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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
056d7991d476f8d0bf3dc096fa4ace03ede2fdbc
| 11,708
|
py
|
Python
|
src/generator/AutoRest.Python.Tests/Expected/AcceptanceTests/BodyString/autorestswaggerbatservice/operations/enum_operations.py
|
fhoering/autorest
|
b36c77ebb6a5c92aca72eea0894a683506af5817
|
[
"MIT"
] | null | null | null |
src/generator/AutoRest.Python.Tests/Expected/AcceptanceTests/BodyString/autorestswaggerbatservice/operations/enum_operations.py
|
fhoering/autorest
|
b36c77ebb6a5c92aca72eea0894a683506af5817
|
[
"MIT"
] | null | null | null |
src/generator/AutoRest.Python.Tests/Expected/AcceptanceTests/BodyString/autorestswaggerbatservice/operations/enum_operations.py
|
fhoering/autorest
|
b36c77ebb6a5c92aca72eea0894a683506af5817
|
[
"MIT"
] | null | null | null |
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.pipeline import ClientRawResponse
from .. import models
class EnumOperations(object):
"""EnumOperations operations.
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
"""
def __init__(self, client, config, serializer, deserializer):
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self.config = config
def get_not_expandable(
self, custom_headers=None, raw=False, **operation_config):
"""Get enum value 'red color' from enumeration of 'red color',
'green-color', 'blue_color'.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: :class:`Colors
<Fixtures.AcceptanceTestsBodyString.models.Colors>`
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsBodyString.models.ErrorException>`
"""
# Construct URL
url = '/string/enum/notExpandable'
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('Colors', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
def put_not_expandable(
self, string_body, custom_headers=None, raw=False, **operation_config):
"""Sends value 'red color' from enumeration of 'red color',
'green-color', 'blue_color'.
:param string_body: Possible values include: 'red color',
'green-color', 'blue_color'
:type string_body: str or :class:`Colors
<Fixtures.AcceptanceTestsBodyString.models.Colors>`
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: None
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsBodyString.models.ErrorException>`
"""
# Construct URL
url = '/string/enum/notExpandable'
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(string_body, 'Colors')
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
def get_referenced(
self, custom_headers=None, raw=False, **operation_config):
"""Get enum value 'red color' from enumeration of 'red color',
'green-color', 'blue_color'.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: :class:`Colors
<Fixtures.AcceptanceTestsBodyString.models.Colors>`
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsBodyString.models.ErrorException>`
"""
# Construct URL
url = '/string/enum/Referenced'
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('Colors', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
def put_referenced(
self, enum_string_body, custom_headers=None, raw=False, **operation_config):
"""Sends value 'red color' from enumeration of 'red color',
'green-color', 'blue_color'.
:param enum_string_body: Possible values include: 'red color',
'green-color', 'blue_color'
:type enum_string_body: str or :class:`Colors
<Fixtures.AcceptanceTestsBodyString.models.Colors>`
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: None
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsBodyString.models.ErrorException>`
"""
# Construct URL
url = '/string/enum/Referenced'
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(enum_string_body, 'Colors')
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
def get_referenced_constant(
self, custom_headers=None, raw=False, **operation_config):
"""Get value 'green-color' from the constant.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: :class:`RefColorConstant
<Fixtures.AcceptanceTestsBodyString.models.RefColorConstant>`
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsBodyString.models.ErrorException>`
"""
# Construct URL
url = '/string/enum/ReferencedConstant'
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('RefColorConstant', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
def put_referenced_constant(
self, field1=None, custom_headers=None, raw=False, **operation_config):
"""Sends value 'green-color' from a constant.
:param field1: Sample string.
:type field1: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: None
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsBodyString.models.ErrorException>`
"""
enum_string_body = models.RefColorConstant(field1=field1)
# Construct URL
url = '/string/enum/ReferencedConstant'
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(enum_string_body, 'RefColorConstant')
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
| 37.405751
| 90
| 0.654339
| 1,161
| 11,708
| 6.443583
| 0.11714
| 0.041706
| 0.036893
| 0.024061
| 0.872343
| 0.872343
| 0.872343
| 0.872343
| 0.872343
| 0.859377
| 0
| 0.004446
| 0.250854
| 11,708
| 312
| 91
| 37.525641
| 0.848478
| 0.417578
| 0
| 0.811966
| 0
| 0
| 0.078269
| 0.02642
| 0
| 0
| 0
| 0
| 0
| 1
| 0.059829
| false
| 0
| 0.017094
| 0
| 0.162393
| 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
|
5537614555a7111675bc7d0366d8b1818cb8f3d4
| 13,840
|
py
|
Python
|
tests/test_live_cp_remote.py
|
robclewley/gs-wrap
|
124f3bb54301c27c5389ca626fb16e21f9343b0f
|
[
"MIT"
] | 9
|
2020-03-19T13:16:32.000Z
|
2021-02-15T16:42:08.000Z
|
tests/test_live_cp_remote.py
|
robclewley/gs-wrap
|
124f3bb54301c27c5389ca626fb16e21f9343b0f
|
[
"MIT"
] | 3
|
2019-02-11T11:28:21.000Z
|
2021-02-15T16:40:34.000Z
|
tests/test_live_cp_remote.py
|
robclewley/gs-wrap
|
124f3bb54301c27c5389ca626fb16e21f9343b0f
|
[
"MIT"
] | 3
|
2019-06-17T07:39:20.000Z
|
2020-07-23T00:03:23.000Z
|
#!/usr/bin/env python
"""Test gs-wrap cp remote live."""
# pylint: disable=missing-docstring
# pylint: disable=too-many-lines
# pylint: disable=protected-access
# pylint: disable=expression-not-assigned
import subprocess
import tempfile
import unittest
import uuid
from typing import Set
import google.api_core.exceptions
import gswrap
import tests.common
class TestCPRemote(unittest.TestCase):
def setUp(self) -> None:
self.client = gswrap.Client()
self.client._change_bucket(tests.common.TEST_GCS_BUCKET)
self.bucket_prefix = str(uuid.uuid4())
self.tmp_dir = tempfile.TemporaryDirectory()
tests.common.gcs_test_setup(
tmp_dir_name=self.tmp_dir.name, prefix=self.bucket_prefix)
def tearDown(self) -> None:
tests.common.gcs_test_teardown(prefix=self.bucket_prefix)
self.tmp_dir.cleanup()
def test_copy_file_to_file_in_same_bucket(self) -> None:
src = 'gs://{}/{}/d1/f11'.format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
dst = 'gs://{}/{}/ftest'.format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
self.client.cp(src=src, dst=dst, recursive=False)
src_blob = self.client._bucket.get_blob(
blob_name="{}/d1/f11".format(self.bucket_prefix))
src_text = src_blob.download_as_string()
dst_blob = self.client._bucket.get_blob(
blob_name="{}/ftest".format(self.bucket_prefix))
dst_text = dst_blob.download_as_string()
self.assertEqual(src_text, dst_text)
def test_copy_folder_in_same_bucket(self) -> None:
src = 'gs://{}/{}/d1/'.format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
dst = 'gs://{}/{}/dtest1/'.format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
self.client.cp(src=src, dst=dst, recursive=True)
src_list = self.client.ls(url=src, recursive=True)
dst_list = self.client.ls(url=dst, recursive=True)
for src_file, dst_file in zip(src_list, dst_list):
src_file = src_file.replace(src, dst + 'd1/')
self.assertEqual(src_file, dst_file)
def test_copy_files_in_same_bucket(self) -> None:
src = 'gs://{}/{}/d1/'.format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
dst = 'gs://{}/{}/dtest1'.format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
self.client.cp(src=src, dst=dst, recursive=True)
src_list = self.client.ls(url=src, recursive=True)
dst_list = self.client.ls(url=dst, recursive=True)
for src_file, dst_file in zip(src_list, dst_list):
src_file = src_file.replace(src, dst + '/')
self.assertEqual(src_file, dst_file)
def test_gsutil_vs_gswrap_copy_recursive(self) -> None: # pylint: disable=invalid-name
# yapf: disable
test_cases = [
["gs://{}/{}/d1".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/dtest/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/dtest/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/dtest".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/dtest".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d3/d31/d311/f3111".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/ftest".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d3/d31/d311/f3111".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/ftest/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1/f11".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/ftest".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1/f11".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/ftest/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
]
# yapf: enable
gsutil_ls_set = set() # type: Set[str]
gcs_ls_set = set() # type: Set[str]
ls_path = "gs://{}/{}/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
for test_case in test_cases:
self.client.cp(src=test_case[0], dst=test_case[1], recursive=True)
gcs_paths = self.client.ls(url=ls_path, recursive=True)
gcs_ls_set.union(gcs_paths)
tests.common.call_gsutil_rm(
path="gs://{}/{}/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
recursive=True)
tests.common.gcs_test_setup(
tmp_dir_name=self.tmp_dir.name, prefix=self.bucket_prefix)
tests.common.call_gsutil_cp(
src=test_case[0], dst=test_case[1], recursive=True)
gsutil_paths = self.client.ls(url=ls_path, recursive=True)
gsutil_ls_set.union(gsutil_paths)
tests.common.call_gsutil_rm(
path="gs://{}/{}/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
recursive=True)
tests.common.gcs_test_setup(
tmp_dir_name=self.tmp_dir.name, prefix=self.bucket_prefix)
self.assertListEqual(sorted(gsutil_paths), sorted(gcs_paths))
self.assertListEqual(list(gsutil_ls_set), list(gcs_ls_set))
def test_gsutil_vs_gswrap_copy_non_recursive(self) -> None: # pylint: disable=invalid-name
# yapf: disable
test_cases = [
["gs://{}/{}/d3/d31/d311/f3111".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/ftest".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d3/d31/d311/f3111".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/ftest/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1/f11".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/ftest".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1/f11".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/ftest/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
]
# yapf: enable
gsutil_ls_set = set() # type: Set[str]
gcs_ls_set = set() # type: Set[str]
ls_path = "gs://{}/{}/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
for test_case in test_cases:
self.client.cp(src=test_case[0], dst=test_case[1], recursive=False)
gcs_paths = self.client.ls(url=ls_path, recursive=True)
gcs_ls_set.union(gcs_paths)
tests.common.call_gsutil_rm(
path="gs://{}/{}/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
recursive=True)
tests.common.gcs_test_setup(
tmp_dir_name=self.tmp_dir.name, prefix=self.bucket_prefix)
tests.common.call_gsutil_cp(
src=test_case[0], dst=test_case[1], recursive=False)
gsutil_paths = self.client.ls(url=ls_path, recursive=True)
gsutil_ls_set.union(gsutil_paths)
tests.common.call_gsutil_rm(
path="gs://{}/{}/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
recursive=True)
tests.common.gcs_test_setup(
tmp_dir_name=self.tmp_dir.name, prefix=self.bucket_prefix)
self.assertListEqual(sorted(gsutil_paths), sorted(gcs_paths))
self.assertListEqual(list(gsutil_ls_set), list(gcs_ls_set))
def test_gsutil_vs_gswrap_copy_non_recursive_check_raises(self) -> None: # pylint: disable=invalid-name
# yapf: disable
test_cases = [
["gs://{}/{}/d1".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/dtest/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/dtest/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/dtest".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
["gs://{}/{}/d1/".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix),
"gs://{}/{}/dtest".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)],
]
# yapf: enable
for test_case in test_cases:
self.assertRaises(
google.api_core.exceptions.GoogleAPIError,
self.client.cp,
src=test_case[0],
dst=test_case[1],
recursive=False)
self.assertRaises(
subprocess.CalledProcessError,
tests.common.call_gsutil_cp,
src=test_case[0],
dst=test_case[1],
recursive=False)
def test_cp_no_clobber(self) -> None:
# yapf: disable
test_case = [
"gs://{}/{}/d1/d11/f111".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
,
"gs://{}/{}/play/d2/ff".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
]
# yapf: enable
path_f111 = gswrap.resource_type(res_loc=test_case[0])
path_ff = gswrap.resource_type(res_loc=test_case[1])
assert isinstance(path_f111, gswrap._GCSURL)
assert isinstance(path_ff, gswrap._GCSURL)
blob_f11 = self.client._bucket.get_blob(path_f111.prefix)
blob_ff = self.client._bucket.get_blob(path_ff.prefix)
timestamp_f11 = blob_f11.updated
timestamp_ff = blob_ff.updated
self.client.cp(src=test_case[0], dst=test_case[1], no_clobber=True)
blob_f11_not_updated = self.client._bucket.get_blob(path_f111.prefix)
blob_ff_not_updated = self.client._bucket.get_blob(path_ff.prefix)
timestamp_f11_not_updated = blob_f11_not_updated.updated
timestamp_ff_not_updated = blob_ff_not_updated.updated
self.assertEqual(timestamp_f11, timestamp_f11_not_updated)
self.assertEqual(timestamp_ff, timestamp_ff_not_updated)
def test_cp_clobber(self) -> None:
# yapf: disable
test_case = [
"gs://{}/{}/d1/d11/f111".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
,
"gs://{}/{}/play/d2/ff".format(tests.common.TEST_GCS_BUCKET,
self.bucket_prefix)
]
# yapf: enable
path_f111 = gswrap.resource_type(res_loc=test_case[0])
path_ff = gswrap.resource_type(res_loc=test_case[1])
assert isinstance(path_f111, gswrap._GCSURL)
assert isinstance(path_ff, gswrap._GCSURL)
blob_f11 = self.client._bucket.get_blob(path_f111.prefix)
blob_ff = self.client._bucket.get_blob(path_ff.prefix)
timestamp_f11 = blob_f11.updated
timestamp_ff = blob_ff.updated
self.client.cp(src=test_case[0], dst=test_case[1], no_clobber=False)
blob_f11_not_updated = self.client._bucket.get_blob(path_f111.prefix)
blob_ff_updated = self.client._bucket.get_blob(path_ff.prefix)
timestamp_f11_not_updated = blob_f11_not_updated.updated
timestamp_ff_updated = blob_ff_updated.updated
self.assertEqual(timestamp_f11, timestamp_f11_not_updated)
self.assertNotEqual(timestamp_ff, timestamp_ff_updated)
if __name__ == '__main__':
unittest.main()
| 44.645161
| 108
| 0.548699
| 1,554
| 13,840
| 4.585586
| 0.085586
| 0.09725
| 0.127982
| 0.123772
| 0.865422
| 0.861774
| 0.859248
| 0.855599
| 0.82641
| 0.82641
| 0
| 0.017384
| 0.326662
| 13,840
| 309
| 109
| 44.789644
| 0.74729
| 0.033887
| 0
| 0.733333
| 0
| 0
| 0.062125
| 0.014838
| 0
| 0
| 0
| 0
| 0.070833
| 1
| 0.041667
| false
| 0
| 0.033333
| 0
| 0.079167
| 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
|
e971803a569b37321b878f28958b44e7c1f9bb96
| 47
|
py
|
Python
|
Solutions/Challenges/__init__.py
|
dev-11/codility-solutions
|
01b0ce4a43b1390fe15f2daabea95e90b834fbfc
|
[
"MIT"
] | null | null | null |
Solutions/Challenges/__init__.py
|
dev-11/codility-solutions
|
01b0ce4a43b1390fe15f2daabea95e90b834fbfc
|
[
"MIT"
] | null | null | null |
Solutions/Challenges/__init__.py
|
dev-11/codility-solutions
|
01b0ce4a43b1390fe15f2daabea95e90b834fbfc
|
[
"MIT"
] | null | null | null |
from .omega_2013 import solution as omega_2013
| 23.5
| 46
| 0.851064
| 8
| 47
| 4.75
| 0.75
| 0.473684
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.195122
| 0.12766
| 47
| 1
| 47
| 47
| 0.731707
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
75ced06dd92a74c3a7ce739cf0dca496e1a8cc8e
| 2,946
|
py
|
Python
|
tests/domain/test_Track_remove_tracks.py
|
josiah-wolf-oberholtzer/tloen
|
731e57f2a0634d5e472c5878ff5b9cc7b4d84974
|
[
"MIT"
] | 3
|
2020-02-09T09:29:45.000Z
|
2021-12-29T01:37:45.000Z
|
tests/domain/test_Track_remove_tracks.py
|
josiah-wolf-oberholtzer/tloen
|
731e57f2a0634d5e472c5878ff5b9cc7b4d84974
|
[
"MIT"
] | null | null | null |
tests/domain/test_Track_remove_tracks.py
|
josiah-wolf-oberholtzer/tloen
|
731e57f2a0634d5e472c5878ff5b9cc7b4d84974
|
[
"MIT"
] | 1
|
2020-12-12T22:29:48.000Z
|
2020-12-12T22:29:48.000Z
|
import pytest
from tloen.domain import Application
@pytest.mark.asyncio
async def test_1():
"""
Remove one track
"""
application = Application()
context = await application.add_context()
parent = await context.add_track()
track = await parent.add_track()
await parent.remove_tracks(track)
assert list(parent.tracks) == []
assert track.application is None
assert track.graph_order == ()
assert track.parent is None
assert track.provider is None
@pytest.mark.asyncio
async def test_2():
"""
Remove two tracks
"""
application = Application()
context = await application.add_context()
parent = await context.add_track()
track_one = await parent.add_track()
track_two = await parent.add_track()
await parent.remove_tracks(track_one, track_two)
assert list(parent.tracks) == []
assert track_one.application is None
assert track_one.graph_order == ()
assert track_one.parent is None
assert track_one.provider is None
assert track_two.application is None
assert track_two.graph_order == ()
assert track_two.parent is None
assert track_two.provider is None
@pytest.mark.asyncio
async def test_3():
"""
Remove first track, leaving second untouched
"""
application = Application()
context = await application.add_context()
parent = await context.add_track()
track_one = await parent.add_track()
track_two = await parent.add_track()
await parent.remove_tracks(track_one)
assert list(parent.tracks) == [track_two]
assert track_one.application is None
assert track_one.graph_order == ()
assert track_one.parent is None
assert track_one.provider is None
assert track_two.application is context.application
assert track_two.graph_order == (3, 0, 0, 0, 1, 0)
assert track_two.parent is parent.tracks
assert track_two.provider is None
@pytest.mark.asyncio
async def test_4():
"""
Boot, remove first track, leaving second untouched
"""
application = Application()
context = await application.add_context()
parent = await context.add_track()
track_one = await parent.add_track()
track_two = await parent.add_track()
await application.boot()
with context.provider.server.osc_protocol.capture() as transcript:
await parent.remove_tracks(track_one)
assert list(parent.tracks) == [track_two]
assert track_one.application is None
assert track_one.graph_order == ()
assert track_one.parent is None
assert track_one.provider is None
assert track_two.application is context.application
assert track_two.graph_order == (3, 0, 0, 0, 1, 0)
assert track_two.parent is parent.tracks
assert track_two.provider is context.provider
assert len(transcript.sent_messages) == 1
_, message = transcript.sent_messages[0]
assert message.to_list() == [None, [["/n_set", 1009, "gate", 0]]]
| 32.021739
| 70
| 0.705703
| 395
| 2,946
| 5.081013
| 0.134177
| 0.153463
| 0.077728
| 0.110115
| 0.854011
| 0.801694
| 0.759841
| 0.759841
| 0.759841
| 0.714998
| 0
| 0.009766
| 0.200611
| 2,946
| 91
| 71
| 32.373626
| 0.842463
| 0
| 0
| 0.685714
| 0
| 0
| 0.00363
| 0
| 0
| 0
| 0
| 0
| 0.485714
| 1
| 0
| false
| 0
| 0.028571
| 0
| 0.028571
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
75f40bc548570ffd6006738a0001e0702d85658c
| 6,979
|
py
|
Python
|
mayan/apps/document_states/tests/test_workflow_template_transition_views.py
|
bonitobonita24/Mayan-EDMS
|
7845fe0e1e83c81f5d227a16116397a3d3883b85
|
[
"Apache-2.0"
] | 343
|
2015-01-05T14:19:35.000Z
|
2018-12-10T19:07:48.000Z
|
mayan/apps/document_states/tests/test_workflow_template_transition_views.py
|
bonitobonita24/Mayan-EDMS
|
7845fe0e1e83c81f5d227a16116397a3d3883b85
|
[
"Apache-2.0"
] | 191
|
2015-01-03T00:48:19.000Z
|
2018-11-30T09:10:25.000Z
|
mayan/apps/document_states/tests/test_workflow_template_transition_views.py
|
bonitobonita24/Mayan-EDMS
|
7845fe0e1e83c81f5d227a16116397a3d3883b85
|
[
"Apache-2.0"
] | 114
|
2015-01-08T20:21:05.000Z
|
2018-12-10T19:07:53.000Z
|
from mayan.apps.testing.tests.base import GenericViewTestCase
from ..events import event_workflow_template_edited
from ..models import WorkflowTransition
from ..permissions import (
permission_workflow_template_edit, permission_workflow_template_view
)
from .literals import TEST_WORKFLOW_TEMPLATE_TRANSITION_LABEL
from .mixins.workflow_template_mixins import (
WorkflowTemplateTestMixin, WorkflowTemplateViewTestMixin
)
from .mixins.workflow_template_transition_mixins import (
WorkflowTemplateTransitionViewTestMixin
)
class WorkflowTransitionViewTestCase(
WorkflowTemplateTestMixin, WorkflowTemplateViewTestMixin,
WorkflowTemplateTransitionViewTestMixin, GenericViewTestCase
):
def setUp(self):
super().setUp()
self._create_test_workflow_template()
self._create_test_workflow_template_state()
self._create_test_workflow_template_state()
def test_workflow_template_transition_create_view_no_permission(self):
self._clear_events()
response = self._request_test_workflow_template_transition_create_view()
self.assertEqual(response.status_code, 404)
self.assertEqual(WorkflowTransition.objects.count(), 0)
events = self._get_test_events()
self.assertEqual(events.count(), 0)
def test_workflow_template_transition_create_view_with_access(self):
self.grant_access(
obj=self._test_workflow_template,
permission=permission_workflow_template_edit
)
self._clear_events()
response = self._request_test_workflow_template_transition_create_view()
self.assertEqual(response.status_code, 302)
self.assertEqual(WorkflowTransition.objects.count(), 1)
self.assertEqual(
WorkflowTransition.objects.all()[0].label,
TEST_WORKFLOW_TEMPLATE_TRANSITION_LABEL
)
self.assertEqual(
WorkflowTransition.objects.all()[0].origin_state,
self._test_workflow_template_states[0]
)
self.assertEqual(
WorkflowTransition.objects.all()[0].destination_state,
self._test_workflow_template_states[1]
)
events = self._get_test_events()
self.assertEqual(events.count(), 1)
self.assertEqual(
events[0].action_object, self._test_workflow_template_transition
)
self.assertEqual(events[0].actor, self._test_case_user)
self.assertEqual(events[0].target, self._test_workflow_template)
self.assertEqual(events[0].verb, event_workflow_template_edited.id)
def test_workflow_template_transition_delete_view_no_permission(self):
self._create_test_workflow_template_transition()
self._clear_events()
response = self._request_test_workflow_template_transition_delete_view()
self.assertEqual(response.status_code, 404)
self.assertTrue(
self._test_workflow_template_transition in WorkflowTransition.objects.all()
)
events = self._get_test_events()
self.assertEqual(events.count(), 0)
def test_workflow_template_transition_delete_view_with_access(self):
self._create_test_workflow_template_transition()
self.grant_access(
obj=self._test_workflow_template,
permission=permission_workflow_template_edit
)
self._clear_events()
response = self._request_test_workflow_template_transition_delete_view()
self.assertEqual(response.status_code, 302)
self.assertFalse(
self._test_workflow_template_transition in WorkflowTransition.objects.all()
)
events = self._get_test_events()
self.assertEqual(events.count(), 1)
self.assertEqual(events[0].action_object, None)
self.assertEqual(events[0].actor, self._test_case_user)
self.assertEqual(events[0].target, self._test_workflow_template)
self.assertEqual(events[0].verb, event_workflow_template_edited.id)
def test_workflow_template_transition_edit_view_no_permission(self):
self._create_test_workflow_template_transition()
test_workflow_template_transition_label = self._test_workflow_template_transition.label
self._clear_events()
response = self._request_test_workflow_template_transition_edit_view()
self.assertEqual(response.status_code, 404)
self._test_workflow_template_transition.refresh_from_db()
self.assertEqual(
self._test_workflow_template_transition.label,
test_workflow_template_transition_label
)
events = self._get_test_events()
self.assertEqual(events.count(), 0)
def test_workflow_template_transition_edit_view_with_access(self):
self._create_test_workflow_template_transition()
test_workflow_template_transition_label = self._test_workflow_template_transition.label
self.grant_access(
obj=self._test_workflow_template,
permission=permission_workflow_template_edit
)
self._clear_events()
response = self._request_test_workflow_template_transition_edit_view()
self.assertEqual(response.status_code, 302)
self._test_workflow_template_transition.refresh_from_db()
self.assertNotEqual(
self._test_workflow_template_transition.label,
test_workflow_template_transition_label
)
events = self._get_test_events()
self.assertEqual(events.count(), 1)
self.assertEqual(
events[0].action_object, self._test_workflow_template_transition
)
self.assertEqual(events[0].actor, self._test_case_user)
self.assertEqual(events[0].target, self._test_workflow_template)
self.assertEqual(events[0].verb, event_workflow_template_edited.id)
def test_workflow_template_transition_list_view_no_permission(self):
self._create_test_workflow_template_transition()
self._clear_events()
response = self._request_test_workflow_template_transition_list_view()
self.assertNotContains(
response=response,
text=self._test_workflow_template_transition.label,
status_code=404
)
events = self._get_test_events()
self.assertEqual(events.count(), 0)
def test_workflow_template_transition_list_view_with_access(self):
self._create_test_workflow_template_transition()
self.grant_access(
obj=self._test_workflow_template,
permission=permission_workflow_template_view
)
self._clear_events()
response = self._request_test_workflow_template_transition_list_view()
self.assertContains(
response=response,
text=self._test_workflow_template_transition.label,
status_code=200
)
events = self._get_test_events()
self.assertEqual(events.count(), 0)
| 36.348958
| 95
| 0.722023
| 741
| 6,979
| 6.311741
| 0.105263
| 0.218944
| 0.222365
| 0.256575
| 0.85247
| 0.814625
| 0.747915
| 0.730597
| 0.723327
| 0.701518
| 0
| 0.009204
| 0.206047
| 6,979
| 191
| 96
| 36.539267
| 0.834867
| 0
| 0
| 0.594595
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0.060811
| false
| 0
| 0.047297
| 0
| 0.114865
| 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
|
f99206c4c5916af18add1da2237fa81731bd6f09
| 40,251
|
py
|
Python
|
circuit_training/environment/plc_client_test.py
|
sguada/circuit_training
|
220ca925c83cdc6e67181c305da577f305c602b3
|
[
"Apache-2.0"
] | 280
|
2022-01-15T01:09:34.000Z
|
2022-03-24T01:47:04.000Z
|
circuit_training/environment/plc_client_test.py
|
google-research/circuit-training
|
dd197800aa3c82a5712bc3c29a0790058a54bad2
|
[
"Apache-2.0"
] | 14
|
2022-01-19T02:42:45.000Z
|
2022-03-31T03:42:36.000Z
|
circuit_training/environment/plc_client_test.py
|
google-research/circuit-training
|
dd197800aa3c82a5712bc3c29a0790058a54bad2
|
[
"Apache-2.0"
] | 42
|
2022-01-14T22:58:45.000Z
|
2022-03-26T13:20:31.000Z
|
# coding=utf-8
# Copyright 2021 The Circuit Training Team Authors.
#
# 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.
"""Tests for plc_client."""
import os
from absl import flags
from circuit_training.environment import plc_client
from circuit_training.utils import test_utils
import gin
FLAGS = flags.FLAGS
MACRO_ADJACENCY = [
0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0,
3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0,
0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0,
0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0,
0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0,
0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0,
0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0,
0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3,
0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0,
3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3,
0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0,
3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0,
0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0,
0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,
0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0,
0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0,
0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0,
0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3,
0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0,
0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0,
0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,
0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0,
0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0,
0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0,
0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3,
0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0
]
class PlcClientTest(test_utils.TestCase):
"""Tests for the PlcClient.
# Internal circuit training docs link.
"""
def test_plc_client(self):
test_netlist_dir = ('circuit_training/'
'environment/test_data/macro_tiles_10x10')
netlist_file = os.path.join(FLAGS.test_srcdir, test_netlist_dir,
'netlist.pb.txt')
plc = plc_client.PlacementCost(netlist_file)
self.assertAlmostEqual(plc.get_cost(), 0.007745966692414834)
self.assertEqual(plc.get_area(), 250000)
self.assertEqual(plc.get_wirelength(), 5400)
self.assertAlmostEqual(plc.get_congestion_cost(), 1.124405186246434)
self.assertAlmostEqual(plc.get_density_cost(), 0.3570806661517036)
self.assertTrue(plc.set_canvas_size(1200.0, 1200.0))
self.assertEqual(plc.get_canvas_width_height(), (1200.0, 1200.0))
self.assertTrue(plc.set_placement_grid(20, 20))
self.assertEqual(plc.get_grid_num_columns_rows(), (20, 20))
self.assertEqual(plc.get_macro_indices(), [
0, 13, 26, 39, 52, 65, 78, 91, 104, 117, 130, 143, 156, 169, 182, 195,
208, 221, 234, 247, 260, 273, 286, 299, 312, 325, 338, 351, 364, 377,
390, 403, 416, 429, 442, 455, 468, 481, 494, 507, 520, 533, 546, 559,
572, 585, 598, 611, 624, 637, 650, 663, 676, 689, 702, 715, 728, 741,
754, 767, 780, 793, 806, 819, 832, 845, 858, 871, 884, 897, 910, 923,
936, 949, 962, 975, 988, 1001, 1014, 1027, 1040, 1053, 1066, 1079, 1092,
1105, 1118, 1131, 1144, 1157, 1170, 1183, 1196, 1209, 1222, 1235, 1248,
1261, 1274, 1287
])
plc.set_project_name('circuit_training')
self.assertEqual(plc.get_project_name(), 'circuit_training')
plc.set_block_name('macro_tiles_10x10')
self.assertEqual(plc.get_block_name(), 'macro_tiles_10x10')
plc.set_routes_per_micron(1.0, 2.0)
self.assertEqual(plc.get_routes_per_micron(), (1.0, 2.0))
plc.set_congestion_smooth_range(2.0)
self.assertEqual(plc.get_congestion_smooth_range(), 2.0)
plc.set_overlap_threshold(2.0)
self.assertEqual(plc.get_overlap_threshold(), 2.0)
plc.set_canvas_boundary_check(False)
self.assertFalse(plc.get_canvas_boundary_check())
plc.set_macro_routing_allocation(3.0, 4.0)
self.assertEqual(plc.get_macro_routing_allocation(), (3.0, 4.0))
self.assertFalse(plc.is_node_soft_macro(13))
self.assertEqual(
plc.get_node_mask(13), [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0,
0, 0, 0, 0, 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, 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, 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,
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, 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
])
self.assertEqual(
plc.get_node_mask('M_R0_C1'), [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0,
0, 0, 0, 0, 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, 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, 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,
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, 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
])
self.assertEqual(plc.get_node_type(9), 'MACRO_PIN')
plc.make_soft_macros_square()
self.assertEqual(plc.get_macro_adjacency(), MACRO_ADJACENCY)
self.assertFalse(plc.is_node_fixed(13))
plc.unplace_all_nodes()
self.assertTrue(plc.place_node(13, 180))
self.assertTrue(plc.place_node('M_R0_C1', 230))
initial_placement = os.path.join(FLAGS.test_srcdir, test_netlist_dir,
'initial.plc')
self.assertTrue(plc.restore_placement(initial_placement))
use_current_loc = False
move_stdcells = True
move_macros = False
log_scale_conns = False
use_sizes = False
io_factor = 1.0
num_steps = [100, 100, 100]
max_move_distance = [1200.0, 1200.0, 1200.0]
attract_factor = [100, 1e-3, 1e-5]
repel_factor = [0, 1e6, 1e7]
self.assertTrue(
plc.optimize_stdcells(use_current_loc, move_stdcells, move_macros,
log_scale_conns, use_sizes, io_factor, num_steps,
max_move_distance, attract_factor, repel_factor))
self.assertTrue(plc.update_node_coords(13, 50.0, 50.0))
self.assertTrue(plc.update_node_coords(13, 50.0, 50.0, True))
self.assertTrue(plc.update_node_coords('M_R0_C1', 50.0, 50.0))
self.assertTrue(plc.fix_node_coord(13))
self.assertTrue(plc.fix_node_coord('M_R0_C1'))
plc.update_port_sides()
plc.snap_ports_to_edges()
self.assertEqual(plc.get_macro_and_clustered_port_adjacency(),
(MACRO_ADJACENCY, []))
self.assertEqual(plc.get_node_location(13), (50.0, 50.0))
self.assertTrue(plc.is_node_placed(13))
self.assertEqual(plc.get_node_location(13), (50.0, 50.0))
self.assertEqual(plc.get_grid_cell_of_node(13), 0)
self.assertTrue(plc.update_macro_orientation(13, 'S'))
self.assertTrue(plc.update_macro_orientation('M_R0_C1', 'S'))
self.assertEqual(plc.get_macro_orientation(13), 'S')
self.assertTrue(plc.unfix_node_coord(13))
self.assertTrue(plc.unplace_node(13))
self.assertFalse(plc.is_node_placed(13))
self.assertEqual(plc.get_source_filename(), netlist_file)
self.assertEqual(plc.get_blockages(), [])
self.assertEqual(plc.get_ref_node_id(13), -1)
initial_placement = os.path.join(self.create_tempdir(), 'initial.plc')
self.assertTrue(plc.save_placement(initial_placement, 'Info'))
self.assertTrue(os.path.exists(initial_placement))
if __name__ == '__main__':
test_utils.main()
| 69.759099
| 80
| 0.369308
| 11,648
| 40,251
| 1.25807
| 0.027387
| 1.290979
| 1.875256
| 2.418725
| 0.827351
| 0.795619
| 0.775078
| 0.766002
| 0.761226
| 0.75215
| 0
| 0.430959
| 0.344538
| 40,251
| 576
| 81
| 69.880208
| 0.124474
| 0.016695
| 0
| 0.811808
| 0
| 0
| 0.005487
| 0.000986
| 0
| 0
| 0
| 0
| 0.088561
| 1
| 0.001845
| false
| 0
| 0.009225
| 0
| 0.012915
| 0
| 0
| 0
| 1
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 13
|
f9b19fdc316292c0b707c4b4053cda99f3ce195b
| 131
|
py
|
Python
|
h1st/model/rule_based_model.py
|
phanhongan/h1st
|
ddde59018b7ad44133135d2bfc7f47dc7277e00e
|
[
"Apache-2.0"
] | 2
|
2021-08-20T18:11:54.000Z
|
2021-09-28T15:59:58.000Z
|
h1st/model/rule_based_model.py
|
phanhongan/h1st
|
ddde59018b7ad44133135d2bfc7f47dc7277e00e
|
[
"Apache-2.0"
] | null | null | null |
h1st/model/rule_based_model.py
|
phanhongan/h1st
|
ddde59018b7ad44133135d2bfc7f47dc7277e00e
|
[
"Apache-2.0"
] | 1
|
2021-06-05T01:30:47.000Z
|
2021-06-05T01:30:47.000Z
|
from h1st.model.model import Model
from .predictive_model import PredictiveModel
class RuleBasedModel(PredictiveModel):
pass
| 18.714286
| 45
| 0.824427
| 15
| 131
| 7.133333
| 0.6
| 0.205607
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008772
| 0.129771
| 131
| 6
| 46
| 21.833333
| 0.929825
| 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 | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 7
|
ddaa3151e89a2fde3e7c1ea432eda1dbb617a75e
| 79,808
|
py
|
Python
|
groupdocs/MergeApi.py
|
groupdocs-legacy-sdk/python
|
80e5ef5a9a14ac4a7815c6cf933b5b2997381455
|
[
"Apache-2.0"
] | null | null | null |
groupdocs/MergeApi.py
|
groupdocs-legacy-sdk/python
|
80e5ef5a9a14ac4a7815c6cf933b5b2997381455
|
[
"Apache-2.0"
] | null | null | null |
groupdocs/MergeApi.py
|
groupdocs-legacy-sdk/python
|
80e5ef5a9a14ac4a7815c6cf933b5b2997381455
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
"""
Copyright 2012 GroupDocs.
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.
NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually.
"""
import sys
import os
from models import *
from groupdocs.FileStream import FileStream
from groupdocs.ApiClient import ApiException
class MergeApi(object):
def __init__(self, apiClient):
self.apiClient = apiClient
self.__basePath = "https://api.groupdocs.com/v2.0"
@property
def basePath(self):
return self.__basePath
@basePath.setter
def basePath(self, value):
self.__basePath = value
def AddJobDocumentDataSource(self, userId, jobId, fileId, datasourceId, **kwargs):
"""Add job document datasource
Args:
userId, str: User GUID (required)
jobId, int: Job indetifier (required)
fileId, int: File indetifier (required)
datasourceId, int: Datasource indetifier (required)
Returns: AddDocumentDataSourceResponse
"""
if( userId == None or jobId == None or fileId == None or datasourceId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'jobId', 'fileId', 'datasourceId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method AddJobDocumentDataSource" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/jobs/{jobId}/files/{fileId}/datasources/{datasourceId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('jobId' in params):
replacement = str(self.apiClient.toPathValue(params['jobId']))
resourcePath = resourcePath.replace('{' + 'jobId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
if ('datasourceId' in params):
replacement = str(self.apiClient.toPathValue(params['datasourceId']))
resourcePath = resourcePath.replace('{' + 'datasourceId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddDocumentDataSourceResponse')
return responseObject
def AddJobDocumentDataSourceFields(self, userId, jobId, fileId, body, **kwargs):
"""Add job document datasource fields
Args:
userId, str: User GUID (required)
jobId, str: Job id (required)
fileId, str: File GUID (required)
body, List[DatasourceField]: Fields (required)
Returns: AddDocumentDataSourceResponse
"""
if( userId == None or jobId == None or fileId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'jobId', 'fileId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method AddJobDocumentDataSourceFields" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/jobs/{jobId}/files/{fileId}/datasources'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('jobId' in params):
replacement = str(self.apiClient.toPathValue(params['jobId']))
resourcePath = resourcePath.replace('{' + 'jobId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddDocumentDataSourceResponse')
return responseObject
def FillQuestionnaire(self, userId, collectorId, datasourceId, **kwargs):
"""Merge datasource
Args:
userId, str: User global unique identifier (required)
collectorId, str: Collector global unique identifier to fill (required)
datasourceId, str: Datasource identifier (required)
targetType, str: Filled document type (optional)
emailResults, str: Email results (optional)
callbackUrl, str: Callback url (optional)
Returns: MergeTemplateResponse
"""
if( userId == None or collectorId == None or datasourceId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'collectorId', 'datasourceId', 'targetType', 'emailResults', 'callbackUrl']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method FillQuestionnaire" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/collectors/{collectorId}/datasources/{datasourceId}?new_type={targetType}&email_results={emailResults}&callback={callbackUrl}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('targetType' in params):
queryParams['new_type'] = self.apiClient.toPathValue(params['targetType'])
if ('emailResults' in params):
queryParams['email_results'] = self.apiClient.toPathValue(params['emailResults'])
if ('callbackUrl' in params):
queryParams['callback'] = self.apiClient.toPathValue(params['callbackUrl'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('collectorId' in params):
replacement = str(self.apiClient.toPathValue(params['collectorId']))
resourcePath = resourcePath.replace('{' + 'collectorId' + '}',
replacement)
if ('datasourceId' in params):
replacement = str(self.apiClient.toPathValue(params['datasourceId']))
resourcePath = resourcePath.replace('{' + 'datasourceId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'MergeTemplateResponse')
return responseObject
def FillExecution(self, userId, executionId, datasourceId, **kwargs):
"""Scheduled questionnaire execution fullfilment job
Args:
userId, str: User global unique identifier (required)
executionId, str: Execution global unique identifier to fill (required)
datasourceId, str: Datasource identifier (required)
targetType, str: Filled document type (optional)
emailResults, str: Email results (optional)
callbackUrl, str: Callback url (optional)
Returns: MergeTemplateResponse
"""
if( userId == None or executionId == None or datasourceId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'executionId', 'datasourceId', 'targetType', 'emailResults', 'callbackUrl']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method FillExecution" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/executions/{executionId}/datasources/{datasourceId}?new_type={targetType}&email_results={emailResults}&callback={callbackUrl}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('targetType' in params):
queryParams['new_type'] = self.apiClient.toPathValue(params['targetType'])
if ('emailResults' in params):
queryParams['email_results'] = self.apiClient.toPathValue(params['emailResults'])
if ('callbackUrl' in params):
queryParams['callback'] = self.apiClient.toPathValue(params['callbackUrl'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('executionId' in params):
replacement = str(self.apiClient.toPathValue(params['executionId']))
resourcePath = resourcePath.replace('{' + 'executionId' + '}',
replacement)
if ('datasourceId' in params):
replacement = str(self.apiClient.toPathValue(params['datasourceId']))
resourcePath = resourcePath.replace('{' + 'datasourceId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'MergeTemplateResponse')
return responseObject
def MergeDatasource(self, userId, fileId, datasourceId, **kwargs):
"""Merge datasource
Args:
userId, str: User GUID (required)
fileId, str: File GUID (required)
datasourceId, str: Datasource id (required)
targetType, str: Target type (optional)
emailResults, str: Email results (optional)
Returns: MergeTemplateResponse
"""
if( userId == None or fileId == None or datasourceId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId', 'datasourceId', 'targetType', 'emailResults']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method MergeDatasource" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/files/{fileId}/datasources/{datasourceId}?new_type={targetType}&email_results={emailResults}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('targetType' in params):
queryParams['new_type'] = self.apiClient.toPathValue(params['targetType'])
if ('emailResults' in params):
queryParams['email_results'] = self.apiClient.toPathValue(params['emailResults'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
if ('datasourceId' in params):
replacement = str(self.apiClient.toPathValue(params['datasourceId']))
resourcePath = resourcePath.replace('{' + 'datasourceId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'MergeTemplateResponse')
return responseObject
def MergeDatasourceFields(self, userId, fileId, body, **kwargs):
"""Merge datasource fields
Args:
userId, str: User GUID (required)
fileId, str: File GUID (required)
targetType, str: Target type (optional)
emailResults, str: Email results (optional)
assemblyName, str: Assembly name (optional)
body, List[DatasourceField]: Fields (required)
Returns: MergeTemplateResponse
"""
if( userId == None or fileId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId', 'targetType', 'emailResults', 'assemblyName', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method MergeDatasourceFields" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/files/{fileId}/datasources?new_type={targetType}&email_results={emailResults}&assembly_name={assemblyName}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('targetType' in params):
queryParams['new_type'] = self.apiClient.toPathValue(params['targetType'])
if ('emailResults' in params):
queryParams['email_results'] = self.apiClient.toPathValue(params['emailResults'])
if ('assemblyName' in params):
queryParams['assembly_name'] = self.apiClient.toPathValue(params['assemblyName'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'MergeTemplateResponse')
return responseObject
def GetQuestionnaire(self, userId, questionnaireId, **kwargs):
"""Get questionnaire
Args:
userId, str: User GUID (required)
questionnaireId, str: Questionnaire id (required)
Returns: GetQuestionnaireResponse
"""
if( userId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaire" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetQuestionnaireResponse')
return responseObject
def GetQuestionnaires(self, userId, **kwargs):
"""Get questionnaires
Args:
userId, str: User GUID (required)
status, str: Questionnaire status to filter by (optional)
pageNumber, int: Page number to return questionnaires on (optional)
pageSize, int: Number of questionnaires to return (optional)
Returns: GetQuestionnairesResponse
"""
if( userId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'status', 'pageNumber', 'pageSize']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaires" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires?status={status}&page_number={pageNumber}&page_size={pageSize}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('status' in params):
queryParams['status'] = self.apiClient.toPathValue(params['status'])
if ('pageNumber' in params):
queryParams['page_number'] = self.apiClient.toPathValue(params['pageNumber'])
if ('pageSize' in params):
queryParams['page_size'] = self.apiClient.toPathValue(params['pageSize'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetQuestionnairesResponse')
return responseObject
def CreateQuestionnaire(self, userId, body, **kwargs):
"""Create questionnaire
Args:
userId, str: User GUID (required)
body, QuestionnaireInfo: Questionnaire (required)
Returns: CreateQuestionnaireResponse
"""
if( userId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method CreateQuestionnaire" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'CreateQuestionnaireResponse')
return responseObject
def UpdateQuestionnaire(self, userId, questionnaireId, body, **kwargs):
"""Update questionnaire
Args:
userId, str: User GUID (required)
questionnaireId, str: Questionnaire id (required)
body, QuestionnaireInfo: Questionnaire (required)
Returns: UpdateQuestionnaireResponse
"""
if( userId == None or questionnaireId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UpdateQuestionnaire" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UpdateQuestionnaireResponse')
return responseObject
def DeleteQuestionnaire(self, userId, questionnaireId, **kwargs):
"""Delete questionnaire
Args:
userId, str: User GUID (required)
questionnaireId, str: Questionnaire id (required)
Returns: DeleteQuestionnaireResponse
"""
if( userId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method DeleteQuestionnaire" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DeleteQuestionnaireResponse')
return responseObject
def GetDocumentQuestionnaires(self, userId, fileId, **kwargs):
"""Get document questionnaires
Args:
userId, str: User GUID (required)
fileId, str: File GUID (required)
Returns: GetDocumentQuestionnairesResponse
"""
if( userId == None or fileId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetDocumentQuestionnaires" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/files/{fileId}/questionnaires'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetDocumentQuestionnairesResponse')
return responseObject
def CreateDocumentQuestionnaire(self, userId, fileId, body, **kwargs):
"""Create document questionnaire
Args:
userId, str: User GUID (required)
fileId, str: File GUID (required)
body, QuestionnaireInfo: Questionnaire (required)
Returns: AddDocumentQuestionnaireResponse
"""
if( userId == None or fileId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method CreateDocumentQuestionnaire" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/files/{fileId}/questionnaires'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddDocumentQuestionnaireResponse')
return responseObject
def AddDocumentQuestionnaire(self, userId, fileId, questionnaireId, **kwargs):
"""Add document questionnaire
Args:
userId, str: User GUID (required)
fileId, str: File GUID (required)
questionnaireId, str: Questionnaire id (required)
Returns: AddDocumentQuestionnaireResponse
"""
if( userId == None or fileId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId', 'questionnaireId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method AddDocumentQuestionnaire" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/files/{fileId}/questionnaires/{questionnaireId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddDocumentQuestionnaireResponse')
return responseObject
def DeleteDocumentQuestionnaire(self, userId, fileId, questionnaireId, **kwargs):
"""Delete document questionnaire
Args:
userId, str: User GUID (required)
fileId, str: File GUID (required)
questionnaireId, str: Questionnaire id (required)
Returns: DeleteDocumentQuestionnaireResponse
"""
if( userId == None or fileId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'fileId', 'questionnaireId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method DeleteDocumentQuestionnaire" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/files/{fileId}/questionnaires/{questionnaireId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('fileId' in params):
replacement = str(self.apiClient.toPathValue(params['fileId']))
resourcePath = resourcePath.replace('{' + 'fileId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DeleteDocumentQuestionnaireResponse')
return responseObject
def AddDataSource(self, userId, body, **kwargs):
"""Add datasource
Args:
userId, str: User GUID (required)
body, Datasource: Datasource (required)
Returns: AddDatasourceResponse
"""
if( userId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method AddDataSource" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/datasources'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddDatasourceResponse')
return responseObject
def UpdateDataSource(self, userId, datasourceId, body, **kwargs):
"""Update datasource
Args:
userId, str: User GUID (required)
datasourceId, str: Datasource id (required)
body, Datasource: Datasource (required)
Returns: AddDatasourceResponse
"""
if( userId == None or datasourceId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'datasourceId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UpdateDataSource" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/datasources/{datasourceId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('datasourceId' in params):
replacement = str(self.apiClient.toPathValue(params['datasourceId']))
resourcePath = resourcePath.replace('{' + 'datasourceId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddDatasourceResponse')
return responseObject
def UpdateDataSourceFields(self, userId, datasourceId, body, **kwargs):
"""Update datasource fields
Args:
userId, str: User GUID (required)
datasourceId, str: Datasource id (required)
body, Datasource: Datasource (required)
Returns: AddDatasourceResponse
"""
if( userId == None or datasourceId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'datasourceId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UpdateDataSourceFields" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/datasources/{datasourceId}/fields'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('datasourceId' in params):
replacement = str(self.apiClient.toPathValue(params['datasourceId']))
resourcePath = resourcePath.replace('{' + 'datasourceId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddDatasourceResponse')
return responseObject
def DeleteDataSource(self, userId, datasourceId, **kwargs):
"""Delete datasource fields
Args:
userId, str: User GUID (required)
datasourceId, str: Datasource id (required)
Returns: DeleteDatasourceResponse
"""
if( userId == None or datasourceId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'datasourceId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method DeleteDataSource" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/datasources/{datasourceId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('datasourceId' in params):
replacement = str(self.apiClient.toPathValue(params['datasourceId']))
resourcePath = resourcePath.replace('{' + 'datasourceId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DeleteDatasourceResponse')
return responseObject
def GetDataSource(self, userId, datasourceId, **kwargs):
"""Get datasource
Args:
userId, str: User GUID (required)
datasourceId, str: Datasource id (required)
fields, str: Fields (optional)
Returns: GetDatasourceResponse
"""
if( userId == None or datasourceId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'datasourceId', 'fields']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetDataSource" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/datasources/{datasourceId}?field={fields}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('fields' in params):
queryParams['field'] = self.apiClient.toPathValue(params['fields'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('datasourceId' in params):
replacement = str(self.apiClient.toPathValue(params['datasourceId']))
resourcePath = resourcePath.replace('{' + 'datasourceId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetDatasourceResponse')
return responseObject
def GetQuestionnaireDataSources(self, userId, questionnaireId, **kwargs):
"""Get questionnaire datasources
Args:
userId, str: User GUID (required)
questionnaireId, str: QuestionnaireId id (required)
includeFields, bool: Include fields (optional)
Returns: GetDatasourcesResponse
"""
if( userId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId', 'includeFields']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaireDataSources" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}/datasources?include_fields={includeFields}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('includeFields' in params):
queryParams['include_fields'] = self.apiClient.toPathValue(params['includeFields'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetDatasourcesResponse')
return responseObject
def AddQuestionnaireExecution(self, userId, collectorId, body, **kwargs):
"""Add questionnaire execution
Args:
userId, str: User GUID (required)
collectorId, str: Questionnaire collector id (required)
body, QuestionnaireExecutionInfo: Execution (required)
Returns: AddQuestionnaireExecutionResponse
"""
if( userId == None or collectorId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'collectorId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method AddQuestionnaireExecution" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/collectors/{collectorId}/executions'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('collectorId' in params):
replacement = str(self.apiClient.toPathValue(params['collectorId']))
resourcePath = resourcePath.replace('{' + 'collectorId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddQuestionnaireExecutionResponse')
return responseObject
def GetQuestionnaireCollectorExecutions(self, userId, collectorId, **kwargs):
"""Get questionnaire collector executions
Args:
userId, str: User GUID (required)
collectorId, str: Questionnaire collector global unique identifier (required)
Returns: GetQuestionnaireExecutionsResponse
"""
if( userId == None or collectorId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'collectorId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaireCollectorExecutions" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/collectors/{collectorId}/executions'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('collectorId' in params):
replacement = str(self.apiClient.toPathValue(params['collectorId']))
resourcePath = resourcePath.replace('{' + 'collectorId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetQuestionnaireExecutionsResponse')
return responseObject
def GetQuestionnaireExecutions(self, userId, questionnaireId, **kwargs):
"""Get questionnaire executions
Args:
userId, str: User GUID (required)
questionnaireId, str: Questionnaire global unique identifier (required)
Returns: GetQuestionnaireExecutionsResponse
"""
if( userId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaireExecutions" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}/executions'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetQuestionnaireExecutionsResponse')
return responseObject
def GetQuestionnaireExecution(self, userId, executionId, **kwargs):
"""Get questionnaire execution
Args:
userId, str: User GUID (required)
executionId, str: Questionnaire execution global unique identifier (required)
Returns: GetQuestionnaireExecutionResponse
"""
if( userId == None or executionId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'executionId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaireExecution" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/executions/{executionId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('executionId' in params):
replacement = str(self.apiClient.toPathValue(params['executionId']))
resourcePath = resourcePath.replace('{' + 'executionId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetQuestionnaireExecutionResponse')
return responseObject
def DeleteQuestionnaireExecution(self, userId, executionId, **kwargs):
"""Removes questionnaire execution
Args:
userId, str: User GUID (required)
executionId, str: Execution id (required)
Returns: DeleteQuestionnaireExecutionResponse
"""
if( userId == None or executionId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'executionId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method DeleteQuestionnaireExecution" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/executions/{executionId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('executionId' in params):
replacement = str(self.apiClient.toPathValue(params['executionId']))
resourcePath = resourcePath.replace('{' + 'executionId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DeleteQuestionnaireExecutionResponse')
return responseObject
def UpdateQuestionnaireExecution(self, userId, executionId, body, **kwargs):
"""Update questionnaire execution
Args:
userId, str: User GUID (required)
executionId, str: Execution id (required)
body, QuestionnaireExecutionInfo: Execution (required)
Returns: UpdateQuestionnaireExecutionResponse
"""
if( userId == None or executionId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'executionId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UpdateQuestionnaireExecution" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/executions/{executionId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('executionId' in params):
replacement = str(self.apiClient.toPathValue(params['executionId']))
resourcePath = resourcePath.replace('{' + 'executionId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UpdateQuestionnaireExecutionResponse')
return responseObject
def UpdateQuestionnaireExecutionStatus(self, userId, executionId, body, **kwargs):
"""Update questionnaire execution status
Args:
userId, str: User GUID (required)
executionId, str: Execution id (required)
body, str: Status (required)
Returns: UpdateQuestionnaireExecutionResponse
"""
if( userId == None or executionId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'executionId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UpdateQuestionnaireExecutionStatus" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/executions/{executionId}/status'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('executionId' in params):
replacement = str(self.apiClient.toPathValue(params['executionId']))
resourcePath = resourcePath.replace('{' + 'executionId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UpdateQuestionnaireExecutionResponse')
return responseObject
def GetQuestionnaireCollectors(self, userId, questionnaireId, **kwargs):
"""Get questionnaire collectors
Args:
userId, str: User global unique identifier (required)
questionnaireId, str: Questionnaire identifier (required)
Returns: GetQuestionnaireCollectorsResponse
"""
if( userId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaireCollectors" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}/collectors'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetQuestionnaireCollectorsResponse')
return responseObject
def GetQuestionnaireCollector(self, userId, collectorId, **kwargs):
"""Returns questionnaire collector
Args:
userId, str: User global unique identifier (required)
collectorId, str: Questionnaire collector global unique identifier (required)
Returns: GetQuestionnaireCollectorResponse
"""
if( userId == None or collectorId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'collectorId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaireCollector" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/collectors/{collectorId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('collectorId' in params):
replacement = str(self.apiClient.toPathValue(params['collectorId']))
resourcePath = resourcePath.replace('{' + 'collectorId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetQuestionnaireCollectorResponse')
return responseObject
def AddQuestionnaireCollector(self, userId, questionnaireId, body, **kwargs):
"""Add questionnaire collector
Args:
userId, str: User global unique identifier (required)
questionnaireId, str: Questionnaire identifier (required)
body, QuestionnaireCollectorInfo: Questionnaire collector to be added (required)
Returns: AddQuestionnaireCollectorResponse
"""
if( userId == None or questionnaireId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method AddQuestionnaireCollector" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}/collectors'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'AddQuestionnaireCollectorResponse')
return responseObject
def UpdateQuestionnaireCollector(self, userId, collectorId, body, **kwargs):
"""Update questionnaire collector
Args:
userId, str: User global unique identifier (required)
collectorId, str: Questionnaire collector global unique identifier (required)
body, QuestionnaireCollectorInfo: Questionnaire collector data (required)
Returns: UpdateQuestionnaireCollectorResponse
"""
if( userId == None or collectorId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'collectorId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UpdateQuestionnaireCollector" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/collectors/{collectorId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('collectorId' in params):
replacement = str(self.apiClient.toPathValue(params['collectorId']))
resourcePath = resourcePath.replace('{' + 'collectorId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UpdateQuestionnaireCollectorResponse')
return responseObject
def DeleteQuestionnaireCollector(self, userId, collectorId, **kwargs):
"""Removes questionnaire collector
Args:
userId, str: User global unique identifier (required)
collectorId, str: Questionnaire collector global unique identifier (required)
Returns: DeleteQuestionnaireCollectorResponse
"""
if( userId == None or collectorId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'collectorId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method DeleteQuestionnaireCollector" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/collectors/{collectorId}'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('collectorId' in params):
replacement = str(self.apiClient.toPathValue(params['collectorId']))
resourcePath = resourcePath.replace('{' + 'collectorId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DeleteQuestionnaireCollectorResponse')
return responseObject
def GetTemplates(self, userId, **kwargs):
"""Get template documents information
Args:
userId, str: User global unique identifier (required)
Returns: GetTemplatesResponse
"""
if( userId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetTemplates" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/templates'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetTemplatesResponse')
return responseObject
def GetQuestionnaireFields(self, userId, questionnaireId, **kwargs):
"""Get questionnaire fields
Args:
userId, str: User global unique identifier (required)
questionnaireId, str: Questionnaire global unique identifier (required)
includeGeometry, bool: A flag indicating whether fields coordinates and size should be included into the response. (optional)
Returns: TemplateFieldsResponse
"""
if( userId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId', 'includeGeometry']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaireFields" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}/fields?include_geometry={includeGeometry}'.replace('*', '')
pos = resourcePath.find("?")
