.000000141149485, 2.06797658E-11, -1.29913248E-15, -1215.97725, 3.41536184]
N2 = [2.95257626, 0.00139690057, -0.000000492631691, 7.86010367E-11, -4.60755321E-15, -923.948645, 5.87189252]
H2O = [2.67703787, 0.00297318329, -0.00000077376969, 9.44336689E-11, -4.26900959E-15, -801.0769913, 6.88255571]
else:
CO2 = [2.35677352, 0.00898459677, -0.000007123556269, 2.45919022E-09, -1.43699548E-13, -1043.865014, 9.90105222]
CO = [3.57953347, -0.00061035368, 0.00000101681433, 9.07005884E-10, -9.04424499E-13, -1050.458397, 3.50840928]
O2 = [3.782456636, -0.00299673415, 0.000009847302, -9.68129508E-09, 3.24372836E-12, -1063.94356, 3.65767573]
N2 = [3.53100528, -0.000123660987, -0.000000502999437, 2.43530612E-09, -1.40881235E-12, -1046.97628, 2.96747468]
H2O = [4.19864056, -0.0020364341, 0.00000652040211, -5.48797062E-09, 1.77197817E-12, -1208.90995, -0.849032208]
A_prom=[]
for i in range(0,7):
A_prom.append((CO2[i] * yco2) + (CO[i] * yco) + (O2[i] * yo2) + (N2[i] * yn2) + (H2O[i] * yh2o))
# aPRUEBA = A_prom[i]
H = 0.0
for i in range(0,5):
H = H + (A_prom[i]*(((T+273.15)**(i + 1))/(i + 1)))
Ho = H + A_prom[6]
return Ho
def Cp(T , yco , yco2 , yn2 , yo2 , yh2o ):
#As Double
R = 8.314472 #'J/mol ªC - KJ/Kmol ªC
MM = MasaMolecular(yco, yco2, yn2, yo2, yh2o)
if (T + 273.15 > 1000):
CO2 = [4.63659493, 0.00274131991, -0.000000995828531, 1.60373011E-10, -9.16103468E-15, -1696.827307, -1.93534855]
CO = [3.04848583, 0.00135172818, -0.000000485794075, 7.88536486E-11, -4.69807489E-15, -972.4894446, 6.0170979]
O2 = [3.66096083, 0.000656365523, -0.000000141149485, 2.06797658E-11, -1.29913248E-15, -1215.97725, 3.41536184]
N2 = [2.95257626, 0.00139690057, -0.000000492631691, 7.86010367E-11, -4.60755321E-15, -923.948645, 5.87189252]
H2O = [2.67703787, 0.00297318329, -0.00000077376969, 9.44336689E-11, -4.26900959E-15, -801.0769913, 6.88255571]
else:
CO2 = [2.35677352, 0.00898459677, -0.000007123556269, 2.45919022E-09, -1.43699548E-13, -1043.865014, 9.90105222]
CO = [3.57953347, -0.00061035368, 0.00000101681433, 9.07005884E-10, -9.04424499E-13, -1050.458397, 3.50840928]
O2 = [3.782456636, -0.00299673415, 0.000009847302, -9.68129508E-09, 3.24372836E-12, -1063.94356, 3.65767573]
N2 = [3.53100528, -0.000123660987, -0.000000502999437, 2.43530612E-09, -1.40881235E-12, -1046.97628, 2.96747468]
H2O = [4.19864056, -0.0020364341, 0.00000652040211, -5.48797062E-09, 1.77197817E-12, -1208.90995, -0.849032208]
A_prom=[]
for i in range(0,6):
A_prom.append(CO2[i]*yco2 + CO[i]*yco + O2[i]*yo2 + N2[i]*yn2 + H2O[i]*yh2o)
Cpp = 0
for i in range(0,5):
Cpp = Cpp + (A_prom[i] * (((T + 273.15)**i)))
Cp = Cpp * R / MM
return Cp
def DH_KJKmol(Tin , Tout , yco , yco2 , yn2 , yo2 , yh2o ):
#As Double
R = 8.314472
DH_KJKmol = (Ho(Tout, yco, yco2, yn2, yo2, yh2o) - Ho(Tin, yco, yco2, yn2, yo2, yh2o)) * R
return DH_KJKmol
def DH_KJKg(Tin , Tout , yco , yco2 , yn2 , yo2 , yh2o ):
#As Double
R = 8.314472
MM = MasaMolecular(yco, yco2, yn2, yo2, yh2o)
DH_KJKg = DH_KJKmol(Tin, Tout, yco, yco2, yn2, yo2, yh2o) / MM
return DH_KJKmol
def Densidad_kgm3(yco , yco2 , yn2 , yo2 , yh2o , P , T ):
#As Double
MM = MasaMolecular(yco, yco2, yn2, yo2, yh2o)
R = 8.314472
Densidad_kgm3 = P * MM / (R * (T + 273.15))
return Densidad_kgm3
| 30.779661
| 121
| 0.582966
| 886
| 5,448
| 3.529345
| 0.191874
| 0.028782
| 0.038375
| 0.049888
| 0.801087
| 0.795651
| 0.774544
| 0.721138
| 0.712504
| 0.699712
| 0
| 0.473879
| 0.25514
| 5,448
| 177
| 122
| 30.779661
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| 0.026982
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| 0
| 0
| 0
| 0
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| 0
| 0
| 1
| 0.078014
| false
| 0
| 0.014184
| 0
| 0.170213
| 0
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| null | 0
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|
0
| 8
|
30f0f7337839fe57c7cc8825f6fbfb87b119e2b5
| 86,289
|
py
|
Python
|
maskrcnn_benchmark/modeling/roi_heads/relation_head/roi_relation_predictors.py
|
dongxingning/SHA_GCL_for_SGG
|
61c40befd84de32ff57271799aac4efedb5899a6
|
[
"MIT"
] | 5
|
2022-03-22T02:37:50.000Z
|
2022-03-28T03:23:24.000Z
|
maskrcnn_benchmark/modeling/roi_heads/relation_head/roi_relation_predictors.py
|
dongxingning/SHA_GCL_for_SGG
|
61c40befd84de32ff57271799aac4efedb5899a6
|
[
"MIT"
] | null | null | null |
maskrcnn_benchmark/modeling/roi_heads/relation_head/roi_relation_predictors.py
|
dongxingning/SHA_GCL_for_SGG
|
61c40befd84de32ff57271799aac4efedb5899a6
|
[
"MIT"
] | 2
|
2022-03-22T01:28:10.000Z
|
2022-03-28T13:26:25.000Z
|
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import os
import numpy as np
import torch
from maskrcnn_benchmark.modeling import registry
from torch import nn
from torch.nn import functional as F
from maskrcnn_benchmark.layers import smooth_l1_loss, kl_div_loss, entropy_loss, Label_Smoothing_Regression
from maskrcnn_benchmark.modeling.utils import cat
from .model_msg_passing import IMPContext
from .model_vtranse import VTransEFeature
from .model_vctree import VCTreeLSTMContext
from .model_motifs import LSTMContext, FrequencyBias
from .model_motifs_with_attribute import AttributeLSTMContext
from .model_transformer import TransformerContext
from SHA_GCL_extra.kl_divergence import KL_divergence
from .model_Hybrid_Attention import SHA_Context
from .model_Cross_Attention import CA_Context
from .utils_relation import layer_init
from maskrcnn_benchmark.data import get_dataset_statistics
from SHA_GCL_extra.utils_funcion import FrequencyBias_GCL
from SHA_GCL_extra.extra_function_utils import generate_num_stage_vector, generate_sample_rate_vector, \
generate_current_sequence_for_bias, get_current_predicate_idx
from SHA_GCL_extra.group_chosen_function import get_group_splits
import random
@registry.ROI_RELATION_PREDICTOR.register("TransLike_GCL")
class TransLike_GCL(nn.Module):
def __init__(self, config, in_channels):
super(TransLike_GCL, self).__init__()
# load parameters
self.config = config
if config.GLOBAL_SETTING.DATASET_CHOICE == 'VG':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.VG_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.VG_NUM_CLASSES
elif config.GLOBAL_SETTING.DATASET_CHOICE == 'GQA_200':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.GQA_200_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.GQA_200_NUM_CLASSES
assert in_channels is not None
num_inputs = in_channels
self.use_vision = config.MODEL.ROI_RELATION_HEAD.PREDICT_USE_VISION
self.use_bias = config.GLOBAL_SETTING.USE_BIAS
# load class dict
statistics = get_dataset_statistics(config)
obj_classes, rel_classes = statistics['obj_classes'], statistics['rel_classes']
assert self.num_obj_cls == len(obj_classes)
assert self.num_rel_cls == len(rel_classes)
self.obj_classes = obj_classes
self.rel_classes = rel_classes
self.in_channels = in_channels
# module construct
if config.GLOBAL_SETTING.BASIC_ENCODER == 'Self-Attention':
self.context_layer = TransformerContext(config, obj_classes, rel_classes, in_channels)
elif config.GLOBAL_SETTING.BASIC_ENCODER == 'Cross-Attention':
self.context_layer = CA_Context(config, obj_classes, rel_classes, in_channels)
elif config.GLOBAL_SETTING.BASIC_ENCODER == 'Hybrid-Attention':
self.context_layer = SHA_Context(config, obj_classes, rel_classes, in_channels)
# post decoding
self.hidden_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_HIDDEN_DIM
self.pooling_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_POOLING_DIM
self.post_emb = nn.Linear(self.hidden_dim, self.hidden_dim * 2)
self.post_cat = nn.Linear(self.hidden_dim * 2, self.pooling_dim)
# initialize layer parameters
layer_init(self.post_emb, 10.0 * (1.0 / self.hidden_dim) ** 0.5, normal=True)
layer_init(self.post_cat, xavier=True)
if self.pooling_dim != config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM:
self.union_single_not_match = True
self.up_dim = nn.Linear(config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM, self.pooling_dim)
layer_init(self.up_dim, xavier=True)
else:
self.union_single_not_match = False
# get model configs
self.Knowledge_Transfer_Mode = config.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_TRANSFER_MODE
self.no_relation_restrain = config.GLOBAL_SETTING.GCL_SETTING.NO_RELATION_RESTRAIN
self.zero_label_padding_mode = config.GLOBAL_SETTING.GCL_SETTING.ZERO_LABEL_PADDING_MODE
self.knowledge_loss_coefficient = config.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_LOSS_COEFFICIENT
# generate the auxiliary lists
self.group_split_mode = config.GLOBAL_SETTING.GCL_SETTING.GROUP_SPLIT_MODE
num_of_group_element_list, predicate_stage_count = get_group_splits(config.GLOBAL_SETTING.DATASET_CHOICE, self.group_split_mode)
self.max_group_element_number_list = generate_num_stage_vector(num_of_group_element_list)
self.incre_idx_list, self.max_elemnt_list, self.group_matrix, self.kd_matrix = get_current_predicate_idx(
num_of_group_element_list, 0.1, config.GLOBAL_SETTING.DATASET_CHOICE)
self.sample_rate_matrix = generate_sample_rate_vector(config.GLOBAL_SETTING.DATASET_CHOICE, self.max_group_element_number_list)
self.bias_for_group_split = generate_current_sequence_for_bias(num_of_group_element_list, config.GLOBAL_SETTING.DATASET_CHOICE)
self.num_groups = len(self.max_elemnt_list)
self.rel_compress_all, self.ctx_compress_all = self.generate_muti_networks(self.num_groups)
self.CE_loss = nn.CrossEntropyLoss()
if self.use_bias:
self.freq_bias_all = self.generate_multi_bias(config, statistics, self.num_groups)
if self.Knowledge_Transfer_Mode != 'None':
self.NLL_Loss = nn.NLLLoss()
self.pre_group_matrix = torch.tensor(self.group_matrix, dtype=torch.int64).cuda()
self.pre_kd_matrix = torch.tensor(self.kd_matrix, dtype=torch.float16).cuda()
self.criterion_loss = nn.CrossEntropyLoss()
def forward(self, proposals, rel_pair_idxs, rel_labels, rel_binarys, roi_features, union_features, logger=None):
add_losses = {}
obj_dists, obj_preds, edge_ctx = self.context_layer(roi_features, proposals, logger)
# post decode
edge_rep = self.post_emb(edge_ctx)
edge_rep = edge_rep.view(edge_rep.size(0), 2, self.hidden_dim)
head_rep = edge_rep[:, 0].contiguous().view(-1, self.hidden_dim)
tail_rep = edge_rep[:, 1].contiguous().view(-1, self.hidden_dim)
num_rels = [r.shape[0] for r in rel_pair_idxs]
num_objs = [len(b) for b in proposals]
assert len(num_rels) == len(num_objs)
head_reps = head_rep.split(num_objs, dim=0)
tail_reps = tail_rep.split(num_objs, dim=0)
obj_preds = obj_preds.split(num_objs, dim=0)
# from object level feature to pairwise relation level feature
prod_reps = []
pair_preds = []
for pair_idx, head_rep, tail_rep, obj_pred in zip(rel_pair_idxs, head_reps, tail_reps, obj_preds):
prod_reps.append(torch.cat((head_rep[pair_idx[:,0]], tail_rep[pair_idx[:,1]]), dim=-1))
pair_preds.append(torch.stack((obj_pred[pair_idx[:,0]], obj_pred[pair_idx[:,1]]), dim=1))
prod_rep = cat(prod_reps, dim=0)
pair_pred = cat(pair_preds, dim=0)
ctx_gate = self.post_cat(prod_rep)
# use union box and mask convolution
if self.union_single_not_match:
visual_rep = ctx_gate * self.up_dim(union_features)
else:
visual_rep = ctx_gate * union_features
if self.training:
if not self.config.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL:
fg_labels = cat([proposal.get_field("labels") for proposal in proposals], dim=0)
loss_refine_obj = self.criterion_loss(obj_dists, fg_labels.long())
add_losses['obj_loss'] = loss_refine_obj
rel_labels = cat(rel_labels, dim=0)
max_label = max(rel_labels)
num_groups = self.incre_idx_list[max_label.item()]
if num_groups == 0:
num_groups = max(self.incre_idx_list)
cur_chosen_matrix = []
for i in range(num_groups):
cur_chosen_matrix.append([])
for i in range(len(rel_labels)):
rel_tar = rel_labels[i].item()
if rel_tar == 0:
if self.zero_label_padding_mode == 'rand_insert':
random_idx = random.randint(0, num_groups - 1)
cur_chosen_matrix[random_idx].append(i)
elif self.zero_label_padding_mode == 'rand_choose' or self.zero_label_padding_mode == 'all_include':
if self.zero_label_padding_mode == 'rand_choose':
rand_zeros = random.random()
else:
rand_zeros = 1.0
if rand_zeros >= 0.4:
for zix in range(len(cur_chosen_matrix)):
cur_chosen_matrix[zix].append(i)
else:
rel_idx = self.incre_idx_list[rel_tar]
random_num = random.random()
for j in range(num_groups):
act_idx = num_groups - j
threshold_cur = self.sample_rate_matrix[act_idx - 1][rel_tar]
if random_num <= threshold_cur or act_idx < rel_idx:
# print('%d-%d-%d-%.2f-%.2f'%(i, rel_idx, act_idx, random_num, threshold_cur))
for k in range(act_idx):
cur_chosen_matrix[k].append(i)
break
for i in range(num_groups):
if max_label == 0:
group_visual = visual_rep
group_input = prod_rep
group_label = rel_labels
group_pairs = pair_pred
else:
group_visual = visual_rep[cur_chosen_matrix[i]]
group_input = prod_rep[cur_chosen_matrix[i]]
group_label = rel_labels[cur_chosen_matrix[i]]
group_pairs = pair_pred[cur_chosen_matrix[i]]
'''count Cross Entropy Loss'''
jdx = i
rel_compress_now = self.rel_compress_all[jdx]
ctx_compress_now = self.ctx_compress_all[jdx]
group_output_now = rel_compress_now(group_visual) + ctx_compress_now(group_input)
if self.use_bias:
rel_bias_now = self.freq_bias_all[jdx]
group_output_now = group_output_now + rel_bias_now.index_with_labels(group_pairs.long())
# actual_label_piece: if label is out of range, then filter it to ensure the training can continue
actual_label_now = self.pre_group_matrix[jdx][group_label]
add_losses['%d_CE_loss' % (jdx + 1)] = self.CE_loss(group_output_now, actual_label_now)
if self.Knowledge_Transfer_Mode == 'KL_logit_Neighbor':
if i > 0:
'''count knowledge transfer loss'''
jbef = i - 1
rel_compress_bef = self.rel_compress_all[jbef]
ctx_compress_bef = self.ctx_compress_all[jbef]
group_output_bef = rel_compress_bef(group_visual) + ctx_compress_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_vecify = kd_loss_matrix * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * kd_loss_matrix
add_losses['%d%d_kl_loss' % (jbef + 1, jdx + 1)] = kd_loss_final
elif self.Knowledge_Transfer_Mode == 'KL_logit_TopDown':
layer_total_loss = 0
for jbef in range(i):
rel_compress_bef = self.rel_compress_all[jbef]
ctx_compress_bef = self.ctx_compress_all[jbef]
group_output_bef = rel_compress_bef(group_visual) + ctx_compress_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_vecify = kd_loss_matrix * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * kd_loss_matrix
layer_total_loss += kd_loss_final
if i > 0:
add_losses['%d_DKS_loss' % (jdx + 1)] = layer_total_loss
elif self.Knowledge_Transfer_Mode == 'KL_logit_BiDirection':
layer_total_loss = 0
for jbef in range(i):
rel_compress_bef = self.rel_compress_all[jbef]
ctx_compress_bef = self.ctx_compress_all[jbef]
group_output_bef = rel_compress_bef(group_visual) + ctx_compress_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix_td = KL_divergence(group_output_bef[:, 1:],
group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_matrix_bu = KL_divergence(group_output_now[:, 1:max_vector],
group_output_bef[:, 1:],
reduce=False)
kd_loss_vecify = (kd_loss_matrix_td + kd_loss_matrix_bu) * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix_td = KL_divergence(group_output_bef[:, 1:],
group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_matrix_bu = KL_divergence(group_output_now[:, 1:max_vector],
group_output_bef[:, 1:],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * (kd_loss_matrix_td + kd_loss_matrix_bu)
layer_total_loss += kd_loss_final
if i > 0:
add_losses['%d_DKS_loss' % (jdx + 1)] = layer_total_loss
return None, None, add_losses
else:
rel_compress_test = self.rel_compress_all[-1]
ctx_compress_test = self.ctx_compress_all[-1]
rel_dists = rel_compress_test(visual_rep) + ctx_compress_test(prod_rep)
if self.use_bias:
rel_bias_test = self.freq_bias_all[-1]
rel_dists = rel_dists + rel_bias_test.index_with_labels(pair_pred.long())
rel_dists = rel_dists.split(num_rels, dim=0)
obj_dists = obj_dists.split(num_objs, dim=0)
return obj_dists, rel_dists, add_losses
def generate_muti_networks(self, num_cls):
'''generate all the hier-net in the model, need to set mannually if use new hier-class'''
self.rel_classifer_1 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[0] + 1)
self.rel_classifer_2 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[1] + 1)
self.rel_classifer_3 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[2] + 1)
self.rel_classifer_4 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[3] + 1)
self.rel_compress_1 = nn.Linear(self.hidden_dim * 2, self.max_group_element_number_list[0] + 1)
self.rel_compress_2 = nn.Linear(self.hidden_dim * 2, self.max_group_element_number_list[1] + 1)
self.rel_compress_3 = nn.Linear(self.hidden_dim * 2, self.max_group_element_number_list[2] + 1)
self.rel_compress_4 = nn.Linear(self.hidden_dim * 2, self.max_group_element_number_list[3] + 1)
layer_init(self.rel_classifer_1, xavier=True)
layer_init(self.rel_classifer_2, xavier=True)
layer_init(self.rel_classifer_3, xavier=True)
layer_init(self.rel_classifer_4, xavier=True)
layer_init(self.rel_compress_1, xavier=True)
layer_init(self.rel_compress_2, xavier=True)
layer_init(self.rel_compress_3, xavier=True)
layer_init(self.rel_compress_4, xavier=True)
if num_cls == 4:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3, self.rel_classifer_4]
compress_all = [self.rel_compress_1, self.rel_compress_2, self.rel_compress_3, self.rel_compress_4]
elif num_cls < 4:
exit('wrong num in compress_all')
else:
self.rel_classifer_5 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[4] + 1)
layer_init(self.rel_classifer_5, xavier=True)
self.rel_compress_5 = nn.Linear(self.hidden_dim * 2, self.max_group_element_number_list[4] + 1)
layer_init(self.rel_compress_5, xavier=True)
if num_cls == 5:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5]
compress_all = [self.rel_compress_1, self.rel_compress_2, self.rel_compress_3,
self.rel_compress_4, self.rel_compress_5]
else:
self.rel_classifer_6 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[5] + 1)
layer_init(self.rel_classifer_6, xavier=True)
self.rel_compress_6 = nn.Linear(self.hidden_dim * 2, self.max_group_element_number_list[5] + 1)
layer_init(self.rel_compress_6, xavier=True)
if num_cls == 6:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5, self.rel_classifer_6]
compress_all = [self.rel_compress_1, self.rel_compress_2, self.rel_compress_3,
self.rel_compress_4, self.rel_compress_5, self.rel_compress_6]
else:
self.rel_classifer_7 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[6] + 1)
layer_init(self.rel_classifer_7, xavier=True)
self.rel_compress_7 = nn.Linear(self.hidden_dim * 2, self.max_group_element_number_list[6] + 1)
layer_init(self.rel_compress_7, xavier=True)
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5, self.rel_classifer_6,
self.rel_classifer_7]
compress_all = [self.rel_compress_1, self.rel_compress_2, self.rel_compress_3,
self.rel_compress_4, self.rel_compress_5, self.rel_compress_6, self.rel_compress_7]
if num_cls > 7:
exit('wrong num in compress_all')
return classifer_all, compress_all
def generate_multi_bias(self, config, statistics, num_cls):
self.freq_bias_1 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[0])
self.freq_bias_2 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[1])
self.freq_bias_3 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[2])
self.freq_bias_4 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[3])
if num_cls < 4:
exit('wrong num in multi_bias')
elif num_cls == 4:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3, self.freq_bias_4]
else:
self.freq_bias_5 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[4])
if num_cls == 5:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3, self.freq_bias_4,
self.freq_bias_5]
else:
self.freq_bias_6 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE,
predicate_all_list=self.bias_for_group_split[5])
if num_cls == 6:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3,
self.freq_bias_4, self.freq_bias_5, self.freq_bias_6]
else:
self.freq_bias_7 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE,
predicate_all_list=self.bias_for_group_split[6])
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3,
self.freq_bias_4, self.freq_bias_5, self.freq_bias_6, self.freq_bias_7]
if num_cls > 7:
exit('wrong num in multi_bias')
return freq_bias_all
@registry.ROI_RELATION_PREDICTOR.register("MotifsLikePredictor")
class MotifsLikePredictor(nn.Module):
def __init__(self, config, in_channels):
super(MotifsLikePredictor, self).__init__()
self.config = config
if config.GLOBAL_SETTING.DATASET_CHOICE == 'VG':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.VG_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.VG_NUM_CLASSES
elif config.GLOBAL_SETTING.DATASET_CHOICE == 'GQA_200':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.GQA_200_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.GQA_200_NUM_CLASSES
assert in_channels is not None
num_inputs = in_channels
self.use_vision = config.MODEL.ROI_RELATION_HEAD.PREDICT_USE_VISION
self.use_bias = config.GLOBAL_SETTING.USE_BIAS
# load class dict
statistics = get_dataset_statistics(config)
obj_classes, rel_classes = statistics['obj_classes'], statistics['rel_classes']
assert self.num_obj_cls == len(obj_classes)
assert self.num_rel_cls == len(rel_classes)
# init contextual lstm encoding
if config.GLOBAL_SETTING.BASIC_ENCODER == 'Motifs':
self.context_layer = LSTMContext(config, obj_classes, rel_classes, in_channels)
elif config.GLOBAL_SETTING.BASIC_ENCODER == 'VTransE':
self.context_layer = VTransEFeature(config, obj_classes, rel_classes, in_channels)
else:
exit('wrong mode!')