if pos != -1:
resourcePath = resourcePath[0:pos]
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('includeGeometry' in params):
queryParams['include_geometry'] = self.apiClient.toPathValue(params['includeGeometry'])
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'TemplateFieldsResponse')
return responseObject
def GetQuestionnaireMetadata(self, userId, questionnaireId, **kwargs):
"""Get questionnaire metadata
Args:
userId, str: User global unique identifier (required)
questionnaireId, str: Questionnaire global unique identifier (required)
Returns: GetQuestionnaireMetadataResponse
"""
if( userId == None or questionnaireId == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method GetQuestionnaireMetadata" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}/metadata'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'GetQuestionnaireMetadataResponse')
return responseObject
def UpdateQuestionnaireMetadata(self, userId, questionnaireId, body, **kwargs):
"""Update questionnaire metadata
Args:
userId, str: User global unique identifier (required)
questionnaireId, str: Questionnaire global unique identifier (required)
body, QuestionnaireMetadata: Questionnaire metadata to update (required)
Returns: UpdateQuestionnaireResponse
"""
if( userId == None or questionnaireId == None or body == None ):
raise ApiException(400, "missing required parameters")
allParams = ['userId', 'questionnaireId', 'body']
params = locals()
for (key, val) in params['kwargs'].iteritems():
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method UpdateQuestionnaireMetadata" % key)
params[key] = val
del params['kwargs']
resourcePath = '/merge/{userId}/questionnaires/{questionnaireId}/metadata'.replace('*', '')
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
if ('userId' in params):
replacement = str(self.apiClient.toPathValue(params['userId']))
resourcePath = resourcePath.replace('{' + 'userId' + '}',
replacement)
if ('questionnaireId' in params):
replacement = str(self.apiClient.toPathValue(params['questionnaireId']))
resourcePath = resourcePath.replace('{' + 'questionnaireId' + '}',
replacement)
postData = (params['body'] if 'body' in params else None)
response = self.apiClient.callAPI(self.basePath, resourcePath, method, queryParams,
postData, headerParams)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'UpdateQuestionnaireResponse')
return responseObject
| 43.023181
| 198
| 0.572912
| 6,458
| 79,808
| 7.074481
| 0.045525
| 0.048657
| 0.078031
| 0.062381
| 0.860617
| 0.853678
| 0.842362
| 0.828682
| 0.819073
| 0.816206
| 0
| 0.002521
| 0.318978
| 79,808
| 1,854
| 199
| 43.046386
| 0.838071
| 0.115753
| 0
| 0.867389
| 0
| 0.003336
| 0.177953
| 0.059298
| 0
| 0
| 0
| 0
| 0
| 1
| 0.033361
| false
| 0
| 0.00417
| 0.000834
| 0.100917
| 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
|
ddb3c1cb4a455e75b186581c539e2329f4c60e9f
| 3,249
|
py
|
Python
|
tests/test_tolerances.py
|
olymk2/pytest-inomaly
|
93fda23c9a5359d6708cef180b128356dcafdab5
|
[
"MIT"
] | 1
|
2019-12-20T18:22:18.000Z
|
2019-12-20T18:22:18.000Z
|
tests/test_tolerances.py
|
olymk2/pytest-inomaly
|
93fda23c9a5359d6708cef180b128356dcafdab5
|
[
"MIT"
] | null | null | null |
tests/test_tolerances.py
|
olymk2/pytest-inomaly
|
93fda23c9a5359d6708cef180b128356dcafdab5
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
import os
import pytest
@pytest.yield_fixture(autouse=True)
def run_around_tests():
pytest.update_images = False
def test_exact_antialiasing_difference(testdir):
test_directory = os.path.abspath(os.path.dirname(__file__))
result = pytest.idiff(
'%s/fixture/100x100-cube.png' % (test_directory),
'%s/fixture/100x100-cube-antialias-01.png' % (test_directory),
tolerance=0.05)
assert result is True
def test_exact_extreme_difference(testdir):
test_directory = os.path.abspath(os.path.dirname(__file__))
result = pytest.idiff(
'%s/fixture/100x100-cube-white.png' % (test_directory),
'%s/fixture/100x100-cube-black.png' % (test_directory),
tolerance=0.05)
assert result is False
def test_exact_identical_images_idiff(testdir):
test_directory = os.path.abspath(os.path.dirname(__file__))
result = pytest.idiff(
'%s/fixture/100x100-cube.png' % (test_directory),
'%s/fixture/100x100-cube.png' % (test_directory),
tolerance=0.05)
assert result is True
result = pytest.idiff(
'%s/fixture/original.png' % (test_directory),
'%s/fixture/original.png' % (test_directory),
tolerance=0.05)
assert result is True
def test_exact_pixel_diference_images_idiff(testdir):
test_directory = os.path.abspath(os.path.dirname(__file__))
result = pytest.idiff(
'%s/fixture/100x100-cube.png' % (test_directory),
'%s/fixture/100x100-cube-pixel-difference.png' % (test_directory),
tolerance=0.05)
assert result is True
result = pytest.idiff(
'%s/fixture/original.png' % (test_directory),
'%s/fixture/pixel.png' % (test_directory),
tolerance=0.05)
assert result is True
def test_exact_glitch_diference_images_idiff(testdir):
test_directory = os.path.abspath(os.path.dirname(__file__))
#small image with glitch large enough to detect
result = pytest.idiff(
'%s/fixture/100x100-cube.png' % (test_directory),
'%s/fixture/100x100-cube-glitch-line.png' % (test_directory),
tolerance=0.1)
assert result is False
# much larger images so difference is not big enough to detect
result = pytest.idiff(
'%s/fixture/original.png' % (test_directory),
'%s/fixture/glitch.png' % (test_directory),
tolerance=0.1)
assert result is True
def test_exact_color_diference_images_idiff(testdir):
test_directory = os.path.abspath(os.path.dirname(__file__))
result = pytest.idiff(
'%s/fixture/100x100-cube.png' % (test_directory),
'%s/fixture/100x100-cube-color-difference.png' % (test_directory),
tolerance=0.1)
assert result is False
result = pytest.idiff(
'%s/fixture/original.png' % (test_directory),
'%s/fixture/different_colors.png' % (test_directory),
tolerance=0.1)
assert result is False
def test_exact_rotated_diference_images_idiff(testdir):
test_directory = os.path.abspath(os.path.dirname(__file__))
result = pytest.idiff(
'%s/fixture/original.png' % (test_directory),
'%s/fixture/rotated.png' % (test_directory),
tolerance=0.1)
assert result is False
| 31.852941
| 74
| 0.675592
| 418
| 3,249
| 5.0311
| 0.157895
| 0.179268
| 0.16738
| 0.108417
| 0.858773
| 0.858773
| 0.845459
| 0.807418
| 0.794104
| 0.754636
| 0
| 0.039494
| 0.197291
| 3,249
| 101
| 75
| 32.168317
| 0.766871
| 0.039705
| 0
| 0.702703
| 0
| 0
| 0.20122
| 0.194801
| 0
| 0
| 0
| 0
| 0.148649
| 1
| 0.108108
| false
| 0
| 0.027027
| 0
| 0.135135
| 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
|
fb1d57f4fd75aa333c7c73092d45f033a35416f5
| 35,699
|
py
|
Python
|
tests/test_api.py
|
varunsaral/Python-Honeypot
|
aefedaccf1f2ea31324af52e4a66f65e0dde5211
|
[
"Apache-2.0"
] | 1
|
2021-02-03T10:03:30.000Z
|
2021-02-03T10:03:30.000Z
|
tests/test_api.py
|
varunsaral/Python-Honeypot
|
aefedaccf1f2ea31324af52e4a66f65e0dde5211
|
[
"Apache-2.0"
] | 3
|
2021-07-28T01:25:31.000Z
|
2022-03-29T22:10:45.000Z
|
tests/test_api.py
|
varunsaral/Python-Honeypot
|
aefedaccf1f2ea31324af52e4a66f65e0dde5211
|
[
"Apache-2.0"
] | 1
|
2021-06-24T17:22:08.000Z
|
2021-06-24T17:22:08.000Z
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import unittest
import requests
from core.get_modules import load_all_modules
API_URL = 'http://127.0.0.1:5000'
class TestApi(unittest.TestCase):
def test_index(self):
"""
Test if the API is running
"""
response = requests.get(API_URL)
self.assertEqual(response.status_code, 200)
def test_count_all_events(self):
response = requests.get(API_URL + "/api/events/count/all")
self.assertGreaterEqual(response.json()["count"], 0)
self.assertEqual(response.status_code, 200)
def test_count_honeypot_events(self):
response = requests.get(API_URL + "/api/events/count/honeypot")
self.assertGreaterEqual(response.json()["count"], 0)
self.assertEqual(response.status_code, 200)
def test_count_network_events(self):
response = requests.get(API_URL + "/api/events/count/network")
self.assertGreaterEqual(response.json()["count"], 0)
self.assertEqual(response.status_code, 200)
def test_count_credential_events(self):
response = requests.get(API_URL + "/api/events/count/credential")
self.assertGreaterEqual(response.json()["count"], 0)
self.assertEqual(response.status_code, 200)
def test_count_file_events(self):
response = requests.get(API_URL + "/api/events/count/file")
self.assertGreaterEqual(response.json()["count"], 0)
self.assertEqual(response.status_code, 200)
def test_count_data_events(self):
response = requests.get(API_URL + "/api/events/count/data")
self.assertGreaterEqual(response.json()["count"], 0)
self.assertEqual(response.status_code, 200)
response = requests.get(API_URL + "/api/events/count/data?date=2020-08-14")
self.assertGreaterEqual(response.json()["count"], 0)
self.assertEqual(response.status_code, 200)
def test_top_ten_honeypot_events(self):
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/ip")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/ip?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/ip?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/ip?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/port")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/port?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/port?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/port?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/username")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/username?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/username?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/username?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/password")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/password?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/password?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/password?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/machine_name")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/machine_name?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/machine_name?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/honeypot/machine_name?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/country")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/country?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/honeypot/country?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/honeypot/country?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
def test_top_ten_network_events(self):
response_port = requests.get(API_URL + "/api/events/count/groupby/network/ip")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/ip?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/ip?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/ip?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/port")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/port?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/port?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/port?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/username")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/username?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/username?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/username?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/password")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/password?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/password?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/password?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/machine_name")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/machine_name?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/machine_name?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/network/machine_name?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/country")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/country?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/network/country?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/network/country?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
def test_top_ten_credential_events(self):
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/ip")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/ip?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/ip?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/ip?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/port")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/port?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/port?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/port?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/username")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/username?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/username?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/credential/username?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/password")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/password?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/password?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/credential/password?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/machine_name")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/machine_name?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/machine_name?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/credential/machine_name?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/country")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/country?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/credential/country?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/credential/country?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
def test_top_ten_file_events(self):
response_port = requests.get(API_URL + "/api/events/count/groupby/file/ip")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/ip?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/ip?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/ip?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/port")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/port?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/port?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/port?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/username")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/username?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/username?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/username?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/password")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/password?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/password?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/password?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/machine_name")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/machine_name?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/machine_name?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/file/machine_name?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/country")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/country?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/file/country?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/file/country?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
def test_top_ten_data_events(self):
response_port = requests.get(API_URL + "/api/events/count/groupby/data/ip")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/ip?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/ip?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/ip?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/port")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/port?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/port?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/port?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/username")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/username?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/username?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/username?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/password")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/password?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/password?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/password?country=US&date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/machine_name")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/machine_name?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/machine_name?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/data/machine_name?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/country")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/country?country=US")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(API_URL + "/api/events/count/groupby/data/country?date=2020-08-14")
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
response_port = requests.get(
API_URL + "/api/events/count/groupby/data/country?country=US&date=2020-08-14"
)
self.assertGreaterEqual(len(response_port.json()), 0)
self.assertEqual(response_port.status_code, 200)
def test_honeypot_events_list(self):
response_honeypot = requests.get(API_URL + "/api/events/explore/honeypot")
self.assertGreaterEqual(len(response_honeypot.json()), 0)
self.assertEqual(response_honeypot.status_code, 200)
response_honeypot_countries = requests.get(
API_URL + "/api/events/explore/honeypot?module_name=ssh/strong_password"
)
self.assertGreaterEqual(len(response_honeypot_countries.json()), 0)
self.assertEqual(response_honeypot_countries.status_code, 200)
response_honeypot_countries = requests.get(
API_URL + "/api/events/explore/honeypot?date=2020-08-14"
)
self.assertGreaterEqual(len(response_honeypot_countries.json()), 0)
self.assertEqual(response_honeypot_countries.status_code, 200)
response_honeypot_machinenames = requests.get(
API_URL + "/api/events/explore/honeypot?module_name=ssh/strong_password&date=2020-08-14"
)
self.assertGreaterEqual(len(response_honeypot_machinenames.json()), 0)
self.assertEqual(response_honeypot_machinenames.status_code, 200)
def test_network_events_list(self):
response_network = requests.get(API_URL + "/api/events/explore/network")
self.assertGreaterEqual(len(response_network.json()), 0)
self.assertEqual(response_network.status_code, 200)
response_network_countries = requests.get(
API_URL + "/api/events/explore/network?module_name=ssh/strong_password"
)
self.assertGreaterEqual(len(response_network_countries.json()), 0)
self.assertEqual(response_network_countries.status_code, 200)
response_network_countries = requests.get(
API_URL + "/api/events/explore/network?date=2020-08-14"
)
self.assertGreaterEqual(len(response_network_countries.json()), 0)
self.assertEqual(response_network_countries.status_code, 200)
response_network_machinenames = requests.get(
API_URL + "/api/events/explore/network?module_name=ssh/strong_password&date=2020-08-14"
)
self.assertGreaterEqual(len(response_network_machinenames.json()), 0)
self.assertEqual(response_network_machinenames.status_code, 200)
def test_credential_events_list(self):
response_credential = requests.get(API_URL + "/api/events/explore/credential")
self.assertGreaterEqual(len(response_credential.json()), 0)
self.assertEqual(response_credential.status_code, 200)
response_credential_countries = requests.get(
API_URL + "/api/events/explore/credential?module_name=ssh/strong_password"
)
self.assertGreaterEqual(len(response_credential_countries.json()), 0)
self.assertEqual(response_credential_countries.status_code, 200)
response_credential_countries = requests.get(
API_URL + "/api/events/explore/credential?date=2020-08-14"
)
self.assertGreaterEqual(len(response_credential_countries.json()), 0)
self.assertEqual(response_credential_countries.status_code, 200)
response_credential_machinenames = requests.get(
API_URL + "/api/events/explore/credential?module_name=ssh/strong_password&date=2020-08-14"
)
self.assertGreaterEqual(len(response_credential_machinenames.json()), 0)
self.assertEqual(response_credential_machinenames.status_code, 200)
def test_file_events_list(self):
response_file = requests.get(API_URL + "/api/events/explore/file")
self.assertGreaterEqual(len(response_file.json()), 0)
self.assertEqual(response_file.status_code, 200)
response_file_countries = requests.get(
API_URL + "/api/events/explore/file?module_name=ssh/strong_password"
)
self.assertGreaterEqual(len(response_file_countries.json()), 0)
self.assertEqual(response_file_countries.status_code, 200)
response_file_countries = requests.get(
API_URL + "/api/events/explore/file?date=2020-08-14"
)
self.assertGreaterEqual(len(response_file_countries.json()), 0)
self.assertEqual(response_file_countries.status_code, 200)
response_file_machinenames = requests.get(
API_URL + "/api/events/explore/file?module_name=ssh/strong_password&date=2020-08-14"
)
self.assertGreaterEqual(len(response_file_machinenames.json()), 0)
self.assertEqual(response_file_machinenames.status_code, 200)
def test_data_events_list(self):
response_data = requests.get(API_URL + "/api/events/explore/data")
self.assertGreaterEqual(len(response_data.json()), 0)
self.assertEqual(response_data.status_code, 200)
response_data_countries = requests.get(
API_URL + "/api/events/explore/data?module_name=ssh/strong_password"
)
self.assertGreaterEqual(len(response_data_countries.json()), 0)
self.assertEqual(response_data_countries.status_code, 200)
response_data_countries = requests.get(
API_URL + "/api/events/explore/data?date=2020-08-14"
)
self.assertGreaterEqual(len(response_data_countries.json()), 0)
self.assertEqual(response_data_countries.status_code, 200)
response_data_machinenames = requests.get(
API_URL + "/api/events/explore/data?module_name=ssh/strong_password&date=2020-08-14"
)
self.assertGreaterEqual(len(response_data_machinenames.json()), 0)
self.assertEqual(response_data_machinenames.status_code, 200)
def test_all_module_names(self):
"""
Test module-names endpoint
"""
module_names = load_all_modules()
response = requests.get(API_URL + "/api/core/list/modules")
self.assertCountEqual(module_names, response.json())
module_names = [
'ics/veeder_root_guardian_ast',
'http/basic_auth_strong_password',
'http/basic_auth_weak_password',
'ftp/strong_password',
'ftp/weak_password',
'ssh/strong_password',
'ssh/weak_password',
'smtp/strong_password'
]
self.assertCountEqual(module_names, response.json())
if __name__ == '__main__':
unittest.main()
| 51.144699
| 120
| 0.705678
| 4,492
| 35,699
| 5.40984
| 0.018923
| 0.17777
| 0.08584
| 0.104234
| 0.970166
| 0.960989
| 0.933007
| 0.932266
| 0.921649
| 0.913913
| 0
| 0.039354
| 0.167204
| 35,699
| 697
| 121
| 51.218077
| 0.778036
| 0.002689
| 0
| 0.559925
| 0
| 0.065543
| 0.223091
| 0.218703
| 0
| 0
| 0
| 0
| 0.55618
| 1
| 0.033708
| false
| 0.069288
| 0.005618
| 0
| 0.041199
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 8
|
5510e27c479ce5f7cdfbf47de020595ecbb7b1ab
| 3,118
|
py
|
Python
|
polymarket/liquidity.py
|
michel1506/polymarket-trading
|
9169c528dcfa044e44f3860c8ab7e3139cb7a467
|
[
"MIT"
] | null | null | null |
polymarket/liquidity.py
|
michel1506/polymarket-trading
|
9169c528dcfa044e44f3860c8ab7e3139cb7a467
|
[
"MIT"
] | null | null | null |
polymarket/liquidity.py
|
michel1506/polymarket-trading
|
9169c528dcfa044e44f3860c8ab7e3139cb7a467
|
[
"MIT"
] | null | null | null |
from .markets import get_active_markets
from .utils import approve_erc20, load_evm_abi
def add_liquidity(web3_provider, slug=None, market_maker_address=None, amount=0):
if slug is None and market_maker_address is None:
raise RuntimeError('Most provide either slug or market address.')
if not market_maker_address:
market_json = get_active_markets(slug=slug)[0]
market_maker_address = market_json['marketMakerAddress']
fixed_product_market_maker_address_abi = load_evm_abi('FixedProductMarketMaker.json')
approved_amount = approve_erc20(web3_provider, market_maker_address, amount)
contract = web3_provider.eth.contract(address=market_maker_address, abi=fixed_product_market_maker_address_abi)
trx_hash = contract.functions.addFunding(approved_amount, []).transact()
web3_provider.eth.wait_for_transaction_receipt(trx_hash)
return trx_hash
def remove_liquidity(web3_provider, slug=None, market_maker_address=None, amount=0):
if slug is None and market_maker_address is None:
raise RuntimeError('Most provide either slug or market address.')
if not market_maker_address:
market_json = get_active_markets(slug=slug)[0]
market_maker_address = market_json['marketMakerAddress']
fixed_product_market_maker_address_abi = load_evm_abi('FixedProductMarketMaker.json')
amount = int(amount * (10 ** 6))
contract = web3_provider.eth.contract(address=market_maker_address, abi=fixed_product_market_maker_address_abi)
trx_hash = contract.functions.removeFunding(amount).transact()
web3_provider.eth.wait_for_transaction_receipt(trx_hash)
return trx_hash
def liquidity_balance(web3_provider, slug=None, market_maker_address=None, user=None):
if slug is None and market_maker_address is None:
raise RuntimeError('Most provide either slug or market address.')
if not market_maker_address:
market_json = get_active_markets(slug=slug)[0]
market_maker_address = market_json['marketMakerAddress']
fixed_product_market_maker_address_abi = load_evm_abi('FixedProductMarketMaker.json')
contract = web3_provider.eth.contract(address=market_maker_address, abi=fixed_product_market_maker_address_abi)
value = contract.functions.balanceOf(web3_provider.eth.default_account).call()
print(f"LP Tokens: {value / (10 ** 6)}")
def liquidity_withdraw_fees(web3_provider, slug=None, market_maker_address=None):
if slug is None and market_maker_address is None:
raise RuntimeError('Most provide either slug or market address.')
if not market_maker_address:
market_json = get_active_markets(slug=slug)[0]
market_maker_address = market_json['marketMakerAddress']
fixed_product_market_maker_address_abi = load_evm_abi('FixedProductMarketMaker.json')
contract = web3_provider.eth.contract(address=market_maker_address, abi=fixed_product_market_maker_address_abi)
trx_hash = contract.functions.withdrawFees(web3_provider.eth.default_account).transact()
web3_provider.eth.wait_for_transaction_receipt(trx_hash)
return trx_hash
| 45.188406
| 115
| 0.784798
| 419
| 3,118
| 5.47494
| 0.167064
| 0.139058
| 0.22755
| 0.109852
| 0.866609
| 0.841325
| 0.841325
| 0.841325
| 0.806452
| 0.806452
| 0
| 0.011161
| 0.137909
| 3,118
| 68
| 116
| 45.852941
| 0.842262
| 0
| 0
| 0.723404
| 0
| 0
| 0.123797
| 0.03592
| 0
| 0
| 0
| 0
| 0
| 1
| 0.085106
| false
| 0
| 0.042553
| 0
| 0.191489
| 0.021277
| 0
| 0
| 0
| null | 0
| 1
| 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
|
9b36067f34bcd1fdfc93521cde06fb66db017e9c
| 43
|
py
|
Python
|
hello-world/Hello.py
|
anmolpal1999/python-for-beginners
|
738d73006cf21206cd10ea89d9796669fc141df3
|
[
"MIT"
] | null | null | null |
hello-world/Hello.py
|
anmolpal1999/python-for-beginners
|
738d73006cf21206cd10ea89d9796669fc141df3
|
[
"MIT"
] | null | null | null |
hello-world/Hello.py
|
anmolpal1999/python-for-beginners
|
738d73006cf21206cd10ea89d9796669fc141df3
|
[
"MIT"
] | null | null | null |
print 'Hello World'
print ("Hello! World")
| 14.333333
| 22
| 0.697674
| 6
| 43
| 5
| 0.5
| 0.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.139535
| 43
| 2
| 23
| 21.5
| 0.810811
| 0
| 0
| 0
| 0
| 0
| 0.534884
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 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
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 7
|
9b863c628d9f814239bd65c6d3a87ed9848dde1f
| 2,233
|
py
|
Python
|
test/tests.py
|
Pendosv/CreateProject
|
a2da3fd164c47b1d159027ab18ed4b01beae3670
|
[
"RSA-MD"
] | 1
|
2021-08-20T22:09:53.000Z
|
2021-08-20T22:09:53.000Z
|
test/tests.py
|
Pendosv/CreateProject
|
a2da3fd164c47b1d159027ab18ed4b01beae3670
|
[
"RSA-MD"
] | null | null | null |
test/tests.py
|
Pendosv/CreateProject
|
a2da3fd164c47b1d159027ab18ed4b01beae3670
|
[
"RSA-MD"
] | null | null | null |
import unittest
from src.CreateProject import CreateProject
get_script_name = CreateProject.get_script_name
is_camel_case = CreateProject.is_camel_case
class MyTestCase(unittest.TestCase):
def test_get_script_name(self):
self.assertEqual(get_script_name('ImageCrypt'), 'image-crypt')
self.assertEqual(get_script_name('Imagecrypt'), 'imagecrypt')
self.assertEqual(get_script_name('ImageCrypt'), 'image-crypt')
self.assertEqual(get_script_name('imagecrypt'), 'imagecrypt')
self.assertEqual(get_script_name('imagecryptT'), 'imagecryptt')
self.assertEqual(get_script_name('ImageCryptTEST'), 'image-crypt-test')
self.assertEqual(get_script_name('ImageCRYPTTest'), 'image-crypt-test')
self.assertEqual(get_script_name('IMAGECryptTest'), 'image-crypt-test')
self.assertEqual(get_script_name('IMAGECryptTEST'), 'image-crypt-test')
self.assertEqual(get_script_name('ImageCryptSave'), 'image-crypt-save')
self.assertEqual(get_script_name('.ImageCryptSave'), 'image-crypt-save')
self.assertEqual(get_script_name('ImageCryptSave.'), 'image-crypt-save.')
self.assertEqual(get_script_name('_camelCase-'), '_camel-case')
self.assertEqual(get_script_name('-camelCase_'), 'camel-case_')
self.assertEqual(get_script_name('ImageCryptSaveSegaMegaDriveUltraSuper'),
'image-crypt-save-sega-mega-drive-ultra-super')
def test_is_project_name_camelcase(self):
self.assertTrue(is_camel_case('camelCase'))
self.assertTrue(is_camel_case('CamelCase'))
self.assertTrue(is_camel_case('Camelcase'))
self.assertTrue(is_camel_case('Case'))
self.assertTrue(is_camel_case('_camelCase-'))
self.assertTrue(is_camel_case('-camelCase_'))
self.assertFalse(is_camel_case('-camelcase_'))
self.assertFalse(is_camel_case('-CAMELCASE_'))
self.assertFalse(is_camel_case('camel'))
self.assertFalse(is_camel_case('CAMELCASE'))
self.assertFalse(is_camel_case('camelcase'))
self.assertFalse(is_camel_case('camel_case'))
self.assertFalse(is_camel_case('camel-Case'))
if __name__ == '__main__':
unittest.main()
| 42.132075
| 82
| 0.71339
| 253
| 2,233
| 5.948617
| 0.146245
| 0.113621
| 0.155482
| 0.239203
| 0.77608
| 0.77608
| 0.77608
| 0.750166
| 0.750166
| 0.750166
| 0
| 0
| 0.152709
| 2,233
| 52
| 83
| 42.942308
| 0.795455
| 0
| 0
| 0.052632
| 0
| 0
| 0.254366
| 0.036274
| 0
| 0
| 0
| 0
| 0.736842
| 1
| 0.052632
| false
| 0
| 0.052632
| 0
| 0.131579
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
9bbe614bff71cb11893f922d88d9c6bddb68d499
| 22,884
|
py
|
Python
|
collector_service_sdk/api/metric/metric_client.py
|
easyopsapis/easyops-api-python
|
adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0
|
[
"Apache-2.0"
] | 5
|
2019-07-31T04:11:05.000Z
|
2021-01-07T03:23:20.000Z
|
collector_service_sdk/api/metric/metric_client.py
|
easyopsapis/easyops-api-python
|
adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0
|
[
"Apache-2.0"
] | null | null | null |
collector_service_sdk/api/metric/metric_client.py
|
easyopsapis/easyops-api-python
|
adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
import os
import sys
import collector_service_sdk.model.collector_service.aggregate_metric_rule_pb2
import collector_service_sdk.api.metric.create_aggregate_metric_rule_pb2
import collector_service_sdk.api.metric.create_metric_pb2
import collector_service_sdk.api.metric.delete_aggregate_metric_rule_pb2
import google.protobuf.empty_pb2
import collector_service_sdk.api.metric.detail_aggregate_metric_rule_pb2
import collector_service_sdk.api.metric.get_metric_name_detail_pb2
import collector_service_sdk.api.metric.list_aggregate_metric_rule_pb2
import collector_service_sdk.api.metric.list_collector_alias_metric_pb2
import collector_service_sdk.api.metric.list_collector_metric_pb2
import collector_service_sdk.api.metric.list_metric_names_pb2
import collector_service_sdk.api.metric.set_resource_key_metric_pb2
import collector_service_sdk.api.metric.update_aggregate_metric_rule_pb2
import collector_service_sdk.api.metric.update_metric_pb2
import collector_service_sdk.utils.http_util
import google.protobuf.json_format
class MetricClient(object):
def __init__(self, server_ip="", server_port=0, service_name="", host=""):
"""
初始化client
:param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由
:param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由
:param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和service_name同时设置，server_ip优先级更高
:param host: 指定sdk请求服务的host名称, 如cmdb.easyops-only.com
"""
if server_ip == "" and server_port != 0 or server_ip != "" and server_port == 0:
raise Exception("server_ip和server_port必须同时指定")
self._server_ip = server_ip
self._server_port = server_port
self._service_name = service_name
self._host = host
def create_collector_aggregate_metric_rule(self, request, org, user, timeout=10):
# type: (collector_service_sdk.model.collector_service.aggregate_metric_rule_pb2.CollectorAggregateMetricRule, int, str, int) -> collector_service_sdk.api.metric.create_aggregate_metric_rule_pb2.CreateCollectorAggregateMetricRuleResponse
"""
创建聚合指标规则
:param request: create_collector_aggregate_metric_rule请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.api.metric.create_aggregate_metric_rule_pb2.CreateCollectorAggregateMetricRuleResponse
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.CreateCollectorAggregateMetricRule"
uri = "/api/v1/collector-aggregate-metric-rule"
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="POST",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.api.metric.create_aggregate_metric_rule_pb2.CreateCollectorAggregateMetricRuleResponse()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
def create_collector_metric(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.create_metric_pb2.CreateCollectorMetricRequest, int, str, int) -> collector_service_sdk.api.metric.create_metric_pb2.CreateCollectorMetricResponse
"""
创建指标
:param request: create_collector_metric请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.api.metric.create_metric_pb2.CreateCollectorMetricResponse
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.CreateCollectorMetric"
uri = "/api/v1/collector-metric"
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="POST",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.api.metric.create_metric_pb2.CreateCollectorMetricResponse()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
def delete_collector_aggregate_metric_rule(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.delete_aggregate_metric_rule_pb2.DeleteCollectorAggregateMetricRuleRequest, int, str, int) -> google.protobuf.empty_pb2.Empty
"""
删除聚合指标规则
:param request: delete_collector_aggregate_metric_rule请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: google.protobuf.empty_pb2.Empty
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.DeleteCollectorAggregateMetricRule"
uri = "/api/v1/collector-aggregate-metric-rule/{instanceId}".format(
instanceId=request.instanceId,
)
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="DELETE",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = google.protobuf.empty_pb2.Empty()
google.protobuf.json_format.ParseDict(rsp_obj, rsp, ignore_unknown_fields=True)
return rsp
def detail_collector_aggregate_metric_rule(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.detail_aggregate_metric_rule_pb2.DetailCollectorAggregateMetricRuleRequest, int, str, int) -> collector_service_sdk.model.collector_service.aggregate_metric_rule_pb2.CollectorAggregateMetricRule
"""
聚合指标规则详情
:param request: detail_collector_aggregate_metric_rule请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.model.collector_service.aggregate_metric_rule_pb2.CollectorAggregateMetricRule
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.DetailCollectorAggregateMetricRule"
uri = "/api/v1/collector-aggregate-metric-rule/{instanceId}".format(
instanceId=request.instanceId,
)
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="GET",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.model.collector_service.aggregate_metric_rule_pb2.CollectorAggregateMetricRule()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
def detail_collector_metric_name(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.get_metric_name_detail_pb2.DetailCollectorMetricNameRequest, int, str, int) -> collector_service_sdk.api.metric.get_metric_name_detail_pb2.DetailCollectorMetricNameResponse
"""
按模型名称获取采集指标名详情
:param request: detail_collector_metric_name请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.api.metric.get_metric_name_detail_pb2.DetailCollectorMetricNameResponse
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.DetailCollectorMetricName"
uri = "/api/v1/detail-collector-metric-name"
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="GET",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.api.metric.get_metric_name_detail_pb2.DetailCollectorMetricNameResponse()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
def list_collector_aggregate_metric_rule(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.list_aggregate_metric_rule_pb2.ListCollectorAggregateMetricRuleRequest, int, str, int) -> collector_service_sdk.api.metric.list_aggregate_metric_rule_pb2.ListCollectorAggregateMetricRuleResponse
"""
获取聚合指标规则
:param request: list_collector_aggregate_metric_rule请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.api.metric.list_aggregate_metric_rule_pb2.ListCollectorAggregateMetricRuleResponse
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.ListCollectorAggregateMetricRule"
uri = "/api/v1/collector-aggregate-metric-rule"
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="GET",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.api.metric.list_aggregate_metric_rule_pb2.ListCollectorAggregateMetricRuleResponse()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
def list_collector_alias_metric(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.list_collector_alias_metric_pb2.ListCollectorAliasMetricRequest, int, str, int) -> collector_service_sdk.api.metric.list_collector_alias_metric_pb2.ListCollectorAliasMetricResponse
"""
获取采集指标
:param request: list_collector_alias_metric请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.api.metric.list_collector_alias_metric_pb2.ListCollectorAliasMetricResponse
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.ListCollectorAliasMetric"
uri = "/api/v1/collector-alias-metric"
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="GET",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.api.metric.list_collector_alias_metric_pb2.ListCollectorAliasMetricResponse()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
def list_collector_metric(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.list_collector_metric_pb2.ListCollectorMetricRequest, int, str, int) -> collector_service_sdk.api.metric.list_collector_metric_pb2.ListCollectorMetricResponse
"""
获取采集指标
:param request: list_collector_metric请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.api.metric.list_collector_metric_pb2.ListCollectorMetricResponse
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.ListCollectorMetric"
uri = "/api/v1/collector-metric"
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="GET",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.api.metric.list_collector_metric_pb2.ListCollectorMetricResponse()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
def list_collector_metric_names(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.list_metric_names_pb2.ListCollectorMetricNamesRequest, int, str, int) -> collector_service_sdk.api.metric.list_metric_names_pb2.ListCollectorMetricNamesResponse
"""
按模型名称获取采集指标名映射列表
:param request: list_collector_metric_names请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.api.metric.list_metric_names_pb2.ListCollectorMetricNamesResponse
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.ListCollectorMetricNames"
uri = "/api/v1/collector-metric-names"
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="GET",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.api.metric.list_metric_names_pb2.ListCollectorMetricNamesResponse()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
def set_resource_key_metric(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.set_resource_key_metric_pb2.SetResourceKeyMetricRequest, int, str, int) -> google.protobuf.empty_pb2.Empty
"""
设置资源关键指标
:param request: set_resource_key_metric请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: google.protobuf.empty_pb2.Empty
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.SetResourceKeyMetric"
uri = "/api/v1/resource-key-metric/{objectId}".format(
objectId=request.objectId,
)
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="POST",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = google.protobuf.empty_pb2.Empty()
google.protobuf.json_format.ParseDict(rsp_obj, rsp, ignore_unknown_fields=True)
return rsp
def update_collector_aggregate_metric_rule(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.update_aggregate_metric_rule_pb2.UpdateCollectorAggregateMetricRuleRequest, int, str, int) -> google.protobuf.empty_pb2.Empty
"""
更新聚合指标规则
:param request: update_collector_aggregate_metric_rule请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: google.protobuf.empty_pb2.Empty
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.UpdateCollectorAggregateMetricRule"
uri = "/api/v1/collector-aggregate-metric-rule/{instanceId}".format(
instanceId=request.instanceId,
)
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="PUT",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = google.protobuf.empty_pb2.Empty()
google.protobuf.json_format.ParseDict(rsp_obj, rsp, ignore_unknown_fields=True)
return rsp
def update_collector_metric_by_name(self, request, org, user, timeout=10):
# type: (collector_service_sdk.api.metric.update_metric_pb2.UpdateCollectorMetricByNameRequest, int, str, int) -> collector_service_sdk.api.metric.update_metric_pb2.UpdateCollectorMetricByNameResponse
"""
依据name更新指标
:param request: update_collector_metric_by_name请求
:param org: 客户的org编号，为数字
:param user: 调用api使用的用户名
:param timeout: 调用超时时间，单位秒
:return: collector_service_sdk.api.metric.update_metric_pb2.UpdateCollectorMetricByNameResponse
"""
headers = {"org": org, "user": user}
route_name = ""
server_ip = self._server_ip
if self._service_name != "":
route_name = self._service_name
elif self._server_ip != "":
route_name = "easyops.api.collector_service.metric.UpdateCollectorMetricByName"
uri = "/api/v1/collector-metric/update-by-name"
requestParam = request
rsp_obj = collector_service_sdk.utils.http_util.do_api_request(
method="PUT",
src_name="logic.collector_service_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
params=google.protobuf.json_format.MessageToDict(
requestParam, preserving_proto_field_name=True),
headers=headers,
timeout=timeout,
)
rsp = collector_service_sdk.api.metric.update_metric_pb2.UpdateCollectorMetricByNameResponse()
google.protobuf.json_format.ParseDict(rsp_obj["data"], rsp, ignore_unknown_fields=True)
return rsp
| 42.456401
| 245
| 0.660855
| 2,454
| 22,884
| 5.810106
| 0.0652
| 0.105485
| 0.102609
| 0.072521
| 0.878524
| 0.87116
| 0.864778
| 0.863726
| 0.85026
| 0.815682
| 0
| 0.005972
| 0.253671
| 22,884
| 538
| 246
| 42.535316
| 0.828854
| 0.235667
| 0
| 0.763006
| 0
| 0
| 0.104398
| 0.094678
| 0
| 0
| 0
| 0
| 0
| 1
| 0.037572
| false
| 0
| 0.052023
| 0
| 0.127168
| 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
|
fd060aaec0545c197324820b7cc9eb01e2125344
| 130
|
py
|
Python
|
models/robnet.py
|
Stonepia/RobNets
|
195a41f37ff278d7acf2f17543ec51b5f92993fb
|
[
"MIT"
] | 121
|
2020-04-04T09:18:27.000Z
|
2022-03-24T10:32:52.000Z
|
models/robnet.py
|
Stonepia/RobNets
|
195a41f37ff278d7acf2f17543ec51b5f92993fb
|
[
"MIT"
] | 17
|
2020-06-14T02:27:04.000Z
|
2021-11-06T07:19:29.000Z
|
models/robnet.py
|
Stonepia/RobNets
|
195a41f37ff278d7acf2f17543ec51b5f92993fb
|
[
"MIT"
] | 17
|
2020-04-14T03:52:27.000Z
|
2022-03-17T11:06:27.000Z
|
from .basic_model import Network
def robnet(genotype_list, **kwargs):
return Network(genotype_list=genotype_list, **kwargs)
| 21.666667
| 57
| 0.776923
| 17
| 130
| 5.705882
| 0.647059
| 0.371134
| 0.371134
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0.123077
| 130
| 5
| 58
| 26
| 0.850877
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
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| 0
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| 1
| 1
| 1
| 0
|
0
| 8
|
b5bfe8a09b18146489c98caf350bd7c1bc38475c
| 26,824
|
py
|
Python
|
QCA4020_SDK/target/quartz/serializer/qapiSerGen/qsgQuartz_Cb.py
|
r8d8/lastlock
|
78c02e5fbb129b1bc4147bd55eec2882267d7e87
|
[
"Apache-2.0"
] | null | null | null |
QCA4020_SDK/target/quartz/serializer/qapiSerGen/qsgQuartz_Cb.py
|
r8d8/lastlock
|
78c02e5fbb129b1bc4147bd55eec2882267d7e87
|
[
"Apache-2.0"
] | null | null | null |
QCA4020_SDK/target/quartz/serializer/qapiSerGen/qsgQuartz_Cb.py
|
r8d8/lastlock
|
78c02e5fbb129b1bc4147bd55eec2882267d7e87
|
[
"Apache-2.0"
] | null | null | null |
# =============================================================================
# Copyright (c) 2018 Qualcomm Technologies, Inc.
# All Rights Reserved.
# Copyright (c) 2018 Qualcomm Technologies, Inc.
# All rights reserved.
# Redistribution and use in source and binary forms, with or without modification, are permitted (subject to the limitations in the disclaimer below)
# provided that the following conditions are met:
# Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
# Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
# Neither the name of Qualcomm Technologies, Inc. nor the names of its contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
# NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,
# BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
# IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
# OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import os
import sys
import re
from optparse import OptionParser
from xml.etree.ElementTree import Element, ElementTree, SubElement, Comment, tostring, parse
from xml.dom import minidom
from qsgUtils import *
from qsgPackedReadWrite import *
import qsgCommon
def CreateQuartzCallbackHeaders(xmlFile, component, root):
c_file = open(os.path.join(qsgCommon.qapiDir, 'qz', 'include', xmlFile.replace('.xml', '') + '_qz_cb.h'), 'w+')
# Generate the Quartz headers.
c_file.write('/*\n * Copyright (c) 2018 Qualcomm Technologies, Inc.\n * All Rights Reserved.\n')
// Copyright (c) 2018 Qualcomm Technologies, Inc.
// All rights reserved.
// Redistribution and use in source and binary forms, with or without modification, are permitted (subject to the limitations in the disclaimer below)
// provided that the following conditions are met:
// Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
// Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
// Neither the name of Qualcomm Technologies, Inc. nor the names of its contributors may be used to endorse or promote products derived
// from this software without specific prior written permission.
// NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE.
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,
// BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
// IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
// LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
// WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
// EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
c_file.write('#include "idlist.h"\n')
c_file.write('#include "qsCommon.h"\n')
c_file.write('#include "qapi_' + component + '.h"\n')
c_file.write('#include "' + xmlFile.replace('.xml', '') + '_common.h"\n\n')
# Generate the Quartz callback function handler prototypes
for callbackElement in root.findall('callback'):
CreateQzCallbackHandlerDeclaration(callbackElement, c_file)
c_file.close()
# Creates the files for manual callbacks
def CreateManualCbFiles(xmlFile, component):
# Generate the Quartz C files.
manual_h_file = open(os.path.join(qsgCommon.manualDir, 'qz', 'include', xmlFile.replace('.xml', '') + '_qz_cb_mnl.h'), 'w+')
manual_h_file.write('/*\n * Copyright (c) 2018 Qualcomm Technologies, Inc.\n * All Rights Reserved.\n')
// Copyright (c) 2018 Qualcomm Technologies, Inc.
// All rights reserved.
// Redistribution and use in source and binary forms, with or without modification, are permitted (subject to the limitations in the disclaimer below)
// provided that the following conditions are met:
// Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
// Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
// Neither the name of Qualcomm Technologies, Inc. nor the names of its contributors may be used to endorse or promote products derived
// from this software without specific prior written permission.
// NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE.
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,
// BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
// IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
// LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
// WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
// EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
manual_c_file = open(os.path.join(qsgCommon.manualDir, 'qz', xmlFile.replace('.xml', '') + '_qz_cb_mnl.c'), 'w+')
manual_c_file.write('/*\n * Copyright (c) 2018 Qualcomm Technologies, Inc.\n * All Rights Reserved.\n')
// Copyright (c) 2018 Qualcomm Technologies, Inc.
// All rights reserved.
// Redistribution and use in source and binary forms, with or without modification, are permitted (subject to the limitations in the disclaimer below)
// provided that the following conditions are met:
// Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
// Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
// Neither the name of Qualcomm Technologies, Inc. nor the names of its contributors may be used to endorse or promote products derived
// from this software without specific prior written permission.
// NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE.
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,
// BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
// IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
// LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
// WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
// EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
manual_c_file.write('#include <string.h>\n')
manual_c_file.write('#include "idlist.h"\n')
manual_c_file.write('#include "qsCommon.h"\n')
manual_c_file.write('#include "qsQuartz.h"\n')
manual_c_file.write('#include "qsPack.h"\n')
manual_c_file.write('#include "qapi_' + component + '.h"\n')
manual_h_file.write('#include "qsCommon.h"\n')
manual_h_file.write('#include "qapi_' + component + '.h"\n')
manual_h_file.write('#include "' + xmlFile.replace('.xml', '') + '_common.h"\n')
manual_c_file.write('#include "' + xmlFile.replace('.xml', '') + '_common.h"\n')
manual_c_file.write('#include "' + xmlFile.replace('.xml', '') + '_qz_cb_mnl.h"\n\n')
return manual_c_file, manual_h_file
def CreateQuartzCallbackCode(xmlFile, component, root):
# Find out if we need to create a manually written code file for functions in this module
fileName = xmlFile.replace('.xml', '')
manual_c_file = None
manual_h_file = None
manualCbFileNeeded = False
for callbackElement in root.findall('callback'):
if callbackElement.get('name') in qsgCommon.manualCbList:
manualCbFileNeeded = True
if qsgCommon.generateManual:
manual_c_file, manual_h_file = CreateManualCbFiles(xmlFile, component)
# Generate the Quartz C files.
c_file = open(os.path.join(qsgCommon.qapiDir, 'qz', fileName + '_qz_cb.c'), 'w+')
c_file.write('/*\n * Copyright (c) 2018 Qualcomm Technologies, Inc.\n * All Rights Reserved.\n')
// Copyright (c) 2018 Qualcomm Technologies, Inc.
// All rights reserved.
// Redistribution and use in source and binary forms, with or without modification, are permitted (subject to the limitations in the disclaimer below)
// provided that the following conditions are met:
// Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
// Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
// Neither the name of Qualcomm Technologies, Inc. nor the names of its contributors may be used to endorse or promote products derived
// from this software without specific prior written permission.
// NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE.
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,
// BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
// IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
// OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
// LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
// WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
// EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
c_file.write('#include <string.h>\n')
c_file.write('#include "qsCommon.h"\n')
c_file.write('#include "qsQuartz.h"\n')
c_file.write('#include "qapi_' + component + '.h"\n')
c_file.write('#include "' + fileName + '_common.h"\n')
if manualCbFileNeeded:
c_file.write('#include "' + fileName + '_qz_cb_mnl.h"\n')
c_file.write('#include "' + fileName + '_qz_cb.h"\n\n')
CreateQuartzCallbackHeaders(xmlFile, component, root)
# Generate the Quartz callback function handler prototypes
for callbackElement in root.findall('callback'):
if callbackElement.get('name') in qsgCommon.manualCbList:
# Create the stub function that calls the manual callback
CreateQzManualCallbackHandlerStubs(root, callbackElement, c_file)
if qsgCommon.generateManual:
# Create the manual callback declarations
CreateQzManualCallbackHandlerDeclaration(root, callbackElement, manual_h_file)
# Go ahead and generate the code in the manual file, but flag it for manual writing
CreateQzCallbackHandlerFunctions(component, fileName, callbackElement, manual_c_file, True)
else:
CreateQzCallbackHandlerFunctions(component, fileName, callbackElement, c_file, False)
# Close the files
if manual_c_file is not None:
manual_c_file.close()
if manual_h_file is not None:
manual_h_file.close()
c_file.close()
def CreateQzManualCallbackHandlerDeclaration(root, callbackElement, c_file):
# Handle return value
retElement = callbackElement.findall('return')[0]
# Write the return value.
if 'const' in retElement.get('attributes'):
c_file.write('const')
c_file.write('\n' + retElement.get('type') + ' ')
if 'ptr' in retElement.get('attributes'):
c_file.write('*')
if 'doubleptr' in retElement.get('attributes'):
c_file.write('*')
# Write function name and arguments
c_file.write('Mnl_QZ_' + callbackElement.get('name') + '_Handler(')
if len(callbackElement.findall('argument')) > 0:
for argElement in callbackElement.findall('argument'):
if 'value' in argElement.get('attributes'):
if 'const' in argElement.get('attributes'):
c_file.write('const ')
c_file.write(argElement.get('type') + ' ' + argElement.get('name') + ', ')
elif argElement.get('attributes') == 'ptr':
c_file.write(argElement.get('type') + ' *' + argElement.get('name') + ', ')
elif argElement.get('attributes') == 'ptr,const':
c_file.write('const ' + argElement.get('type') + ' *' + argElement.get('name') + ', ')
elif argElement.get('attributes') == 'doubleptr':
c_file.write(argElement.get('type') + ' **' + argElement.get('name') + ', ')
elif argElement.get('attributes') == 'doubleptr,const':
c_file.write('const ' + argElement.get('type') + ' **' + argElement.get('name') + ', ')
else:
print '#warning# Unhandled argument type ' + argElement.get('name') + ' in ' + callbackElement.get('name')
c_file.seek(-2,1)
c_file.write(');\n\n')
else:
c_file.write('void);\n\n')
# Generates function definitions for packing structures.
def CreateQzCallbackHandlerDeclaration(callbackElement, c_file):
if (callbackElement.findall('return')) > 0:
# Write the return value
retElement = callbackElement.findall('return')[0]
if 'const' in retElement.get('attributes'):
c_file.write('const ')
c_file.write(retElement.get('type') + ' ')
if 'ptr' in retElement.get('attributes'):
c_file.write('*')
if 'doubleptr' in retElement.get('attributes'):
c_file.write('*')
# Write the function name
c_file.write('QZ_' + callbackElement.get('name') + '_Handler(')
# Write the function arguments
if len(callbackElement.findall('argument')) > 0:
for argElement in callbackElement.findall('argument'):
if 'const' in argElement.get('attributes'):
c_file.write('const ')
c_file.write(argElement.get('type') + ' ')
if 'ptr' in argElement.get('attributes'):
c_file.write('*')
if 'doubleptr' in argElement.get('attributes'):
c_file.write('*')
c_file.write(argElement.get('name') + ', ')
c_file.seek(-2,1)
c_file.write(');\n')
else:
# Write void function parameter
c_file.write('void);\n')
def CreateQzManualCallbackHandlerStubs(root, callbackElement, c_file):
# Write out the function definition.
if (callbackElement.findall('return')) > 0:
# Write the return value
retElement = callbackElement.findall('return')[0]
if 'const' in retElement.get('attributes'):
c_file.write('const ')
c_file.write(retElement.get('type') + ' ')
if 'ptr' in retElement.get('attributes'):
c_file.write('*')
if 'doubleptr' in retElement.get('attributes'):
c_file.write('*')
c_file.write('QZ_' + callbackElement.get('name') + '_Handler(')
# Write the function arguments
if len(callbackElement.findall('argument')) > 0:
for argElement in callbackElement.findall('argument'):
if 'const' in argElement.get('attributes'):
c_file.write('const ')
c_file.write(argElement.get('type') + ' ')
if 'ptr' in argElement.get('attributes'):
c_file.write('*')
if 'doubleptr' in argElement.get('attributes'):
c_file.write('*')
c_file.write(argElement.get('name') + ', ')
c_file.seek(-2,1)
c_file.write(')\n')
else:
# Write void function parameter
c_file.write('void)\n')
c_file.write('{\n')
if 'void' in callbackElement.findall('return')[0].get('type') and callbackElement.findall('return')[0].get('attributes') == 'value':
c_file.write(' Mnl_QZ_' + callbackElement.get('name') + '_Handler(')
for argElement in callbackElement.findall('argument'):
c_file.write(argElement.get('name') + ', ')
c_file.seek(-2,1)
c_file.write(');\n}\n')
else:
c_file.write(' return(Mnl_' + callbackElement.get('name') + '_Handler(')
if len(callbackElement.findall('argument')) > 0:
for argElement in callbackElement.findall('argument'):
c_file.write(argElement.get('name') + ', ')
c_file.seek(-2,1)
c_file.write('));\n}\n')
else:
c_file.write('void);\n}\n')
# Generates function definitions for packing structures.
def CreateQzCallbackHandlerFunctions(component, fileName, callbackElement, c_file, isManualCode):
decSize = 0
numPtrs = 0
structSizeStr = ''
varStructSizeStr = ''
# Get the packed write parameters string.
WriteParamString = MakePackedWriteParametersString(callbackElement, callbackElement.findall('argument'), True, ['out'], ' ', '&qsInputBuffer', '')
# Write out the function definition.
if (callbackElement.findall('return')) > 0:
# Write the return value
retElement = callbackElement.findall('return')[0]
if 'const' in retElement.get('attributes'):
c_file.write('const ')
c_file.write(retElement.get('type') + ' ')
if 'ptr' in retElement.get('attributes'):
c_file.write('*')
if 'doubleptr' in retElement.get('attributes'):
c_file.write('*')
# Write the function name
if isManualCode:
c_file.write('Mnl_')
c_file.write('QZ_' + callbackElement.get('name') + '_Handler(')
# Write the function arguments
if len(callbackElement.findall('argument')) > 0:
for argElement in callbackElement.findall('argument'):
if 'const' in argElement.get('attributes'):
c_file.write('const ')
c_file.write(argElement.get('type') + ' ')
if 'ptr' in argElement.get('attributes'):
c_file.write('*')
if 'doubleptr' in argElement.get('attributes'):
c_file.write('*')
c_file.write(argElement.get('name') + ', ')
c_file.seek(-2,1)
c_file.write(')\n')
else:
# Write void function parameter
c_file.write('void)\n')
c_file.write('{\n')
# Generate an error if this is supposed to be manual code
if isManualCode:
c_file.write('\n#error Must complete this code manually.\n\n')
# Create local variables.
c_file.write(' PackedBuffer_t qsInputBuffer = { NULL, 0, 0, 0, NULL, NULL };\n')
c_file.write(' SerStatus_t qsResult = ssSuccess;\n')
c_file.write(' uint32_t qsIndex = 0;\n')
# c_file.write(' uint32_t FunctionID = 0;\n')
c_file.write(' uint16_t qsSize = 0;\n\n')
c_file.write(' UNUSED(qsIndex);\n\n')
if not (retElement.get('attributes') == 'value' and retElement.get('type') == 'void'):
# Create return variable
c_file.write(' /* Return value. */\n')
if 'value' in retElement.get('attributes'):
c_file.write(' ' + retElement.get('type') + ' qsRetVal = 0;\n\n')
elif retElement.get('attributes') == 'ptr':
c_file.write(' ' + retElement.get('type') + ' *qsRetVal = NULL;\n\n')
elif retElement.get('attributes') == 'ptr,const':
c_file.write(' const ' + retElement.get('type') + ' *qsRetVal = NULL;\n\n')
elif retElement.get('attributes') == 'doubleptr':
c_file.write(' ' + retElement.get('type') + ' **qsRetVal = NULL;\n\n')
elif retElement.get('attributes') == 'doubleptr,const':
c_file.write(' const ' + retElement.get('type') + ' **qsRetVal = NULL;\n\n')
else:
print '#warning# Unhandled return type ' + retElement.get('type') + ' in ' + callbackElement.get('name')
# Calculate output buffer size.
c_file.write(' /* Calculate size of packed function arguments. */\n')
for argElement in callbackElement.findall('argument'):
if argElement.get('type') in qsgCommon.callbackList:
structSizeStr = structSizeStr
elif 'value' in argElement.get('attributes'):
if IsPrimitive(argElement.get('type')):
decSize = decSize + GetPrimitiveSize(argElement.get('type'))
else:
structSizeStr = structSizeStr + GetCalcPackedSizeFunctionName(argElement.get('type')) + '(' + GetCastStr(argElement.get('type')) + argElement.get('name') + ') + '
elif (argElement.get('attributes') == 'ptr' or argElement.get('attributes') == 'ptr,const'):
if argElement.get('lengthParam') == '1':
numPtrs = numPtrs + 1
structSizeStr = structSizeStr + GetCalcPackedSizeFunctionName(argElement.get('type')) + '(' + GetCastStr(argElement.get('type')) + argElement.get('name') + ') + '
elif isParamLengthInt(argElement.get('lengthParam')) == True:
numPtrs = numPtrs + 1
structSizeStr = structSizeStr + argElement.get('lengthParam') + ' + '
elif argElement.get('lengthParam') == '__strlen__':
numPtrs = numPtrs + 1
structSizeStr = structSizeStr + '((' + argElement.get('name') + ' != NULL) ? (strlen((const char *)' + argElement.get('name') + ')+1) : 0) + '
else:
# Loop through variable length data.
for otherArg in callbackElement.findall('argument'):
if otherArg.get('name') == argElement.get('lengthParam'):
numPtrs = numPtrs + 1
if 'value' in otherArg.get('attributes'):
if IsPrimitive(argElement.get('type')):
varStructSizeStr = varStructSizeStr + ' qsSize = qsSize + ((' + argElement.get('lengthParam') + ')*(' + str(GetPrimitiveSize(argElement.get('type'))) + '));\n'
else:
varStructSizeStr = varStructSizeStr + ' for (qsIndex = 0; qsIndex < ' + argElement.get('lengthParam') + '; qsIndex++)\n'
varStructSizeStr = varStructSizeStr + ' {\n'
varStructSizeStr = varStructSizeStr + ' qsSize = qsSize + ' + GetCalcPackedSizeFunctionName(argElement.get('type')) + '(' + GetCastStr(argElement.get('type')) + '(&' + argElement.get('name') + ')[qsIndex]);\n'
varStructSizeStr = varStructSizeStr + ' }\n'
else:
if IsPrimitive(argElement.get('type')):
varStructSizeStr = varStructSizeStr + ' qsSize = qsSize + ((*' + argElement.get('lengthParam') + ')*(' + str(GetPrimitiveSize(argElement.get('type'))) + '));\n'
else:
varStructSizeStr = varStructSizeStr + ' for (qsIndex = 0; qsIndex < *' + argElement.get('lengthParam') + '; qsIndex++)\n'
varStructSizeStr = varStructSizeStr + ' {\n'
varStructSizeStr = varStructSizeStr + ' qsSize = qsSize + ' + GetCalcPackedSizeFunctionName(argElement.get('type')) + '(' + GetCastStr(argElement.get('type')) + '(&' + argElement.get('name') + ')[qsIndex]);\n'
varStructSizeStr = varStructSizeStr + ' }\n'
if numPtrs > 0:
structSizeStr = structSizeStr + '(QS_POINTER_HEADER_SIZE * ' + str(numPtrs) + ') + '
if decSize == 0 and structSizeStr == '':
c_file.write(' qsSize = 0')
if decSize <> 0 and structSizeStr == '':
c_file.write(' qsSize = ' + str(decSize))
if decSize <> 0 and structSizeStr <> '':
c_file.write(' qsSize = (' + str(decSize) + ' + ' + structSizeStr)
c_file.seek(-3,1)
c_file.write(')')
if decSize == 0 and structSizeStr <> '':
c_file.write(' qsSize = (' + structSizeStr)
c_file.seek(-3,1)
c_file.write(')')
c_file.write(';\n\n')
if varStructSizeStr <> '':
c_file.write(varStructSizeStr);
c_file.write('\n');
# Allocate packed buffer
c_file.write(' if(AllocatePackedBuffer(NULL, QS_ASYNC_E, MODULE_' + component.upper() + ', ' + fileName.upper() + '_FILE_ID, ' + callbackElement.get('name').upper() + '_CALLBACK_ID, &qsInputBuffer, qsSize))\n')
c_file.write(' {\n')
# Write each element to the buffer.
if len(callbackElement.findall('argument')) > 0:
c_file.write(' /* Write arguments packed. */\n')
c_file.write(WriteParamString)
# Send command and get response.
c_file.write(' /* Send the event. */\n')
c_file.write(' if(qsResult == ssSuccess)\n')
c_file.write(' qsResult = SendEvent(&qsInputBuffer);\n')
c_file.write(' }\n')
c_file.write(' else\n')
c_file.write(' qsResult = ssAllocationError;\n\n')
c_file.write('#ifdef ENABLE_DEBUG_CALLBACKS\n')
c_file.write(' if(qsResult != ssSuccess)\n')
c_file.write(' SendErrorCallback(MODULE_' + component.upper() + ', ' + fileName.upper() + '_FILE_ID, ' + callbackElement.get('name').upper() + '_CALLBACK_ID);\n')
c_file.write('#endif // ENABLE_DEBUG_CALLBACKS\n')
c_file.write('}\n')
| 58.567686
| 240
| 0.669512
| 3,281
| 26,824
| 5.39683
| 0.097531
| 0.040944
| 0.06777
| 0.016773
| 0.834698
| 0.809793
| 0.789914
| 0.752866
| 0.737053
| 0.717908
| 0
| 0.004746
| 0.206643
| 26,824
| 457
| 241
| 58.695842
| 0.827311
| 0.119445
| 0
| 0.590028
| 0
| 0.044321
| 0.166094
| 0.007428
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.024931
| null | null | 0.00554
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
bd5319f2c5a0b5a304ad511eabf784452fb08260
| 2,408
|
py
|
Python
|
REGUL/temp.py
|
RandallBalestriero/Hessian
|
e0e084fef1ee803e22b345c0058a0c0fd64d2bde
|
[
"Apache-2.0"
] | null | null | null |
REGUL/temp.py
|
RandallBalestriero/Hessian
|
e0e084fef1ee803e22b345c0058a0c0fd64d2bde
|
[
"Apache-2.0"
] | null | null | null |
REGUL/temp.py
|
RandallBalestriero/Hessian
|
e0e084fef1ee803e22b345c0058a0c0fd64d2bde
|
[
"Apache-2.0"
] | null | null | null |
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
def doit(imagenb, name):
image1 = imagenb
image = dataset['images/test_set'][image1]
lab = dataset['labels/test_set'][image1]
other = np.where(dataset['labels/test_set'] == lab)[0][100]
dest = dataset['images/test_set'][other]
time = np.linspace(0, 1, 32*5).reshape((-1, 1, 1, 1))
interp = np.expand_dims(image, 0) * time + np.expand_dims(dest, 0) * (1 - time)
outs = list()
for b in range(5):
batch = interp[32*b:32*(b+1)]
out = workplace.session.run(dnn[-1][:32], feed_dict={dataset.images: batch,
**dnn.deter_dict(True)})
outs.append(out)
outs = np.concatenate(outs, 0)
plt.figure(figsize=(14,5))
plt.subplot(131)
image -= image.min()
plt.imshow(image.transpose((1, 2, 0)) / image.max(), aspect='auto')
plt.subplot(132)
dest -= dest.min()
plt.imshow(dest.transpose((1, 2, 0)) / image.max(), aspect='auto')
plt.subplot(133)
for c in range(10):
plt.plot(outs[:, c], c='k')
plt.savefig(name+'test_{}_{}.png'.format(imagenb,
dataset['labels/test_set'][image1]))
plt.close()
image = dataset['images/train_set'][image1]
lab = dataset['labels/train_set'][image1]
other = np.where(dataset['labels/train_set'] == lab)[0][100]
dest = dataset['images/train_set'][other]
time = np.linspace(0, 1, 32*5).reshape((-1, 1, 1, 1))
interp = np.expand_dims(image, 0) * time + np.expand_dims(dest, 0) * (1 - time)
outs = list()
for b in range(5):
batch = interp[32*b:32*(b+1)]
out = workplace.session.run(dnn[-1][:32], feed_dict={dataset.images: batch,
**dnn.deter_dict(True)})
outs.append(out)
outs = np.concatenate(outs, 0)
plt.figure(figsize=(14,5))
plt.subplot(131)
image -= image.min()
plt.imshow(image.transpose((1, 2, 0)) / image.max(), aspect='auto')
plt.subplot(132)
dest -= dest.min()
plt.imshow(dest.transpose((1, 2, 0)) / image.max(), aspect='auto')
plt.subplot(133)
for c in range(10):
plt.plot(outs[:, c], c='k')
plt.savefig(name+'train_{}_{}.png'.format(imagenb,
dataset['labels/test_set'][image1]))
plt.close()
| 37.625
| 83
| 0.559385
| 334
| 2,408
| 3.967066
| 0.224551
| 0.058868
| 0.039245
| 0.060377
| 0.873962
| 0.833208
| 0.833208
| 0.741132
| 0.741132
| 0.741132
| 0
| 0.055246
| 0.255814
| 2,408
| 63
| 84
| 38.222222
| 0.684152
| 0
| 0
| 0.736842
| 0
| 0
| 0.084823
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.017544
| false
| 0
| 0.035088
| 0
| 0.052632
| 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
|
1fe20467e818df004b4972ca51e8441282654731
| 10,577
|
py
|
Python
|
src/util_html.py
|
Opdoop/Parallel-Text-Extraction
|
dd2f49099c922899b9612884c58d67a1c1448fa4
|
[
"MIT"
] | 3
|
2021-01-04T06:18:03.000Z
|
2021-10-13T10:48:14.000Z
|
src/util_html.py
|
Opdoop/Parallel-Text-Extraction
|
dd2f49099c922899b9612884c58d67a1c1448fa4
|
[
"MIT"
] | null | null | null |
src/util_html.py
|
Opdoop/Parallel-Text-Extraction
|
dd2f49099c922899b9612884c58d67a1c1448fa4
|
[
"MIT"
] | null | null | null |
from bs4 import BeautifulSoup
import os
import json
import re
from langdetect import detect
import nltk
from nltk.util import ngrams
import jieba
from config import *
import time
def get_dir_list(in_dir):
'''
Return dir list
:param in_dir: input dir
:return: dir list
'''
files_list = list()
for (dirpath, dirnames, filenames) in os.walk(in_dir):
files_list += [os.path.join(dirpath, file) for file in filenames]