# post decoding
self.hidden_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_HIDDEN_DIM
self.pooling_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_POOLING_DIM
self.post_emb = nn.Linear(self.hidden_dim, self.hidden_dim * 2)
self.post_cat = nn.Linear(self.hidden_dim * 2, self.pooling_dim)
self.rel_compress = nn.Linear(self.pooling_dim, self.num_rel_cls, bias=True)
# initialize layer parameters
layer_init(self.post_emb, 10.0 * (1.0 / self.hidden_dim) ** 0.5, normal=True)
layer_init(self.post_cat, xavier=True)
layer_init(self.rel_compress, xavier=True)
if self.pooling_dim != config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM:
self.union_single_not_match = True
self.up_dim = nn.Linear(config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM, self.pooling_dim)
layer_init(self.up_dim, xavier=True)
else:
self.union_single_not_match = False
if self.use_bias:
# convey statistics into FrequencyBias to avoid loading again
self.freq_bias = FrequencyBias(config, statistics)
self.criterion_loss = nn.CrossEntropyLoss()
def forward(self, proposals, rel_pair_idxs, rel_labels, rel_binarys, roi_features, union_features, logger=None):
"""
Returns:
obj_dists (list[Tensor]): logits of object label distribution
rel_dists (list[Tensor])
rel_pair_idxs (list[Tensor]): (num_rel, 2) index of subject and object
union_features (Tensor): (batch_num_rel, context_pooling_dim): visual union feature of each pair
"""
# encode context infomation
obj_dists, obj_preds, edge_ctx, _ = self.context_layer(roi_features, proposals, logger)
# post decode
edge_rep = self.post_emb(edge_ctx)
edge_rep = edge_rep.view(edge_rep.size(0), 2, self.hidden_dim)
head_rep = edge_rep[:, 0].contiguous().view(-1, self.hidden_dim)
tail_rep = edge_rep[:, 1].contiguous().view(-1, self.hidden_dim)
num_rels = [r.shape[0] for r in rel_pair_idxs]
num_objs = [len(b) for b in proposals]
assert len(num_rels) == len(num_objs)
head_reps = head_rep.split(num_objs, dim=0)
tail_reps = tail_rep.split(num_objs, dim=0)
obj_preds = obj_preds.split(num_objs, dim=0)
prod_reps = []
pair_preds = []
for pair_idx, head_rep, tail_rep, obj_pred in zip(rel_pair_idxs, head_reps, tail_reps, obj_preds):
prod_reps.append( torch.cat((head_rep[pair_idx[:,0]], tail_rep[pair_idx[:,1]]), dim=-1) )
pair_preds.append( torch.stack((obj_pred[pair_idx[:,0]], obj_pred[pair_idx[:,1]]), dim=1) )
prod_rep = cat(prod_reps, dim=0)
pair_pred = cat(pair_preds, dim=0)
prod_rep = self.post_cat(prod_rep)
if self.use_vision:
if self.union_single_not_match:
prod_rep = prod_rep * self.up_dim(union_features)
else:
prod_rep = prod_rep * union_features
rel_dists = self.rel_compress(prod_rep)
if self.use_bias:
rel_dists = rel_dists + self.freq_bias.index_with_labels(pair_pred.long())
add_losses = {}
if self.training:
if not self.config.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL:
fg_labels = cat([proposal.get_field("labels") for proposal in proposals], dim=0)
loss_refine_obj = self.criterion_loss(obj_dists, fg_labels.long())
add_losses['obj_loss'] = loss_refine_obj
rel_labels = cat(rel_labels, dim=0)
add_losses['rel_loss'] = self.criterion_loss(rel_dists, rel_labels)
return None, None, add_losses
else:
obj_dists = obj_dists.split(num_objs, dim=0)
rel_dists = rel_dists.split(num_rels, dim=0)
return obj_dists, rel_dists, add_losses
@registry.ROI_RELATION_PREDICTOR.register("VCTreePredictor")
class VCTreePredictor(nn.Module):
def __init__(self, config, in_channels):
super(VCTreePredictor, self).__init__()
self.config = config
if config.GLOBAL_SETTING.DATASET_CHOICE == 'VG':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.VG_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.VG_NUM_CLASSES
elif config.GLOBAL_SETTING.DATASET_CHOICE == 'GQA_200':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.GQA_200_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.GQA_200_NUM_CLASSES
assert in_channels is not None
num_inputs = in_channels
# load class dict
statistics = get_dataset_statistics(config)
obj_classes, rel_classes = statistics['obj_classes'], statistics['rel_classes']
assert self.num_obj_cls == len(obj_classes)
assert self.num_rel_cls == len(rel_classes)
# init contextual lstm encoding
self.context_layer = VCTreeLSTMContext(config, obj_classes, rel_classes, statistics, in_channels)
# post decoding
self.hidden_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_HIDDEN_DIM
self.pooling_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_POOLING_DIM
self.post_emb = nn.Linear(self.hidden_dim, self.hidden_dim * 2)
self.post_cat = nn.Linear(self.hidden_dim * 2, self.pooling_dim)
# learned-mixin
#self.uni_gate = nn.Linear(self.pooling_dim, self.num_rel_cls)
#self.frq_gate = nn.Linear(self.pooling_dim, self.num_rel_cls)
self.ctx_compress = nn.Linear(self.pooling_dim, self.num_rel_cls)
#self.uni_compress = nn.Linear(self.pooling_dim, self.num_rel_cls)
#layer_init(self.uni_gate, xavier=True)
#layer_init(self.frq_gate, xavier=True)
layer_init(self.ctx_compress, xavier=True)
#layer_init(self.uni_compress, xavier=True)
# initialize layer parameters
layer_init(self.post_emb, 10.0 * (1.0 / self.hidden_dim) ** 0.5, normal=True)
layer_init(self.post_cat, xavier=True)
if self.pooling_dim != config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM:
self.union_single_not_match = True
self.up_dim = nn.Linear(config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM, self.pooling_dim)
layer_init(self.up_dim, xavier=True)
else:
self.union_single_not_match = False
self.freq_bias = FrequencyBias(config, statistics)
self.criterion_loss = nn.CrossEntropyLoss()
def forward(self, proposals, rel_pair_idxs, rel_labels, rel_binarys, roi_features, union_features, logger=None):
"""
Returns:
obj_dists (list[Tensor]): logits of object label distribution
rel_dists (list[Tensor])
rel_pair_idxs (list[Tensor]): (num_rel, 2) index of subject and object
union_features (Tensor): (batch_num_rel, context_pooling_dim): visual union feature of each pair
"""
# encode context infomation
obj_dists, obj_preds, edge_ctx, binary_preds = self.context_layer(roi_features, proposals, rel_pair_idxs, logger)
# post decode
edge_rep = F.relu(self.post_emb(edge_ctx))
edge_rep = edge_rep.view(edge_rep.size(0), 2, self.hidden_dim)
head_rep = edge_rep[:, 0].contiguous().view(-1, self.hidden_dim)
tail_rep = edge_rep[:, 1].contiguous().view(-1, self.hidden_dim)
num_rels = [r.shape[0] for r in rel_pair_idxs]
num_objs = [len(b) for b in proposals]
assert len(num_rels) == len(num_objs)
head_reps = head_rep.split(num_objs, dim=0)
tail_reps = tail_rep.split(num_objs, dim=0)
obj_preds = obj_preds.split(num_objs, dim=0)
prod_reps = []
pair_preds = []
for pair_idx, head_rep, tail_rep, obj_pred in zip(rel_pair_idxs, head_reps, tail_reps, obj_preds):
prod_reps.append( torch.cat((head_rep[pair_idx[:,0]], tail_rep[pair_idx[:,1]]), dim=-1) )
pair_preds.append( torch.stack((obj_pred[pair_idx[:,0]], obj_pred[pair_idx[:,1]]), dim=1) )
prod_rep = cat(prod_reps, dim=0)
pair_pred = cat(pair_preds, dim=0)
prod_rep = self.post_cat(prod_rep)
# learned-mixin Gate
#uni_gate = torch.tanh(self.uni_gate(self.drop(prod_rep)))
#frq_gate = torch.tanh(self.frq_gate(self.drop(prod_rep)))
if self.union_single_not_match:
union_features = self.up_dim(union_features)
ctx_dists = self.ctx_compress(prod_rep * union_features)
#uni_dists = self.uni_compress(self.drop(union_features))
frq_dists = self.freq_bias.index_with_labels(pair_pred.long())
rel_dists = ctx_dists + frq_dists
#rel_dists = ctx_dists + uni_gate * uni_dists + frq_gate * frq_dists
add_losses = {}
if self.training:
binary_loss = []
for bi_gt, bi_pred in zip(rel_binarys, binary_preds):
bi_gt = (bi_gt > 0).float()
binary_loss.append(F.binary_cross_entropy_with_logits(bi_pred, bi_gt))
add_losses["binary_loss"] = sum(binary_loss) / len(binary_loss)
if not self.config.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL:
fg_labels = cat([proposal.get_field("labels") for proposal in proposals], dim=0)
loss_refine_obj = self.criterion_loss(obj_dists, fg_labels.long())
add_losses['obj_loss'] = loss_refine_obj
rel_labels = cat(rel_labels, dim=0)
add_losses['rel_loss'] = self.criterion_loss(rel_dists, rel_labels)
return None, None, add_losses
else:
obj_dists = obj_dists.split(num_objs, dim=0)
rel_dists = rel_dists.split(num_rels, dim=0)
return obj_dists, rel_dists, add_losses
@registry.ROI_RELATION_PREDICTOR.register("MotifsLike_GCL")
class MotifsLike_GCL(nn.Module):
def __init__(self, config, in_channels):
super(MotifsLike_GCL, self).__init__()
self.config = config
if config.GLOBAL_SETTING.DATASET_CHOICE == 'VG':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.VG_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.VG_NUM_CLASSES
elif config.GLOBAL_SETTING.DATASET_CHOICE == 'GQA_200':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.GQA_200_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.GQA_200_NUM_CLASSES
assert in_channels is not None
num_inputs = in_channels
self.use_vision = config.MODEL.ROI_RELATION_HEAD.PREDICT_USE_VISION
self.use_bias = config.GLOBAL_SETTING.USE_BIAS
# load class dict
statistics = get_dataset_statistics(config)
obj_classes, rel_classes = statistics['obj_classes'], statistics['rel_classes']
assert self.num_obj_cls==len(obj_classes)
assert self.num_rel_cls==len(rel_classes)
# init contextual lstm encoding
if config.GLOBAL_SETTING.BASIC_ENCODER == 'Motifs':
self.context_layer = LSTMContext(config, obj_classes, rel_classes, in_channels)
elif config.GLOBAL_SETTING.BASIC_ENCODER == 'VTransE':
self.context_layer = VTransEFeature(config, obj_classes, rel_classes, in_channels)
else:
exit('wrong mode!')
# post decoding
self.hidden_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_HIDDEN_DIM
self.pooling_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_POOLING_DIM
self.post_emb = nn.Linear(self.hidden_dim, self.hidden_dim * 2)
self.post_cat = nn.Linear(self.hidden_dim * 2, self.pooling_dim)
# initialize layer parameters
layer_init(self.post_emb, 10.0 * (1.0 / self.hidden_dim) ** 0.5, normal=True)
layer_init(self.post_cat, xavier=True)
if self.pooling_dim != config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM:
self.union_single_not_match = True
self.up_dim = nn.Linear(config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM, self.pooling_dim)
layer_init(self.up_dim, xavier=True)
else:
self.union_single_not_match = False
# get model configs
self.Knowledge_Transfer_Mode = config.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_TRANSFER_MODE
self.no_relation_restrain = config.GLOBAL_SETTING.GCL_SETTING.NO_RELATION_RESTRAIN
self.zero_label_padding_mode = config.GLOBAL_SETTING.GCL_SETTING.ZERO_LABEL_PADDING_MODE
self.knowledge_loss_coefficient = config.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_LOSS_COEFFICIENT
# generate the auxiliary lists
self.group_split_mode = config.GLOBAL_SETTING.GCL_SETTING.GROUP_SPLIT_MODE
num_of_group_element_list, predicate_stage_count = get_group_splits(config.GLOBAL_SETTING.DATASET_CHOICE, self.group_split_mode)
self.max_group_element_number_list = generate_num_stage_vector(num_of_group_element_list)
self.incre_idx_list, self.max_elemnt_list, self.group_matrix, self.kd_matrix = get_current_predicate_idx(
num_of_group_element_list, 0.1, config.GLOBAL_SETTING.DATASET_CHOICE)
self.sample_rate_matrix = generate_sample_rate_vector(config.GLOBAL_SETTING.DATASET_CHOICE, self.max_group_element_number_list)
self.bias_for_group_split = generate_current_sequence_for_bias(num_of_group_element_list, config.GLOBAL_SETTING.DATASET_CHOICE)
self.num_groups = len(self.max_elemnt_list)
self.rel_classifer_all = self.generate_muti_networks(self.num_groups)
self.CE_loss = nn.CrossEntropyLoss()
if self.use_bias:
self.freq_bias_all = self.generate_multi_bias(config, statistics, self.num_groups)
if self.Knowledge_Transfer_Mode != 'None':
self.NLL_Loss = nn.NLLLoss()
self.pre_group_matrix = torch.tensor(self.group_matrix, dtype=torch.int64).cuda()
self.pre_kd_matrix = torch.tensor(self.kd_matrix, dtype=torch.float16).cuda()
self.criterion_loss = nn.CrossEntropyLoss()
'''
torch.int64
torch.float16
'''
def forward(self, proposals, rel_pair_idxs, rel_labels, rel_binarys, roi_features, union_features, logger=None):
"""
Returns:
obj_dists (list[Tensor]): logits of object label distribution
rel_dists (list[Tensor])
rel_pair_idxs (list[Tensor]): (num_rel, 2) index of subject and object
union_features (Tensor): (batch_num_rel, context_pooling_dim): visual union feature of each pair
"""
# encode context infomation
obj_dists, obj_preds, edge_ctx, _ = self.context_layer(roi_features, proposals, logger)
# post decode
edge_rep = self.post_emb(edge_ctx)
edge_rep = edge_rep.view(edge_rep.size(0), 2, self.hidden_dim)
head_rep = edge_rep[:, 0].contiguous().view(-1, self.hidden_dim)
tail_rep = edge_rep[:, 1].contiguous().view(-1, self.hidden_dim)
num_rels = [r.shape[0] for r in rel_pair_idxs]
num_objs = [len(b) for b in proposals]
assert len(num_rels) == len(num_objs)
head_reps = head_rep.split(num_objs, dim=0)
tail_reps = tail_rep.split(num_objs, dim=0)
obj_preds = obj_preds.split(num_objs, dim=0)
prod_reps = []
pair_preds = []
for pair_idx, head_rep, tail_rep, obj_pred in zip(rel_pair_idxs, head_reps, tail_reps, obj_preds):
prod_reps.append(torch.cat((head_rep[pair_idx[:, 0]], tail_rep[pair_idx[:, 1]]), dim=-1))
pair_preds.append(torch.stack((obj_pred[pair_idx[:, 0]], obj_pred[pair_idx[:, 1]]), dim=1))
prod_rep = cat(prod_reps, dim=0)
pair_pred = cat(pair_preds, dim=0)
prod_rep = self.post_cat(prod_rep)
if self.use_vision:
if self.union_single_not_match:
prod_rep = prod_rep * self.up_dim(union_features)
else:
prod_rep = prod_rep * union_features
'''begin to change'''
add_losses = {}
if self.training:
if not self.config.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL:
fg_labels = cat([proposal.get_field("labels") for proposal in proposals], dim=0)
loss_refine_obj = self.criterion_loss(obj_dists, fg_labels.long())
add_losses['obj_loss'] = loss_refine_obj
rel_labels = cat(rel_labels, dim=0)
max_label = max(rel_labels)
num_groups = self.incre_idx_list[max_label.item()]
if num_groups == 0:
num_groups = max(self.incre_idx_list)
cur_chosen_matrix = []
for i in range(num_groups):
cur_chosen_matrix.append([])
for i in range(len(rel_labels)):
rel_tar = rel_labels[i].item()
if rel_tar == 0:
if self.zero_label_padding_mode == 'rand_insert':
random_idx = random.randint(0, num_groups - 1)
cur_chosen_matrix[random_idx].append(i)
elif self.zero_label_padding_mode == 'rand_choose' or self.zero_label_padding_mode == 'all_include':
if self.zero_label_padding_mode == 'rand_choose':
rand_zeros = random.random()
else:
rand_zeros = 1.0
if rand_zeros >= 0.4:
for zix in range(len(cur_chosen_matrix)):
cur_chosen_matrix[zix].append(i)
else:
rel_idx = self.incre_idx_list[rel_tar]
random_num = random.random()
for j in range(num_groups):
act_idx = num_groups - j
threshold_cur = self.sample_rate_matrix[act_idx - 1][rel_tar]
if random_num <= threshold_cur or act_idx < rel_idx:
# print('%d-%d-%d-%.2f-%.2f'%(i, rel_idx, act_idx, random_num, threshold_cur))
for k in range(act_idx):
cur_chosen_matrix[k].append(i)
break
for i in range(num_groups):
if max_label == 0:
group_input = prod_rep
group_label = rel_labels
group_pairs = pair_pred
else:
group_input = prod_rep[cur_chosen_matrix[i]]
group_label = rel_labels[cur_chosen_matrix[i]]
group_pairs = pair_pred[cur_chosen_matrix[i]]
'''count Cross Entropy loss'''
jdx = i
rel_classier_now = self.rel_classifer_all[jdx]
group_output_now = rel_classier_now(group_input)
if self.use_bias:
rel_bias_now = self.freq_bias_all[jdx]
group_output_now = group_output_now + rel_bias_now.index_with_labels(group_pairs.long())
# actual_label_piece: if label is out of range, then filter it to ensure the training can continue
actual_label_now = self.pre_group_matrix[jdx][group_label]
add_losses['%d_CE_loss' % (jdx + 1)] = self.CE_loss(group_output_now, actual_label_now)
if self.Knowledge_Transfer_Mode == 'KL_logit_Neighbor':
if i > 0:
'''count knowledge transfer loss'''
jbef = i - 1
rel_classier_bef = self.rel_classifer_all[jbef]
group_output_bef = rel_classier_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_vecify = kd_loss_matrix * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * kd_loss_matrix
add_losses['%d%d_kl_loss' % (jbef + 1, jdx + 1)] = kd_loss_final
elif self.Knowledge_Transfer_Mode == 'KL_logit_TopDown':
layer_total_loss = 0
for jbef in range(i):
rel_classier_bef = self.rel_classifer_all[jbef]
group_output_bef = rel_classier_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
# kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_vecify = kd_loss_matrix * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * kd_loss_matrix
layer_total_loss += kd_loss_final
if i > 0:
add_losses['%d_DKS_loss' % (jdx + 1)] = layer_total_loss
elif self.Knowledge_Transfer_Mode == 'KL_logit_BiDirection':
layer_total_loss = 0
for jbef in range(i):
rel_classier_bef = self.rel_classifer_all[jbef]
group_output_bef = rel_classier_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
# kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix_td = KL_divergence(group_output_bef[:, 1:],
group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_matrix_bu = KL_divergence(group_output_now[:, 1:max_vector],
group_output_bef[:, 1:],
reduce=False)
kd_loss_vecify = (kd_loss_matrix_td + kd_loss_matrix_bu) * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix_td = KL_divergence(group_output_bef[:, 1:],
group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_matrix_bu = KL_divergence(group_output_now[:, 1:max_vector],
group_output_bef[:, 1:],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * (kd_loss_matrix_td + kd_loss_matrix_bu)
layer_total_loss += kd_loss_final
if i > 0:
add_losses['%d_DKS_loss' % (jdx + 1)] = layer_total_loss
return None, None, add_losses
else:
rel_classier_test = self.rel_classifer_all[-1]
rel_dists = rel_classier_test(prod_rep)
if self.use_bias:
rel_bias_test = self.freq_bias_all[-1]
rel_dists = rel_dists + rel_bias_test.index_with_labels(pair_pred.long())
rel_dists = rel_dists.split(num_rels, dim=0)
obj_dists = obj_dists.split(num_objs, dim=0)
return obj_dists, rel_dists, add_losses
def generate_muti_networks(self, num_cls):
'''generate all the hier-net in the model, need to set mannually if use new hier-class'''
self.rel_classifer_1 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[0] + 1)
self.rel_classifer_2 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[1] + 1)
self.rel_classifer_3 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[2] + 1)
self.rel_classifer_4 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[3] + 1)
layer_init(self.rel_classifer_1, xavier=True)
layer_init(self.rel_classifer_2, xavier=True)
layer_init(self.rel_classifer_3, xavier=True)
layer_init(self.rel_classifer_4, xavier=True)
if num_cls == 4:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3, self.rel_classifer_4]
elif num_cls < 4:
exit('wrong num in compress_all')
else:
self.rel_classifer_5 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[4] + 1)
layer_init(self.rel_classifer_5, xavier=True)
if num_cls == 5:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5]
else:
self.rel_classifer_6 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[5] + 1)
layer_init(self.rel_classifer_6, xavier=True)
if num_cls == 6:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5, self.rel_classifer_6]
else:
self.rel_classifer_7 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[6] + 1)
layer_init(self.rel_classifer_7, xavier=True)
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5, self.rel_classifer_6,
self.rel_classifer_7]
if num_cls > 7:
exit('wrong num in compress_all')
return classifer_all
def generate_multi_bias(self, config, statistics, num_cls):
self.freq_bias_1 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[0])
self.freq_bias_2 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[1])
self.freq_bias_3 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[2])
self.freq_bias_4 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[3])
if num_cls < 4:
exit('wrong num in multi_bias')
elif num_cls == 4:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3, self.freq_bias_4]
else:
self.freq_bias_5 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[4])
if num_cls == 5:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3, self.freq_bias_4,
self.freq_bias_5]
else:
self.freq_bias_6 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE,