return files_list
# Function to generate n-grams from sentences.
def extract_it_ngrams(data, num):
'''
抽取 ngram
:param data: 字符串
:param num: n
:return: n-gram list
'''
n_grams = ngrams(nltk.word_tokenize(data), num)
return [' '.join(grams) for grams in n_grams]
def extract_zh_ngrams(data, num):
'''
抽取 ngram
:param data: 字符串
:param num: n
:return: n-gram list
'''
seg_list = jieba.cut(data, cut_all=False)
seg_str = ' '.join(seg_list)
n_grams = ngrams(nltk.word_tokenize(seg_str), num)
return [''.join(grams) for grams in n_grams]
def text_check_zh(text):
'''
chinese candidates filter
:param text: input string
:return: ture or false
'''
text_len = len(text)
if text_len >= 5 and text_len <= 20:
if not re.search(
u"[（）()【】“”@《》:：；;0-9a-zA-Z\u30a0-\u30ff\u3040-\u309f\／▽▼＜／——、\[\]\-~#￥%……&*/\|>●「」→★『』～ _＞◎·■ 丨◇♀├─＂·〔※◆〜]+",
text): # 不包含片假名和平假名，不包含特殊字符英文和数字
try:
if (detect(text) == 'zh-cn' or detect(text) == 'zh-tw'):
return True
except:
pass
# print(text)
return False
def text_check_it(text):
'''
italian candidates filter
:param text: input string
:return: ture or false
'''
text_len = len(text)
if text_len < 100 and text_len > 5:
if not re.search(u"[\u4e00-\u9fa5、\[\]\-~#￥%……&*/\|“”>●「」→★『』～_＞◎·■ 丨◇♀├─＂《》·〔※◆〜0-9:：；;——（）()【】@]+",text): # 不包含片假名和平假名，不包含特殊字符英文和数字
try:
if detect(text) == 'it':
return True
except:
pass
# print(text)
return False
def html_to_json_zh(files_list, bin_size, save_json_dir):
'''
读取 html，转为字典 {id: {text:str, file:str, location:str}}
'''
## 获取目录下的所有文件名
## 遍历文件，截取字符串
location_dict = {}
text_id = 0
text_set = set()
file_nbr = 0
start = time.time()
for file in files_list:
try:
with open(file, 'r', encoding='utf-8') as f: ## 有些文件可能是反扒， utf8 无法解码
raw_html = f.read()
except:
print(file) ## continue，不做任何处理。
continue
try:
soup = BeautifulSoup(raw_html, 'html.parser') ## new 一个 parser
except:
continue
raw_text = soup.get_text().split('\n')
for text in filter(None, raw_text): # 过滤 \n
text = text.strip() # 过滤空格
index = raw_html.find(text) # 查找下标
if index != -1: # 有找到
### 对 raw 的长句进行切分，这样感觉比较合理
for clause in re.split('[,，。.?？!！]', text):
if text_check_zh(clause): # 满足文本条件
## 坐标拼接
# pdb.set_trace()
try:
for place in re.finditer(clause, raw_html):
location = '{}:{}'.format(place.start(), place.end()) # 按照提交时候需要的格式存下此句在原 html 中的坐标
## 拼接一条记录 {text:str, file:str, location:str}
line_dict = {}
line_dict['text'] = clause
line_dict['file'] = file[3:] # 提交格式为 'zh/2020-04-15/balabala.html'， 这里的 file 为项目内结构内的相对路径 '../zh/2020-04-15/balabala.html'，裁剪。
line_dict['location'] = location
if clause in text_set:
continue
## 并入总表
location_dict[text_id] = line_dict
text_set.add(clause)
text_id += 1 # 更新 id
break
## add n-gram
# pdb.set_trace()
if USE_N_GRAM:
for n in [2, 3]:
for n_gram in extract_zh_ngrams(clause, n):
# pdb.set_trace()
if len(n_gram) > 4 and len(n_gram) < 9:
for place in re.finditer(n_gram, raw_html):
location = '{}:{}'.format(place.start(),place.end()) # 按照提交时候需要的格式存下此句在原 html 中的坐标
## 拼接一条记录 {text:str, file:str, location:str}
line_dict = {}
line_dict['text'] = n_gram
line_dict['file'] = file[3:] # 提交格式为 'zh/2020-04-15/balabala.html'， 这里的 file 为项目内结构内的相对路径 '../zh/2020-04-15/balabala.html'，裁剪。
line_dict['location'] = location
if n_gram in text_set:
continue
## 并入总表
location_dict[text_id] = line_dict
text_set.add(n_gram)
text_id += 1 # 更新 id
break
except:
continue
# print(file)
if text_id > bin_size:
break
file_nbr += 1
## 存为 json
with open(save_json_dir, 'w') as fp:
json.dump(location_dict, fp)
end = time.time()
print('Finish chinese in : {}'.format(end - start)) # log time cost
return save_json_dir
def html_to_json_it(files_list, bin_size, save_json_dir):
'''
读取 html，转为字典 {id: {text:str, file:str, location:str}}
'''
## 获取目录下的所有文件名
## 遍历文件，截取字符串
location_dict = {}
text_id = 0
text_set = set()
file_nbr = 0
start = time.time()
for file in files_list:
try:
with open(file, 'r', encoding='utf-8') as f: ## 有些文件可能是反扒， utf8 无法解码
raw_html = f.read()
except:
print(file) ## continue，不做任何处理。
continue
try:
soup = BeautifulSoup(raw_html, 'html.parser') ## new 一个 parser
except:
continue
raw_text = soup.get_text().split('\n')
for text in filter(None, raw_text): # 过滤 \n
text = text.strip() # 过滤空格
index = raw_html.find(text) # 查找下标
if index != -1: # 有找到
### 对 raw 的长句进行切分，这样感觉比较合理
for clause in re.split('[,，。.?？!！]', text):
# pdb.set_trace()
if text_check_it(clause): # 满足文本条件
## 坐标拼接
# pdb.set_trace()
try:
for place in re.finditer(clause, raw_html):
location = '{}:{}'.format(place.start(), place.end()) # 按照提交时候需要的格式存下此句在原 html 中的坐标
## 拼接一条记录 {text:str, file:str, location:str}
line_dict = {}
line_dict['text'] = clause
line_dict['file'] = file[3:] # 提交格式为 'zh/2020-04-15/balabala.html'， 这里的 file 为项目内结构内的相对路径 '../zh/2020-04-15/balabala.html'，裁剪。
line_dict['location'] = location
if clause in text_set:
continue
## 并入总表
location_dict[text_id] = line_dict
text_set.add(clause)
text_id += 1 # 更新 id
# if text_id % 100 == 0 :
# print(text_id)
break
## add n-gram
if USE_N_GRAM:
for n in [2, 3]:
for n_gram in extract_it_ngrams(clause, n):
if detect(n_gram) == 'it':
for place in re.finditer(n_gram, raw_html):
location = '{}:{}'.format(place.start(),place.end()) # 按照提交时候需要的格式存下此句在原 html 中的坐标
## 拼接一条记录 {text:str, file:str, location:str}
line_dict = {}
line_dict['text'] = n_gram
line_dict['file'] = file[3:] # 提交格式为 'zh/2020-04-15/balabala.html'， 这里的 file 为项目内结构内的相对路径 '../zh/2020-04-15/balabala.html'，裁剪。
line_dict['location'] = location
if n_gram in text_set:
continue
## 并入总表
location_dict[text_id] = line_dict
text_set.add(n_gram)
text_id += 1 # 更新 id
break
except:
continue
# print(file)
if text_id > bin_size:
break
file_nbr += 1
## 存为 json
with open(save_json_dir, 'w') as fp:
json.dump(location_dict, fp)
end = time.time()
print('Finish italian in : {}'.format(end - start)) # log time cost
return save_json_dir
| 40.680769
| 176
| 0.405503
| 1,043
| 10,577
| 4.009588
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| 0.038259
| 0.022956
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| 10,577
| 259
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| 40.837838
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| 0.040936
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| 0.011696
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| 0.023392
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0
| 7
|
951eb3a4fcada7cb210654b2ac3dc4c8fb67f5bb
| 307
|
py
|
Python
|
models/__init__.py
|
r-o-s-h-a-n/semisupervisedFL
|
4c568b4a9cead5aa57f403c1e1bc10e2eaac07e3
|
[
"MIT"
] | 5
|
2020-02-25T00:24:11.000Z
|
2021-03-19T12:28:14.000Z
|
models/__init__.py
|
r-o-s-h-a-n/semisupervisedFL
|
4c568b4a9cead5aa57f403c1e1bc10e2eaac07e3
|
[
"MIT"
] | 9
|
2020-02-11T02:33:56.000Z
|
2021-11-10T19:54:17.000Z
|
models/__init__.py
|
r-o-s-h-a-n/semisupervisedFL
|
4c568b4a9cead5aa57f403c1e1bc10e2eaac07e3
|
[
"MIT"
] | 2
|
2020-02-13T15:12:02.000Z
|
2020-05-28T18:23:17.000Z
|
from models.dense_model import DenseSupervisedModel, DenseAutoencoderModel
from models.conv_model import ConvSupervisedModel, ConvAutoencoderModel
from models.rotation_model import DeepRotationSupervisedModel, DeepRotationSelfSupervisedModel, SimpleRotationSupervisedModel, SimpleRotationSelfSupervisedModel
| 102.333333
| 160
| 0.921824
| 23
| 307
| 12.173913
| 0.652174
| 0.107143
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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| 0.052117
| 307
| 3
| 160
| 102.333333
| 0.962199
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|
0
| 7
|
95314bc6c31b8c2963a02d9145804c7ef63278cc
| 182
|
py
|
Python
|
client_code/utilities/__init__.py
|
Alcampopiano/OpenQuestion
|
8576ec3372eca3b3b51661ad7f5c615fe8193946
|
[
"BSD-3-Clause"
] | 4
|
2021-01-27T15:36:21.000Z
|
2021-06-04T17:43:27.000Z
|
client_code/utilities/__init__.py
|
Alcampopiano/OpenQuestion
|
8576ec3372eca3b3b51661ad7f5c615fe8193946
|
[
"BSD-3-Clause"
] | 1
|
2021-02-04T20:24:38.000Z
|
2021-02-05T13:47:41.000Z
|
client_code/utilities/__init__.py
|
Alcampopiano/OpenQuestion
|
8576ec3372eca3b3b51661ad7f5c615fe8193946
|
[
"BSD-3-Clause"
] | 2
|
2021-01-27T15:36:30.000Z
|
2021-02-02T06:11:35.000Z
|
import anvil.facebook.auth
import anvil.google.auth, anvil.google.drive
from anvil.google.drive import app_files
import anvil.microsoft.auth
import anvil.users
from . import augment
| 26
| 44
| 0.835165
| 28
| 182
| 5.392857
| 0.428571
| 0.291391
| 0.198676
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| 182
| 6
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| 30.333333
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|
0
| 7
|
1f14761d44c46e8aa96db0f9e7937b42f59aa297
| 16,775
|
py
|
Python
|
net.py
|
MitraDP/Pancreas-CT-image-and-volumetric-segmentation
|
31b9b83187c8fc105bd491e31780b323b13b2ca5
|
[
"MIT"
] | 11
|
2021-03-16T01:59:16.000Z
|
2022-02-27T13:29:16.000Z
|
net.py
|
zz10001/Pancreas-CT-image-and-volumetric-semantic-segmentation
|
25fa090c3a1e7f4f0220c3a09a91a444044f0c13
|
[
"MIT"
] | 1
|
2021-09-14T08:04:27.000Z
|
2021-09-14T08:04:27.000Z
|
net.py
|
zz10001/Pancreas-CT-image-and-volumetric-semantic-segmentation
|
25fa090c3a1e7f4f0220c3a09a91a444044f0c13
|
[
"MIT"
] | 3
|
2021-03-16T01:59:19.000Z
|
2022-02-22T13:47:27.000Z
|
#-----------------------------------------------------------------------#
# Library imports #
#-----------------------------------------------------------------------#
import torch
import torch.nn as nn
from collections import OrderedDict
#-----------------------------------------------------------------------#
# UNet_2D #
# 2 Dimensional Implementation of UNet acrchitecture #
#-----------------------------------------------------------------------#
# Reference: #
# Ronneberger, O.; Fischer, P.; Brox, T. U-Net: Convolutional Networks #
# for Biomedical Image Segmentation. In Proceedings of the International#
# Conference on Medical image computing and computer-assisted #
# intervention, Munich, Germany, 5–9 October 2015; pp. 234–241. #
#-----------------------------------------------------------------------#
# Adopted from: #
# The net: #
# github.com/mateuszbuda/brain-segmentation-pytorch/blob/master/unet.py #
# https://github.com/hlamba28/UNET-TGS/blob/master/TGS%20UNET.ipynb #
# The weight initialization: #
# https://discuss.pytorch.org/t/pytorch-how-to-initialize-weights #
# /81511/4 #
# https://discuss.pytorch.org/t #
# /how-are-layer-weights-and-biases-initialized-by-default/13073/24 #
# The weight standardization: #
# https://github.com/joe-siyuan-qiao/WeightStandardization #
# Siyuan Qiao et al., Micro-Batch Training with Batch-Channel #
# Normalization and Weight Standardization,arXiv:1903.10520v2,2020 #
#-----------------------------------------------------------------------#
# in_channels: number of input channels #
# out_channels: number of output channels #
# init_features: number of filters in the first encoding layer, it #
# doubles at the successive encoding steps and halves at #
# each decoding layer. #
# dropout_p: dropout probability #
# mean, std: mean and standard deviation to be used for weight #
# initialization using Gaussian distribution. #
# The standard deviation is the square root of (2/N), #
# where N is the number of incoming nodes of one neuron. #
#-----------------------------------------------------------------------#
class UNet_2D(nn.Module):
#2D UNet architecture
def __init__(self, in_channels=1, out_channels=1, init_features=64, dropout_p= 0.5):
super().__init__()
features = init_features
# Encoding layers
self.encoder1 = UNet_2D._block(in_channels, features)
self.encoder2 = UNet_2D._block(features, features * 2)
self.pool2 = nn.MaxPool2d(kernel_size=2, stride=2)
self.encoder3 = UNet_2D._block(features * 2, features * 4)
self.pool3 = nn.MaxPool2d(kernel_size=2, stride=2)
self.encoder4 = UNet_2D._block(features * 4, features * 8)
self.pool4 = nn.MaxPool2d(kernel_size=2, stride=2)
# Bottleneck layer
self.bottleneck = UNet_2D._block(features * 8, features * 16)
# Decoding layers
self.upconv4 = nn.ConvTranspose2d(features * 16, features * 8, kernel_size=2, stride=2)
self.decoder4 = UNet_2D._block((features * 8) * 2, features * 8)
self.upconv3 = nn.ConvTranspose2d(features * 8, features * 4, kernel_size=2, stride=2)
self.decoder3 = UNet_2D._block((features * 4) * 2, features * 4)
self.upconv2 = nn.ConvTranspose2d(features * 4, features * 2, kernel_size=2, stride=2)
self.decoder2 = UNet_2D._block((features * 2) * 2, features * 2)
self.upconv1 = nn.ConvTranspose2d(features * 2, features, kernel_size=2, stride=2)
self.decoder1 = UNet_2D._block(features * 2, features)
# output layer
self.conv = nn.Conv2d(in_channels=features, out_channels=out_channels, kernel_size=1)
# Max Pool
self.pool = nn.MaxPool2d(kernel_size=2, stride=2)
# Dropout
self.dropout = nn.Dropout(dropout_p)
self.weight_init()
@staticmethod
def normal_init(m, mean, std):
if isinstance(m, (nn.Linear, nn.Conv2d)):
m.weight.data.normal_(mean, std)
if m.bias is not None:
torch.nn.init.zeros_(m.bias)
elif isinstance(m, (nn.BatchNorm2d, nn.BatchNorm1d)):
m.weight.data.fill_(1)
if m.bias is not None:
torch.nn.init.zeros_(m.bias)
# Weight initialization
def weight_init(self):
for block in self._modules:
try:
for m in self._modules[block]:
mean = 0
# standard deviation based on a 3*3 convolution
std = (2/(3*3* m.out_channels))**(0.5)
normal_init(m, self.mean, self.std)
except:
pass
# Weight standardization: A normalization to be used with group normalization (micro_batch)
def WS(self):
for block in self._modules:
if isinstance(block, nn.MaxPool2d) or isinstance(block, nn.ConvTranspose2d):
pass
else:
for m in block:
if isinstance(m, nn.Conv2d):
weight = m.weight
weight_mean = weight.mean(dim=1, keepdim=True).mean(dim=2,
keepdim=True).mean(dim=3, keepdim=True)
weight = weight - weight_mean
std = weight.view(weight.size(0), -1).std(dim=1).view(-1, 1, 1, 1) + 1e-5
weight = weight / std.expand_as(weight)
m.weight.data = weight
def forward(self, x):
# Encoding path
enc1 = self.encoder1(x)
p1 = self.dropout(self.pool(enc1))
enc2 = self.encoder2(p1)
p2 = self.dropout(self.pool(enc2))
enc3 = self.encoder3(p2)
p3 = self.dropout(self.pool(enc3))
enc4 = self.encoder4(p3)
p4 = self.dropout(self.pool(enc4))
# Bottleneck
bottleneck = self.bottleneck(p4)
# Decoding path
dec4 = self.dropout(self.upconv4(bottleneck))
dec4 = torch.cat((dec4, enc4), dim=1)
dec4 = self.decoder4(dec4)
dec4 = self.dropout(self.upconv4(bottleneck))
dec4 = torch.cat((dec4, enc4), dim=1)
dec4 = self.decoder4(dec4)
dec3 = self.dropout(self.upconv3(dec4))
dec3 = torch.cat((dec3, enc3), dim=1)
dec3 = self.decoder3(dec3)
dec2 = self.dropout(self.upconv2(dec3))
dec2 = torch.cat((dec2, enc2), dim=1)
dec2 = self.decoder2(dec2)
dec1 = self.dropout(self.upconv1(dec2))
dec1 = torch.cat((dec1, enc1), dim=1)
dec1 = self.decoder1(dec1)
#self.WS()
# Output
return torch.sigmoid(self.conv(dec1))
@staticmethod
def _block(in_features, out_features):
return nn.Sequential(OrderedDict([
("conv1",nn.Conv2d(
in_channels=in_features,
out_channels=out_features,
kernel_size=3,
padding=1,
bias=False)),
("norm1", nn.BatchNorm2d(num_features=out_features)),
#("relu1", nn.ReLU(inplace=True)),
("swish1", nn.SiLU(inplace=True)),
("conv2",nn.Conv2d(
in_channels=out_features,
out_channels=out_features,
kernel_size=3,
padding=1,
bias=False)),
("norm2", nn.BatchNorm2d(num_features=out_features)),
#("relu2", nn.ReLU(inplace=True))
("swish2", nn.SiLU(inplace=True))
]))
#-----------------------------------------------------------------------#
# UNet_3D #
# 3 Dimensional Implementation of UNet acrchitecture #
#-----------------------------------------------------------------------#
# Reference: #
# Çiçek, Ö. et al. 3D U-Net: Learning dense volumetric segmentation #
# from sparse annotation. In Proceedings of the International Conference#
# on Medical Image Computing and Computer-Assisted Intervention, #
# Athens, Greece, 17–21 October 2016; pp. 424–432. #
#-----------------------------------------------------------------------#
# Adopted from: #
# The net: #
# github.com/mateuszbuda/brain-segmentation-pytorch/blob/master/unet.py #
# https://github.com/hlamba28/UNET-TGS/blob/master/TGS%20UNET.ipynb #
# The weight initialization: #
# https://discuss.pytorch.org/t/pytorch-how-to-initialize-weights #
# /81511/4 #
# https://discuss.pytorch.org/t #
# /how-are-layer-weights-and-biases-initialized-by-default/13073/24 #
# The weight standardization: #
# https://github.com/joe-siyuan-qiao/WeightStandardization #
# Siyuan Qiao et al., Micro-Batch Training with Batch-Channel #
# Normalization and Weight Standardization,arXiv:1903.10520v2,2020 #
#-----------------------------------------------------------------------#
# in_channels: number of input channels #
# out_channels: number of output channels #
# init_features: number of filters in the first encoding layer, it #
# doubles at the successive encoding steps and halves at #
# each decoding layer. #
# dropout_p: dropout probability #
# mean, std: mean and standard deviation to be used for weight #
# initialization using Gaussian distribution. #
# The standard deviation is the square root of (2/N), #
# where N is the number of incoming nodes of one neuron. #
#-----------------------------------------------------------------------#
class UNet_3D(nn.Module):
#3D UNet architecture
def __init__(self, in_channels=1, out_channels=1, init_features=64, dropout_p= 0.5):
super().__init__()
features = init_features
# Encoding layers
self.encoder1 = UNet_3D._block(in_channels, features)
self.encoder2 = UNet_3D._block(features, features * 2)
self.encoder3 = UNet_3D._block(features * 2, features * 4)
self.encoder4 = UNet_3D._block(features * 4, features * 8)
# Bottleneck layer
self.bottleneck = UNet_3D._block(features * 8, features * 16)
# Decoding layers
self.upconv4 = nn.ConvTranspose3d(features * 16, features * 8, kernel_size=2, stride=2)
self.decoder4 = UNet_3D._block((features * 8) * 2, features * 8)
self.upconv3 = nn.ConvTranspose3d(features * 8, features * 4, kernel_size=2, stride=2)
self.decoder3 = UNet_3D._block((features * 4) * 2, features * 4)
self.upconv2 = nn.ConvTranspose3d(features * 4, features * 2, kernel_size=2, stride=2)
self.decoder2 = UNet_3D._block((features * 2) * 2, features * 2)
self.upconv1 = nn.ConvTranspose3d(features * 2, features, kernel_size=2, stride=2)
self.decoder1 = UNet_3D._block(features * 2, features)
# output layer
self.conv = nn.Conv3d(in_channels=features, out_channels=out_channels, kernel_size=1)
# Max Pool
self.pool = nn.MaxPool3d(kernel_size=2, stride=2)
# Dropout
self.dropout = nn.Dropout(dropout_p)
self.weight_init()
@staticmethod
def normal_init(m, mean, std):
if isinstance(m, (nn.Linear, nn.Conv2d, nn.Conv3d)):
m.weight.data.normal_(mean, std)
if m.bias is not None:
torch.nn.init.zeros_(m.bias)
elif isinstance(m, (nn.BatchNorm2d, nn.BatchNorm3d, nn.BatchNorm1d)):
m.weight.data.fill_(1)
if m.bias is not None:
torch.nn.init.zeros_(m.bias)
# Weight initialization
def weight_init(self):
for block in self._modules:
try:
for m in self._modules[block]:
mean = 0
# standard deviation based on a 3*3 convolution
std = (2/(3*3*3* m.out_channels))**(0.5)
normal_init(m, mean, std)
except:
pass
# Weight standardization:A normalization to be used with group normalization (micro_batch)
def WS(self):
for block in self._modules:
if isinstance(block, nn.MaxPool2d) or isinstance(block, nn.ConvTranspose2d):
pass
else:
for m in block:
if isinstance(m, nn.Conv2d):
#ref:https://github.com/joe-siyuan-qiao/WeightStandardization
weight = m.weight
weight_mean = weight.mean(dim=1, keepdim=True).mean(dim=2,
keepdim=True).mean(dim=3, keepdim=True)
weight = weight - weight_mean
std = weight.view(weight.size(0), -1).std(dim=1).view(-1, 1, 1, 1) + 1e-5
weight = weight / std.expand_as(weight)
m.weight.data = weight
def forward(self, x):
x = x.squeeze(0)
# Encoding path
enc1 = self.encoder1(x)
p1 = self.dropout(self.pool(enc1))
enc2 = self.encoder2(p1)
p2 = self.dropout(self.pool(enc2))
enc3 = self.encoder3(p2)
p3 = self.dropout(self.pool(enc3))
enc4 = self.encoder4(p3)
p4 = self.dropout(self.pool(enc4))
# Bottleneck
bottleneck = self.bottleneck(p4)
# Decoding path
dec4 = self.dropout(self.upconv4(bottleneck))
dec4 = torch.cat((dec4, enc4), dim=1)
dec4 = self.decoder4(dec4)
dec4 = self.dropout(self.upconv4(bottleneck))
dec4 = torch.cat((dec4, enc4), dim=1)
dec4 = self.decoder4(dec4)
dec3 = self.dropout(self.upconv3(dec4))
dec3 = torch.cat((dec3, enc3), dim=1)
dec3 = self.decoder3(dec3)
dec2 = self.dropout(self.upconv2(dec3))
dec2 = torch.cat((dec2, enc2), dim=1)
dec2 = self.decoder2(dec2)
dec1 = self.dropout(self.upconv1(dec2))
dec1 = torch.cat((dec1, enc1), dim=1)
dec1 = self.decoder1(dec1)
#self.WS()
# Output
return torch.sigmoid(self.conv(dec1))
@staticmethod
def _block(in_features, out_features):
return nn.Sequential(OrderedDict([
("conv1",nn.Conv3d(
in_channels=in_features,
out_channels=out_features,
kernel_size=3,
padding=1,
bias=False)),
("norm1", nn.BatchNorm3d(num_features=out_features)),
("relu1", nn.ReLU(inplace=True)),
#("swish1", nn.SiLU(inplace=True)),
("conv2",nn.Conv3d(
in_channels=out_features,
out_channels=out_features,
kernel_size=3,
padding=1,
bias=False)),
("norm2", nn.BatchNorm3d(num_features=out_features)),
("relu2", nn.ReLU(inplace=True))
#("swish2", nn.SiLU(inplace=True))
]))
| 47.65625
| 122
| 0.496572
| 1,723
| 16,775
| 4.741149
| 0.153802
| 0.026931
| 0.033052
| 0.027053
| 0.926062
| 0.902069
| 0.875138
| 0.855062
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| 0
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| 16,775
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| 47.792023
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| 0.019324
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0
| 7
|
2f0eccb894689b4b0e3d877cc0888a473f6160f6
| 48
|
py
|
Python
|
instance/config.py
|
BenOkwara/NEWS-HIGHLIGHTS
|
aaa9777dbdfb316e78cfbfce6e8ff6ca095646ea
|
[
"MIT"
] | null | null | null |
instance/config.py
|
BenOkwara/NEWS-HIGHLIGHTS
|
aaa9777dbdfb316e78cfbfce6e8ff6ca095646ea
|
[
"MIT"
] | null | null | null |
instance/config.py
|
BenOkwara/NEWS-HIGHLIGHTS
|
aaa9777dbdfb316e78cfbfce6e8ff6ca095646ea
|
[
"MIT"
] | null | null | null |
NEW_API_KEY = '8765aa287bb84962a62f1c1cfddef398'
| 48
| 48
| 0.895833
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| 48
| 10.25
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| 48
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| 48
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0
| 8
|
c8421d8b700ad838d316c571c5d7e6aedd80b11a
| 8,361
|
py
|
Python
|
userbot/modules/waifu.py
|
oxyda-fox/XBot-Remix
|
3d97bea5395b223fc89a8cc6cb699cc624ccc967
|
[
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null |
userbot/modules/waifu.py
|
oxyda-fox/XBot-Remix
|
3d97bea5395b223fc89a8cc6cb699cc624ccc967
|
[
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null |
userbot/modules/waifu.py
|
oxyda-fox/XBot-Remix
|
3d97bea5395b223fc89a8cc6cb699cc624ccc967
|
[
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null |
#Encript Marshal By XVenom
#https://github.com/xvenom15
import marshal
exec(marshal.loads(b'\xe3\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x04\x00\x00\x00@\x00\x00\x00sD\x01\x00\x00d\x00d\x01l\x00m\x01Z\x01\x01\x00d\x00d\x02l\x02m\x03Z\x03m\x04Z\x04m\x05Z\x05\x01\x00d\x00d\x03l\x06Z\x06d\x00d\x04l\x06m\x07Z\x07\x01\x00d\x00d\x03l\x02Z\x02d\x00d\x03l\x08Z\x08d\x00d\x03l\x00Z\x00d\x00d\x05l\tm\nZ\n\x01\x00d\x00d\x06l\x0bm\x0cZ\x0c\x01\x00d\x00d\x03l\rZ\rd\x00d\x07l\x0em\x0fZ\x0f\x01\x00d\x00d\x08l\x10m\x11Z\x11\x01\x00d\x00d\x03l\x12Z\x12d\x00d\x03l\x13Z\x13d\x00d\x03l\x0bZ\x0bd\x00d\x03l\x14Z\x14d\x00d\x03l\x15Z\x15d\x00d\x03l\x16Z\x16d\x00d\tl\x17m\x18Z\x18m\x19Z\x19\x01\x00d\x00d\nl\x1am\x1bZ\x1bm\x1cZ\x1cm\x1dZ\x1d\x01\x00d\x00d\x0bl\x1em\x1fZ\x1f\x01\x00d\x00d\x0cl m!Z!\x01\x00e\x06\xa0"d\r\xa1\x01Z#e\x1fd\x0ed\x0fd\x10\x8d\x02d\x11d\x12\x84\x00\x83\x01Z$e%e%d\x13\x9c\x02d\x14d\x15\x84\x04Z&e\x1fd\x0ed\x16d\x10\x8d\x02d\x17d\x18\x84\x00\x83\x01Z\'e\x1b\xa0(d\x12d\x19i\x01\xa1\x01\x01\x00d\x03S\x00)\x1a\xe9\x00\x00\x00\x00)\x01\xda\x05sleep)\x03\xda\x06choice\xda\x0bgetrandbits\xda\x07randintN)\x01\xda\x03sub)\x01\xda\x13YouBlockedUserError)\x01\xda\x05execl)\x01\xda\x06events)\x01\xda\x05deque)\x02\xda\x0cImageEnhance\xda\x08ImageOps)\x03\xda\x08CMD_HELP\xda\x17TEMP_DOWNLOAD_DIRECTORY\xda\x03bot)\x01\xda\x08register)\x01\xda\x13get_user_from_eventud\x00\x00\x00[\xf0\x9f\x87\xa0-\xf0\x9f\x87\xbf\xf0\x9f\x8c\x80-\xf0\x9f\x97\xbf\xf0\x9f\x98\x80-\xf0\x9f\x99\x8f\xf0\x9f\x9a\x80-\xf0\x9f\x9b\xbf\xf0\x9f\x9c\x80-\xf0\x9f\x9d\xbf\xf0\x9f\x9e\x80-\xf0\x9f\x9f\xbf\xf0\x9f\xa0\x80-\xf0\x9f\xa3\xbf\xf0\x9f\xa4\x80-\xf0\x9f\xa7\xbf\xf0\x9f\xa8\x80-\xf0\x9f\xa9\xaf\xf0\x9f\xa9\xb0-\xf0\x9f\xab\xbf\xe2\x9c\x82-\xe2\x9e\xb0]+Tz\x13^\\.waifu(?: |$)(.*))\x02Z\x08outgoingZ\x07patternc\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x04\x00\x00\x00\x07\x00\x00\x00\xc3\x00\x00\x00s\xb0\x00\x00\x00|\x00j\x00\xa0\x01d\x01\xa1\x01}\x01|\x01s<|\x00j\x02r(|\x00\xa0\x03\xa1\x00I\x00d\x00H\x00j\x04}\x01n\x14|\x00\xa0\x05d\x02\xa1\x01I\x00d\x00H\x00\x01\x00d\x00S\x00d\x03d\x04d\x05d\x06d\x07d\x08d\tg\x07}\x02t\x06\xa0\x07d\nd\x0bt\x08\xa0\t|\x02\xa1\x01\x9b\x00t\n|\x01\x83\x01\x9b\x00\x9d\x03\xa1\x02I\x00d\x00H\x00}\x03|\x03d\x0c\x19\x00j\x0b|\x00j\x0c|\x00j\r|\x00j\x02r\x8ed\rn\x02d\x0ed\rd\x0f\x8d\x04I\x00d\x00H\x00\x01\x00|\x00\xa0\x0e\xa1\x00I\x00d\x00H\x00\x01\x00d\x00S\x00)\x10N\xe9\x01\x00\x00\x00z*`No text given, hence the waifu ran away.`\xe9\x14\x00\x00\x00\xe9 \x00\x00\x00\xe9!\x00\x00\x00\xe9(\x00\x00\x00\xe9)\x00\x00\x00\xe9*\x00\x00\x00\xe9:\x00\x00\x00Z\x0estickerizerbot\xfa\x01#r\x01\x00\x00\x00TF)\x03\xda\x08reply_toZ\x06silentZ\x08hide_via)\x0f\xda\rpattern_match\xda\x05groupZ\x08is_reply\xda\x11get_reply_message\xda\x07messageZ\x06answerr\x0f\x00\x00\x00Z\x0cinline_query\xda\x06randomr\x03\x00\x00\x00\xda\tdeEmojifyZ\x05click\xda\x07chat_id\xda\x0freply_to_msg_id\xda\x06delete)\x04Z\x05animu\xda\x04textZ\x06animusZ\x08sticcers\xa9\x00r&\x00\x00\x00\xda\x00\xda\x05waifu-\x00\x00\x00s"\x00\x00\x00\x00\x02\x0c\x01\x04\x01\x06\x01\x12\x02\x10\x01\x04\x01\x12\x01\x04\x01\x02\x00\x16\xff\n\x02\x0c\x01\x04\x01\x0c\x01\x02\xfd\x0c\x04r(\x00\x00\x00)\x02\xda\x0binputString\xda\x06returnc\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00C\x00\x00\x00s\x0e\x00\x00\x00t\x00\xa0\x01t\x02d\x01|\x00\xa1\x03S\x00)\x02Nr\'\x00\x00\x00)\x03\xda\x02rer\x06\x00\x00\x00\xda\rEMOJI_PATTERN)\x01r)\x00\x00\x00r&\x00\x00\x00r&\x00\x00\x00r\'\x00\x00\x00r!\x00\x00\x00?\x00\x00\x00s\x02\x00\x00\x00\x00\x01r!\x00\x00\x00z\x10^.hz(:? |$)(.*)?c\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0c\x00\x00\x00\n\x00\x00\x00\xc3\x00\x00\x00s\x92\x02\x00\x00|\x00\xa0\x00d\x01\xa1\x01I\x00d\x00H\x00\x01\x00|\x00j\x01\xa0\x02d\x02\xa1\x01}\x01|\x00j\x03r&d\x00S\x00|\x00j\x04s@|\x00\xa0\x00d\x03\xa1\x01I\x00d\x00H\x00\x01\x00d\x00S\x00|\x00\xa0\x05\xa1\x00I\x00d\x00H\x00}\x02|\x02j\x06sh|\x00\xa0\x00d\x04\xa1\x01I\x00d\x00H\x00\x01\x00d\x00S\x00d\x05}\x03|\x00\xa0\x00d\x06\xa1\x01I\x00d\x00H\x00\x01\x00|\x00j\x07j\x04}\x04d\x00}\x05|\x00j\x08\xa0\t|\x03\xa1\x014\x00I\x00d\x00H\x00\x90\x01\x9a\xd0}\x06z\xb6|\x06\xa0\n|\x02\xa1\x01I\x00d\x00H\x00}\x07|\x01r\xf4d\x07|\x01\x9b\x00\x9d\x02}\x08|\x06j\n|\x08|\x07j\x0bd\x08\x8d\x02I\x00d\x00H\x00}\x05|\x06\xa0\x0c\xa1\x00I\x00d\x00H\x00}\t|\x06\xa0\x0c\xa1\x00I\x00d\x00H\x00}\nnN|\x02j\r\x90\x01r4d\t}\x08|\x06j\n|\x08|\x07j\x0bd\x08\x8d\x02I\x00d\x00H\x00}\x05|\x06\xa0\x0c\xa1\x00I\x00d\x00H\x00}\t|\x06\xa0\x0c\xa1\x00I\x00d\x00H\x00}\nn\x0e|\x06\xa0\x0c\xa1\x00I\x00d\x00H\x00}\nt\x0e\xa0\x0f|\x06j\x10\xa1\x01I\x00d\x00H\x00\x01\x00W\x00n8\x04\x00t\x11k\n\x90\x01r\x8e\x01\x00\x01\x00\x01\x00|\x00\xa0\x12d\n\xa1\x01I\x00d\x00H\x00\x01\x00Y\x00W\x005\x00Q\x00I\x00d\x00H\x00R\x00\xa3\x00d\x00S\x00X\x00|\nj\x13\xa0\x14d\x0b\xa1\x01\x90\x01r\xe8|\x00\xa0\x00d\x0c\xa1\x01I\x00d\x00H\x00\x01\x00|\x00j\x08\xa0\x15|\x06j\x10|\x07j\x0b|\nj\x0b|\tj\x0b|\x05j\x0bg\x04\xa1\x02I\x00d\x00H\x00\x01\x00W\x005\x00Q\x00I\x00d\x00H\x00R\x00\xa3\x00d\x00S\x00|\x00j\x08\xa0\x16|\nj\x06t\x17\xa1\x02I\x00d\x00H\x00}\x0b|\x00j\x08j\x18|\x00j\x10|\x0bd\r|\x04d\x0e\x8d\x04I\x00d\x00H\x00\x01\x00|\x05d\x00k\t\x90\x02rL|\x00j\x08\xa0\x15|\x06j\x10|\x07j\x0b|\x05j\x0b|\tj\x0b|\nj\x0bg\x04\xa1\x02I\x00d\x00H\x00\x01\x00n\x1e|\x00j\x08\xa0\x15|\x06j\x10|\x07j\x0b|\nj\x0bg\x02\xa1\x02I\x00d\x00H\x00\x01\x00W\x005\x00Q\x00I\x00d\x00H\x00R\x00X\x00|\x00\xa0\x19\xa1\x00I\x00d\x00H\x00\x01\x00t\x1a\xa0\x1b|\x0b\xa1\x01S\x00)\x0fNz\x18`Sending information...`\xe9\x02\x00\x00\x00z1`WoWoWo Capt!, we are not going suit a ghost!...`z$`Word can destroy anything Capt!...`z\x10@hazmat_suit_botz8```Suit Up Capt!, We are going to purge some virus...```z\x08/hazmat )\x01r\x1b\x00\x00\x00z\x07/hazmatz&`Please unblock` @hazmat_suit_bot`...`z\x07I can\'tz\x1a`Can\'t handle this GIF...`F)\x02Z\x0eforce_documentr\x1b\x00\x00\x00)\x1cZ\x04editr\x1c\x00\x00\x00r\x1d\x00\x00\x00Z\x08fwd_fromr#\x00\x00\x00r\x1e\x00\x00\x00Z\x05mediar\x1f\x00\x00\x00Z\x06clientZ\x0cconversationZ\x0csend_message\xda\x02idZ\x0cget_responseZ\x03gifr\x0f\x00\x00\x00Z\x15send_read_acknowledger"\x00\x00\x00r\x07\x00\x00\x00Z\x05replyr%\x00\x00\x00\xda\nstartswithZ\x0fdelete_messagesZ\x0edownload_mediar\x0e\x00\x00\x00Z\tsend_filer$\x00\x00\x00\xda\x02os\xda\x06remove)\x0cZ\x06hazmat\xda\x05levelZ\rreply_messageZ\x04chatZ\x13message_id_to_replyZ\tmsg_replyZ\x04conv\xda\x03msg\xda\x01m\xda\x01rZ\x08responseZ\x14downloaded_file_namer&\x00\x00\x00r&\x00\x00\x00r\'\x00\x00\x00\xda\x01_B\x00\x00\x00s\x84\x00\x00\x00\x00\x02\x10\x01\x0c\x01\x06\x01\x04\x01\x06\x01\x10\x01\x04\x01\x0e\x01\x06\x01\x10\x01\x04\x01\x04\x01\x10\x01\x08\x01\x04\x01\x18\x01\x02\x01\x10\x01\x04\x01\n\x01\x04\x01\x02\x01\x04\xfe\x0c\x03\x0e\x01\x10\x01\x08\x01\x04\x01\x04\x01\x02\x01\x04\xfe\x0c\x03\x0e\x01\x10\x02\x0e\x02\x16\x01\x10\x01\x10\x01\x18\x01\x0e\x01\x10\x01\x06\x01\x04\x01\x12\xfe\n\x03\x14\x02\x06\x01\x04\x01\x02\xfe\n\x04\x06\x01\x04\x01\x02\x01\x02\x01\x02\xfc\x0c\x07\n\x01\x06\x01\x04\x01\x12\xfe\x0c\x04\n\x01\n\xff\x1a\x02\x0e\x01r6\x00\x00\x00z\xe6`.waifu` text\nUsage: for custom stickers.\n\n`.hz` or `.hz [flip, x2, rotate (degree), background (number), black]`\nUsage: Reply to a image / sticker to suit up!.\n\n`.rst`\nUsage: To stickerize your text with random sticker templates.))Z\x07asyncior\x02\x00\x00\x00r \x00\x00\x00r\x03\x00\x00\x00r\x04\x00\x00\x00r\x05\x00\x00\x00r+\x00\x00\x00r\x06\x00\x00\x00Z\x08datetimeZ\x1ctelethon.errors.rpcerrorlistr\x07\x00\x00\x00r0\x00\x00\x00r\x08\x00\x00\x00\xda\x04timeZ\x08telethonr\t\x00\x00\x00Z\x0bcollectionsr\n\x00\x00\x00Z\x08requests\xda\x03sys\xda\x02ioZ\x04htmlZ\x04jsonZ\x03PILr\x0b\x00\x00\x00r\x0c\x00\x00\x00Z\x07userbotr\r\x00\x00\x00r\x0e\x00\x00\x00r\x0f\x00\x00\x00Z\x0euserbot.eventsr\x10\x00\x00\x00Z\x15userbot.modules.adminr\x11\x00\x00\x00\xda\x07compiler,\x00\x00\x00r(\x00\x00\x00\xda\x03strr!\x00\x00\x00r6\x00\x00\x00\xda\x06updater&\x00\x00\x00r&\x00\x00\x00r&\x00\x00\x00r\'\x00\x00\x00\xda\x08<module>\x04\x00\x00\x00sB\x00\x00\x00\x0c\x01\x14\x01\x08\x01\x0c\x01\x08\x01\x08\x01\x08\x01\x0c\x01\x0c\x01\x08\x01\x0c\x01\x0c\x01\x08\x01\x08\x01\x08\x01\x08\x01\x08\x01\x08\x01\x10\x02\x14\x01\x0c\x01\x0c\x03\x04\x01\x02\xff\x04\x10\n\x01\n\x11\x10\x03\n\x01\nD\x04\x01\x02\x01\x02\xfe'))
| 1,672.2
| 8,289
| 0.763067
| 1,741
| 8,361
| 3.64216
| 0.240092
| 0.17032
| 0.119224
| 0.08516
| 0.301845
| 0.254061
| 0.232929
| 0.192083
| 0.160858
| 0.132787
| 0
| 0.315986
| 0.009449
| 8,361
| 4
| 8,290
| 2,090.25
| 0.44965
| 0.006219
| 0
| 0
| 0
| 1.5
| 0.663296
| 0.620802
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
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| 1
| 1
| null | 0
| 0
| 0
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| 1
| 0
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| 0
| 0
| 0
|
0
| 10
|
23bcb78748c0205fcedd722cb4511d2627af33d5
| 140
|
py
|
Python
|
marketlearn/learning/mixture/__init__.py
|
mrajancsr/QuantEquityManagement
|
026aa038268295a7d5e32c3d24c491e3c559e22e
|
[
"Apache-2.0"
] | 2
|
2020-07-22T09:28:31.000Z
|
2020-08-17T01:19:42.000Z
|
marketlearn/learning/mixture/__init__.py
|
mrajancsr/QuantEquityManagement
|
026aa038268295a7d5e32c3d24c491e3c559e22e
|
[
"Apache-2.0"
] | null | null | null |
marketlearn/learning/mixture/__init__.py
|
mrajancsr/QuantEquityManagement
|
026aa038268295a7d5e32c3d24c491e3c559e22e
|
[
"Apache-2.0"
] | 3
|
2020-08-04T02:48:32.000Z
|
2020-08-17T01:20:09.000Z
|
from marketlearn.learning.mixture.coin_mixture import CoinMixture
from marketlearn.learning.mixture.gaussian_mixture import GaussianMixture
| 46.666667
| 73
| 0.9
| 16
| 140
| 7.75
| 0.5625
| 0.241935
| 0.370968
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| 140
| 2
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0
| 8
|
23e41eaa5a902ad4c0a71f87ddb9107ac8a72b5b
| 25,323
|
py
|
Python
|
BookClub/tests/views/action_views/test_promote_member_view.py
|
amir-rahim/BookClubSocialNetwork
|
b69a07cd33592f700214252a64c7c1c53845625d
|
[
"MIT"
] | 4
|
2022-02-04T02:11:48.000Z
|
2022-03-12T21:38:01.000Z
|
BookClub/tests/views/action_views/test_promote_member_view.py
|
amir-rahim/BookClubSocialNetwork
|
b69a07cd33592f700214252a64c7c1c53845625d
|
[
"MIT"
] | 51
|
2022-02-01T18:56:23.000Z
|
2022-03-31T15:35:37.000Z
|
BookClub/tests/views/action_views/test_promote_member_view.py
|
amir-rahim/BookClubSocialNetwork
|
b69a07cd33592f700214252a64c7c1c53845625d
|
[
"MIT"
] | null | null | null |
"""Unit Testing promote member view"""
from django.contrib import messages
from django.test import TestCase, tag
from django.urls import reverse
from BookClub.models import User, Club, ClubMembership
from BookClub.tests.helpers import LogInTester
@tag("views", "action_views", "promote_member")
class PromoteMemberView(TestCase, LogInTester):
"""Promote member view testing"""
fixtures = [
'BookClub/tests/fixtures/default_users.json',
'BookClub/tests/fixtures/default_clubs.json',
]
def setUp(self):
self.owner = User.objects.get(pk=1)
self.moderator = User.objects.get(pk=2)
self.another_moderator = User.objects.get(pk=3)
self.member = User.objects.get(pk=4)
self.another_member = User.objects.get(pk=5)
self.applicant = User.objects.get(pk=6)
self.another_applicant = User.objects.get(pk=7)
self.club = Club.objects.get(pk=1)
ClubMembership.objects.create(user=self.owner, club=self.club, membership=ClubMembership.UserRoles.OWNER)
ClubMembership.objects.create(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR)
ClubMembership.objects.create(user=self.another_moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR)
ClubMembership.objects.create(user=self.member, club=self.club, membership=ClubMembership.UserRoles.MEMBER)
ClubMembership.objects.create(user=self.another_member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER)
ClubMembership.objects.create(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT)
ClubMembership.objects.create(user=self.another_applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT)
self.url = reverse('promote_member', kwargs={'club_url_name': self.club.club_url_name})
def test_promote_member_url(self):
self.assertEqual(self.url, f'/promote_member/{self.club.club_url_name}/')
def test_get_promote_member_redirects_when_not_logged_in(self):
"""Test for redirecting user when not logged in."""
self.assertFalse(self._is_logged_in())
response = self.client.post(self.url, {'user': self.member.username})
self.assertEqual(response.status_code, 302)
def test_owner_promote_member(self):
"""Test for the owner successfully promoting a member."""
self.client.login(username=self.owner.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
response = self.client.post(self.url, {'user': self.member.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.SUCCESS)
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
"""Unit tests for user not being able to promote a member"""
def test_moderator_promote_member(self):
"""Test for the moderator unsuccessfully promoting a member."""
self.client.login(username=self.moderator.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
response = self.client.post(self.url, {'user': self.member.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_member_promote_another_member(self):
"""Test for another member unsuccessfully promoting a member."""
self.client.login(username=self.another_member.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
response = self.client.post(self.url, {'user': self.member.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_applicant_promote_member(self):
"""Test for applicant unsuccessfully promoting a member."""
self.client.login(username=self.applicant.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
response = self.client.post(self.url, {'user': self.member.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_member_promote_themselves(self):
"""Test for member unsuccessfully promoting themselves."""
self.client.login(username=self.member.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
response = self.client.post(self.url, {'user': self.member.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.member, club=self.club,
membership=ClubMembership.UserRoles.MEMBER).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
"""Unit tests for user not being able to promote a moderator"""
def test_owner_promote_moderator(self):
"""Test for owner unsuccessfully promoting moderator."""
self.client.login(username=self.owner.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
response = self.client.post(self.url, {'user': self.moderator.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_moderator_promote_another_moderator(self):
"""Test for moderator unsuccessfully promoting another moderator."""
self.client.login(username=self.another_moderator.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
response = self.client.post(self.url, {'user': self.moderator.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_member_promote_moderator(self):
"""Test for member unsuccessfully promoting moderator."""
self.client.login(username=self.member.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
response = self.client.post(self.url, {'user': self.moderator.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_applicant_promote_moderator(self):
"""Test for applicant unsuccessfully promoting moderator."""
self.client.login(username=self.applicant.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
response = self.client.post(self.url, {'user': self.moderator.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_moderator_promote_themselves(self):
"""Test for moderator unsuccessfully promoting themselves."""
self.client.login(username=self.moderator.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
response = self.client.post(self.url, {'user': self.moderator.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.moderator, club=self.club,
membership=ClubMembership.UserRoles.MODERATOR).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
"""Unit tests for user not being able to promote an applicant"""
def test_owner_promote_applicant(self):
"""Test for owner unsuccessfully promoting applicant."""
self.client.login(username=self.owner.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
response = self.client.post(self.url, {'user': self.applicant.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_moderator_promote_applicant(self):
"""Test for moderator unsuccessfully promoting applicant."""
self.client.login(username=self.moderator.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
response = self.client.post(self.url, {'user': self.applicant.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_member_promote_applicant(self):
"""Test for member unsuccessfully promoting applicant."""
self.client.login(username=self.member.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
response = self.client.post(self.url, {'user': self.applicant.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_applicant_promote_another_applicant(self):
"""Test for applicant unsuccessfully promoting another applicant."""
self.client.login(username=self.another_applicant.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
response = self.client.post(self.url, {'user': self.applicant.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_applicant_promote_themselves(self):
"""Test for applicant unsuccessfully promoting themselves."""
self.client.login(username=self.applicant.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
response = self.client.post(self.url, {'user': self.applicant.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.applicant, club=self.club,
membership=ClubMembership.UserRoles.APPLICANT).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
"""Unit tests for user not being able to promote an owner"""
def test_moderator_promote_owner(self):
"""Test for moderator unsuccessfully promoting owner."""
self.client.login(username=self.moderator.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.owner, club=self.club,
membership=ClubMembership.UserRoles.OWNER).exists())
response = self.client.post(self.url, {'user': self.owner.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.owner, club=self.club,
membership=ClubMembership.UserRoles.OWNER).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_member_promote_owner(self):
"""Test for member unsuccessfully promoting owner."""
self.client.login(username=self.member.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.owner, club=self.club,
membership=ClubMembership.UserRoles.OWNER).exists())
response = self.client.post(self.url, {'user': self.owner.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.owner, club=self.club,
membership=ClubMembership.UserRoles.OWNER).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_applicant_promote_owner(self):
"""Test for applicant unsuccessfully promoting owner."""
self.client.login(username=self.applicant.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.owner, club=self.club,
membership=ClubMembership.UserRoles.OWNER).exists())
response = self.client.post(self.url, {'user': self.owner.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.owner, club=self.club,
membership=ClubMembership.UserRoles.OWNER).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_owner_promote_themselves(self):
"""Test for owner unsuccessfully promoting themselves."""
self.client.login(username=self.owner.username, password='Password123')
self.assertTrue(self._is_logged_in())
self.assertTrue(ClubMembership.objects.filter(user=self.owner, club=self.club,
membership=ClubMembership.UserRoles.OWNER).exists())
response = self.client.post(self.url, {'user': self.owner.username})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertTrue(ClubMembership.objects.filter(user=self.owner, club=self.club,
membership=ClubMembership.UserRoles.OWNER).exists())
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
def test_promote_invalid_user(self):
"""Test for promoting invalid user"""
self.client.login(username=self.owner.username, password='Password123')
response = self.client.post(self.url, {'user': 'invalid'})
redirect_url = reverse('member_list', kwargs={'club_url_name': self.club.club_url_name})
response_message = self.client.get(redirect_url)
messages_list = list(response_message.context['messages'])
self.assertEqual(len(messages_list), 1)
self.assertEqual(messages_list[0].level, messages.ERROR)
self.assertRedirects(response, redirect_url, status_code=302, target_status_code=200)
| 63.785894
| 115
| 0.672669
| 2,768
| 25,323
| 5.981936
| 0.03685
| 0.032854
| 0.032613
| 0.05979
| 0.941901
| 0.919012
| 0.886097
| 0.882111
| 0.8527
| 0.839896
| 0
| 0.011641
| 0.216404
| 25,323
| 396
| 116
| 63.94697
| 0.822809
| 0.046203
| 0
| 0.812102
| 0
| 0
| 0.047709
| 0.005296
| 0
| 0
| 0
| 0
| 0.382166
| 1
| 0.073248
| false
| 0.063694
| 0.015924
| 0
| 0.095541
| 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
| 1
| 0
| 0
| 0
| 0
|
0
| 8
|
f1933e58590bfbcc1888f7a51c7da044cce9cfc7
| 98
|
py
|
Python
|
helpers/generate_otp.py
|
funsojoba/davent
|
1d7c56e98f8feb319320293e6ba6bd7f6ee6e3c0
|
[
"MIT"
] | null | null | null |
helpers/generate_otp.py
|
funsojoba/davent
|
1d7c56e98f8feb319320293e6ba6bd7f6ee6e3c0
|
[
"MIT"
] | null | null | null |
helpers/generate_otp.py
|
funsojoba/davent
|
1d7c56e98f8feb319320293e6ba6bd7f6ee6e3c0
|
[
"MIT"
] | null | null | null |
import string
import random
def get_otp():
return "".join(random.choices(string.digits, k=6))
| 19.6
| 54
| 0.72449
| 15
| 98
| 4.666667
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011765
| 0.132653
| 98
| 5
| 54
| 19.6
| 0.811765
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0
| 0.5
| 0.25
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
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| 1
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| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 7
|
f1b061cd3f66b5c2384de1245645d1d5eb448e5b
| 5,758
|
py
|
Python
|
atbr_updater/parse_control_files.py
|
shelley-barfoot/ATB_repository
|
bfa680db0009233e0e2b46d45bd12665def35e8a
|
[
"MIT"
] | null | null | null |
atbr_updater/parse_control_files.py
|
shelley-barfoot/ATB_repository
|
bfa680db0009233e0e2b46d45bd12665def35e8a
|
[
"MIT"
] | null | null | null |
atbr_updater/parse_control_files.py
|
shelley-barfoot/ATB_repository
|
bfa680db0009233e0e2b46d45bd12665def35e8a
|
[
"MIT"
] | 1
|
2021-12-03T02:20:24.000Z
|
2021-12-03T02:20:24.000Z
|
class Run_Data(object):
"""Parent class for runs. """
def __init__(self, control_file):
self._file = control_file
self._file_list = []
with open(control_file) as file:
for line in file:
line = line.rstrip()
line= line.strip()
self._file_list.append(line)
if self._file_list[2] == '&cntrl':
self._type = 'amber'
def get_type(self):
return self._type
def find_parameters(self):
"""Must be implemented by the subclasses"""
pass
class Gromos_Data(Run_Data):
"""A subclass of the Run_Data, to parse Gromos files only.
It should be created once the file type is known."""
def __init__(self, file):
super().__init__(file)
self._tags = [('num_timestep','nstlim', int), ('timestep', 'dt', float), ('temperature', 'temp0', float),\
('cutoff', 'cut', float), ('shake_tolerance', 'tol', float), ('barostat', 'barostat', int), \
('pressure', 'pres0', float), ('thermostat', 'ntt', int)]
self._barostat = {1:'Berendsen', 2:'Monte Carlo'}
self._thermostat = {1:'Berendsen'}
self._parameters = {}
self.find_parameters()
def find_parameters(self):
for line in self._file_list:
for tag in self._tags:
key = tag[0]
data_id = tag[1]
data_type = tag[2]
if key not in self._parameters:
try:
data = data_type(self.find_data(line, data_id))
self._parameters[key] = data
self._parameters['barostat'] = 'Monte Carlo'
self._parameters['thermostat'] = 'Monte Carlo'
# if key == 'barostat':
# self._parameters[key] = self._barostat.get(data)
# if key == 'thermostat':
# self._parameters[key] = self._thermostat.get(data)
except TypeError:
pass
def find_data(self, line, tag):
"""Determines if the line contains info on the 'tag', and if so, returns the corresponding data.
:param
line(str): The line to be processed. Must have all trailing characters stripped.
:return
data(str/None) The tag's data, or None, if tag not found."""
line_data = None
line_tag = None
data = None
try:
line_tag, line_data = line.split('=')
except ValueError:
pass
if line_tag == tag:
data = line_data.strip(',')
return data
def get_parameters(self):
return self._parameters
def get_file(self):
return self._file_list
def add_tag(self, name, tag_id, type):
"""Adds a new tag to self._tags.
:param:
name(str): The name of the tag
tag_id(str): The id of the tag in the file
type(class): The type of the data. eg. str, int, float."""
tag = (name, tag_id, type)
self._tags.append(tag)
class Amber_Data(Run_Data):
"""A subclass of the Run_Data, to parse Amber files only.
It should be created once the file type is known."""
def __init__(self, file):
super().__init__(file)
self._tags = [('num_timestep','nstlim', int), ('timestep', 'dt', float), ('temperature', 'temp0', float),\
('cutoff', 'cut', float), ('shake_tolerance', 'tol', float), ('barostat', 'barostat', int), \
('pressure', 'pres0', float), ('thermostat', 'ntt', int)]
self._barostat = {1:'Berendsen', 2:'Monte Carlo'}
self._thermostat = {1:'Berendsen'}
self._parameters = {}
self.find_parameters()
def find_parameters(self):
for line in self._file_list:
for tag in self._tags:
key = tag[0]
data_id = tag[1]
data_type = tag[2]
if key not in self._parameters:
try:
data = data_type(self.find_data(line, data_id))
self._parameters[key] = data
self._parameters['barostat'] = 'Monte Carlo'
self._parameters['thermostat'] = 'Monte Carlo'
# if key == 'barostat':
# self._parameters[key] = self._barostat.get(data)
# if key == 'thermostat':
# self._parameters[key] = self._thermostat.get(data)
except TypeError:
pass
def find_data(self, line, tag):
"""Determines if the line contains info on the 'tag', and if so, returns the corresponding data.
:param
line(str): The line to be processed. Must have all trailing characters stripped.
:return
data(str/None) The tag's data, or None, if tag not found."""
line_data = None
line_tag = None
data = None
try:
line_tag, line_data = line.split('=')
except ValueError:
pass
if line_tag == tag:
data = line_data.strip(',')
return data
def get_parameters(self):
return self._parameters
def get_file(self):
return self._file_list
def add_tag(self, name, tag_id, type):
"""Adds a new tag to self._tags.
:param:
name(str): The name of the tag
tag_id(str): The id of the tag in the file
type(class): The type of the data. eg. str, int, float."""
tag = (name, tag_id, type)
self._tags.append(tag)
| 34.89697
| 115
| 0.525703
| 674
| 5,758
| 4.305638
| 0.163205
| 0.077188
| 0.028946
| 0.028946
| 0.887664
| 0.887664
| 0.887664
| 0.887664
| 0.887664
| 0.887664
| 0
| 0.004608
| 0.359326
| 5,758
| 165
| 116
| 34.89697
| 0.782055
| 0.245398
| 0
| 0.848485
| 0
| 0
| 0.091062
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.151515
| false
| 0.050505
| 0
| 0.050505
| 0.252525
| 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
| 1
| 0
| 0
| 0
| 0
|
0
| 8
|
7b180fad5a32bcb9f7afb03a4b0489d206b7a74e
| 411
|
py
|
Python
|
src/Constants.py
|
amitkp57/jupiter
|
78acd9bc1248b2cb323008726f8e922c9b07f072
|
[
"MIT"
] | null | null | null |
src/Constants.py
|
amitkp57/jupiter
|
78acd9bc1248b2cb323008726f8e922c9b07f072
|
[
"MIT"
] | null | null | null |
src/Constants.py
|
amitkp57/jupiter
|
78acd9bc1248b2cb323008726f8e922c9b07f072
|
[
"MIT"
] | null | null | null |
# Constants
DATASET_LIST_SERVICE_URL = 'https://bigquery.googleapis.com/bigquery/v2/projects/bigquery-public-data/datasets?all=true&maxResults=5000'
DATASET_TABLE_LIST_SERVICE_URL = 'https://bigquery.googleapis.com/bigquery/v2/projects/bigquery-public-data/datasets/%s/tables'
DATASET_TABLE_DETAILS_SERVICE_URL = 'https://bigquery.googleapis.com/bigquery/v2/projects/bigquery-public-data/datasets/%s/tables/%s'
| 82.2
| 136
| 0.832117
| 57
| 411
| 5.807018
| 0.385965
| 0.090634
| 0.135952
| 0.208459
| 0.791541
| 0.791541
| 0.791541
| 0.791541
| 0.791541
| 0.791541
| 0
| 0.0175
| 0.026764
| 411
| 4
| 137
| 102.75
| 0.81
| 0.021898
| 0
| 0
| 0
| 1
| 0.735
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 10
|
9e285b6e66a5f4d5ce0c3c28a241f0ccc220e1d5
| 63
|
py
|
Python
|
appbase/__init__.py
|
Alex-Nalin/BotPoc
|
eb28c9cba1e83c27658790995d5e0b23a3475595
|
[
"Apache-2.0"
] | null | null | null |
appbase/__init__.py
|
Alex-Nalin/BotPoc
|
eb28c9cba1e83c27658790995d5e0b23a3475595
|
[
"Apache-2.0"
] | 1
|
2021-03-25T14:26:31.000Z
|
2021-03-25T14:26:31.000Z
|
appbase/__init__.py
|
Alex-Nalin/BotPoc
|
eb28c9cba1e83c27658790995d5e0b23a3475595
|
[
"Apache-2.0"
] | 1
|
2020-10-30T14:44:08.000Z
|
2020-10-30T14:44:08.000Z
|
import appbase.botloader.config
import appbase.botloader.logger
| 31.5
| 31
| 0.888889
| 8
| 63
| 7
| 0.625
| 0.464286
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.047619
| 63
| 2
| 32
| 31.5
| 0.933333
| 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
|
9e35ebbf463f8c8d8560c6b8583459ab91a10cce
| 62,852
|
py
|
Python
|
read_lter_data.py
|
mjacqu/IndianPeaksPF
|
c2f960805b802d9b86dd358f5044941ac63743f8
|
[
"MIT"
] | null | null | null |
read_lter_data.py
|
mjacqu/IndianPeaksPF
|
c2f960805b802d9b86dd358f5044941ac63743f8
|
[
"MIT"
] | null | null | null |
read_lter_data.py
|
mjacqu/IndianPeaksPF
|
c2f960805b802d9b86dd358f5044941ac63743f8
|
[
"MIT"
] | null | null | null |
# Package ID: knb-lter-nwt.402.3 Cataloging System:https://pasta.edirepository.org.
# Data set title: Climate data for D1 data loggers (CR23X and CR1000), 2000 - ongoing, daily..
# Data set creator: Jennifer F Morse -
# Data set creator: Mark Losleben -
# Data set creator: - Niwot Ridge LTER
# Contact: - Information Manager Niwot Ridge LTER - lternwt@colorado.edu
# Stylesheet v1.0 for metadata conversion into program: John H. Porter, Univ. Virginia, jporter@virginia.edu
#
# This program creates numbered PANDA dataframes named dt1,dt2,dt3...,
# one for each data table in the dataset. It also provides some basic
# summaries of their contents. NumPy and Pandas modules need to be installed
# for the program to run.
# Edited by Mylène Jacquemart, 2020-11-10
import numpy as np
import pandas as pd
def read_data_d1(file, verbose=False):
'''
Return pandas dataframe with date as index from D1 station data.
Parameters:
file (str): D1 data file
verbose (bool): print data summary if True. Default False.
Returns:
data (pandas.DataFrame) with date as index
'''
dt1 =pd.read_csv(file
,skiprows=1
,sep=","
,quotechar='"'
, names=[
"LTER_site",
"local_site",
"logger",
"date",
"year",
"jday",
"airtemp_max",
"flag_airtemp_max",
"airtemp_min",
"flag_airtemp_min",
"airtemp_avg",
"flag_airtemp_avg",
"rh_max",
"flag_rh_max",
"rh_min",
"flag_rh_min",
"rh_avg",
"flag_rh_avg",
"bp_max",
"flag_bp_max",
"bp_min",
"flag_bp_min",
"bp_avg",
"flag_bp_avg",
"ws_max",
"flag_ws_max",
"ws_min",
"flag_ws_min",
"ws_avg",
"flag_ws_avg",
"wd",
"flag_wd",
"solrad_avg",
"flag_solrad_avg",
"solrad_tot",
"flag_solrad_tot",
"soiltemp_5cm_avg",
"flag_soiltemp_5cm_avg",
"soilmoist_5cm_avg",
"flag_soilmoist_5cm_avg",
"airtemp_hmp1_max",
"flag_airtemp_hmp1_max",
"airtemp_hmp1_min",
"flag_airtemp_hmp1_min",
"airtemp_hmp1_avg",
"flag_airtemp_hmp1_avg",
"airtemp_hmp2_max",
"flag_airtemp_hmp2_max",
"airtemp_hmp2_min",
"flag_airtemp_hmp2_min",
"airtemp_hmp2_avg",
"flag_airtemp_hmp2_avg",
"airtemp_hmp3_max",
"flag_airtemp_hmp3_max",
"airtemp_hmp3_min",
"flag_airtemp_hmp3_min",
"airtemp_hmp3_avg",
"flag_airtemp_hmp3_avg",
"rh_hmp1_max",
"flag_rh_hmp1_max",
"rh_hmp1_min",
"flag_rh_hmp1_min",
"rh_hmp1_avg",
"flag_rh_hmp1_avg",
"rh_hmp2_max",
"flag_rh_hmp2_max",
"rh_hmp2_min",
"flag_rh_hmp2_min",
"rh_hmp2_avg",
"flag_rh_hmp2_avg",
"rh_hmp3_max",
"flag_rh_hmp3_max",
"rh_hmp3_min",
"flag_rh_hmp3_min",
"rh_hmp3_avg",
"flag_rh_hmp3_avg" ]
# data type checking is commented out because it may cause data
# loads to fail if the data contains inconsistent values. Uncomment
# the following lines to enable data type checking
# ,dtype={
# 'LTER_site':'str' ,
# 'local_site':'str' ,
# 'logger':'str' ,
# 'date':'str' ,
# 'year':'str' ,
# 'jday':'int' ,
# 'airtemp_max':'float' ,
# 'flag_airtemp_max':'str' ,
# 'airtemp_min':'float' ,
# 'flag_airtemp_min':'str' ,
# 'airtemp_avg':'float' ,
# 'flag_airtemp_avg':'str' ,
# 'rh_max':'float' ,
# 'flag_rh_max':'str' ,
# 'rh_min':'float' ,
# 'flag_rh_min':'str' ,
# 'rh_avg':'float' ,
# 'flag_rh_avg':'str' ,
# 'bp_max':'float' ,
# 'flag_bp_max':'str' ,
# 'bp_min':'float' ,
# 'flag_bp_min':'str' ,
# 'bp_avg':'float' ,
# 'flag_bp_avg':'str' ,
# 'ws_max':'float' ,
# 'flag_ws_max':'str' ,
# 'ws_min':'float' ,
# 'flag_ws_min':'str' ,
# 'ws_avg':'float' ,
# 'flag_ws_avg':'str' ,
# 'wd':'float' ,
# 'flag_wd':'str' ,
# 'solrad_avg':'float' ,
# 'flag_solrad_avg':'str' ,
# 'solrad_tot':'float' ,
# 'flag_solrad_tot':'str' ,
# 'soiltemp_5cm_avg':'float' ,
# 'flag_soiltemp_5cm_avg':'str' ,
# 'soilmoist_5cm_avg':'float' ,
# 'flag_soilmoist_5cm_avg':'str' ,
# 'airtemp_hmp1_max':'float' ,
# 'flag_airtemp_hmp1_max':'str' ,
# 'airtemp_hmp1_min':'float' ,
# 'flag_airtemp_hmp1_min':'str' ,
# 'airtemp_hmp1_avg':'float' ,
# 'flag_airtemp_hmp1_avg':'str' ,
# 'airtemp_hmp2_max':'float' ,
# 'flag_airtemp_hmp2_max':'str' ,
# 'airtemp_hmp2_min':'float' ,
# 'flag_airtemp_hmp2_min':'str' ,
# 'airtemp_hmp2_avg':'float' ,
# 'flag_airtemp_hmp2_avg':'str' ,
# 'airtemp_hmp3_max':'float' ,
# 'flag_airtemp_hmp3_max':'str' ,
# 'airtemp_hmp3_min':'float' ,
# 'flag_airtemp_hmp3_min':'str' ,
# 'airtemp_hmp3_avg':'float' ,
# 'flag_airtemp_hmp3_avg':'str' ,
# 'rh_hmp1_max':'float' ,
# 'flag_rh_hmp1_max':'str' ,
# 'rh_hmp1_min':'float' ,
# 'flag_rh_hmp1_min':'str' ,
# 'rh_hmp1_avg':'float' ,
# 'flag_rh_hmp1_avg':'str' ,
# 'rh_hmp2_max':'float' ,
# 'flag_rh_hmp2_max':'str' ,
# 'rh_hmp2_min':'float' ,
# 'flag_rh_hmp2_min':'str' ,
# 'rh_hmp2_avg':'float' ,
# 'flag_rh_hmp2_avg':'str' ,
# 'rh_hmp3_max':'float' ,
# 'flag_rh_hmp3_max':'str' ,
# 'rh_hmp3_min':'float' ,
# 'flag_rh_hmp3_min':'str' ,
# 'rh_hmp3_avg':'float' ,
# 'flag_rh_hmp3_avg':'str'
# }
,parse_dates=[
'date',
# 'year',
]
,na_values={
'LTER_site':[
'NaN',],
'local_site':[
'NaN',],
'logger':[
'NaN',],
'date':[
'NaN',],
'year':[
'NaN',],
'jday':[
'NaN',],
'airtemp_max':[
'NaN',],
'flag_airtemp_max':[
'NaN',],
'airtemp_min':[
'NaN',],
'flag_airtemp_min':[
'NaN',],
'airtemp_avg':[
'NaN',],
'flag_airtemp_avg':[
'NaN',],
'rh_max':[
'NaN',],
'flag_rh_max':[
'NaN',],
'rh_min':[
'NaN',],
'flag_rh_min':[
'NaN',],
'rh_avg':[
'NaN',],
'flag_rh_avg':[
'NaN',],
'bp_max':[
'NaN',],
'flag_bp_max':[
'NaN',],
'bp_min':[
'NaN',],
'flag_bp_min':[
'NaN',],
'bp_avg':[
'NaN',],
'flag_bp_avg':[
'NaN',],
'ws_max':[
'NaN',],
'flag_ws_max':[
'NaN',],
'ws_min':[
'NaN',],
'flag_ws_min':[
'NaN',],
'ws_avg':[
'NaN',],
'flag_ws_avg':[
'NaN',],
'wd':[
'NaN',],
'flag_wd':[
'NaN',],
'solrad_avg':[
'NaN',],
'flag_solrad_avg':[
'NaN',],
'solrad_tot':[
'NaN',],
'flag_solrad_tot':[
'NaN',],
'soiltemp_5cm_avg':[
'NaN',],
'flag_soiltemp_5cm_avg':[
'NaN',],
'soilmoist_5cm_avg':[
'NaN',],
'flag_soilmoist_5cm_avg':[
'NaN',],
'airtemp_hmp1_max':[
'NaN',],
'flag_airtemp_hmp1_max':[
'NaN',],
'airtemp_hmp1_min':[
'NaN',],
'flag_airtemp_hmp1_min':[
'NaN',],
'airtemp_hmp1_avg':[
'NaN',],
'flag_airtemp_hmp1_avg':[
'NaN',],
'airtemp_hmp2_max':[
'NaN',],
'flag_airtemp_hmp2_max':[
'NaN',],
'airtemp_hmp2_min':[
'NaN',],
'flag_airtemp_hmp2_min':[
'NaN',],
'airtemp_hmp2_avg':[
'NaN',],
'flag_airtemp_hmp2_avg':[
'NaN',],
'airtemp_hmp3_max':[
'NaN',],
'flag_airtemp_hmp3_max':[
'NaN',],
'airtemp_hmp3_min':[
'NaN',],
'flag_airtemp_hmp3_min':[
'NaN',],
'airtemp_hmp3_avg':[
'NaN',],
'flag_airtemp_hmp3_avg':[
'NaN',],
'rh_hmp1_max':[
'NaN',],
'flag_rh_hmp1_max':[
'NaN',],
'rh_hmp1_min':[
'NaN',],
'flag_rh_hmp1_min':[
'NaN',],
'rh_hmp1_avg':[
'NaN',],
'flag_rh_hmp1_avg':[
'NaN',],
'rh_hmp2_max':[
'NaN',],
'flag_rh_hmp2_max':[
'NaN',],
'rh_hmp2_min':[
'NaN',],
'flag_rh_hmp2_min':[
'NaN',],
'rh_hmp2_avg':[
'NaN',],
'flag_rh_hmp2_avg':[
'NaN',],
'rh_hmp3_max':[
'NaN',],
'flag_rh_hmp3_max':[
'NaN',],
'rh_hmp3_min':[
'NaN',],
'flag_rh_hmp3_min':[
'NaN',],
'rh_hmp3_avg':[
'NaN',],
'flag_rh_hmp3_avg':[
'NaN',],}
)
# Coerce the data into the types specified in the metadata
dt1.LTER_site=dt1.LTER_site.astype('category')
dt1.local_site=dt1.local_site.astype('category')
dt1.logger=dt1.logger.astype('category')
# Since date conversions are tricky, the coerced dates will go into a new column with _datetime appended
# This new column is added to the dataframe but does not show up in automated summaries below.
#dt1=dt1.assign(date_datetime=pd.to_datetime(dt1.date,errors='coerce'))