predicate_all_list=self.bias_for_group_split[5])
if num_cls == 6:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3,
self.freq_bias_4, self.freq_bias_5, self.freq_bias_6]
else:
self.freq_bias_7 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE,
predicate_all_list=self.bias_for_group_split[6])
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3,
self.freq_bias_4, self.freq_bias_5, self.freq_bias_6, self.freq_bias_7]
if num_cls > 7:
exit('wrong num in multi_bias')
return freq_bias_all
@registry.ROI_RELATION_PREDICTOR.register("VCTree_GCL")
class VCTree_GCL(nn.Module):
def __init__(self, config, in_channels):
super(VCTree_GCL, self).__init__()
self.config = config
if config.GLOBAL_SETTING.DATASET_CHOICE == 'VG':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.VG_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.VG_NUM_CLASSES
elif config.GLOBAL_SETTING.DATASET_CHOICE == 'GQA_200':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.GQA_200_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.GQA_200_NUM_CLASSES
assert in_channels is not None
num_inputs = in_channels
self.use_bias = config.GLOBAL_SETTING.USE_BIAS
# load class dict
statistics = get_dataset_statistics(config)
obj_classes, rel_classes = statistics['obj_classes'], statistics['rel_classes']
assert self.num_obj_cls == len(obj_classes)
assert self.num_rel_cls == len(rel_classes)
# init contextual lstm encoding
self.context_layer = VCTreeLSTMContext(config, obj_classes, rel_classes, statistics, in_channels)
# post decoding
self.hidden_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_HIDDEN_DIM
self.pooling_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_POOLING_DIM
self.post_emb = nn.Linear(self.hidden_dim, self.hidden_dim * 2)
self.post_cat = nn.Linear(self.hidden_dim * 2, self.pooling_dim)
# initialize layer parameters
layer_init(self.post_emb, 10.0 * (1.0 / self.hidden_dim) ** 0.5, normal=True)
layer_init(self.post_cat, xavier=True)
if self.pooling_dim != config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM:
self.union_single_not_match = True
self.up_dim = nn.Linear(config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM, self.pooling_dim)
layer_init(self.up_dim, xavier=True)
else:
self.union_single_not_match = False
# get model configs
self.Knowledge_Transfer_Mode = config.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_TRANSFER_MODE
self.no_relation_restrain = config.GLOBAL_SETTING.GCL_SETTING.NO_RELATION_RESTRAIN
self.zero_label_padding_mode = config.GLOBAL_SETTING.GCL_SETTING.ZERO_LABEL_PADDING_MODE
self.knowledge_loss_coefficient = config.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_LOSS_COEFFICIENT
# generate the auxiliary lists
self.group_split_mode = config.GLOBAL_SETTING.GCL_SETTING.GROUP_SPLIT_MODE
num_of_group_element_list, predicate_stage_count = get_group_splits(config.GLOBAL_SETTING.DATASET_CHOICE, self.group_split_mode)
self.max_group_element_number_list = generate_num_stage_vector(num_of_group_element_list)
self.incre_idx_list, self.max_elemnt_list, self.group_matrix, self.kd_matrix = get_current_predicate_idx(
num_of_group_element_list, 0.1, config.GLOBAL_SETTING.DATASET_CHOICE)
self.sample_rate_matrix = generate_sample_rate_vector(config.GLOBAL_SETTING.DATASET_CHOICE, self.max_group_element_number_list)
self.bias_for_group_split = generate_current_sequence_for_bias(num_of_group_element_list, config.GLOBAL_SETTING.DATASET_CHOICE)
self.num_groups = len(self.max_elemnt_list)
self.rel_classifer_all = self.generate_muti_networks(self.num_groups)
self.CE_loss = nn.CrossEntropyLoss()
if self.use_bias:
self.freq_bias_all = self.generate_multi_bias(config, statistics, self.num_groups)
if self.Knowledge_Transfer_Mode != 'None':
self.NLL_Loss = nn.NLLLoss()
self.pre_group_matrix = torch.tensor(self.group_matrix, dtype=torch.int64).cuda()
self.pre_kd_matrix = torch.tensor(self.kd_matrix, dtype=torch.float16).cuda()
self.criterion_loss = nn.CrossEntropyLoss()
def forward(self, proposals, rel_pair_idxs, rel_labels, rel_binarys, roi_features, union_features, logger=None):
"""
Returns:
obj_dists (list[Tensor]): logits of object label distribution
rel_dists (list[Tensor])
rel_pair_idxs (list[Tensor]): (num_rel, 2) index of subject and object
union_features (Tensor): (batch_num_rel, context_pooling_dim): visual union feature of each pair
"""
# encode context infomation
obj_dists, obj_preds, edge_ctx, binary_preds = self.context_layer(roi_features, proposals, rel_pair_idxs, logger)
# post decode
edge_rep = F.relu(self.post_emb(edge_ctx))
edge_rep = edge_rep.view(edge_rep.size(0), 2, self.hidden_dim)
head_rep = edge_rep[:, 0].contiguous().view(-1, self.hidden_dim)
tail_rep = edge_rep[:, 1].contiguous().view(-1, self.hidden_dim)
num_rels = [r.shape[0] for r in rel_pair_idxs]
num_objs = [len(b) for b in proposals]
assert len(num_rels) == len(num_objs)
head_reps = head_rep.split(num_objs, dim=0)
tail_reps = tail_rep.split(num_objs, dim=0)
obj_preds = obj_preds.split(num_objs, dim=0)
prod_reps = []
pair_preds = []
for pair_idx, head_rep, tail_rep, obj_pred in zip(rel_pair_idxs, head_reps, tail_reps, obj_preds):
prod_reps.append(torch.cat((head_rep[pair_idx[:, 0]], tail_rep[pair_idx[:, 1]]), dim=-1))
pair_preds.append(torch.stack((obj_pred[pair_idx[:, 0]], obj_pred[pair_idx[:, 1]]), dim=1))
prod_rep = cat(prod_reps, dim=0)
pair_pred = cat(pair_preds, dim=0)
prod_rep = self.post_cat(prod_rep)
if self.union_single_not_match:
union_features = self.up_dim(union_features)
prod_rep = prod_rep * union_features
add_losses = {}
if self.training:
binary_loss = []
for bi_gt, bi_pred in zip(rel_binarys, binary_preds):
bi_gt = (bi_gt > 0).float()
binary_loss.append(F.binary_cross_entropy_with_logits(bi_pred, bi_gt))
add_losses["binary_loss"] = sum(binary_loss) / len(binary_loss)
if not self.config.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL:
fg_labels = cat([proposal.get_field("labels") for proposal in proposals], dim=0)
loss_refine_obj = self.criterion_loss(obj_dists, fg_labels.long())
add_losses['obj_loss'] = loss_refine_obj
rel_labels = cat(rel_labels, dim=0)
max_label = max(rel_labels)
num_groups = self.incre_idx_list[max_label.item()]
if num_groups == 0:
num_groups = max(self.incre_idx_list)
cur_chosen_matrix = []
for i in range(num_groups):
cur_chosen_matrix.append([])
for i in range(len(rel_labels)):
rel_tar = rel_labels[i].item()
if rel_tar == 0:
if self.zero_label_padding_mode == 'rand_insert':
random_idx = random.randint(0, num_groups - 1)
cur_chosen_matrix[random_idx].append(i)
elif self.zero_label_padding_mode == 'rand_choose' or self.zero_label_padding_mode == 'all_include':
if self.zero_label_padding_mode == 'rand_choose':
rand_zeros = random.random()
else:
rand_zeros = 1.0
if rand_zeros >= 0.4:
for zix in range(len(cur_chosen_matrix)):
cur_chosen_matrix[zix].append(i)
else:
rel_idx = self.incre_idx_list[rel_tar]
random_num = random.random()
for j in range(num_groups):
act_idx = num_groups - j
threshold_cur = self.sample_rate_matrix[act_idx - 1][rel_tar]
if random_num <= threshold_cur or act_idx < rel_idx:
# print('%d-%d-%d-%.2f-%.2f'%(i, rel_idx, act_idx, random_num, threshold_cur))
for k in range(act_idx):
cur_chosen_matrix[k].append(i)
break
for i in range(num_groups):
if max_label == 0:
group_input = prod_rep
group_label = rel_labels
group_pairs = pair_pred
else:
group_input = prod_rep[cur_chosen_matrix[i]]
group_label = rel_labels[cur_chosen_matrix[i]]
group_pairs = pair_pred[cur_chosen_matrix[i]]
'''count Cross Entropy loss'''
jdx = i
rel_classier_now = self.rel_classifer_all[jdx]
group_output_now = rel_classier_now(group_input)
if self.use_bias:
rel_bias_now = self.freq_bias_all[jdx]
group_output_now = group_output_now + rel_bias_now.index_with_labels(group_pairs.long())
# actual_label_piece: if label is out of range, then filter it to ensure the training can continue
actual_label_now = self.pre_group_matrix[jdx][group_label]
add_losses['%d_CE_loss' % (jdx + 1)] = self.CE_loss(group_output_now, actual_label_now)
if self.Knowledge_Transfer_Mode == 'KL_logit_Neighbor':
if i > 0:
'''count knowledge transfer loss'''
jbef = i - 1
rel_classier_bef = self.rel_classifer_all[jbef]
group_output_bef = rel_classier_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_vecify = kd_loss_matrix * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * kd_loss_matrix
add_losses['%d%d_kl_loss' % (jbef + 1, jdx + 1)] = kd_loss_final
elif self.Knowledge_Transfer_Mode == 'KL_logit_TopDown':
layer_total_loss = 0
for jbef in range(i):
rel_classier_bef = self.rel_classifer_all[jbef]
group_output_bef = rel_classier_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
# kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_vecify = kd_loss_matrix * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix = KL_divergence(group_output_bef[:, 1:], group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * kd_loss_matrix
layer_total_loss += kd_loss_final
if i > 0:
add_losses['%d_DKS_loss' % (jdx + 1)] = layer_total_loss
elif self.Knowledge_Transfer_Mode == 'KL_logit_BiDirection':
layer_total_loss = 0
for jbef in range(i):
rel_classier_bef = self.rel_classifer_all[jbef]
group_output_bef = rel_classier_bef(group_input)
if self.use_bias:
rel_bias_bef = self.freq_bias_all[jbef]
group_output_bef = group_output_bef + rel_bias_bef.index_with_labels(group_pairs.long())
# kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
max_vector = self.max_elemnt_list[jbef] + 1
if self.no_relation_restrain:
kd_choice_vector = self.pre_kd_matrix[jbef][group_label]
kd_loss_matrix_td = KL_divergence(group_output_bef[:, 1:],
group_output_now[:, 1:max_vector],
reduce=False)
kd_loss_matrix_bu = KL_divergence(group_output_now[:, 1:max_vector],
group_output_bef[:, 1:],
reduce=False)
kd_loss_vecify = (kd_loss_matrix_td + kd_loss_matrix_bu) * kd_choice_vector
kd_loss_final = self.knowledge_loss_coefficient * torch.mean(kd_loss_vecify)
else:
kd_loss_matrix_td = KL_divergence(group_output_bef[:, 1:],
group_output_now[:, 1:max_vector],
reduce=True)
kd_loss_matrix_bu = KL_divergence(group_output_now[:, 1:max_vector],
group_output_bef[:, 1:],
reduce=True)
kd_loss_final = self.knowledge_loss_coefficient * (kd_loss_matrix_td + kd_loss_matrix_bu)
layer_total_loss += kd_loss_final
if i > 0:
add_losses['%d_DKS_loss' % (jdx + 1)] = layer_total_loss
return None, None, add_losses
else:
rel_classier_test = self.rel_classifer_all[-1]
rel_dists = rel_classier_test(prod_rep)
if self.use_bias:
rel_bias_test = self.freq_bias_all[-1]
rel_dists = rel_dists + rel_bias_test.index_with_labels(pair_pred.long())
rel_dists = rel_dists.split(num_rels, dim=0)
obj_dists = obj_dists.split(num_objs, dim=0)
return obj_dists, rel_dists, add_losses
ctx_dists = self.ctx_compress(prod_rep * union_features)
# uni_dists = self.uni_compress(self.drop(union_features))
frq_dists = self.freq_bias.index_with_labels(pair_pred.long())
rel_dists = ctx_dists + frq_dists
add_losses = {}
if self.training:
binary_loss = []
for bi_gt, bi_pred in zip(rel_binarys, binary_preds):
bi_gt = (bi_gt > 0).float()
binary_loss.append(F.binary_cross_entropy_with_logits(bi_pred, bi_gt))
add_losses["binary_loss"] = sum(binary_loss) / len(binary_loss)
if not self.config.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL:
fg_labels = cat([proposal.get_field("labels") for proposal in proposals], dim=0)
loss_refine_obj = self.criterion_loss(obj_dists, fg_labels.long())
add_losses['obj_loss'] = loss_refine_obj
rel_labels = cat(rel_labels, dim=0)
add_losses['rel_loss'] = self.criterion_loss(rel_dists, rel_labels)
return None, None, add_losses
else:
obj_dists = obj_dists.split(num_objs, dim=0)
rel_dists = rel_dists.split(num_rels, dim=0)
return obj_dists, rel_dists, add_losses
def generate_muti_networks(self, num_cls):
'''generate all the hier-net in the model, need to set mannually if use new hier-class'''
self.rel_classifer_1 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[0] + 1)
self.rel_classifer_2 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[1] + 1)
self.rel_classifer_3 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[2] + 1)
self.rel_classifer_4 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[3] + 1)
layer_init(self.rel_classifer_1, xavier=True)
layer_init(self.rel_classifer_2, xavier=True)
layer_init(self.rel_classifer_3, xavier=True)
layer_init(self.rel_classifer_4, xavier=True)
if num_cls == 4:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3, self.rel_classifer_4]
elif num_cls < 4:
exit('wrong num in compress_all')
else:
self.rel_classifer_5 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[4] + 1)
layer_init(self.rel_classifer_5, xavier=True)
if num_cls == 5:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5]
else:
self.rel_classifer_6 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[5] + 1)
layer_init(self.rel_classifer_6, xavier=True)
if num_cls == 6:
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5, self.rel_classifer_6]
else:
self.rel_classifer_7 = nn.Linear(self.pooling_dim, self.max_group_element_number_list[6] + 1)
layer_init(self.rel_classifer_7, xavier=True)
classifer_all = [self.rel_classifer_1, self.rel_classifer_2, self.rel_classifer_3,
self.rel_classifer_4, self.rel_classifer_5, self.rel_classifer_6,
self.rel_classifer_7]
if num_cls > 7:
exit('wrong num in compress_all')
return classifer_all
def generate_multi_bias(self, config, statistics, num_cls):
self.freq_bias_1 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[0])
self.freq_bias_2 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[1])
self.freq_bias_3 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[2])
self.freq_bias_4 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[3])
if num_cls < 4:
exit('wrong num in multi_bias')
elif num_cls == 4:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3, self.freq_bias_4]
else:
self.freq_bias_5 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE, predicate_all_list=self.bias_for_group_split[4])
if num_cls == 5:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3, self.freq_bias_4,
self.freq_bias_5]
else:
self.freq_bias_6 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE,
predicate_all_list=self.bias_for_group_split[5])
if num_cls == 6:
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3,
self.freq_bias_4, self.freq_bias_5, self.freq_bias_6]
else:
self.freq_bias_7 = FrequencyBias_GCL(config, statistics, config.GLOBAL_SETTING.DATASET_CHOICE,
predicate_all_list=self.bias_for_group_split[6])
freq_bias_all = [self.freq_bias_1, self.freq_bias_2, self.freq_bias_3,
self.freq_bias_4, self.freq_bias_5, self.freq_bias_6, self.freq_bias_7]
if num_cls > 7:
exit('wrong num in multi_bias')
return freq_bias_all
@registry.ROI_RELATION_PREDICTOR.register("TransLikePredictor")
class TransLikePredictor(nn.Module):
def __init__(self, config, in_channels):
super(TransLikePredictor, self).__init__()
self.config = config
if config.GLOBAL_SETTING.DATASET_CHOICE == 'VG':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.VG_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.VG_NUM_CLASSES
elif config.GLOBAL_SETTING.DATASET_CHOICE == 'GQA_200':
self.num_obj_cls = config.MODEL.ROI_BOX_HEAD.GQA_200_NUM_CLASSES
self.num_rel_cls = config.MODEL.ROI_RELATION_HEAD.GQA_200_NUM_CLASSES
assert in_channels is not None
num_inputs = in_channels
self.use_vision = config.MODEL.ROI_RELATION_HEAD.PREDICT_USE_VISION
self.use_bias = config.MODEL.ROI_RELATION_HEAD.PREDICT_USE_BIAS
# load class dict
statistics = get_dataset_statistics(config)
obj_classes, rel_classes = statistics['obj_classes'], statistics['rel_classes']
assert self.num_obj_cls == len(obj_classes)
assert self.num_rel_cls == len(rel_classes)
# module construct
if config.GLOBAL_SETTING.BASIC_ENCODER == 'Self-Attention':
self.context_layer = TransformerContext(config, obj_classes, rel_classes, in_channels)
elif config.GLOBAL_SETTING.BASIC_ENCODER == 'Cross-Attention':
self.context_layer = CA_Context(config, obj_classes, rel_classes, in_channels)
elif config.GLOBAL_SETTING.BASIC_ENCODER == 'Hybrid-Attention':
self.context_layer = SHA_Context(config, obj_classes, rel_classes, in_channels)
# post decoding
self.hidden_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_HIDDEN_DIM
self.pooling_dim = config.MODEL.ROI_RELATION_HEAD.CONTEXT_POOLING_DIM
self.post_emb = nn.Linear(self.hidden_dim, self.hidden_dim * 2)
self.post_cat = nn.Linear(self.hidden_dim * 2, self.pooling_dim)
self.rel_compress = nn.Linear(self.pooling_dim, self.num_rel_cls)
self.ctx_compress = nn.Linear(self.hidden_dim * 2, self.num_rel_cls)
# initialize layer parameters
layer_init(self.post_emb, 10.0 * (1.0 / self.hidden_dim) ** 0.5, normal=True)
layer_init(self.rel_compress, xavier=True)
layer_init(self.ctx_compress, xavier=True)
layer_init(self.post_cat, xavier=True)
if self.pooling_dim != config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM:
self.union_single_not_match = True
self.up_dim = nn.Linear(config.MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM, self.pooling_dim)
layer_init(self.up_dim, xavier=True)
else:
self.union_single_not_match = False
if self.use_bias:
# convey statistics into FrequencyBias to avoid loading again
self.freq_bias = FrequencyBias(config, statistics)
self.criterion_loss = nn.CrossEntropyLoss()
def forward(self, proposals, rel_pair_idxs, rel_labels, rel_binarys, roi_features, union_features, logger=None):
"""
Returns:
obj_dists (list[Tensor]): logits of object label distribution
rel_dists (list[Tensor])
rel_pair_idxs (list[Tensor]): (num_rel, 2) index of subject and object
union_features (Tensor): (batch_num_rel, context_pooling_dim): visual union feature of each pair
"""
obj_dists, obj_preds, edge_ctx = self.context_layer(roi_features, proposals, logger)
# post decode
edge_rep = self.post_emb(edge_ctx)
edge_rep = edge_rep.view(edge_rep.size(0), 2, self.hidden_dim)
head_rep = edge_rep[:, 0].contiguous().view(-1, self.hidden_dim)
tail_rep = edge_rep[:, 1].contiguous().view(-1, self.hidden_dim)
num_rels = [r.shape[0] for r in rel_pair_idxs]
num_objs = [len(b) for b in proposals]
assert len(num_rels) == len(num_objs)
head_reps = head_rep.split(num_objs, dim=0)
tail_reps = tail_rep.split(num_objs, dim=0)
obj_preds = obj_preds.split(num_objs, dim=0)
# from object level feature to pairwise relation level feature
prod_reps = []
pair_preds = []
for pair_idx, head_rep, tail_rep, obj_pred in zip(rel_pair_idxs, head_reps, tail_reps, obj_preds):
prod_reps.append(torch.cat((head_rep[pair_idx[:, 0]], tail_rep[pair_idx[:, 1]]), dim=-1))
pair_preds.append(torch.stack((obj_pred[pair_idx[:, 0]], obj_pred[pair_idx[:, 1]]), dim=1))
prod_rep = cat(prod_reps, dim=0)
pair_pred = cat(pair_preds, dim=0)
ctx_gate = self.post_cat(prod_rep)
# use union box and mask convolution
if self.use_vision:
if self.union_single_not_match:
visual_rep = ctx_gate * self.up_dim(union_features)
else:
visual_rep = ctx_gate * union_features
rel_dists = self.rel_compress(visual_rep) + self.ctx_compress(prod_rep)
add_losses = {}
if self.training:
if not self.config.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL:
fg_labels = cat([proposal.get_field("labels") for proposal in proposals], dim=0)
loss_refine_obj = self.criterion_loss(obj_dists, fg_labels.long())
add_losses['obj_loss'] = loss_refine_obj
rel_labels = cat(rel_labels, dim=0)
add_losses['rel_loss'] = self.criterion_loss(rel_dists, rel_labels)
return None, None, add_losses
else:
obj_dists = obj_dists.split(num_objs, dim=0)
rel_dists = rel_dists.split(num_rels, dim=0)
return obj_dists, rel_dists, add_losses
def make_roi_relation_predictor(cfg, in_channels):
import time
result_str = '---'*20
result_str += ('\n\nthe dataset we use is [ %s ]' % cfg.GLOBAL_SETTING.DATASET_CHOICE)
if cfg.GLOBAL_SETTING.USE_BIAS:
result_str += ('\nwe use [ bias ]!')
else:
result_str += ('\nwe do [ not ] use bias!')
result_str += ('\nthe model we use is [ %s ]' % cfg.GLOBAL_SETTING.RELATION_PREDICTOR)
if cfg.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL == True and cfg.MODEL.ROI_RELATION_HEAD.USE_GT_BOX == True:
result_str += ('\ntraining mode is [ predcls ]')
elif cfg.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL == False and cfg.MODEL.ROI_RELATION_HEAD.USE_GT_BOX == True:
result_str += ('\ntraining mode is [ sgcls ]')
elif cfg.MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL == False and cfg.MODEL.ROI_RELATION_HEAD.USE_GT_BOX == False:
result_str += ('\ntraining mode is [ sgdet ]')
else:
exit('wrong training mode!')