# Since date conversions are tricky, the coerced dates will go into a new column with _datetime appended
# This new column is added to the dataframe but does not show up in automated summaries below.
#dt1=dt1.assign(year_datetime=pd.to_datetime(dt1.year,errors='coerce'))
dt1.jday=pd.to_numeric(dt1.jday,errors='coerce',downcast='integer')
dt1.airtemp_max=pd.to_numeric(dt1.airtemp_max,errors='coerce')
dt1.flag_airtemp_max=dt1.flag_airtemp_max.astype('category')
dt1.airtemp_min=pd.to_numeric(dt1.airtemp_min,errors='coerce')
dt1.flag_airtemp_min=dt1.flag_airtemp_min.astype('category')
dt1.airtemp_avg=pd.to_numeric(dt1.airtemp_avg,errors='coerce')
dt1.flag_airtemp_avg=dt1.flag_airtemp_avg.astype('category')
dt1.rh_max=pd.to_numeric(dt1.rh_max,errors='coerce')
dt1.flag_rh_max=dt1.flag_rh_max.astype('category')
dt1.rh_min=pd.to_numeric(dt1.rh_min,errors='coerce')
dt1.flag_rh_min=dt1.flag_rh_min.astype('category')
dt1.rh_avg=pd.to_numeric(dt1.rh_avg,errors='coerce')
dt1.flag_rh_avg=dt1.flag_rh_avg.astype('category')
dt1.bp_max=pd.to_numeric(dt1.bp_max,errors='coerce')
dt1.flag_bp_max=dt1.flag_bp_max.astype('category')
dt1.bp_min=pd.to_numeric(dt1.bp_min,errors='coerce')
dt1.flag_bp_min=dt1.flag_bp_min.astype('category')
dt1.bp_avg=pd.to_numeric(dt1.bp_avg,errors='coerce')
dt1.flag_bp_avg=dt1.flag_bp_avg.astype('category')
dt1.ws_max=pd.to_numeric(dt1.ws_max,errors='coerce')
dt1.flag_ws_max=dt1.flag_ws_max.astype('category')
dt1.ws_min=pd.to_numeric(dt1.ws_min,errors='coerce')
dt1.flag_ws_min=dt1.flag_ws_min.astype('category')
dt1.ws_avg=pd.to_numeric(dt1.ws_avg,errors='coerce')
dt1.flag_ws_avg=dt1.flag_ws_avg.astype('category')
dt1.wd=pd.to_numeric(dt1.wd,errors='coerce')
dt1.flag_wd=dt1.flag_wd.astype('category')
dt1.solrad_avg=pd.to_numeric(dt1.solrad_avg,errors='coerce')
dt1.flag_solrad_avg=dt1.flag_solrad_avg.astype('category')
dt1.solrad_tot=pd.to_numeric(dt1.solrad_tot,errors='coerce')
dt1.flag_solrad_tot=dt1.flag_solrad_tot.astype('category')
dt1.soiltemp_5cm_avg=pd.to_numeric(dt1.soiltemp_5cm_avg,errors='coerce')
dt1.flag_soiltemp_5cm_avg=dt1.flag_soiltemp_5cm_avg.astype('category')
dt1.soilmoist_5cm_avg=pd.to_numeric(dt1.soilmoist_5cm_avg,errors='coerce')
dt1.flag_soilmoist_5cm_avg=dt1.flag_soilmoist_5cm_avg.astype('category')
dt1.airtemp_hmp1_max=pd.to_numeric(dt1.airtemp_hmp1_max,errors='coerce')
dt1.flag_airtemp_hmp1_max=dt1.flag_airtemp_hmp1_max.astype('category')
dt1.airtemp_hmp1_min=pd.to_numeric(dt1.airtemp_hmp1_min,errors='coerce')
dt1.flag_airtemp_hmp1_min=dt1.flag_airtemp_hmp1_min.astype('category')
dt1.airtemp_hmp1_avg=pd.to_numeric(dt1.airtemp_hmp1_avg,errors='coerce')
dt1.flag_airtemp_hmp1_avg=dt1.flag_airtemp_hmp1_avg.astype('category')
dt1.airtemp_hmp2_max=pd.to_numeric(dt1.airtemp_hmp2_max,errors='coerce')
dt1.flag_airtemp_hmp2_max=dt1.flag_airtemp_hmp2_max.astype('category')
dt1.airtemp_hmp2_min=pd.to_numeric(dt1.airtemp_hmp2_min,errors='coerce')
dt1.flag_airtemp_hmp2_min=dt1.flag_airtemp_hmp2_min.astype('category')
dt1.airtemp_hmp2_avg=pd.to_numeric(dt1.airtemp_hmp2_avg,errors='coerce')
dt1.flag_airtemp_hmp2_avg=dt1.flag_airtemp_hmp2_avg.astype('category')
dt1.airtemp_hmp3_max=pd.to_numeric(dt1.airtemp_hmp3_max,errors='coerce')
dt1.flag_airtemp_hmp3_max=dt1.flag_airtemp_hmp3_max.astype('category')
dt1.airtemp_hmp3_min=pd.to_numeric(dt1.airtemp_hmp3_min,errors='coerce')
dt1.flag_airtemp_hmp3_min=dt1.flag_airtemp_hmp3_min.astype('category')
dt1.airtemp_hmp3_avg=pd.to_numeric(dt1.airtemp_hmp3_avg,errors='coerce')
dt1.flag_airtemp_hmp3_avg=dt1.flag_airtemp_hmp3_avg.astype('category')
dt1.rh_hmp1_max=pd.to_numeric(dt1.rh_hmp1_max,errors='coerce')
dt1.flag_rh_hmp1_max=dt1.flag_rh_hmp1_max.astype('category')
dt1.rh_hmp1_min=pd.to_numeric(dt1.rh_hmp1_min,errors='coerce')
dt1.flag_rh_hmp1_min=dt1.flag_rh_hmp1_min.astype('category')
dt1.rh_hmp1_avg=pd.to_numeric(dt1.rh_hmp1_avg,errors='coerce')
dt1.flag_rh_hmp1_avg=dt1.flag_rh_hmp1_avg.astype('category')
dt1.rh_hmp2_max=pd.to_numeric(dt1.rh_hmp2_max,errors='coerce')
dt1.flag_rh_hmp2_max=dt1.flag_rh_hmp2_max.astype('category')
dt1.rh_hmp2_min=pd.to_numeric(dt1.rh_hmp2_min,errors='coerce')
dt1.flag_rh_hmp2_min=dt1.flag_rh_hmp2_min.astype('category')
dt1.rh_hmp2_avg=pd.to_numeric(dt1.rh_hmp2_avg,errors='coerce')
dt1.flag_rh_hmp2_avg=dt1.flag_rh_hmp2_avg.astype('category')
dt1.rh_hmp3_max=pd.to_numeric(dt1.rh_hmp3_max,errors='coerce')
dt1.flag_rh_hmp3_max=dt1.flag_rh_hmp3_max.astype('category')
dt1.rh_hmp3_min=pd.to_numeric(dt1.rh_hmp3_min,errors='coerce')
dt1.flag_rh_hmp3_min=dt1.flag_rh_hmp3_min.astype('category')
dt1.rh_hmp3_avg=pd.to_numeric(dt1.rh_hmp3_avg,errors='coerce')
dt1.flag_rh_hmp3_avg=dt1.flag_rh_hmp3_avg.astype('category')
dt1 = dt1.set_index('date')
if verbose:
print("Here is a description of the data frame dt1 and number of lines\n")
print(dt1.info())
print("--------------------\n\n")
print("Here is a summary of numerical variables in the data frame dt1\n")
print(dt1.describe())
print("--------------------\n\n")
print("The analyses below are basic descriptions of the variables. After testing, they should be replaced.\n")
print(dt1.LTER_site.describe())
print("--------------------\n\n")
print(dt1.local_site.describe())
print("--------------------\n\n")
print(dt1.logger.describe())
print("--------------------\n\n")
# print(dt1.date.describe())
# print("--------------------\n\n")
print(dt1.year.describe())
print("--------------------\n\n")
print(dt1.jday.describe())
print("--------------------\n\n")
print(dt1.airtemp_max.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_max.describe())
print("--------------------\n\n")
print(dt1.airtemp_min.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_min.describe())
print("--------------------\n\n")
print(dt1.airtemp_avg.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_avg.describe())
print("--------------------\n\n")
print(dt1.rh_max.describe())
print("--------------------\n\n")
print(dt1.flag_rh_max.describe())
print("--------------------\n\n")
print(dt1.rh_min.describe())
print("--------------------\n\n")
print(dt1.flag_rh_min.describe())
print("--------------------\n\n")
print(dt1.rh_avg.describe())
print("--------------------\n\n")
print(dt1.flag_rh_avg.describe())
print("--------------------\n\n")
print(dt1.bp_max.describe())
print("--------------------\n\n")
print(dt1.flag_bp_max.describe())
print("--------------------\n\n")
print(dt1.bp_min.describe())
print("--------------------\n\n")
print(dt1.flag_bp_min.describe())
print("--------------------\n\n")
print(dt1.bp_avg.describe())
print("--------------------\n\n")
print(dt1.flag_bp_avg.describe())
print("--------------------\n\n")
print(dt1.ws_max.describe())
print("--------------------\n\n")
print(dt1.flag_ws_max.describe())
print("--------------------\n\n")
print(dt1.ws_min.describe())
print("--------------------\n\n")
print(dt1.flag_ws_min.describe())
print("--------------------\n\n")
print(dt1.ws_avg.describe())
print("--------------------\n\n")
print(dt1.flag_ws_avg.describe())
print("--------------------\n\n")
print(dt1.wd.describe())
print("--------------------\n\n")
print(dt1.flag_wd.describe())
print("--------------------\n\n")
print(dt1.solrad_avg.describe())
print("--------------------\n\n")
print(dt1.flag_solrad_avg.describe())
print("--------------------\n\n")
print(dt1.solrad_tot.describe())
print("--------------------\n\n")
print(dt1.flag_solrad_tot.describe())
print("--------------------\n\n")
print(dt1.soiltemp_5cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soiltemp_5cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoist_5cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoist_5cm_avg.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp1_max.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp1_max.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp1_min.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp1_min.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp1_avg.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp1_avg.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp2_max.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp2_max.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp2_min.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp2_min.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp2_avg.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp2_avg.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp3_max.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp3_max.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp3_min.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp3_min.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp3_avg.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp3_avg.describe())
print("--------------------\n\n")
print(dt1.rh_hmp1_max.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp1_max.describe())
print("--------------------\n\n")
print(dt1.rh_hmp1_min.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp1_min.describe())
print("--------------------\n\n")
print(dt1.rh_hmp1_avg.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp1_avg.describe())
print("--------------------\n\n")
print(dt1.rh_hmp2_max.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp2_max.describe())
print("--------------------\n\n")
print(dt1.rh_hmp2_min.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp2_min.describe())
print("--------------------\n\n")
print(dt1.rh_hmp2_avg.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp2_avg.describe())
print("--------------------\n\n")
print(dt1.rh_hmp3_max.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp3_max.describe())
print("--------------------\n\n")
print(dt1.rh_hmp3_min.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp3_min.describe())
print("--------------------\n\n")
print(dt1.rh_hmp3_avg.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp3_avg.describe())
print("--------------------\n\n")
return dt1
# Package ID: knb-lter-nwt.401.4 Cataloging System:https://pasta.edirepository.org.
# Data set title: Climate data for C1 data loggers (CR23X and CR1000), 2000 - ongoing, daily..
# Data set creator: Jennifer F Morse -
# Data set creator: - Niwot Ridge LTER
# Contact: - Information Manager Niwot Ridge LTER - lternwt@colorado.edu
# Stylesheet v1.0 for metadata conversion into program: John H. Porter, Univ. Virginia, jporter@virginia.edu
#
# This program creates numbered PANDA dataframes named dt1,dt2,dt3...,
# one for each data table in the dataset. It also provides some basic
# summaries of their contents. NumPy and Pandas modules need to be installed
# for the program to run.
def read_data_c1(file, verbose=False):
'''
Return pandas dataframe with date as index from D1 station data.
Parameters:
file (str): C1 data file
verbose (bool): print data summary if True. Default False.
Returns:
data (pandas.DataFrame) with date as index
'''
dt1 =pd.read_csv(file
,skiprows=1
,sep=","
,quotechar='"'
, names=[
"LTER_site",
"local_site",
"logger",
"date",
"year",
"jday",
"airtemp_max",
"flag_airtemp_max",
"airtemp_min",
"flag_airtemp_min",
"airtemp_avg",
"flag_airtemp_avg",
"rh_max",
"flag_rh_max",
"rh_min",
"flag_rh_min",
"rh_avg",
"flag_rh_avg",
"bp_max",
"flag_bp_max",
"bp_min",
"flag_bp_min",
"bp_avg",
"flag_bp_avg",
"ws_max",
"flag_ws_max",
"ws_min",
"flag_ws_min",
"ws_avg",
"flag_ws_avg",
"wd",
"flag_wd",
"solrad_avg",
"flag_solrad_avg",
"solrad_tot",
"flag_solrad_tot",
"ppt_tot",
"flag_ppt_tot",
"snowdepth_avg",
"flag_snowdepth_avg",
"soiltemp_5cm_max",
"flag_soiltemp_5cm_max",
"soiltemp_5cm_min",
"flag_soiltemp_5cm_min",
"soiltemp_5cm_avg",
"flag_soiltemp_5cm_avg",
"soilmoist_5cm_avg",
"flag_soilmoist_5cm_avg",
"soilmoistprof_10cm_avg",
"flag_soilmoistprof_10cm_avg",
"soilmoistprof_20cm_avg",
"flag_soilmoistprof_20cm_avg",
"soilmoistprof_30cm_avg",
"flag_soilmoistprof_30cm_avg",
"soilmoistprof_50cm_avg",
"flag_soilmoistprof_50cm_avg",
"soilmoistprof_70cm_avg",
"flag_soilmoistprof_70cm_avg",
"soilmoistprof_100cm_avg",
"flag_soilmoistprof_100cm_avg",
"soilmoistprof_150cm_avg",
"flag_soilmoistprof_150cm_avg",
"soilmoistprof_200cm_avg",
"flag_soilmoistprof_200cm_avg",
"airtemp_hmp1_max",
"flag_airtemp_hmp1_max",
"airtemp_hmp1_min",
"flag_airtemp_hmp1_min",
"airtemp_hmp1_avg",
"flag_airtemp_hmp1_avg",
"airtemp_hmp2_max",
"flag_airtemp_hmp2_max",
"airtemp_hmp2_min",
"flag_airtemp_hmp2_min",
"airtemp_hmp2_avg",
"flag_airtemp_hmp2_avg",
"airtemp_hmp3_max",
"flag_airtemp_hmp3_max",
"airtemp_hmp3_min",
"flag_airtemp_hmp3_min",
"airtemp_hmp3_avg",
"flag_airtemp_hmp3_avg",
"rh_hmp1_max",
"flag_rh_hmp1_max",
"rh_hmp1_min",
"flag_rh_hmp1_min",
"rh_hmp1_avg",
"flag_rh_hmp1_avg",
"rh_hmp2_max",
"flag_rh_hmp2_max",
"rh_hmp2_min",
"flag_rh_hmp2_min",
"rh_hmp2_avg",
"flag_rh_hmp2_avg",
"rh_hmp3_max",
"flag_rh_hmp3_max",
"rh_hmp3_min",
"flag_rh_hmp3_min",
"rh_hmp3_avg",
"flag_rh_hmp3_avg" ]
# data type checking is commented out because it may cause data
# loads to fail if the data contains inconsistent values. Uncomment
# the following lines to enable data type checking
# ,dtype={
# 'LTER_site':'str' ,
# 'local_site':'str' ,
# 'logger':'str' ,
# 'date':'str' ,
# 'year':'str' ,
# 'jday':'int' ,
# 'airtemp_max':'float' ,
# 'flag_airtemp_max':'str' ,
# 'airtemp_min':'float' ,
# 'flag_airtemp_min':'str' ,
# 'airtemp_avg':'float' ,
# 'flag_airtemp_avg':'str' ,
# 'rh_max':'float' ,
# 'flag_rh_max':'str' ,
# 'rh_min':'float' ,
# 'flag_rh_min':'str' ,
# 'rh_avg':'float' ,
# 'flag_rh_avg':'str' ,
# 'bp_max':'float' ,
# 'flag_bp_max':'str' ,
# 'bp_min':'float' ,
# 'flag_bp_min':'str' ,
# 'bp_avg':'float' ,
# 'flag_bp_avg':'str' ,
# 'ws_max':'float' ,
# 'flag_ws_max':'str' ,
# 'ws_min':'float' ,
# 'flag_ws_min':'str' ,
# 'ws_avg':'float' ,
# 'flag_ws_avg':'str' ,
# 'wd':'float' ,
# 'flag_wd':'str' ,
# 'solrad_avg':'float' ,
# 'flag_solrad_avg':'str' ,
# 'solrad_tot':'float' ,
# 'flag_solrad_tot':'str' ,
# 'ppt_tot':'float' ,
# 'flag_ppt_tot':'str' ,
# 'snowdepth_avg':'float' ,
# 'flag_snowdepth_avg':'str' ,
# 'soiltemp_5cm_max':'float' ,
# 'flag_soiltemp_5cm_max':'str' ,
# 'soiltemp_5cm_min':'float' ,
# 'flag_soiltemp_5cm_min':'str' ,
# 'soiltemp_5cm_avg':'float' ,
# 'flag_soiltemp_5cm_avg':'str' ,
# 'soilmoist_5cm_avg':'float' ,
# 'flag_soilmoist_5cm_avg':'str' ,
# 'soilmoistprof_10cm_avg':'float' ,
# 'flag_soilmoistprof_10cm_avg':'str' ,
# 'soilmoistprof_20cm_avg':'float' ,
# 'flag_soilmoistprof_20cm_avg':'str' ,
# 'soilmoistprof_30cm_avg':'float' ,
# 'flag_soilmoistprof_30cm_avg':'str' ,
# 'soilmoistprof_50cm_avg':'float' ,
# 'flag_soilmoistprof_50cm_avg':'str' ,
# 'soilmoistprof_70cm_avg':'float' ,
# 'flag_soilmoistprof_70cm_avg':'str' ,
# 'soilmoistprof_100cm_avg':'float' ,
# 'flag_soilmoistprof_100cm_avg':'str' ,
# 'soilmoistprof_150cm_avg':'float' ,
# 'flag_soilmoistprof_150cm_avg':'str' ,
# 'soilmoistprof_200cm_avg':'float' ,
# 'flag_soilmoistprof_200cm_avg':'str' ,
# 'airtemp_hmp1_max':'float' ,
# 'flag_airtemp_hmp1_max':'str' ,
# 'airtemp_hmp1_min':'float' ,
# 'flag_airtemp_hmp1_min':'str' ,
# 'airtemp_hmp1_avg':'float' ,
# 'flag_airtemp_hmp1_avg':'str' ,
# 'airtemp_hmp2_max':'float' ,
# 'flag_airtemp_hmp2_max':'str' ,
# 'airtemp_hmp2_min':'float' ,
# 'flag_airtemp_hmp2_min':'str' ,
# 'airtemp_hmp2_avg':'float' ,
# 'flag_airtemp_hmp2_avg':'str' ,
# 'airtemp_hmp3_max':'float' ,
# 'flag_airtemp_hmp3_max':'str' ,
# 'airtemp_hmp3_min':'float' ,
# 'flag_airtemp_hmp3_min':'str' ,
# 'airtemp_hmp3_avg':'float' ,
# 'flag_airtemp_hmp3_avg':'str' ,
# 'rh_hmp1_max':'float' ,
# 'flag_rh_hmp1_max':'str' ,
# 'rh_hmp1_min':'float' ,
# 'flag_rh_hmp1_min':'str' ,
# 'rh_hmp1_avg':'float' ,
# 'flag_rh_hmp1_avg':'str' ,
# 'rh_hmp2_max':'float' ,
# 'flag_rh_hmp2_max':'str' ,
# 'rh_hmp2_min':'float' ,
# 'flag_rh_hmp2_min':'str' ,
# 'rh_hmp2_avg':'float' ,
# 'flag_rh_hmp2_avg':'str' ,
# 'rh_hmp3_max':'float' ,
# 'flag_rh_hmp3_max':'str' ,
# 'rh_hmp3_min':'float' ,
# 'flag_rh_hmp3_min':'str' ,
# 'rh_hmp3_avg':'float' ,
# 'flag_rh_hmp3_avg':'str'
# }
,parse_dates=[
'date',
'year',
]
,na_values={
'LTER_site':[
'NaN',],
'local_site':[
'NaN',],
'logger':[
'NaN',],
'date':[
'NaN',],
'year':[
'NaN',],
'jday':[
'NaN',],
'airtemp_max':[
'NaN',
'NP',],
'flag_airtemp_max':[
'NaN',],
'airtemp_min':[
'NaN',
'NP',],
'flag_airtemp_min':[
'NaN',],
'airtemp_avg':[
'NaN',
'NP',],
'flag_airtemp_avg':[
'NaN',],
'rh_max':[
'NaN',
'NP',],
'flag_rh_max':[
'NaN',],
'rh_min':[
'NaN',
'NP',],
'flag_rh_min':[
'NaN',],
'rh_avg':[
'NaN',
'NP',],
'flag_rh_avg':[
'NaN',],
'bp_max':[
'NaN',
'NP',],
'flag_bp_max':[
'NaN',],
'bp_min':[
'NaN',
'NP',],
'flag_bp_min':[
'NaN',],
'bp_avg':[
'NaN',
'NP',],
'flag_bp_avg':[
'NaN',],
'ws_max':[
'NaN',
'NP',],
'flag_ws_max':[
'NaN',],
'ws_min':[
'NaN',
'NP',],
'flag_ws_min':[
'NaN',],
'ws_avg':[
'NaN',
'NP',],
'flag_ws_avg':[
'NaN',],
'wd':[
'NaN',
'NP',],
'flag_wd':[
'NaN',],
'solrad_avg':[
'NaN',
'NP',],
'flag_solrad_avg':[
'NaN',],
'solrad_tot':[
'NaN',
'NP',],
'flag_solrad_tot':[
'NaN',],
'ppt_tot':[
'NaN',],
'flag_ppt_tot':[
'NaN',],
'snowdepth_avg':[
'NaN',
'NP',],
'flag_snowdepth_avg':[
'NaN',],
'soiltemp_5cm_max':[
'NaN',
'NP',],
'flag_soiltemp_5cm_max':[
'NaN',],
'soiltemp_5cm_min':[
'NaN',
'NP',],
'flag_soiltemp_5cm_min':[
'NaN',],
'soiltemp_5cm_avg':[
'NaN',
'NP',],
'flag_soiltemp_5cm_avg':[
'NaN',],
'soilmoist_5cm_avg':[
'NaN',
'NP',],
'flag_soilmoist_5cm_avg':[
'NaN',],
'soilmoistprof_10cm_avg':[
'NaN',
'NP',],
'flag_soilmoistprof_10cm_avg':[
'NaN',],
'soilmoistprof_20cm_avg':[
'NaN',
'NP',],
'flag_soilmoistprof_20cm_avg':[
'NaN',],
'soilmoistprof_30cm_avg':[
'NaN',
'NP',],
'flag_soilmoistprof_30cm_avg':[
'NaN',],
'soilmoistprof_50cm_avg':[
'NaN',
'NP',],
'flag_soilmoistprof_50cm_avg':[
'NaN',],
'soilmoistprof_70cm_avg':[
'NaN',
'NP',],
'flag_soilmoistprof_70cm_avg':[
'NaN',],
'soilmoistprof_100cm_avg':[
'NaN',
'NP',],
'flag_soilmoistprof_100cm_avg':[
'NaN',],
'soilmoistprof_150cm_avg':[
'NaN',
'NP',],
'flag_soilmoistprof_150cm_avg':[
'NaN',],
'soilmoistprof_200cm_avg':[
'NaN',
'NP',],
'flag_soilmoistprof_200cm_avg':[
'NaN',],
'airtemp_hmp1_max':[
'NaN',],
'flag_airtemp_hmp1_max':[
'NaN',],
'airtemp_hmp1_min':[
'NaN',],
'flag_airtemp_hmp1_min':[
'NaN',],
'airtemp_hmp1_avg':[
'NaN',],
'flag_airtemp_hmp1_avg':[
'NaN',],
'airtemp_hmp2_max':[
'NaN',],
'flag_airtemp_hmp2_max':[
'NaN',],
'airtemp_hmp2_min':[
'NaN',],
'flag_airtemp_hmp2_min':[
'NaN',],
'airtemp_hmp2_avg':[
'NaN',],
'flag_airtemp_hmp2_avg':[
'NaN',],
'airtemp_hmp3_max':[
'NaN',],
'flag_airtemp_hmp3_max':[
'NaN',],
'airtemp_hmp3_min':[
'NaN',],
'flag_airtemp_hmp3_min':[
'NaN',],
'airtemp_hmp3_avg':[
'NaN',],
'flag_airtemp_hmp3_avg':[
'NaN',],
'rh_hmp1_max':[
'NaN',],
'flag_rh_hmp1_max':[
'NaN',],
'rh_hmp1_min':[
'NaN',],
'flag_rh_hmp1_min':[
'NaN',],
'rh_hmp1_avg':[
'NaN',],
'flag_rh_hmp1_avg':[
'NaN',],
'rh_hmp2_max':[
'NaN',],
'flag_rh_hmp2_max':[
'NaN',],
'rh_hmp2_min':[
'NaN',],
'flag_rh_hmp2_min':[
'NaN',],
'rh_hmp2_avg':[
'NaN',],
'flag_rh_hmp2_avg':[
'NaN',],
'rh_hmp3_max':[
'NaN',],
'flag_rh_hmp3_max':[
'NaN',],
'rh_hmp3_min':[
'NaN',],
'flag_rh_hmp3_min':[
'NaN',],
'rh_hmp3_avg':[
'NaN',],
'flag_rh_hmp3_avg':[
'NaN',],}
)
# Coerce the data into the types specified in the metadata
dt1.LTER_site=dt1.LTER_site.astype('category')
dt1.local_site=dt1.local_site.astype('category')
dt1.logger=dt1.logger.astype('category')
# Since date conversions are tricky, the coerced dates will go into a new column with _datetime appended
# This new column is added to the dataframe but does not show up in automated summaries below.
#dt1=dt1.assign(date_datetime=pd.to_datetime(dt1.date,errors='coerce'))
# Since date conversions are tricky, the coerced dates will go into a new column with _datetime appended
# This new column is added to the dataframe but does not show up in automated summaries below.
#dt1=dt1.assign(year_datetime=pd.to_datetime(dt1.year,errors='coerce'))
dt1.jday=pd.to_numeric(dt1.jday,errors='coerce',downcast='integer')
dt1.airtemp_max=pd.to_numeric(dt1.airtemp_max,errors='coerce')
dt1.flag_airtemp_max=dt1.flag_airtemp_max.astype('category')
dt1.airtemp_min=pd.to_numeric(dt1.airtemp_min,errors='coerce')
dt1.flag_airtemp_min=dt1.flag_airtemp_min.astype('category')
dt1.airtemp_avg=pd.to_numeric(dt1.airtemp_avg,errors='coerce')
dt1.flag_airtemp_avg=dt1.flag_airtemp_avg.astype('category')
dt1.rh_max=pd.to_numeric(dt1.rh_max,errors='coerce')
dt1.flag_rh_max=dt1.flag_rh_max.astype('category')
dt1.rh_min=pd.to_numeric(dt1.rh_min,errors='coerce')
dt1.flag_rh_min=dt1.flag_rh_min.astype('category')
dt1.rh_avg=pd.to_numeric(dt1.rh_avg,errors='coerce')
dt1.flag_rh_avg=dt1.flag_rh_avg.astype('category')
dt1.bp_max=pd.to_numeric(dt1.bp_max,errors='coerce')
dt1.flag_bp_max=dt1.flag_bp_max.astype('category')
dt1.bp_min=pd.to_numeric(dt1.bp_min,errors='coerce')
dt1.flag_bp_min=dt1.flag_bp_min.astype('category')
dt1.bp_avg=pd.to_numeric(dt1.bp_avg,errors='coerce')
dt1.flag_bp_avg=dt1.flag_bp_avg.astype('category')
dt1.ws_max=pd.to_numeric(dt1.ws_max,errors='coerce')
dt1.flag_ws_max=dt1.flag_ws_max.astype('category')
dt1.ws_min=pd.to_numeric(dt1.ws_min,errors='coerce')
dt1.flag_ws_min=dt1.flag_ws_min.astype('category')
dt1.ws_avg=pd.to_numeric(dt1.ws_avg,errors='coerce')
dt1.flag_ws_avg=dt1.flag_ws_avg.astype('category')
dt1.wd=pd.to_numeric(dt1.wd,errors='coerce')
dt1.flag_wd=dt1.flag_wd.astype('category')
dt1.solrad_avg=pd.to_numeric(dt1.solrad_avg,errors='coerce')
dt1.flag_solrad_avg=dt1.flag_solrad_avg.astype('category')
dt1.solrad_tot=pd.to_numeric(dt1.solrad_tot,errors='coerce')
dt1.flag_solrad_tot=dt1.flag_solrad_tot.astype('category')
dt1.ppt_tot=pd.to_numeric(dt1.ppt_tot,errors='coerce')
dt1.flag_ppt_tot=dt1.flag_ppt_tot.astype('category')
dt1.snowdepth_avg=pd.to_numeric(dt1.snowdepth_avg,errors='coerce')
dt1.flag_snowdepth_avg=dt1.flag_snowdepth_avg.astype('category')
dt1.soiltemp_5cm_max=pd.to_numeric(dt1.soiltemp_5cm_max,errors='coerce')
dt1.flag_soiltemp_5cm_max=dt1.flag_soiltemp_5cm_max.astype('category')
dt1.soiltemp_5cm_min=pd.to_numeric(dt1.soiltemp_5cm_min,errors='coerce')
dt1.flag_soiltemp_5cm_min=dt1.flag_soiltemp_5cm_min.astype('category')
dt1.soiltemp_5cm_avg=pd.to_numeric(dt1.soiltemp_5cm_avg,errors='coerce')
dt1.flag_soiltemp_5cm_avg=dt1.flag_soiltemp_5cm_avg.astype('category')
dt1.soilmoist_5cm_avg=pd.to_numeric(dt1.soilmoist_5cm_avg,errors='coerce')
dt1.flag_soilmoist_5cm_avg=dt1.flag_soilmoist_5cm_avg.astype('category')
dt1.soilmoistprof_10cm_avg=pd.to_numeric(dt1.soilmoistprof_10cm_avg,errors='coerce')
dt1.flag_soilmoistprof_10cm_avg=dt1.flag_soilmoistprof_10cm_avg.astype('category')
dt1.soilmoistprof_20cm_avg=pd.to_numeric(dt1.soilmoistprof_20cm_avg,errors='coerce')
dt1.flag_soilmoistprof_20cm_avg=dt1.flag_soilmoistprof_20cm_avg.astype('category')
dt1.soilmoistprof_30cm_avg=pd.to_numeric(dt1.soilmoistprof_30cm_avg,errors='coerce')
dt1.flag_soilmoistprof_30cm_avg=dt1.flag_soilmoistprof_30cm_avg.astype('category')
dt1.soilmoistprof_50cm_avg=pd.to_numeric(dt1.soilmoistprof_50cm_avg,errors='coerce')
dt1.flag_soilmoistprof_50cm_avg=dt1.flag_soilmoistprof_50cm_avg.astype('category')
dt1.soilmoistprof_70cm_avg=pd.to_numeric(dt1.soilmoistprof_70cm_avg,errors='coerce')
dt1.flag_soilmoistprof_70cm_avg=dt1.flag_soilmoistprof_70cm_avg.astype('category')
dt1.soilmoistprof_100cm_avg=pd.to_numeric(dt1.soilmoistprof_100cm_avg,errors='coerce')
dt1.flag_soilmoistprof_100cm_avg=dt1.flag_soilmoistprof_100cm_avg.astype('category')
dt1.soilmoistprof_150cm_avg=pd.to_numeric(dt1.soilmoistprof_150cm_avg,errors='coerce')
dt1.flag_soilmoistprof_150cm_avg=dt1.flag_soilmoistprof_150cm_avg.astype('category')
dt1.soilmoistprof_200cm_avg=pd.to_numeric(dt1.soilmoistprof_200cm_avg,errors='coerce')
dt1.flag_soilmoistprof_200cm_avg=dt1.flag_soilmoistprof_200cm_avg.astype('category')
dt1.airtemp_hmp1_max=pd.to_numeric(dt1.airtemp_hmp1_max,errors='coerce')
dt1.flag_airtemp_hmp1_max=dt1.flag_airtemp_hmp1_max.astype('category')
dt1.airtemp_hmp1_min=pd.to_numeric(dt1.airtemp_hmp1_min,errors='coerce')
dt1.flag_airtemp_hmp1_min=dt1.flag_airtemp_hmp1_min.astype('category')
dt1.airtemp_hmp1_avg=pd.to_numeric(dt1.airtemp_hmp1_avg,errors='coerce')
dt1.flag_airtemp_hmp1_avg=dt1.flag_airtemp_hmp1_avg.astype('category')
dt1.airtemp_hmp2_max=pd.to_numeric(dt1.airtemp_hmp2_max,errors='coerce')
dt1.flag_airtemp_hmp2_max=dt1.flag_airtemp_hmp2_max.astype('category')
dt1.airtemp_hmp2_min=pd.to_numeric(dt1.airtemp_hmp2_min,errors='coerce')
dt1.flag_airtemp_hmp2_min=dt1.flag_airtemp_hmp2_min.astype('category')
dt1.airtemp_hmp2_avg=pd.to_numeric(dt1.airtemp_hmp2_avg,errors='coerce')
dt1.flag_airtemp_hmp2_avg=dt1.flag_airtemp_hmp2_avg.astype('category')
dt1.airtemp_hmp3_max=pd.to_numeric(dt1.airtemp_hmp3_max,errors='coerce')
dt1.flag_airtemp_hmp3_max=dt1.flag_airtemp_hmp3_max.astype('category')
dt1.airtemp_hmp3_min=pd.to_numeric(dt1.airtemp_hmp3_min,errors='coerce')
dt1.flag_airtemp_hmp3_min=dt1.flag_airtemp_hmp3_min.astype('category')
dt1.airtemp_hmp3_avg=pd.to_numeric(dt1.airtemp_hmp3_avg,errors='coerce')
dt1.flag_airtemp_hmp3_avg=dt1.flag_airtemp_hmp3_avg.astype('category')
dt1.rh_hmp1_max=pd.to_numeric(dt1.rh_hmp1_max,errors='coerce')
dt1.flag_rh_hmp1_max=dt1.flag_rh_hmp1_max.astype('category')
dt1.rh_hmp1_min=pd.to_numeric(dt1.rh_hmp1_min,errors='coerce')
dt1.flag_rh_hmp1_min=dt1.flag_rh_hmp1_min.astype('category')
dt1.rh_hmp1_avg=pd.to_numeric(dt1.rh_hmp1_avg,errors='coerce')
dt1.flag_rh_hmp1_avg=dt1.flag_rh_hmp1_avg.astype('category')
dt1.rh_hmp2_max=pd.to_numeric(dt1.rh_hmp2_max,errors='coerce')
dt1.flag_rh_hmp2_max=dt1.flag_rh_hmp2_max.astype('category')
dt1.rh_hmp2_min=pd.to_numeric(dt1.rh_hmp2_min,errors='coerce')
dt1.flag_rh_hmp2_min=dt1.flag_rh_hmp2_min.astype('category')
dt1.rh_hmp2_avg=pd.to_numeric(dt1.rh_hmp2_avg,errors='coerce')
dt1.flag_rh_hmp2_avg=dt1.flag_rh_hmp2_avg.astype('category')
dt1.rh_hmp3_max=pd.to_numeric(dt1.rh_hmp3_max,errors='coerce')
dt1.flag_rh_hmp3_max=dt1.flag_rh_hmp3_max.astype('category')
dt1.rh_hmp3_min=pd.to_numeric(dt1.rh_hmp3_min,errors='coerce')
dt1.flag_rh_hmp3_min=dt1.flag_rh_hmp3_min.astype('category')
dt1.rh_hmp3_avg=pd.to_numeric(dt1.rh_hmp3_avg,errors='coerce')
dt1.flag_rh_hmp3_avg=dt1.flag_rh_hmp3_avg.astype('category')
dt1 = dt1.set_index('date')
if verbose:
print("Here is a description of the data frame dt1 and number of lines\n")
print(dt1.info())
print("--------------------\n\n")
print("Here is a summary of numerical variables in the data frame dt1\n")
print(dt1.describe())
print("--------------------\n\n")
print("The analyses below are basic descriptions of the variables. After testing, they should be replaced.\n")
print(dt1.LTER_site.describe())
print("--------------------\n\n")
print(dt1.local_site.describe())
print("--------------------\n\n")
print(dt1.logger.describe())
print("--------------------\n\n")
print(dt1.date.describe())
print("--------------------\n\n")
#print(dt1.year.describe())
#print("--------------------\n\n")
print(dt1.jday.describe())
print("--------------------\n\n")
print(dt1.airtemp_max.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_max.describe())
print("--------------------\n\n")
print(dt1.airtemp_min.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_min.describe())
print("--------------------\n\n")
print(dt1.airtemp_avg.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_avg.describe())
print("--------------------\n\n")
print(dt1.rh_max.describe())
print("--------------------\n\n")
print(dt1.flag_rh_max.describe())
print("--------------------\n\n")
print(dt1.rh_min.describe())
print("--------------------\n\n")
print(dt1.flag_rh_min.describe())
print("--------------------\n\n")
print(dt1.rh_avg.describe())
print("--------------------\n\n")
print(dt1.flag_rh_avg.describe())
print("--------------------\n\n")
print(dt1.bp_max.describe())
print("--------------------\n\n")
print(dt1.flag_bp_max.describe())
print("--------------------\n\n")
print(dt1.bp_min.describe())
print("--------------------\n\n")
print(dt1.flag_bp_min.describe())
print("--------------------\n\n")
print(dt1.bp_avg.describe())
print("--------------------\n\n")
print(dt1.flag_bp_avg.describe())
print("--------------------\n\n")
print(dt1.ws_max.describe())
print("--------------------\n\n")
print(dt1.flag_ws_max.describe())
print("--------------------\n\n")
print(dt1.ws_min.describe())
print("--------------------\n\n")
print(dt1.flag_ws_min.describe())
print("--------------------\n\n")
print(dt1.ws_avg.describe())
print("--------------------\n\n")
print(dt1.flag_ws_avg.describe())
print("--------------------\n\n")
print(dt1.wd.describe())
print("--------------------\n\n")
print(dt1.flag_wd.describe())
print("--------------------\n\n")
print(dt1.solrad_avg.describe())
print("--------------------\n\n")
print(dt1.flag_solrad_avg.describe())
print("--------------------\n\n")
print(dt1.solrad_tot.describe())
print("--------------------\n\n")
print(dt1.flag_solrad_tot.describe())
print("--------------------\n\n")
print(dt1.ppt_tot.describe())
print("--------------------\n\n")
print(dt1.flag_ppt_tot.describe())
print("--------------------\n\n")
print(dt1.snowdepth_avg.describe())
print("--------------------\n\n")
print(dt1.flag_snowdepth_avg.describe())
print("--------------------\n\n")
print(dt1.soiltemp_5cm_max.describe())
print("--------------------\n\n")
print(dt1.flag_soiltemp_5cm_max.describe())
print("--------------------\n\n")
print(dt1.soiltemp_5cm_min.describe())
print("--------------------\n\n")
print(dt1.flag_soiltemp_5cm_min.describe())
print("--------------------\n\n")
print(dt1.soiltemp_5cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soiltemp_5cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoist_5cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoist_5cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoistprof_10cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoistprof_10cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoistprof_20cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoistprof_20cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoistprof_30cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoistprof_30cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoistprof_50cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoistprof_50cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoistprof_70cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoistprof_70cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoistprof_100cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoistprof_100cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoistprof_150cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoistprof_150cm_avg.describe())
print("--------------------\n\n")
print(dt1.soilmoistprof_200cm_avg.describe())
print("--------------------\n\n")
print(dt1.flag_soilmoistprof_200cm_avg.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp1_max.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp1_max.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp1_min.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp1_min.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp1_avg.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp1_avg.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp2_max.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp2_max.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp2_min.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp2_min.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp2_avg.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp2_avg.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp3_max.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp3_max.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp3_min.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp3_min.describe())
print("--------------------\n\n")
print(dt1.airtemp_hmp3_avg.describe())
print("--------------------\n\n")
print(dt1.flag_airtemp_hmp3_avg.describe())
print("--------------------\n\n")
print(dt1.rh_hmp1_max.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp1_max.describe())
print("--------------------\n\n")
print(dt1.rh_hmp1_min.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp1_min.describe())
print("--------------------\n\n")
print(dt1.rh_hmp1_avg.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp1_avg.describe())
print("--------------------\n\n")
print(dt1.rh_hmp2_max.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp2_max.describe())
print("--------------------\n\n")
print(dt1.rh_hmp2_min.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp2_min.describe())
print("--------------------\n\n")
print(dt1.rh_hmp2_avg.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp2_avg.describe())
print("--------------------\n\n")
print(dt1.rh_hmp3_max.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp3_max.describe())
print("--------------------\n\n")
print(dt1.rh_hmp3_min.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp3_min.describe())
print("--------------------\n\n")
print(dt1.rh_hmp3_avg.describe())
print("--------------------\n\n")
print(dt1.flag_rh_hmp3_avg.describe())
print("--------------------\n\n")
return dt1
| 42.467568
| 118
| 0.44573
| 6,246
| 62,852
| 4.135607
| 0.036663
| 0.066664
| 0.062715
| 0.082691
| 0.935581
| 0.894855
| 0.867524
| 0.846386
| 0.841121
| 0.805853
| 0
| 0.034138
| 0.377347
| 62,852
| 1,479
| 119
| 42.496281
| 0.62591
| 0.164768
| 0
| 0.90455
| 0
| 0
| 0.220971
| 0.116482
| 0
| 0
| 0
| 0
| 0
| 1
| 0.001784
| false
| 0
| 0.001784
| 0
| 0.005352
| 0.322926
| 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
|
9e453e33149e4bccc7198a40da51fd02fb9e5c1b
| 4,458
|
py
|
Python
|
examples/stereo.py
|
thehappydinoa/iTachModulePython
|
5fc0597ffc29bf899ec2cf0d09ad557bf071fc4f
|
[
"MIT"
] | 3
|
2019-01-10T04:10:47.000Z
|
2021-05-12T18:29:59.000Z
|
examples/stereo.py
|
thehappydinoa/iTachModulePython
|
5fc0597ffc29bf899ec2cf0d09ad557bf071fc4f
|
[
"MIT"
] | 3
|
2020-09-24T10:47:24.000Z
|
2021-06-25T15:42:18.000Z
|
examples/stereo.py
|
thehappydinoa/iTachModulePython
|
5fc0597ffc29bf899ec2cf0d09ad557bf071fc4f
|
[
"MIT"
] | 6
|
2018-08-12T13:27:24.000Z
|
2021-12-09T01:11:11.000Z
|
from itachip2ir import VirtualDevice, iTach
commands = {
"toggle_power": "sendir,1:3,7,40064,1,1,96,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,908,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,908,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,908,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,908,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,908,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,4000",
"toggle_mute": "sendir,1:3,1,40192,1,1,97,23,25,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,912,96,23,25,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,912,96,23,25,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,934,97,23,25,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,935,97,23,25,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,935,97,23,25,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,4000",
"volume_up": "sendir,1:3,2,40192,1,1,97,23,25,23,49,23,25,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,915,96,23,25,23,49,23,25,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,912,96,23,25,23,49,23,25,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,932,97,23,25,23,49,23,25,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,4000",
"volume_down": "sendir,1:3,8,40192,1,1,97,23,49,23,49,23,25,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,891,96,23,49,23,49,23,25,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,888,96,23,49,23,49,23,25,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,4000",
"input_sat": "sendir,1:3,1,40192,1,1,97,23,49,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,49,898,96,23,49,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,49,888,96,23,49,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,49,921,97,23,49,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,49,921,97,23,49,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,49,921,97,23,49,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,49,921,97,23,49,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,49,4000",
"input_tv": "sendir,1:3,1,40192,1,1,97,23,25,23,49,23,25,23,49,23,25,23,49,23,49,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,874,96,23,25,23,49,23,25,23,49,23,25,23,49,23,49,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,864,96,23,25,23,49,23,25,23,49,23,25,23,49,23,49,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,897,97,23,25,23,49,23,25,23,49,23,25,23,49,23,49,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,897,97,23,25,23,49,23,25,23,49,23,25,23,49,23,49,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,897,97,23,25,23,49,23,25,23,49,23,25,23,49,23,49,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,897,97,23,25,23,49,23,25,23,49,23,25,23,49,23,49,23,25,23,25,23,25,23,25,23,49,23,49,23,25,23,25,4000",
"input_bd": "sendir,1:3,1,40192,2,1,97,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,25,23,25,628,96,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,25,23,25,624,96,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,25,23,25,660,97,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,25,23,25,660,97,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,25,23,25,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,25,23,25,4000"
}
itach = iTach(ipaddress="192.168.1.111", port=4998)
stereo = itach.add(VirtualDevice(
name="stereo", commands=commands))
if __name__ == "__main__":
print(stereo.toggle_power())
print(stereo.volume_up())
print(stereo.volume_down())
| 202.636364
| 722
| 0.667564
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| 4,458
| 2.163862
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| 21
| 723
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0
| 16
|
9eb8dea966a61a5f419194a52d7b13b33d632456
| 12,499
|
py
|
Python
|
SimModel_Python_API/simmodel_swig/Release/SimAppObjNameDefault_BldgComponentGroup_HvacComponent.py
|
EnEff-BIM/EnEffBIM-Framework
|
6328d39b498dc4065a60b5cc9370b8c2a9a1cddf
|
[
"MIT"
] | 3
|
2016-05-30T15:12:16.000Z
|
2022-03-22T08:11:13.000Z
|
SimModel_Python_API/simmodel_swig/Release/SimAppObjNameDefault_BldgComponentGroup_HvacComponent.py
|
EnEff-BIM/EnEffBIM-Framework
|
6328d39b498dc4065a60b5cc9370b8c2a9a1cddf
|
[
"MIT"
] | 21
|
2016-06-13T11:33:45.000Z
|
2017-05-23T09:46:52.000Z
|
SimModel_Python_API/simmodel_swig/Release/SimAppObjNameDefault_BldgComponentGroup_HvacComponent.py
|
EnEff-BIM/EnEffBIM-Framework
|
6328d39b498dc4065a60b5cc9370b8c2a9a1cddf
|
[
"MIT"
] | null | null | null |
# This file was automatically generated by SWIG (http://www.swig.org).
# Version 3.0.7
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
from sys import version_info
if version_info >= (2, 6, 0):
def swig_import_helper():
from os.path import dirname
import imp
fp = None
try:
fp, pathname, description = imp.find_module('_SimAppObjNameDefault_BldgComponentGroup_HvacComponent', [dirname(__file__)])
except ImportError:
import _SimAppObjNameDefault_BldgComponentGroup_HvacComponent
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent
if fp is not None:
try:
_mod = imp.load_module('_SimAppObjNameDefault_BldgComponentGroup_HvacComponent', fp, pathname, description)
finally:
fp.close()
return _mod
_SimAppObjNameDefault_BldgComponentGroup_HvacComponent = swig_import_helper()
del swig_import_helper
else:
import _SimAppObjNameDefault_BldgComponentGroup_HvacComponent
del version_info
try:
_swig_property = property
except NameError:
pass # Python < 2.2 doesn't have 'property'.
def _swig_setattr_nondynamic(self, class_type, name, value, static=1):
if (name == "thisown"):
return self.this.own(value)
if (name == "this"):
if type(value).__name__ == 'SwigPyObject':
self.__dict__[name] = value
return
method = class_type.__swig_setmethods__.get(name, None)
if method:
return method(self, value)
if (not static):
if _newclass:
object.__setattr__(self, name, value)
else:
self.__dict__[name] = value
else:
raise AttributeError("You cannot add attributes to %s" % self)
def _swig_setattr(self, class_type, name, value):
return _swig_setattr_nondynamic(self, class_type, name, value, 0)
def _swig_getattr_nondynamic(self, class_type, name, static=1):
if (name == "thisown"):
return self.this.own()
method = class_type.__swig_getmethods__.get(name, None)
if method:
return method(self)
if (not static):
return object.__getattr__(self, name)
else:
raise AttributeError(name)
def _swig_getattr(self, class_type, name):
return _swig_getattr_nondynamic(self, class_type, name, 0)
def _swig_repr(self):
try:
strthis = "proxy of " + self.this.__repr__()
except:
strthis = ""
return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)
try:
_object = object
_newclass = 1
except AttributeError:
class _object:
pass
_newclass = 0
try:
import weakref
weakref_proxy = weakref.proxy
except:
weakref_proxy = lambda x: x
import base
class SimAppObjNameDefault(base.SimAppDefault):
__swig_setmethods__ = {}
for _s in [base.SimAppDefault]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, SimAppObjNameDefault, name, value)
__swig_getmethods__ = {}
for _s in [base.SimAppDefault]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, SimAppObjNameDefault, name)
__repr__ = _swig_repr
def DefaultForObjectType(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_DefaultForObjectType(self, *args)
def NameString1(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_NameString1(self, *args)
def NameString2(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_NameString2(self, *args)
def IndexType1(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_IndexType1(self, *args)
def IndexType2(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_IndexType2(self, *args)
def LastUsedIndex1(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_LastUsedIndex1(self, *args)
def LastUsedIndex2(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_LastUsedIndex2(self, *args)
def __init__(self, *args):
this = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.new_SimAppObjNameDefault(*args)
try:
self.this.append(this)
except:
self.this = this
def _clone(self, f=0, c=None):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault__clone(self, f, c)
__swig_destroy__ = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.delete_SimAppObjNameDefault
__del__ = lambda self: None
SimAppObjNameDefault_swigregister = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_swigregister
SimAppObjNameDefault_swigregister(SimAppObjNameDefault)
class SimAppObjNameDefault_BldgComponentGroup(SimAppObjNameDefault):
__swig_setmethods__ = {}
for _s in [SimAppObjNameDefault]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, SimAppObjNameDefault_BldgComponentGroup, name, value)
__swig_getmethods__ = {}
for _s in [SimAppObjNameDefault]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, SimAppObjNameDefault_BldgComponentGroup, name)
__repr__ = _swig_repr
def __init__(self, *args):
this = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.new_SimAppObjNameDefault_BldgComponentGroup(*args)
try:
self.this.append(this)
except:
self.this = this
def _clone(self, f=0, c=None):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup__clone(self, f, c)
__swig_destroy__ = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.delete_SimAppObjNameDefault_BldgComponentGroup
__del__ = lambda self: None
SimAppObjNameDefault_BldgComponentGroup_swigregister = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_swigregister
SimAppObjNameDefault_BldgComponentGroup_swigregister(SimAppObjNameDefault_BldgComponentGroup)
class SimAppObjNameDefault_BldgComponentGroup_HvacComponent(SimAppObjNameDefault_BldgComponentGroup):
__swig_setmethods__ = {}
for _s in [SimAppObjNameDefault_BldgComponentGroup]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, SimAppObjNameDefault_BldgComponentGroup_HvacComponent, name, value)
__swig_getmethods__ = {}
for _s in [SimAppObjNameDefault_BldgComponentGroup]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, SimAppObjNameDefault_BldgComponentGroup_HvacComponent, name)
__repr__ = _swig_repr
def __init__(self, *args):
this = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.new_SimAppObjNameDefault_BldgComponentGroup_HvacComponent(*args)
try:
self.this.append(this)
except:
self.this = this
def _clone(self, f=0, c=None):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent__clone(self, f, c)
__swig_destroy__ = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.delete_SimAppObjNameDefault_BldgComponentGroup_HvacComponent
__del__ = lambda self: None
SimAppObjNameDefault_BldgComponentGroup_HvacComponent_swigregister = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_swigregister
SimAppObjNameDefault_BldgComponentGroup_HvacComponent_swigregister(SimAppObjNameDefault_BldgComponentGroup_HvacComponent)
class SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence(base.sequence_common):
__swig_setmethods__ = {}
for _s in [base.sequence_common]:
__swig_setmethods__.update(getattr(_s, '__swig_setmethods__', {}))
__setattr__ = lambda self, name, value: _swig_setattr(self, SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence, name, value)
__swig_getmethods__ = {}
for _s in [base.sequence_common]:
__swig_getmethods__.update(getattr(_s, '__swig_getmethods__', {}))
__getattr__ = lambda self, name: _swig_getattr(self, SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence, name)
__repr__ = _swig_repr
def __init__(self, *args):
this = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.new_SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence(*args)
try:
self.this.append(this)
except:
self.this = this
def assign(self, n, x):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_assign(self, n, x)
def begin(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_begin(self, *args)
def end(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_end(self, *args)
def rbegin(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_rbegin(self, *args)
def rend(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_rend(self, *args)
def at(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_at(self, *args)
def front(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_front(self, *args)
def back(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_back(self, *args)
def push_back(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_push_back(self, *args)
def pop_back(self):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_pop_back(self)
def detach_back(self, pop=True):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_detach_back(self, pop)
def insert(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_insert(self, *args)
def erase(self, *args):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_erase(self, *args)
def detach(self, position, r, erase=True):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_detach(self, position, r, erase)
def swap(self, x):
return _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_swap(self, x)
__swig_destroy__ = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.delete_SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence
__del__ = lambda self: None
SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_swigregister = _SimAppObjNameDefault_BldgComponentGroup_HvacComponent.SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_swigregister
SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence_swigregister(SimAppObjNameDefault_BldgComponentGroup_HvacComponent_sequence)
# This file is compatible with both classic and new-style classes.
| 46.812734
| 208
| 0.782223
| 1,153
| 12,499
| 7.910668
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0
| 7
|
7b5769eefdedff180569181a1cc842cf5aaf3dba
| 170
|
py
|
Python
|
backend/tests/conftest.py
|
nerds-amp-mods/login-pack
|
c006f2c15317893d87ce9e1ff1701920680ce64f
|
[
"MIT"
] | 2
|
2020-10-10T12:58:11.000Z
|
2020-11-07T02:44:32.000Z
|
backend/tests/conftest.py
|
nerds-amp-mods/login-pack
|
c006f2c15317893d87ce9e1ff1701920680ce64f
|
[
"MIT"
] | 5
|
2020-11-14T16:28:39.000Z
|
2020-11-14T16:41:06.000Z
|
backend/tests/conftest.py
|
nerds-amp-mods/Hackathon-Starter-Pack
|
c006f2c15317893d87ce9e1ff1701920680ce64f
|
[
"MIT"
] | 1
|
2020-11-06T15:01:29.000Z
|
2020-11-06T15:01:29.000Z
|
import pytest
from app import hackathon_backend_api
@pytest.fixture
def client():
# app.app.config['TESTING'] = True
yield hackathon_backend_api.test_client()
| 17
| 45
| 0.752941
| 23
| 170
| 5.347826
| 0.652174
| 0.260163
| 0.308943
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152941
| 170
| 9
| 46
| 18.888889
| 0.854167
| 0.188235
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| true
| 0
| 0.4
| 0
| 0.6
| 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
|
7b919400020dcf01bd921a7e924dbd385a8afa28
| 94
|
py
|
Python
|
src/socketclient/utils/__init__.py
|
TKaxv-7S/jd-assistant
|
426940efa4254246e9eb85e32fc81f8b3728f323
|
[
"MIT"
] | 16
|
2020-12-17T11:19:38.000Z
|
2022-02-17T06:03:34.000Z
|
src/socketclient/utils/__init__.py
|
JackMa777/jd-assistant
|
426940efa4254246e9eb85e32fc81f8b3728f323
|
[
"MIT"
] | null | null | null |
src/socketclient/utils/__init__.py
|
JackMa777/jd-assistant
|
426940efa4254246e9eb85e32fc81f8b3728f323
|
[
"MIT"
] | 4
|
2020-12-04T05:06:14.000Z
|
2021-12-28T09:03:24.000Z
|
from socketclient.utils.http import cookie_util
from socketclient.utils.http import http_util
| 31.333333
| 47
| 0.87234
| 14
| 94
| 5.714286
| 0.5
| 0.4
| 0.525
| 0.625
| 0.775
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085106
| 94
| 2
| 48
| 47
| 0.930233
| 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
|
7bc446fcfb9a4cc6ab11f2a96bb7700c328f81b7
| 51,037
|
py
|
Python
|
tests/test_featured_blocks.py
|
tate138/Martindale_Automation
|
082169df9f88ddc96fa81365f9c5e8aa460f7d14
|
[
"Apache-2.0"
] | null | null | null |
tests/test_featured_blocks.py
|
tate138/Martindale_Automation
|
082169df9f88ddc96fa81365f9c5e8aa460f7d14
|
[
"Apache-2.0"
] | null | null | null |
tests/test_featured_blocks.py
|
tate138/Martindale_Automation
|
082169df9f88ddc96fa81365f9c5e8aa460f7d14
|
[
"Apache-2.0"
] | null | null | null |
from library.page_models.martindale.martindale_module_setup import MartindaleModuleSetup
from library.page_models.martindale.martindale_login import MartindaleLogin
from library.page_models.martindale.martindale_navigation import MartindaleNavigation
from library.selenium_actions import *
from library.tools import Tools
from library.page_data.martindale_app.featured_blocks_data import FeaturedBlocksData
from library.page_data.martindale_app.martindale_data import MartindalePageData
from tests.test_setup.common_setup import CommonSetup, TestRailStatus
import pytest
import sys
####
# Featured Blocks Module Test
####
'''
python -m pytest "Documents/IB/Martindale Automation/tests/test_featured_blocks.py" -s
'''
class TestFeaturedBlocksModule(CommonSetup):
####
# Suite Setup and Teardown
####
@pytest.fixture(autouse=True, scope='module')
def set_up_class(self):
'''
Will be run once first before any test
'''
web_driver = self.fetch_webdriver()
Tools.log("Executing Featured Blocks module tests...")
MartindaleNavigation.navigate_to_home_page(web_driver)
MartindaleLogin.login_to_app(web_driver)
CommonSetup.selected_module = "featured"
MartindaleModuleSetup.module_open(web_driver)
# will run at end of all tests
def teardown_class(self):
'''
Will be run once when all tests are complete
'''
Tools.log("Featured Blocks module test run complete.")
####
# Case Setup and Teardown
####
def case_setup(self):
'''
Methods that will be run to setup individual cases
called in test as
self.case_setup()
'''
def case_teardown(self):
'''
Methods that will be run to cleanup individual cases
called in test as
self.case_teardown()
'''
self.common_test_teardown()
####
# Test Case Setup and Teardown
####
def test_c18521219(self):
test_case_number = "18521219"
web_driver = self.fetch_webdriver()
try:
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
element_path = FeaturedBlocksData.FEATURED_BLOCKS_MODULE_HEADER
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
blade_text = SeleniumActions.read_web_element_text(web_element)
try:
assert(blade_text == "FEATURED BLOCKS MODULE")
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521219 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521222(self):
test_case_number = "18521222"
web_driver = self.fetch_webdriver()
try:
click_settings_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_TAB)
SeleniumActions.click_element(web_driver, click_settings_tab)
Tools.sleep(1)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_TITLE)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521222 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527231(self):
test_case_number = "18527231"
web_driver = self.fetch_webdriver()
try:
click_layout_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_TAB)
SeleniumActions.click_element(web_driver, click_layout_tab)
Tools.sleep(1)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_LABEL)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527231 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521229(self):
test_case_number = "18521229"
web_driver = self.fetch_webdriver()
try:
click_content_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_TAB)
SeleniumActions.click_element(web_driver, click_content_tab)
Tools.sleep(1)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_TITLE)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521229 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521228(self):
test_case_number = "18521228"
web_driver = self.fetch_webdriver()
try:
# Module Information
click_module_info = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_MODULE_INFORMATION)
SeleniumActions.click_element(web_driver, click_module_info)
Tools.sleep(1)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_TITLE)
try:
assert(SeleniumActions.element_is_not_visible(web_element))
test_one = "Passed"
except AssertionError:
test_one = "Failed"
SeleniumActions.click_element(web_driver, click_module_info)
Tools.sleep(2)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_TITLE)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
test_two = "Passed"
except AssertionError:
test_two = "Failed"
# Manage Content
click_manage_content = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_MANAGE_CONTENT)
SeleniumActions.click_element(web_driver, click_manage_content)
Tools.sleep(1)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_ADD_CONTENT)
try:
assert(SeleniumActions.element_is_not_visible(web_element))
test_three = "Passed"
except AssertionError:
test_three = "Failed"
SeleniumActions.click_element(web_driver, click_manage_content)
Tools.sleep(2)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_ADD_CONTENT)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
test_four = "Passed"
except AssertionError:
test_four = "Failed"
if test_one == "Passed" and test_two == "Passed" and test_three == "Passed" and test_four == "Passed":
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
else:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521228 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521223(self):
test_case_number = "18521223"
web_driver = self.fetch_webdriver()
try:
click_add_content = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_ADD_CONTENT)
SeleniumActions.click_element(web_driver, click_add_content)
Tools.sleep(1)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_BLOCK_TITLE)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521223 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527150(self):
test_case_number = "18527150"
web_driver = self.fetch_webdriver()
try:
click_csncel_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_CANCEL_BUTTON)
SeleniumActions.click_element(web_driver, click_csncel_button)
Tools.sleep(3)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_MODULE_INFORMATION)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527150 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521225(self):
test_case_number = "18521225"
web_driver = self.fetch_webdriver()
try:
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_EDIT_BUTTON)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(1)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_BLOCK_TITLE)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521225 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521224(self):
test_case_number = "18521224"
web_driver = self.fetch_webdriver()
try:
click_csncel_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_CANCEL_BUTTON)
SeleniumActions.click_element(web_driver, click_csncel_button)
Tools.sleep(3)
click_delete_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_DELETE_BUTTON)
SeleniumActions.click_element(web_driver, click_delete_button)
Tools.sleep(1)
delete_modal = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.DELETE_FEATURED_BLOCKS_MODAL)
featured_blocks_delete_modal = SeleniumActions.read_web_element_text(delete_modal)
try:
assert(featured_blocks_delete_modal == "Are you sure you want to remove this link?")
test_one = "Passed"
except AssertionError:
test_one = "Failed"
click_csncel_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.DELETE_FEATURED_BLOCKS_MODAL_CANCEL_BUTTON)
SeleniumActions.click_element(web_driver, click_csncel_button)
Tools.sleep(1)
featured_block = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCK)
try:
assert(SeleniumActions.element_is_visible(web_driver, featured_block))
test_two = "Passed"
except AssertionError:
test_two = "Failed"
click_delete_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_DELETE_BUTTON)
SeleniumActions.click_element(web_driver, click_delete_button)
Tools.sleep(1)
click_modal_ok = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.DELETE_FEATURED_BLOCKS_MODAL_OK_BUTTON)
SeleniumActions.click_element(web_driver, click_modal_ok)
Tools.sleep(2)
try:
assert(SeleniumActions.check_element_exists(web_driver,
"//*[contains(@id, 'link_link-')]/div[2]/div/div[2]/div[1]"))
test_three = "Failed"
except AssertionError:
test_three = "Passed"
if test_one == "Passed" and test_two == "Passed" and test_three == "Passed":
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
else:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521224 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527155(self):
test_case_number = "18527155"
web_driver = self.fetch_webdriver()
try:
click_add_content = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_ADD_CONTENT)
SeleniumActions.click_element(web_driver, click_add_content)
Tools.sleep(3)
click_select_gallery = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SELECT_FROM_GALLERY)
SeleniumActions.click_element(web_driver, click_select_gallery)
Tools.sleep(3)
click_gallery_image = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SELECT_GALLERY_IMAGE)
SeleniumActions.click_element(web_driver, click_gallery_image)
element_path = FeaturedBlocksData.ADD_CONTENT_SELECT_GALLERY_IMAGE_TEXT
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
image_text = SeleniumActions.read_web_element_text(web_element)
click_insert_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SELECT_GALLERY_INSERT_BUTTON)
SeleniumActions.click_element(web_driver, click_insert_button)
Tools.sleep(2)
element_path = FeaturedBlocksData.ADD_CONTENT_IMAGE_CONTAINER
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
SeleniumActions.move_to_element(web_driver, web_element)
element_path = FeaturedBlocksData.ADD_CONTENT_IMAGE_TEXT
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
added_image_text = SeleniumActions.read_web_element_text(web_element)
try:
assert("/" + image_text == added_image_text)
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527155 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527161(self):
test_case_number = "18527161"
web_driver = self.fetch_webdriver()
try:
element_path = FeaturedBlocksData.ADD_CONTENT_IMAGE_CONTAINER
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
SeleniumActions.move_to_element(web_driver, web_element)
click_replace_image = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_REPLACE_BUTTON)
SeleniumActions.click_element(web_driver, click_replace_image)
Tools.sleep(3)
gallery_image = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SELECT_GALLERY_IMAGE)
try:
assert(SeleniumActions.element_is_visible(web_driver, gallery_image))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527161 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527151(self):
test_case_number = "18527151"
web_driver = self.fetch_webdriver()
try:
click_cancel_image = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SELECT_GALLERY_CANCEL_BUTTON)
SeleniumActions.click_element(web_driver, click_cancel_image)
Tools.sleep(3)
element_path = FeaturedBlocksData.FEATURED_BLOCK_LINK_TYPE
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
SeleniumActions.select_by_index(web_element, "1")
Tools.sleep(2)
link_drop_down = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCK_LINK_DROP_DOWN)
try:
assert(SeleniumActions.element_is_visible(web_driver, link_drop_down))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527151 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527152(self):
test_case_number = "18527152"
web_driver = self.fetch_webdriver()
try:
element_path = FeaturedBlocksData.FEATURED_BLOCK_LINK_TYPE
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
SeleniumActions.select_by_index(web_element, "2")
Tools.sleep(2)
link_drop_down = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCK_EXTERNAL_LINK)
try:
assert(SeleniumActions.element_is_visible(web_driver, link_drop_down))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527152 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527172(self):
test_case_number = "18527172"
web_driver = self.fetch_webdriver()
try:
click_select_gallery = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SELECT_FROM_GALLERY)
SeleniumActions.click_element(web_driver, click_select_gallery)
Tools.sleep(3)
click_gallery_image = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SELECT_GALLERY_IMAGE)
SeleniumActions.click_element(web_driver, click_gallery_image)
click_insert_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SELECT_GALLERY_INSERT_BUTTON)
SeleniumActions.click_element(web_driver, click_insert_button)
Tools.sleep(2)
write_block_title = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_BLOCK_TITLE)
SeleniumActions.write_to_element(web_driver, write_block_title, "ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ012")
click_save_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SAVE_BUTTON)
SeleniumActions.click_element(web_driver, click_save_button)
Tools.sleep(2)
element_path = FeaturedBlocksData.ADD_BLOCK_TITLE_ERROR
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
block_title_error = SeleniumActions.read_web_element_text(web_element)
write_block_description = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_BLOCK_DESCRIPTION)
SeleniumActions.write_to_element(web_driver, write_block_description, "ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ012ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ012ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ012")
click_save_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SAVE_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_save_button)
element_path = FeaturedBlocksData.ADD_BLOCK_DESCRIPTION_ERROR
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
block_description_error = SeleniumActions.read_web_element_text(web_element)
try:
assert(block_title_error == "Please enter no more than 100 characters."
and block_description_error == "Please enter no more than 300 characters.")
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527172 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527153(self):
test_case_number = "18527153"
web_driver = self.fetch_webdriver()
try:
write_block_title = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_BLOCK_TITLE)
SeleniumActions.clearTextField(web_driver, write_block_title)
SeleniumActions.write_to_element(web_driver, write_block_title, "Automated")
write_block_description = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_BLOCK_DESCRIPTION)
SeleniumActions.clearTextField(web_driver, write_block_description)
SeleniumActions.write_to_element(web_driver, write_block_description, "This is an automated test.")
write_link_box_text = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_BLOCK_LINK_TEXT_BOX)
SeleniumActions.clearTextField(web_driver, write_link_box_text)
SeleniumActions.write_to_element(web_driver, write_link_box_text, "Black Vinyl 45")
write_external_link_text = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCK_EXTERNAL_LINK)
SeleniumActions.clearTextField(web_driver, write_external_link_text)
SeleniumActions.write_to_element(web_driver, write_external_link_text, "http://www.blackvinyl45.com")
write_block_alt_text = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_ALT_TEXT)
SeleniumActions.clearTextField(web_driver, write_block_alt_text)
SeleniumActions.write_to_element(web_driver, write_block_alt_text, "alt")
click_save_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SAVE_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_save_button)
Tools.sleep(4)
saved_image = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCK_IMAGE)
try:
assert(SeleniumActions.element_is_visible(web_driver, saved_image))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527153 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527162(self):
test_case_number = "18527162"
web_driver = self.fetch_webdriver()
try:
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_EDIT_BUTTON)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(1)
click_modal_no = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.DELETE_FEATURED_BLOCKS_MODAL_CANCEL_BUTTON)
SeleniumActions.click_element(web_driver, click_modal_no)
Tools.sleep(1)
write_block_title = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_BLOCK_TITLE)
SeleniumActions.clearTextField(web_driver, write_block_title)
SeleniumActions.write_to_element(web_driver, write_block_title, "Automated")
write_block_description = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_BLOCK_DESCRIPTION)
SeleniumActions.clearTextField(web_driver, write_block_description)
SeleniumActions.write_to_element(web_driver, write_block_description, "This is an automated test.")
element_path = FeaturedBlocksData.ADD_BLOCK_LINK_APPEARANCE_DROP_DOWN
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
select = Select(web_element)
select.select_by_index("1")
Tools.sleep(2)
link_text = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_BLOCK_LINK_TEXT_LABEL)
read_link_text = SeleniumActions.read_web_element_text(link_text)
try:
assert(read_link_text == "Link text*")
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527162 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527163(self):
test_case_number = "18527163"
web_driver = self.fetch_webdriver()
try:
element_path = FeaturedBlocksData.ADD_BLOCK_LINK_APPEARANCE_DROP_DOWN
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
select = Select(web_element)
select.select_by_index("2")
Tools.sleep(2)
link_text = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_BLOCK_BUTTON_TEXT_LABEL)
read_link_text = SeleniumActions.read_web_element_text(link_text)
try:
assert(read_link_text == "Button text*")
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527163 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521234(self):
test_case_number = "18521234"
web_driver = self.fetch_webdriver()
try:
element_path = FeaturedBlocksData.ADD_BLOCK_LINK_APPEARANCE_DROP_DOWN
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
SeleniumActions.select_by_index(web_element, "0")
click_save_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_SAVE_BUTTON)
SeleniumActions.click_element(web_driver, click_save_button)
Tools.sleep(3)
click_done_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURE_BLOCK_DONE_BUTTON)
SeleniumActions.click_element(web_driver, click_done_button)
web_driver.switch_to.frame(web_driver.find_element_by_xpath(MartindalePageData.MARTINDALE_IFRAME))
Tools.sleep(4)
web_element = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_BLOCK_TITLE)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
test_one = "Passed"
except AssertionError:
test_one = "Failed"
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
click_settings_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_TAB)
SeleniumActions.click_element(web_driver, click_settings_tab)
Tools.sleep(1)
click_show_title = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_BLOCK_TITLE)
SeleniumActions.click_element(web_driver, click_show_title)
click_done_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURE_BLOCK_DONE_BUTTON)
SeleniumActions.click_element(web_driver, click_done_button)
Tools.sleep(4)
web_driver.switch_to.frame(web_driver.find_element_by_xpath(MartindalePageData.MARTINDALE_IFRAME))
try:
assert(SeleniumActions.check_element_exists(web_driver,
"//*[@id=\"ple_column-0\"]/div[3]/div/div/div/div/ul/li/div/a/span[2]"))
test_two = "Failed"
except AssertionError:
test_two = "Passed"
if test_one == "Passed" and test_two == "Passed":
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
else:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527232 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527232(self):
test_case_number = "18527232"
web_driver = self.fetch_webdriver()
try:
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
click_settings_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_TAB)
SeleniumActions.click_element(web_driver, click_settings_tab)
Tools.sleep(1)
click_show_title = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_BLOCK_TITLE)
SeleniumActions.click_element(web_driver, click_show_title)
click_layout_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_TAB)
SeleniumActions.click_element(web_driver, click_layout_tab)
Tools.sleep(1)
element_path = FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_OVERLAY
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
SeleniumActions.move_to_element(web_driver, web_element)
click_layout_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CHANGE_LAYOUT_BUTTON)
SeleniumActions.click_element(web_driver, click_layout_tab)
Tools.sleep(1)
click_layout = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_ONE)
SeleniumActions.click_element(web_driver, click_layout)
click_done_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURE_BLOCK_DONE_BUTTON)
SeleniumActions.click_element(web_driver, click_done_button)
web_driver.switch_to.frame(web_driver.find_element_by_xpath(MartindalePageData.MARTINDALE_IFRAME))
Tools.sleep(4)
element_path = FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
except:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18527232 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521231(self):
test_case_number = "18521231"
web_driver = self.fetch_webdriver()
try:
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
write_block_title = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_TITLE)
SeleniumActions.clearTextField(web_driver, write_block_title)
SeleniumActions.write_to_element(web_driver, write_block_title, "Automated Title")
write_block_caption = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CAPTION)
SeleniumActions.clearTextField(web_driver, write_block_caption)
SeleniumActions.write_to_element(web_driver, write_block_caption, "Automated Caption")
click_done_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURE_BLOCK_DONE_BUTTON)
SeleniumActions.click_element(web_driver, click_done_button)
web_driver.switch_to.frame(web_driver.find_element_by_xpath(MartindalePageData.MARTINDALE_IFRAME))
Tools.sleep(4)
element_path = FeaturedBlocksData.FEATURED_BLOCKS_TITLE
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
test_one = "Passed"
except AssertionError:
test_one = "Failed"
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
click_settings_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_TAB)
SeleniumActions.click_element(web_driver, click_settings_tab)
Tools.sleep(1)
click_show_title = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_TITLE)
SeleniumActions.click_element(web_driver, click_show_title)
click_done_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURE_BLOCK_DONE_BUTTON)
SeleniumActions.click_element(web_driver, click_done_button)
web_driver.switch_to.frame(web_driver.find_element_by_xpath(MartindalePageData.MARTINDALE_IFRAME))
Tools.sleep(4)
try:
assert(SeleniumActions.check_element_exists(web_driver, "//*[@id=\"ple_column-0\"]/div[3]/div/div/div/div[1]/h2"))
test_two = "Failed"
except AssertionError:
test_two = "Passed"
if test_one == "Passed" and test_two == "Passed":
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
else:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521231 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521232(self):
test_case_number = "18521232"
web_driver = self.fetch_webdriver()
try:
element_path = FeaturedBlocksData.FEATURED_BLOCKS_CAPTION_DISPLAY
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
test_one = "Passed"
except AssertionError:
test_one = "Failed"
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
click_settings_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_TAB)
SeleniumActions.click_element(web_driver, click_settings_tab)
Tools.sleep(1)
click_show_title = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_TITLE)
SeleniumActions.click_element(web_driver, click_show_title)
click_show_caption = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_CAPTION)
SeleniumActions.click_element(web_driver, click_show_caption)
click_done_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURE_BLOCK_DONE_BUTTON)
SeleniumActions.click_element(web_driver, click_done_button)
web_driver.switch_to.frame(web_driver.find_element_by_xpath(MartindalePageData.MARTINDALE_IFRAME))
Tools.sleep(4)
element_path = FeaturedBlocksData.FEATURED_BLOCKS_TITLE
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
try:
assert(SeleniumActions.check_element_exists(web_driver, "//*[@id=\"ple_column-0\"]/div[3]/div/div/div/div[1]/h3"))
test_two = "Failed"
except AssertionError:
test_two = "Passed"
if test_one == "Passed" and test_two == "Passed":
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
else:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521232 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18521235(self):
test_case_number = "18521235"
web_driver = self.fetch_webdriver()
try:
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
click_settings_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_TAB)
SeleniumActions.click_element(web_driver, click_settings_tab)
Tools.sleep(1)
click_show_caption = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_CAPTION)
SeleniumActions.click_element(web_driver, click_show_caption)
click_show_description = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_BLOCK_DESCRIPTION)
SeleniumActions.click_element(web_driver, click_show_description)
click_done_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURE_BLOCK_DONE_BUTTON)
SeleniumActions.click_element(web_driver, click_done_button)
web_driver.switch_to.frame(web_driver.find_element_by_xpath(MartindalePageData.MARTINDALE_IFRAME))
Tools.sleep(4)
element_path = FeaturedBlocksData.FEATURED_BLOCKS_DESCRIPTION
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
element_text = SeleniumActions.read_web_element_text(web_element)
try:
assert(element_text == "LEARN MORE")
test_one = "Passed"
except AssertionError:
test_one = "Failed"
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
click_settings_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_TAB)
SeleniumActions.click_element(web_driver, click_settings_tab)
Tools.sleep(1)
click_show_description = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SETTINGS_SHOW_BLOCK_DESCRIPTION)
SeleniumActions.click_element(web_driver, click_show_description)
click_done_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURE_BLOCK_DONE_BUTTON)
SeleniumActions.click_element(web_driver, click_done_button)
web_driver.switch_to.frame(web_driver.find_element_by_xpath(MartindalePageData.MARTINDALE_IFRAME))
Tools.sleep(4)
element_path = FeaturedBlocksData.FEATURED_BLOCKS_DESCRIPTION
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
try:
assert(SeleniumActions.element_is_visible(web_driver, web_element))
test_two = "Passed"
except AssertionError:
test_two = "Failed"
if test_one == "Passed" and test_two == "Passed":
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
else:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
except:
print("C18521235 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
def test_c18527148(self):
test_case_number = "18527148"
web_driver = self.fetch_webdriver()
try:
click_blade_module = SeleniumActions.fetch_web_element(web_driver, MartindalePageData.MODULE)
SeleniumActions.click_element(web_driver, click_blade_module)
Tools.sleep(2)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, MartindalePageData.IFRAME_EDIT_BUTTON_TWO)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(5)
web_driver.switch_to.default_content()
click_layout_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_TAB)
SeleniumActions.click_element(web_driver, click_layout_tab)
Tools.sleep(1)
element_path = FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_OVERLAY
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
SeleniumActions.move_to_element(web_driver, web_element)
change_layout_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CHANGE_LAYOUT_BUTTON)
SeleniumActions.click_element(web_driver, change_layout_button)
Tools.sleep(1)
click_layout = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_TWO)
SeleniumActions.click_element(web_driver, click_layout)
click_content_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_CONTENT_TAB)
SeleniumActions.click_element(web_driver, click_content_tab)
Tools.sleep(1)
click_edit_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_EDIT_BUTTON)
SeleniumActions.click_element(web_driver, click_edit_button)
Tools.sleep(4)
element_path = FeaturedBlocksData.DELETE_FEATURED_BLOCKS_MODAL
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
modal_text = SeleniumActions.read_web_element_text(web_element)
try:
assert(modal_text == "You're about to navigate out of the featured blocks settings")
test_one = "Passed"
except AssertionError:
test_one = "Failed"
click_yes_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_SAVE_CHANGES_YES_BUTTON)
SeleniumActions.click_element(web_driver, click_yes_button)
Tools.sleep(2)
click_cancel_button = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.ADD_CONTENT_CANCEL_BUTTON)
SeleniumActions.click_element(web_driver, click_cancel_button)
Tools.sleep(2)
click_layout_tab = \
SeleniumActions.fetch_web_element(web_driver, FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_TAB)
SeleniumActions.click_element(web_driver, click_layout_tab)
Tools.sleep(2)
element_path = FeaturedBlocksData.FEATURED_BLOCKS_LAYOUT_LABEL
web_element = SeleniumActions.find_by_xpath(web_driver, element_path)
layout_label_text = SeleniumActions.read_web_element_text(web_element)
try:
assert(layout_label_text == "Fly-Up A")
test_two = "Passed"
except AssertionError:
test_two = "Failed"
if test_one == "Passed" and test_two == "Passed":
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().PASS, '')
else:
CommonSetup.report_test_rail(self, test_case_number, TestRailStatus().FAIL, '')
self.case_teardown()
except:
print("C18527148 Not Tested")
e = sys.exc_info()[0]
print("<p>Error: %s</p>" % e)
| 39.168841
| 388
| 0.662559
| 5,289
| 51,037
| 5.980337
| 0.05086
| 0.088207
| 0.103699
| 0.103383
| 0.895795
| 0.883054
| 0.860639
| 0.850617
| 0.829877
| 0.810623
| 0
| 0.020431
| 0.263476
| 51,037
| 1,302
| 389
| 39.198925
| 0.821016
| 0.008484
| 0
| 0.783908
| 0
| 0.002299
| 0.047751
| 0.010865
| 0
| 0
| 0
| 0
| 0.057471
| 1
| 0.031034
| false
| 0.054023
| 0.011494
| 0
| 0.043678
| 0.052874
| 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
| 1
| 0
| 0
| 0
| 0
|
0
| 8
|
c8c798a26b3a6b2a45b7ee42d4230003df155e05
| 186
|
py
|
Python
|
tests/tests.py
|
nephila/django-lock-tokens
|
0be748d9a6a599f75f9e33da506f544de295a3e6
|
[
"MIT"
] | 22
|
2016-10-21T14:14:51.000Z
|
2021-08-30T11:16:20.000Z
|
tests/tests.py
|
nephila/django-lock-tokens
|
0be748d9a6a599f75f9e33da506f544de295a3e6
|
[
"MIT"
] | 16
|
2017-07-25T23:06:01.000Z
|
2021-03-18T13:14:33.000Z
|
tests/tests.py
|
nephila/django-lock-tokens
|
0be748d9a6a599f75f9e33da506f544de295a3e6
|
[
"MIT"
] | 11
|
2017-09-04T17:47:46.000Z
|
2021-12-29T15:51:46.000Z
|
# -*- coding: utf-8
from __future__ import absolute_import
from tests.test_admin import *
from tests.test_api import *
from tests.test_models import *
from tests.test_sessions import *
| 23.25
| 38
| 0.790323
| 28
| 186
| 4.928571
| 0.464286
| 0.289855
| 0.434783
| 0.550725
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006211
| 0.134409
| 186
| 7
| 39
| 26.571429
| 0.850932
| 0.091398
| 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
|
c8d5fcb774564c88ac7e8b95f77ad7446f1dc1ea
| 39
|
py
|
Python
|
utils/dpbench_python/rambo/__init__.py
|
geexie/dpbench
|
7d41409ded3c816f35003bc5aea071852bceb892
|
[
"BSD-2-Clause"
] | 8
|
2021-03-26T15:17:58.000Z
|
2022-01-21T21:56:19.000Z
|
utils/dpbench_python/rambo/__init__.py
|
geexie/dpbench
|
7d41409ded3c816f35003bc5aea071852bceb892
|
[
"BSD-2-Clause"
] | 22
|
2021-03-30T21:20:57.000Z
|
2022-02-22T13:42:17.000Z
|
utils/dpbench_python/rambo/__init__.py
|
geexie/dpbench
|
7d41409ded3c816f35003bc5aea071852bceb892
|
[
"BSD-2-Clause"
] | 7
|
2021-03-23T11:00:43.000Z
|
2022-02-02T12:28:55.000Z
|
from .rambo_python import rambo_python
| 19.5
| 38
| 0.871795
| 6
| 39
| 5.333333
| 0.666667
| 0.6875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102564
| 39
| 1
| 39
| 39
| 0.914286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
cda7346979c106af4766549dbf350d54c9aefab5
| 65
|
py
|
Python
|
instance/config.py
|
trevin-livele/flask-news-App
|
8662737def4dc629f64453fce08b0f39a4ad4526
|
[
"Unlicense"
] | null | null | null |
instance/config.py
|
trevin-livele/flask-news-App
|
8662737def4dc629f64453fce08b0f39a4ad4526
|
[
"Unlicense"
] | null | null | null |
instance/config.py
|
trevin-livele/flask-news-App
|
8662737def4dc629f64453fce08b0f39a4ad4526
|
[
"Unlicense"
] | null | null | null |
#news api key
NEWS_API_KEY = 'ffb788ce77dc47d3aa4d36f8cccc8f43'
| 16.25
| 49
| 0.830769
| 7
| 65
| 7.428571
| 0.571429
| 0.269231
| 0.384615
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.258621
| 0.107692
| 65
| 3
| 50
| 21.666667
| 0.637931
| 0.184615
| 0
| 0
| 0
| 0
| 0.627451
| 0.627451
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
cdad6eed2d3c73aea9dde3c3a244d15081e14922
| 4,814
|
py
|
Python
|
architectures.py
|
Aralas/icassp19
|
5f54e7d6b9818fabf63e87be22786a45c6b2c9fc
|
[
"MIT"
] | null | null | null |
architectures.py
|
Aralas/icassp19
|
5f54e7d6b9818fabf63e87be22786a45c6b2c9fc
|
[
"MIT"
] | null | null | null |
architectures.py
|
Aralas/icassp19
|
5f54e7d6b9818fabf63e87be22786a45c6b2c9fc
|
[
"MIT"
] | null | null | null |
from keras.layers import Dense, Input, Dropout, Conv2D, BatchNormalization, MaxPooling2D, Flatten, Activation
from keras.models import Model
from keras.regularizers import l2
# =====================================================================================
def get_model_baseline(params_learn=None, params_extract=None):
"""
:param params_learn:
:param params_extract:
:return:
"""
input_shape = (1, params_extract.get('patch_len'), params_extract.get('n_mels'))
channel_axis = 1
n_class = params_learn.get('n_classes')
spec_start = Input(shape=input_shape)
spec_x = spec_start
# l1
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = Conv2D(24, (5, 5),
padding='same', # fmap has same size as input
kernel_initializer='he_normal',
data_format='channels_first')(spec_x)
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = MaxPooling2D(pool_size=(4, 2), data_format="channels_first")(spec_x)
# l2
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = Conv2D(48, (5, 5),
padding='same', # fmap has same size as input
kernel_initializer='he_normal',
data_format='channels_first')(spec_x)
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = MaxPooling2D(pool_size=(4, 2), data_format="channels_first")(spec_x)
# l3
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = Conv2D(48, (5, 5),
padding='same', # fmap has same size as input
kernel_initializer='he_normal',
data_format='channels_first')(spec_x)
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = Flatten()(spec_x)
spec_x = Dropout(0.5)(spec_x)
spec_x = Dense(64,
kernel_initializer='he_normal',
kernel_regularizer=l2(1e-3),
activation='relu',
name='dense_1')(spec_x)
spec_x = Dropout(0.5)(spec_x)
out = Dense(n_class,
kernel_initializer='he_normal',
kernel_regularizer=l2(1e-3),
activation='softmax',
name='prediction')(spec_x)
model = Model(inputs=spec_start, outputs=out)
return model
def get_model_binary(params_learn=None, params_extract=None):
"""
:param params_learn:
:param params_extract:
:return:
"""
input_shape = (1, params_extract.get('patch_len'), params_extract.get('n_mels'))
channel_axis = 1
n_class = 1
spec_start = Input(shape=input_shape)
spec_x = spec_start
# l1
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = Conv2D(24, (5, 5),
padding='same', # fmap has same size as input
kernel_initializer='he_normal',
data_format='channels_first')(spec_x)
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = MaxPooling2D(pool_size=(4, 2), data_format="channels_first")(spec_x)
# l2
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = Conv2D(48, (5, 5),
padding='same', # fmap has same size as input
kernel_initializer='he_normal',
data_format='channels_first')(spec_x)
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = MaxPooling2D(pool_size=(4, 2), data_format="channels_first")(spec_x)
# l3
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = Conv2D(48, (5, 5),
padding='same', # fmap has same size as input
kernel_initializer='he_normal',
data_format='channels_first')(spec_x)
spec_x = BatchNormalization(axis=1)(spec_x)
spec_x = Activation('relu')(spec_x)
spec_x = Flatten()(spec_x)
spec_x = Dropout(0.5)(spec_x)
spec_x = Dense(64,
kernel_initializer='he_normal',
kernel_regularizer=l2(1e-3),
activation='relu',
name='dense_1')(spec_x)
spec_x = Dropout(0.5)(spec_x)
out = Dense(n_class,
kernel_initializer='he_normal',
kernel_regularizer=l2(1e-3),
activation='sigmoid',
name='prediction')(spec_x)
model = Model(inputs=spec_start, outputs=out)
return model
| 32.972603
| 109
| 0.592646
| 610
| 4,814
| 4.388525
| 0.121311
| 0.164363
| 0.127755
| 0.134479
| 0.918192
| 0.918192
| 0.918192
| 0.918192
| 0.918192
| 0.918192
| 0
| 0.02675
| 0.270046
| 4,814
| 146
| 110
| 32.972603
| 0.73506
| 0.078521
| 0
| 0.907216
| 0
| 0
| 0.090743
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.020619
| false
| 0
| 0.030928
| 0
| 0.072165
| 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
|
cde498781415c87e370cc05b5e3d87c74b8cc4d0
| 158
|
py
|
Python
|
pydigilent/lowlevel/__init__.py
|
greedysquid/pydigilent
|
8ec18dcf97602038ee57b35365dfd9df86e5f72e
|
[
"MIT"
] | 7
|
2015-01-09T21:39:14.000Z
|
2020-04-06T07:32:01.000Z
|
pydigilent/lowlevel/__init__.py
|
greedysquid/pydigilent
|
8ec18dcf97602038ee57b35365dfd9df86e5f72e
|
[
"MIT"
] | 2
|
2018-05-06T09:35:43.000Z
|
2018-10-23T14:15:56.000Z
|
pydigilent/lowlevel/__init__.py
|
greedysquid/pydigilent
|
8ec18dcf97602038ee57b35365dfd9df86e5f72e
|
[
"MIT"
] | 5
|
2015-01-13T21:15:15.000Z
|
2019-07-03T13:08:03.000Z
|
from pydigilent.lowlevel.common import *
from pydigilent.lowlevel.djtg import *
from pydigilent.lowlevel.dmgr import *
from pydigilent.lowlevel.depp import *
| 31.6
| 40
| 0.822785
| 20
| 158
| 6.5
| 0.4
| 0.430769
| 0.676923
| 0.646154
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.101266
| 158
| 4
| 41
| 39.5
| 0.915493
| 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
|
b54eefeeba2fbb3c34a2facc438ea799f9bafc5d
| 31,288
|
py
|
Python
|
packages/gtmapi/lmsrvlabbook/tests/snapshots/snap_test_environment_base_image_queries.py
|
gigabackup/gigantum-client
|
70fe6b39b87b1c56351f2b4c551b6f1693813e4f
|
[
"MIT"
] | 60
|
2018-09-26T15:46:00.000Z
|
2021-10-10T02:37:14.000Z
|
packages/gtmapi/lmsrvlabbook/tests/snapshots/snap_test_environment_base_image_queries.py
|
gigabackup/gigantum-client
|
70fe6b39b87b1c56351f2b4c551b6f1693813e4f
|
[
"MIT"
] | 1,706
|
2018-09-26T16:11:22.000Z
|
2021-08-20T13:37:59.000Z
|
packages/gtmapi/lmsrvlabbook/tests/snapshots/snap_test_environment_base_image_queries.py
|
griffinmilsap/gigantum-client
|
70fe6b39b87b1c56351f2b4c551b6f1693813e4f
|
[
"MIT"
] | 11
|
2019-03-14T13:23:51.000Z
|
2022-01-25T01:29:16.000Z
|
# -*- coding: utf-8 -*-
# snapshottest: v1 - https://goo.gl/zC4yUc
from __future__ import unicode_literals
from snapshottest import Snapshot
snapshots = Snapshot()
snapshots['TestEnvironmentBaseImageQueries.test_get_base_image_by_node 1'] = {
'data': {
'node': {
'componentId': 'quickstart-jupyterlab',
'description': 'Data Science Quickstart using Jupyterlab, numpy, and Matplotlib. A great base for any analysis.',
'developmentTools': [
'jupyterlab'
],
'dockerImageNamespace': 'gigantum',
'dockerImageRepository': 'python3-minimal',
'dockerImageServer': 'hub.docker.com',
'dockerImageTag': '826b6f24-2018-02-09',
'icon': 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=',
'id': 'QmFzZUNvbXBvbmVudDpnaWdhbnR1bV9iYXNlLWltYWdlcy10ZXN0aW5nJnF1aWNrc3RhcnQtanVweXRlcmxhYiYx',
'languages': [
'python3'
],
'license': 'MIT',
'name': 'Data Science Quickstart with JupyterLab',
'osClass': 'ubuntu',
'osRelease': '16.04',
'packageManagers': [
'apt',
'pip3'
],
'readme': 'Empty for now',
'tags': [
'ubuntu',
'python3',
'jupyterlab'
],
'url': None
}
}
}
snapshots['TestEnvironmentBaseImageQueries.test_get_available_base_images 1'] = {
'data': {
'availableBases': {
'edges': [
{
'node': {
'componentId': 'quickstart-jupyterlab',
'cudaVersion': None,
'description': 'Data Science Quickstart using Jupyterlab, numpy, and Matplotlib. A great base for any analysis.',
'developmentTools': [
'jupyterlab'
],
'dockerImageNamespace': 'gigantum',
'dockerImageRepository': 'python3-minimal',
'dockerImageServer': 'hub.docker.com',
'dockerImageTag': '1effaaea-2018-05-23',
'icon': 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=',
'id': 'QmFzZUNvbXBvbmVudDpnaWdhbnR1bV9iYXNlLWltYWdlcy10ZXN0aW5nJnF1aWNrc3RhcnQtanVweXRlcmxhYiYy',
'installedPackages': [
'apt|vim|2:7.4.1689-3ubuntu1.2',
'pip3|numpy|1.14.0',
'pip3|matplotlib|2.1.1',
'pip3|jupyter|1.0.0',
'pip3|jupyterlab|0.31.1',
'pip3|ipywidgets|7.1.0',
'pip3|pandas|0.22.0'
],
'languages': [
'python3'
],
'license': 'MIT',
'name': 'Data Science Quickstart with JupyterLab',
'osClass': 'ubuntu',
'osRelease': '18.04',
'packageManagers': [
'apt',
'pip3'
],
'readme': 'Empty for now',
'revision': 2,
'schema': 1,
'tags': [
'ubuntu',
'python3',
'jupyterlab'
],
'url': None
}
},
{
'node': {
'componentId': 'ut-busybox',
'cudaVersion': None,
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'tags': [
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'url': None
}
},
{
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the "discuss" link (in the lower-right "?" bubble in the app) if you\'d like
some guidance!
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}
}
}
snapshots['TestEnvironmentBaseImageQueries.test_get_available_base_images_pagination 1'] = {
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snapshots['TestEnvironmentBaseImageQueries.test_get_available_base_images_pagination 2'] = {
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snapshots['TestEnvironmentBaseImageQueries.test_get_available_base_images_pagination 3'] = {
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}
snapshots['TestEnvironmentBaseImageQueries.test_get_available_base_images_pagination_reverse 1'] = {
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*RStudio® and the RStudio logo are registered trademarks of RStudio, Inc.*
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b561841a68441aa96796ec9055f52b4938c81cd8
| 34,843
|
py
|
Python
|
tests/integration/test_portia.py
|
AgrinessEdgeIoT/portiapy
|
efc5e4af2d94c57aa03b447ee015755532baaf70
|
[
"MIT"
] | 1
|
2019-05-22T18:38:01.000Z
|
2019-05-22T18:38:01.000Z
|
tests/integration/test_portia.py
|
AgrinessEdgeIoT/portiapy
|
efc5e4af2d94c57aa03b447ee015755532baaf70
|
[
"MIT"
] | 4
|
2018-09-17T13:16:18.000Z
|
2021-02-26T13:30:49.000Z
|
tests/integration/test_portia.py
|
AgrinessEdgeIoT/portiapy
|
efc5e4af2d94c57aa03b447ee015755532baaf70
|
[
"MIT"
] | null | null | null |
"""Integration testing for the application's portia module.
"""
import os
import unittest
from portiapy import portia
from dotenv import load_dotenv, find_dotenv
load_dotenv(find_dotenv())
class TestEdgeDevice(unittest.TestCase):
"""Set of integration tests for all functions concerning the EdgeDevice
instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_ports(self):
ports = self.portia_api.device('2DPEQ572HEXP').ports(params={
'from': None,
'to': None,
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
self.assertListEqual(ports, [0, 1, 2, 4, 5, 8, 9, 10, 11, 12, 13])
def test_ports_last(self):
ports = self.portia_api.device('2DPEQ572HEXP').ports(
last=True,
params={
'from': None,
'to': None,
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertListEqual(
ports['port'].tolist(), [0, 1, 2, 4, 5, 8, 9, 10, 11, 12, 13]
)
self.assertListEqual(
ports['dimension_thing_code'].tolist(),
[69, 15, 15, 16, 16, 22, 22, 22, 23, 68, 68]
)
def test_profile(self):
device = self.portia_api.device('2DPEQ572HEXP').profile(params={
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
self.assertEqual(device.get('device'), '2DPEQ572HEXP')
self.assertEqual(device.get('channel_id'), '1BTU7542G5EY')
self.assertEqual(device.get('channel_code'), 14)
self.assertEqual(device.get('thing_code'), 69)
self.assertEqual(len(device.get('ports')), 9)
class TestEdgeDevicePort(unittest.TestCase):
"""Set of integration tests for all functions concerning the EdgeDevicePort
instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_sensors(self):
sensors = self.portia_api.device('2DPEQ572HEXP').port(1).sensors(
params={
'from': None,
'to': None,
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertListEqual(sensors, [1])
def test_sensors_last(self):
sensors = self.portia_api.device('2DPEQ572HEXP').port(1).sensors(
last=True,
params={
'from': None,
'to': None,
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(sensors.iloc[0]['sensor'], 1)
self.assertEqual(sensors.iloc[0]['dimension_code'], 1)
self.assertEqual(sensors.iloc[0]['dimension_unity_code'], 1)
self.assertEqual(sensors.iloc[0]['dimension_thing_code'], 15)
humanized_sensors = sensors.humanize()
self.assertEqual(humanized_sensors.iloc[0]['sensor'], 1)
self.assertEqual(
humanized_sensors.iloc[0]['dimension_code'], 1
)
self.assertEqual(
humanized_sensors.iloc[0]['dimension'], 'Point Temperature'
)
self.assertEqual(
humanized_sensors.iloc[0]['dimension_unity_code'], 1
)
self.assertEqual(
humanized_sensors.iloc[0]['dimension_unity'], '°C'
)
self.assertEqual(
humanized_sensors.iloc[0]['dimension_thing_code'], 15
)
self.assertEqual(
humanized_sensors.iloc[0]['dimension_thing'], 'Sensor_Inobram_T'
)
def test_dimensions(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(1).dimensions(
params={
'from': None,
'to': None,
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertListEqual(dimensions, [1, 9])
def test_dimensions_last(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(1).dimensions(
last=True,
params={
'from': None,
'to': None,
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(dimensions.iloc[0]['sensor'], 1)
self.assertEqual(dimensions.iloc[0]['dimension_code'], 1)
self.assertEqual(dimensions.iloc[0]['dimension_thing_code'], 15)
self.assertEqual(dimensions.iloc[1]['sensor'], 1)
self.assertEqual(dimensions.iloc[1]['dimension_code'], 9)
self.assertEqual(dimensions.iloc[1]['dimension_thing_code'], 15)
humanized_dimensions = dimensions.humanize()
self.assertEqual(humanized_dimensions.iloc[0]['sensor'], 1)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension_code'], 1
)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension'], 'Point Temperature'
)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension_thing_code'], 15
)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension_thing'], 'Sensor_Inobram_T'
)
self.assertEqual(humanized_dimensions.iloc[1]['sensor'], 1)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension_code'], 9
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension'],
'Point Water Temperature'
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension_thing_code'], 15
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension_thing'], 'Sensor_Inobram_T'
)
def test_profile(self):
port = self.portia_api.device('2DPEQ572HEXP').port(4).profile(params={
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
self.assertEqual(port.get('device'), '2DPEQ572HEXP')
self.assertEqual(port.get('channel_id'), '1BTU7542G5EY')
self.assertEqual(port.get('channel_code'), 14)
self.assertEqual(port.get('thing_code'), 69)
self.assertEqual(len(port.get('ports')), 1)
self.assertEqual(len(port.get('ports')[0].get('sensors')), 2)
class TestEdgeDeviceSensor(unittest.TestCase):
"""Set of integration tests for all functions concerning the
EdgeDeviceSensor instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_dimensions(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(1).sensor(1) \
.dimensions(
params={
'from': None,
'to': None,
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertListEqual(dimensions, [1, 9])
def test_dimensions_last(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(1).sensor(1) \
.dimensions(
last=True,
params={
'from': None,
'to': None,
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(dimensions.iloc[0]['dimension_code'], 1)
self.assertEqual(dimensions.iloc[0]['dimension_unity_code'], 1)
self.assertEqual(dimensions.iloc[0]['dimension_thing_code'], 15)
self.assertEqual(dimensions.iloc[1]['dimension_code'], 9)
self.assertEqual(dimensions.iloc[1]['dimension_unity_code'], 1)
self.assertEqual(dimensions.iloc[1]['dimension_thing_code'], 15)
humanized_dimensions = dimensions.humanize()
self.assertEqual(
humanized_dimensions.iloc[0]['dimension_code'], 1
)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension'], 'Point Temperature'
)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension_unity_code'], 1
)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension_unity'], '°C'
)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension_thing_code'], 15
)
self.assertEqual(
humanized_dimensions.iloc[0]['dimension_thing'], 'Sensor_Inobram_T'
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension_code'], 9
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension'],
'Point Water Temperature'
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension_unity_code'], 1
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension_unity'], '°C'
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension_thing_code'], 15
)
self.assertEqual(
humanized_dimensions.iloc[1]['dimension_thing'], 'Sensor_Inobram_T'
)
def test_profile(self):
sensor = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1). \
profile(params={
'sort': True,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
self.assertEqual(sensor.get('device'), '2DPEQ572HEXP')
self.assertEqual(sensor.get('channel_id'), '1BTU7542G5EY')
self.assertEqual(sensor.get('channel_code'), 14)
self.assertEqual(sensor.get('thing_code'), 69)
self.assertEqual(len(sensor.get('ports')), 1)
self.assertEqual(len(sensor.get('ports')[0].get('sensors')), 1)
def test_select(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(4) \
.sensor(1).select(params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in dimensions.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
for i, row in dimensions.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
def test_select_last(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(4) \
.sensor(1).select(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(dimensions.iloc[0].dimension_thing_code, 16)
self.assertEqual(dimensions.iloc[0].dimension_unity_code, 1)
self.assertEqual(dimensions.iloc[0].dimension_code, 1)
humanized_dimensions = dimensions.humanize()
self.assertEqual(
humanized_dimensions.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension, 'Point Temperature'
)
def test_summary(self):
summarized_dimensions = self.portia_api.device('2DPEQ572HEXP') \
.port(4).sensor(1).summary(params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'offset': 0,
'fill': None,
'order': None,
'limit': None,
'avg': True,
'min': True,
'max': True,
'sum': False,
'median': False,
'mode': False,
'stddev': False,
'spread': False,
'last_timestamp': False,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in summarized_dimensions.iterrows():
self.assertEqual(row.dimension_unity_code, 1)
for i, row in summarized_dimensions.humanize().iterrows():
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
def test_events(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4) \
.sensor(1).events(params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in events.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.event_code, 1)
for i, row in events.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
self.assertEqual(row.event_code, 1)
self.assertEqual(row.event, 'Communication State')
def test_events_last(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4) \
.sensor(1).events(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(events.iloc[0].dimension_thing_code, 16)
self.assertEqual(events.iloc[0].dimension_unity_code, 1)
self.assertEqual(events.iloc[0].dimension_code, 1)
self.assertEqual(events.iloc[0].event_code, 1)
humanized_events = events.humanize()
self.assertEqual(
humanized_events.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_events.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_events.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension, 'Point Temperature'
)
self.assertEqual(
humanized_events.iloc[0].event_code, 1
)
self.assertEqual(
humanized_events.iloc[0].event, 'Communication State'
)
class TestEdgeDeviceDimensionFromDevice(unittest.TestCase):
"""Set of integration tests for all functions concerning the
EdgeDeviceDimensionFromDevice instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_summary(self):
summarized_dimensions = self.portia_api.device('2DPEQ572HEXP') \
.dimension(1).summary(None, params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'offset': 0,
'fill': None,
'order': None,
'limit': None,
'avg': True,
'min': True,
'max': True,
'sum': False,
'median': False,
'mode': False,
'stddev': False,
'spread': False,
'last_timestamp': False,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in summarized_dimensions.iterrows():
self.assertEqual(row.dimension_unity_code, 1)
for i, row in summarized_dimensions.humanize().iterrows():
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
class TestEdgeDeviceDimensionFromPort(unittest.TestCase):
"""Set of integration tests for all functions concerning the
EdgeDeviceDimensionFromPort instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_select(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(4) \
.dimension(1).select(params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in dimensions.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
for i, row in dimensions.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
def test_select_last(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(4) \
.dimension(1).select(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(dimensions.iloc[0].dimension_thing_code, 16)
self.assertEqual(dimensions.iloc[0].dimension_unity_code, 1)
self.assertEqual(dimensions.iloc[0].dimension_code, 1)
humanized_dimensions = dimensions.humanize()
self.assertEqual(
humanized_dimensions.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension, 'Point Temperature'
)
def test_events(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4) \
.dimension(1).events(params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in events.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.event_code, 1)
for i, row in events.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
self.assertEqual(row.event_code, 1)
self.assertEqual(row.event, 'Communication State')
def test_events_last(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4) \
.dimension(1).events(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(events.iloc[0].dimension_thing_code, 16)
self.assertEqual(events.iloc[0].dimension_unity_code, 1)
self.assertEqual(events.iloc[0].dimension_code, 1)
self.assertEqual(events.iloc[0].event_code, 1)
humanized_events = events.humanize()
self.assertEqual(
humanized_events.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_events.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_events.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension, 'Point Temperature'
)
self.assertEqual(
humanized_events.iloc[0].event_code, 1
)
self.assertEqual(
humanized_events.iloc[0].event, 'Communication State'
)
class TestEdgeDeviceDimensionFromSensor(unittest.TestCase):
"""Set of integration tests for all functions concerning the
EdgeDeviceDimensionFromSensor instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_select(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1) \
.dimension(1).select(params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in dimensions.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
for i, row in dimensions.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
def test_select_last(self):
dimensions = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1) \
.dimension(1).select(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(dimensions.iloc[0].dimension_thing_code, 16)
self.assertEqual(dimensions.iloc[0].dimension_unity_code, 1)
self.assertEqual(dimensions.iloc[0].dimension_code, 1)
humanized_dimensions = dimensions.humanize()
self.assertEqual(
humanized_dimensions.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_dimensions.iloc[0].dimension, 'Point Temperature'
)
def test_summary(self):
summarized_dimensions = self.portia_api.device('2DPEQ572HEXP') \
.port(4).sensor(1).dimension(1).summary(params={
'from': 1609470000000,
'to': 1609729199000,
'lower_bound': None,
'upper_bound': None,
'offset': 0,
'fill': None,
'order': None,
'limit': None,
'avg': True,
'min': True,
'max': True,
'sum': False,
'median': False,
'mode': False,
'stddev': False,
'spread': False,
'last_timestamp': False,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in summarized_dimensions.iterrows():
self.assertEqual(row.dimension_unity_code, 1)
for i, row in summarized_dimensions.humanize().iterrows():
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
def test_events(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1) \
.dimension(1).events(params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in events.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.event_code, 1)
for i, row in events.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
self.assertEqual(row.event_code, 1)
self.assertEqual(row.event, 'Communication State')
def test_events_last(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1) \
.dimension(1).events(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(events.iloc[0].dimension_thing_code, 16)
self.assertEqual(events.iloc[0].dimension_unity_code, 1)
self.assertEqual(events.iloc[0].dimension_code, 1)
self.assertEqual(events.iloc[0].event_code, 1)
humanized_events = events.humanize()
self.assertEqual(
humanized_events.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_events.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_events.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension, 'Point Temperature'
)
self.assertEqual(
humanized_events.iloc[0].event_code, 1
)
self.assertEqual(
humanized_events.iloc[0].event, 'Communication State'
)
class TestEdgeDeviceEventFromSensor(unittest.TestCase):
"""Set of integration tests for all functions concerning the
EdgeDeviceEventFromSensor instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_events(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1) \
.event(1).events(params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in events.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.event_code, 1)
for i, row in events.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
self.assertEqual(row.event_code, 1)
self.assertEqual(row.event, 'Communication State')
def test_events_last(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1) \
.event(1).events(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(events.iloc[0].dimension_thing_code, 16)
self.assertEqual(events.iloc[0].dimension_unity_code, 1)
self.assertEqual(events.iloc[0].dimension_code, 1)
self.assertEqual(events.iloc[0].event_code, 1)
humanized_events = events.humanize()
self.assertEqual(
humanized_events.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_events.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_events.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension, 'Point Temperature'
)
self.assertEqual(
humanized_events.iloc[0].event_code, 1
)
self.assertEqual(
humanized_events.iloc[0].event, 'Communication State'
)
class TestEdgeDeviceEventFromDimension(unittest.TestCase):
"""Set of integration tests for all functions concerning the
EdgeDeviceEventFromDimension instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_events(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4).dimension(1) \
.event(1).events(params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in events.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.event_code, 1)
for i, row in events.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
self.assertEqual(row.event_code, 1)
self.assertEqual(row.event, 'Communication State')
def test_events_last(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4).dimension(1) \
.event(1).events(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(events.iloc[0].dimension_thing_code, 16)
self.assertEqual(events.iloc[0].dimension_unity_code, 1)
self.assertEqual(events.iloc[0].dimension_code, 1)
self.assertEqual(events.iloc[0].event_code, 1)
humanized_events = events.humanize()
self.assertEqual(
humanized_events.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_events.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_events.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension, 'Point Temperature'
)
self.assertEqual(
humanized_events.iloc[0].event_code, 1
)
self.assertEqual(
humanized_events.iloc[0].event, 'Communication State'
)
class TestEdgeDeviceEventFromSensorDimension(unittest.TestCase):
"""Set of integration tests for all functions concerning the
EdgeDeviceEventFromSensorDimension instance.
"""
@classmethod
def setUpClass(cls):
"""Creates a Portia configuration to test the instance.
"""
# Settings for test
base_url = os.getenv('PORTIA_URL', 'https://api-portia.agriness.io/v3')
token = os.getenv('PORTIA_TOKEN')
# Creating Portia API instance
cls.portia_api = portia.PortiaApi({
'baseurl': base_url,
'authorization': token,
'debug': False,
'Accept': 'text/csv'
})
def test_events(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1) \
.dimension(1).event(1).events(params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
})
for i, row in events.iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.event_code, 1)
for i, row in events.humanize().iterrows():
self.assertEqual(row.dimension_thing_code, 16)
self.assertEqual(row.dimension_thing, 'Sensor_Inobram_TU')
self.assertEqual(row.dimension_unity_code, 1)
self.assertEqual(row.dimension_unity, '°C')
self.assertEqual(row.dimension_code, 1)
self.assertEqual(row.dimension, 'Point Temperature')
self.assertEqual(row.event_code, 1)
self.assertEqual(row.event, 'Communication State')
def test_events_last(self):
events = self.portia_api.device('2DPEQ572HEXP').port(4).sensor(1) \
.dimension(1).event(1).events(
last=True,
params={
'from': 1609470000000,
'to': 1609729199000,
'order': None,
'limit': None,
'precision': 'ms',
'timezone': 'Etc/UTC'
}
)
self.assertEqual(events.iloc[0].dimension_thing_code, 16)
self.assertEqual(events.iloc[0].dimension_unity_code, 1)
self.assertEqual(events.iloc[0].dimension_code, 1)
self.assertEqual(events.iloc[0].event_code, 1)
humanized_events = events.humanize()
self.assertEqual(
humanized_events.iloc[0].dimension_thing_code, 16
)
self.assertEqual(
humanized_events.iloc[0].dimension_thing, 'Sensor_Inobram_TU'
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension_unity, '°C'
)
self.assertEqual(
humanized_events.iloc[0].dimension_code, 1
)
self.assertEqual(
humanized_events.iloc[0].dimension, 'Point Temperature'
)
self.assertEqual(
humanized_events.iloc[0].event_code, 1
)
self.assertEqual(
humanized_events.iloc[0].event, 'Communication State'
)
if __name__ == '__main__':
unittest.main()
| 29.108605
| 76
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0
| 7
|
b59e1d7259c42a73090662cd85d800bf76b71d21
| 4,108
|
py
|
Python
|
paratransit/api/migrations/0005_auto_20170413_0505.py
|
NiJeLorg/paratransit_api
|
f3e1cfd922e58c6c539a9c11c29d04e4bdd701f2
|
[
"MIT"
] | null | null | null |
paratransit/api/migrations/0005_auto_20170413_0505.py
|
NiJeLorg/paratransit_api
|
f3e1cfd922e58c6c539a9c11c29d04e4bdd701f2
|
[
"MIT"
] | null | null | null |
paratransit/api/migrations/0005_auto_20170413_0505.py
|
NiJeLorg/paratransit_api
|
f3e1cfd922e58c6c539a9c11c29d04e4bdd701f2
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2017-04-13 05:05
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('api', '0004_auto_20170413_0458'),
]
operations = [
migrations.AlterField(
model_name='trips',
name='d_a_pop',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_d_pop',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_lat',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_lon',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_nr_bus',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_nr_hea',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_nr_sub',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_p_pop',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_xcoord',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='d_ycoord',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='osrm_dist',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='osrmminsdelta',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_a_pop',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_d_pop',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_lat',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_lon',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_nr_bus',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_nr_hea',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_nr_sub',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_p_pop',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_xcoord',
field=models.FloatField(blank=True, default=0, null=True),
),
migrations.AlterField(
model_name='trips',
name='p_ycoord',
field=models.FloatField(blank=True, default=0, null=True),
),
]
| 32.603175
| 70
| 0.5426
| 421
| 4,108
| 5.144893
| 0.133017
| 0.203139
| 0.253924
| 0.294552
| 0.90397
| 0.90397
| 0.90397
| 0.885965
| 0.885965
| 0.885965
| 0
| 0.019658
| 0.331305
| 4,108
| 125
| 71
| 32.864
| 0.768839
| 0.016066
| 0
| 0.745763
| 1
| 0
| 0.074276
| 0.005694
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.016949
| 0
| 0.042373
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 11
|
b5ad817e5402359d3aaa235ec2e112b5f5992fdc
| 700
|
py
|
Python
|
Python/0-references/dunder_functions_template_compare.py
|
Tombmyst/Empire
|
f28782787c5fa9127e353549b73ec90d3c82c003
|
[
"Apache-2.0"
] | null | null | null |
Python/0-references/dunder_functions_template_compare.py
|
Tombmyst/Empire
|
f28782787c5fa9127e353549b73ec90d3c82c003
|
[
"Apache-2.0"
] | null | null | null |
Python/0-references/dunder_functions_template_compare.py
|
Tombmyst/Empire
|
f28782787c5fa9127e353549b73ec90d3c82c003
|
[
"Apache-2.0"
] | null | null | null |
from typing import *
def __eq__(self, other: Any) -> bool:
try:
pass # TODO compare
except:
return False
def __ne__(self, other: Any) -> bool:
return not (self == other)
def __gt__(self, other: Any) -> bool:
try:
pass # TODO compare
except:
return False
def __ge__(self, other: Any) -> bool:
try:
pass # TODO compare
except:
return False
def __lt__(self, other: Any) -> bool:
try:
return not (self >= other)
except:
return False
def __le__(self, other: Any) -> bool:
try:
return not (self > other)
except:
return False
| 16.666667
| 38
| 0.521429
| 80
| 700
| 4.2625
| 0.275
| 0.237537
| 0.211144
| 0.281525
| 0.791789
| 0.791789
| 0.791789
| 0.791789
| 0.791789
| 0.791789
| 0
| 0
| 0.382857
| 700
| 41
| 39
| 17.073171
| 0.789352
| 0.054286
| 0
| 0.642857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.02439
| 0
| 1
| 0.214286
| false
| 0.107143
| 0.035714
| 0.035714
| 0.535714
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 12
|
b5b23f5251a31aa43b718935fb8ff0544c4fd865
| 210
|
py
|
Python
|
ads/fundamentals/__init__.py
|
Aminul-Momin/Algorithms_and_Data_Structures
|
cba73b36b73ad92fb34bc34a0e03503f7a137713
|
[
"MIT"
] | null | null | null |
ads/fundamentals/__init__.py
|
Aminul-Momin/Algorithms_and_Data_Structures
|
cba73b36b73ad92fb34bc34a0e03503f7a137713
|
[
"MIT"
] | null | null | null |
ads/fundamentals/__init__.py
|
Aminul-Momin/Algorithms_and_Data_Structures
|
cba73b36b73ad92fb34bc34a0e03503f7a137713
|
[
"MIT"
] | null | null | null |
from .bag import *
from .doubly_linked_list import *
from .resizing_array_stack import *
from .resizing_array_queue import *
from .singly_linked_list import *
from .disjoint_sets import *
from ._nodes import *
| 26.25
| 35
| 0.8
| 30
| 210
| 5.266667
| 0.466667
| 0.379747
| 0.202532
| 0.253165
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133333
| 210
| 7
| 36
| 30
| 0.868132
| 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
|
a98f197d830c75c860254d032e4dbda7b170f363
| 17,321
|
py
|
Python
|
unit_tests/appzoo_tests/test_ez_text_classify.py
|
WyAzx/EasyTransfer
|
d3b5493d7c4fd344787088330ba86519232ec98d
|
[
"Apache-2.0"
] | 13
|
2020-09-19T13:12:48.000Z
|
2021-11-15T09:40:13.000Z
|
unit_tests/appzoo_tests/test_ez_text_classify.py
|
WyAzx/EasyTransfer
|
d3b5493d7c4fd344787088330ba86519232ec98d
|
[
"Apache-2.0"
] | 1
|
2020-09-24T15:19:13.000Z
|
2020-09-24T15:19:13.000Z
|
unit_tests/appzoo_tests/test_ez_text_classify.py
|
CLUEbenchmark/EasyTransfer
|
866be7c6b32d39f78302d45a9a65aefbe673e1ea
|
[
"Apache-2.0"
] | 7
|
2020-11-20T02:44:59.000Z
|
2021-06-23T05:31:48.000Z
|
# coding=utf-8
# Copyright (c) 2019 Alibaba PAI team.
#
# 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 os
import subprocess
import shutil
import unittest
class TestEzTextClassify(unittest.TestCase):
def test_1_train_mode(self):
argvs = ['easy_transfer_app',
'--mode', 'train',
'--inputTable', '../ut_data/ez_text_classify/train.csv,../ut_data/ez_text_classify/dev.csv',
'--inputSchema', "example_id:int:1,content:str:1,label:str:1,label_str:str:1,keywords:str:1",
'--firstSequence', 'content',
'--labelName', 'label',
'--labelEnumerateValues', '100,101,102,103,104,105,106,107,108,109,110,112,113,114,115,116',
'--checkpointDir', 'ez_text_classify_models',
'--numEpochs', '1',
'--batchSize', '5',
'--optimizerType', 'adam',
'--learningRate', '2e-5',
'--modelName', 'text_classify_bert',
'--distributionStrategy', 'none',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1',
'--advancedParameters', """'
pretrain_model_name_or_path=google-bert-base-zh # For BERT
log_step_count_steps=100
throttle_secs=100
keep_checkpoint_max=10
lr_decay=polynomial
warmup_ratio=0.1
weight_decay_ratio=0
gradient_clip=true
num_accumulated_batches=1
eval_batch_size=256
'
"""
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
def test_2_predict_mode(self):
argvs = ['easy_transfer_app',
'--mode', 'predict',
'--inputTable', '../ut_data/ez_text_classify/dev.csv',
'--outputTable', 'ez_text_classify.pred.csv',
'--inputSchema', 'example_id:int:1,content:str:1,label:str:1,label_str:str:1,keywords:str:1',
'--firstSequence', 'content',
'--appendCols', 'example_id,keywords,label_str',
'--outputSchema', 'predictions,probabilities,logits',
'--checkpointPath', 'ez_text_classify_models/',
'--batchSize', '100',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1',
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
self.assertTrue(os.path.exists('ez_text_classify.pred.csv'))
os.remove('ez_text_classify.pred.csv')
def test_3_evaluate_mode(self):
argvs = ['easy_transfer_app',
'--mode', 'evaluate',
'--inputTable', '../ut_data/ez_text_classify/dev.csv',
'--checkpointPath', 'ez_text_classify_models/model.ckpt-0',
'--batchSize', '100'
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
def test_4_export_predict_mode(self):
argvs = ['easy_transfer_app',
'--mode', 'export',
'--checkpointPath', 'ez_text_classify_models/model.ckpt-0',
'--exportType', 'app_model',
'--exportDirBase', 'ez_text_classify_models/saved_app_model/',
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
argvs = ['easy_transfer_app',
'--mode', 'predict',
'--inputTable', '../ut_data/ez_text_classify/dev.csv',
'--outputTable', 'ez_text_classify.pred.csv',
'--inputSchema', 'example_id:int:1,content:str:1,label:str:1,label_str:str:1,keywords:str:1',
'--firstSequence', 'content',
'--appendCols', 'example_id,keywords,label_str',
'--outputSchema', 'predictions,probabilities,logits',
'--checkpointPath', 'ez_text_classify_models/saved_app_model',
'--batchSize', '100',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1',
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
self.assertTrue(os.path.exists('ez_text_classify.pred.csv'))
os.remove('ez_text_classify.pred.csv')
def test_5_ez_bert_feat_mode(self):
argvs = ['easy_transfer_app',
'--mode', 'export',
'--checkpointPath', 'ez_text_classify_models/model.ckpt-0',
'--exportType', 'ez_bert_feat',
'--exportDirBase', 'ez_text_classify_models/saved_model/',
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
argvs = ['ez_bert_feat',
'--inputTable', '../ut_data/ez_bert_feat/one.seq.txt',
'--outputTable', 'ez_text_classify.feats.txt',
'--inputSchema', 'example_id:int:1,query1:str:1,label:str:1,category:str:1,score:float:1',
'--firstSequence', 'query1',
'--appendCols', 'example_id,label,category,score,xxx',
'--outputSchema', 'pool_output,first_token_output,all_hidden_outputs',
'--modelName', 'ez_text_classify_models/saved_model/',
'--sequenceLength', '50',
'--batchSize', '1']
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
os.remove('ez_text_classify.feats.txt')
def test_6_continue_train_mode(self):
argvs = ['easy_transfer_app',
'--mode', 'train',
'--inputTable', '../ut_data/ez_text_classify/train.csv,../ut_data/ez_text_classify/dev.csv',
'--inputSchema', "example_id:int:1,content:str:1,label:str:1,label_str:str:1,keywords:str:1",
'--firstSequence', 'content',
'--labelName', 'label',
'--labelEnumerateValues', '100,101,102,103,104,105,106,107,108,109,110,112,113,114,115,116',
'--checkpointDir', 'ez_text_classify_continue_models',
'--numEpochs', '1',
'--batchSize', '5',
'--optimizerType', 'adam',
'--learningRate', '2e-5',
'--modelName', 'text_classify_bert',
'--distributionStrategy', 'none',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1',
'--advancedParameters', """'
pretrain_model_name_or_path=google-bert-base-zh # For BERT
init_checkpoint_path=./ez_text_classify_models/model.ckpt-0
'
"""
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
shutil.rmtree('ez_text_classify_models', ignore_errors=True)
shutil.rmtree('ez_text_classify_continue_models', ignore_errors=True)
def test_7_textcnn(self):
argvs = ['easy_transfer_app',
'--mode', 'train',
'--inputTable', '../ut_data/ez_text_classify/train.csv,../ut_data/ez_text_classify/dev.csv',
'--inputSchema', "example_id:int:1,content:str:1,label:str:1,label_str:str:1,keywords:str:1",
'--firstSequence', 'content',
'--labelName', 'label',
'--labelEnumerateValues', '100,101,102,103,104,105,106,107,108,109,110,112,113,114,115,116',
'--checkpointDir', 'ez_text_classify_cnn_models',
'--numEpochs', '1',
'--batchSize', '5',
'--optimizerType', 'adadelta',
'--learningRate', '0.1',
'--modelName', 'text_classify_cnn',
'--distributionStrategy', 'none',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1',
'--advancedParameters', """'
fix_embedding=false
max_vocab_size=20000
num_filters=100
filter_sizes=3,4,5
dropout_rate=0.5
lr_decay=none
warmup_ratio=0.0
weight_decay_ratio=0
gradient_clip=true
clip_norm_value=5.0
throttle_secs=10
'
"""
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
argvs = ['easy_transfer_app',
'--mode', 'predict',
'--inputTable', '../ut_data/ez_text_classify/dev.csv',
'--outputTable', 'ez_text_classify.pred.csv',
'--inputSchema', 'example_id:int:1,content:str:1,label:str:1,label_str:str:1,keywords:str:1',
'--firstSequence', 'content',
'--appendCols', 'example_id,keywords,label_str',
'--outputSchema', 'predictions,probabilities,logits',
'--checkpointPath', 'ez_text_classify_cnn_models/',
'--batchSize', '100',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1',
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
self.assertTrue(os.path.exists('ez_text_classify.pred.csv'))
shutil.rmtree('ez_text_classify_cnn_models', ignore_errors=True)
os.remove('ez_text_classify.pred.csv')
def test_8_multi_label(self):
argvs = ['easy_transfer_app',
'--mode', 'train',
'--inputTable', '../ut_data/ez_text_classify/train.multi_label.csv,../ut_data/ez_text_classify/dev.multi_label.csv',
'--inputSchema', "example_id:int:1,content:str:1,accusations:str:1,articles:str:1",
'--firstSequence', 'content',
'--labelName', 'accusations',
'--labelEnumerateValues', '../ut_data/ez_text_classify/multi_labels.txt',
'--checkpointDir', 'ez_text_classify_multi_label_models',
'--numEpochs', '1',
'--batchSize', '5',
'--optimizerType', 'adam',
'--learningRate', '2e-5',
'--modelName', 'text_classify_bert',
'--distributionStrategy', 'none',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1',
'--advancedParameters', """'
multi_label=true
max_num_labels=5
pretrain_model_name_or_path=google-bert-base-zh # For BERT
'
"""
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
argvs = ['easy_transfer_app',
'--mode', 'predict',
'--inputTable', '../ut_data/ez_text_classify/dev.multi_label.csv',
'--outputTable', 'ez_text_classify.pred.csv',
'--inputSchema', "example_id:int:1,content:str:1,accusations:str:1,articles:str:1",
'--firstSequence', 'content',
'--appendCols', 'example_id,accusations,articles',
'--outputSchema', 'predictions,probabilities,logits',
'--checkpointPath', 'ez_text_classify_multi_label_models/',
'--batchSize', '100',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1'
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
self.assertTrue(os.path.exists('ez_text_classify.pred.csv'))
shutil.rmtree('ez_text_classify_multi_label_models', ignore_errors=True)
os.remove('ez_text_classify.pred.csv')
def test_9_regression_bert(self):
argvs = ['easy_transfer_app',
'--mode', 'train',
'--inputTable', '../ut_data/ez_text_match/train.csv,../ut_data/ez_text_match/dev.csv',
'--inputSchema', "example_id:int:1,query1:str:1,query2:str:1,is_same_question:str:1,category:str:1,score:float:1",
'--firstSequence', 'query1',
'--labelName', 'score',
'--checkpointDir', 'ez_text_classify_models',
'--numEpochs', '1',
'--batchSize', '5',
'--saveCheckpointSteps', '10000',
'--optimizerType', 'adam',
'--learningRate', '2e-5',
'--modelName', 'text_classify_bert',
'--distributionStrategy', 'MirroredStrategy',
'--workerCount', '1',
'--workerGPU', '1',
'--workerCPU', '1',
'--advancedParameters', """'
pretrain_model_name_or_path=google-bert-base-zh # For BERT
save_steps=300
log_step_count_steps=100
throttle_secs=100
keep_checkpoint_max=10
lr_decay=polynomial
warmup_ratio=0.1
weight_decay_ratio=0
gradient_clip=true
num_accumulated_batches=1
eval_batch_size=256
'
"""
]
print(' '.join(argvs))
try:
res = subprocess.check_output(' '.join(argvs), stderr=subprocess.STDOUT, shell=True)
print(res)
except subprocess.CalledProcessError as e:
print(e.output)
raise RuntimeError
shutil.rmtree('ez_text_classify_models', ignore_errors=True)
if __name__ == '__main__':
unittest.main()
| 45.944297
| 133
| 0.51146
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| 134
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0
| 7
|
8d2de8e1ba1c52c55da70185066cafb9b45f78dd
| 3,183
|
py
|
Python
|
video/train.py
|
EPFL-LCN/pub-illing2021-neurips
|
f5c9d7380f123a155a7c2b913df6f1fddb787be1
|
[
"MIT"
] | 11
|
2021-10-31T09:10:45.000Z
|
2022-03-24T12:18:28.000Z
|
video/train.py
|
EPFL-LCN/pub-illing2021-neurips
|
f5c9d7380f123a155a7c2b913df6f1fddb787be1
|
[
"MIT"
] | 1
|
2022-02-24T06:19:35.000Z
|
2022-02-24T18:12:45.000Z
|
video/train.py
|
EPFL-LCN/pub-illing2021-neurips
|
f5c9d7380f123a155a7c2b913df6f1fddb787be1
|
[
"MIT"
] | 2
|
2021-12-02T08:19:13.000Z
|
2021-12-27T02:39:44.000Z
|
# -*- coding: utf-8 -*-
from tqdm import tqdm
import torch
from utils import AverageMeter
def train(model, data_loader, optimizer, epoch):
cuda = torch.device('cuda')
# SET THE LOSSES AND ACCURACIES
# WARNING: USING x*[OBJECT] DUPLICATES REFERENCES TO THE SAME OBJECT INSTANCE
# HENCE THE FOR LOOP
losses = []
accuracies = []
for i in range( model.get_nb_losses()):
losses.append(AverageMeter())
accuracies.append([AverageMeter(),AverageMeter(),AverageMeter()])
model.train()
for input_seq in tqdm(data_loader):
# INPUT HAS DIMENSION (B, 1, 3, T, X, Y)
# 1 COMES FROM DPC TREATING SEQUENCES OF SEQUENCES,SOLVED WITH SQUEEZE
input_seq = input_seq.squeeze().to(cuda)
B = input_seq.size(0)
# MODEL OUTPUTS LOSSES, ACCURACIES, Z
res_losses, res_accs, _ = model(input_seq)
# UPDATE THE RUNNING LOSSES AND ACCURACIES
for i,(res_loss, res_acc) in enumerate(zip(res_losses, res_accs)):
losses[i].update(res_loss.item(), B)
for j in range(3):
accuracies[i][j].update(res_acc[j].item(), B)
# PERFORM BACKWARD(S) AND BACK-PROPAGATION
optimizer.zero_grad()
for loss in res_losses:
loss.backward()
optimizer.step()
# PRINT PERFORMANCES INDEXES AT EVERY EPOCH
for loss, acc in zip(losses, accuracies):
print('Training loss: {:.4f} | top1: {:.4f} | top3: {:.4f} | top5: {:.4f}'.format(loss.avg, acc[0].avg, acc[1].avg ,acc[2].avg))
return [loss.local_avg for loss in losses], [[acc[0].avg,acc[1].avg,acc[2].avg] for acc in accuracies]
def validate(model, data_loader, epoch):
cuda = torch.device('cuda')
# SET THE LOSSES AND ACCURACIES
# WARNING: USING x*[OBJECT] DUPLICATES REFERENCES TO THE SAME OBJECT INSTANCE
# HENCE THE FOR LOOP
losses = []
accuracies = []
for i in range(model.get_nb_losses()):
losses.append(AverageMeter())
accuracies.append([AverageMeter(),AverageMeter(),AverageMeter()])
model.eval()
for input_seq in tqdm(data_loader):
# INPUT HAS DIMENSION (B, 1, 3, T, X, Y)
# 1 COMES FROM DPC TREATING SEQUENCES OF SEQUENCES,SOLVED WITH SQUEEZE
input_seq = input_seq.squeeze().to(cuda)
B = input_seq.size(0)
# MODEL OUTPUTS LOSSES, ACCURACIES, Z
res_losses, res_accs, _ = model(input_seq)
# UPDATE THE RUNNING LOSSES AND ACCURACIES
for i,(res_loss, res_acc) in enumerate(zip(res_losses, res_accs)):
losses[i].update(res_loss.item(), B)
for j in range(3):
accuracies[i][j].update(res_acc[j].item(), B)
# PRINT PERFORMANCES INDEXES AT EVERY EPOCH
for loss, acc in zip(losses, accuracies):
print('Validation loss: {:.4f} | top1: {:.4f} | top3: {:.4f} | top5: {:.4f}'.format(loss.avg, acc[0].avg, acc[1].avg ,acc[2].avg))
return [loss.local_avg for loss in losses], [[acc[0].avg,acc[1].avg,acc[2].avg] for acc in accuracies]
| 36.586207
| 139
| 0.598492
| 426
| 3,183
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0
| 7
|
93a5f3cafdd2b19d4ef0f0833c5c5c8450a79521
| 11,503
|
py
|
Python
|
lip_demo.py
|
justinham/rasp
|
63511dd64cb0dfc13cbbaa202cad00866d98749a
|
[
"Apache-2.0"
] | null | null | null |
lip_demo.py
|
justinham/rasp
|
63511dd64cb0dfc13cbbaa202cad00866d98749a
|
[
"Apache-2.0"
] | null | null | null |
lip_demo.py
|
justinham/rasp
|
63511dd64cb0dfc13cbbaa202cad00866d98749a
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 2 16:00:02 2020
@author: chait
"""
import numpy as np
import matplotlib.pyplot as plt
import cv2
import os
from sklearn.model_selection import LeaveOneOut
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC
import sklearn.metrics as metrics
from joblib import dump, load
# Get histogram of each channel, bins=6
def get_hist(img):
img = cv2.imread(img)
size1,size2,_ = img.shape
R = img[:,:,0].reshape(size1*size2)
G = img[:,:,1].reshape(size1*size2)
B = img[:,:,2].reshape(size1*size2)
#bins = [15,30,45,60,75,90,105,120,135,150,165,180,195,210,225,240,255]
R_hist, R_bins = np.histogram(R, bins=6)
G_hist, G_bins = np.histogram(G, bins=6)
B_hist, B_bins = np.histogram(B, bins=6)
R_hist = [a/(size1*size2) for a in R_hist]
G_hist = [a/(size1*size2) for a in G_hist]
B_hist = [a/(size1*size2) for a in B_hist]
data = np.concatenate((R_hist,G_hist),axis=0)
data = np.concatenate((data,B_hist),axis=0)
return data
# LOOCV - prepare data
PATH = "images/train"
labels = []
hist = []
for file in os.listdir(PATH):
if file[0] == 'n':
labels.append(0)
else:
labels.append(1)
hist.append(get_hist(os.path.join(PATH,file)))
# loocv with logistic regression
loocv = LeaveOneOut()
correct = 0
wrong = 0
tp = 0
fp = 0
tn = 0
fn = 0
lr_pred_labels = []
for train_idx, test_idx in loocv.split(hist):
train_hist = []
train_labels = []
for i in train_idx:
train_hist.append(hist[i])
train_labels.append(labels[i])
lr = LogisticRegression(random_state=0, solver='lbfgs').fit(train_hist, train_labels)
pred = lr.predict([hist[test_idx[0]]])
lr_pred_labels.append(pred[0])
if pred[0] == labels[test_idx[0]]:
correct += 1
if pred[0] == 1:
tp += 1
else:
tn += 1
else:
wrong += 1
if pred[0] == 1:
fn += 1
else:
fp += 1
accuracy = correct/len(labels)
#print('LR accuracy, tp, fp, tn, fn:', accuracy, tp, fp, tn, fn)
# loocv with knn - 71.43
loocv = LeaveOneOut()
correct = 0
wrong = 0
tp = 0
fp = 0
tn = 0
fn = 0
knn_pred_labels = []
for train_idx, test_idx in loocv.split(hist):
train_hist = []
train_labels = []
for i in train_idx:
train_hist.append(hist[i])
train_labels.append(labels[i])
knn = KNeighborsClassifier(n_neighbors=3).fit(train_hist, train_labels)
pred = knn.predict([hist[test_idx[0]]])
knn_pred_labels.append(pred[0])
if pred[0] == labels[test_idx[0]]:
correct += 1
if pred[0] == 1:
tp += 1
else:
tn += 1
else:
wrong += 1
if pred[0] == 1:
fn += 1
else:
fp += 1
accuracy = correct/len(labels)
#print('KNN accuracy, tp, fp, tn, fn:', accuracy, tp, fp, tn, fn)
# loocv with svm - 77
loocv = LeaveOneOut()
correct = 0
wrong = 0
tp = 0
fp = 0
tn = 0
fn = 0
svc_pred_labels = []
for train_idx, test_idx in loocv.split(hist):
train_hist = []
train_labels = []
for i in train_idx:
train_hist.append(hist[i])
train_labels.append(labels[i])
svc = SVC(C=2,gamma='scale',degree=3,probability=True)
svc.fit(train_hist, train_labels)
pred = svc.predict([hist[test_idx[0]]])
svc_pred_labels.append(pred[0])
if pred[0] == labels[test_idx[0]]:
correct += 1
if pred[0] == 1:
tp += 1
else:
tn += 1
else:
wrong += 1
if pred[0] == 1:
fn += 1
else:
fp += 1
accuracy = correct/len(labels)
# Save svm model
dump(svc, './_models/lip_model.pb')
print('SVC accuracy, tp, fp, tn, fn:', accuracy, tp, fp, tn, fn)
#clf = load('svc_model.joblib')
#pred=[]
#for i in range(len(labels)):
# pred.append(clf.predict([hist[i]]))
########################################## Plot ROC and AUC ######################################
# For LR
#probs = lr.predict_proba(hist)
#preds = probs[:,1]
#fpr, tpr, threshold = metrics.roc_curve(labels, preds, pos_label=1)
#roc_auc = metrics.auc(fpr, tpr)
#plt.figure()
#plt.title('Receiver Operating Characteristic - LR')
#plt.plot(fpr, tpr, 'b', label = 'AUC = %0.2f' % roc_auc)
#plt.legend(loc = 'lower right')
#plt.plot([0, 1], [0, 1],'r--')
#plt.xlim([0, 1])
#plt.ylim([0, 1])
#plt.ylabel('True Positive Rate')
#plt.xlabel('False Positive Rate')
#plt.show()
#roc_auc_score(labels,preds)
## Feature importance for LR
#feat_wght_lr = np.zeros(np.shape(hist)[1]) #columns of X are features. So X.shape[1] is the number of features.