result_str += ('\nlearning rate is [ %.5f ]' % cfg.SOLVER.BASE_LR)
result_str += ('\nthe knowledge distillation strategy is [ %s ]' % cfg.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_TRANSFER_MODE)
assert cfg.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_TRANSFER_MODE in ['None', 'KL_logit_Neighbor', 'KL_logit_None',
'KL_logit_TopDown', 'KL_logit_BottomUp', 'KL_logit_BiDirection']
if cfg.GLOBAL_SETTING.RELATION_PREDICTOR in ['TransLike_GCL', 'TransLikePredictor']:
result_str += ('\nrel labels=0 is use [ %s ] to process' % cfg.GLOBAL_SETTING.GCL_SETTING.ZERO_LABEL_PADDING_MODE)
assert cfg.GLOBAL_SETTING.GCL_SETTING.ZERO_LABEL_PADDING_MODE in ['rand_insert', 'rand_choose', 'all_include']
assert cfg.GLOBAL_SETTING.BASIC_ENCODER in ['Self-Attention', 'Cross-Attention', 'Hybrid-Attention']
result_str += ('\n-----Transformer layer is [ %d ] in obj and [ %d ] in rel' %
(cfg.MODEL.ROI_RELATION_HEAD.TRANSFORMER.OBJ_LAYER,
cfg.MODEL.ROI_RELATION_HEAD.TRANSFORMER.REL_LAYER))
result_str += ('\n-----Transformer mode is [ %s ]' % cfg.GLOBAL_SETTING.BASIC_ENCODER)
if cfg.GLOBAL_SETTING.RELATION_PREDICTOR in ['MotifsLike_GCL', 'MotifsLikePredictor']:
assert cfg.GLOBAL_SETTING.BASIC_ENCODER in ['Motifs', 'VTransE']
result_str += ('\n-----Model mode is [ %s ]' % cfg.GLOBAL_SETTING.BASIC_ENCODER)
num_of_group_element_list, predicate_stage_count = get_group_splits(cfg.GLOBAL_SETTING.DATASET_CHOICE, cfg.GLOBAL_SETTING.GCL_SETTING.GROUP_SPLIT_MODE)
max_group_element_number_list = generate_num_stage_vector(num_of_group_element_list)
incre_idx_list, max_elemnt_list, group_matrix, kd_matrix = get_current_predicate_idx(
num_of_group_element_list, cfg.GLOBAL_SETTING.GCL_SETTING.NO_RELATION_PENALTY, cfg.GLOBAL_SETTING.DATASET_CHOICE)
result_str += ('\n the number of elements in each group is {}'.format(incre_idx_list))
result_str += ('\n incremental stage list is {}'.format(num_of_group_element_list))
result_str += ('\n the length of each line in group is {}'.format(predicate_stage_count))
result_str += ('\n the max number of elements in each group is {}'.format(max_group_element_number_list))
result_str += ('\n the knowledge distillation strategy is [ %s ]' % cfg.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_TRANSFER_MODE)
result_str += ('\n the penalty for whole distillation loss is [ %.2f ]' % cfg.GLOBAL_SETTING.GCL_SETTING.KNOWLEDGE_LOSS_COEFFICIENT)
with open(os.path.join(cfg.OUTPUT_DIR, 'control_info.txt'), 'w') as outfile:
outfile.write(result_str)
result_str += '\n\n'
result_str += '---'*20
print(result_str)
time.sleep(2)
func = registry.ROI_RELATION_PREDICTOR[cfg.GLOBAL_SETTING.RELATION_PREDICTOR]
return func(cfg, in_channels)
| 57.334884
| 155
| 0.619511
| 11,211
| 86,289
| 4.372937
| 0.033984
| 0.024131
| 0.039164
| 0.025456
| 0.940398
| 0.932014
| 0.927364
| 0.916573
| 0.912045
| 0.906925
| 0
| 0.012536
| 0.295565
| 86,289
| 1,504
| 156
| 57.373005
| 0.793995
| 0.049265
| 0
| 0.895128
| 0
| 0
| 0.028119
| 0
| 0
| 0
| 0
| 0
| 0.023121
| 1
| 0.01569
| false
| 0.000826
| 0.019818
| 0
| 0.057803
| 0.000826
| 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
|
eb5c500a123174f927c6db7ca19aa7a0b12e7434
| 5,241
|
py
|
Python
|
System/Boolean/__init__.py
|
Grim-es/udon-pie-auto-completion
|
c2cd86554ed615cdbbb01e19fa40665eafdfaedc
|
[
"MIT"
] | null | null | null |
System/Boolean/__init__.py
|
Grim-es/udon-pie-auto-completion
|
c2cd86554ed615cdbbb01e19fa40665eafdfaedc
|
[
"MIT"
] | null | null | null |
System/Boolean/__init__.py
|
Grim-es/udon-pie-auto-completion
|
c2cd86554ed615cdbbb01e19fa40665eafdfaedc
|
[
"MIT"
] | null | null | null |
from typing import overload
from UdonPie import System
from UdonPie.Undefined import *
class Boolean:
def __new__(cls, arg1=None):
'''
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_Equality(arg1, arg2):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:param arg2: Boolean
:type arg2: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_Inequality(arg1, arg2):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:param arg2: Boolean
:type arg2: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_LogicalAnd(arg1, arg2):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:param arg2: Boolean
:type arg2: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_LogicalOr(arg1, arg2):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:param arg2: Boolean
:type arg2: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_LogicalXor(arg1, arg2):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:param arg2: Boolean
:type arg2: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_ConditionalAnd(arg1, arg2):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:param arg2: Boolean
:type arg2: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_ConditionalOr(arg1, arg2):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:param arg2: Boolean
:type arg2: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_ConditionalXor(arg1, arg2):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:param arg2: Boolean
:type arg2: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def op_UnaryNegation(arg1):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def get_TrueString():
'''
:returns: String
:rtype: System.String
'''
pass
@staticmethod
def get_FalseString():
'''
:returns: String
:rtype: System.String
'''
pass
@staticmethod
def GetHashCode():
'''
:returns: Int32
:rtype: System.Int32
'''
pass
@staticmethod
@overload
def Equals(arg1):
'''
:param arg1: Object
:type arg1: System.Object
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
@overload
def Equals(arg1):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def Equals(arg1=None):
pass
@staticmethod
@overload
def CompareTo(arg1):
'''
:param arg1: Object
:type arg1: System.Object
:returns: Int32
:rtype: System.Int32
'''
pass
@staticmethod
@overload
def CompareTo(arg1):
'''
:param arg1: Boolean
:type arg1: System.Boolean or bool
:returns: Int32
:rtype: System.Int32
'''
pass
@staticmethod
def CompareTo(arg1=None):
pass
@staticmethod
def Parse(arg1):
'''
:param arg1: String
:type arg1: System.String or str
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
@overload
def ToString():
'''
:returns: String
:rtype: System.String
'''
pass
@staticmethod
@overload
def ToString(arg1):
'''
:param arg1: IFormatProvider
:type arg1: System.IFormatProvider
:returns: String
:rtype: System.String
'''
pass
@staticmethod
def ToString(arg1=None):
pass
@staticmethod
def TryParse(arg1, arg2):
'''
:param arg1: String
:type arg1: System.String or str
:param arg2: Undefined variable
:type arg2: BooleanRef.BooleanRef
:returns: Boolean
:rtype: System.Boolean
'''
pass
@staticmethod
def GetType():
'''
:returns: Type
:rtype: System.Type
'''
pass
| 20.964
| 42
| 0.524137
| 492
| 5,241
| 5.552846
| 0.101626
| 0.157028
| 0.104319
| 0.132138
| 0.836018
| 0.806369
| 0.806369
| 0.775988
| 0.68265
| 0.521962
| 0
| 0.028121
| 0.382561
| 5,241
| 249
| 43
| 21.048193
| 0.816131
| 0.432551
| 0
| 0.702381
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.297619
| false
| 0.297619
| 0.035714
| 0
| 0.345238
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
eb96c97812a619f4e699b72196517cb57e3b5455
| 15,169
|
py
|
Python
|
tests/test_config_flow.py
|
firstof9/ha-openei
|
ac01f6756b846591049d629249d11a0d1edfb867
|
[
"MIT"
] | 7
|
2021-09-08T14:46:11.000Z
|
2021-11-14T18:14:09.000Z
|
tests/test_config_flow.py
|
firstof9/ha-openei
|
ac01f6756b846591049d629249d11a0d1edfb867
|
[
"MIT"
] | 44
|
2021-09-03T22:09:21.000Z
|
2021-12-15T17:21:25.000Z
|
tests/test_config_flow.py
|
firstof9/ha-openei
|
ac01f6756b846591049d629249d11a0d1edfb867
|
[
"MIT"
] | 1
|
2021-09-04T13:15:51.000Z
|
2021-09-04T13:15:51.000Z
|
"""Test OpenEI config flow."""
from unittest.mock import patch
import pytest
from homeassistant import config_entries, setup
from pytest_homeassistant_custom_component.common import MockConfigEntry
from custom_components.openei.const import DOMAIN
@pytest.mark.parametrize(
"input_1,step_id_2,input_2,step_id_3,input_3,title,data",
[
(
{
"api_key": "fakeAPIKey",
"radius": 0,
"location": "",
},
"user_2",
{
"utility": "Fake Utility Co",
},
"user_3",
{
"rate_plan": "randomstring",
"sensor": "(none)",
"manual_plan": "",
},
"Fake Utility Co",
{
"api_key": "fakeAPIKey",
"radius": 0,
"utility": "Fake Utility Co",
"rate_plan": "randomstring",
"sensor": "(none)",
"location": "",
"manual_plan": "",
},
),
],
)
async def test_form(
input_1,
step_id_2,
input_2,
step_id_3,
input_3,
title,
data,
hass,
mock_api,
):
"""Test we get the form."""
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
assert result["type"] == "form"
assert result["errors"] == {}
# assert result['title'] == title_1
with patch(
"custom_components.openei.async_setup", return_value=True
) as mock_setup, patch(
"custom_components.openei.async_setup_entry",
return_value=True,
) as mock_setup_entry, patch(
"custom_components.openei.config_flow._lookup_plans",
return_value={
"Fake Utility Co": [{"name": "Fake Plan Name", "label": "randomstring"}]
},
), patch(
"custom_components.openei.config_flow._get_entities",
return_value=["(none)"],
):
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"], input_1
)
assert result2["type"] == "form"
assert result2["step_id"] == step_id_2
result3 = await hass.config_entries.flow.async_configure(
result["flow_id"], input_2
)
assert result3["type"] == "form"
assert result3["step_id"] == step_id_3
result4 = await hass.config_entries.flow.async_configure(
result["flow_id"], input_3
)
assert result4["type"] == "create_entry"
assert result4["title"] == title
assert result4["data"] == data
await hass.async_block_till_done()
assert len(mock_setup.mock_calls) == 1
assert len(mock_setup_entry.mock_calls) == 1
@pytest.mark.parametrize(
"input_1,step_id_2,input_2,step_id_3,input_3,title,data",
[
(
{
"api_key": "fakeAPIKey_new",
"radius": 20,
"location": "",
},
"user_2",
{
"utility": "Fake Utility Co",
},
"user_3",
{
"rate_plan": "randomstring",
"sensor": "(none)",
"manual_plan": "",
},
"Fake Utility Co",
{
"api_key": "fakeAPIKey_new",
"radius": 20,
"utility": "Fake Utility Co",
"rate_plan": "randomstring",
"sensor": "(none)",
"location": "",
"manual_plan": "",
},
),
],
)
async def test_options_flow(
input_1,
step_id_2,
input_2,
step_id_3,
input_3,
title,
data,
hass,
mock_api_config,
):
"""Test config flow options."""
entry = MockConfigEntry(
domain=DOMAIN,
title="Fake Utility Co",
data={
"api_key": "fakeAPIKey",
"radius": None,
"location": "",
"utility": "Fake Utility Co",
"rate_plan": "randomstring",
"sensor": "(none)",
"manual_plan": None,
},
)
entry.add_to_hass(hass)
assert await hass.config_entries.async_setup(entry.entry_id)
await hass.async_block_till_done()
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.options.async_init(entry.entry_id)
assert result["type"] == "form"
assert result["errors"] == {}
# assert result['title'] == title_1
with patch("custom_components.openei.async_setup", return_value=True), patch(
"custom_components.openei.async_setup_entry",
return_value=True,
), patch(
"custom_components.openei.config_flow._get_entities",
return_value=["(none)"],
):
result2 = await hass.config_entries.options.async_configure(
result["flow_id"], input_1
)
await hass.async_block_till_done()
assert result2["type"] == "form"
assert result2["step_id"] == step_id_2
result3 = await hass.config_entries.options.async_configure(
result["flow_id"], input_2
)
await hass.async_block_till_done()
assert result3["type"] == "form"
assert result3["step_id"] == step_id_3
result4 = await hass.config_entries.options.async_configure(
result["flow_id"], input_3
)
await hass.async_block_till_done()
assert result4["type"] == "create_entry"
assert data == entry.data.copy()
await hass.async_block_till_done()
@pytest.mark.parametrize(
"input_1,step_id_2,input_2,step_id_3,input_3,title,data",
[
(
{
"api_key": "fakeAPIKey",
"radius": 0,
"location": "",
},
"user_2",
{
"utility": "Fake Utility Co",
},
"user_3",
{
"rate_plan": "randomstring",
"sensor": "(none)",
"manual_plan": "",
},
"Fake Utility Co",
{
"api_key": "fakeAPIKey",
"radius": 0,
"utility": "Fake Utility Co",
"rate_plan": "randomstring",
"sensor": "(none)",
"location": "",
"manual_plan": "",
},
),
],
)
async def test_options_flow_no_changes(
input_1,
step_id_2,
input_2,
step_id_3,
input_3,
title,
data,
hass,
mock_api,
caplog,
):
"""Test config flow options."""
entry = MockConfigEntry(
domain=DOMAIN,
title="Fake Utility Co",
data={
"api_key": "fakeAPIKey",
"radius": None,
"location": "",
"utility": "Fake Utility Co",
"rate_plan": "randomstring",
"sensor": "(none)",
"manual_plan": "",
},
)
entry.add_to_hass(hass)
assert await hass.config_entries.async_setup(entry.entry_id)
await hass.async_block_till_done()
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.options.async_init(entry.entry_id)
assert result["type"] == "form"
assert result["errors"] == {}
# assert result['title'] == title_1
with patch("custom_components.openei.async_setup", return_value=True), patch(
"custom_components.openei.async_setup_entry",
return_value=True,
), patch(
"custom_components.openei.config_flow._lookup_plans",
return_value={
"Fake Utility Co": [{"name": "Fake Plan Name", "label": "randomstring"}]
},
):
result2 = await hass.config_entries.options.async_configure(
result["flow_id"], input_1
)
await hass.async_block_till_done()
assert result2["type"] == "form"
assert result2["step_id"] == step_id_2
result3 = await hass.config_entries.options.async_configure(
result["flow_id"], input_2
)
await hass.async_block_till_done()
assert result3["type"] == "form"
assert result3["step_id"] == step_id_3
result4 = await hass.config_entries.options.async_configure(
result["flow_id"], input_3
)
await hass.async_block_till_done()
assert result4["type"] == "create_entry"
assert data == entry.data.copy()
await hass.async_block_till_done()
assert (
"Attempting to reload entities from the openei integration" in caplog.text
)
@pytest.mark.parametrize(
"input_1,step_id_2,input_2,step_id_3,input_3,title,data",
[
(
{
"api_key": "fakeAPIKey",
"radius": 0,
"location": '""',
},
"user_2",
{
"utility": "Not Listed",
},
"user_3",
{
"rate_plan": "Not Listed",
"sensor": "(none)",
"manual_plan": "randomstring",
},
"Fake Utility Co",
{
"api_key": "fakeAPIKey",
"radius": 0,
"utility": "Not Listed",
"rate_plan": "Not Listed",
"sensor": "(none)",
"location": "",
"manual_plan": "randomstring",
},
),
],
)
async def test_options_flow_some_changes(
input_1,
step_id_2,
input_2,
step_id_3,
input_3,
title,
data,
hass,
mock_api,
caplog,
):
"""Test config flow options."""
entry = MockConfigEntry(
domain=DOMAIN,
title="Fake Utility Co",
data={
"api_key": "fakeAPIKey",
"radius": None,
"location": "12345",
"utility": "Fake Utility Co",
"rate_plan": "randomstring",
"sensor": "(none)",
"manual_plan": "",
},
)
entry.add_to_hass(hass)
assert await hass.config_entries.async_setup(entry.entry_id)
await hass.async_block_till_done()
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.options.async_init(entry.entry_id)
assert result["type"] == "form"
assert result["errors"] == {}
# assert result['title'] == title_1
with patch("custom_components.openei.async_setup", return_value=True), patch(
"custom_components.openei.async_setup_entry",
return_value=True,
), patch(
"custom_components.openei.config_flow._lookup_plans",
return_value={
"Fake Utility Co": [{"name": "Fake Plan Name", "label": "randomstring"}],
"Not Listed": [{"name": "Not Listed", "label": "Not Listed"}],
},
):
result2 = await hass.config_entries.options.async_configure(
result["flow_id"], input_1
)
await hass.async_block_till_done()
assert result2["type"] == "form"
assert result2["step_id"] == step_id_2
result3 = await hass.config_entries.options.async_configure(
result["flow_id"], input_2
)
await hass.async_block_till_done()
assert result3["type"] == "form"
assert result3["step_id"] == step_id_3
result4 = await hass.config_entries.options.async_configure(
result["flow_id"], input_3
)
await hass.async_block_till_done()
assert result4["type"] == "create_entry"
assert data == entry.data.copy()
await hass.async_block_till_done()
assert (
"Attempting to reload entities from the openei integration" in caplog.text
)
@pytest.mark.parametrize(
"input_1,step_id_2,input_2,step_id_3,input_3,title,data",
[
(
{
"api_key": "fakeAPIKey",
"radius": 0,
"location": '""',
},
"user_2",
{
"utility": "Fake Utility Co",
},
"user_3",
{
"rate_plan": "randomstring",
"sensor": "(none)",
"manual_plan": '""',
},
"Fake Utility Co",
{
"api_key": "fakeAPIKey",
"radius": 0,
"utility": "Fake Utility Co",
"rate_plan": "randomstring",
"sensor": "(none)",
"location": "",
"manual_plan": "",
},
),
],
)
async def test_options_flow_some_changes_2(
input_1,
step_id_2,
input_2,
step_id_3,
input_3,
title,
data,
hass,
mock_api,
caplog,
):
"""Test config flow options."""
entry = MockConfigEntry(
domain=DOMAIN,
title="Fake Utility Co",
data={
"api_key": "fakeAPIKey",
"radius": 0,
"location": "12345",
"utility": "Not Listed",
"rate_plan": "Not Listed",
"sensor": "(none)",
"manual_plan": "somerandomstring",
},
)
entry.add_to_hass(hass)
assert await hass.config_entries.async_setup(entry.entry_id)
await hass.async_block_till_done()
await setup.async_setup_component(hass, "persistent_notification", {})
result = await hass.config_entries.options.async_init(entry.entry_id)
assert result["type"] == "form"
assert result["errors"] == {}
# assert result['title'] == title_1
with patch("custom_components.openei.async_setup", return_value=True), patch(
"custom_components.openei.async_setup_entry",
return_value=True,
), patch(
"custom_components.openei.config_flow._lookup_plans",
return_value={
"Fake Utility Co": [{"name": "Fake Plan Name", "label": "randomstring"}],
"Not Listed": [{"name": "Not Listed", "label": "Not Listed"}],
},
):
result2 = await hass.config_entries.options.async_configure(
result["flow_id"], input_1
)
await hass.async_block_till_done()
assert result2["type"] == "form"
assert result2["step_id"] == step_id_2
result3 = await hass.config_entries.options.async_configure(
result["flow_id"], input_2
)
await hass.async_block_till_done()
assert result3["type"] == "form"
assert result3["step_id"] == step_id_3
result4 = await hass.config_entries.options.async_configure(
result["flow_id"], input_3
)
await hass.async_block_till_done()
assert result4["type"] == "create_entry"
assert data == entry.data.copy()
await hass.async_block_till_done()
assert (
"Attempting to reload entities from the openei integration" in caplog.text
)
| 28.513158
| 86
| 0.533522
| 1,550
| 15,169
| 4.93871
| 0.066452
| 0.052907
| 0.040758
| 0.068975
| 0.941346
| 0.938994
| 0.927629
| 0.916786
| 0.910647
| 0.894709
| 0
| 0.015725
| 0.337596
| 15,169
| 532
| 87
| 28.513158
| 0.746119
| 0.012855
| 0
| 0.75594
| 0
| 0
| 0.239773
| 0.072566
| 0
| 0
| 0
| 0
| 0.107991
| 1
| 0
| false
| 0
| 0.010799
| 0
| 0.010799
| 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
|
692af92ef3031a9fa77d99255869ab76eac2ad1b
| 303
|
py
|
Python
|
bayesrl/agents/__init__.py
|
OlehLuk/bayesrl
|
ceaee729e93254f8209738274e724afd463c994e
|
[
"MIT"
] | null | null | null |
bayesrl/agents/__init__.py
|
OlehLuk/bayesrl
|
ceaee729e93254f8209738274e724afd463c994e
|
[
"MIT"
] | null | null | null |
bayesrl/agents/__init__.py
|
OlehLuk/bayesrl
|
ceaee729e93254f8209738274e724afd463c994e
|
[
"MIT"
] | null | null | null |
from bayesrl.agents.agent import *
from bayesrl.agents.modelbasedagent import *
from bayesrl.agents.qlearningagent import *
from bayesrl.agents.rmaxagent import *
from bayesrl.agents.sarsaagent import *
from bayesrl.agents.thompsonsampagent import *
from bayesrl.agents.thompsonsampagent_pomdp import *
| 37.875
| 52
| 0.838284
| 36
| 303
| 7.027778
| 0.305556
| 0.304348
| 0.470356
| 0.545455
| 0.316206
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.092409
| 303
| 7
| 53
| 43.285714
| 0.92
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 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
| 7
|
692fe488852dc64db1f9bb15f5d27b0a09887f85
| 5,781
|
py
|
Python
|
Scripts/sims4communitylib/utils/sims/common_sim_loot_action_utils.py
|
ColonolNutty/Sims4CommunityLibrary
|
684f28dc3c7deb4d9fd520e21e63942b65a91d31
|
[
"CC-BY-4.0"
] | 118
|
2019-08-31T04:33:18.000Z
|
2022-03-28T21:12:14.000Z
|
Scripts/sims4communitylib/utils/sims/common_sim_loot_action_utils.py
|
ColonolNutty/Sims4CommunityLibrary
|
684f28dc3c7deb4d9fd520e21e63942b65a91d31
|
[
"CC-BY-4.0"
] | 15
|
2019-12-05T01:29:46.000Z
|
2022-02-18T17:13:46.000Z
|
Scripts/sims4communitylib/utils/sims/common_sim_loot_action_utils.py
|
ColonolNutty/Sims4CommunityLibrary
|
684f28dc3c7deb4d9fd520e21e63942b65a91d31
|
[
"CC-BY-4.0"
] | 28
|
2019-09-07T04:11:05.000Z
|
2022-02-07T18:31:40.000Z
|
"""
The Sims 4 Community Library is licensed under the Creative Commons Attribution 4.0 International public license (CC BY 4.0).
https://creativecommons.org/licenses/by/4.0/
https://creativecommons.org/licenses/by/4.0/legalcode
Copyright (c) COLONOLNUTTY
"""
from typing import Tuple
from event_testing.resolver import SingleSimResolver, DoubleSimResolver
from interactions.utils.loot import LootActions
from sims.sim_info import SimInfo
from sims4communitylib.utils.resources.common_loot_action_utils import CommonLootActionUtils
class CommonSimLootActionUtils:
"""Utilities for manipulating Loot Actions for Sims."""
@staticmethod
def apply_loot_actions_to_sim(loot_actions: LootActions, sim_info: SimInfo) -> bool:
"""apply_loot_actions_to_sim(loot_actions, sim_info)
Apply loot actions to a Sim.
:param loot_actions: The loot actions to apply.
:type loot_actions: LootActions
:param sim_info: The Sim to apply the loot actions to.
:type sim_info: SimInfo
:return: True, if the loot actions applied successfully. False, if not.
:rtype: bool
"""
if sim_info is None:
return False
return CommonLootActionUtils.apply_loot_actions_using_resolver(loot_actions, SingleSimResolver(sim_info))
@staticmethod
def apply_loot_actions_by_id_to_sim(loot_actions_id: int, sim_info: SimInfo) -> bool:
"""apply_loot_actions_by_id_to_sim(loot_actions_id, sim_info)
Apply loot actions to a Sim.
:param loot_actions_id: The decimal identifier of a loot actions instance to apply.
:type loot_actions_id: int
:param sim_info: The Sim to apply the loot actions to.
:type sim_info: SimInfo
:return: True, if the loot actions applied successfully. False, if not.
:rtype: bool
"""
if sim_info is None:
return False
return CommonLootActionUtils.apply_loot_actions_by_id_using_resolver(loot_actions_id, SingleSimResolver(sim_info))
@staticmethod
def apply_loot_actions_by_ids_to_sim(loot_actions_ids: Tuple[int], sim_info: SimInfo) -> bool:
"""apply_loot_actions_by_ids_to_sim(loot_actions_ids, sim_info)
Apply loot actions to a Sim.
:param loot_actions_ids: The decimal identifiers of the loot actions to apply.
:type loot_actions_ids: Tuple[int]
:param sim_info: The Sim to apply the loot actions to.
:type sim_info: SimInfo
:return: True, if the loot actions applied successfully. False, if not.
:rtype: bool
"""
if sim_info is None:
return False
return CommonLootActionUtils.apply_loot_actions_by_ids_using_resolver(loot_actions_ids, SingleSimResolver(sim_info))
@staticmethod
def apply_loot_actions_to_duo_sims(loot_actions: LootActions, sim_info_actor: SimInfo, sim_info_target: SimInfo) -> bool:
"""apply_loot_actions_to_duo_sims(loot_actions, sim_info_actor, sim_info_target)
Apply loot actions to two Sims at once.
:param loot_actions: The loot actions to apply.
:type loot_actions: LootActions
:param sim_info_actor: The Actor Sim to apply the loot actions to.
:type sim_info_actor: SimInfo
:param sim_info_target: The Target Sim to apply the loot actions to.
:type sim_info_target: SimInfo
:return: True, if the loot actions applied successfully. False, if not.
:rtype: bool
"""
if sim_info_actor is None or sim_info_target is None:
return False
return CommonLootActionUtils.apply_loot_actions_using_resolver(loot_actions, DoubleSimResolver(sim_info_actor, sim_info_target))
@staticmethod
def apply_loot_actions_by_id_to_duo_sims(loot_actions_id: int, sim_info_actor: SimInfo, sim_info_target: SimInfo) -> bool:
"""apply_loot_actions_by_id_to_duo_sims(loot_actions_id, sim_info_actor, sim_info_target)
Apply loot actions by decimal identifier to two Sims at once.
:param loot_actions_id: The decimal identifier of a loot actions instance to apply.
:type loot_actions_id: int
:param sim_info_actor: The Actor Sim to apply the loot actions to.
:type sim_info_actor: SimInfo
:param sim_info_target: The Target Sim to apply the loot actions to.
:type sim_info_target: SimInfo
:return: True, if the loot actions applied successfully. False, if not.
:rtype: bool
"""
if sim_info_actor is None or sim_info_target is None:
return False
return CommonLootActionUtils.apply_loot_actions_by_id_using_resolver(loot_actions_id, DoubleSimResolver(sim_info_actor, sim_info_target))
@staticmethod
def apply_loot_actions_by_ids_to_duo_sims(loot_actions_ids: Tuple[int], sim_info_actor: SimInfo, sim_info_target: SimInfo) -> bool:
"""apply_loot_actions_by_id_to_duo_sims(loot_actions_ids, sim_info_actor, sim_info_target)
Apply loot actions by decimal identifiers to two Sims at once.
:param loot_actions_ids: The decimal identifiers of the loot actions to apply.
:type loot_actions_ids: Tuple[int]
:param sim_info_actor: The Actor Sim to apply the loot actions to.
:type sim_info_actor: SimInfo
:param sim_info_target: The Target Sim to apply the loot actions to.
:type sim_info_target: SimInfo
:return: True, if the loot actions applied successfully. False, if not.