#feat_wght_lr += lr.coef_.reshape(-1) / 70
#
## For KNN
#probs = knn.predict_proba(hist)
#preds = probs[:,1]
#fpr, tpr, threshold = metrics.roc_curve(labels, preds, pos_label=1)
#roc_auc = metrics.auc(fpr, tpr)
#plt.figure()
#plt.title('Receiver Operating Characteristic - KNN (K=3)')
#plt.plot(fpr, tpr, 'b', label = 'AUC = %0.2f' % roc_auc)
#plt.legend(loc = 'lower right')
#plt.plot([0, 1], [0, 1],'r--')
#plt.xlim([0, 1])
#plt.ylim([0, 1])
#plt.ylabel('True Positive Rate')
#plt.xlabel('False Positive Rate')
#plt.show()
##roc_auc_score(labels,knn_pred_labels)
#
## For SVC
#probs = svc.predict_proba(hist)
#preds = probs[:,1]
#fpr, tpr, threshold = metrics.roc_curve(labels, preds, pos_label=1)
#roc_auc = metrics.auc(fpr, tpr)
#plt.figure()
#plt.title('Receiver Operating Characteristic - SVC')
#plt.plot(fpr, tpr, 'b', label = 'AUC = %0.2f' % roc_auc)
#plt.legend(loc = 'lower right')
#plt.plot([0, 1], [0, 1],'r--')
#plt.xlim([0, 1])
#plt.ylim([0, 1])
#plt.ylabel('True Positive Rate')
#plt.xlabel('False Positive Rate')
#plt.show()
##roc_auc_score(labels,svc_pred_labels)
#
############### Try with only mean of each channel #############################
def get_channel_mean(img):
img = cv2.imread(img)
size1,size2,_ = img.shape
R = img[:,:,0].reshape(size1*size2)
G = img[:,:,1].reshape(size1*size2)
B = img[:,:,2].reshape(size1*size2)
#bins = [15,30,45,60,75,90,105,120,135,150,165,180,195,210,225,240,255]
R_mean = np.mean(R)
G_mean = np.mean(G)
B_mean = np.mean(B)
data = [R_mean, G_mean, B_mean]
#data = np.concatenate((R_mean,G_mean),axis=0)
#data = np.concatenate((data,B_mean),axis=0)
return data
# LOOCV - prepare data
PATH = "./images/train"
labels = []
means = []
for file in os.listdir(PATH):
if file[0] == 'n':
labels.append(0)
else:
labels.append(1)
means.append(get_channel_mean(os.path.join(PATH,file)))
# loocv with logistic regression
loocv = LeaveOneOut()
correct = 0
wrong = 0
tp = 0
fp = 0
tn = 0
fn = 0
lr_pred_labels = []
for train_idx, test_idx in loocv.split(means):
train_mean = []
train_labels = []
for i in train_idx:
train_mean.append(means[i])
train_labels.append(labels[i])
lr = LogisticRegression(random_state=0, solver='lbfgs').fit(train_mean, train_labels)
pred = lr.predict([means[test_idx[0]]])
lr_pred_labels.append(pred[0])
if pred[0] == labels[test_idx[0]]:
correct += 1
if pred[0] == 1:
tp += 1
else:
tn += 1
else:
wrong += 1
if pred[0] == 1:
fn += 1
else:
fp += 1
accuracy = correct/len(labels)
#print('LR accuracy, tp, fp, tn, fn:', accuracy, tp, fp, tn, fn)
# loocv with knn - 71.43
loocv = LeaveOneOut()
correct = 0
wrong = 0
tp = 0
fp = 0
tn = 0
fn = 0
knn_pred_labels = []
for train_idx, test_idx in loocv.split(means):
train_mean = []
train_labels = []
for i in train_idx:
train_mean.append(means[i])
train_labels.append(labels[i])
knn = KNeighborsClassifier(n_neighbors=3).fit(train_mean, train_labels)
pred = knn.predict([means[test_idx[0]]])
knn_pred_labels.append(pred[0])
if pred[0] == labels[test_idx[0]]:
correct += 1
if pred[0] == 1:
tp += 1
else:
tn += 1
else:
wrong += 1
if pred[0] == 1:
fn += 1
else:
fp += 1
accuracy = correct/len(labels)
#print('KNN accuracy, tp, fp, tn, fn:', accuracy, tp, fp, tn, fn)
# loocv with svm - 77
loocv = LeaveOneOut()
correct = 0
wrong = 0
tp = 0
fp = 0
tn = 0
fn = 0
svc_pred_labels = []
for train_idx, test_idx in loocv.split(means):
train_mean = []
train_labels = []
for i in train_idx:
train_mean.append(means[i])
train_labels.append(labels[i])
svc = SVC(C=2,gamma='scale',degree=3,probability=True)
svc.fit(train_mean, train_labels)
pred = svc.predict([means[test_idx[0]]])
svc_pred_labels.append(pred[0])
if pred[0] == labels[test_idx[0]]:
correct += 1
if pred[0] == 1:
tp += 1
else:
tn += 1
else:
wrong += 1
if pred[0] == 1:
fn += 1
else:
fp += 1
accuracy = correct/len(labels)
print('SVC accuracy, tp, fp, tn, fn:', accuracy, tp, fp, tn, fn)
######################## ROC and AUC
## For LR
#probs = lr.predict_proba(means)
#preds = probs[:,1]
#fpr, tpr, threshold = metrics.roc_curve(labels, preds, pos_label=1)
#roc_auc = metrics.auc(fpr, tpr)
#plt.figure()
#plt.title('Receiver Operating Characteristic - LR')
#plt.plot(fpr, tpr, 'b', label = 'AUC = %0.2f' % roc_auc)
#plt.legend(loc = 'lower right')
#plt.plot([0, 1], [0, 1],'r--')
#plt.xlim([0, 1])
#plt.ylim([0, 1])
#plt.ylabel('True Positive Rate')
#plt.xlabel('False Positive Rate')
#plt.show()
##roc_auc_score(labels,preds)
#
## Feature importance for LR
#feat_wght_lr = np.zeros(np.shape(means)[1]) #columns of X are features. So X.shape[1] is the number of features.
#feat_wght_lr += lr.coef_.reshape(-1) / 70 ############## CHANGE DENOMINATOR!!!!!!
#bars = [1,2,3]
#plt.figure()
#plt.bar(bars,feat_wght_lr)
#plt.xlabel('Features - R, G, B channel means')
#plt.ylabel('Weight')
#
## For KNN
#probs = knn.predict_proba(means)
#preds = probs[:,1]
#fpr, tpr, threshold = metrics.roc_curve(labels, preds, pos_label=1)
#roc_auc = metrics.auc(fpr, tpr)
#plt.figure()
#plt.title('Receiver Operating Characteristic - KNN (K=3)')
#plt.plot(fpr, tpr, 'b', label = 'AUC = %0.2f' % roc_auc)
#plt.legend(loc = 'lower right')
#plt.plot([0, 1], [0, 1],'r--')
#plt.xlim([0, 1])
#plt.ylim([0, 1])
#plt.ylabel('True Positive Rate')
#plt.xlabel('False Positive Rate')
#plt.show()
##roc_auc_score(labels,knn_pred_labels)
#
## For SVC
#probs = svc.predict_proba(means)
#preds = probs[:,1]
#fpr, tpr, threshold = metrics.roc_curve(labels, preds, pos_label=1)
#roc_auc = metrics.auc(fpr, tpr)
#plt.figure()
#plt.title('Receiver Operating Characteristic - SVC')
#plt.plot(fpr, tpr, 'b', label = 'AUC = %0.2f' % roc_auc)
#plt.legend(loc = 'lower right')
#plt.plot([0, 1], [0, 1],'r--')
#plt.xlim([0, 1])
#plt.ylim([0, 1])
#plt.ylabel('True Positive Rate')
#plt.xlabel('False Positive Rate')
#plt.show()
##roc_auc_score(labels,svc_pred_labels)
| 26.689095
| 114
| 0.577936
| 1,721
| 11,503
| 3.750726
| 0.112144
| 0.011154
| 0.01952
| 0.014872
| 0.863052
| 0.849884
| 0.827885
| 0.80976
| 0.80976
| 0.803253
| 0
| 0.043177
| 0.246979
| 11,503
| 430
| 115
| 26.751163
| 0.702032
| 0.377119
| 0
| 0.820084
| 0
| 0
| 0.019978
| 0.003434
| 0
| 0
| 0
| 0
| 0
| 1
| 0.008368
| false
| 0
| 0.041841
| 0
| 0.058577
| 0.008368
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
|
0
| 7
|
f51404245794c245096dd184c83ac42e59a46ac3
| 223
|
py
|
Python
|
src/flask_mega_tutorial/microblog/microblog.py
|
sfortson/random-scripts
|
94911dd7ca40d41a442699cf3086be4552c57a61
|
[
"MIT"
] | null | null | null |
src/flask_mega_tutorial/microblog/microblog.py
|
sfortson/random-scripts
|
94911dd7ca40d41a442699cf3086be4552c57a61
|
[
"MIT"
] | 1
|
2020-02-27T18:08:55.000Z
|
2020-02-27T18:08:55.000Z
|
src/flask_mega_tutorial/microblog/microblog.py
|
sfortson/random-scripts
|
94911dd7ca40d41a442699cf3086be4552c57a61
|
[
"MIT"
] | null | null | null |
from app import app
from app import db
from app import cli
from app.models import Post
from app.models import User
@app.shell_context_processor
def make_shell_context():
return {'db': db, 'User': User, 'Post': Post}
| 18.583333
| 49
| 0.744395
| 37
| 223
| 4.378378
| 0.378378
| 0.216049
| 0.240741
| 0.234568
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.165919
| 223
| 11
| 50
| 20.272727
| 0.870968
| 0
| 0
| 0
| 0
| 0
| 0.045045
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.125
| true
| 0
| 0.625
| 0.125
| 0.875
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
| 0
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| null | 0
| 0
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| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 7
|
f519eb174ff9de446cbdc7dc5845d4e2f8c4c573
| 2,293
|
py
|
Python
|
tests/kyu_7_tests/test_regexp_basics_is_eight_bit_number.py
|
the-zebulan/CodeWars
|
1eafd1247d60955a5dfb63e4882e8ce86019f43a
|
[
"MIT"
] | 40
|
2016-03-09T12:26:20.000Z
|
2022-03-23T08:44:51.000Z
|
tests/kyu_7_tests/test_regexp_basics_is_eight_bit_number.py
|
akalynych/CodeWars
|
1eafd1247d60955a5dfb63e4882e8ce86019f43a
|
[
"MIT"
] | null | null | null |
tests/kyu_7_tests/test_regexp_basics_is_eight_bit_number.py
|
akalynych/CodeWars
|
1eafd1247d60955a5dfb63e4882e8ce86019f43a
|
[
"MIT"
] | 36
|
2016-11-07T19:59:58.000Z
|
2022-03-31T11:18:27.000Z
|
import unittest
from katas.kyu_7.regexp_basics_is_eight_bit_number import \
signed_eight_bit_number
class EightBitNumberTestCase(unittest.TestCase):
def test_true(self):
self.assertTrue(signed_eight_bit_number("0"))
def test_true_2(self):
self.assertTrue(signed_eight_bit_number("55"))
def test_true_3(self):
self.assertTrue(signed_eight_bit_number("-23"))
def test_true_4(self):
self.assertTrue(signed_eight_bit_number("127"))
def test_true_5(self):
self.assertTrue(signed_eight_bit_number("-128"))
def test_false(self):
self.assertFalse(signed_eight_bit_number(""))
def test_false_2(self):
self.assertFalse(signed_eight_bit_number("00"))
def test_false_3(self):
self.assertFalse(signed_eight_bit_number("-0"))
def test_false_4(self):
self.assertFalse(signed_eight_bit_number("042"))
def test_false_5(self):
self.assertFalse(signed_eight_bit_number("128"))
def test_false_6(self):
self.assertFalse(signed_eight_bit_number("999"))
def test_false_7(self):
self.assertFalse(signed_eight_bit_number("-129"))
def test_false_8(self):
self.assertFalse(signed_eight_bit_number("-999"))
def test_false_9(self):
self.assertFalse(signed_eight_bit_number("1\n"))
def test_false_10(self):
self.assertFalse(signed_eight_bit_number("1 "))
def test_false_11(self):
self.assertFalse(signed_eight_bit_number(" 1"))
def test_false_12(self):
self.assertFalse(signed_eight_bit_number("1\n2"))
def test_false_13(self):
self.assertFalse(signed_eight_bit_number("+1"))
def test_false_14(self):
self.assertFalse(signed_eight_bit_number("--1"))
def test_false_15(self):
self.assertFalse(signed_eight_bit_number("1\n"))
def test_false_16(self):
self.assertFalse(signed_eight_bit_number("1 "))
def test_false_17(self):
self.assertFalse(signed_eight_bit_number(" 1"))
def test_false_18(self):
self.assertFalse(signed_eight_bit_number("1\n2"))
def test_false_19(self):
self.assertFalse(signed_eight_bit_number("+1"))
def test_false_20(self):
self.assertFalse(signed_eight_bit_number("--1"))
| 27.963415
| 59
| 0.698648
| 322
| 2,293
| 4.565217
| 0.164596
| 0.146939
| 0.257143
| 0.353742
| 0.813605
| 0.813605
| 0.813605
| 0.541497
| 0.466667
| 0.466667
| 0
| 0.041622
| 0.18273
| 2,293
| 81
| 60
| 28.308642
| 0.742796
| 0
| 0
| 0.222222
| 0
| 0
| 0.028783
| 0
| 0
| 0
| 0
| 0
| 0.462963
| 1
| 0.462963
| false
| 0
| 0.037037
| 0
| 0.518519
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
f574814c84ebedc7439c6850fc1c38dadcb185c4
| 12,284
|
py
|
Python
|
example_leg.py
|
vkurenkov/tensegrity
|
c0cafcdd434ed41a99e75605b15657370d5cfddb
|
[
"MIT"
] | 4
|
2019-08-02T11:07:02.000Z
|
2021-05-11T09:10:42.000Z
|
example_leg.py
|
vkurenkov/tensegrity
|
c0cafcdd434ed41a99e75605b15657370d5cfddb
|
[
"MIT"
] | 1
|
2019-08-07T14:51:29.000Z
|
2019-08-07T14:51:29.000Z
|
example_leg.py
|
vkurenkov/tensegrity
|
c0cafcdd434ed41a99e75605b15657370d5cfddb
|
[
"MIT"
] | null | null | null |
import numpy as np
import visualisation as rob_vis
from model import Rod, RodState, Cable, TensegrityRobot
from simulation import run_simulation
from copy import deepcopy
from scipy.spatial.transform import Rotation
np.set_printoptions( precision=5 )
np.set_printoptions( suppress=True )
LENGTH = 0.1
OFFSET = LENGTH / 8.0
UNSTRETCHED_LENGTH = 0.05
STIFFNESS = 1
VISCOSITY_DR = 1
VISCOSITY_W = 1
VISCOSITY = 1
MASS = 0.8
INERTIA = np.diag( [ (1 / 12) * MASS * LENGTH ** 2, (1 / 12) * MASS * LENGTH ** 2, (1 / 12) * MASS * LENGTH ** 2 ] )
DELTA_L = 0.001
rod1 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH,
state=RodState( r=np.array( [ 0, 0, -OFFSET ] ),
q=Rotation.from_euler( "xyz", [ 0, 0, 0 ],
degrees=True ) ),
viscosity_dr=VISCOSITY_DR,
viscosity_w=VISCOSITY_W )
rod2 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH,
state=RodState( r=np.array( [ 0, 0, OFFSET ] ), q=Rotation.from_euler( "xyz", [ 0, 0, 0 ], degrees=True ) ),
viscosity_dr=VISCOSITY_DR, viscosity_w=VISCOSITY_W )
rod3 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH * 3, state=RodState( r=np.array( [ -OFFSET, 0, 0 ] ),
q=Rotation.from_euler( "xyz", [ 0, 0, 90 ],
degrees=True ) ),
viscosity_dr=VISCOSITY_DR,
viscosity_w=VISCOSITY_W )
rod4 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH * 3, state=RodState( r=np.array( [ OFFSET, 0, 0 ] ),
q=Rotation.from_euler( "xyz", [ 0, 0, 90 ],
degrees=True ) ),
viscosity_dr=VISCOSITY_DR,
viscosity_w=VISCOSITY_W )
rod5 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH * 3, state=RodState( r=np.array( [ 0, -OFFSET, 0 ] ),
q=Rotation.from_euler( "xyz", [ 0, 90, 0 ],
degrees=True ) ),
viscosity_dr=VISCOSITY_DR,
viscosity_w=VISCOSITY_W )
rod6 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH, state=RodState( r=np.array( [ 0, OFFSET, 0 ] ),
q=Rotation.from_euler( "xyz", [ 0, 90, 0 ],
degrees=True ) ),
viscosity_dr=VISCOSITY_DR,
viscosity_w=VISCOSITY_W )
rod7 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH,
state=RodState( r=np.array( [ 0, OFFSET * 10, 0 ] ),
q=Rotation.from_euler( "xyz", [ 0, 90, 0 ], degrees=True ) ), viscosity_dr=VISCOSITY_DR,
viscosity_w=VISCOSITY_W )
rod8 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH,
state=RodState( r=np.array( [ 0, OFFSET * 8, -OFFSET ] ),
q=Rotation.from_euler( "xyz", [ 0, 0, 0 ], degrees=True ) ), viscosity_dr=VISCOSITY_DR,
viscosity_w=VISCOSITY_W ,fixed=True)
rod9 = Rod( mass=MASS, inertia=INERTIA, length=LENGTH,
state=RodState( r=np.array( [ 0, OFFSET * 8, OFFSET ] ),
q=Rotation.from_euler( "xyz", [ 0, 0, 0 ], degrees=True ) ), viscosity_dr=VISCOSITY_DR,
viscosity_w=VISCOSITY_W ,fixed=True)
cab1 = Cable( end_point1=rod1.get_endpoint_a(), end_point2=rod3.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab2 = Cable( end_point1=rod1.get_endpoint_a(), end_point2=rod3.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab3 = Cable( end_point1=rod1.get_endpoint_a(), end_point2=rod6.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab4 = Cable( end_point1=rod1.get_endpoint_a(), end_point2=rod5.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab5 = Cable( end_point1=rod1.get_endpoint_b(), end_point2=rod4.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab6 = Cable( end_point1=rod1.get_endpoint_b(), end_point2=rod4.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab7 = Cable( end_point1=rod1.get_endpoint_b(), end_point2=rod6.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab8 = Cable( end_point1=rod1.get_endpoint_b(), end_point2=rod5.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab9 = Cable( end_point1=rod5.get_endpoint_b(), end_point2=rod3.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab10 = Cable( end_point1=rod5.get_endpoint_b(), end_point2=rod4.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab11 = Cable( end_point1=rod6.get_endpoint_b(), end_point2=rod3.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab12 = Cable( end_point1=rod6.get_endpoint_b(), end_point2=rod4.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab13 = Cable( end_point1=rod3.get_endpoint_a(), end_point2=rod2.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab14 = Cable( end_point1=rod3.get_endpoint_a(), end_point2=rod5.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab15 = Cable( end_point1=rod4.get_endpoint_a(), end_point2=rod2.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab16 = Cable( end_point1=rod4.get_endpoint_a(), end_point2=rod5.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab17 = Cable( end_point1=rod3.get_endpoint_b(), end_point2=rod2.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab18 = Cable( end_point1=rod3.get_endpoint_b(), end_point2=rod6.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab19 = Cable( end_point1=rod4.get_endpoint_b(), end_point2=rod6.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab20 = Cable( end_point1=rod4.get_endpoint_b(), end_point2=rod2.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab21 = Cable( end_point1=rod2.get_endpoint_a(), end_point2=rod6.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab22 = Cable( end_point1=rod2.get_endpoint_a(), end_point2=rod5.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab23 = Cable( end_point1=rod2.get_endpoint_b(), end_point2=rod6.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab24 = Cable( end_point1=rod2.get_endpoint_b(), end_point2=rod5.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH * 4, viscosity=VISCOSITY )
cab25 = Cable( end_point1=rod7.get_endpoint_a(), end_point2=rod3.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab26 = Cable( end_point1=rod7.get_endpoint_a(), end_point2=rod4.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab27 = Cable( end_point1=rod7.get_endpoint_b(), end_point2=rod3.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab28 = Cable( end_point1=rod7.get_endpoint_b(), end_point2=rod4.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab29 = Cable( end_point1=rod3.get_endpoint_b(), end_point2=rod8.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab30 = Cable( end_point1=rod3.get_endpoint_b(), end_point2=rod9.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab31 = Cable( end_point1=rod4.get_endpoint_b(), end_point2=rod8.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab32 = Cable( end_point1=rod4.get_endpoint_b(), end_point2=rod9.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab33 = Cable( end_point1=rod7.get_endpoint_a(), end_point2=rod9.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab34 = Cable( end_point1=rod7.get_endpoint_a(), end_point2=rod9.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab35 = Cable( end_point1=rod7.get_endpoint_b(), end_point2=rod8.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab36 = Cable( end_point1=rod7.get_endpoint_b(), end_point2=rod8.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH / 4, viscosity=VISCOSITY )
cab37 = Cable( end_point1=rod6.get_endpoint_a(), end_point2=rod9.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH, viscosity=VISCOSITY )
cab38 = Cable( end_point1=rod6.get_endpoint_a(), end_point2=rod9.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH, viscosity=VISCOSITY )
cab39 = Cable( end_point1=rod6.get_endpoint_b(), end_point2=rod8.get_endpoint_a(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH, viscosity=VISCOSITY )
cab40 = Cable( end_point1=rod6.get_endpoint_b(), end_point2=rod8.get_endpoint_b(), stiffness=STIFFNESS,
unstretched_length=UNSTRETCHED_LENGTH, viscosity=VISCOSITY )
robot = TensegrityRobot()
robot.add_rods( [ rod1, rod2, rod3, rod4, rod5, rod6, rod7, rod8, rod9 ] )
robot.add_cables( [ cab1, cab3, cab4, cab5, cab7, cab8, cab9, cab10, cab11, cab12 ] )
robot.add_cables( [ cab13, cab14, cab15, cab16, cab18, cab19, cab21, cab22, cab23, cab24 ] )
robot.add_cables( [ cab25, cab26, cab27, cab28, cab29, cab30, cab31, cab32, cab33, cab34, cab35, cab36 ] )
robot.add_cables( [ cab37, cab38, cab39, cab40 ] )
# rob_vis.plot_cur_state(robot)
hist_states = run_simulation( robot, time=7, dt=0.001 )
print(robot.get_kinetic_energy())
#rob_vis.animate_historical_states( robot=robot, states=hist_states, interval=0.1 )
pos0 = robot.get_rods()[4].get_endpoint_a().get_position()
K = []
for i in robot.get_cables():
print("1", i.get_unstretched_length())
len = i.get_unstretched_length()
#i.set_unstretched_length(len + DELTA_L)
hist_states = run_simulation( robot, time=1, dt=0.001 )
#rob_vis.animate_historical_states( robot=robot, states=hist_states, interval=0.1 )
print("2", i.get_unstretched_length() )
K.append(robot.get_rods()[4].get_endpoint_a().get_position() - pos0)
#i.set_unstretched_length(len)
print( "3",i.get_unstretched_length() )
K = np.array(K).transpose() / DELTA_L
print(K)
rob_vis.plot_cur_state(robot)
| 67.494505
| 120
| 0.673966
| 1,517
| 12,284
| 5.17996
| 0.092287
| 0.188216
| 0.067193
| 0.178162
| 0.866251
| 0.854543
| 0.840545
| 0.840545
| 0.840545
| 0.745864
| 0
| 0.047278
| 0.214832
| 12,284
| 181
| 121
| 67.867403
| 0.767444
| 0.021247
| 0
| 0.402516
| 0
| 0
| 0.002496
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.037736
| 0
| 0.037736
| 0.044025
| 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
|
f598460667d781486854b0fce89946b98f5e293a
| 975
|
py
|
Python
|
src/beginner/1045.py
|
henrikhorbovyi/URI
|
6df34d87bb7bbbf760ab774e01da87ad669acae9
|
[
"Apache-2.0"
] | 1
|
2018-07-04T01:53:29.000Z
|
2018-07-04T01:53:29.000Z
|
src/beginner/1045.py
|
henrikhorbovyi/URI
|
6df34d87bb7bbbf760ab774e01da87ad669acae9
|
[
"Apache-2.0"
] | null | null | null |
src/beginner/1045.py
|
henrikhorbovyi/URI
|
6df34d87bb7bbbf760ab774e01da87ad669acae9
|
[
"Apache-2.0"
] | null | null | null |
A,B,C = input().split(" ")
A,B,C = sorted([float(A),float(B),float(C)],reverse=True)
if A >= (B+C):
print("NAO FORMA TRIANGULO")
else:
if ( (A**2) == ((B**2) + (C**2)) ):
print("TRIANGULO RETANGULO")
if (A == B) and (B == C):
print("TRIANGULO EQUILATERO")
if ( (A == B) or (A == C) or (B == C)) and ((A != B) or (A != C) or (B != C)):
print("TRIANGULO ISOSCELES")
if (A**2) > ((B**2) + (C**2)):
print("TRIANGULO OBTUSANGULO")
if (A == B) and (B == C):
print("TRIANGULO EQUILATERO")
if ( (A == B) or (A == C) or (B == C)) and ((A != B) or (A != C) or (B != C)):
print("TRIANGULO ISOSCELES")
if (A**2) < ((B**2) + (C**2)):
print("TRIANGULO ACUTANGULO")
if (A == B) and (B == C):
print("TRIANGULO EQUILATERO")
if ( (A == B) or (A == C) or (B == C)) and ((A != B) or (A != C) or (B != C)):
print("TRIANGULO ISOSCELES")
| 40.625
| 86
| 0.431795
| 146
| 975
| 2.883562
| 0.157534
| 0.057007
| 0.066508
| 0.228029
| 0.733967
| 0.733967
| 0.733967
| 0.733967
| 0.733967
| 0.68171
| 0
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| 975
| 24
| 87
| 40.625
| 0.621418
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| 0
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0
| 8
|
f5a6b346e9dcc7f8f503d18493f3b851e5e1ba78
| 11,473
|
py
|
Python
|
model_g_episodes.py
|
bjdarrer/tf2-model-g-velocity
|
2d9078fa386911a11d6aa659091e1443ac671535
|
[
"MIT"
] | null | null | null |
model_g_episodes.py
|
bjdarrer/tf2-model-g-velocity
|
2d9078fa386911a11d6aa659091e1443ac671535
|
[
"MIT"
] | null | null | null |
model_g_episodes.py
|
bjdarrer/tf2-model-g-velocity
|
2d9078fa386911a11d6aa659091e1443ac671535
|
[
"MIT"
] | 3
|
2020-11-09T19:49:22.000Z
|
2021-03-14T20:26:19.000Z
|
# coding: utf-8
import numpy as np
from util import bl_noise, l2_location
from mpl_toolkits import mplot3d
import pylab
from matplotlib.animation import FuncAnimation
from model_g import ModelG
def self_stabilizing_soliton_2D():
params = {
"A": 4.2,
"B": 18,
"k2": 1.0,
"k-2": 0.2,
"k5": 0.9,
"D_G": 1.0,
"D_X": 1.0,
"D_Y": 2.0,
}
x = np.linspace(-16, 16, 256)
dx = x[1] - x[0]
x, y = np.meshgrid(x, x)
r2 = x*x+y*y
model_g = ModelG(
-np.exp(-0.1*r2)*1.0,
np.exp(-r2)*0.01,
np.exp(-r2)*0.01 + bl_noise(x.shape)*0.02,
dx,
0.1*dx,
params,
)
def get_data():
G, X, Y = model_g.numpy()
x_scale = 0.2
y_scale = 0.1
return (
G[64],
X[64] * x_scale,
Y[64] * y_scale,
)
G, X, Y = get_data()
plots = []
plots.extend(pylab.plot(x[0], G))
plots.extend(pylab.plot(x[0], X))
plots.extend(pylab.plot(x[0], Y))
pylab.ylim(-0.03, 0.03)
def update(frame):
for _ in range(5):
model_g.step()
G, X, Y = get_data()
plots[0].set_ydata(G)
plots[1].set_ydata(X)
plots[2].set_ydata(Y)
return plots
FuncAnimation(pylab.gcf(), update, frames=range(100), init_func=lambda: plots, blit=True, repeat=True, interval=20)
pylab.show()
G, X, Y = model_g.numpy()
pylab.imshow(Y)
pylab.show()
def self_stabilizing_soliton_3D():
params = {
"A": 3.42,
"B": 13.5,
"k2": 1.0,
"k-2": 0.1,
"k5": 0.9,
"D_G": 1.0,
"D_X": 1.0,
"D_Y": 2.0,
}
x = np.linspace(-16, 16, 128)
dx = x[1] - x[0]
x, y, z = np.meshgrid(x, x, x)
r2 = x*x+y*y+z*z
model_g = ModelG(
-np.exp(-0.1*r2)*1.0,
-np.exp(-r2)*0.01,
np.exp(-r2)*0.01 + bl_noise(x.shape)*0.02,
dx,
dx*0.1,
params,
)
def get_data():
G, X, Y = model_g.numpy()
x_scale = 0.5
y_scale = 0.04
return (
G[64, 64],
X[64, 64] * x_scale,
Y[64, 64] * y_scale,
)
G, X, Y = get_data()
plots = []
plots.extend(pylab.plot(z[0,0], G))
plots.extend(pylab.plot(z[0,0], X))
plots.extend(pylab.plot(z[0,0], Y))
pylab.ylim(-0.4, 0.4)
def update(frame):
for _ in range(5):
model_g.step()
G, X, Y = get_data()
plots[0].set_ydata(G)
plots[1].set_ydata(X)
plots[2].set_ydata(Y)
return plots
FuncAnimation(pylab.gcf(), update, frames=range(100), init_func=lambda: plots, blit=True, repeat=True, interval=20)
pylab.show()
G, X, Y = model_g.numpy()
pylab.imshow(Y[64])
pylab.show()
# XXX: Nucleates, but still doesn't move
def nucleation_and_motion_in_G_gradient_1D():
params = {
"A": 14,
"B": 29,
"k2": 1.0,
"k-2": 0.1,
"k5": 0.9,
"D_G": 1.0,
"D_X": 1.0,
"D_Y": 12,
}
x = np.linspace(-24, 24, 512)
dx = x[1] - x[0]
def source_G(t):
center = -np.exp(-0.1*(t-5)**2) * 5
gradient = (1+np.tanh(t-50)) * 0.0005
print("t={}\tcenter={}\tgradient={}".format(t, center, gradient))
return np.exp(-0.25*x*x) * center + (x*0.5 + 7) * gradient
def source_X(t):
center = np.exp(-0.1*(t-5)**2) * 5
return -np.exp(-0.25*x*x) * center
def source_Y(t):
center = np.exp(-0.1*(t-5)**2) * 0
return np.exp(-0.25*x*x) * center
source_functions = {
'G': source_G,
'X': source_X,
'Y': source_Y,
}
r2 = x*x
model_g = ModelG(
np.exp(-0.1*r2)*0,
np.exp(-r2)*0.01*0,
np.exp(-r2)*0.01*0,
dx,
dt=0.05*dx,
params=params,
source_functions=source_functions,
)
def get_data():
G, X, Y = model_g.numpy()
x_scale = 0.1
y_scale = 0.1
return (
G,
X * x_scale,
Y * y_scale,
)
G, X, Y = get_data()
plots = []
plots.extend(pylab.plot(x, G))
plots.extend(pylab.plot(x, X))
plots.extend(pylab.plot(x, Y))
pylab.ylim(-0.1, 0.1)
def update(frame):
for _ in range(32):
model_g.step()
G, X, Y = get_data()
plots[0].set_ydata(G)
plots[1].set_ydata(X)
plots[2].set_ydata(Y)
return plots
FuncAnimation(pylab.gcf(), update, frames=range(100), init_func=lambda: plots, blit=True, repeat=True, interval=20)
pylab.show()
G, X, Y = model_g.numpy()
print("Total G={}, X={} Y={}".format(G.sum(), X.sum(), Y.sum()))
print("Total G²={}, X²={} Y²={}".format((G**2).sum(), (X**2).sum(), (Y**2).sum()))
def nucleation_and_motion_in_G_gradient_2D():
params = {
"A": 3.42,
"B": 13.5,
"k2": 1.0,
"k-2": 0.1,
"k5": 0.9,
"D_G": 1.0,
"D_X": 1.0,
"D_Y": 1.95,
}
x = np.linspace(-16, 16, 128)
dx = x[1] - x[0]
x, y = np.meshgrid(x, x)
def source_G(t):
center = np.exp(-0.5*(t-5)**2) * 10
gradient = (1+np.tanh(t-40)) * 0.0005
# print("t = {}\tcenter potential = {}\tx-gradient = {}".format(t, center, gradient))
return -np.exp(-0.5*(x*x+y*y))* center + (x+8) * gradient
source_functions = {
'G': source_G,
}
r2 = x*x+y*y
model_g = ModelG(
-np.exp(-0.1*r2)*0,
-np.exp(-r2)*0.01*0,
np.exp(-r2)*0.01*0,
dx,
dt=0.1*dx,
params=params,
source_functions=source_functions,
)
times = []
locs = []
def get_data():
G, X, Y = model_g.numpy()
loc = l2_location(X, x, y)
times.append(model_g.t)
locs.append(loc[0])
print("t={}\tL2 location: {}".format(model_g.t, tuple(loc)))
x_scale = 0.1
y_scale = 0.1
return (
G[64],
X[64] * x_scale,
Y[64] * y_scale,
)
G, X, Y = get_data()
plots = []
plots.extend(pylab.plot(x[0], G))
plots.extend(pylab.plot(x[0], X))
plots.extend(pylab.plot(x[0], Y))
pylab.ylim(-0.1, 0.1)
def update(frame):
for _ in range(20):
model_g.step()
G, X, Y = get_data()
plots[0].set_ydata(G)
plots[1].set_ydata(X)
plots[2].set_ydata(Y)
return plots
FuncAnimation(pylab.gcf(), update, frames=range(100), init_func=lambda: plots, blit=True, repeat=True, interval=20)
pylab.show()
G, X, Y = model_g.numpy()
pylab.imshow(X)
pylab.show()
pylab.plot(times, locs)
pylab.show()
def random_2D():
r = np.random.randn
params = {
"A": 2 + r()*0.1,
"B": 10 + r(),
"k2": 1.0 + 0.1*r(),
"k-2": 0.1 + 0.01*r(),
"k5": 0.9 + 0.1*r(),
"D_G": 1.0,
"D_X": 1.0 + 0.1*r(),
"D_Y": 2.0 + 0.1*r(),
}
print(params)
x = np.linspace(-16, 16, 256)
dx = x[1] - x[0]
x, y = np.meshgrid(x, x)
def source_G(t):
center = np.exp(-0.5*(t-20)**2) * 10
gradient = (1+np.tanh(t-40)) * 0.0005
print("t = {}\tcenter potential = {}\tx-gradient = {}".format(t, center, gradient))
return -np.exp(-0.5*(x*x+y*y)) * center + x * gradient
source_functions = {
'G': source_G,
}
model_g = ModelG(
bl_noise(x.shape)*0.01,
bl_noise(x.shape)*0.01,
bl_noise(x.shape)*0.01,
dx,
0.1*dx,
params,
source_functions=source_functions,
)
def get_data():
G, X, Y = model_g.numpy()
x_scale = 0.1
y_scale = 0.1
return (
G[64],
X[64] * x_scale,
Y[64] * y_scale,
)
G, X, Y = get_data()
plots = []
plots.extend(pylab.plot(x[0], G))
plots.extend(pylab.plot(x[0], X))
plots.extend(pylab.plot(x[0], Y))
pylab.ylim(-0.5, 0.5)
def update(frame):
model_g.step()
G, X, Y = get_data()
plots[0].set_ydata(G)
plots[1].set_ydata(X)
plots[2].set_ydata(Y)
return plots
FuncAnimation(pylab.gcf(), update, frames=range(100), init_func=lambda: plots, blit=True, repeat=True, interval=20)
pylab.show()
G, X, Y = model_g.numpy()
plots = [pylab.imshow(X)]
def update(frame):
model_g.step()
G, X, Y = model_g.numpy()
plots[0].set_data(X)
return plots
FuncAnimation(pylab.gcf(), update, frames=range(100), init_func=lambda: plots, blit=True, repeat=True, interval=20)
pylab.show()
def random_3D():
r = np.random.randn
params = {
"A": 2 + r()*0.1,
"B": 10 + r(),
"k2": 1.0 + 0.1*r(),
"k-2": 0.1 + 0.01*r(),
"k5": 0.9 + 0.1*r(),
"D_G": 1.0,
"D_X": 1.0 + 0.1*r(),
"D_Y": 2.0 + 0.1*r(),
}
print(params)
x = np.linspace(-16, 16, 128)
dx = x[1] - x[0]
x, y, z = np.meshgrid(x, x, x)
def source_G(t):
center = np.exp(-0.5*(t-20)**2) * 10
gradient = (1+np.tanh(t-40)) * 0.0005
print("t = {}\tcenter potential = {}\tx-gradient = {}".format(t, center, gradient))
return -np.exp(-0.5*(x*x+y*y+z*z)) * center + x * gradient
source_functions = {
'G': source_G,
}
model_g = ModelG(
bl_noise(x.shape)*0.01,
bl_noise(x.shape)*0.01,
bl_noise(x.shape)*0.01,
dx,
params,
source_functions=source_functions,
)
def get_data():
G, X, Y = model_g.numpy()
x_scale = 0.1
y_scale = 0.1
return (
G[64, 64],
X[64, 64] * x_scale,
Y[64, 64] * y_scale,
)
G, X, Y = get_data()
plots = []
plots.extend(pylab.plot(z[0,0], G))
plots.extend(pylab.plot(z[0,0], X))
plots.extend(pylab.plot(z[0,0], Y))
pylab.ylim(-0.5, 0.5)
def update(frame):
model_g.step()
G, X, Y = get_data()
plots[0].set_ydata(G)
plots[1].set_ydata(X)
plots[2].set_ydata(Y)
return plots
FuncAnimation(pylab.gcf(), update, frames=range(100), init_func=lambda: plots, blit=True, repeat=True, interval=20)
pylab.show()
G, X, Y = model_g.numpy()
plots = [pylab.imshow(X[64])]
def update(frame):
model_g.step()
G, X, Y = model_g.numpy()
plots[0].set_data(X[64])
return plots
FuncAnimation(pylab.gcf(), update, frames=range(100), init_func=lambda: plots, blit=True, repeat=True, interval=20)
pylab.show()
fig = pylab.figure()
ax = fig.add_subplot(111, projection='3d')
G, X, Y = model_g.numpy()
m = X.max() - (X.max() - X.min()) * 0.3
points = []
for _ in range(1000000):
px = np.random.randint(x.shape[0])
py = np.random.randint(y.shape[1])
pz = np.random.randint(z.shape[2])
c = X[px, py, pz]
if c > m:
points.append((px, py, pz, c))
if len(points) > 20000:
break
xs, ys, zs, cs = zip(*points)
ax.scatter3D(xs, ys, zs, c=cs)
pylab.show()
if __name__ == '__main__':
# self_stabilizing_soliton_2D()
# self_stabilizing_soliton_3D()
nucleation_and_motion_in_G_gradient_1D()
# random_3D()
# nucleation_and_motion_in_G_gradient_2D()
| 23.951983
| 119
| 0.491153
| 1,811
| 11,473
| 2.996135
| 0.094975
| 0.015481
| 0.015481
| 0.066347
| 0.823996
| 0.811279
| 0.792849
| 0.756727
| 0.73885
| 0.731294
| 0
| 0.078272
| 0.324065
| 11,473
| 478
| 120
| 24.002092
| 0.621406
| 0.021703
| 0
| 0.709184
| 0
| 0
| 0.027639
| 0.002496
| 0
| 0
| 0
| 0
| 0
| 1
| 0.066327
| false
| 0
| 0.015306
| 0
| 0.132653
| 0.020408
| 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
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| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
271c8cc66066397467120508567e70c9aa0d742c
| 12,289
|
py
|
Python
|
espnet2/layers/encoder_decoder.py
|
ishine/DPSL-ASR
|
fabb66cbd7f24f7a05c64f5b7e87af154f39ceb2
|
[
"Apache-2.0"
] | null | null | null |
espnet2/layers/encoder_decoder.py
|
ishine/DPSL-ASR
|
fabb66cbd7f24f7a05c64f5b7e87af154f39ceb2
|
[
"Apache-2.0"
] | null | null | null |
espnet2/layers/encoder_decoder.py
|
ishine/DPSL-ASR
|
fabb66cbd7f24f7a05c64f5b7e87af154f39ceb2
|
[
"Apache-2.0"
] | 1
|
2022-03-25T14:51:17.000Z
|
2022-03-25T14:51:17.000Z
|
#!/usr/bin/env python3
from typing import Tuple
from typing import Optional
from typeguard import check_argument_types
import logging
import math
import torch
import torch.nn as nn
'''
by Yuchen on Aug 2, 2021
reference: 'Interactive Speech and Noise Modeling for Speech Enhancement'
https://arxiv.org/pdf/2012.09408.pdf
'''
class MSCAM(nn.Module):
def __init__(
self,
num_channels: int = 64,
r: int = 2,
):
check_argument_types()
super().__init__()
self.num_channels = num_channels
self.left = nn.Sequential(
nn.AdaptiveAvgPool2d(1),
nn.Conv2d(num_channels, num_channels // r, (1, 1), (1, 1)),
nn.BatchNorm2d(num_channels // r),
nn.PReLU(),
nn.Conv2d(num_channels // r, num_channels, (1, 1), (1, 1)),
nn.BatchNorm2d(num_channels),
)
self.right = nn.Sequential(
nn.Conv2d(num_channels, num_channels // r, (1, 1), (1, 1)),
nn.BatchNorm2d(num_channels // r),
nn.PReLU(),
nn.Conv2d(num_channels // r, num_channels, (1, 1), (1, 1)),
nn.BatchNorm2d(num_channels),
)
self.sigmoid = nn.Sigmoid()
def forward(
self,
x1, # (B, C, T, F)
x2, # (B, C, T, F)
):
x = x1 + x2
x_left = self.left(x) # (B, C, 1, 1)
x_right = self.right(x) # (B, C, T, F)
mask = self.sigmoid(x_left + x_right) # (B, C, T, F)
output = x1 * mask + x2 * (1 - mask) # (B, C, T, F)
return output
class AttnFuse(nn.Module):
def __init__(
self,
num_channels: int = 64,
):
check_argument_types()
super().__init__()
self.num_channels = num_channels
self.conv_mask = nn.Sequential(
nn.Conv2d(num_channels * 2, num_channels, (1, 1), (1, 1)),
nn.BatchNorm2d(num_channels),
nn.Sigmoid(),
)
self.mscam = MSCAM(num_channels)
def forward(
self,
x1, # (B, C, T, F)
x2, # (B, C, T, F)
):
x = torch.cat((x1, x2), dim=1) # (B, 2C, T, F)
mask = self.conv_mask(x) # (B, C, T, F)
output = self.mscam(x1 * mask, x2) # (B, C, T, F)
output = torch.cat((output, x2), dim=1) # (B, 2C, T, F)
return output
class AttnEncoder(nn.Module):
def __init__(
self,
num_channels: int = 64,
):
check_argument_types()
super().__init__()
self.conv_1 = nn.Sequential(
nn.Conv2d(1, num_channels // 2, (1, 1), (1, 1), (0, 0)),
nn.BatchNorm2d(num_channels // 2),
nn.PReLU(),
)
self.conv_2 = nn.Sequential(
nn.Conv2d(num_channels // 2, num_channels // 2, (3, 3), (1, 2), (1, 0)),
nn.BatchNorm2d(num_channels // 2),
nn.PReLU(),
)
self.conv_3 = nn.Sequential(
nn.Conv2d(num_channels // 2, num_channels, (3, 3), (1, 2), (1, 0)),
nn.BatchNorm2d(num_channels),
nn.PReLU(),
)
def forward(
self,
x: torch.Tensor, # (B, 1, T, F)
) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
x1 = self.conv_1(x) # (B, C/2, T, F)
x2 = self.conv_2(x1) # (B, C/2, T, F/2)
x3 = self.conv_3(x2) # (B, C, T, F/4)
return x3, [x3, x2, x1]
class AttnDecoder(nn.Module):
def __init__(
self,
num_channels: int = 64,
):
check_argument_types()
super().__init__()
self.attn_fuse3 = AttnFuse(num_channels)
self.conv_3 = nn.Sequential(
nn.ConvTranspose2d(num_channels * 2, num_channels // 2, (3, 3), (1, 2), (1, 0)),
nn.BatchNorm2d(num_channels // 2),
nn.PReLU(),
)
self.attn_fuse2 = AttnFuse(num_channels // 2)
self.conv_2 = nn.Sequential(
nn.ConvTranspose2d(num_channels, num_channels // 2, (3, 3), (1, 2), (1, 0), output_padding=(0, 1)),
nn.BatchNorm2d(num_channels // 2),
nn.PReLU(),
)
self.attn_fuse1 = AttnFuse(num_channels // 2)
self.conv_1 = nn.Sequential(
nn.Conv2d(num_channels, 1, (1, 1), (1, 1), (0, 0)),
nn.BatchNorm2d(1),
nn.PReLU(),
)
def forward(
self,
x: torch.Tensor, # (B, C, T, F/4)
x_list, # [(B, C, T, F/4), (B, C/2, T, F/2), (B, C/2, T, F)]
) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
x3 = self.attn_fuse3(x_list[0], x) # (B, 2C, T, F/4)
x3 = self.conv_3(x3) # (B, C/2, T, F/2)
x2 = self.attn_fuse2(x_list[1], x3) # (B, C, T, F/2)
x2 = self.conv_2(x2) # (B, C/2, T, F)
x1 = self.attn_fuse1(x_list[2], x2) # (B, C, T, F)
x1 = self.conv_1(x1) # (B, 1, T, F)
return x1
class Encoder(nn.Module):
def __init__(
self,
num_channels: int = 64,
):
check_argument_types()
super().__init__()
self.conv_1 = nn.Sequential(
nn.Conv2d(1, num_channels // 2, (1, 1), (1, 1), (0, 0)),
nn.BatchNorm2d(num_channels // 2),
nn.PReLU(),
)
self.conv_2 = nn.Sequential(
nn.Conv2d(num_channels // 2, num_channels // 2, (3, 3), (1, 2), (1, 0)),
nn.BatchNorm2d(num_channels // 2),
nn.PReLU(),
)
self.conv_3 = nn.Sequential(
nn.Conv2d(num_channels // 2, num_channels, (3, 3), (1, 2), (1, 0)),
nn.BatchNorm2d(num_channels),
nn.PReLU(),
)
def forward(
self,
x: torch.Tensor, # (B, 1, T, F)
) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
x1 = self.conv_1(x) # (B, C/2, T, F)
x2 = self.conv_2(x1) # (B, C/2, T, F/2)
x3 = self.conv_3(x2) # (B, C, T, F/4)
return x3, [x3, x2, x1]
class Decoder(nn.Module):
def __init__(
self,
num_channels: int = 64,
):
check_argument_types()
super().__init__()
self.conv_3 = nn.Sequential(
nn.ConvTranspose2d(num_channels * 2, num_channels // 2, (3, 3), (1, 2), (1, 0)),
nn.BatchNorm2d(num_channels // 2),
nn.PReLU(),
)
self.conv_2 = nn.Sequential(
nn.ConvTranspose2d(num_channels, num_channels // 2, (3, 3), (1, 2), (1, 0), output_padding=(0, 1)),
nn.BatchNorm2d(num_channels // 2),
nn.PReLU(),
)
self.conv_1 = nn.Sequential(
nn.Conv2d(num_channels, 1, (1, 1), (1, 1), (0, 0)),
nn.BatchNorm2d(1),
nn.PReLU(),
)
def forward(
self,
x: torch.Tensor, # (B, C, T, F/4)
x_list, # [(B, C, T, F/4), (B, C/2, T, F/2), (B, C/2, T, F)]
) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
x3 = torch.cat([x, x_list[0]], dim=1) # (B, 2C, T, F/4)
x3 = self.conv_3(x3) # (B, C/2, T, F/2)
x2 = torch.cat([x3, x_list[1]], dim=1) # (B, C, T, F/2)
x2 = self.conv_2(x2) # (B, C/2, T, F)
x1 = torch.cat([x2, x_list[2]], dim=1) # (B, C, T, F)
x1 = self.conv_1(x1) # (B, 1, T, F)
return x1
# class Encoder(nn.Module):
# def __init__(
# self,
# num_channels: int = 64,
# ):
# check_argument_types()
# super().__init__()
# self.conv_1 = nn.Sequential(
# nn.Conv2d(1, num_channels // 4, (1, 1), (1, 1), (0, 0)),
# nn.BatchNorm2d(num_channels // 4),
# nn.PReLU(),
# )
# self.conv_2 = nn.Sequential(
# nn.Conv2d(num_channels // 4, num_channels // 4, (1, 1), (1, 1), (0, 0)),
# nn.BatchNorm2d(num_channels // 4),
# nn.PReLU(),
# )
# self.conv_3 = nn.Sequential(
# nn.Conv2d(num_channels // 4, num_channels // 2, (3, 3), (1, 2), (1, 0)),
# nn.BatchNorm2d(num_channels // 2),
# nn.PReLU(),
# )
# self.conv_4 = nn.Sequential(
# nn.Conv2d(num_channels // 2, num_channels // 2, (1, 1), (1, 1), (0, 0)),
# nn.BatchNorm2d(num_channels // 2),
# nn.PReLU(),
# )
# self.conv_5 = nn.Sequential(
# nn.Conv2d(num_channels // 2, num_channels, (3, 3), (1, 2), (1, 0)),
# nn.BatchNorm2d(num_channels),
# nn.PReLU(),
# )
# self.conv_6 = nn.Sequential(
# nn.Conv2d(num_channels, num_channels, (1, 1), (1, 1), (0, 0)),
# nn.BatchNorm2d(num_channels),
# nn.PReLU(),
# )
# def forward(
# self,
# x: torch.Tensor, # (B, 1, T, F)
# ) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
# x1 = self.conv_1(x) # (B, C/4, T, F)
# x2 = self.conv_2(x1) # (B, C/4, T, F)
# x3 = self.conv_3(x2) # (B, C/2, T, F/2)
# x4 = self.conv_4(x3) # (B, C/2, T, F/2)
# x5 = self.conv_5(x4) # (B, C, T, F/4)
# x6 = self.conv_6(x5) # (B, C, T, F/4)
# return x6, [x6, x5, x4, x3, x2, x1]
# class Decoder(nn.Module):
# def __init__(
# self,
# num_channels: int = 64,
# ):
# check_argument_types()
# super().__init__()
# self.conv_6 = nn.Sequential(
# nn.Conv2d(num_channels * 2, num_channels, (1, 1), (1, 1), (0, 0)),
# nn.BatchNorm2d(num_channels),
# nn.PReLU(),
# )
# self.conv_5 = nn.Sequential(
# nn.ConvTranspose2d(num_channels * 2, num_channels // 2, (3, 3), (1, 2), (1, 0)),
# nn.BatchNorm2d(num_channels // 2),
# nn.PReLU(),
# )
# self.conv_4 = nn.Sequential(
# nn.Conv2d(num_channels, num_channels // 2, (1, 1), (1, 1), (0, 0)),
# nn.BatchNorm2d(num_channels // 2),
# nn.PReLU(),
# )
# self.conv_3 = nn.Sequential(
# nn.ConvTranspose2d(num_channels, num_channels // 4, (3, 3), (1, 2), (1, 0), output_padding=(0, 1)),
# nn.BatchNorm2d(num_channels // 4),
# nn.PReLU(),
# )
# self.conv_2 = nn.Sequential(
# nn.Conv2d(num_channels // 2, num_channels // 4, (1, 1), (1, 1), (0, 0)),
# nn.BatchNorm2d(num_channels // 4),
# nn.PReLU(),
# )
# self.conv_1 = nn.Sequential(
# nn.Conv2d(num_channels // 2, 1, (1, 1), (1, 1), (0, 0)),
# nn.BatchNorm2d(1),
# nn.PReLU(),
# )
# def forward(
# self,
# x: torch.Tensor, # (B, C, T, F/4)
# x_list, # [(B, C, T, F/4), (B, C, T, F/4), (B, C/2, T, F/2), (B, C/2, T, F/2), (B, C/4, T, F), (B, C/4, T, F)]
# ) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
# x6 = torch.cat([x, x_list[0]], dim=1) # (B, 2C, T, F/4)
# x6 = self.conv_6(x6) # (B, C, T, F/4)
# x5 = torch.cat([x6, x_list[1]], dim=1) # (B, 2C, T, F/4)
# x5 = self.conv_5(x5) # (B, C/2, T, F/2)
# x4 = torch.cat([x5, x_list[2]], dim=1) # (B, C, T, F/2)
# x4 = self.conv_4(x4) # (B, C/2, T, F/2)
# x3 = torch.cat([x4, x_list[3]], dim=1) # (B, C, T, F/2)
# x3 = self.conv_3(x3) # (B, C/4, T, F)
# x2 = torch.cat([x3, x_list[4]], dim=1) # (B, C/2, T, F)
# x2 = self.conv_2(x2) # (B, C/4, T, F)
# x1 = torch.cat([x2, x_list[5]], dim=1) # (B, C/2, T, F)
# x1 = self.conv_1(x1) # (B, 1, T, F)
# return x1
| 34.616901
| 132
| 0.444218
| 1,635
| 12,289
| 3.183486
| 0.058716
| 0.198655
| 0.089914
| 0.020749
| 0.864553
| 0.845533
| 0.827474
| 0.794621
| 0.776561
| 0.742555
| 0
| 0.074911
| 0.384083
| 12,289
| 354
| 133
| 34.714689
| 0.612763
| 0.404101
| 0
| 0.722222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.060606
| false
| 0
| 0.035354
| 0
| 0.156566
| 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
|
278365c8b68781c0a4e3de074c7809b4691fadc0
| 8,918
|
py
|
Python
|
Finance2Go/solvers/ParametersOfInterestRateAgreements.py
|
DenManokhin/Finance2Go
|
d8ad58ad8d6957e3b1c5809e44105552f6cfa05c
|
[
"MIT"
] | null | null | null |
Finance2Go/solvers/ParametersOfInterestRateAgreements.py
|
DenManokhin/Finance2Go
|
d8ad58ad8d6957e3b1c5809e44105552f6cfa05c
|
[
"MIT"
] | 4
|
2021-11-19T23:36:19.000Z
|
2021-12-07T22:41:43.000Z
|
Finance2Go/solvers/ParametersOfInterestRateAgreements.py
|
DenManokhin/Finance2Go
|
d8ad58ad8d6957e3b1c5809e44105552f6cfa05c
|
[
"MIT"
] | null | null | null |
import numpy as np
# 1
def get_years_period_duration_with_i(p: float, s: float, i:float) -> float:
""""
Повертає тривалість періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
i : float
Відсоткова ставка віднесена до певного періоду
Returns
-------
n : float Тривалість періоду у роках.
"""
return (s/p - 1) / i
# 2
def get_years_period_duration_with_d(p: float, s: float, d:float) -> float:
""""
Повертає тривалість періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
d : float
Облікова ставка
Returns
-------
n : float Тривалість періоду у роках.
"""
return (1 - p/s) / d
# 3
def get_days_period_duration_with_i(p: float, s: float,
i: float, k: int) -> float:
""""
Повертає тривалість періоду у днях.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
i : float
Відсоткова ставка віднесена до певного періоду
Returns
-------
t : float Тривалість періоду у днях.
"""
return ((s/p - 1) / i) * k
# 4
def get_days_period_duration_with_d(p: float, s: float,
d: float, k: int) -> float:
""""
Повертає тривалість періоду у днях.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
d : float
Облікова ставка
k: int
Часова база нарахування відсотків
Returns
-------
t : float Тривалість періоду у днях.
"""
return ((1 - p/s) / d) * k
# 5
def get_interest_rate_with_years_period_duration(p: float, s: float,
n: float) -> float:
""""
Повертає відсоткову ставку для періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
n : float
Тривалість періоду у роках
Returns
-------
i : float Відсоткова ставка віднесена до певного періоду.
"""
return (s/p - 1) / n
# 6
def get_discount_rate_with_years_period_duration(p: float, s: float,
n: float) -> float:
""""
Повертає облікову ставку для періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
n : float
Тривалість періоду у роках
Returns
-------
d : float Облікова ставка віднесена до певного періоду.
"""
return (1 - p/s) / n
# 7
def get_interest_rate_with_days_period_duration(p: float, s: float,
t: float, k: int) -> float:
""""
Повертає відсоткову ставку для періоду у днях.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
t : float
Тривалість періоду у днях
k: int
Часова база нарахування відсотків
Returns
-------
i : float Відсоткова ставка віднесена до певного періоду.
"""
return ((s/p - 1) / t) * k
# 8
def get_discount_rate_with_days_period_duration(p: float, s: float,
t: float, k: int) -> float:
""""
Повертає облікову ставку для періоду у днях.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
t : float
Тривалість періоду у днях
k: int
Часова база нарахування відсотків
Returns
-------
d : float Облікова ставка віднесена до певного періоду.
"""
return ((1 - p/s) / t) * k
# 10
def get_complex_interest_years_period_duration_with_i(p: float, s: float,
i: float) -> float:
""""
Повертає тривалість періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
i : float
Відсоткова ставка віднесена до певного періоду
Returns
-------
n : float Тривалість періоду у роках.
"""
return np.log(s/p) / np.log(1 + i)
# 11
def get_complex_interest_years_period_duration_with_d(p: float, s: float,
d: float) -> float:
""""
Повертає тривалість періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
d : float
Облікова ставка
Returns
-------
n : float Тривалість періоду у роках.
"""
return np.log(p/s) / np.log(1 - d)
# 12
def get_years_period_duration_with_j(p: float, s: float,
j: float, m: int) -> float:
""""
Повертає тривалість періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
j : float
Річний множник нарощення за номінальною ставкою
m: int
Кількість нарахувань у році.
Returns
-------
n : float Тривалість періоду у роках.
"""
return np.log(s/p) / (m * np.log(1 + j/m))
# 13
def get_years_period_duration_with_f(p: float, s: float,
f: float, m: int) -> float:
""""
Повертає тривалість періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
f : float
Номінальна річна облікова ставка
m: int
Кількість нарахувань у році.
Returns
-------
n : float Тривалість періоду у роках.
"""
return np.log(p/s) / (m * np.log(1 + f/m))
# 14
def get_complex_interest_interest_rate_with_years_period_duration(
p: float,
s: float,
n: float) -> float:
""""
Повертає відсоткову ставку для періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
n : float
Тривалість періоду у роках
Returns
-------
i : float Відсоткова ставка віднесена до певного періоду.
"""
return (s/p)**(1/n) - 1
# 15
def get_complex_interest_discount_rate_with_years_period_duration(
p: float,
s: float,
n: float) -> float:
""""
Повертає облікову ставку для періоду у роках.
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
n : float
Тривалість періоду у роках
Returns
-------
d : float Облікова ставка віднесена до певного періоду.
"""
return 1 - (p/s)**(1/n)
# 16
def get_annual_accumulation_factor_with_years_period_duration(p: float,
s: float,
n: float,
m: int) -> float:
""""
Повертає річний множник нарощення за номінальною ставкою
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
n : float
Тривалість періоду у роках
m : int
Кількість нарахувань в році
Returns
-------
j : float Річний множник нарощення за номінальною ставкою.
"""
return ((s/p)**(1/n*m) - 1) * m
# 17
def get_annual_discount_rate_with_years_period_duration(p: float,
s: float,
n: float,
m: int) -> float:
""""
Повертає номінальну річну облікову ставку
Parameters
----------
p : float
Сума грошей (капітал), що даються в борг
s : float
Нарощена сума боргу
n : float
Тривалість періоду у роках
m : int
Кількість нарахувань в році
Returns
-------
f : float Номінальна річна облікова ставка.
"""
return (1 - (p/s)**(1/n*m)) * m
| 24.910615
| 79
| 0.505607
| 990
| 8,918
| 4.455556
| 0.092929
| 0.043528
| 0.097937
| 0.093856
| 0.948991
| 0.934029
| 0.885287
| 0.873498
| 0.82521
| 0.82521
| 0
| 0.008185
| 0.397174
| 8,918
| 357
| 80
| 24.980392
| 0.812314
| 0.51682
| 0
| 0.290909
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.290909
| false
| 0
| 0.018182
| 0
| 0.6
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
27991fd6917892ee77ffc6de492284f4ad3db331
| 146
|
py
|
Python
|
test/test_paintball.py
|
erichaase/topcoder-python
|
de285d8092a94f2ec1b5c0c33eba55b5c27a5390
|
[
"MIT"
] | 1
|
2017-03-25T17:40:57.000Z
|
2017-03-25T17:40:57.000Z
|
test/test_paintball.py
|
erichaase/topcoder-python
|
de285d8092a94f2ec1b5c0c33eba55b5c27a5390
|
[
"MIT"
] | null | null | null |
test/test_paintball.py
|
erichaase/topcoder-python
|
de285d8092a94f2ec1b5c0c33eba55b5c27a5390
|
[
"MIT"
] | null | null | null |
from test.assert_json import assert_json
from topcoder.paintball import solution
def test_paintball ():
assert_json('paintball', solution)
| 24.333333
| 42
| 0.794521
| 19
| 146
| 5.894737
| 0.473684
| 0.267857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136986
| 146
| 5
| 43
| 29.2
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0.061644
| 0
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0.25
| true
| 0
| 0.5
| 0
| 0.75
| 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
| 1
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
27b100d331409732f5388a139c1378a169b3a11d
| 82
|
py
|
Python
|
apps/oob/views/__init__.py
|
dbjennings/order-of-business
|
8f424bd36b323e4c102b3d8704bb576c150d585a
|
[
"MIT"
] | null | null | null |
apps/oob/views/__init__.py
|
dbjennings/order-of-business
|
8f424bd36b323e4c102b3d8704bb576c150d585a
|
[
"MIT"
] | null | null | null |
apps/oob/views/__init__.py
|
dbjennings/order-of-business
|
8f424bd36b323e4c102b3d8704bb576c150d585a
|
[
"MIT"
] | null | null | null |
from apps.oob.views.task_views import *
from apps.oob.views.project_views import *
| 41
| 42
| 0.817073
| 14
| 82
| 4.642857
| 0.5
| 0.246154
| 0.338462
| 0.492308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085366
| 82
| 2
| 42
| 41
| 0.866667
| 0
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| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
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| null | 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
27b470a8499c5f8342b5907375007741b0043c6c
| 2,257
|
py
|
Python
|
foundations_ui/cypress/fixtures/atlas_scheduler/log_param/log_param_project/ints.py
|
DeepLearnI/atlas
|
8aca652d7e647b4e88530b93e265b536de7055ed
|
[
"Apache-2.0"
] | 296
|
2020-03-16T19:55:00.000Z
|
2022-01-10T19:46:05.000Z
|
foundations_ui/cypress/fixtures/atlas_scheduler/log_param/log_param_project/ints.py
|
DeepLearnI/atlas
|
8aca652d7e647b4e88530b93e265b536de7055ed
|
[
"Apache-2.0"
] | 57
|
2020-03-17T11:15:57.000Z
|
2021-07-10T14:42:27.000Z
|
foundations_ui/cypress/fixtures/atlas_scheduler/log_param/log_param_project/ints.py
|
DeepLearnI/atlas
|
8aca652d7e647b4e88530b93e265b536de7055ed
|
[
"Apache-2.0"
] | 38
|
2020-03-17T21:06:05.000Z
|
2022-02-08T03:19:34.000Z
|
import foundations
from time import sleep
foundations.log_param("param_int", 1)
foundations.log_param("param_large_int", 8888888888888888888888888)
foundations.log_param("param_list_of_ints", [1, 2])
foundations.log_param("param_long_list_of_ints", [1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2])
foundations.log_param("param_long_list_of_long_ints", [8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888,
8888888888888888888888888])
foundations.log_param("param_mixed_type", 1)
for i in range(20):
foundations.log_param("param_repeat", i)
sleep(.1)
| 64.485714
| 158
| 0.424014
| 124
| 2,257
| 7.516129
| 0.193548
| 1.180258
| 1.689914
| 2.145923
| 0.824034
| 0.730687
| 0.730687
| 0.730687
| 0.730687
| 0.655579
| 0
| 0.601497
| 0.526362
| 2,257
| 34
| 159
| 66.382353
| 0.270346
| 0
| 0
| 0.636364
| 0
| 0
| 0.053611
| 0.022596
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.060606
| 0
| 0.060606
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 12
|
27c1621002268e065bbcb12a37a6b4ca74282840
| 3,447
|
py
|
Python
|
net/NeuralNets.py
|
mbed92/soft-grip
|
4399a4ab719bf29303769de33977a037624d864d
|
[
"MIT"
] | 5
|
2020-01-19T08:55:55.000Z
|
2021-07-08T13:12:24.000Z
|
net/NeuralNets.py
|
mbed92/soft-grip
|
4399a4ab719bf29303769de33977a037624d864d
|
[
"MIT"
] | null | null | null |
net/NeuralNets.py
|
mbed92/soft-grip
|
4399a4ab719bf29303769de33977a037624d864d
|
[
"MIT"
] | 1
|
2020-06-28T08:20:33.000Z
|
2020-06-28T08:20:33.000Z
|
import tensorflow as tf
from .layers import _create_signal_network
class ConvNet(tf.keras.Model):
def __init__(self, batch_size):
super(ConvNet, self).__init__()
self.batch_size = batch_size
self.conv1d, _, self.fc = _create_signal_network(batch_size,
num_outputs=1,
conv_filters=[128, 256, 512],
conv_kernels=[3, 3, 3],
conv_strides=[2, 2, 2],
bilstm_units=[],
fc_layers=[512, 256, 128, 64])
self.pooling = tf.keras.layers.GlobalAveragePooling1D()
def call(self, inputs, training=None, mask=None):
inputs = tf.cast(inputs, tf.float32)
x = self.conv1d(inputs, training=training)
x = self.pooling(x, training=training)
x = self.fc(x, training=training)
return x
class ConvBiLstmNet(tf.keras.Model):
def __init__(self, batch_size):
super(ConvBiLstmNet, self).__init__()
self.batch_size = batch_size
self.conv1d, self.lstm, self.fc = _create_signal_network(batch_size,
num_outputs=1,
conv_filters=[128, 256, 256],
conv_kernels=[3, 3, 3],
conv_strides=[2, 2, 2],
bilstm_units=[128],
fc_layers=[512, 256, 128, 64])
self.pooling = tf.keras.layers.GlobalAveragePooling1D()
def call(self, inputs, training=None, mask=None):
inputs = tf.cast(inputs, tf.float32)
x = self.conv1d(inputs, training=training)
x = self.lstm(x, training=training)
x = self.fc(x, training=training)
return x
class ConvLstmNet(tf.keras.Model):
def __init__(self, batch_size):
super(ConvLstmNet, self).__init__()
self.batch_size = batch_size
self.conv1d, _, self.fc = _create_signal_network(batch_size,
num_outputs=1,
conv_filters=[128, 256, 256],
conv_kernels=[3, 3, 3],
conv_strides=[2, 2, 2],
bilstm_units=[],
fc_layers=[512, 256, 128, 64])
self.lstm = tf.keras.Sequential([
tf.keras.layers.LSTM(128, return_sequences=True, dtype=tf.float64, dropout=0.3),
tf.keras.layers.LSTM(128, return_sequences=False, dtype=tf.float64, dropout=0.3)
])
self.pooling = tf.keras.layers.GlobalAveragePooling1D()
def call(self, inputs, training=None, mask=None):
inputs = tf.cast(inputs, tf.float32)
x = self.conv1d(inputs, training=training)
x = self.lstm(x, training=training)
x = self.fc(x, training=training)
return x
| 42.555556
| 95
| 0.454308
| 328
| 3,447
| 4.560976
| 0.176829
| 0.072193
| 0.052139
| 0.068182
| 0.887032
| 0.887032
| 0.856283
| 0.809492
| 0.809492
| 0.735294
| 0
| 0.059947
| 0.453148
| 3,447
| 80
| 96
| 43.0875
| 0.733687
| 0
| 0
| 0.733333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.1
| false
| 0
| 0.033333
| 0
| 0.233333
| 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
|
27de09abaf0058b5d02c604890dfd44ace203142
| 4,953
|
py
|
Python
|
instructions/fixedpointarithmetic.py
|
RenolY2/python-ppc
|
7b7ccbaf467813843975773795efa3436544ca9a
|
[
"MIT"
] | 3
|
2019-09-04T07:18:00.000Z
|
2021-03-09T23:41:38.000Z
|
instructions/fixedpointarithmetic.py
|
RenolY2/python-ppc
|
7b7ccbaf467813843975773795efa3436544ca9a
|
[
"MIT"
] | null | null | null |
instructions/fixedpointarithmetic.py
|
RenolY2/python-ppc
|
7b7ccbaf467813843975773795efa3436544ca9a
|
[
"MIT"
] | null | null | null |
from .common import *
class AddImmediate(Instruction):
def __init__(self, val):
self.opcode, self.RT, self.RA, self.SI = parse_dform(val)
self.SI = sign_extend_short(self.SI)
def execute(self, machine):
gpr = machine.context.gpr
if self.RA == 0:
gpr[self.RT] = self.SI
else:
gpr[self.RT] = add_32bit(gpr[self.RA], self.SI)
def __str__(self):
SI = to_python_int(self.SI)
if self.RA == 0:
return "li r{0}, {1}".format(self.RT, SI)
elif SI < 0:
return "subi r{0}, r{1}, {2}".format(self.RT, self.RA, -SI)
else:
return "addi r{0}, r{1}, {2}".format(self.RT, self.RA, SI)
class AddImmediateShifted(Instruction):
def __init__(self, val):
self.opcode, self.RT, self.RA, self.SI = parse_dform(val)
self.SI = sign_extend_short(self.SI)
def execute(self, machine):
gpr = machine.context.gpr
SI = (self.SI << 16) & 0xFFFFFFFF
if self.RA == 0:
gpr[self.RT] = SI
else:
gpr[self.RT] = add_32bit(gpr[self.RA], SI)
def __str__(self):
SI = to_python_int(self.SI)
if self.RA == 0:
return "lis r{0}, {1}".format(self.RT, self.SI)
elif SI < 0:
return "subis r{0}, r{1}, {2}".format(self.RT, self.RA, -SI)
else:
return "addis r{0}, r{1}, {2}".format(self.RT, self.RA, SI)
class Add(Instruction):
def __init__(self, val):
self.opcode, self.RT, self.RA, self.RB, self.OE, self.opcode2, self.RC = parse_xoform(val)
def execute(self, machine):
gpr = machine.context.gpr
gpr[self.RT], ovhappened = add_32bit_overflow(gpr[self.RA], gpr[self.RB])
if self.OE:
raise RuntimeError("Overflow not supported yet")
if self.RC == 1:
machine.context.cr.compare(0, to_python_int(gpr[self.RT]), 0)
def __str__(self):
instruction = "add"
if self.OE:
instruction += "o"
if self.RC:
instruction += "."
return "{0} r{1}, r{2}, r{3}".format(instruction, self.RT, self.RA, self.RB)
class SubtractFrom(Instruction):
def __init__(self, val):
self.opcode, self.RT, self.RA, self.RB, self.OE, self.opcode2, self.RC = parse_xoform(val)
def execute(self, machine):
gpr = machine.context.gpr
gpr[self.RT], ovhappened = add_32bit_overflow(negate(gpr[self.RA]), gpr[self.RB])
if self.OE:
raise RuntimeError("Overflow not supported yet")
if self.RC == 1:
machine.context.cr.compare(0, to_python_int(gpr[self.RT]), 0)
def __str__(self):
instruction = "sub"
if self.OE:
instruction += "o"
if self.RC:
instruction += "."
return "{0} r{1}, r{3}, r{2}".format(instruction, self.RT, self.RA, self.RB)
class SubtractFromImmediateCarrying(Instruction):
def __init__(self, val):
self.opcode, self.RT, self.RA, self.SI = parse_dform(val)
self.SI = sign_extend_short(self.SI)
def execute(self, machine):
gpr = machine.context.gpr
gpr[self.RT], ov = add_32bit_overflow(negate(gpr[self.RA]), self.SI)
if ov:
machine.xer.CA = 1
else:
machine.xer.CA = 0
def __str__(self):
SI = to_python_int(self.SI)
return "subfic r{0}, r{1}, {2}".format(self.RT, self.RA, SI)
class AddImmediateCarrying(Instruction):
def __init__(self, val):
self.opcode, self.RT, self.RA, self.SI = parse_dform(val)
self.SI = sign_extend_short(self.SI)
def execute(self, machine):
gpr = machine.context.gpr
gpr[self.RT], ov = add_32bit_overflow(gpr[self.RA], self.SI)
if ov:
machine.context.xer.CA = 1
else:
machine.context.xer.CA = 0
def __str__(self):
SI = to_python_int(self.SI)
return "addic r{0}, r{1}, {2}".format(self.RT, self.RA, SI)
class AddImmediateCarryingRecord(Instruction):
def __init__(self, val):
self.opcode, self.RT, self.RA, self.SI = parse_dform(val)
self.SI = sign_extend_short(self.SI)
def execute(self, machine):
gpr = machine.context.gpr
gpr[self.RT], ov = add_32bit_overflow(gpr[self.RA], self.SI)
if ov:
machine.context.xer.CA = 1
else:
machine.context.xer.CA = 0
machine.context.cr.compare(0, to_python_int(gpr[self.RT]), 0)
def __str__(self):
SI = to_python_int(self.SI)
return "addic. r{0}, r{1}, {2}".format(self.RT, self.RA, SI)
| 30.386503
| 98
| 0.539673
| 669
| 4,953
| 3.844544
| 0.110613
| 0.07465
| 0.069984
| 0.07465
| 0.917963
| 0.898134
| 0.88647
| 0.867807
| 0.857698
| 0.826594
| 0
| 0.021461
| 0.322633
| 4,953
| 163
| 99
| 30.386503
| 0.745156
| 0
| 0
| 0.730435
| 0
| 0
| 0.055309
| 0
| 0
| 0
| 0.002019
| 0
| 0
| 1
| 0.182609
| false
| 0
| 0.008696
| 0
| 0.347826
| 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
|
7e1228de302e4026c84c79bb15044e94b045da16
| 18,051
|
py
|
Python
|
sdk/python/pulumi_gcp/essentialcontacts/contact.py
|
sisisin/pulumi-gcp
|
af6681d70ea457843409110c1324817fe55f68ad
|
[
"ECL-2.0",
"Apache-2.0"
] | 121
|
2018-06-18T19:16:42.000Z
|
2022-03-31T06:06:48.000Z
|
sdk/python/pulumi_gcp/essentialcontacts/contact.py
|
sisisin/pulumi-gcp
|
af6681d70ea457843409110c1324817fe55f68ad
|
[
"ECL-2.0",
"Apache-2.0"
] | 492
|
2018-06-22T19:41:03.000Z
|
2022-03-31T15:33:53.000Z
|
sdk/python/pulumi_gcp/essentialcontacts/contact.py
|
sisisin/pulumi-gcp
|
af6681d70ea457843409110c1324817fe55f68ad
|
[
"ECL-2.0",
"Apache-2.0"
] | 43
|
2018-06-19T01:43:13.000Z
|
2022-03-23T22:43:37.000Z
|
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
__all__ = ['ContactArgs', 'Contact']
@pulumi.input_type
class ContactArgs:
def __init__(__self__, *,
email: pulumi.Input[str],
language_tag: pulumi.Input[str],
notification_category_subscriptions: pulumi.Input[Sequence[pulumi.Input[str]]],
parent: pulumi.Input[str]):
"""
The set of arguments for constructing a Contact resource.
:param pulumi.Input[str] email: The email address to send notifications to. This does not need to be a Google account.
:param pulumi.Input[str] language_tag: The preferred language for notifications, as a ISO 639-1 language code. See Supported languages for a list of supported languages.
:param pulumi.Input[Sequence[pulumi.Input[str]]] notification_category_subscriptions: The categories of notifications that the contact will receive communications for.
:param pulumi.Input[str] parent: The resource to save this contact for. Format: organizations/{organization_id}, folders/{folder_id} or projects/{project_id}
"""
pulumi.set(__self__, "email", email)
pulumi.set(__self__, "language_tag", language_tag)
pulumi.set(__self__, "notification_category_subscriptions", notification_category_subscriptions)
pulumi.set(__self__, "parent", parent)
@property
@pulumi.getter
def email(self) -> pulumi.Input[str]:
"""
The email address to send notifications to. This does not need to be a Google account.
"""
return pulumi.get(self, "email")
@email.setter
def email(self, value: pulumi.Input[str]):
pulumi.set(self, "email", value)
@property
@pulumi.getter(name="languageTag")
def language_tag(self) -> pulumi.Input[str]:
"""
The preferred language for notifications, as a ISO 639-1 language code. See Supported languages for a list of supported languages.
"""
return pulumi.get(self, "language_tag")
@language_tag.setter
def language_tag(self, value: pulumi.Input[str]):
pulumi.set(self, "language_tag", value)
@property
@pulumi.getter(name="notificationCategorySubscriptions")
def notification_category_subscriptions(self) -> pulumi.Input[Sequence[pulumi.Input[str]]]:
"""
The categories of notifications that the contact will receive communications for.
"""
return pulumi.get(self, "notification_category_subscriptions")
@notification_category_subscriptions.setter
def notification_category_subscriptions(self, value: pulumi.Input[Sequence[pulumi.Input[str]]]):
pulumi.set(self, "notification_category_subscriptions", value)
@property
@pulumi.getter
def parent(self) -> pulumi.Input[str]:
"""
The resource to save this contact for. Format: organizations/{organization_id}, folders/{folder_id} or projects/{project_id}
"""
return pulumi.get(self, "parent")
@parent.setter
def parent(self, value: pulumi.Input[str]):
pulumi.set(self, "parent", value)
@pulumi.input_type
class _ContactState:
def __init__(__self__, *,
email: Optional[pulumi.Input[str]] = None,
language_tag: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
notification_category_subscriptions: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
parent: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering Contact resources.
:param pulumi.Input[str] email: The email address to send notifications to. This does not need to be a Google account.
:param pulumi.Input[str] language_tag: The preferred language for notifications, as a ISO 639-1 language code. See Supported languages for a list of supported languages.
:param pulumi.Input[str] name: The identifier for the contact. Format: {resourceType}/{resource_id}/contacts/{contact_id}
:param pulumi.Input[Sequence[pulumi.Input[str]]] notification_category_subscriptions: The categories of notifications that the contact will receive communications for.
:param pulumi.Input[str] parent: The resource to save this contact for. Format: organizations/{organization_id}, folders/{folder_id} or projects/{project_id}
"""
if email is not None:
pulumi.set(__self__, "email", email)
if language_tag is not None:
pulumi.set(__self__, "language_tag", language_tag)
if name is not None:
pulumi.set(__self__, "name", name)
if notification_category_subscriptions is not None:
pulumi.set(__self__, "notification_category_subscriptions", notification_category_subscriptions)
if parent is not None:
pulumi.set(__self__, "parent", parent)
@property
@pulumi.getter
def email(self) -> Optional[pulumi.Input[str]]:
"""
The email address to send notifications to. This does not need to be a Google account.
"""
return pulumi.get(self, "email")
@email.setter
def email(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "email", value)
@property
@pulumi.getter(name="languageTag")
def language_tag(self) -> Optional[pulumi.Input[str]]:
"""
The preferred language for notifications, as a ISO 639-1 language code. See Supported languages for a list of supported languages.
"""
return pulumi.get(self, "language_tag")
@language_tag.setter
def language_tag(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "language_tag", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
The identifier for the contact. Format: {resourceType}/{resource_id}/contacts/{contact_id}
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@property
@pulumi.getter(name="notificationCategorySubscriptions")
def notification_category_subscriptions(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
The categories of notifications that the contact will receive communications for.
"""
return pulumi.get(self, "notification_category_subscriptions")
@notification_category_subscriptions.setter
def notification_category_subscriptions(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "notification_category_subscriptions", value)
@property
@pulumi.getter
def parent(self) -> Optional[pulumi.Input[str]]:
"""
The resource to save this contact for. Format: organizations/{organization_id}, folders/{folder_id} or projects/{project_id}
"""
return pulumi.get(self, "parent")
@parent.setter
def parent(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "parent", value)
class Contact(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
email: Optional[pulumi.Input[str]] = None,
language_tag: Optional[pulumi.Input[str]] = None,
notification_category_subscriptions: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
parent: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
A contact that will receive notifications from Google Cloud.
To get more information about Contact, see:
* [API documentation](https://cloud.google.com/resource-manager/docs/reference/essentialcontacts/rest/v1beta1/projects.contacts)
* How-to Guides
* [Official Documentation](https://cloud.google.com/resource-manager/docs/managing-notification-contacts)
> **Warning:** If you are using User ADCs (Application Default Credentials) with this resource,
you must specify a `billing_project` and set `user_project_override` to true
in the provider configuration. Otherwise the Essential Contacts API will return a 403 error.
Your account must have the `serviceusage.services.use` permission on the
`billing_project` you defined.
## Example Usage
### Essential Contact
```python
import pulumi
import pulumi_gcp as gcp
project = gcp.organizations.get_project()
contact = gcp.essentialcontacts.Contact("contact",
parent=project.id,
email="foo@bar.com",
language_tag="en-GB",
notification_category_subscriptions=["ALL"])
```
## Import
Contact can be imported using any of these accepted formats
```sh
$ pulumi import gcp:essentialcontacts/contact:Contact default {{name}}
```
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] email: The email address to send notifications to. This does not need to be a Google account.
:param pulumi.Input[str] language_tag: The preferred language for notifications, as a ISO 639-1 language code. See Supported languages for a list of supported languages.
:param pulumi.Input[Sequence[pulumi.Input[str]]] notification_category_subscriptions: The categories of notifications that the contact will receive communications for.
:param pulumi.Input[str] parent: The resource to save this contact for. Format: organizations/{organization_id}, folders/{folder_id} or projects/{project_id}
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: ContactArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
A contact that will receive notifications from Google Cloud.
To get more information about Contact, see:
* [API documentation](https://cloud.google.com/resource-manager/docs/reference/essentialcontacts/rest/v1beta1/projects.contacts)
* How-to Guides
* [Official Documentation](https://cloud.google.com/resource-manager/docs/managing-notification-contacts)
> **Warning:** If you are using User ADCs (Application Default Credentials) with this resource,
you must specify a `billing_project` and set `user_project_override` to true
in the provider configuration. Otherwise the Essential Contacts API will return a 403 error.
Your account must have the `serviceusage.services.use` permission on the
`billing_project` you defined.
## Example Usage
### Essential Contact
```python
import pulumi
import pulumi_gcp as gcp
project = gcp.organizations.get_project()
contact = gcp.essentialcontacts.Contact("contact",
parent=project.id,
email="foo@bar.com",
language_tag="en-GB",
notification_category_subscriptions=["ALL"])
```
## Import
Contact can be imported using any of these accepted formats
```sh
$ pulumi import gcp:essentialcontacts/contact:Contact default {{name}}
```
:param str resource_name: The name of the resource.
:param ContactArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(ContactArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
email: Optional[pulumi.Input[str]] = None,
language_tag: Optional[pulumi.Input[str]] = None,
notification_category_subscriptions: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
parent: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = ContactArgs.__new__(ContactArgs)
if email is None and not opts.urn:
raise TypeError("Missing required property 'email'")
__props__.__dict__["email"] = email
if language_tag is None and not opts.urn:
raise TypeError("Missing required property 'language_tag'")
__props__.__dict__["language_tag"] = language_tag
if notification_category_subscriptions is None and not opts.urn:
raise TypeError("Missing required property 'notification_category_subscriptions'")
__props__.__dict__["notification_category_subscriptions"] = notification_category_subscriptions
if parent is None and not opts.urn:
raise TypeError("Missing required property 'parent'")
__props__.__dict__["parent"] = parent
__props__.__dict__["name"] = None
super(Contact, __self__).__init__(
'gcp:essentialcontacts/contact:Contact',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
email: Optional[pulumi.Input[str]] = None,
language_tag: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
notification_category_subscriptions: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
parent: Optional[pulumi.Input[str]] = None) -> 'Contact':
"""
Get an existing Contact resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] email: The email address to send notifications to. This does not need to be a Google account.
:param pulumi.Input[str] language_tag: The preferred language for notifications, as a ISO 639-1 language code. See Supported languages for a list of supported languages.
:param pulumi.Input[str] name: The identifier for the contact. Format: {resourceType}/{resource_id}/contacts/{contact_id}
:param pulumi.Input[Sequence[pulumi.Input[str]]] notification_category_subscriptions: The categories of notifications that the contact will receive communications for.
:param pulumi.Input[str] parent: The resource to save this contact for. Format: organizations/{organization_id}, folders/{folder_id} or projects/{project_id}
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _ContactState.__new__(_ContactState)
__props__.__dict__["email"] = email
__props__.__dict__["language_tag"] = language_tag
__props__.__dict__["name"] = name
__props__.__dict__["notification_category_subscriptions"] = notification_category_subscriptions
__props__.__dict__["parent"] = parent
return Contact(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter
def email(self) -> pulumi.Output[str]:
"""
The email address to send notifications to. This does not need to be a Google account.
"""
return pulumi.get(self, "email")
@property
@pulumi.getter(name="languageTag")
def language_tag(self) -> pulumi.Output[str]:
"""
The preferred language for notifications, as a ISO 639-1 language code. See Supported languages for a list of supported languages.
"""
return pulumi.get(self, "language_tag")
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
"""
The identifier for the contact. Format: {resourceType}/{resource_id}/contacts/{contact_id}
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="notificationCategorySubscriptions")
def notification_category_subscriptions(self) -> pulumi.Output[Sequence[str]]:
"""
The categories of notifications that the contact will receive communications for.
"""
return pulumi.get(self, "notification_category_subscriptions")
@property
@pulumi.getter
def parent(self) -> pulumi.Output[str]:
"""
The resource to save this contact for. Format: organizations/{organization_id}, folders/{folder_id} or projects/{project_id}
"""
return pulumi.get(self, "parent")
| 46.16624
| 177
| 0.667553
| 2,080
| 18,051
| 5.599038
| 0.105769
| 0.07084
| 0.072128
| 0.041559
| 0.854628
| 0.826206
| 0.79684
| 0.77606
| 0.760261
| 0.731324
| 0
| 0.002831
| 0.236884
| 18,051
| 390
| 178
| 46.284615
| 0.842613
| 0.416376
| 0
| 0.556701
| 1
| 0
| 0.112767
| 0.051575
| 0
| 0
| 0
| 0
| 0
| 1
| 0.154639
| false
| 0.005155
| 0.025773
| 0
| 0.273196
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
fdb746d95a16c7ef15da34b65defd8ed81b2564f
| 156
|
py
|
Python
|
pyconfidentiality/__init__.py
|
smaranjitghose/pyconfidentiality
|
cd5fd6f73a5150c2b58e741dac2eef7318c9d448
|
[
"MIT"
] | 1
|
2020-07-19T21:42:07.000Z
|
2020-07-19T21:42:07.000Z
|
pyconfidentiality/__init__.py
|
smaranjitghose/pyconfidentiality
|
cd5fd6f73a5150c2b58e741dac2eef7318c9d448
|
[
"MIT"
] | null | null | null |
pyconfidentiality/__init__.py
|
smaranjitghose/pyconfidentiality
|
cd5fd6f73a5150c2b58e741dac2eef7318c9d448
|
[
"MIT"
] | null | null | null |
from .concealer import encrypt_message
from .concealer import generate_keypair
from .concealer import decrypt_message
from .send_email import send_message
| 26
| 39
| 0.865385
| 21
| 156
| 6.190476
| 0.47619
| 0.3
| 0.438462
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108974
| 156
| 5
| 40
| 31.2
| 0.935252
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
fddd5560a2f1d5f67d17d4629598c1f24c0ae5e4
| 20,261
|
py
|
Python
|
migrations/versions/30115ede2fc7_added_kazr1_to_prosensing_paf.py
|
ARM-DOE/warno
|
231f0eb87fa3011133f361ebac780fc21d0968c6
|
[
"BSD-3-Clause"
] | 4
|
2017-08-09T15:27:19.000Z
|
2021-03-11T07:16:09.000Z
|
migrations/versions/30115ede2fc7_added_kazr1_to_prosensing_paf.py
|
ARM-DOE/warno
|
231f0eb87fa3011133f361ebac780fc21d0968c6
|
[
"BSD-3-Clause"
] | null | null | null |
migrations/versions/30115ede2fc7_added_kazr1_to_prosensing_paf.py
|
ARM-DOE/warno
|
231f0eb87fa3011133f361ebac780fc21d0968c6
|
[
"BSD-3-Clause"
] | 2
|
2017-08-09T15:27:28.000Z
|
2019-05-22T16:09:06.000Z
|
"""Added KAZR1 to prosensing_paf
Revision ID: 30115ede2fc7
Revises: 37b800d049f7
Create Date: 2016-06-28 15:33:50.135812
"""
# revision identifiers, used by Alembic.
revision = '30115ede2fc7'
down_revision = '37b800d049f7'
branch_labels = None
depends_on = None
from alembic import op
import sqlalchemy as sa
def upgrade():
op.add_column('prosensing_paf', sa.Column('one_twenty_mhz_plo_lock', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('sixteen_twenty_mhz_plo_lock', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('one_sixty_five_sixty_mhz_plo_lock', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('three_sixty_mhz_plo_lock', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('ad_skip_count_ch1', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('ad_skip_count_ch2', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('antenna_feedhorn_temp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('asp_internal_delay', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('burst_amplitude_scaling', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('burst_attenuation_db', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('burst_freq', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('burst_range_resolution', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('burst_tukey_coef', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('burst_width', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('cathode_voltage', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('chirp_range_resolution', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('chirp_width', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('cic_dec', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('clutter_filter_len_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('clutter_filter_len_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('clutter_filter_window_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('clutter_filter_window_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('coherent_on_recv_before_sw_filter', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('coherent_on_recv_gate_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('coherent_on_recv_gate_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('cold_noise_burst_a', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('cold_noise_burst_b', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('cold_noise_chirp_a', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('cold_noise_chirp_b', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('collector_voltage', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('component_plate_temp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('counts_to_voltage_scale', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('digrcv_fir_gain', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('digrcv_nco_freq_burst', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('digrcv_nco_freq_chirp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('ems_3_override', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('ems_delay_a', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('ems_delay_b', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('fan_ki', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('fan_kp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('fan_mode', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('fan_sp_celcius', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('fault_flags', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('filament_voltage', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('five_vdc_0', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('five_vdc_1', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('four_port_circulator_temp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('group_a_enabled', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('heater_ki', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('heater_mode', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('heater_sp_celcius', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('helix_current', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('hot_noise_burst_a', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('hot_noise_burst_b', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('hot_noise_chirp_a', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('hot_noise_chirp_b', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('lna_1_on', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('lna_2_on', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('lna_temp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('min_auto_fan_speed', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('moments_pwr_threshold_db', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('n_gates_proc_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('n_gates_proc_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('n_group_pulses_total', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_delay_a', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_delay_b', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_diode_temp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_region_len_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_region_len_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_region_offset_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_region_offset_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_width_a', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('noise_width_b', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pid_parameters_temp_ctl', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pri_average', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pri_group_total', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_filepath_ch1', sa.String(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_filepath_ch2', sa.String(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_input_offset_index_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_input_offset_index_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_output_len_ratio_burst', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_output_len_ratio_chirp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_output_len_samps_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_output_len_samps_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_output_offset_index_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_output_offset_index_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_output_offset_ratio_burst', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('pulse_filter_output_offset_ratio_chirp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('range_offset_burst', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('range_offset_chirp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('rcb_mode_if_running', sa.String(), nullable=True))
op.add_column('prosensing_paf', sa.Column('rcb_temperature', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('record_raw_iq', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_a_1', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_a_2', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_a_3', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_a_4', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_b_1', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_b_2', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_b_3', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_b_4', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('scope_delay_zero', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('signal_region_len_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('signal_region_len_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('signal_region_offset_burst', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('signal_region_offset_chirp', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('sky_noise_burst_a', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('sky_noise_burst_b', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('sky_noise_chirp_a', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('sky_noise_chirp_b', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('sum_powers', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('timing_mode', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_internal_delay', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_latest_fault_time', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_powered_on', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_pulse_bracketing', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_pulse_width_a', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_pulse_width_b', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_remote_control_enabled', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_state', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_status_is_valid', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_temp', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_trig_delay_a', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('twta_trig_delay_b', sa.Integer(), nullable=True))
op.add_column('prosensing_paf', sa.Column('zero_gate_range_burst', sa.Float(), nullable=True))
op.add_column('prosensing_paf', sa.Column('zero_gate_range_chirp', sa.Float(), nullable=True))
def downgrade():
op.drop_column('prosensing_paf', '120_mhz_plo_lock')
op.drop_column('prosensing_paf', '1620_mhz_plo_lock')
op.drop_column('prosensing_paf', '16560_mhz_plo_lock')
op.drop_column('prosensing_paf', '360_mhz_plo_lock')
op.drop_column('prosensing_paf', 'ad_skip_count_ch1')
op.drop_column('prosensing_paf', 'ad_skip_count_ch2')
op.drop_column('prosensing_paf', 'antenna_feedhorn_temp')
op.drop_column('prosensing_paf', 'asp_internal_delay')
op.drop_column('prosensing_paf', 'burst_amplitude_scaling')
op.drop_column('prosensing_paf', 'burst_attenuation_db')
op.drop_column('prosensing_paf', 'burst_freq')
op.drop_column('prosensing_paf', 'burst_range_resolution')
op.drop_column('prosensing_paf', 'burst_tukey_coef')
op.drop_column('prosensing_paf', 'burst_width')
op.drop_column('prosensing_paf', 'cathode_voltage')
op.drop_column('prosensing_paf', 'chirp_range_resolution')
op.drop_column('prosensing_paf', 'chirp_width')
op.drop_column('prosensing_paf', 'cic_dec')
op.drop_column('prosensing_paf', 'clutter_filter_len_burst')
op.drop_column('prosensing_paf', 'clutter_filter_len_chirp')
op.drop_column('prosensing_paf', 'clutter_filter_window_burst')
op.drop_column('prosensing_paf', 'clutter_filter_window_chirp')
op.drop_column('prosensing_paf', 'coherent_on_recv_before_sw_filter')
op.drop_column('prosensing_paf', 'coherent_on_recv_gate_burst')
op.drop_column('prosensing_paf', 'coherent_on_recv_gate_chirp')
op.drop_column('prosensing_paf', 'cold_noise_burst_a')
op.drop_column('prosensing_paf', 'cold_noise_burst_b')
op.drop_column('prosensing_paf', 'cold_noise_chirp_a')
op.drop_column('prosensing_paf', 'cold_noise_chirp_b')
op.drop_column('prosensing_paf', 'collector_voltage')
op.drop_column('prosensing_paf', 'component_plate_temp')
op.drop_column('prosensing_paf', 'counts_to_voltage_scaleX')
op.drop_column('prosensing_paf', 'digrcv_fir_gain')
op.drop_column('prosensing_paf', 'digrcv_nco_freq_burst')
op.drop_column('prosensing_paf', 'digrcv_nco_freq_chirp')
op.drop_column('prosensing_paf', 'ems_3_override')
op.drop_column('prosensing_paf', 'ems_delay_a')
op.drop_column('prosensing_paf', 'ems_delay_b')
op.drop_column('prosensing_paf', 'fan_ki')
op.drop_column('prosensing_paf', 'fan_kp')
op.drop_column('prosensing_paf', 'fan_mode')
op.drop_column('prosensing_paf', 'fan_sp_celciusX')
op.drop_column('prosensing_paf', 'fault_flags')
op.drop_column('prosensing_paf', 'filament_voltage')
op.drop_column('prosensing_paf', 'five_vdc_0')
op.drop_column('prosensing_paf', 'five_vdc_1')
op.drop_column('prosensing_paf', 'four_port_circulator_temp')
op.drop_column('prosensing_paf', 'group_a_enabled')
op.drop_column('prosensing_paf', 'heater_ki')
op.drop_column('prosensing_paf', 'heater_mode')
op.drop_column('prosensing_paf', 'heater_sp_celciusX')
op.drop_column('prosensing_paf', 'helix_current')
op.drop_column('prosensing_paf', 'hot_noise_burst_a')
op.drop_column('prosensing_paf', 'hot_noise_burst_b')
op.drop_column('prosensing_paf', 'hot_noise_chirp_a')
op.drop_column('prosensing_paf', 'hot_noise_chirp_b')
op.drop_column('prosensing_paf', 'lna_1_on')
op.drop_column('prosensing_paf', 'lna_2_on')
op.drop_column('prosensing_paf', 'lna_temp')
op.drop_column('prosensing_paf', 'min_auto_fan_speed')
op.drop_column('prosensing_paf', 'moments_pwr_threshold_db')
op.drop_column('prosensing_paf', 'n_gates_proc_burst')
op.drop_column('prosensing_paf', 'n_gates_proc_chirp')
op.drop_column('prosensing_paf', 'n_group_pulses_total')
op.drop_column('prosensing_paf', 'noise_delay_a')
op.drop_column('prosensing_paf', 'noise_delay_b')
op.drop_column('prosensing_paf', 'noise_diode_temp')
op.drop_column('prosensing_paf', 'noise_region_len_burst')
op.drop_column('prosensing_paf', 'noise_region_len_chirp')
op.drop_column('prosensing_paf', 'noise_region_offset_burst')
op.drop_column('prosensing_paf', 'noise_region_offset_chirp')
op.drop_column('prosensing_paf', 'noise_width_a')
op.drop_column('prosensing_paf', 'noise_width_b')
op.drop_column('prosensing_paf', 'pid_parameters_temp_ctl')
op.drop_column('prosensing_paf', 'pri_average')
op.drop_column('prosensing_paf', 'pri_group_total')
op.drop_column('prosensing_paf', 'pulse_filter_filepath_ch1')
op.drop_column('prosensing_paf', 'pulse_filter_filepath_ch2')
op.drop_column('prosensing_paf', 'pulse_filter_input_offset_index_burst')
op.drop_column('prosensing_paf', 'pulse_filter_input_offset_index_chirp')
op.drop_column('prosensing_paf', 'pulse_filter_output_len_ratio_burst')
op.drop_column('prosensing_paf', 'pulse_filter_output_len_ratio_chirp')
op.drop_column('prosensing_paf', 'pulse_filter_output_len_samps_burst')
op.drop_column('prosensing_paf', 'pulse_filter_output_len_samps_chirp')
op.drop_column('prosensing_paf', 'pulse_filter_output_offset_index_burst')
op.drop_column('prosensing_paf', 'pulse_filter_output_offset_index_chirp')
op.drop_column('prosensing_paf', 'pulse_filter_output_offset_ratio_burst')
op.drop_column('prosensing_paf', 'pulse_filter_output_offset_ratio_chirp')
op.drop_column('prosensing_paf', 'range_offset_burst')
op.drop_column('prosensing_paf', 'range_offset_chirp')
op.drop_column('prosensing_paf', 'rcb_mode_if_running')
op.drop_column('prosensing_paf', 'rcb_temperature')
op.drop_column('prosensing_paf', 'record_raw_iq')
op.drop_column('prosensing_paf', 'scope_delay_a_1')
op.drop_column('prosensing_paf', 'scope_delay_a_2')
op.drop_column('prosensing_paf', 'scope_delay_a_3')
op.drop_column('prosensing_paf', 'scope_delay_a_4')
op.drop_column('prosensing_paf', 'scope_delay_b_1')
op.drop_column('prosensing_paf', 'scope_delay_b_2')
op.drop_column('prosensing_paf', 'scope_delay_b_3')
op.drop_column('prosensing_paf', 'scope_delay_b_4')
op.drop_column('prosensing_paf', 'scope_delay_zero')
op.drop_column('prosensing_paf', 'signal_region_len_burst')
op.drop_column('prosensing_paf', 'signal_region_len_chirp')
op.drop_column('prosensing_paf', 'signal_region_offset_burst')
op.drop_column('prosensing_paf', 'signal_region_offset_chirp')
op.drop_column('prosensing_paf', 'sky_noise_burst_a')
op.drop_column('prosensing_paf', 'sky_noise_burst_b')
op.drop_column('prosensing_paf', 'sky_noise_chirp_a')
op.drop_column('prosensing_paf', 'sky_noise_chirp_b')
op.drop_column('prosensing_paf', 'sum_powers')
op.drop_column('prosensing_paf', 'timing_mode')
op.drop_column('prosensing_paf', 'twta_internal_delay')
op.drop_column('prosensing_paf', 'twta_latest_fault_time')
op.drop_column('prosensing_paf', 'twta_powered_on')
op.drop_column('prosensing_paf', 'twta_pulse_bracketing')
op.drop_column('prosensing_paf', 'twta_pulse_width_a')
op.drop_column('prosensing_paf', 'twta_pulse_width_b')
op.drop_column('prosensing_paf', 'twta_remote_control_enabled')
op.drop_column('prosensing_paf', 'twta_state')
op.drop_column('prosensing_paf', 'twta_status_is_valid')
op.drop_column('prosensing_paf', 'twta_temp')
op.drop_column('prosensing_paf', 'twta_trig_delay_a')
op.drop_column('prosensing_paf', 'twta_trig_delay_b')
op.drop_column('prosensing_paf', 'zero_gate_range_burst')
op.drop_column('prosensing_paf', 'zero_gate_range_chirp')
| 73.676364
| 117
| 0.753369
| 2,977
| 20,261
| 4.734296
| 0.063487
| 0.233362
| 0.339719
| 0.187739
| 0.922449
| 0.911877
| 0.834894
| 0.7787
| 0.624095
| 0.617993
| 0
| 0.00553
| 0.08963
| 20,261
| 274
| 118
| 73.945255
| 0.75858
| 0.007798
| 0
| 0
| 0
| 0
| 0.413785
| 0.118238
| 0
| 0
| 0
| 0
| 0
| 1
| 0.007692
| false
| 0
| 0.007692
| 0
| 0.015385
| 0
| 0
| 0
| 0
| null | 1
| 1
| 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
| 0
| 0
|
0
| 8
|
e3230d46e1347dba9b7a7eae36779015312346c1
| 191
|
py
|
Python
|
avroconvert/sources/__init__.py
|
shrinivdeshmukh/avroconvert
|
5e3863a9a8374f127cbdd7b54fe22907de3a8e5d
|
[
"MIT"
] | 20
|
2021-06-18T14:40:17.000Z
|
2022-02-16T20:29:33.000Z
|
avroconvert/sources/__init__.py
|
shrinivdeshmukh/avroconvert
|
5e3863a9a8374f127cbdd7b54fe22907de3a8e5d
|
[
"MIT"
] | null | null | null |
avroconvert/sources/__init__.py
|
shrinivdeshmukh/avroconvert
|
5e3863a9a8374f127cbdd7b54fe22907de3a8e5d
|
[
"MIT"
] | 2
|
2021-06-27T06:24:44.000Z
|
2022-02-16T20:29:34.000Z
|
from avroconvert.sources.gcs.reader import GCS as gs_reader
from avroconvert.sources.s3.reader import S3 as s3_reader
from avroconvert.sources.filesystem.reader import FileSystem as fs_reader
| 63.666667
| 73
| 0.863874
| 30
| 191
| 5.4
| 0.366667
| 0.277778
| 0.407407
| 0.345679
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017241
| 0.089005
| 191
| 3
| 73
| 63.666667
| 0.913793
| 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
|
8b781d0a77d2a3239f5dc391306528fd73e570fe
| 1,977
|
py
|
Python
|
html_comps.py
|
StoicSun/Proto.Board
|
e7381869c5928677c8b54986ce6cd7d9db7f33ed
|
[
"MIT"
] | null | null | null |
html_comps.py
|
StoicSun/Proto.Board
|
e7381869c5928677c8b54986ce6cd7d9db7f33ed
|
[
"MIT"
] | null | null | null |
html_comps.py
|
StoicSun/Proto.Board
|
e7381869c5928677c8b54986ce6cd7d9db7f33ed
|
[
"MIT"
] | null | null | null |
input_table_html = """
<table class="mt-24">
<tbody>
<tr>
<th class="pr-2">Simi</th>
<th style="text-align: center;">
<input style="background-color: #5a5861; text-align: center; color: #0c0;" type="number" value="0" step="1" name="i-score">
</th>
</tr>
<tr>
<th class="pr-2">Suraj</th>
<th style="text-align: center;">
<input style="background-color: #5a5861; text-align: center; color: #0c0;" type="number" value="0" step="1" name="i-score">
</th>
</tr>
<tr>
<th class="pr-2">Abhi</th>
<th style="text-align: center;">
<input style="background-color: #5a5861; text-align: center; color: #0c0;" type="number" value="0" step="1" name="i-score">
</th>
</tr>
<tr>
<th class="pr-2">Piyush</th>
<th style="text-align: center;">
<input style="background-color: #5a5861; text-align: center; color: #0c0;" type="number" value="0" step="1" name="i-score">
</th>
</tr>
<tr>
<th class="pr-2">Ashish</th>
<th style="text-align: center;">
<input style="background-color: #5a5861; text-align: center; color: #0c0;" type="number" value="0" step="1" name="i-score">
</th>
</tr>
<tr>
<th class="pr-2">Nitu</th>
<th style="text-align: center;">
<input style="background-color: #5a5861; text-align: center; color: #0c0;" type="number" value="0" step="1" name="i-score">
</th>
</tr>
<tr>
<th class="pr-2">Parle</th>
<th style="text-align: center;">
<input style="background-color: #5a5861; text-align: center; color: #0c0;" type="number" value="0" step="1" name="i-score">
</th>
</tr>
</tbody>
</table>
"""
| 40.346939
| 139
| 0.482549
| 241
| 1,977
| 3.950207
| 0.145228
| 0.132353
| 0.220588
| 0.080882
| 0.919118
| 0.906513
| 0.906513
| 0.906513
| 0.906513
| 0.906513
| 0
| 0.053492
| 0.31917
| 1,977
| 48
| 140
| 41.1875
| 0.653789
| 0
| 0
| 0.729167
| 0
| 0.145833
| 0.986849
| 0.165908
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 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
|
8b9d9ff278959642ad2b5dbccc0f1b1068d5b6ef
| 8,546
|
py
|
Python
|
Pycompile/compile_deobfuscated.py
|
Alpha-Demon404/RE-14
|
b5b46a9f0eee218f2a642b615c77135c33c6f4ad
|
[
"MIT"
] | 39
|
2020-02-26T09:44:36.000Z
|
2022-03-23T00:18:25.000Z
|
Pycompile/compile_deobfuscated.py
|
B4BY-DG/reverse-enginnering
|
b5b46a9f0eee218f2a642b615c77135c33c6f4ad
|
[
"MIT"
] | 15
|
2020-05-14T10:07:26.000Z
|
2022-01-06T02:55:32.000Z
|
Pycompile/compile_deobfuscated.py
|
B4BY-DG/reverse-enginnering
|
b5b46a9f0eee218f2a642b615c77135c33c6f4ad
|
[
"MIT"
] | 41
|
2020-03-16T22:36:38.000Z
|
2022-03-17T14:47:19.000Z
|
# original author : https://github.com/LOoLzeC
# original tools : https://pastebin.com/z4TtgLiU
# changing the name of the maker will not make you a great person
import os
import sys
import time
import base64
import marshal
import zlib
R = '\033[1;31m'
G = '\033[1;32m'
Y = '\033[1;33m'
B = '\033[1;34m'
C = '\033[1;36m'
W = '\033[1;37m'
def slowprint(s):
for c in s + '\n':
sys.stdout.write(c)
sys.stdout.flush()
time.sleep(1.0 / 100)
logo = """
\033[1;32m ______ \033[1;33m _______ _ _
\033[1;32m(_____ \ \033[1;33m (_______) (_) |
\033[1;32m _____) ) _ \033[1;33m _ ___ ____ ____ _| | _____
\033[1;32m| ____/ | | | \033[1;33m | | / _ \| \| _ \| | || ___ |
\033[1;32m| | | |_| | \033[1;33m | |____| |_| | | | | |_| | | || ____|
\033[1;32m|_| \__ | \033[1;33m \______)___/|_|_|_| __/|_|\_)_____)
\033[1;32m (____/ \033[1;33m |_|
\033[1;33mCreated By HTR-TECH \033[1;37m( \033[1;33mTahmid Rayat\033[1;37m )
"""
banner = """
\033[1;31m[\033[1;37m01\033[1;31m]\033[1;33m Encrypt Marshal
\033[1;31m[\033[1;37m02\033[1;31m]\033[1;33m Encrypt Base64
\033[1;31m[\033[1;37m03\033[1;31m]\033[1;33m Encrypt Marshal\033[1;37m,\033[1;33mBase32
\033[1;31m[\033[1;37m04\033[1;31m]\033[1;33m Encrypt Zlib\033[1;37m,\033[1;33mBase64
\033[1;31m[\033[1;37m05\033[1;31m]\033[1;33m Encrypt Marshal\033[1;37m,\033[1;33mZlib\033[1;37m,\033[1;33mBase64
\033[1;31m[\033[1;37m06\033[1;31m]\033[1;33m Encrypt Marshal\033[1;37m,\033[1;33mZlib\033[1;37m,\033[1;33mBase32
\033[1;31m[\033[1;37m07\033[1;31m]\033[1;33m Encrypt Marshal\033[1;37m,\033[1;33mZlib\033[1;37m,\033[1;33mBase16
\033[1;31m[\033[1;37m00\033[1;31m]\033[1;33m Exit
"""
os.system("clear")
print logo
slowprint (banner)
mainmenu = raw_input(G + " Select an option" + C + " > " + Y)
if mainmenu == "1" or mainmenu == "01":
print ("")
slowprint(G + ' Launching Encryption Tool...')
time.sleep(2)
print ("")
file = raw_input(G + " Name of the File to Encrypt" + C + " > " + Y)
print ("")
c = raw_input(G + " Output File Name" + C + " > " + Y)
print ("")
slowprint (G + " Encrypting...")
print ("")
fileopen = open(file).read()
a = compile(fileopen, 'dg', 'exec')
m = marshal.dumps(a)
s = repr(m)
b = '# Obfuscated by Py Compile\n# Created by HTR-TECH (https://github.com/htr-tech)\n# Instagram : @tahmid.rayat\n\nimport marshal\nexec(marshal.loads(' + s + '))'
d = open(c, 'w')
d.write(b)
d.close()
time.sleep(3)
slowprint(G + " Encryption Completed...")
time.sleep(3)
print ("")
print G + ' Output File Name : ' + Y, c
print ("")
print (W)
elif mainmenu == "2" or mainmenu == "02":
print ("")
slowprint(G + ' Launching Encryption Tool...')
time.sleep(2)
print ("")
file = raw_input(G + " Name of the File to Encrypt" + C + " > " + Y)
print ("")
c = raw_input(G + " Output File Name" + C + " > " + Y)
print ("")
slowprint (G + " Encrypting...")
print ("")
fileopen = open(file).read()
a = base64.b64encode(fileopen)
b = "# Obfuscated by Py Compile\n# Created by HTR-TECH (https://github.com/htr-tech)\n# Instagram : @tahmid.rayat\n\nimport base64\nexec(base64.b64decode('" + a + "'))"
d = open(c, 'w')
d.write(b)
d.close()
time.sleep(3)
slowprint(G + " Encryption Completed...")
time.sleep(3)
print ("")
print G + ' Output File Name : ' + Y, c
print ("")
print (W)
elif mainmenu == "3" or mainmenu == "03":
print ("")
slowprint(G + ' Launching Encryption Tool...')
time.sleep(2)
print ("")
file = raw_input(G + " Name of the File to Encrypt" + C + " > " + Y)
print ("")
c = raw_input(G + " Output File Name" + C + " > " + Y)
print ("")
slowprint (G + " Encrypting...")
print ("")
fileopen = open(file).read()
sa = compile(fileopen, 'dg', 'exec')
sb = marshal.dumps(sa)
sc = base64.b32encode(sb)
b = '# Obfuscated by Py Compile\n# Created by HTR-TECH (https://github.com/htr-tech)\n# Instagram : @tahmid.rayat\n\nimport marshal,base64\nexec(marshal.loads(base64.b32decode("' + str(sc) + '")))'
d = open(c, 'w')
d.write(b)
d.close()
time.sleep(3)
slowprint(G + " Encryption Completed...")
time.sleep(3)
print ("")
print G + ' Output File Name : ' + Y, c
print ("")
print (W)
elif mainmenu == "4" or mainmenu == "04":
print ("")
slowprint(G + ' Launching Encryption Tool...')
time.sleep(2)
print ("")
file = raw_input(G + " Name of the File to Encrypt" + C + " > " + Y)
print ("")
c = raw_input(G + " Output File Name" + C + " > " + Y)
print ("")
slowprint (G + " Encrypting...")
print ("")
fileopen = open(file).read()
sa = zlib.compress(fileopen)
sb = base64.b64encode(sa)
b = '# Obfuscated by Py Compile\n# Created by HTR-TECH (https://github.com/htr-tech)\n# Instagram : @tahmid.rayat\n\nimport zlib,base64\nexec(zlib.decompress(base64.b64decode("' + sb + '")))'
d = open(c, 'w')
d.write(b)
d.close()
time.sleep(3)
slowprint(G + " Encryption Completed...")
time.sleep(3)
print ("")
print G + ' Output File Name : ' + Y, c
print ("")
print (W)
elif mainmenu == "5" or mainmenu == "05":
print ("")
slowprint(G + ' Launching Encryption Tool...')
time.sleep(2)
print ("")
file = raw_input(G + " Name of the File to Encrypt" + C + " > " + Y)
print ("")
c = raw_input(G + " Output File Name" + C + " > " + Y)
print ("")
slowprint (G + " Encrypting...")
print ("")
fileopen = open(file).read()
sa = compile(fileopen, 'dg', 'exec')
sb = marshal.dumps(sa)
sc = zlib.compress(sb)
sd = base64.b64encode(sc)
b = '# Obfuscated by Py Compile\n# Created by HTR-TECH (https://github.com/htr-tech)\n# Instagram : @tahmid.rayat\n\nimport marshal,zlib,base64\nexec(marshal.loads(zlib.decompress(base64.b64decode("' + str(sd) + '"))))'
d = open(c, 'w')
d.write(b)
d.close()
time.sleep(3)
slowprint(G + " Encryption Completed...")
time.sleep(3)
print ("")
print G + ' Output File Name : ' + Y, c
print ("")
print (W)
elif mainmenu == "6" or mainmenu == "06":
print ("")
slowprint(G + ' Launching Encryption Tool...')
time.sleep(2)
print ("")
file = raw_input(G + " Name of the File to Encrypt" + C + " > " + Y)
print ("")
c = raw_input(G + " Output File Name" + C + " > " + Y)
print ("")
slowprint (G + " Encrypting...")
print ("")
fileopen = open(file).read()
sa = compile(fileopen, 'dg', 'exec')
sb = marshal.dumps(sa)
sc = zlib.compress(sb)
sd = base64.b32encode(sc)
b = '# Obfuscated by Py Compile\n# Created by HTR-TECH (https://github.com/htr-tech)\n# Instagram : @tahmid.rayat\n\nimport marshal,zlib,base64\nexec(marshal.loads(zlib.decompress(base64.b32decode("' + str(sd) + '"))))'
d = open(c, 'w')
d.write(b)
d.close()
time.sleep(3)
slowprint(G + " Encryption Completed...")
time.sleep(3)
print ("")
print G + ' Output File Name : ' + Y, c
print ("")
print (W)
elif mainmenu == "7" or mainmenu == "07":
print ("")
slowprint(G + ' Launching Encryption Tool...')
time.sleep(2)
print ("")
file = raw_input(G + " Name of the File to Encrypt" + C + " > " + Y)
print ("")
c = raw_input(G + " Output File Name" + C + " > " + Y)
print ("")
slowprint (G + " Encrypting...")
print ("")
fileopen = open(file).read()
sa = compile(fileopen, 'dg', 'exec')
sb = marshal.dumps(sa)
sc = zlib.compress(sb)
sd = base64.b16encode(sc)
b = '# Obfuscated by Py Compile\n# Created by HTR-TECH (https://github.com/htr-tech)\n# Instagram : @tahmid.rayat\n\nimport marshal,zlib,base64\nexec(marshal.loads(zlib.decompress(base64.b16decode("' + str(sd) + '"))))'
d = open(c, 'w')
d.write(b)
d.close()
time.sleep(3)
slowprint(G + " Encryption Completed...")