:rtype: bool
"""
if sim_info_actor is None or sim_info_target is None:
return False
return CommonLootActionUtils.apply_loot_actions_by_ids_using_resolver(loot_actions_ids, DoubleSimResolver(sim_info_actor, sim_info_target))
| 46.248
| 147
| 0.724269
| 816
| 5,781
| 4.828431
| 0.104167
| 0.212183
| 0.097462
| 0.063959
| 0.883503
| 0.877919
| 0.871574
| 0.83401
| 0.797208
| 0.756345
| 0
| 0.002206
| 0.21588
| 5,781
| 124
| 148
| 46.620968
| 0.866976
| 0.508044
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.138889
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 1
| 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
| 0
| 1
| 0
|
0
| 8
|
694a160d8386cbaecd982660c48b93e1a8f1e1db
| 13,191
|
py
|
Python
|
src/climsoft_api/api/form_synoptic_2_ra1/schema.py
|
opencdms/climsoft-api
|
860656423f78a2360ea7a581ea1642f6c3acb442
|
[
"MIT"
] | null | null | null |
src/climsoft_api/api/form_synoptic_2_ra1/schema.py
|
opencdms/climsoft-api
|
860656423f78a2360ea7a581ea1642f6c3acb442
|
[
"MIT"
] | 2
|
2022-01-16T15:41:27.000Z
|
2022-01-30T18:37:13.000Z
|
src/climsoft_api/api/form_synoptic_2_ra1/schema.py
|
openclimateinitiative/climsoft-api
|
3591d7499dd7777617b8086332dc83fab1af9588
|
[
"MIT"
] | 2
|
2021-12-22T21:50:19.000Z
|
2022-01-28T12:53:32.000Z
|
from pydantic import BaseModel, Field, constr
import datetime
from climsoft_api.api.schema import Response
from typing import Optional, List
field_mapping = {
"stationId": "station_id",
"entryDatetime": "entry_datetime",
"Val_Elem106": "val_elem106",
"Val_Elem107": "val_elem107",
"Val_Elem400": "val_elem400",
"Val_Elem814": "val_elem814",
"Val_Elem399": "val_elem399",
"Val_Elem301": "val_elem301",
"Val_Elem185": "val_elem185",
"Val_Elem101": "val_elem101",
"Val_Elem102": "val_elem102",
"Val_Elem103": "val_elem103",
"Val_Elem105": "val_elem105",
"Val_Elem192": "val_elem192",
"Val_Elem110": "val_elem110",
"Val_Elem114": "val_elem114",
"Val_Elem112": "val_elem112",
"Val_Elem111": "val_elem111",
"Val_Elem167": "val_elem167",
"Val_Elem197": "val_elem197",
"Val_Elem193": "val_elem193",
"Val_Elem115": "val_elem115",
"Val_Elem168": "val_elem168",
"Val_Elem169": "val_elem169",
"Val_Elem170": "val_elem170",
"Val_Elem171": "val_elem171",
"Val_Elem119": "val_elem119",
"Val_Elem116": "val_elem116",
"Val_Elem117": "val_elem117",
"Val_Elem118": "val_elem118",
"Val_Elem123": "val_elem123",
"Val_Elem120": "val_elem120",
"Val_Elem121": "val_elem121",
"Val_Elem122": "val_elem122",
"Val_Elem127": "val_elem127",
"Val_Elem124": "val_elem124",
"Val_Elem125": "val_elem125",
"Val_Elem126": "val_elem126",
"Val_Elem131": "val_elem131",
"Val_Elem128": "val_elem128",
"Val_Elem129": "val_elem129",
"Val_Elem130": "val_elem130",
"Val_Elem002": "val_elem002",
"Val_Elem003": "val_elem003",
"Val_Elem099": "val_elem099",
"Val_Elem018": "val_elem018",
"Val_Elem084": "val_elem084",
"Val_Elem132": "val_elem132",
"Val_Elem005": "val_elem005",
"Val_Elem174": "val_elem174",
"Val_Elem046": "val_elem046",
"Flag106": "flag106",
"Flag107": "flag107",
"Flag400": "flag400",
"Flag814": "flag814",
"Flag399": "flag399",
"Flag301": "flag301",
"Flag185": "flag185",
"Flag101": "flag101",
"Flag102": "flag102",
"Flag103": "flag103",
"Flag105": "flag105",
"Flag192": "flag192",
"Flag110": "flag110",
"Flag114": "flag114",
"Flag112": "flag112",
"Flag111": "flag111",
"Flag167": "flag167",
"Flag197": "flag197",
"Flag193": "flag193",
"Flag115": "flag115",
"Flag168": "flag168",
"Flag169": "flag169",
"Flag170": "flag170",
"Flag171": "flag171",
"Flag119": "flag119",
"Flag116": "flag116",
"Flag117": "flag117",
"Flag118": "flag118",
"Flag123": "flag123",
"Flag120": "flag120",
"Flag121": "flag121",
"Flag122": "flag122",
"Flag127": "flag127",
"Flag124": "flag124",
"Flag125": "flag125",
"Flag126": "flag126",
"Flag131": "flag131",
"Flag128": "flag128",
"Flag129": "flag129",
"Flag130": "flag130",
"Flag002": "flag002",
"Flag003": "flag003",
"Flag099": "flag099",
"Flag018": "flag018",
"Flag084": "flag084",
"Flag132": "flag132",
"Flag005": "flag005",
"Flag174": "flag174",
"Flag046": "flag046",
}
class CreateFormSynoptic2Ra1(BaseModel):
stationId: constr(max_length=50)
yyyy: int
mm: int
dd: int
hh: int
Val_Elem106: Optional[constr(max_length=6)]
Val_Elem107: Optional[constr(max_length=6)]
Val_Elem400: Optional[constr(max_length=6)]
Val_Elem814: Optional[constr(max_length=6)]
Val_Elem399: Optional[constr(max_length=6)]
Val_Elem301: Optional[constr(max_length=6)]
Val_Elem185: Optional[constr(max_length=6)]
Val_Elem101: Optional[constr(max_length=6)]
Val_Elem102: Optional[constr(max_length=6)]
Val_Elem103: Optional[constr(max_length=6)]
Val_Elem105: Optional[constr(max_length=6)]
Val_Elem192: Optional[constr(max_length=6)]
Val_Elem110: Optional[constr(max_length=6)]
Val_Elem114: Optional[constr(max_length=6)]
Val_Elem112: Optional[constr(max_length=6)]
Val_Elem111: Optional[constr(max_length=6)]
Val_Elem167: Optional[constr(max_length=6)]
Val_Elem197: Optional[constr(max_length=6)]
Val_Elem193: Optional[constr(max_length=6)]
Val_Elem115: Optional[constr(max_length=6)]
Val_Elem168: Optional[constr(max_length=6)]
Val_Elem169: Optional[constr(max_length=6)]
Val_Elem170: Optional[constr(max_length=6)]
Val_Elem171: Optional[constr(max_length=6)]
Val_Elem119: Optional[constr(max_length=6)]
Val_Elem116: Optional[constr(max_length=6)]
Val_Elem117: Optional[constr(max_length=6)]
Val_Elem118: Optional[constr(max_length=6)]
Val_Elem123: Optional[constr(max_length=6)]
Val_Elem120: Optional[constr(max_length=6)]
Val_Elem121: Optional[constr(max_length=6)]
Val_Elem122: Optional[constr(max_length=6)]
Val_Elem127: Optional[constr(max_length=6)]
Val_Elem124: Optional[constr(max_length=6)]
Val_Elem125: Optional[constr(max_length=6)]
Val_Elem126: Optional[constr(max_length=6)]
Val_Elem131: Optional[constr(max_length=6)]
Val_Elem128: Optional[constr(max_length=6)]
Val_Elem129: Optional[constr(max_length=6)]
Val_Elem130: Optional[constr(max_length=6)]
Val_Elem002: Optional[constr(max_length=6)]
Val_Elem003: Optional[constr(max_length=6)]
Val_Elem099: Optional[constr(max_length=6)]
Val_Elem018: Optional[constr(max_length=6)]
Val_Elem084: Optional[constr(max_length=6)]
Val_Elem132: Optional[constr(max_length=6)]
Val_Elem005: Optional[constr(max_length=6)]
Val_Elem174: Optional[constr(max_length=6)]
Val_Elem046: Optional[constr(max_length=6)]
Flag106: Optional[constr(max_length=1)]
Flag107: Optional[constr(max_length=1)]
Flag400: Optional[constr(max_length=1)]
Flag814: Optional[constr(max_length=1)]
Flag399: Optional[constr(max_length=1)]
Flag301: Optional[constr(max_length=1)]
Flag185: Optional[constr(max_length=1)]
Flag101: Optional[constr(max_length=1)]
Flag102: Optional[constr(max_length=1)]
Flag103: Optional[constr(max_length=1)]
Flag105: Optional[constr(max_length=1)]
Flag192: Optional[constr(max_length=1)]
Flag110: Optional[constr(max_length=1)]
Flag114: Optional[constr(max_length=1)]
Flag112: Optional[constr(max_length=1)]
Flag111: Optional[constr(max_length=1)]
Flag167: Optional[constr(max_length=1)]
Flag197: Optional[constr(max_length=1)]
Flag193: Optional[constr(max_length=1)]
Flag115: Optional[constr(max_length=1)]
Flag168: Optional[constr(max_length=1)]
Flag169: Optional[constr(max_length=1)]
Flag170: Optional[constr(max_length=1)]
Flag171: Optional[constr(max_length=1)]
Flag119: Optional[constr(max_length=1)]
Flag116: Optional[constr(max_length=1)]
Flag117: Optional[constr(max_length=1)]
Flag118: Optional[constr(max_length=1)]
Flag123: Optional[constr(max_length=1)]
Flag120: Optional[constr(max_length=1)]
Flag121: Optional[constr(max_length=1)]
Flag122: Optional[constr(max_length=1)]
Flag127: Optional[constr(max_length=1)]
Flag124: Optional[constr(max_length=1)]
Flag125: Optional[constr(max_length=1)]
Flag126: Optional[constr(max_length=1)]
Flag131: Optional[constr(max_length=1)]
Flag128: Optional[constr(max_length=1)]
Flag129: Optional[constr(max_length=1)]
Flag130: Optional[constr(max_length=1)]
Flag002: Optional[constr(max_length=1)]
Flag003: Optional[constr(max_length=1)]
Flag099: Optional[constr(max_length=1)]
Flag018: Optional[constr(max_length=1)]
Flag084: Optional[constr(max_length=1)]
Flag132: Optional[constr(max_length=1)]
Flag005: Optional[constr(max_length=1)]
Flag174: Optional[constr(max_length=1)]
Flag046: Optional[constr(max_length=1)]
signature: Optional[constr(max_length=45)]
entryDatetime: Optional[datetime.datetime]
class Config:
allow_population_by_field_name = True
fields = field_mapping
class UpdateFormSynoptic2Ra1(BaseModel):
Val_Elem106: Optional[constr(max_length=6)]
Val_Elem107: Optional[constr(max_length=6)]
Val_Elem400: Optional[constr(max_length=6)]
Val_Elem814: Optional[constr(max_length=6)]
Val_Elem399: Optional[constr(max_length=6)]
Val_Elem301: Optional[constr(max_length=6)]
Val_Elem185: Optional[constr(max_length=6)]
Val_Elem101: Optional[constr(max_length=6)]
Val_Elem102: Optional[constr(max_length=6)]
Val_Elem103: Optional[constr(max_length=6)]
Val_Elem105: Optional[constr(max_length=6)]
Val_Elem192: Optional[constr(max_length=6)]
Val_Elem110: Optional[constr(max_length=6)]
Val_Elem114: Optional[constr(max_length=6)]
Val_Elem112: Optional[constr(max_length=6)]
Val_Elem111: Optional[constr(max_length=6)]
Val_Elem167: Optional[constr(max_length=6)]
Val_Elem197: Optional[constr(max_length=6)]
Val_Elem193: Optional[constr(max_length=6)]
Val_Elem115: Optional[constr(max_length=6)]
Val_Elem168: Optional[constr(max_length=6)]
Val_Elem169: Optional[constr(max_length=6)]
Val_Elem170: Optional[constr(max_length=6)]
Val_Elem171: Optional[constr(max_length=6)]
Val_Elem119: Optional[constr(max_length=6)]
Val_Elem116: Optional[constr(max_length=6)]
Val_Elem117: Optional[constr(max_length=6)]
Val_Elem118: Optional[constr(max_length=6)]
Val_Elem123: Optional[constr(max_length=6)]
Val_Elem120: Optional[constr(max_length=6)]
Val_Elem121: Optional[constr(max_length=6)]
Val_Elem122: Optional[constr(max_length=6)]
Val_Elem127: Optional[constr(max_length=6)]
Val_Elem124: Optional[constr(max_length=6)]
Val_Elem125: Optional[constr(max_length=6)]
Val_Elem126: Optional[constr(max_length=6)]
Val_Elem131: Optional[constr(max_length=6)]
Val_Elem128: Optional[constr(max_length=6)]
Val_Elem129: Optional[constr(max_length=6)]
Val_Elem130: Optional[constr(max_length=6)]
Val_Elem002: Optional[constr(max_length=6)]
Val_Elem003: Optional[constr(max_length=6)]
Val_Elem099: Optional[constr(max_length=6)]
Val_Elem018: Optional[constr(max_length=6)]
Val_Elem084: Optional[constr(max_length=6)]
Val_Elem132: Optional[constr(max_length=6)]
Val_Elem005: Optional[constr(max_length=6)]
Val_Elem174: Optional[constr(max_length=6)]
Val_Elem046: Optional[constr(max_length=6)]
Flag106: Optional[constr(max_length=1)]
Flag107: Optional[constr(max_length=1)]
Flag400: Optional[constr(max_length=1)]
Flag814: Optional[constr(max_length=1)]
Flag399: Optional[constr(max_length=1)]
Flag301: Optional[constr(max_length=1)]
Flag185: Optional[constr(max_length=1)]
Flag101: Optional[constr(max_length=1)]
Flag102: Optional[constr(max_length=1)]
Flag103: Optional[constr(max_length=1)]
Flag105: Optional[constr(max_length=1)]
Flag192: Optional[constr(max_length=1)]
Flag110: Optional[constr(max_length=1)]
Flag114: Optional[constr(max_length=1)]
Flag112: Optional[constr(max_length=1)]
Flag111: Optional[constr(max_length=1)]
Flag167: Optional[constr(max_length=1)]
Flag197: Optional[constr(max_length=1)]
Flag193: Optional[constr(max_length=1)]
Flag115: Optional[constr(max_length=1)]
Flag168: Optional[constr(max_length=1)]
Flag169: Optional[constr(max_length=1)]
Flag170: Optional[constr(max_length=1)]
Flag171: Optional[constr(max_length=1)]
Flag119: Optional[constr(max_length=1)]
Flag116: Optional[constr(max_length=1)]
Flag117: Optional[constr(max_length=1)]
Flag118: Optional[constr(max_length=1)]
Flag123: Optional[constr(max_length=1)]
Flag120: Optional[constr(max_length=1)]
Flag121: Optional[constr(max_length=1)]
Flag122: Optional[constr(max_length=1)]
Flag127: Optional[constr(max_length=1)]
Flag124: Optional[constr(max_length=1)]
Flag125: Optional[constr(max_length=1)]
Flag126: Optional[constr(max_length=1)]
Flag131: Optional[constr(max_length=1)]
Flag128: Optional[constr(max_length=1)]
Flag129: Optional[constr(max_length=1)]
Flag130: Optional[constr(max_length=1)]
Flag002: Optional[constr(max_length=1)]
Flag003: Optional[constr(max_length=1)]
Flag099: Optional[constr(max_length=1)]
Flag018: Optional[constr(max_length=1)]
Flag084: Optional[constr(max_length=1)]
Flag132: Optional[constr(max_length=1)]
Flag005: Optional[constr(max_length=1)]
Flag174: Optional[constr(max_length=1)]
Flag046: Optional[constr(max_length=1)]
signature: Optional[constr(max_length=45)]
entryDatetime: Optional[datetime.datetime]
class Config:
allow_population_by_field_name = True
fields = field_mapping
class FormSynoptic2Ra1(CreateFormSynoptic2Ra1):
class Config:
allow_population_by_field_name = True
fields = field_mapping
orm_mode = True
class FormSynoptic2Ra1Response(Response):
result: List[FormSynoptic2Ra1] = Field(title="Result")
class FormSynoptic2Ra1QueryResponse(FormSynoptic2Ra1Response):
limit: int = Field(title="Limit")
page: int = Field(title="Page")
pages: int = Field(title="Pages")
| 38.234783
| 62
| 0.706694
| 1,701
| 13,191
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| 0.33513
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| 13,191
| 344
| 63
| 38.34593
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| 0.633333
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| 0.138731
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| 0
| 0
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| 0
| 0
| 1
| 0
| false
| 0
| 0.012121
| 0
| 0.669697
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
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| 1
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0
| 9
|
695b40bd76a214fb1030f620dbef4ff22b9933c6
| 46,129
|
py
|
Python
|
casty.py
|
thekeshavgoel/Casty
|
6a6d16173257f26047005a6b24c30cdcf2839b1d
|
[
"MIT"
] | 1
|
2020-04-29T11:07:53.000Z
|
2020-04-29T11:07:53.000Z
|
casty.py
|
thekeshavgoel/Casty
|
6a6d16173257f26047005a6b24c30cdcf2839b1d
|
[
"MIT"
] | null | null | null |
casty.py
|
thekeshavgoel/Casty
|
6a6d16173257f26047005a6b24c30cdcf2839b1d
|
[
"MIT"
] | null | null | null |
import json
import numpy as np
import pandas as pd
import re
import random
import math
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
from sklearn import linear_model
from sklearn.naive_bayes import MultinomialNB
from sklearn.metrics import accuracy_score
from sklearn.metrics import precision_score
from sklearn.model_selection import train_test_split
from sklearn.decomposition import TruncatedSVD
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import Normalizer
from scipy import stats
from sklearn.ensemble import RandomForestClassifier
from sklearn.svm import SVC
from sklearn.svm import LinearSVC
from sklearn.model_selection import cross_val_score
from sklearn.metrics import roc_curve, auc
from sklearn.metrics import precision_recall_curve
from sklearn.metrics import average_precision_score
from sklearn.metrics import roc_auc_score
from sklearn.svm import SVC
from sklearn.metrics import precision_recall_fscore_support
# import matplotlib.pyplot as plt
# import MySQLdb
import gc
df = pd.read_csv("movie.csv")
actor = pd.read_csv("actor_new.csv")
actress = pd.read_csv("actress_new.csv")
mcast = pd.read_csv("male_cast.csv")
fcast = pd.read_csv("female_cast.csv")
mc = mcast.copy()
mc = mc.set_index('movie_id')
fc = fcast.copy()
fc = fc.set_index('movie_id')
names = pd.read_csv("name_all.csv")
names = names.set_index('Id')
df = df.set_index('Id')
df['Cast'] = mc['group_concat(person_id)'] + "," + fc['group_concat(person_id)']
col = df.columns.tolist()
# col = col[:2]+col[4:13]+col[14:17]+col[-1:]+col[2:4]+col[13:14]
col = col[:1]+col[3:12]+col[13:15]+col[-1:]+col[1:3]+col[12:13]+col[15:17]
df = df[col]
#break countries string into array
df[col[1:13]] = df[col[1:13]].replace(np.nan, '', regex=True)
df[col[1:13]] = df[col[1:13]].fillna(value='')
for i in range(1, 13):
df[col[i]] = df[col[i]].apply(lambda x: x.split(",") if len(x)>0 else [])
df[col[i]] = df[col[i]].apply(lambda x: [col[i][:3]+e.strip() if len(e.strip())>0 else e.strip() for e in x] if len(x)>0 else [])
counts = actor.person_id.value_counts(sort=True).copy()
fcounts = actress.person_id.value_counts(sort=True).copy()
def actorsCount(fname, lname):
counts = actor.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 30 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
fcounts = actress.person_id.value_counts(sort=True).copy()
fnewCount = fcounts.where( fcounts > 4 )
fnewCount = fnewCount.dropna()
p_ids = p_ids + fnewCount.index.tolist()
counts = pd.concat([newCount, fnewCount])
cur.execute("Select id, name from name where lower(name) like '%"+fname+"%' and lower(name) like '%"+lname+"%'")
arr = {}
for row in cur:
arr[int(row[0])] = row[1]
all_ids = arr.keys()
intersection = np.intersect1d(all_ids, p_ids)
user_ids = []
for i in intersection:
user_ids.append([i, arr[i].decode('utf8').encode('ascii', errors='ignore'), counts[i]])
return user_ids
def findActor(fname, lname):
found = names[names['Name'].str.contains(".*"+lname+".*"+fname+".*", regex=True, case=False)]
id_found = found.index
users = []
c_ind = counts.index
f_ind = fcounts.index
for i in id_found:
if i in c_ind:
users.append([i, names.loc[i]['Name'].decode('utf8').encode('ascii', errors='ignore'), counts[i]])
else:
users.append([i, names.loc[i]['Name'].decode('utf8').encode('ascii', errors='ignore'), fcounts[i]])
return users
def logreg(actor_id, lg=0):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx+len_inds/2]
else:
p_ids = idxs[idx:idx+len_inds]
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
X = movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
X_train, X_test, y_train, y_test = train_test_split(X, 1*y, test_size=0.33)
X_train_tfidf = tfidf.fit_transform(X_train)
X_test_tfidf = tfidf.transform(X_test)
# logreg = linear_model.LogisticRegression()
# logreg = LinearSVC(random_state=0, C=100000, fit_intercept=False, tol=0)
logreg = linear_model.LogisticRegression(C=200, penalty='l1', fit_intercept=False)
# logreg = RandomForestClassifier(n_estimators=100, random_state=0)
# logreg = SVC(C=3200)
logreg.fit(X_train_tfidf, y_train)
y_pred = logreg.predict(X_test_tfidf)
# sum(y_pred)*1.0/sum(y_test)
yt = np.where(y_test ==1)
yn = np.where(y_pred ==1)
yf = np.intersect1d(yt[0], yn[0])
#movies
proba = logreg.predict_proba(X_test_tfidf)
top10_idx = np.argsort(proba[:, 1])[-10:][::-1]
if lg == 1:
top10_idx = np.argsort(proba[:, 1])[-20:][::-1]
indc = np.array(y_test.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
y_score = logreg.decision_function(X_test_tfidf)
fpr, tpr, _ = roc_curve(y_test, y_score)
roc_auc = auc(fpr, tpr)
# plt.figure()
# lw = 2
# plt.plot(fpr, tpr, color='darkorange', lw=lw, label='ROC curve (area = %0.2f)' % roc_auc)
# plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
# plt.xlim([0.0, 1.0])
# plt.ylim([0.0, 1.05])
# plt.xlabel('False Positive Rate')
# plt.ylabel('True Positive Rate')
# plt.title('Receiver operating characteristic example')
# plt.legend(loc="lower right")
# plt.savefig(str(actor_id)+".png")
return [[len(y_train), len(y_test)], [i.decode('utf8').encode('ascii', errors='ignore') for i in df.loc[inxs].Title.tolist()], proba[top10_idx, 1], y_pred[top10_idx], y_test.values[top10_idx], [sum(y_train), sum(y_test), sum(y_pred), len(yf)]]
def svmc(actor_id, lg=0):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx+len_inds/2]
else:
p_ids = idxs[idx:idx+len_inds]
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
# movies['features'] = df[col[3:14]+['Cast']].values.tolist()
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
X = movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
X_train, X_test, y_train, y_test = train_test_split(X, 1*y, test_size=0.33)
X_train_tfidf = tfidf.fit_transform(X_train)
X_test_tfidf = tfidf.transform(X_test)
logreg = SVC(C=3200, probability=True)
logreg.fit(X_train_tfidf, y_train)
y_pred = logreg.predict(X_test_tfidf)
yt = np.where(y_test ==1)
yn = np.where(y_pred ==1)
print yn
yf = np.intersect1d(yt[0], yn[0])
#movies
proba = logreg.predict_proba(X_test_tfidf)
top10_idx = np.argsort(proba[:, 1])[-10:][::-1]
if lg == 1:
top10_idx = np.argsort(proba[:, 1])[-20:][::-1]
indc = np.array(y_test.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
return [[len(y_train), len(y_test)], [i.decode('utf8').encode('ascii', errors='ignore') for i in df.loc[inxs].Title.tolist()], proba[top10_idx, 1], y_pred[top10_idx], y_test.values[top10_idx], [sum(y_train), sum(y_test), sum(y_pred), len(yf)]]
def jaccard_sim(actor_id, lg=0):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx] + idxs[idx+1:idx+len_inds/2]
else:
p_ids = idxs[idx+1:idx+len_inds]
col = df.columns.tolist()
#actor movies
orig_movie_ids = dataframe.loc[dataframe['person_id'] == actor_id]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
rndom = np.random.choice(orig_movie_ids, int(math.ceil(0.7*len(orig_movie_ids))), replace=False)
to_add = np.setdiff1d(orig_movie_ids, rndom)
movies_co = df.loc[df.index.isin(rndom)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
x_0 = movies['features'].tolist()
x_0 = [i for obj in x_0 for i in obj]
#job pool
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy().tolist()
orig_movie_ids = np.unique(orig_movie_ids).tolist() + to_add.tolist()
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
# tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
# X = [x_0] + movies['features'].tolist()
# y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
# y = y*1
X = movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
y = y*1
sim = np.zeros(len(X))
j=0
for i in X:
union = np.union1d(x_0, i)
inter = np.intersect1d(x_0, i)
if len(union) > 0:
sim[j] = (len(inter)*1.0)/len(union)
j = j+1
# X_tfidf = tfidf.fit_transform(X)
# feat_names = tfidf.get_feature_names()
# similarity = np.zeros((len(X)))
# for i in range(count):
# similarity += cosine_similarity(X_tfidf[0+i:i+1], X_tfidf)[0]
z = np.where(y == 1)
v = np.where(sim >0.0007)
yf = len(np.intersect1d(z[0], v))
y_pred = np.zeros(len(y))
y_pred[v] = 1
top10_idx = np.argsort(sim)[-10:][::-1]
if lg == 1:
top10_idx = np.argsort(sim)[-20:][9::-1]
top10_idx = [i for i in top10_idx]
indc = np.array(y.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
return [[len(rndom), len(to_add)], [i.decode('utf8').encode('ascii', errors='ignore') for i in df.loc[inxs].Title.tolist()], sim[top10_idx].tolist(), y_pred[top10_idx], y.values[top10_idx], [len(rndom), sum(y), sum(y_pred), yf]]
def cosine_sim(actor_id, lg=0):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx] + idxs[idx+1:idx+len_inds/2]
else:
p_ids = idxs[idx+1:idx+len_inds]
col = df.columns.tolist()
#actor movies
orig_movie_ids = dataframe.loc[dataframe['person_id'] == actor_id]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
rndom = np.random.choice(orig_movie_ids, int(math.ceil(0.7*len(orig_movie_ids))), replace=False)
to_add = np.setdiff1d(orig_movie_ids, rndom)
movies_co = df.loc[df.index.isin(rndom)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
x_0 = movies['features'].tolist()
x_0 = [i for obj in x_0 for i in obj]
#job pool
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy().tolist()
orig_movie_ids = np.unique(orig_movie_ids).tolist() + to_add.tolist()
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
X = [x_0] + movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
y = y*1
X_tfidf = tfidf.fit_transform(X)
# feat_names = tfidf.get_feature_names()
# similarity = np.zeros((len(X)))
# for i in range(count):
# similarity += cosine_similarity(X_tfidf[0+i:i+1], X_tfidf)[0]
z = np.where(y == 1)
sim = cosine_similarity(X_tfidf[0:1], X_tfidf)[0]
v = np.where(sim >0.05)
v = np.setdiff1d(v, [0])
v = [i-1 for i in v]
yf = len(np.intersect1d(z[0], v))
y_pred = np.zeros(len(y))
y_pred[v] = 1
top10_idx = np.argsort(sim)[-10:][::-1]
if lg == 1:
top10_idx = np.argsort(sim)[-20:][9::-1]
top10_idx = [i for i in top10_idx]
indc = np.array(y.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
return [[len(rndom), len(to_add)], [i.decode('utf8').encode('ascii', errors='ignore') for i in df.loc[inxs].Title.tolist()], sim[top10_idx].tolist(), y_pred[top10_idx], y.values[top10_idx], [len(rndom), sum(y), sum(y_pred), yf]]
def pearson_sim(actor_id, lg=0):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx] + idxs[idx+1:idx+len_inds/2]
else:
p_ids = idxs[idx+1:idx+len_inds]
col = df.columns.tolist()
#actor movies
orig_movie_ids = dataframe.loc[dataframe['person_id'] == actor_id]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
rndom = np.random.choice(orig_movie_ids, int(math.ceil(0.7*len(orig_movie_ids))), replace=False)
to_add = np.setdiff1d(orig_movie_ids, rndom)
movies_co = df.loc[df.index.isin(rndom)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
x_0 = movies['features'].tolist()
x_0 = [i for obj in x_0 for i in obj]
#job pool
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy().tolist()
orig_movie_ids = np.unique(orig_movie_ids).tolist() + to_add.tolist()
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
X = [x_0] + movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
y = y*1
X_tfidf = tfidf.fit_transform(X)
# feat_names = tfidf.get_feature_names()
# similarity = np.zeros((len(X)))
# for i in range(count):
# similarity += cosine_similarity(X_tfidf[0+i:i+1], X_tfidf)[0]
z = np.where(y == 1)
sim = np.corrcoef(X_tfidf.A[0:1], X_tfidf.A)[0]
v = np.where(sim >0.0)
v = np.setdiff1d(v, [0])
v = [i-1 for i in v]
yf = len(np.intersect1d(z[0], v))
y_pred = np.zeros(len(y))
y_pred[v] = 1
top10_idx = np.argsort(sim)[-10:][::-1]
if lg == 1:
top10_idx = np.argsort(sim)[-20:][9::-1]
top10_idx = [i for i in top10_idx]
indc = np.array(y.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
return [[len(rndom), len(to_add)], [i.decode('utf8').encode('ascii', errors='ignore') for i in df.loc[inxs].Title.tolist()], sim[top10_idx].tolist(), y_pred[top10_idx], y.values[top10_idx], [sum(rndom), sum(y), sum(y_pred), yf]]
def logreg_filer(actor_id):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx+len_inds/2]
else:
p_ids = idxs[idx:idx+len_inds]
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: [i if i != col[12][3]+str(actor_id) else '' for i in x ] if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
# movies['features'] = df[col[3:14]+['Cast']].values.tolist()
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
X = movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
X_train, X_test, y_train, y_test = train_test_split(X, 1*y, test_size=0.33)
X_train_tfidf = tfidf.fit_transform(X_train)
X_test_tfidf = tfidf.transform(X_test)
# logreg = linear_model.LogisticRegression()
# logreg = linear_model.LogisticRegression(C=200, penalty='l1', fit_intercept=False)
# logreg = RandomForestClassifier(n_estimators=100, random_state=0)
logreg = SVC(C=3200, probability=True)
logreg.fit(X_train_tfidf, y_train)
y_pred = logreg.predict(X_test_tfidf)
# sum(y_pred)*1.0/sum(y_test)
yt = np.where(y_test ==1)
yn = np.where(y_pred ==1)
yf = np.intersect1d(yt[0], yn[0])
yf_arr = 0
if (sum(y_test) >0 ):
yf_arr = len(yf)*1.0/sum(y_test)
scores = cross_val_score(logreg, tfidf.fit_transform(X), y*1, cv=5)
if sum(y_test) > 0:
y_score = logreg.decision_function(X_test_tfidf)
fpr, tpr,_ = roc_curve(y_test, y_score)
roc_auc = roc_auc_score(y_test, y_score)
avg_prc = average_precision_score(y_test, y_score)
prec, recall, _ = precision_recall_curve(y_test, y_score)
y_score = y_score.tolist()
prec = prec.tolist()
recall = recall.tolist()
else:
y_score = []
fpr, tpr = 0,0
roc_auc = 0
avg_prc = 0
prec, recall = [],[]
#movies
proba = logreg.predict_proba(X_test_tfidf)
top10_idx = np.argsort(proba[:, 1])[-10:][::-1]
indc = np.array(y_test.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
return [counts[actor_id], inxs.tolist(), yf_arr, np.mean(scores), roc_auc, avg_prc, y_test.tolist(), y_pred.tolist(), y_score, prec, recall]
def logreg_lsa_filer(actor_id):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx+len_inds/2]
else:
p_ids = idxs[idx:idx+len_inds]
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
X = movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
svd = TruncatedSVD(200)
lsa = make_pipeline(svd, Normalizer(copy=False))
X_train, X_test, y_train, y_test = train_test_split(X, 1*y, test_size=0.33)
X_train_tfidf = tfidf.fit_transform(X_train)
X_test_tfidf = tfidf.transform(X_test)
feat_names = tfidf.get_feature_names()
X_train_lsa = lsa.fit_transform(X_train_tfidf)
explained_variance = svd.explained_variance_ratio_.sum()
X_test_lsa = lsa.transform(X_test_tfidf)
# logreg = linear_model.LogisticRegression()
# logreg = linear_model.LogisticRegression(C=200, penalty='l1', fit_intercept=False)
# logreg = RandomForestClassifier(n_estimators=100, random_state=0)
# logreg = RandomForestClassifier(n_estimators=100, random_state=0)
logreg = SVC(C=3200, probability=True)
logreg.fit(X_train_lsa, y_train)
y_pred = logreg.predict(X_test_lsa)
# sum(y_pred)*1.0/sum(y_test)
yt = np.where(y_test ==1)
yn = np.where(y_pred ==1)
yf = np.intersect1d(yt[0], yn[0])
yf_arr = 0
if (sum(y_test) >0 ):
yf_arr = len(yf)*1.0/sum(y_test)
scores = cross_val_score(logreg, tfidf.fit_transform(X), y*1, cv=5)
if sum(y_test) > 0:
y_score = logreg.decision_function(X_test_lsa)
fpr, tpr,_ = roc_curve(y_test, y_score)
roc_auc = roc_auc_score(y_test, y_score)
avg_prc = average_precision_score(y_test, y_score)
prec, recall, _ = precision_recall_curve(y_test, y_score)
y_score = y_score.tolist()
prec = prec.tolist()
recall = recall.tolist()
else:
y_score = []
fpr, tpr = 0,0
roc_auc = 0
avg_prc = 0
prec, recall = [],[]
#movies
proba = logreg.predict_proba(X_test_lsa)
top10_idx = np.argsort(proba[:, 1])[-10:][::-1]
indc = np.array(y_test.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
return [counts[actor_id], inxs.tolist(), yf_arr, np.mean(scores), roc_auc, avg_prc, y_test.tolist(), y_pred.tolist(), y_score, prec, recall]
def cosine_sim_filer(actor_id):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx] + idxs[idx+1:idx+len_inds/2]
else:
p_ids = idxs[idx+1:idx+len_inds]
col = df.columns.tolist()
#actor movies
orig_movie_ids = dataframe.loc[dataframe['person_id'] == actor_id]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
rndom = np.random.choice(orig_movie_ids, int(math.ceil(0.7*len(orig_movie_ids))), replace=False)
to_add = np.setdiff1d(orig_movie_ids, rndom)
movies_co = df.loc[df.index.isin(rndom)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
x_0 = movies['features'].tolist()
x_0 = [i for obj in x_0 for i in obj]
#job pool
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy().tolist()
orig_movie_ids = np.unique(orig_movie_ids).tolist() + to_add.tolist()
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
X = [x_0] + movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
y = y*1
X_tfidf = tfidf.fit_transform(X)
# feat_names = tfidf.get_feature_names()
# similarity = np.zeros((len(X)))
# for i in range(count):
# similarity += cosine_similarity(X_tfidf[0+i:i+1], X_tfidf)[0]
z = np.where(y == 1)
sim = cosine_similarity(X_tfidf[0:1], X_tfidf)[0]
v = np.where(sim >0.05)
v = np.setdiff1d(v, [0])
v = [i-1 for i in v]
yf = len(np.intersect1d(z[0], v))
y_pred = np.zeros(len(y))
y_pred[v] = 1
top10_idx = np.argsort(sim)[-11:][9::-1]
top10_idx = [i-1 for i in top10_idx]
indc = np.array(y.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
if sum(y) > 0:
y_score = sim[1:]
roc_auc = roc_auc_score(y, y_score)
avg_prc = average_precision_score(y, y_score)
prec, recall, _, _ = precision_recall_fscore_support(y, y_pred)
prec = prec.tolist()
recall = recall.tolist()
yf_arr = (1.0*yf)/sum(y)
y_score = y_score.tolist()
else:
y_score = []
fpr, tpr = 0,0
roc_auc = 0
avg_prc = 0
prec, recall = [],[]
yf_arr = 0
return [counts[actor_id], inxs.tolist(), sim[top10_idx].tolist(), yf_arr, roc_auc, avg_prc, y.values.tolist(), y_pred.tolist(), y_score, prec, recall]
def pearson_sim_filer(actor_id):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx] + idxs[idx+1:idx+len_inds/2]
else:
p_ids = idxs[idx+1:idx+len_inds]
col = df.columns.tolist()
#actor movies
orig_movie_ids = dataframe.loc[dataframe['person_id'] == actor_id]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
rndom = np.random.choice(orig_movie_ids, int(math.ceil(0.7*len(orig_movie_ids))), replace=False)
to_add = np.setdiff1d(orig_movie_ids, rndom)
movies_co = df.loc[df.index.isin(rndom)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
x_0 = movies['features'].tolist()
x_0 = [i for obj in x_0 for i in obj]
#job pool
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy().tolist()
orig_movie_ids = np.unique(orig_movie_ids).tolist() + to_add.tolist()
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
X = [x_0] + movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
y = y*1
X_tfidf = tfidf.fit_transform(X)
# feat_names = tfidf.get_feature_names()
# similarity = np.zeros((len(X)))
# for i in range(count):
# similarity += cosine_similarity(X_tfidf[0+i:i+1], X_tfidf)[0]
z = np.where(y == 1)
sim = np.corrcoef(X_tfidf.A[0:1], X_tfidf.A)[0][1:]
sim = np.nan_to_num(sim)
v = np.where(sim >0)
v = np.setdiff1d(v, [0])
v = [i-1 for i in v]
yf = len(np.intersect1d(z[0], v))
y_pred = np.zeros(len(y))
y_pred[v] = 1
top10_idx = np.argsort(sim)[-11:][9::-1]
top10_idx = [i-1 for i in top10_idx]
indc = np.array(y.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
if sum(y) > 0:
y_score = sim[1:]
roc_auc = roc_auc_score(y, y_score)
avg_prc = average_precision_score(y, y_score)
prec, recall, _, _ = precision_recall_fscore_support(y, y_pred)
prec = prec.tolist()
recall = recall.tolist()
yf_arr = (1.0*yf)/sum(y)
y_score = y_score.tolist()
else:
y_score = []
fpr, tpr = 0,0
roc_auc = 0
avg_prc = 0
prec, recall = [],[]
yf_arr = 0
return [counts[actor_id], inxs.tolist(), sim[top10_idx].tolist(), yf_arr, roc_auc, avg_prc, y.values.tolist(), y_pred.tolist(), y_score, prec, recall]
def jaccard_sim_filer(actor_id):
counts = actor.person_id.value_counts(sort=True).copy()
dataframe = actor
a = np.where(counts.index == actor_id)
if len(a[0]) == 0:
counts = actress.person_id.value_counts(sort=True).copy()
dataframe = actress
idx = counts.index.get_loc(actor_id)
idxs = counts.index.tolist()
count = counts[actor_id]
len_inds = 1000/count
if idx > len_inds:
p_ids = idxs[idx-len_inds/2:idx] + idxs[idx+1:idx+len_inds/2]
else:
p_ids = idxs[idx+1:idx+len_inds]
col = df.columns.tolist()
#actor movies
orig_movie_ids = dataframe.loc[dataframe['person_id'] == actor_id]['movie_id'].values.copy()
orig_movie_ids = np.unique(orig_movie_ids)
rndom = np.random.choice(orig_movie_ids, int(math.ceil(0.7*len(orig_movie_ids))), replace=False)
to_add = np.setdiff1d(orig_movie_ids, rndom)
movies_co = df.loc[df.index.isin(rndom)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
x_0 = movies['features'].tolist()
x_0 = [i for obj in x_0 for i in obj]
#job pool
col = df.columns
orig_movie_ids = dataframe.loc[dataframe['person_id'].isin(p_ids)]['movie_id'].values.copy().tolist()
orig_movie_ids = np.unique(orig_movie_ids).tolist() + to_add.tolist()
movies_co = df.loc[df.index.isin(orig_movie_ids)].copy()
# movies_co[col[12]] = movies_co[col[12]].apply(lambda x: x.remove(col[12][3]+str(actor_id)) if len(x)>0 and col[12][3]+str(actor_id) in x else x )
movies_co[col[12]] = movies_co[col[12]].apply(lambda x: filter(lambda a: a != col[12][:3]+str(actor_id), x))
movies = pd.DataFrame()
col = df.columns.tolist()
movies['Id'] = movies_co.index
# df['Cast'] = cast.Cast
movies['features'] = movies_co[col[2:13]].values.tolist()
movies['features'] = movies['features'].apply(lambda x: [i for obj in x for i in obj])
# tfidf = TfidfVectorizer(preprocessor=lambda x: x, tokenizer=lambda x: x)
# X = [x_0] + movies['features'].tolist()
# y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
# y = y*1
X = movies['features'].tolist()
y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
y = y*1
sim = np.zeros(len(X))
j=0
for i in X:
union = np.union1d(x_0, i)
inter = np.intersect1d(x_0, i)
if len(union) > 0:
sim[j] = (len(inter)*1.0)/len(union)
j = j+1
# X_tfidf = tfidf.fit_transform(X)
# feat_names = tfidf.get_feature_names()
# similarity = np.zeros((len(X)))
# for i in range(count):
# similarity += cosine_similarity(X_tfidf[0+i:i+1], X_tfidf)[0]
z = np.where(y == 1)
v = np.where(sim >0.0007)
yf = len(np.intersect1d(z[0], v))
y_pred = np.zeros(len(y))
y_pred[v] = 1
top10_idx = np.argsort(sim)[-11:][9::-1]
top10_idx = [i for i in top10_idx]
indc = np.array(y.index.tolist())[top10_idx]
inxs = movies.iloc[indc].Id.values
if sum(y) > 0:
y_score = sim
roc_auc = roc_auc_score(y, y_score)
avg_prc = average_precision_score(y, y_score)
prec, recall, _, _ = precision_recall_fscore_support(y, y_pred)
prec = prec.tolist()
recall = recall.tolist()
yf_arr = (1.0*yf)/sum(y)
y_score = y_score.tolist()
else:
y_score = []
fpr, tpr = 0,0
roc_auc = 0
avg_prc = 0
prec, recall = [],[]
yf_arr = 0
return [counts[actor_id], inxs.tolist(), sim[top10_idx].tolist(), yf_arr, roc_auc, avg_prc, y.values.tolist(), y_pred.tolist(), y_score, prec, recall]
# X = movies['features'].tolist()
# y = movies['Id'].isin(dataframe.loc[dataframe['person_id']==actor_id]['movie_id'].values.tolist())
# X_train_tfidf, X_test_tfidf, y_train, y_test = train_test_split(X, 1*y, test_size=0.33)
# X_train = tfidf.fit_transform(X_train_tfidf)
# X_test= tfidf.transform(X_test_tfidf)
# indc = np.array(y_test.index.tolist())[yf]
# return [df.loc[indc].Title.tolist(), proba[yf, 1]]
# accuracy = accuracy_score(y_test, y_pred)
# prec = precision_score(y_test, y_pred, average='macro')
# proba = logreg.predict_log_proba(X_test)
# top10_idx = np.argsort(proba[:, 1])[-10:]
# top10_val = [proba[i, 1] for i in top10_idx]
# predicts = [y_pred[i] for i in top10_idx]
# tests = [y_test.tolist()[i] for i in top10_idx]
# print predicts
# print tests
# return [accuracy, prec]
def results_big_cosine():
counts = actor.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
c=0
res = dict()
j=0
for i in p_ids:
if c != newCount[i]:
j=0
if j<10:
print i
res[i] = cosine_sim_filer(i)
gc.collect()
c = newCount[i]
j = j+1
with open('cosine_Big-9Aug-Male.txt', 'w') as file:
file.write(json.dumps(res))
counts = actress.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
c=0
res = dict()
j=0
for i in p_ids:
if c != newCount[i]:
j=0
if j<10:
print i
res[i] = cosine_sim_filer(i)
gc.collect()
c = newCount[i]
j = j+1
with open('cosine_Big-9Aug-Female.txt', 'w') as file:
file.write(json.dumps(res))
def results_big_jaccard():
counts = actor.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
c=0
res = dict()
j=0
for i in p_ids:
if c != newCount[i]:
j=0
if j<10:
print i
res[i] = pearson_sim_filer(i)
gc.collect()
c = newCount[i]
j = j+1
with open('pearson_Big-10_Aug_Male.txt', 'w') as file:
file.write(json.dumps(res))
counts = actress.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
c=0
res = dict()
j=0
for i in p_ids:
if c != newCount[i]:
j=0
if j<10:
print i
res[i] = pearson_sim_filer(i)
gc.collect()
c = newCount[i]
j = j+1
with open('pearson_Big-10Aug_Female.txt', 'w') as file:
file.write(json.dumps(res))
def results_jaccard():
counts = actor.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts == 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
res = dict()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
newCount = counts.where( counts == 4 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
newCount = counts.where( counts == 3 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
newCount = counts.where( counts == 2 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
newCount = counts.where( counts == 1 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
with open('jaccard-24-Jul_Male.txt', 'w') as file:
file.write(json.dumps(res))
counts = actress.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts == 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
res = dict()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
newCount = counts.where( counts == 4 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
newCount = counts.where( counts == 3 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
newCount = counts.where( counts == 2 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
newCount = counts.where( counts == 1 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = jaccard_sim_filer(p_ids[i])
gc.collect()
with open('jaccard-24-Jul_Female.txt', 'w') as file:
file.write(json.dumps(res))
def results_cosine():
counts = actor.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts == 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
res = dict()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
newCount = counts.where( counts == 4 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
newCount = counts.where( counts == 3 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
newCount = counts.where( counts == 2 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
newCount = counts.where( counts == 1 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
with open('cosine-22-Jul_Male.txt', 'w') as file:
file.write(json.dumps(res))
counts = actress.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts == 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
res = dict()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
newCount = counts.where( counts == 4 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
newCount = counts.where( counts == 3 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
newCount = counts.where( counts == 2 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
newCount = counts.where( counts == 1 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
for i in range(100):
res[p_ids[i]] = cosine_sim(p_ids[i])
gc.collect()
with open('cosine-22-Jul_Female.txt', 'w') as file:
file.write(json.dumps(res))
def lsa_res():
counts = actor.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
c=0
res = dict()
j=0
for i in p_ids:
if c != newCount[i]:
j = 0
if j<10:
print i
res[i] = logreg_lsa_filer(i)
gc.collect()
c = newCount[i]
j = j+1
with open('resl/SVM-Lsa200-11-Aug_Male.txt', 'w') as file:
file.write(json.dumps(res))
counts = actress.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
c=0
res = dict()
j=0
for i in p_ids:
if c != newCount[i]:
j = 0
if j<10:
print i
res[i] = logreg_lsa_filer(i)
gc.collect()
c = newCount[i]
j = j+1
with open('resl/SVM-Lsa200-11-Aug_Female.txt', 'w') as file:
file.write(json.dumps(res))
def results():
counts = actor.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
c=0
res = dict()
j=0
for i in p_ids:
if c != newCount[i]:
j = 0
if j<10:
print i
res[i] = logreg_filer(i)
gc.collect()
c = newCount[i]
j = j+1
with open('svm(cast)-7Aug_Male.txt', 'w') as file:
file.write(json.dumps(res))
counts = actress.person_id.value_counts(sort=True).copy()
newCount = counts.where( counts > 5 )
newCount = newCount.dropna()
p_ids = newCount.index.tolist()
c=0
res = dict()
for i in p_ids:
if c != newCount[i]:
j = 0
if j<10:
print i
res[i] = logreg_filer(i)
gc.collect()
c = newCount[i]
j = j+1
with open('svm(cast)-7Aug_Female.txt', 'w') as file:
file.write(json.dumps(res))
# counts = actor.person_id.value_counts(sort=True).copy()
# newCount = counts.where( counts > 5 )
# newCount = newCount.dropna()
# p_ids = newCount.index.tolist()
# c=0
# res = dict()
# for i in p_ids:
# if c != newCount[i]:
# print i
# res[i] = logreg_lsa_filer(i)
# gc.collect()
# c = newCount[i]
# with open('svm(3200)(cast)_LSA(50)-19-Jul_Male.txt', 'w') as file:
# file.write(json.dumps(res))
# counts = actress.person_id.value_counts(sort=True).copy()
# newCount = counts.where( counts > 5 )
# newCount = newCount.dropna()
# p_ids = newCount.index.tolist()
# c=0
# res = dict()
# for i in p_ids:
# if c != newCount[i]:
# print i
# res[i] = logreg_lsa_filer(i)
# gc.collect()
# c = newCount[i]
# with open('svm(3200)(cast)_LSA(50)-19-Jul_Female.txt', 'w') as file:
# file.write(json.dumps(res))
# def actorsCount(con):
# counts = actor.person_id.value_counts(sort=True).copy()
# newCount = counts.where( counts > con )
# newCount = newCount.dropna()
# counts = actress.person_id.value_counts(sort=True).copy()
# fnewCount = counts.where( counts > con )
# fnewCount = fnewCount.dropna()
# return len(newCount), len(fnewCount)
| 30.448185
| 244
| 0.680223
| 7,959
| 46,129
| 3.770951
| 0.039955
| 0.015193
| 0.016393
| 0.025989
| 0.914204
| 0.907507
| 0.898611
| 0.894046
| 0.888215
| 0.880152
| 0
| 0.029657
| 0.141126
| 46,129
| 1,514
| 245
| 30.468296
| 0.727883
| 0.157363
| 0
| 0.877157
| 0
| 0
| 0.043844
| 0.009224
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.028426
| null | null | 0.009137
| 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
|
c6108743546225a5eaece73cb89c74be778cd7a4
| 169
|
py
|
Python
|
IoT/settings/production.py
|
Nolwac/Arduino_Python_IoT
|
615f0cb4599d0ef52b79a0d8733756e23bb6e194
|
[
"MIT"
] | null | null | null |
IoT/settings/production.py
|
Nolwac/Arduino_Python_IoT
|
615f0cb4599d0ef52b79a0d8733756e23bb6e194
|
[
"MIT"
] | null | null | null |
IoT/settings/production.py
|
Nolwac/Arduino_Python_IoT
|
615f0cb4599d0ef52b79a0d8733756e23bb6e194
|
[
"MIT"
] | null | null | null |
from .base import *
import dj_database_url
# dj_url = dj_database_url.config()
DATABASES['default']=dj_database_url.config()
# DATABASES['default']['CONN_MAX_AGE']=500
| 24.142857
| 45
| 0.769231
| 25
| 169
| 4.84
| 0.52
| 0.247934
| 0.322314
| 0.31405
| 0.578512
| 0.578512
| 0
| 0
| 0
| 0
| 0
| 0.019355
| 0.08284
| 169
| 6
| 46
| 28.166667
| 0.76129
| 0.43787
| 0
| 0
| 0
| 0
| 0.076087
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 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
|
d6fcb07a733b2b0744eef182711c1d0c087a9503
| 1,740
|
py
|
Python
|
dqn/uwac_dqn.py
|
hbutsuak95/iv_rl
|
0f72a8f077a238237027ea96b7d1160c35ac9959
|
[
"MIT"
] | 9
|
2022-01-16T11:27:00.000Z
|
2022-03-13T14:04:48.000Z
|
dqn/uwac_dqn.py
|
hbutsuak95/iv_rl
|
0f72a8f077a238237027ea96b7d1160c35ac9959
|
[
"MIT"
] | null | null | null |
dqn/uwac_dqn.py
|
hbutsuak95/iv_rl
|
0f72a8f077a238237027ea96b7d1160c35ac9959
|
[
"MIT"
] | null | null | null |
from .ensembleDQN import *
from .mcdropDQN import *
class UWAC_DQN(EnsembleDQN):
def __init__(self, env, opt, device="cuda"):
"""Initialize an Agent object.
Params
======
state_size (int): dimension of each state
action_size (int): dimension of each action
num_nets (int): number of Q-networks
seed (int): random seed
"""
super().__init__(env, opt, device)
self.beta = opt.uwac_beta
self.use_exp_weight = opt.use_exp_weight
self.clip_bottom = opt.clip_bottom
self.clip_top = opt.clip_top
self.factor = 1
def uwac_weights(self, variance):
weight = torch.clamp(self.beta*self.factor/variance, self.clip_bottom, self.clip_top)
return weight
def get_mse_weights(self, variance):
return self.uwac_weights(variance)
class UWAC_LakshmiBootstrapDQN(LakshmiBootstrapDQN):
def __init__(self, env, opt, device="cuda"):
"""Initialize an Agent object.
Params
======
state_size (int): dimension of each state
action_size (int): dimension of each action
num_nets (int): number of Q-networks
seed (int): random seed
"""
super().__init__(env, opt, device)
self.beta = opt.uwac_beta
self.use_exp_weight = opt.use_exp_weight
self.clip_bottom = opt.clip_bottom
self.clip_top = opt.clip_top
self.factor = 1
def uwac_weights(self, variance):
weight = torch.clamp(self.beta*self.factor/variance, self.clip_bottom, self.clip_top)
return weight
def get_mse_weights(self, variance):
return self.uwac_weights(variance)
| 29.491525
| 93
| 0.62069
| 218
| 1,740
| 4.706422
| 0.233945
| 0.062378
| 0.046784
| 0.070175
| 0.892788
| 0.892788
| 0.892788
| 0.892788
| 0.892788
| 0.892788
| 0
| 0.001603
| 0.282759
| 1,740
| 58
| 94
| 30
| 0.820513
| 0.236207
| 0
| 0.857143
| 0
| 0
| 0.006695
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.214286
| false
| 0
| 0.071429
| 0.071429
| 0.5
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
ba372bc6eaa82a0c7a4a23c9d550546afde2a2b7
| 39
|
py
|
Python
|
tests/fixtures/uniswap/test_smoke.py
|
iamdefinitelyahuman/defi-mocks
|
42167850cad7c83b8257e134df2551906c524800
|
[
"MIT"
] | 3
|
2020-05-26T22:46:00.000Z
|
2022-02-03T08:07:08.000Z
|
tests/fixtures/uniswap/test_smoke.py
|
iamdefinitelyahuman/defi-mocks
|
42167850cad7c83b8257e134df2551906c524800
|
[
"MIT"
] | null | null | null |
tests/fixtures/uniswap/test_smoke.py
|
iamdefinitelyahuman/defi-mocks
|
42167850cad7c83b8257e134df2551906c524800
|
[
"MIT"
] | null | null | null |
# TODO
def test_uniswap():
pass
| 5.571429
| 19
| 0.589744
| 5
| 39
| 4.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0.307692
| 39
| 6
| 20
| 6.5
| 0.814815
| 0.102564
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| 0
| 0
| 0
| 0.166667
| 0
| 1
| 0.5
| true
| 0.5
| 0
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| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| null | 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
ba42ddffca88f07eeb856c67f6ba6466107eb512
| 122
|
py
|
Python
|
bempp/api/operators/boundary/__init__.py
|
pescap/bempp-cl
|
3a68666e8db0e873d418b734289067483f68f12e
|
[
"MIT"
] | null | null | null |
bempp/api/operators/boundary/__init__.py
|
pescap/bempp-cl
|
3a68666e8db0e873d418b734289067483f68f12e
|
[
"MIT"
] | null | null | null |
bempp/api/operators/boundary/__init__.py
|
pescap/bempp-cl
|
3a68666e8db0e873d418b734289067483f68f12e
|
[
"MIT"
] | null | null | null |
from . import laplace
from . import helmholtz
from . import modified_helmholtz
from . import maxwell
from . import sparse
| 20.333333
| 32
| 0.795082
| 16
| 122
| 6
| 0.4375
| 0.520833
| 0.395833
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0.163934
| 122
| 5
| 33
| 24.4
| 0.941176
| 0
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| 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
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
ba74110981a97774a04359fd467815b5bb74b9e7
| 30,476
|
py
|
Python
|
components/core/qcg/pilotjob/tests/test_resources.py
|
LourensVeen/QCG-PilotJob
|
e78c35a9b16b1042a2d5b54352a2ca2e3a58c6b9
|
[
"Apache-2.0"
] | null | null | null |
components/core/qcg/pilotjob/tests/test_resources.py
|
LourensVeen/QCG-PilotJob
|
e78c35a9b16b1042a2d5b54352a2ca2e3a58c6b9
|
[
"Apache-2.0"
] | null | null | null |
components/core/qcg/pilotjob/tests/test_resources.py
|
LourensVeen/QCG-PilotJob
|
e78c35a9b16b1042a2d5b54352a2ca2e3a58c6b9
|
[
"Apache-2.0"
] | null | null | null |
import pytest
import pprint
from qcg.pilotjob.resources import Node, ResourcesType, Resources
from qcg.pilotjob.resources import CRType, CR, CRBind
def test_resources_export():
nodes = [ Node('n1', 10),
Node('n2', 4, 0, [ "2", "3", "4", "5" ]) ]
res = Resources(ResourcesType.LOCAL, nodes, False)
assert all((res.total_nodes == 2, res.total_cores == sum([n.total for n in nodes]), res.used_cores == 0,
res.free_cores == res.total_cores, res.binding == False, res.rtype == ResourcesType.LOCAL))
res_copy = Resources.from_dict(res.to_dict())
assert all((res_copy.total_nodes == res.total_nodes, res_copy.total_cores == res.total_cores,
res_copy.used_cores == res.used_cores, res_copy.free_cores == res.free_cores,
res_copy.binding == res.binding, res_copy.binding == res.binding))
for idx, n in enumerate(nodes):
assert all((n.ids == res_copy.nodes[idx].ids, n.ids == res.nodes[idx].ids,
n.free_ids == res_copy.nodes[idx].free_ids, n.free_ids == res.nodes[idx].free_ids))
assert all((len(res.to_json()) > 0, res.to_json() == res_copy.to_json()))
nodes = [ Node('n1', 10, 3),
Node('n2', 4, 2, [ "2", "3", "4", "5" ]) ]
res = Resources(ResourcesType.SLURM, nodes, True)
assert all((res.total_nodes == 2,
res.total_cores == sum([n.total for n in nodes]),
res.used_cores == sum([n.used for n in nodes]),
res.free_cores == sum([n.total for n in nodes]) - sum([n.used for n in nodes]),
nodes[0].free_ids == [str(cid) for cid in range(3, 10)],
nodes[1].free_ids == ["4", "5"],
res.binding == True, res.rtype == ResourcesType.SLURM)), res.to_json()
res_copy = Resources.from_dict(res.to_dict())
assert all((res_copy.total_nodes == res.total_nodes, res_copy.total_cores == res.total_cores,
res_copy.used_cores == res.used_cores, res_copy.free_cores == res.free_cores,
res_copy.binding == res.binding, res_copy.binding == res.binding))
for idx, n in enumerate(nodes):
assert all((n.ids == res_copy.nodes[idx].ids, n.ids == res.nodes[idx].ids,
n.free_ids == res_copy.nodes[idx].free_ids, n.free_ids == res.nodes[idx].free_ids))
assert all((len(res.to_json()) > 0, res.to_json() == res_copy.to_json()))
# print(res.to_json())
n1Tot = 8
n2Tot = 8
n1GpuTot = 4
n2GpuTot = 2
r = Resources(ResourcesType.LOCAL, [
Node("n1", total_cores=n1Tot, used=0, core_ids=None, crs={CRType.GPU: CRBind(CRType.GPU, list(range(n1GpuTot)))}),
Node("n2", total_cores=n2Tot, used=0, core_ids=None, crs={CRType.GPU: CRBind(CRType.GPU, list(range(n2GpuTot)))})
], binding=False)
assert all((r != None, r.binding == False, r.rtype == ResourcesType.LOCAL,
r.total_nodes == 2, r.total_cores == r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
assert all((r.nodes[0].name == 'n1', r.nodes[0].total == r.nodes[0].free == n1Tot, r.nodes[0].used == 0))
assert all((r.nodes[1].name == 'n2', r.nodes[1].total == r.nodes[1].free == n2Tot, r.nodes[1].used == 0))
n1 = r.nodes[0]
n2 = r.nodes[1]
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == 0, n1.crs[CRType.GPU].available == n1GpuTot))
assert all((len(n2.crs) == 1, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == 0, n2.crs[CRType.GPU].available == n2GpuTot))
r_copy = Resources.from_dict(r.to_dict())
assert all((r_copy != None, r_copy.binding == False, r_copy.rtype == ResourcesType.LOCAL,
r_copy.total_nodes == 2, r_copy.total_cores == r_copy.free_cores == n1Tot + n2Tot, r_copy.used_cores == 0))
assert all((r_copy.nodes[0].name == 'n1', r_copy.nodes[0].total == r_copy.nodes[0].free == n1Tot, r_copy.nodes[0].used == 0))
assert all((r_copy.nodes[1].name == 'n2', r_copy.nodes[1].total == r_copy.nodes[1].free == n2Tot, r_copy.nodes[1].used == 0))
n1 = r_copy.nodes[0]
n2 = r_copy.nodes[1]
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == 0, n1.crs[CRType.GPU].available == n1GpuTot))
assert all((len(n2.crs) == 1, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == 0, n2.crs[CRType.GPU].available == n2GpuTot))
assert all((len(r_copy.to_json()) > 0, r_copy.to_json() == r.to_json()))
n1Tot = 8
n2Tot = 8
n1MemTot = 128
n2MemTot = 256
n2GpuTot = 4
r = Resources(ResourcesType.LOCAL, [
Node("n1", total_cores=n1Tot, used=0, core_ids=None, crs={CRType.MEM: CR(CRType.MEM, n1MemTot)}),
Node("n2", total_cores=n2Tot, used=0, core_ids=None, crs={CRType.MEM: CR(CRType.MEM, n2MemTot),
CRType.GPU: CRBind(CRType.GPU, list(range(n2GpuTot)))})
], binding=False)
assert all((r != None, r.binding == False, r.rtype == ResourcesType.LOCAL,
r.total_nodes == 2, r.total_cores == r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
assert all((r.nodes[0].name == 'n1', r.nodes[0].total == r.nodes[0].free == n1Tot, r.nodes[0].used == 0))
assert all((r.nodes[1].name == 'n2', r.nodes[1].total == r.nodes[1].free == n2Tot, r.nodes[1].used == 0))
n1 = r.nodes[0]
n2 = r.nodes[1]
assert all((len(n1.crs) == 1, CRType.MEM in n1.crs, n1.crs[CRType.MEM].total_count == n1MemTot,
n1.crs[CRType.MEM].used == 0, n1.crs[CRType.MEM].available == n1MemTot))
assert all((len(n2.crs) == 2, CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot,
CRType.GPU in n2.crs, n2.crs[CRType.GPU].available == n2GpuTot))
r_copy = Resources.from_dict(r.to_dict())
assert all((r_copy != None, r_copy.binding == False, r_copy.rtype == ResourcesType.LOCAL,
r_copy.total_nodes == 2, r_copy.total_cores == r_copy.free_cores == n1Tot + n2Tot, r_copy.used_cores == 0))
assert all((r_copy.nodes[0].name == 'n1', r_copy.nodes[0].total == r_copy.nodes[0].free == n1Tot, r_copy.nodes[0].used == 0))
assert all((r_copy.nodes[1].name == 'n2', r_copy.nodes[1].total == r_copy.nodes[1].free == n2Tot, r_copy.nodes[1].used == 0))
n1 = r_copy.nodes[0]
n2 = r_copy.nodes[1]
assert all((len(n1.crs) == 1, CRType.MEM in n1.crs, n1.crs[CRType.MEM].total_count == n1MemTot,
n1.crs[CRType.MEM].used == 0, n1.crs[CRType.MEM].available == n1MemTot))
assert all((len(n2.crs) == 2, CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot,
CRType.GPU in n2.crs, n2.crs[CRType.GPU].available == n2GpuTot))
assert all((len(r_copy.to_json()) > 0, r_copy.to_json() == r.to_json()))
def test_resources_allocate_general():
n1Tot = 12
n2Tot = 10
r = Resources(ResourcesType.LOCAL, [
Node("n1", total_cores=n1Tot, used=0, core_ids=None, crs=None),
Node("n2", total_cores=n2Tot, used=0, core_ids=None, crs=None) ], binding=False)
assert all((r != None, r.binding == False, r.rtype == ResourcesType.LOCAL,
r.total_nodes == 2,
r.total_cores == r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
assert all((r.nodes[0].name == 'n1', r.nodes[0].total == r.nodes[0].free == n1Tot, r.nodes[0].used == 0))
assert all((r.nodes[1].name == 'n2', r.nodes[1].total == r.nodes[1].free == n2Tot, r.nodes[1].used == 0))
# create partial allocation on the first node
n1 = r.nodes[0]
c1 = 4
a1 = n1.allocate_max(c1)
assert all((a1, a1.ncores == c1, a1.cores == [str(cid) for cid in range(c1)], a1.crs == None))
assert all((n1.total == n1Tot, n1.free == n1Tot - c1, n1.used == c1))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1, r.used_cores == c1))
# create partial allocation on the second node
n2 = r.nodes[1]
c2 = 8
a2 = n2.allocate_max(c2)
assert all((a2, a2.ncores == c2, a2.cores == [str(cid) for cid in range(c2)], a2.crs == None))
assert all((n2.total == n2Tot, n2.free == n2Tot - c2, n2.used == c2))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1 - c2, r.used_cores == c1 + c2))
# request for the more resources then are available
c3 = n1Tot - c1 + 2
c3Real = n1Tot - c1
a3 = n1.allocate_max(c3)
assert all((a3, a3.ncores == c3Real, a3.cores == [str(cid) for cid in range(c1, c1 + c3Real)], a3.crs == None))
assert all((n1.total == n1Tot, n1.free == n1Tot - c1 - c3Real == 0, n1.used == c1 + c3Real == n1Tot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1 - c2 - c3Real, r.used_cores == c1 + c2 + c3Real))
# request for no more resources
c4 = 4
a4 = n1.allocate_max(c4)
assert a4 == None
assert all((n1.total == n1Tot, n1.free == n1Tot - c1 - c3Real == 0, n1.used == c1 + c3Real == n1Tot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1 - c2 - c3Real, r.used_cores == c1 + c2 + c3Real))
# release the first allocation (now we should have only c3Real allocated cores)
a1.release()
assert all((n1.total == n1Tot, n1.free == n1Tot - c3Real, n1.used == c3Real))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c2 - c3Real, r.used_cores == c2 + c3Real))
# allocate rest of the free cores
c5 = n1.free
a5 = n1.allocate_max(c5)
assert all((a5, a5.ncores == c5, a5.cores == [str(cid) for cid in list(range(c1)) + list(range(c1 + c3Real, n1Tot))], a5.crs == None))
assert all((n1.total == n1Tot, n1.free == n1Tot - c3Real - c5 == 0, n1.used == c5 + c3Real == n1Tot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c5 - c2 - c3Real, r.used_cores == c5 + c2 + c3Real))
# release once more the first, already released allocation - nothing should change
a1.release()
assert all((n1.total == n1Tot, n1.free == n1Tot - c3Real - c5 == 0, n1.used == c5 + c3Real == n1Tot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c5 - c2 - c3Real, r.used_cores == c5 + c2 + c3Real))
# release all allocations
for a in [ a2, a3, a5 ]:
a.release()
assert all((r.nodes[0].name == 'n1', r.nodes[0].total == r.nodes[0].free == n1Tot, r.nodes[0].used == 0))
assert all((r.nodes[1].name == 'n2', r.nodes[1].total == r.nodes[1].free == n2Tot, r.nodes[1].used == 0))
assert all((r.total_nodes == 2, r.total_cores == r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
def test_resources_allocate_crs_gpu():
n1Tot = 8
n2Tot = 8
n1GpuTot = 4
n2GpuTot = 2
r = Resources(ResourcesType.LOCAL, [
Node("n1", total_cores=n1Tot, used=0, core_ids=None, crs={CRType.GPU: CRBind(CRType.GPU, list(range(n1GpuTot)))}),
Node("n2", total_cores=n2Tot, used=0, core_ids=None, crs={CRType.GPU: CRBind(CRType.GPU, list(range(n2GpuTot)))})
], binding=False)
assert all((r != None, r.binding == False, r.rtype == ResourcesType.LOCAL,
r.total_nodes == 2, r.total_cores == r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
assert all((r.nodes[0].name == 'n1', r.nodes[0].total == r.nodes[0].free == n1Tot, r.nodes[0].used == 0))
assert all((r.nodes[1].name == 'n2', r.nodes[1].total == r.nodes[1].free == n2Tot, r.nodes[1].used == 0))
n1 = r.nodes[0]
n2 = r.nodes[1]
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == 0, n1.crs[CRType.GPU].available == n1GpuTot))
assert all((len(n2.crs) == 1, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == 0, n2.crs[CRType.GPU].available == n2GpuTot))
# create partial allocation on the first node with gpu cr
c1_c = 2
c1_g = 2
a1 = n1.allocate_max(c1_c, {CRType.GPU: c1_g})
assert a1
assert all((a1.ncores == c1_c, a1.cores == [str(cid) for cid in range(c1_c)])), "cores: {}".format(str(a1.cores))
assert a1.crs != None and all((len(a1.crs) == 1, CRType.GPU in a1.crs, a1.crs[CRType.GPU].count == c1_g,
a1.crs[CRType.GPU].instances == list(range(c1_g)))), "crs: {}".format(str(a1.crs))
assert all((n1.total == n1Tot, n1.free == n1Tot - c1_c, n1.used == c1_c))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c1_g, n1.crs[CRType.GPU].available == n1GpuTot - c1_g))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c, r.used_cores == c1_c))
# try to allocate more crs than available, the allocation should not be created and state of resources should not change
c2_c = 2
c2_g = n1GpuTot - c1_g + 2
a2 = n1.allocate_max(c2_c, {CRType.GPU: c2_g})
assert a2 == None
assert all((n1.total == n1Tot, n1.free == n1Tot - c1_c, n1.used == c1_c))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c1_g, n1.crs[CRType.GPU].available == n1GpuTot - c1_g))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c, r.used_cores == c1_c))
# create allocation for the rest of the cpus at the first node
c3_c = n1Tot - c1_c
a3 = n1.allocate_max(c3_c)
assert a3
assert all((a3.ncores == c3_c, a3.cores == [str(cid) for cid in range(c1_c, c1_c + c3_c)])), "cores: {} vs expected {}".format(str(a3.cores), str(list(range(c1_c, c1_c + c3_c))))
assert a3.crs == None
assert all((n1.total == n1Tot, n1.free == n1Tot - c1_c - c3_c == 0, n1.used == c1_c + c3_c == n1Tot))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c1_g, n1.crs[CRType.GPU].available == n1GpuTot - c1_g))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c - c3_c, r.used_cores == c1_c + c3_c))
# try to allocate available crs but without available cpu's, the allocation should not be created and state of resources should not change
c4_c = 1
c4_g = n1GpuTot - c1_g
a4 = n1.allocate_max(c4_c, {CRType.GPU: c4_g})
assert a4 == None
assert all((n1.total == n1Tot, n1.free == n1Tot - c1_c - c3_c == 0, n1.used == c1_c + c3_c == n1Tot))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c1_g, n1.crs[CRType.GPU].available == n1GpuTot - c1_g))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c - c3_c, r.used_cores == c1_c + c3_c))
# release some cpus
a3.release()
assert all((n1.total == n1Tot, n1.free == n1Tot - c1_c, n1.used == c1_c))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c1_g, n1.crs[CRType.GPU].available == n1GpuTot - c1_g))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c, r.used_cores == c1_c))
# release already released cpu's - nothing should change
a3.release()
assert all((n1.total == n1Tot, n1.free == n1Tot - c1_c, n1.used == c1_c))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c1_g, n1.crs[CRType.GPU].available == n1GpuTot - c1_g))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c, r.used_cores == c1_c))
# allocate rest of the resources
c5_c = n1.free
c5_g = n1.crs[CRType.GPU].available
a5 = n1.allocate_max(c5_c, {CRType.GPU: c5_g})
assert a5
assert all((a5.ncores == c5_c, a5.cores == [str(cid) for cid in range(c1_c, c1_c + c5_c)])), "cores: {} vs expected {}".format(str(a5.cores), str(list(range(c1_c, c1_c + c5_c))))
assert a5.crs != None and all((len(a5.crs) == 1, CRType.GPU in a5.crs, a5.crs[CRType.GPU].count == c5_g,
a5.crs[CRType.GPU].instances == list(range(c1_g, c1_g + c5_g)))), "crs: {}".format(str(a5.crs))
assert all((n1.total == n1Tot, n1.free == n1Tot - c1_c - c5_c == 0, n1.used == c1_c + c5_c == n1Tot))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c1_g + c5_g == n1.crs[CRType.GPU].total_count,
n1.crs[CRType.GPU].available == n1GpuTot - c1_g - c5_g == 0))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c - c5_c, r.used_cores == c1_c + c5_c))
# release one gpu allocation
a1.release()
assert all((n1.total == n1Tot, n1.free == n1Tot - c5_c, n1.used == c5_c))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c5_g, n1.crs[CRType.GPU].available == n1GpuTot - c5_g))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c5_c, r.used_cores == c5_c))
# release once more already released gpu allocation - nothing should change
a1.release()
assert all((n1.total == n1Tot, n1.free == n1Tot - c5_c, n1.used == c5_c))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == c5_g, n1.crs[CRType.GPU].available == n1GpuTot - c5_g))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c5_c, r.used_cores == c5_c))
# release rest of the resources
a5.release()
a5.release()
assert all((n1.total == n1Tot, n1.free == n1Tot, n1.used == 0))
assert all((len(n1.crs) == 1, CRType.GPU in n1.crs, n1.crs[CRType.GPU].total_count == n1GpuTot,
n1.crs[CRType.GPU].used == 0, n1.crs[CRType.GPU].available == n1GpuTot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
def test_resources_allocate_crs_mem():
n1Tot = 8
n2Tot = 8
n1MemTot = 128
n2MemTot = 256
n2GpuTot = 4
r = Resources(ResourcesType.LOCAL, [
Node("n1", total_cores=n1Tot, used=0, core_ids=None, crs={CRType.MEM: CR(CRType.MEM, n1MemTot)}),
Node("n2", total_cores=n2Tot, used=0, core_ids=None, crs={CRType.MEM: CR(CRType.MEM, n2MemTot),
CRType.GPU: CRBind(CRType.GPU, list(range(n2GpuTot)))})
], binding=False)
assert all((r != None, r.binding == False, r.rtype == ResourcesType.LOCAL,
r.total_nodes == 2, r.total_cores == r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
assert all((r.nodes[0].name == 'n1', r.nodes[0].total == r.nodes[0].free == n1Tot, r.nodes[0].used == 0))
assert all((r.nodes[1].name == 'n2', r.nodes[1].total == r.nodes[1].free == n2Tot, r.nodes[1].used == 0))
n1 = r.nodes[0]
n2 = r.nodes[1]
assert all((len(n1.crs) == 1, CRType.MEM in n1.crs, n1.crs[CRType.MEM].total_count == n1MemTot,
n1.crs[CRType.MEM].used == 0, n1.crs[CRType.MEM].available == n1MemTot))
assert all((len(n2.crs) == 2, CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot,
CRType.GPU in n2.crs, n2.crs[CRType.GPU].available == n2GpuTot))
# create allocation with both CR's
c1_c = n2.free - 2
c1_g = n2.crs[CRType.GPU].available - 1
c1_m = n2.crs[CRType.MEM].available - 20
a1 = n2.allocate_max(c1_c, {CRType.GPU: c1_g, CRType.MEM: c1_m})
assert a1
assert all((a1.ncores == c1_c, a1.cores == [str(cid) for cid in range(c1_c)])), "cores: {} vs expected {}".format(str(a1.cores), str(list(range(c1_c))))
assert a1.crs != None and all((len(a1.crs) == 2, CRType.GPU in a1.crs, a1.crs[CRType.GPU].count == c1_g,
a1.crs[CRType.GPU].instances == list(range(c1_g)), CRType.MEM in a1.crs, a1.crs[CRType.MEM].count == c1_m)), "crs: {}".format(str(a1.crs))
assert all((n2.total == n2Tot, n2.free == n2Tot - c1_c, n2.used == c1_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c1_g, n2.crs[CRType.GPU].available == n2GpuTot - c1_g,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == c1_m, n2.crs[CRType.MEM].available == n2MemTot - c1_m))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c, r.used_cores == c1_c))
# allocate the rest of the GPU's
c2_c = n2.free
c2_g = n2.crs[CRType.GPU].available
a2 = n2.allocate_max(c2_c, {CRType.GPU: c2_g})
assert a2
assert all((a2.ncores == c2_c, a2.cores == [str(cid) for cid in range(c1_c, c1_c + c2_c)])), "cores: {} vs expected {}".format(str(a2.cores), str(list(range(c1_c, c1_c + c2_c))))
assert a2.crs != None and all((len(a2.crs) == 1, CRType.GPU in a2.crs, a2.crs[CRType.GPU].count == c2_g,
a2.crs[CRType.GPU].instances == list(range(c1_g, c1_g + c2_g))))
assert all((n2.total == n2Tot, n2.free == n2Tot - c1_c - c2_c, n2.used == c1_c + c2_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c1_g + c2_g == n2GpuTot, n2.crs[CRType.GPU].available == n2GpuTot - c1_g - c2_g == 0,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == c1_m, n2.crs[CRType.MEM].available == n2MemTot - c1_m))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c - c2_c, r.used_cores == c1_c + c2_c))
# try to allocate mem - with no available cpu's
c3_c = 1
c3_m = n2.crs[CRType.MEM].available
a3 = n2.allocate_max(c3_c, {CRType.MEM: c3_m})
assert a3 == None
assert all((n2.total == n2Tot, n2.free == n2Tot - c1_c - c2_c, n2.used == c1_c + c2_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c1_g + c2_g == n2GpuTot, n2.crs[CRType.GPU].available == n2GpuTot - c1_g - c2_g == 0,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == c1_m, n2.crs[CRType.MEM].available == n2MemTot - c1_m))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c - c2_c, r.used_cores == c1_c + c2_c))
# try to allocate mem - with no available gpu's
c3_c = 1
c3_m = n2.crs[CRType.MEM].available
a3 = n2.allocate_max(c3_c, {CRType.MEM: c3_m})
assert a3 == None
assert all((n2.total == n2Tot, n2.free == n2Tot - c1_c - c2_c, n2.used == c1_c + c2_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c1_g + c2_g == n2GpuTot, n2.crs[CRType.GPU].available == n2GpuTot - c1_g - c2_g == 0,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == c1_m, n2.crs[CRType.MEM].available == n2MemTot - c1_m))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c1_c - c2_c, r.used_cores == c1_c + c2_c))
# release some resources
a1.release()
assert all((n2.total == n2Tot, n2.free == n2Tot - c2_c, n2.used == c2_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c2_g, n2.crs[CRType.GPU].available == n2GpuTot - c2_g,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c2_c, r.used_cores == c2_c))
# once more release already released resources - nothing should change
a1.release()
assert all((n2.total == n2Tot, n2.free == n2Tot - c2_c, n2.used == c2_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c2_g, n2.crs[CRType.GPU].available == n2GpuTot - c2_g,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c2_c, r.used_cores == c2_c))
# allocate rest of cr
c4_c = n2.free
c4_g = n2.crs[CRType.GPU].available
c4_m = n2.crs[CRType.MEM].available
a4 = n2.allocate_max(c4_c, {CRType.MEM: c4_m,
CRType.GPU: c4_g})
assert a4
assert all((a4.ncores == c4_c, a4.cores == [str(cid) for cid in range(c1_c)])), "cores: {} vs expected {}".format(str(a4.cores), str(list(range(c1_c))))
assert a4.crs != None and all((len(a4.crs) == 2, CRType.GPU in a4.crs, a4.crs[CRType.GPU].count == c4_g,
a4.crs[CRType.GPU].instances == list(range(c4_g)), CRType.MEM in a4.crs, a4.crs[CRType.MEM].count == c4_m)), "crs: {}".format(str(a4.crs))
assert all((n2.total == n2Tot, n2.free == n2Tot - c2_c - c4_c == 0, n2.used == c2_c + c4_c == n2Tot))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c2_g + c4_g == n2GpuTot, n2.crs[CRType.GPU].available == n2GpuTot - c2_g - c4_g == 0,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot))
assert all((n2.crs[CRType.MEM].used == c4_m == n2MemTot, n2.crs[CRType.MEM].available == n2MemTot - c4_m == 0))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c2_c - c4_c, r.used_cores == c2_c + c4_c))
# release last allocation
a4.release()
assert all((n2.total == n2Tot, n2.free == n2Tot - c2_c, n2.used == c2_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c2_g, n2.crs[CRType.GPU].available == n2GpuTot - c2_g,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c2_c, r.used_cores == c2_c))
# release once more already released resources - nothing should change
a4.release()
assert all((n2.total == n2Tot, n2.free == n2Tot - c2_c, n2.used == c2_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c2_g, n2.crs[CRType.GPU].available == n2GpuTot - c2_g,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c2_c, r.used_cores == c2_c))
# release remaining allocation - all resources should be free
a2.release()
assert all((n2.total == n2Tot, n2.free == n2Tot, n2.used == 0))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == 0, n2.crs[CRType.GPU].available == n2GpuTot,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
# release some of mem cr and whole gpu set
c5_c = n2.free - 2
c5_g = n2.crs[CRType.GPU].available
c5_m = n2.crs[CRType.MEM].available - 20
a5 = n2.allocate_max(c5_c, {CRType.MEM: c5_m,
CRType.GPU: c5_g})
assert a5
assert all((a5.ncores == c5_c, a5.cores == [str(cid) for cid in range(c5_c)])), "cores: {} vs expected {}".format(str(a5.cores), str(list(range(c5_c))))
assert a5.crs != None and all((len(a5.crs) == 2, CRType.GPU in a5.crs, a5.crs[CRType.GPU].count == c5_g,
a5.crs[CRType.GPU].instances == list(range(c5_g)), CRType.MEM in a5.crs, a5.crs[CRType.MEM].count == c5_m)), "crs: {}".format(str(a5.crs))
assert all((n2.total == n2Tot, n2.free == n2Tot - c5_c, n2.used == c5_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c5_g == n2GpuTot, n2.crs[CRType.GPU].available == n2GpuTot - c5_g == 0,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot))
assert all((n2.crs[CRType.MEM].used == c5_m, n2.crs[CRType.MEM].available == n2MemTot - c5_m))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c5_c, r.used_cores == c5_c))
# try to allocate rest of mem cr and one of the gpu - allocation should not be created
c6_c = n2.free
c6_g = 1
c6_m = n2.crs[CRType.MEM].available
a6 = n2.allocate_max(c6_c, {CRType.MEM: c6_m,
CRType.GPU: c6_g})
assert a6 == None
assert all((n2.total == n2Tot, n2.free == n2Tot - c5_c, n2.used == c5_c))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == c5_g == n2GpuTot, n2.crs[CRType.GPU].available == n2GpuTot - c5_g == 0,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot))
assert all((n2.crs[CRType.MEM].used == c5_m, n2.crs[CRType.MEM].available == n2MemTot - c5_m))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot - c5_c, r.used_cores == c5_c))
# release all allocations
a5.release()
assert all((n2.total == n2Tot, n2.free == n2Tot, n2.used == 0))
assert all((len(n2.crs) == 2, CRType.GPU in n2.crs, n2.crs[CRType.GPU].total_count == n2GpuTot,
n2.crs[CRType.GPU].used == 0, n2.crs[CRType.GPU].available == n2GpuTot,
CRType.MEM in n2.crs, n2.crs[CRType.MEM].total_count == n2MemTot,
n2.crs[CRType.MEM].used == 0, n2.crs[CRType.MEM].available == n2MemTot))
assert all((r.total_cores == n1Tot + n2Tot, r.free_cores == n1Tot + n2Tot, r.used_cores == 0))
| 59.407407
| 182
| 0.623343
| 5,077
| 30,476
| 3.620051
| 0.029151
| 0.089123
| 0.073127
| 0.041896
| 0.900974
| 0.875129
| 0.847707
| 0.822025
| 0.807498
| 0.796289
| 0
| 0.063368
| 0.198943
| 30,476
| 512
| 183
| 59.523438
| 0.689469
| 0.051943
| 0
| 0.681818
| 0
| 0
| 0.008941
| 0
| 0
| 0
| 0
| 0
| 0.411616
| 1
| 0.010101
| false
| 0
| 0.010101
| 0
| 0.020202
| 0.002525
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
baacfe757ce9b8c531a8eb99e7083d5d9071778e
| 1,249
|
py
|
Python
|
ftp/pluginManager.py
|
uzairAK/serverom-panel
|
3dcde05ad618e6bef280db7d3180f926fe2ab1db
|
[
"MIT"
] | null | null | null |
ftp/pluginManager.py
|
uzairAK/serverom-panel
|
3dcde05ad618e6bef280db7d3180f926fe2ab1db
|
[
"MIT"
] | null | null | null |
ftp/pluginManager.py
|
uzairAK/serverom-panel
|
3dcde05ad618e6bef280db7d3180f926fe2ab1db
|
[
"MIT"
] | null | null | null |
from .signals import *
from plogical.pluginManagerGlobal import pluginManagerGlobal
class pluginManager:
@staticmethod
def preCreateFTPAccount(request):
return pluginManagerGlobal.globalPlug(request, preCreateFTPAccount)
@staticmethod
def postCreateFTPAccount(request, response):
return pluginManagerGlobal.globalPlug(request, postCreateFTPAccount, response)
@staticmethod
def preSubmitFTPCreation(request):
return pluginManagerGlobal.globalPlug(request, preSubmitFTPCreation)
@staticmethod
def postSubmitFTPCreation(request, response):
return pluginManagerGlobal.globalPlug(request, postSubmitFTPCreation, response)
@staticmethod
def preSubmitFTPDelete(request):
return pluginManagerGlobal.globalPlug(request, preSubmitFTPDelete)
@staticmethod
def postSubmitFTPDelete(request, response):
return pluginManagerGlobal.globalPlug(request, postSubmitFTPDelete, response)
@staticmethod
def preChangePassword(request):
return pluginManagerGlobal.globalPlug(request, preChangePassword)
@staticmethod
def postChangePassword(request, response):
return pluginManagerGlobal.globalPlug(request, postChangePassword, response)
| 34.694444
| 87
| 0.777422
| 90
| 1,249
| 10.788889
| 0.233333
| 0.123584
| 0.288363
| 0.346035
| 0.436663
| 0.234809
| 0
| 0
| 0
| 0
| 0
| 0
| 0.161729
| 1,249
| 36
| 88
| 34.694444
| 0.927412
| 0
| 0
| 0.296296
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.296296
| false
| 0.148148
| 0.074074
| 0.296296
| 0.703704
| 0
| 0
| 0
| 1
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 7
|
bada28529525cca3a19289fddfe302ea58c3a375
| 1,555
|
py
|
Python
|
ProjectEulerCode/prob38.py
|
khaleeque-ansari/Online-Coding-Problems-Solutions-Python
|
c8378ccad88ce5f50239f82cf9569344e1b92f18
|
[
"Apache-2.0"
] | null | null | null |
ProjectEulerCode/prob38.py
|
khaleeque-ansari/Online-Coding-Problems-Solutions-Python
|
c8378ccad88ce5f50239f82cf9569344e1b92f18
|
[
"Apache-2.0"
] | null | null | null |
ProjectEulerCode/prob38.py
|
khaleeque-ansari/Online-Coding-Problems-Solutions-Python
|
c8378ccad88ce5f50239f82cf9569344e1b92f18
|
[
"Apache-2.0"
] | null | null | null |
def ispandigital(x):
s = set()
for c in str(x):
s = s.union([int(c)])
if s == set([1,2,3,4,5,6,7,8,9]) :
return True
else:
return False
max_concat_prod = 918273645
for x in range(90,100):
temp = ''
stop = False
i = 0
while(stop != True):
i +=1
temp = temp + str(x*i)
if len(temp) >9:
stop = True
elif len(temp) == 9:
if ispandigital(int(temp)):
if int(temp) > max_concat_prod :
max_concat_prod = int(temp)
print int(temp)
for x in range(900,1000):
temp = ''
stop = False
i = 0
while(stop != True):
i +=1
temp = temp + str(x*i)
if len(temp) >9:
stop = True
elif len(temp) == 9:
if ispandigital(int(temp)):
if int(temp) > max_concat_prod :
max_concat_prod = int(temp)
print int(temp)
for x in range(9000,10000):
temp = ''
stop = False
i = 0
while(stop != True):
i +=1
temp = temp + str(x*i)
if len(temp) >9:
stop = True
elif len(temp) == 9:
if ispandigital(int(temp)):
if int(temp) > max_concat_prod :
max_concat_prod = int(temp)
print int(temp)
print "the answer is : " + str(max_concat_prod)
| 22.214286
| 49
| 0.417363
| 191
| 1,555
| 3.314136
| 0.246073
| 0.132701
| 0.164297
| 0.052133
| 0.736177
| 0.736177
| 0.736177
| 0.736177
| 0.736177
| 0.736177
| 0
| 0.061893
| 0.470096
| 1,555
| 69
| 50
| 22.536232
| 0.706311
| 0
| 0
| 0.75
| 0
| 0
| 0.01144
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.076923
| 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
|
bafaaf1e70b60d89613677a81c2398e2b41f45fa
| 9,055
|
py
|
Python
|
analytic_von_hamos/raytracing/analytic.py
|
fullerf/analytic_von_hamos
|
a8e26cf44a14902b0ce324f530c3d304de87c798
|
[
"MIT"
] | null | null | null |
analytic_von_hamos/raytracing/analytic.py
|
fullerf/analytic_von_hamos
|
a8e26cf44a14902b0ce324f530c3d304de87c798
|
[
"MIT"
] | null | null | null |
analytic_von_hamos/raytracing/analytic.py
|
fullerf/analytic_von_hamos
|
a8e26cf44a14902b0ce324f530c3d304de87c798
|
[
"MIT"
] | null | null | null |
import tensorflow as tf
import numpy as np
#
__all__ = ['dety', 'detz']
#
pi = float(np.pi)
def dety(Cap_Psi,a,b,c,p,q,r,t,u,v,r0,Theta):
sqrt_two = tf.sqrt(tf.constant(2.,dtype=tf.float64))
return -((tf.math.sqrt((t**2 + v**2) * (t**2 + u**2 + v**2)) * (2 * b * r0 * t * tf.math.cos(Theta) + 2 * q * r0 * t * tf.math.cos(Theta) + 2 * b * p * t * tf.math.cos(2 * Theta) + 2 * a * q * t * tf.math.cos(2 * Theta) - 2 * b * r0 * t * tf.math.cos(2 * Theta) - 2 * q * r0 * t * tf.math.cos(2 * Theta) - 2 * b * c * v * tf.math.cos(2 * Theta) + 2 * b * r * v * tf.math.cos(2 * Theta) - 2 * a * r0 * t * tf.math.sin(Theta) - 2 * p * r0 * t * tf.math.sin(Theta) + 4 * r0**2 * t * tf.math.sin(Theta) + 2 * c * r0 * v * tf.math.sin(Theta) - 2 * r * r0 * v * tf.math.sin(Theta) - 2 * a * p * t * tf.math.sin(2 * Theta) + 2 * b * q * t * tf.math.sin(2 * Theta) + 2 * a * r0 * t * tf.math.sin(2 * Theta) + 2 * p * r0 * t * tf.math.sin(2 * Theta) - 2 * r0**2 * t * tf.math.sin(2 * Theta) + 2 * a * c * v * tf.math.sin(2 * Theta) - 2 * a * r * v * tf.math.sin(2 * Theta) - 2 * c * r0 * v * tf.math.sin(2 * Theta) + 2 * r * r0 * v * tf.math.sin(2 * Theta) + sqrt_two * q * v * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta))) - sqrt_two * b * v * tf.math.cos(2 * Theta) * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta))) + 2 * sqrt_two * r0 * v * tf.math.sin(Theta) * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta))) + sqrt_two * a * v * tf.math.sin(2 * Theta) * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta))) - sqrt_two * r0 * v * tf.math.sin(2 * Theta) * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta)))))/((t**2 + v**2) * (2 * a * t * tf.math.cos(2 * Theta) - 2 * r0 * t * tf.math.cos(2 * Theta) - 2 * b * u * tf.math.cos(2 * Theta) + 2 * r0 * u * tf.math.sin(Theta) + 2 * tf.math.cos(Theta) * (r0 * t + 2 * (b * t + (a - r0) * u) * tf.math.sin(Theta)) + sqrt_two * v * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta))))))
def detz(Cap_Psi,a,b,c,p,q,r,t,u,v,r0,Theta):
sqrt_two = tf.sqrt(tf.constant(2.,dtype=tf.float64))
return -(1/tf.math.sqrt(t**2 + v**2)) * v * (-p + r0 - r0 * tf.math.cos(Theta) + ((r0 * tf.math.cos(Theta) + (a - r0) * tf.math.cos(2 * Theta) + b * tf.math.sin(2 * Theta)) * (2 * p * t - 2 * r0 * t + 2 * q * u - 2 * c * v + 2 * r * v + 2 * r0 * t * tf.math.cos(Theta) + 2 * r0 * u * tf.math.sin(Theta) - sqrt_two * v * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta)))))/(2 * a * t * tf.math.cos(2 * Theta) - 2 * r0 * t * tf.math.cos(2 * Theta) - 2 * b * u * tf.math.cos(2 * Theta) + 2 * r0 * u * tf.math.sin(Theta) + 2 * tf.math.cos(Theta) * (r0 * t + 2 * (b * t + (a - r0) * u) * tf.math.sin(Theta)) + sqrt_two * v * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta))))) + 1/tf.math.sqrt(t**2 + v**2) * t * (c - r + 1/sqrt_two * (tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta)))) - (tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta))) * (-2 * p * t + 2 * r0 * t - 2 * q * u + 2 * c * v - 2 * r * v - 2 * r0 * t * tf.math.cos(Theta) - 2 * r0 * u * tf.math.sin(Theta) + sqrt_two * v * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta)))))/(sqrt_two * (2 * a * t * tf.math.cos(2 * Theta) - 2 * r0 * t * tf.math.cos(2 * Theta) - 2 * b * u * tf.math.cos(2 * Theta) + 2 * r0 * u * tf.math.sin(Theta) + 2 * tf.math.cos(Theta) * (r0 * t + 2 * (b * t + (a - r0) * u) * tf.math.sin(Theta)) + sqrt_two * v * tf.math.sqrt((tf.math.sin(Cap_Psi)**(-1))**2 * (r0**2 + (a**2 - b**2 - 2 * a * r0 + r0**2) * tf.math.cos(2 * Theta) + 4 * (a - r0) * r0 * tf.math.cos(Theta) * tf.math.cos(Cap_Psi)**2 + a**2 * tf.math.cos(2 * Cap_Psi) + b**2 * tf.math.cos(2 * Cap_Psi) - 2 * a * r0 * tf.math.cos(2 * Cap_Psi) + 2 * r0**2 * tf.math.cos(2 * Cap_Psi) + 2 * b * r0 * tf.math.sin(Theta) + 2 * b * r0 * tf.math.cos(2 * Cap_Psi) * tf.math.sin(Theta) + 2 * a * b * tf.math.sin(2 * Theta) - 2 * b * r0 * tf.math.sin(2 * Theta))))))
| 603.666667
| 4,565
| 0.501933
| 1,902
| 9,055
| 2.334911
| 0.019453
| 0.301283
| 0.247242
| 0.200405
| 0.976357
| 0.971628
| 0.957442
| 0.92254
| 0.865571
| 0.85206
| 0
| 0.083792
| 0.238211
| 9,055
| 14
| 4,566
| 646.785714
| 0.560017
| 0
| 0
| 0.2
| 0
| 0
| 0.000884
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0
| 0.6
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 12
|
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