time.sleep(3)
print ("")
print G + ' Output File Name : ' + Y, c
print ("")
print (W)
elif mainmenu == "0" or mainmenu == "00":
print ("")
print ("")
slowprint(Y + " Thanks for using this tool")
time.sleep(1)
print ("")
print (W)
sys.exit
else:
print (W + "")
print (C + "[" + R + " !" + C + "]" + Y + " Invalid input " + C + "[" + R + "!" + C + "]")
print (W)
| 34.459677
| 223
| 0.556284
| 1,191
| 8,546
| 3.894207
| 0.123426
| 0.062096
| 0.025658
| 0.034498
| 0.781803
| 0.770806
| 0.767788
| 0.758732
| 0.758732
| 0.758732
| 0
| 0.088923
| 0.244676
| 8,546
| 247
| 224
| 34.59919
| 0.629589
| 0.018254
| 0
| 0.702128
| 0
| 0.089362
| 0.442695
| 0.136076
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.055319
| null | null | 0.404255
| 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
| 1
|
0
| 8
|
8ba1019d815ed0f808d263421641f1bb86f2bf80
| 101
|
py
|
Python
|
test/run/t130.py
|
timmartin/skulpt
|
2e3a3fbbaccc12baa29094a717ceec491a8a6750
|
[
"MIT"
] | 2,671
|
2015-01-03T08:23:25.000Z
|
2022-03-31T06:15:48.000Z
|
test/run/t130.py
|
csev/skulpt
|
9aa25b7dbf29f23ee8d3140d01a6f4353d12e66f
|
[
"MIT"
] | 972
|
2015-01-05T08:11:00.000Z
|
2022-03-29T13:47:15.000Z
|
test/run/t130.py
|
csev/skulpt
|
9aa25b7dbf29f23ee8d3140d01a6f4353d12e66f
|
[
"MIT"
] | 845
|
2015-01-03T19:53:36.000Z
|
2022-03-29T18:34:22.000Z
|
a = range(30)
print a[-10::5]
print a[-10::-6]
a = tuple(range(30))
print a[-10::5]
print a[-10::-6]
| 14.428571
| 20
| 0.564356
| 23
| 101
| 2.478261
| 0.347826
| 0.421053
| 0.561404
| 0.45614
| 0.877193
| 0.877193
| 0.877193
| 0.877193
| 0.877193
| 0.877193
| 0
| 0.183908
| 0.138614
| 101
| 6
| 21
| 16.833333
| 0.471264
| 0
| 0
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.666667
| 1
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 14
|
8bc3728f2027dd690324a1d72a373e870bbf19c6
| 169
|
py
|
Python
|
src/puzzle/pdql/pdql.py
|
PhilHarnish/forge
|
663f19d759b94d84935c14915922070635a4af65
|
[
"MIT"
] | 2
|
2020-08-18T18:43:09.000Z
|
2020-08-18T20:05:59.000Z
|
src/puzzle/pdql/pdql.py
|
PhilHarnish/forge
|
663f19d759b94d84935c14915922070635a4af65
|
[
"MIT"
] | null | null | null |
src/puzzle/pdql/pdql.py
|
PhilHarnish/forge
|
663f19d759b94d84935c14915922070635a4af65
|
[
"MIT"
] | null | null | null |
from puzzle.pdql import q, _query
def input(*args, **kwargs):
return q.Q().input(*args, **kwargs)
def query(*args, **kwargs):
return q.Q().query(*args, **kwargs)
| 18.777778
| 37
| 0.64497
| 26
| 169
| 4.153846
| 0.423077
| 0.37037
| 0.277778
| 0.314815
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142012
| 169
| 8
| 38
| 21.125
| 0.744828
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| true
| 0
| 0.2
| 0.4
| 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
| 1
| 1
| 0
| 0
| 1
| 0
| 0
|
0
| 8
|
478cc523af886aea972da1cb538534b53cd1b8a9
| 943
|
py
|
Python
|
tools/proteonics/frag_singleton_new/test.py
|
globusgenomics/galaxy
|
7caf74d9700057587b3e3434c64e82c5b16540f1
|
[
"CC-BY-3.0"
] | 1
|
2021-02-05T13:19:58.000Z
|
2021-02-05T13:19:58.000Z
|
tools/proteonics/frag_singleton_new/test.py
|
globusgenomics/galaxy
|
7caf74d9700057587b3e3434c64e82c5b16540f1
|
[
"CC-BY-3.0"
] | null | null | null |
tools/proteonics/frag_singleton_new/test.py
|
globusgenomics/galaxy
|
7caf74d9700057587b3e3434c64e82c5b16540f1
|
[
"CC-BY-3.0"
] | null | null | null |
#!/usr/bin/env python
from PeptideFragmentSingleton import PeptideFragment
f = PeptideFragment( 1 ) # mass type = mono
# charge modifications
f.analyze('ACKRM', 3, "16.0@M 57.1@3")
print f.sequence(), ": ", f.composition();
print "---- pI: ---- "
print " ", f.pI()
print "---- b-ions: ---- "
l = f.b_ions();
for i, m in enumerate(l):
print " ", m
print "---- y-ions: ---- "
l = f.y_ions();
for i, m in enumerate(l):
print " ", m
print "---- mass: ---- "
l = f.peptide_mass();
for i, m in enumerate(l):
print " ", m
print
f.analyze('KC')
print f.sequence(), ": ", f.composition();
print "---- pI: ---- "
print " ", f.pI()
print "---- b-ions: ---- "
l = f.b_ions();
for i, m in enumerate(l):
print " ", m
print "---- y-ions: ---- "
l = f.y_ions();
for i, m in enumerate(l):
print " ", m
print "---- mass: ---- "
l = f.peptide_mass();
for i, m in enumerate(l):
print " ", m
| 18.134615
| 52
| 0.516437
| 138
| 943
| 3.485507
| 0.26087
| 0.024948
| 0.06237
| 0.087318
| 0.700624
| 0.700624
| 0.700624
| 0.700624
| 0.700624
| 0.690229
| 0
| 0.01257
| 0.240721
| 943
| 51
| 53
| 18.490196
| 0.659218
| 0.082715
| 0
| 0.857143
| 0
| 0
| 0.199536
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.028571
| null | null | 0.542857
| 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
| 1
|
0
| 8
|
47f3bfcea415989187302d44fe80ea676d65c006
| 3,535
|
py
|
Python
|
v1/item/permissions.py
|
hussu010/Backend-1
|
f5d9a057d6ff947f6574b45f825d7987e2ac2730
|
[
"MIT"
] | 1
|
2021-01-28T15:16:39.000Z
|
2021-01-28T15:16:39.000Z
|
v1/item/permissions.py
|
hussu010/Backend-1
|
f5d9a057d6ff947f6574b45f825d7987e2ac2730
|
[
"MIT"
] | 77
|
2021-02-01T04:53:10.000Z
|
2021-12-07T15:45:43.000Z
|
v1/item/permissions.py
|
hussu010/Backend-1
|
f5d9a057d6ff947f6574b45f825d7987e2ac2730
|
[
"MIT"
] | 3
|
2021-01-28T15:05:56.000Z
|
2021-02-22T17:12:08.000Z
|
from rest_framework.permissions import BasePermission
from v1.shop.models import UserBranch, Shop
from v1.category.models import Category, Menu
from .models import CustomizationGroup, Item
class MenuCategoryPermission(BasePermission):
def has_permission(self, request, view):
user_has_perm = False
item_in_branch = False
if request.data.get('branch') and request.data.get('category') and request.data.get('menu'):
if UserBranch.objects.filter(user=request.user, branch=request.data['branch']).exists():
permission = UserBranch.objects.get(user=request.user, branch=request.data['branch']).permission
if permission == 1 or permission == 2 or permission == 3:
user_has_perm = True
elif Shop.objects.filter(shopbranch=request.data['branch'], owner=request.user).exists():
user_has_perm = True
if Category.objects.filter(uuid=request.data['category'], branch=request.data['branch']).exists() and \
Menu.objects.filter(uuid=request.data['menu'], branch=request.data['branch']).exists():
item_in_branch = True
return (request.user and request.user.is_authenticated) and user_has_perm and item_in_branch
class CustomizationItemPermission(BasePermission):
def has_permission(self, request, view):
user_has_permission = False
item_in_branch = False
if request.data.get('branch') and request.data.get('customization_group') and request.data.get('item'):
if UserBranch.objects.filter(user=request.user, branch=request.data['branch']).exists():
permission = UserBranch.objects.get(user=request.user, branch=request.data['branch']).permission
if permission == 1 or permission == 2 or permission == 3:
user_has_permission = True
elif Shop.objects.filter(shopbranch=request.data['branch'], owner=request.user).exists():
user_has_permission = True
if Item.objects.filter(uuid=request.data['item'], branch=request.data['branch']).exists() and \
CustomizationGroup.objects.filter(uuid=request.data['customization_group'], branch=request.data['branch']).exists():
item_in_branch = True
return (request.user and request.user.is_authenticated) and user_has_permission and item_in_branch
class ModifierGroupPermission(BasePermission):
def has_permission(self, request, view):
user_has_perm = False
item_in_branch = False
if request.data.get('branch') and request.data.get('item') and request.data.get('customization_group'):
if UserBranch.objects.filter(user=request.user, branch=request.data['branch']).exists():
permission = UserBranch.objects.get(user=request.user, branch=request.data['branch']).permission
if permission == 1 or permission == 2 or permission == 3:
user_has_perm = True
elif Shop.objects.filter(shopbranch=request.data['branch'], owner=request.user).exists():
user_has_perm = True
if Item.objects.filter(uuid=request.data['item'], branch=request.data['branch']).exists() and \
CustomizationGroup.objects.filter(uuid=request.data['customization_group'], branch=request.data['branch']).exists():
item_in_branch = True
return (request.user and request.user.is_authenticated) and user_has_perm and item_in_branch
| 54.384615
| 131
| 0.673833
| 422
| 3,535
| 5.518957
| 0.118483
| 0.141692
| 0.109489
| 0.118506
| 0.858308
| 0.812795
| 0.776299
| 0.776299
| 0.776299
| 0.753972
| 0
| 0.003934
| 0.209052
| 3,535
| 64
| 132
| 55.234375
| 0.829041
| 0
| 0
| 0.714286
| 0
| 0
| 0.063366
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.061224
| false
| 0
| 0.081633
| 0
| 0.265306
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
9a0f75a3905b44de1581d4f7ba9338ef95cdb95a
| 17,305
|
py
|
Python
|
tests/core/test_app.py
|
malviguys/frontendcli
|
c4c1875892b46a194013ea1d41ca9b815f42ee20
|
[
"MIT"
] | null | null | null |
tests/core/test_app.py
|
malviguys/frontendcli
|
c4c1875892b46a194013ea1d41ca9b815f42ee20
|
[
"MIT"
] | 3
|
2021-11-26T17:38:31.000Z
|
2021-12-16T07:28:05.000Z
|
tests/core/test_app.py
|
malviguys/frontendcli
|
c4c1875892b46a194013ea1d41ca9b815f42ee20
|
[
"MIT"
] | null | null | null |
import json
from unittest.mock import patch, Mock, mock_open
import pytest
import responses
from core.app import App, ADMIN_PAGE
from core.menu.handler import Handler, API_SERVER_ADDRESS
@pytest.fixture
def mock_fetch_lessons():
Handler.fetch_lessons = Mock()
Handler.fetch_lessons.return_value = json.loads('{"lessons": [{"id":1, "lesson_name":"Guitar With Mario", '
'"teacher":"Mario Alviano", "instrument":"Instrument.GUITAR", '
'"students":[{"name":"Claudio Lucisano"}, {"name":"Giada Gabriele"}], '
'"date_time":"2021-16-12 14:30:00", "duration":"00:02:00", "cost":"100.00€"},'
'{"id":2, "lesson_name":"Fun with the Triangle", "teacher":"Dr. Tri Angle", '
'"instrument":"Instrument.TRIANGLE", "students":[{"name":"Paola Guarasci"}, '
'{"name":"Kerstin Greifensteiner"}], "date_time":"2021-17-02 12:30:00", '
'"duration":"00:03:30", "cost":"120.00€"}]}')
return Handler
@pytest.fixture
def mock_create_lesson():
Handler.create_lesson = Mock()
Handler.create_lesson.return_value = True
return Handler
@pytest.fixture
def mock_modify_lesson():
Handler.modify_lesson = Mock()
Handler.modify_lesson.return_value = True
return Handler
@pytest.fixture
def mock_cancel_lesson():
Handler.cancel_lesson = Mock()
Handler.cancel_lesson.return_value = True
return Handler
@pytest.fixture
def mock_book_lesson():
Handler.book_lesson = Mock()
Handler.book_lesson.return_value = True
return Handler
@pytest.fixture
def mock_cancel_booking():
Handler.cancel_booking = Mock()
Handler.cancel_booking.return_value = True
return Handler
def test_create_app():
App()
def test_run_app():
App().run()
@patch('builtins.print')
def test_app_asks_for_login(mocked_print):
App().run()
line = 'Please, select as you want to login'
mocked_print.assert_any_call('-*-' * len(line))
mocked_print.assert_any_call(line)
@responses.activate
@patch('builtins.input', side_effect=['1', 'student', 'mypassword', '0'])
@patch('builtins.print')
def test_student_login(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('1-\tLog in as a Student')
mocked_print.assert_any_call('2-\tLog in as a Teacher')
mocked_print.assert_any_call('3-\tLog in as an Admin')
mocked_print.assert_any_call('0-\tExit')
mocked_print.assert_any_call('Logging as a Student')
mocked_print.assert_any_call('Successfully logged in!\n')
mocked_print.assert_any_call('1-\tBook a lesson')
mocked_print.assert_any_call('2-\tCancel a booking')
mocked_print.assert_any_call('0-\tExit')
mocked_print.assert_any_call('Goodbye fella')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'myfancypassword', '0'])
@patch('builtins.print')
def test_teacher_login(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('1-\tLog in as a Student')
mocked_print.assert_any_call('2-\tLog in as a Teacher')
mocked_print.assert_any_call('3-\tLog in as an Admin')
mocked_print.assert_any_call('0-\tExit')
mocked_print.assert_any_call('Logging as a Teacher')
mocked_print.assert_any_call('Successfully logged in!\n')
mocked_print.assert_any_call('1-\tCreate a lesson')
mocked_print.assert_any_call('2-\tModify a lesson')
mocked_print.assert_any_call('3-\tCancel a lesson')
mocked_print.assert_any_call('0-\tExit')
mocked_print.assert_any_call('Goodbye fella')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['3', 'admin', 'admin', '0'])
@patch('builtins.print')
def test_admin_login(mocked_print, mocked_input):
# TODO: duplicate
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('1-\tLog in as a Student')
mocked_print.assert_any_call('2-\tLog in as a Teacher')
mocked_print.assert_any_call('3-\tLog in as an Admin')
mocked_print.assert_any_call('0-\tExit')
mocked_print.assert_any_call('Logging as an Admin')
mocked_print.assert_any_call('Successfully logged in!\n')
mocked_print.assert_any_call('1-\tGet admin page link')
mocked_print.assert_any_call('0-\tExit')
mocked_print.assert_any_call('Goodbye fella')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'tchr', '1',
'My Lesson', 'Guitar', 'Myself Thatsit', '08-03-2022 10:00', '120', '80.00'])
@patch('builtins.print')
def test_create_lesson(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'create_lesson') as mocked_create_lesson:
mocked_create_lesson.return_value = True
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Lesson "My Lesson" with Myself Thatsit for GUITAR on 2022-03-08 10:00:00 for '
'2.0 hours and 80.00€ created successfully!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'tchr', '1',
'My Lesson', 'Guitar', 'Myself Thatsit', '08-03-2022 10:00', '120', '80.00', '0'])
@patch('builtins.print')
def test_create_lesson_fails_from_backend(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'create_lesson') as mocked_create_lesson:
mocked_create_lesson.return_value = False
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('The lesson could not be created!\n')
mocked_print.assert_any_call('Goodbye fella')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'tchr', '1',
'My Lesson', 'Bass', 'Myself Thatsit', '08-03-2022 10:00', '120', '80.00'])
@patch('builtins.print')
def test_create_lesson_fails_wrong_instrument(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Sorry, the given instrument was not correct!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'tchr', '2',
'My Lesson', 'Guitar', 'Myself Thatsit', '08-03-2022 10:00', '120', '80.00'])
@patch('builtins.print')
def test_modify_lesson(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'modify_lesson') as mocked_modify_lesson:
mocked_modify_lesson.return_value = True
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Lesson "My Lesson" with Myself Thatsit for GUITAR successfully modified!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'tchr', '2',
'My Lesson', 'Guitar', 'Myself Thatsit', '08-03-2022 10:00', '120', '80.00'])
@patch('builtins.print')
def test_modify_lesson_fails_from_backend(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'modify_lesson') as mocked_modify_lesson:
mocked_modify_lesson.return_value = False
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('The lesson could not be modified!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'tchr', '2',
'My Lesson', 'Lute', 'Myself Thatsit', '08-03-2022 10:00', '120', '80.00'])
@patch('builtins.print')
def test_modify_lesson_fails_wrong_instrument(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Sorry, the given instrument was not correct!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'tchr', '3', 'My Lesson'])
@patch('builtins.print')
def test_cancel_lesson(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'cancel_lesson') as mocked_cancel_lesson:
mocked_cancel_lesson.return_value = True
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Lesson "My Lesson" successfully cancelled!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['2', 'teacher', 'tchr', '3', 'My Lesson'])
@patch('builtins.print')
def test_cancel_lesson_fails(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'cancel_lesson') as mocked_cancel_lesson:
mocked_cancel_lesson.return_value = False
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Could not cancel lesson!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['1', 'student', 'stdnt', '1', 'The Lesson'])
@patch('builtins.print')
def test_book_lesson(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'book_lesson') as mocked_book_lesson:
mocked_book_lesson.return_value = True
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Successfully booked for lesson "The Lesson"!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['1', 'student', 'stdnt', '1', 'The Lesson'])
@patch('builtins.print')
def test_book_lesson_fails(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'book_lesson') as mocked_book_lesson:
mocked_book_lesson.return_value = False
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Could not make booking for this lesson!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['1', 'student', 'stdnt', '2', 'The Lesson'])
@patch('builtins.print')
def test_cancel_booking(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'cancel_booking') as mocked_cancel_booking:
mocked_cancel_booking.return_value = True
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Successfully cancelled booking for "The Lesson"!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['1', 'student', 'stdnt', '2', 'The Lesson'])
@patch('builtins.print')
def test_cancel_booking_fails(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch.object(Handler, 'cancel_booking') as mocked_cancel_booking:
mocked_cancel_booking.return_value = False
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Could not cancel your booking!\n')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['3', 'admin', 'admin', '1'])
@patch('builtins.print')
def test_get_admin_page(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"key": "You are in"}',
'status': 200,
'content_type': 'application/json',
})
with patch.object(Handler, 'fetch_lessons'):
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call(f'Admin page: {ADMIN_PAGE}')
mocked_input.assert_called()
@responses.activate
@patch('builtins.input', side_effect=['3', 'admin', 'admin'])
@patch('builtins.print')
def test_invalid_credentials(mocked_print, mocked_input):
responses.add(**{
'method': responses.POST,
'url': API_SERVER_ADDRESS + '/auth/login/',
'body': '{"UNAUTHENTICATED": "You are NOT in"}',
'status': 401,
'content_type': 'application/json',
})
with patch('builtins.open', mock_open()):
App().run()
mocked_print.assert_any_call('Invalid credential, please try again.\n')
mocked_input.assert_called()
| 39.509132
| 130
| 0.607223
| 2,041
| 17,305
| 4.920627
| 0.086232
| 0.071194
| 0.079558
| 0.093598
| 0.871254
| 0.847655
| 0.833715
| 0.829931
| 0.818381
| 0.813104
| 0
| 0.022268
| 0.242242
| 17,305
| 437
| 131
| 39.599542
| 0.743384
| 0.000867
| 0
| 0.744063
| 0
| 0.007916
| 0.278286
| 0.013478
| 0
| 0
| 0
| 0.002288
| 0.168865
| 1
| 0.068602
| false
| 0.005277
| 0.015831
| 0
| 0.100264
| 0.218997
| 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
|
9a64883d5f653f82effe48e67a5d5177bf02a132
| 66
|
py
|
Python
|
code/groundtruth/__init__.py
|
philipversteeg/validation-yeast
|
a977a2b038618530b75577495ade6b7a9e728da4
|
[
"BSD-2-Clause"
] | 1
|
2018-02-15T10:50:56.000Z
|
2018-02-15T10:50:56.000Z
|
code/groundtruth/__init__.py
|
philipversteeg/validation-yeast
|
a977a2b038618530b75577495ade6b7a9e728da4
|
[
"BSD-2-Clause"
] | null | null | null |
code/groundtruth/__init__.py
|
philipversteeg/validation-yeast
|
a977a2b038618530b75577495ade6b7a9e728da4
|
[
"BSD-2-Clause"
] | null | null | null |
from intervention_score import gt as intervention_score
import sgd
| 33
| 55
| 0.893939
| 10
| 66
| 5.7
| 0.7
| 0.596491
| 0.807018
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106061
| 66
| 2
| 56
| 33
| 0.966102
| 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
|
9a68c3749f5d345494ccce8bfef6a9db98015c37
| 148
|
py
|
Python
|
src/app/dependencies.py
|
adrianblair-codesmart/krygate-game-token-api
|
6b9e477a135c707766e5c88e9a8db9595fececdf
|
[
"MIT"
] | 2
|
2021-02-19T14:35:33.000Z
|
2021-02-20T13:40:46.000Z
|
src/app/dependencies.py
|
adrianblair-codesmart/krygate-game-token-api
|
6b9e477a135c707766e5c88e9a8db9595fececdf
|
[
"MIT"
] | null | null | null |
src/app/dependencies.py
|
adrianblair-codesmart/krygate-game-token-api
|
6b9e477a135c707766e5c88e9a8db9595fececdf
|
[
"MIT"
] | null | null | null |
from functools import lru_cache
from .config import settings
@lru_cache()
def get_settings() -> settings.Settings:
return settings.Settings()
| 18.5
| 40
| 0.77027
| 19
| 148
| 5.842105
| 0.526316
| 0.432432
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.141892
| 148
| 7
| 41
| 21.142857
| 0.874016
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| true
| 0
| 0.4
| 0.2
| 0.8
| 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
| 0
| 1
| 1
| 1
| 0
|
0
| 7
|
d053814f9760e3efdde6691600862af17dc7b2f9
| 325
|
py
|
Python
|
quantumflow/xdiff/__init__.py
|
weichseltree/quantumflow
|
4d7b7239d9243b0bd2421ba7c8d16af4e7e6876c
|
[
"MIT"
] | 1
|
2020-02-13T13:53:26.000Z
|
2020-02-13T13:53:26.000Z
|
quantumflow/xdiff/__init__.py
|
weichseltree/quantumflow
|
4d7b7239d9243b0bd2421ba7c8d16af4e7e6876c
|
[
"MIT"
] | null | null | null |
quantumflow/xdiff/__init__.py
|
weichseltree/quantumflow
|
4d7b7239d9243b0bd2421ba7c8d16af4e7e6876c
|
[
"MIT"
] | 1
|
2021-07-29T12:56:55.000Z
|
2021-07-29T12:56:55.000Z
|
from .transformer import positional_encoding, get_xdiff, scaled_dot_product_attention, XdiffMultiHeadAttention, XdiffEncoderLayer, XdiffTransformer, TFWhileXdiffTransformer, XdiffCrossEncoderLayer, XdiffPerciever
from .dft import XdiffTransformer_KineticEnergyDensityFunctional, XdiffPerciever_KineticEnergyDensityFunctional
| 108.333333
| 212
| 0.913846
| 24
| 325
| 12.083333
| 0.791667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052308
| 325
| 2
| 213
| 162.5
| 0.941558
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
d0aeee550bbcbf02127399d07e16f1f435e09a89
| 179
|
py
|
Python
|
dddm/plotting/__init__.py
|
JoranAngevaare/dddm
|
3461e37984bac4d850beafecc9d1881b84fb226c
|
[
"MIT"
] | null | null | null |
dddm/plotting/__init__.py
|
JoranAngevaare/dddm
|
3461e37984bac4d850beafecc9d1881b84fb226c
|
[
"MIT"
] | 85
|
2021-09-20T12:08:53.000Z
|
2022-03-30T12:48:06.000Z
|
dddm/plotting/__init__.py
|
JoranAngevaare/dddm
|
3461e37984bac4d850beafecc9d1881b84fb226c
|
[
"MIT"
] | null | null | null |
from . import confidence_figures
from .confidence_figures import *
from . import plot_basics
from .plot_basics import *
from . import seaborn_utils
from .seaborn_utils import *
| 19.888889
| 33
| 0.804469
| 24
| 179
| 5.75
| 0.333333
| 0.217391
| 0.231884
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| 0.145251
| 179
| 8
| 34
| 22.375
| 0.901961
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0
| 7
|
d0e5d8eaa205641e1369dc7604f1749a80b6961b
| 14,598
|
py
|
Python
|
data_creator/common.py
|
neduchal/io_classification_experiment
|
f22a0eac84c23dbbcb9eed35c00c37a1e1a1342b
|
[
"MIT"
] | null | null | null |
data_creator/common.py
|
neduchal/io_classification_experiment
|
f22a0eac84c23dbbcb9eed35c00c37a1e1a1342b
|
[
"MIT"
] | null | null | null |
data_creator/common.py
|
neduchal/io_classification_experiment
|
f22a0eac84c23dbbcb9eed35c00c37a1e1a1342b
|
[
"MIT"
] | null | null | null |
import os
import cv2
import description as d
from sklearn import preprocessing
import h5py
import centrist
import gbp
import numpy as np
import wave
import whgo
def get_all_files(directory):
#for root, dirs, files in os.walk(directory):
# filenames = [os.path.join(root, name) for name in files]
filenames = []
for root, dirs, files in os.walk(directory):
for name in files:
filenames.append(os.path.join(root, name))
return filenames
def process_whgo(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, hs=8):
data_x = []
data_y = []
data_y_io = []
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
img = cv2.imread(filename, 0)
im = img.copy()
h1 = whgo.whgo(im[0:im.shape[0]//2, 0:im.shape[1]//2], hs)
h2 = whgo.whgo(im[0:im.shape[0]//2, im.shape[1]//2:im.shape[1]], hs)
h3 = whgo.whgo(im[im.shape[0]//2:im.shape[0], 0:im.shape[1]//2], hs)
h4 = whgo.whgo(im[im.shape[0]//2:im.shape[1], im.shape[1]//2:im.shape[1]], hs)
h = np.concatenate((h1,h2,h3,h4))
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_wave(filenames, classes, classes_io, classes_nums, fname_base_len, val=False):
data_x = []
data_y = []
data_y_io = []
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
img = cv2.imread(filename, 0)
im = img.copy()
h = wave.wave(im)
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_gbp(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, hist_settings=(3,3,8)):
data_x = []
data_y = []
data_y_io = []
hs = hist_settings
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
img = cv2.imread(filename, 0)
im = img.copy()
im = gbp.gbp(im)
h = d.spatial_histogram(im, hs[0], hs[1], hs[2])
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_gbp_multiscale(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, hist_settings=8):
data_x = []
data_y = []
data_y_io = []
hs = hist_settings
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
img = cv2.imread(filename, 0)
im = img.copy()
im2 = cv2.resize(im, dsize=(im.shape[1]//2, im.shape[0]//2))
im3 = cv2.resize(im, dsize=(im.shape[1]//4, im.shape[0]//4))
im = gbp.gbp(im)
im2 = gbp.gbp( im2)
im3 = gbp.gbp( im3)
h1 = d.spatial_histogram_bw(im3, 1, 1 , hs)
h2 = d.spatial_histogram_bw(im2, 2, 2, hs)
h3 = d.spatial_histogram_bw(im, 4, 4, hs)
h = np.concatenate((h1, h2, h3))
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_centrist_io(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, hist_settings=(3,3,8)):
cl = centrist.load()
data_x = []
data_y = []
data_y_io = []
hs = hist_settings
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
img = cv2.imread(filename)
im = img.copy()
im[:,:,0] = centrist.centrist_im(cl, im[:,:,0])
im[:,:,1] = centrist.centrist_im(cl, im[:,:,1])
im[:,:,2] = centrist.centrist_im(cl, im[:,:,2])
h = d.spatial_histogram(im, hs[0], hs[1], hs[2])
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_centrist_io_multiscale(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, hist_settings=4):
cl = centrist.load()
data_x = []
data_y = []
data_y_io = []
hs = hist_settings
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
img = cv2.imread(filename)
im = img.copy()
im[:,:,0] = centrist.centrist_im(cl, im[:,:,0])
im[:,:,1] = centrist.centrist_im(cl, im[:,:,1])
im[:,:,2] = centrist.centrist_im(cl, im[:,:,2])
h1 = d.spatial_histogram(im, 1, 1 , hs)
h2 = d.spatial_histogram(im, 2, 2, hs)
h3 = d.spatial_histogram(im, 4, 4, hs)
h = np.concatenate((h1, h2, h3))
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_centrist_io_multiscale_bw(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, hist_settings=4):
cl = centrist.load()
data_x = []
data_y = []
data_y_io = []
hs = hist_settings
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
img = cv2.imread(filename, 0)
im = img.copy()
im2 = cv2.resize(im, dsize=(im.shape[1]//2, im.shape[0]//2))
im3 = cv2.resize(im, dsize=(im.shape[1]//4, im.shape[0]//4))
im = centrist.centrist_im(cl, im)
im2 = centrist.centrist_im(cl, im2)
im3 = centrist.centrist_im(cl, im3)
h1 = d.spatial_histogram_bw(im3, 1, 1 , hs)
h2 = d.spatial_histogram_bw(im2, 2, 2, hs)
h3 = d.spatial_histogram_bw(im, 4, 4, hs)
h = np.concatenate((h1, h2, h3))
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_hist_io(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, preproc="rgb", hist_settings=(3,3,8)):
data_x = []
data_y = []
data_y_io = []
hs = hist_settings
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
im = cv2.imread(filename)
if preproc == "rgb":
h = d.spatial_histogram(im, hs[0], hs[1], hs[2])
elif preproc == "hsv":
h = d.spatial_histogram_hsv(im, hs[0], hs[1], hs[2])
elif preproc == "luv":
h = d.spatial_histogram_luv(im, hs[0], hs[1], hs[2])
elif preproc == "ohta":
h = d.spatial_histogram_ohta(im, hs[0], hs[1], hs[2])
else:
print("Unknown preprocessing method")
exit(1)
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_hist_io_multiscale(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, preproc="rgb", hist_settings=(3,3,8)):
data_x = []
data_y = []
data_y_io = []
hs = hist_settings
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
im = cv2.imread(filename)
im2 = cv2.resize(im, dsize=(im.shape[1]//2, im.shape[0]//2))
im3 = cv2.resize(im, dsize=(im.shape[1]//4, im.shape[0]//4))
if preproc == "rgb":
h1 = d.spatial_histogram(im3, 1, 1, hs)
h2 = d.spatial_histogram(im2, 2, 2, hs)
h3 = d.spatial_histogram(im, 4, 4, hs)
elif preproc == "hsv":
h1 = d.spatial_histogram_hsv(im3, 1, 1, hs)
h2 = d.spatial_histogram_hsv(im2, 2, 2, hs)
h3 = d.spatial_histogram_hsv(im, 4, 4, hs)
elif preproc == "luv":
h1 = d.spatial_histogram_luv(im3, 1, 1, hs)
h2 = d.spatial_histogram_luv(im2, 2, 2, hs)
h3 = d.spatial_histogram_luv(im, 4, 4, hs)
elif preproc == "ohta":
h1 = d.spatial_histogram_ohta(im3, 1, 1, hs)
h2 = d.spatial_histogram_ohta(im2, 2, 2, hs)
h3 = d.spatial_histogram_ohta(im, 4, 4, hs)
else:
print("Unknown preprocessing method")
exit(1)
h = np.concatenate((h1, h2, h3))
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_nbhs_io(filenames, classes, classes_io, classes_nums, fname_base_len, val=False, hist_settings=(3,3,8)):
data_x = []
data_y = []
data_y_io = []
hs = hist_settings
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
im = cv2.imread(filename)
h = d.spatial_nbhs(im, hs[0], hs[1])
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def process_nbhs_io_multiscale(filenames, classes, classes_io, classes_nums, fname_base_len, val=False):
data_x = []
data_y = []
data_y_io = []
for i, filename in enumerate(filenames):
printProgressBar(i+1, len(filenames))
im = cv2.imread(filename)
im2 = cv2.resize(im, dsize=(im.shape[1]//2, im.shape[0]//2))
im3 = cv2.resize(im, dsize=(im.shape[1]//4, im.shape[0]//4))
h1 = d.spatial_nbhs(im3, 1, 1)
h2 = d.spatial_nbhs(im2, 2, 2)
h3 = d.spatial_nbhs(im, 4, 4)
h = np.concatenate((h1, h2, h3))
index = classes.index(filename[fname_base_len:-13])
data_x.append(h)
if val:
inout = int(classes_io[int(classes[i].split(" ")[1])])
data_y.append(int(classes[i].split(" ")[1]))
data_y_io.append(inout)
else:
data_y.append(int(classes_nums[index]))
data_y_io.append(int(classes_io[index]))
data_x_scaled = preprocessing.scale(data_x)
return data_x_scaled, data_y, data_y_io
def save_to_h5(filename, data_x, data_y, data_y_io):
with h5py.File(filename, "w") as f:
f["data_x"] = data_x
f["data_y"] = data_y
f["data_y_io"] = data_y_io
f.flush()
# Print iterations progress
def printProgressBar (iteration, total, prefix = '', suffix = '', decimals = 1, length = 100, fill = '█', printEnd = "\r"):
"""
Call in a loop to create terminal progress bar
@params:
iteration - Required : current iteration (Int)
total - Required : total iterations (Int)
prefix - Optional : prefix string (Str)
suffix - Optional : suffix string (Str)
decimals - Optional : positive number of decimals in percent complete (Int)
length - Optional : character length of bar (Int)
fill - Optional : bar fill character (Str)
printEnd - Optional : end character (e.g. "\r", "\r\n") (Str)
"""
percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
filledLength = int(length * iteration // total)
bar = fill * filledLength + '-' * (length - filledLength)
print('\r%s |%s| %s%% %s' % (prefix, bar, percent, suffix), end = printEnd)
# Print New Line on Complete
if iteration == total:
print()
| 39.668478
| 142
| 0.58782
| 2,101
| 14,598
| 3.883865
| 0.070443
| 0.057598
| 0.040319
| 0.029412
| 0.843015
| 0.820466
| 0.81201
| 0.793505
| 0.753064
| 0.739951
| 0
| 0.030348
| 0.266406
| 14,598
| 368
| 143
| 39.668478
| 0.731534
| 0.049801
| 0
| 0.779503
| 0
| 0
| 0.011476
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.043478
| false
| 0
| 0.031056
| 0
| 0.111801
| 0.049689
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| null | 0
| 0
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| 0
| 0
| 0
|
0
| 7
|
eff9871a391e819af6d624f7b278cf41391d7d78
| 12,841
|
py
|
Python
|
Projects/MacroFin/Python/odeex.py
|
jepayne/NYU
|
539aaf7fb165a81463bb23be1a0b79aaffb5316f
|
[
"MIT"
] | 3
|
2017-05-13T12:06:09.000Z
|
2020-04-07T02:27:02.000Z
|
Projects/MacroFin/Python/odeex.py
|
jepayne/NYU
|
539aaf7fb165a81463bb23be1a0b79aaffb5316f
|
[
"MIT"
] | null | null | null |
Projects/MacroFin/Python/odeex.py
|
jepayne/NYU
|
539aaf7fb165a81463bb23be1a0b79aaffb5316f
|
[
"MIT"
] | 3
|
2017-01-21T05:10:46.000Z
|
2020-04-07T02:27:02.000Z
|
"""
Example implementation of odes in python
"""
import numpy as np
from scipy.integrate import odeint
from matplotlib import pyplot as plt
# --------------------
# odelay (from the pycse package)
# --------------------
def odelay(func, y0, xspan, events, TOLERANCE = 1e-6, fsolve_args=None, **kwargs):
'''Solve an ODE with events.
func is callable, with signature func(Y, x)
y0 are the initial conditions xspan is what you want to integrate
over
events is a list of callable functions with signature event(Y, x).
These functions return zero when an event has happened.
TOLERANCE is what is used to identify when an event has occurred.
[value, isterminal, direction] = event(Y, x)
value is the value of the event function. When value = 0, an event
is triggered
isterminal = True if the integration is to terminate at a zero of
this event function, otherwise, False.
direction = 0 if all zeros are to be located (the default), +1
if only zeros where the event function is increasing, and -1 if
only zeros where the event function is decreasing.
fsolve_args is a dictionary of options for fsolve
kwargs are any additional options you want to send to odeint.
Returns [x, y, te, ye, ie]
x is the independent variable array
y is the solution
te is an array of independent variable values where events occurred
ye is an array of the solution at the points where events occurred
ie is an array of indices indicating which event function occurred.
'''
if 'full_output' in kwargs:
raise Exception('full_output not supported as an option')
if fsolve_args is None:
fsolve_args = {}
x0 = xspan[0] # initial point
X = [x0]
sol = [y0]
TE, YE, IE = [], [], [] # to store where events occur
# initial value of events
e = np.zeros((len(events), len(xspan)))
for i,event in enumerate(events):
e[i,0], isterminal, direction = event(y0, x0)
# now we step through the integration
for i, x1 in enumerate(xspan[0:-1]):
x2 = xspan[i + 1]
f1 = sol[i]
f2 = odeint(func, f1, [x1, x2])#, **kwargs)
X += [x2]
sol += [f2[-1,:]]
# check event functions. At each step we compute the event
# functions, and check if they have changed sign since the
# last step. If they changed sign, it implies a zero was
# crossed.
for j, event in enumerate(events):
e[j, i + 1], isterminal, direction = event(sol[i + 1], X[i + 1])
if ((e[j, i + 1] * e[j, i] < 0) # sign change in
# event means zero
# crossing
or np.abs(e[j, i + 1]) < TOLERANCE # this point is
# practically 0
or np.abs(e[j, i]) < TOLERANCE):
xLt = X[-1] # Last point
fLt = sol[-1]
eLt = e[j, i+1]
# we need to find a value of x that makes the event zero
def objective(x):
# evaluate ode from xLT to x
txspan = [xLt, x]
tempsol = odeint(func, fLt, txspan)#, **kwargs)
sol = tempsol[-1, :]
val, isterminal, direction = event(sol, x)
return val
from scipy.optimize import fsolve
xZ, = fsolve(objective, xLt, **fsolve_args) # this should be the
# value of x that makes
# the event zero
# now evaluate solution at this point, so we can
# record the function values here.
txspan = [xLt, xZ]
tempsol = odeint(func, fLt, txspan, **kwargs)
fZ = tempsol[-1,:]
vZ, isterminal, direction = event(fZ, xZ)
COLLECTEVENT = False
if direction == 0:
COLLECTEVENT = True
elif (e[j, i + 1] > e[j, i] ) and direction == 1:
COLLECTEVENT = True
elif (e[j, i + 1] < e[j, i] ) and direction == -1:
COLLECTEVENT = True
if COLLECTEVENT:
TE.append(xZ)
YE.append(fZ)
IE.append(j)
if isterminal:
X[-1] = xZ
sol[-1] = fZ
return (np.array(X),
np.array(sol),
np.array(TE),
np.array(YE),
np.array(IE))
# at the end, return what we have
return (np.array(X),
np.array(sol),
np.array(TE),
np.array(YE),
np.array(IE))
# ----------------------------------------
# Example usage : Univariate
# ----------------------------------------
# def myode(f, x):
# return 3*x**2 + 12*x -4
# def event1(f, x):
# 'an event is when f = 0 and event is decreasing'
# isterminal = True
# direction = -1
# return f, isterminal, direction
# def event2(f, x):
# 'an event is when f = 0 and increasing'
# isterminal = False
# direction = 1
# return f, isterminal, direction
# f0 = -120
# xspan = np.linspace(-8, 4)
# events=[event1, event2]
# func = myode
# y0 = f0
# X, F, TE, YE, IE = odelay(myode, f0, xspan, events)
#import matplotlib.pyplot as plt
#plt.plot(X, F, '.-')
# plot the event locations.use a different color for each event
#colors = 'rg'
#for x,y,i in zip(TE, YE, IE):
# plt.plot([x], [y], 'o', color=colors[i])
#plt.savefig('images/event-ode-2.png')
#plt.show()
#print(TE, YE, IE)
# ----------------------------------------
# Example usage: Multivariate
# ----------------------------------------
# System of differential equations:
# z1' = z3
# z2' = z4
# z3' = -g - b*z3
# z4' = -bz4
def myode(z, t):
# PROJ: ODE for projectile motion with linear air resistance
# z = [z0, z1, z2, z3]
g = 9.81 # Specify approximate graviatational constant
b = 0.28 # Representative value
return [z[2], z[3], -g-b*z[2], -b*z[3]]
def linevent(z, t):
# LINEVENT: Contains the event we are looking for
# In this event, z(1) = 0 (hitting the ground)
lookfor = z[0] # Sets this to 0
stop = 1 # Stop when event is located
direction = -1 # specify downward direction
return lookfor, stop, direction
f0 = [0.18, 0, 5, 10]
xspan = np.linspace(0, 10)
events = [linevent]
func = myode
y0 = f0
X, F, TE, YE, IE = odelay(myode, f0, xspan, events)
# --------------------
# odelaym (adapated from the pycse package to account for multivariate case)
# --------------------
# I think there are mistakes in the above code that only show up in the
# multivariate case
def odelaym(func, y0, xspan, events, TOLERANCE = 1e-6, fsolve_args=None, **kwargs):
'''Solve an ODE with events.
func is callable, with signature func(Y, x)
y0 are the initial conditions xspan is what you want to integrate
over
events is a list of callable functions with signature event(Y, x).
These functions return zero when an event has happened.
TOLERANCE is what is used to identify when an event has occurred.
[value, isterminal, direction] = event(Y, x)
value is the value of the event function. When value = 0, an event
is triggered
isterminal = True if the integration is to terminate at a zero of
this event function, otherwise, False.
direction = 0 if all zeros are to be located (the default), +1
if only zeros where the event function is increasing, and -1 if
only zeros where the event function is decreasing.
fsolve_args is a dictionary of options for fsolve
kwargs are any additional options you want to send to odeint.
Returns [x, y, te, ye, ie]
x is the independent variable array
y is the solution
te is an array of independent variable values where events occurred
ye is an array of the solution at the points where events occurred
ie is an array of indices indicating which event function occurred.
'''
if 'full_output' in kwargs:
raise Exception('full_output not supported as an option')
if fsolve_args is None:
fsolve_args = {}
x0 = xspan[0] # initial point
X = [x0]
sol = [y0]
TE, YE, IE = [], [], [] # to store where events occur
# initial value of events
e = np.zeros((len(events), len(xspan)))
for i,event in enumerate(events):
e[i,0], isterminal, direction = event(y0, x0)
# now we step through the integration
for i, x1 in enumerate(xspan[0:-1]):
x2 = xspan[i + 1]
f1 = sol[i]
f2 = odeint(func, f1, [x1, x2])#, **kwargs)
X += [x2]
sol += [f2[-1, :]]
# check event functions. At each step we compute the event
# functions, and check if they have changed sign since the
# last step. If they changed sign, it implies a zero was
# crossed.
for j, event in enumerate(events):
e[j, i + 1], isterminal, direction = event(sol[i + 1], X[i + 1])
if ((e[j, i + 1] * e[j, i] < 0) # sign change in
# event means zero
# crossing
or np.abs(e[j, i + 1]) < TOLERANCE # this point is
# practically 0
or np.abs(e[j, i]) < TOLERANCE):
xLt = X[i+1] # Last point
fLt = sol[i+1]
eLt = e[j, i+1]
# we need to find a value of x that makes the event zero
def objective(x):
# evaluate ode from xLT to x
txspan = [xLt, x]
tempsol = odeint(func, fLt, txspan)#, **kwargs)
sol = tempsol[-1, :]
val, isterminal, direction = event(sol, x)
return val
from scipy.optimize import fsolve
xZ, = fsolve(objective, xLt, **fsolve_args) # this should be the
# value of x that makes
# the event zero
# now evaluate solution at this point, so we can
# record the function values here.
txspan = [xLt, xZ]
tempsol = odeint(func, fLt, txspan, **kwargs)
fZ = tempsol[-1,:]
vZ, isterminal, direction = event(fZ, xZ)
COLLECTEVENT = False
if direction == 0:
COLLECTEVENT = True
elif (e[j, i + 1] > e[j, i] ) and direction == 1:
COLLECTEVENT = True
elif (e[j, i + 1] < e[j, i] ) and direction == -1:
COLLECTEVENT = True
if COLLECTEVENT:
TE.append(xZ)
YE.append(fZ)
IE.append(j)
if isterminal:
X[i+1] = xZ
sol[i+1] = fZ
return (np.array(X),
np.array(sol),
np.array(TE),
np.array(YE),
np.array(IE))
# at the end, return what we have
return (np.array(X),
np.array(sol),
np.array(TE),
np.array(YE),
np.array(IE))
# ----------------------------------------
# Example usage: Multivariate
# ----------------------------------------
# System of differential equations:
# z1' = z3
# z2' = z4
# z3' = -g - b*z3
# z4' = -bz4
def myode(z, t):
# PROJ: ODE for projectile motion with linear air resistance
# z = [z0, z1, z2, z3]
g = 9.81 # Specify approximate graviatational constant
b = 0.28 # Representative value
return [z[2], z[3], -g-b*z[2], -b*z[3]]
def linevent(z, t):
# LINEVENT: Contains the event we are looking for
# In this event, z(1) = 0 (hitting the ground)
lookfor = z[0] # Sets this to 0
stop = True # Stop when event is located
direction = -1 # specify downward direction
return lookfor, stop, direction
f0 = [0.18, 0, 5, 10]
xspan = np.linspace(0, 10)
events = [linevent]
func = myode
y0 = f0
Xm, Fm, TEm, YEm, IEm = odelaym(myode, f0, xspan, events)
| 31.628079
| 83
| 0.50954
| 1,644
| 12,841
| 3.971411
| 0.157543
| 0.006739
| 0.00919
| 0.007352
| 0.897075
| 0.892173
| 0.881146
| 0.881146
| 0.881146
| 0.875019
| 0
| 0.024826
| 0.372635
| 12,841
| 405
| 84
| 31.706173
| 0.785626
| 0.444046
| 0
| 0.89172
| 0
| 0
| 0.014486
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.050955
| false
| 0
| 0.031847
| 0
| 0.146497
| 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
|
4bf08c7a019db2bc81603b5cdcd332ebfbc107a8
| 396
|
py
|
Python
|
tests/unit/handlers/conftest.py
|
atsgen/tf-vcenter-manager
|
2cfa07f038b86b3087842c34abb96b15da0b36fb
|
[
"Apache-2.0"
] | 1
|
2022-03-13T06:31:40.000Z
|
2022-03-13T06:31:40.000Z
|
tests/unit/handlers/conftest.py
|
atsgen/tf-vcenter-manager
|
2cfa07f038b86b3087842c34abb96b15da0b36fb
|
[
"Apache-2.0"
] | null | null | null |
tests/unit/handlers/conftest.py
|
atsgen/tf-vcenter-manager
|
2cfa07f038b86b3087842c34abb96b15da0b36fb
|
[
"Apache-2.0"
] | 1
|
2020-08-25T12:46:12.000Z
|
2020-08-25T12:46:12.000Z
|
import pytest
from mock import Mock
@pytest.fixture()
def vm_service():
return Mock()
@pytest.fixture()
def vn_service():
return Mock()
@pytest.fixture()
def vmi_service():
return Mock()
@pytest.fixture()
def vrouter_port_service():
return Mock()
@pytest.fixture()
def vlan_id_service():
return Mock()
@pytest.fixture()
def vrouter_api_client():
return Mock()
| 12
| 27
| 0.681818
| 51
| 396
| 5.117647
| 0.333333
| 0.229885
| 0.390805
| 0.45977
| 0.685824
| 0.685824
| 0.306513
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 396
| 32
| 28
| 12.375
| 0.805556
| 0
| 0
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3
| true
| 0
| 0.1
| 0.3
| 0.7
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
32620eb3e6b65dbff3612b05ccb1d49e9de6db59
| 88,694
|
py
|
Python
|
symmetry/__init__.py
|
tdaff/automation
|
89d32af3aafe0e027c13d42cd0c43ecb12820b0c
|
[
"BSD-3-Clause"
] | 1
|
2021-12-13T13:33:44.000Z
|
2021-12-13T13:33:44.000Z
|
symmetry/__init__.py
|
tdaff/automation
|
89d32af3aafe0e027c13d42cd0c43ecb12820b0c
|
[
"BSD-3-Clause"
] | null | null | null |
symmetry/__init__.py
|
tdaff/automation
|
89d32af3aafe0e027c13d42cd0c43ecb12820b0c
|
[
"BSD-3-Clause"
] | null | null | null |
"""
symmetry
Tables of symmetry operations and conversions.
"""
symmetry_operations = {
'-x+1,-y+1/2,z': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.5, 0.0),
'-x+1,-y+1/2,z+1/2': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.5, 0.5),
'-x+1,-z+1/2,-y': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, -1.0, 0.0, 1.0, 0.5, 0.0),
'-x+1,-z+1/2,y': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 1.0, 0.5, 0.0),
'-x+1,-z,-y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.5),
'-x+1,-z,y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5),
'-x+1,y+1/2,-z': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 1.0, 0.5, 0.0),
'-x+1,y+1/2,-z+1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 1.0, 0.5, 0.5),
'-x+1,y+1/2,-z+5/4': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 1.0, 0.5, 1.25),
'-x+1,y+1/2,z+1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.5, 0.5),
'-x+1,z+1/2,-y': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, -1.0, 0.0, 1.0, 0.5, 0.0),
'-x+1,z+1/2,y': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.5, 0.0),
'-x+1,z,-y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.5),
'-x+1,z,y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5),
'-x+1/2,-y+1,z+1/2': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 1.0, 0.5),
'-x+1/2,-y+1/2,-z': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.5, 0.0),
'-x+1/2,-y+1/2,-z+1/2': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.5, 0.5),
'-x+1/2,-y+1/2,z': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.5, 0.0),
'-x+1/2,-y+1/2,z+1/2': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.5, 0.5),
'-x+1/2,-y,-z+1/2': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.0, 0.5),
'-x+1/2,-y,z': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.0, 0.0),
'-x+1/2,-y,z+1/2': (-1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.0, 0.5),
'-x+1/2,-z+1/2,-y': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, -1.0, 0.0, 0.5, 0.5, 0.0),
'-x+1/2,-z+1/2,-y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, -1.0, 0.0, 0.5, 0.5, 0.5),
'-x+1/2,-z+1/2,y': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.5, 0.5, 0.0),
'-x+1/2,-z+1/2,y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.5, 0.5, 0.5),
'-x+1/2,-z,-y': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, -1.0, 0.0, 0.5, 0.0, 0.0),
'-x+1/2,-z,-y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, -1.0, 0.0, 0.5, 0.0, 0.5),
'-x+1/2,-z,y': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.5, 0.0, 0.0),
'-x+1/2,-z,y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.5, 0.0, 0.5),
'-x+1/2,y+1,-z+1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 1.0, 0.5),
'-x+1/2,y+1,z+1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 1.0, 0.5),
'-x+1/2,y+1/2,-z': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.5, 0.0),
'-x+1/2,y+1/2,-z+1': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.5, 1.0),
'-x+1/2,y+1/2,-z+1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.5, 0.5),
'-x+1/2,y+1/2,-z+1/4': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.5, 0.25),
'-x+1/2,y+1/2,-z+3/4': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.5, 0.75),
'-x+1/2,y+1/2,z': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.5, 0.0),
'-x+1/2,y+1/2,z+1': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.5, 1.0),
'-x+1/2,y+1/2,z+1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.5, 0.5),
'-x+1/2,y+1/2,z-1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.5, -0.5),
'-x+1/2,y+1/4,z-1/4': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.25, -0.25),
'-x+1/2,y,-z': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.0, 0.0),
'-x+1/2,y,-z+1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.0, 0.5),
'-x+1/2,y,-z+3/4': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.5, 0.0, 0.75),
'-x+1/2,y,z': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.0, 0.0),
'-x+1/2,y,z+1/2': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, 0.0, 0.5),
'-x+1/2,y-1/4,z+1/4': (-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.5, -0.25, 0.25),
'-x+1/2,z+1/2,-y': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, -1.0, 0.0, 0.5, 0.5, 0.0),
'-x+1/2,z+1/2,-y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, -1.0, 0.0, 0.5, 0.5, 0.5),
'-x+1/2,z+1/2,y': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5, 0.5, 0.0),
'-x+1/2,z+1/2,y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5, 0.5, 0.5),
'-x+1/2,z+1/4,y+3/4': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5, 0.25, 0.75),
'-x+1/2,z+1/4,y+5/4': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5, 0.25, 1.25),
'-x+1/2,z+3/4,y+1/4': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5, 0.75, 0.25),
'-x+1/2,z+3/4,y+3/4': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5, 0.75, 0.75),
'-x+1/2,z,-y': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, -1.0, 0.0, 0.5, 0.0, 0.0),
'-x+1/2,z,-y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, -1.0, 0.0, 0.5, 0.0, 0.5),
'-x+1/2,z,y': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5, 0.0, 0.0),
'-x+1/2,z,y+1/2': (-1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5, 0.0, 0.5),
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}
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0
| 12
|
326e445e6e675277d7dbd2a00a633bd3f55f5544
| 128,884
|
py
|
Python
|
Bin/prodtecnica.py
|
mfneirae/GrupLAC-Complete
|
f4ccefe2553b90015d28df0e8d7730b4bad37d84
|
[
"MIT"
] | null | null | null |
Bin/prodtecnica.py
|
mfneirae/GrupLAC-Complete
|
f4ccefe2553b90015d28df0e8d7730b4bad37d84
|
[
"MIT"
] | null | null | null |
Bin/prodtecnica.py
|
mfneirae/GrupLAC-Complete
|
f4ccefe2553b90015d28df0e8d7730b4bad37d84
|
[
"MIT"
] | 1
|
2021-06-10T09:21:18.000Z
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2021-06-10T09:21:18.000Z
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#
#
# #############################################################################
# Copyright (c) 2018 Universidad Nacional de Colombia All Rights Reserved.
#
# This work was made as a development to improve data collection
# for self-assessment and accreditation processes in the Vicedeanship
# of academic affairs in the Engineering Faculty of the Universidad
# Nacional de Colombia and is licensed under a Creative Commons
# Attribution-NonCommercial - ShareAlike 4.0 International License
# and MIT Licence.
#
# by Manuel Embus.
#
# For more information write me to jai@mfneirae.com
# Or visit my webpage at https://mfneirae.com/
# #############################################################################
#
#
def clc(str):
import re
str = re.sub(r'[^A-Za-z0-9:=_?ÁÀÉÈÍÌÓÒÚÙéèáà,éñèíìńúùóò .\-/+]',r'',re.sub(' +',' ',str.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r","")))
if str == ",":
str = "-"
return str;
def cartasextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contcartas
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscacartas = containers[a].td
#print(buscacartas)
try:
if buscacartas.text == "Cartas, mapas o similares":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_cartas = cont.text
index1 = info_cartas.find("- ") + 2
index2 = info_cartas.find(':')
tipo = clc(info_cartas[index1:index2])
#Tipo Artículo
if tipo.strip() == "Aerofotograma":
tipo = "46"
elif tipo.strip() == "Carta":
tipo = "47"
elif tipo.strip() == "Fotograma":
tipo = "48"
elif tipo.strip() == "Mapa":
tipo = "49"
elif tipo.strip() == "Otra":
tipo = "50"
else:
logging.critical('Añadir: ' + tipo + ' a cartas')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_cartas.find('\n', index1, len(info_cartas))
nombreart = clc(info_cartas[index1:index2])
index1 = index2 + 2
index2 = info_cartas.find(',', index1, len(info_cartas))
lugar = clc(info_cartas[index1:index2])
index1 = index2 + 2
index2 = info_cartas.find(',', index1, len(info_cartas))
anopub = clc(info_cartas[index1:index2])
index1 = info_cartas.find('Institución financiadora:') + 25
index2 = info_cartas.find(', Tema:', index1, len(info_cartas))
institucion = clc(info_cartas[index1:index2])
index1 = info_cartas.find('Tema:') + 5
index2 = info_cartas.find('Autores:', index1, len(info_cartas))
tema = clc(info_cartas[index1:index2])
index1 = info_cartas.find('Autores:', index2, len(info_cartas)) + 9
index2 = info_cartas.find('/br', index1, len(info_cartas))
autores = clc(info_cartas[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + tema + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ tema +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene cartas Asociados')
contcartas = [COD_PRODUCTO]
def consultoriasextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contconsultorias
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaconsultorias = containers[a].td
#print(buscaconsultorias)
try:
if buscaconsultorias.text == "Consultorías científico tecnológicas e Informes técnicos":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_consultorias = cont.text
index1 = info_consultorias.find("- ") + 2
index2 = info_consultorias.find(':')
tipo = clc(info_consultorias[index1:index2])
#Tipo Artículo
if tipo.strip() == "Servicios de proyectos de IDI":
tipo = "52"
elif tipo.strip() == "Comercialización de tecnología":
tipo = "53"
elif tipo.strip() == "Análisis de competitividad":
tipo = "54"
elif tipo.strip() == "Informe técnico":
tipo = "55"
elif tipo.strip() == "Otra":
tipo = "56"
elif tipo.strip() == "Acciones de transferencia tecnológica":
tipo = "57"
elif tipo.strip() == "Desarrollo de productos":
tipo = "58"
elif tipo.strip() == "Implementación de sistemas de análisis":
tipo = "59"
elif tipo.strip() == "Consultoría en artes,arquitectura y diseño":
tipo = "60"
elif tipo.strip() == "Servicios de Proyectos de I+D+I":
tipo = "76"
else:
logging.critical('Añadir: ' + tipo + ' a consultorias')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_consultorias.find('\n', index1, len(info_consultorias))
nombreart = clc(info_consultorias[index1:index2])
index1 = index2 + 2
index2 = info_consultorias.find(',', index1, len(info_consultorias))
lugar = clc(info_consultorias[index1:index2])
index1 = index2 + 2
index2 = info_consultorias.find(',', index1, len(info_consultorias))
anopub = clc(info_consultorias[index1:index2])
index1 = info_consultorias.find('Idioma:') + 7
index2 = info_consultorias.find(', Disponibilidad:', index1, len(info_consultorias))
idioma = clc(info_consultorias[index1:index2])
index1 = info_consultorias.find(', Disponibilidad:') + 17
index2 = info_consultorias.find(',\n', index1, len(info_consultorias))
disponibilidad = clc(info_consultorias[index1:index2])
index1 = info_consultorias.find('Número del contrato:') + 20
index2 = info_consultorias.find('Institución que se benefició del servicio:', index1, len(info_consultorias))
contrato = clc(info_consultorias[index1:index2])
index1 = info_consultorias.find('Institución que se benefició del servicio:') + 42
index2 = info_consultorias.find('Autores:', index1, len(info_consultorias))
institucion = clc(info_consultorias[index1:index2])
index1 = info_consultorias.find('Autores:', index2, len(info_consultorias)) + 9
index2 = info_consultorias.find('/br', index1, len(info_consultorias))
autores = clc(info_consultorias[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "'" + idioma + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ idioma +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "'" + contrato + "'," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ contrato +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene consultorias Asociados')
contconsultorias = [COD_PRODUCTO]
def disenosiextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contdisenosi
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscadisenosi = containers[a].td
#print(buscadisenosi)
try:
if buscadisenosi.text == "Diseños industriales":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_disenosi = cont.text
index1 = info_disenosi.find("- ") + 2
index2 = info_disenosi.find(':')
tipo = clc(info_disenosi[index1:index2])
#Tipo Artículo
if tipo.strip() == "Diseño Industrial":
tipo = "40"
elif tipo.strip() == "Diseńo Industrial":
tipo = "40"
elif tipo.strip() == "Industrial":
tipo = "40"
else:
logging.critical('Añadir: ' + tipo + ' a disenosi')
index1 = index2 + 2
index2 = info_disenosi.find('\n ', index1, len(info_disenosi))
nombreart = clc(info_disenosi[index1:index2])
index1 = index2 + 17
index2 = info_disenosi.find(',', index1, len(info_disenosi))
lugar = clc(info_disenosi[index1:index2])
index1 = index2 + 2
index2 = info_disenosi.find(',', index1, len(info_disenosi))
anopub = clc(info_disenosi[index1:index2])
index1 = info_disenosi.find('Disponibilidad:') + 15
index2 = info_disenosi.find(',', index1, len(info_disenosi))
disponibilidad = clc(info_disenosi[index1:index2])
index1 = info_disenosi.find('Institución financiadora:') + 25
index2 = info_disenosi.find('Autores:', index1, len(info_disenosi))
institucion = clc(info_disenosi[index1:index2])
index1 = info_disenosi.find('Autores:', index2, len(info_disenosi)) + 9
index2 = info_disenosi.find('/br', index1, len(info_disenosi))
autores = clc(info_disenosi[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Diseños Industriales Asociados')
contdisenosi = [COD_PRODUCTO]
def esquemas_trazadosextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contesquemas_trazados
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaesquemas_trazados = containers[a].td
#print(buscaesquemas_trazados)
try:
if buscaesquemas_trazados.text == "Esquemas de trazados de circuito integrado":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_esquemas_trazados = cont.text
index1 = info_esquemas_trazados.find("- ") + 2
index2 = info_esquemas_trazados.find(':')
tipo = clc(info_esquemas_trazados[index1:index2])
#Tipo Artículo
if tipo.strip() == "Esquema de circuito integrado":
tipo = "41"
else:
logging.critical('Añadir: ' + tipo + ' a esquemas_trazados')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_esquemas_trazados.find('\n ', index1, len(info_esquemas_trazados))
nombreart = clc(info_esquemas_trazados[index1:index2])
index1 = index2 + 17
index2 = info_esquemas_trazados.find(',', index1, len(info_esquemas_trazados))
lugar = clc(info_esquemas_trazados[index1:index2])
index1 = index2 + 2
index2 = info_esquemas_trazados.find(',', index1, len(info_esquemas_trazados))
anopub = clc(info_esquemas_trazados[index1:index2])
index1 = info_esquemas_trazados.find('Disponibilidad:') + 15
index2 = info_esquemas_trazados.find(',', index1, len(info_esquemas_trazados))
disponibilidad = clc(info_esquemas_trazados[index1:index2])
index1 = info_esquemas_trazados.find('Institución financiadora:') + 25
index2 = info_esquemas_trazados.find('Autores:', index1, len(info_esquemas_trazados))
institucion = clc(info_esquemas_trazados[index1:index2])
index1 = info_esquemas_trazados.find('Autores:', index2, len(info_esquemas_trazados)) + 9
index2 = info_esquemas_trazados.find('/br', index1, len(info_esquemas_trazados))
autores = clc(info_esquemas_trazados[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Esquemas de Cirduitos Trazados Asociados')
contesquemas_trazados = [COD_PRODUCTO]
def innovaciones_en_gestionextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global continnovaciones_en_gestion
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscainnovaciones_en_gestion = containers[a].td
#print(buscainnovaciones_en_gestion)
try:
if buscainnovaciones_en_gestion.text == "Innovaciones generadas en la Gestión Empresarial":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_innovaciones_en_gestion = cont.text
index1 = info_innovaciones_en_gestion.find("- ") + 2
index2 = info_innovaciones_en_gestion.find(':')
tipo = clc(info_innovaciones_en_gestion[index1:index2])
#Tipo Artículo
if tipo.strip() == "Organizacional":
tipo = "42"
elif tipo.strip() == "Empresarial":
tipo = "43"
else:
logging.critical('Añadir: ' + tipo + ' a innovaciones_en_gestion')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_innovaciones_en_gestion.find('\n ', index1, len(info_innovaciones_en_gestion))
nombreart = clc(info_innovaciones_en_gestion[index1:index2])
index1 = index2 + 17
index2 = info_innovaciones_en_gestion.find(',', index1, len(info_innovaciones_en_gestion))
lugar = clc(info_innovaciones_en_gestion[index1:index2])
index1 = index2 + 2
index2 = info_innovaciones_en_gestion.find(',', index1, len(info_innovaciones_en_gestion))
anopub = clc(info_innovaciones_en_gestion[index1:index2])
index1 = info_innovaciones_en_gestion.find('Disponibilidad:') + 15
index2 = info_innovaciones_en_gestion.find(',', index1, len(info_innovaciones_en_gestion))
disponibilidad = clc(info_innovaciones_en_gestion[index1:index2])
index1 = info_innovaciones_en_gestion.find('Institución financiadora:') + 25
index2 = info_innovaciones_en_gestion.find('Autores:', index1, len(info_innovaciones_en_gestion))
institucion = clc(info_innovaciones_en_gestion[index1:index2])
index1 = info_innovaciones_en_gestion.find('Autores:', index2, len(info_innovaciones_en_gestion)) + 9
index2 = info_innovaciones_en_gestion.find('/br', index1, len(info_innovaciones_en_gestion))
autores = clc(info_innovaciones_en_gestion[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Esquemas de Cirduitos Trazados Asociados')
continnovaciones_en_gestion = [COD_PRODUCTO]
def innovaciones_procedimientosextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global continnovaciones_procedimientos
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscainnovaciones_procedimientos = containers[a].td
#print(buscainnovaciones_procedimientos)
try:
if buscainnovaciones_procedimientos.text == "Innovaciones en Procesos y Procedimientos":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_innovaciones_procedimientos = cont.text
index1 = info_innovaciones_procedimientos.find("- ") + 2
index2 = info_innovaciones_procedimientos.find(':')
tipo = clc(info_innovaciones_procedimientos[index1:index2])
#Tipo Artículo
if tipo.strip() == "Innovación de proceso o procedimiento":
tipo = "45"
else:
logging.critical('Añadir: ' + tipo + ' a innovaciones_procedimientos')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_innovaciones_procedimientos.find('\n ', index1, len(info_innovaciones_procedimientos))
nombreart = clc(info_innovaciones_procedimientos[index1:index2])
index1 = index2 + 17
index2 = info_innovaciones_procedimientos.find(',', index1, len(info_innovaciones_procedimientos))
lugar = clc(info_innovaciones_procedimientos[index1:index2])
index1 = index2 + 2
index2 = info_innovaciones_procedimientos.find(',', index1, len(info_innovaciones_procedimientos))
anopub = clc(info_innovaciones_procedimientos[index1:index2])
index1 = info_innovaciones_procedimientos.find('Disponibilidad:') + 15
index2 = info_innovaciones_procedimientos.find(',', index1, len(info_innovaciones_procedimientos))
disponibilidad = clc(info_innovaciones_procedimientos[index1:index2])
index1 = info_innovaciones_procedimientos.find('Institución financiadora:') + 25
index2 = info_innovaciones_procedimientos.find('Autores:', index1, len(info_innovaciones_procedimientos))
institucion = clc(info_innovaciones_procedimientos[index1:index2])
index1 = info_innovaciones_procedimientos.find('Autores:', index2, len(info_innovaciones_procedimientos)) + 9
index2 = info_innovaciones_procedimientos.find('/br', index1, len(info_innovaciones_procedimientos))
autores = clc(info_innovaciones_procedimientos[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "null" + "," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ "" +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Innovaciones en Procedimientos Asociadas')
continnovaciones_procedimientos = [COD_PRODUCTO]
def variedad_animalextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contvariedad_animal
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscavariedad_animal = containers[a].td
#print(buscavariedad_animal)
try:
if buscavariedad_animal.text == "Nuevas variedades animal":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_variedad_animal = cont.text
index1 = info_variedad_animal.find("- ") + 2
index2 = info_variedad_animal.find(':')
tipo = clc(info_variedad_animal[index1:index2])
#Tipo Artículo
if tipo.strip() == "Variedad animal":
tipo = "44"
else:
logging.critical('Añadir: ' + tipo + ' a variedad_animal')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_variedad_animal.find('\n ', index1, len(info_variedad_animal))
nombreart = clc(info_variedad_animal[index1:index2])
index1 = index2 + 17
index2 = info_variedad_animal.find(',', index1, len(info_variedad_animal))
lugar = clc(info_variedad_animal[index1:index2])
index1 = index2 + 2
index2 = info_variedad_animal.find(',', index1, len(info_variedad_animal))
anopub = clc(info_variedad_animal[index1:index2])
index1 = info_variedad_animal.find('Acto administrativo del ICA:') + 28
index2 = info_variedad_animal.find(', Institución financiadora: ', index1, len(info_variedad_animal))
acto = clc(info_variedad_animal[index1:index2])
index1 = info_variedad_animal.find('Institución financiadora:') + 25
index2 = info_variedad_animal.find('Autores:', index1, len(info_variedad_animal))
institucion = clc(info_variedad_animal[index1:index2])
index1 = info_variedad_animal.find('Autores:', index2, len(info_variedad_animal)) + 9
index2 = info_variedad_animal.find('/br', index1, len(info_variedad_animal))
autores = clc(info_variedad_animal[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + acto + "'" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ acto +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Variedades Animales Asociadas')
contvariedad_animal = [COD_PRODUCTO]
def variedad_vegetalextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contvariedad_vegetal
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscavariedad_vegetal = containers[a].td
#print(buscavariedad_vegetal)
try:
if buscavariedad_vegetal.text == "Nuevas variedades vegetal":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_variedad_vegetal = cont.text
index1 = info_variedad_vegetal.find("- ") + 2
index2 = info_variedad_vegetal.find(':')
tipo = clc(info_variedad_vegetal[index1:index2])
#Tipo Artículo
if tipo.strip() == "Variedad vegetal":
tipo = "51"
else:
logging.critical('Añadir: ' + tipo + ' a variedad_vegetal')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_variedad_vegetal.find('\n ', index1, len(info_variedad_vegetal))
nombreart = clc(info_variedad_vegetal[index1:index2])
index1 = index2 + 17
index2 = info_variedad_vegetal.find(',', index1, len(info_variedad_vegetal))
lugar = clc(info_variedad_vegetal[index1:index2])
index1 = index2 + 2
index2 = info_variedad_vegetal.find(',', index1, len(info_variedad_vegetal))
anopub = clc(info_variedad_vegetal[index1:index2])
index1 = info_variedad_vegetal.find(', Sitio web:') + 12
index2 = info_variedad_vegetal.find('\n', index1, len(info_variedad_vegetal))
DOI = clc(info_variedad_vegetal[index1:index2])
index1 = info_variedad_vegetal.find('Tipo de ciclo:') + 14
index2 = info_variedad_vegetal.find(',', index1, len(info_variedad_vegetal))
ciclo = clc(info_variedad_vegetal[index1:index2])
index1 = info_variedad_vegetal.find('Institución financiadora:') + 25
index2 = info_variedad_vegetal.find('Autores:', index1, len(info_variedad_vegetal))
institucion = clc(info_variedad_vegetal[index1:index2])
index1 = info_variedad_vegetal.find('Autores:', index2, len(info_variedad_vegetal)) + 9
index2 = info_variedad_vegetal.find('/br', index1, len(info_variedad_vegetal))
autores = clc(info_variedad_vegetal[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + DOI + "'," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ DOI +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" +ciclo + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ ciclo +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Variedades Vegetales Asociadas')
contvariedad_vegetal = [COD_PRODUCTO]
def planta_pilotoextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contplanta_piloto
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaplanta_piloto = containers[a].td
#print(buscaplanta_piloto)
try:
if buscaplanta_piloto.text == "Plantas piloto":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_planta_piloto = cont.text
index1 = info_planta_piloto.find("- ") + 2
index2 = info_planta_piloto.find(':')
tipo = clc(info_planta_piloto[index1:index2])
#Tipo Artículo
if tipo.strip() == "Planta piloto":
tipo = "93"
else:
logging.critical('Añadir: ' + tipo + ' a planta_piloto')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_planta_piloto.find('\n ', index1, len(info_planta_piloto))
nombreart = clc(info_planta_piloto[index1:index2])
index1 = index2 + 17
index2 = info_planta_piloto.find(',', index1, len(info_planta_piloto))
lugar = clc(info_planta_piloto[index1:index2])
index1 = index2 + 2
index2 = info_planta_piloto.find(',', index1, len(info_planta_piloto))
anopub = clc(info_planta_piloto[index1:index2])
index1 = info_planta_piloto.find('Nombre comercial:') + 17
index2 = info_planta_piloto.find('Institución financiadora:', index1, len(info_planta_piloto))
nombreplanta = clc(info_planta_piloto[index1:index2])
index1 = info_planta_piloto.find('Disponibilidad:') + 15
index2 = info_planta_piloto.find(',', index1, len(info_planta_piloto))
disponibilidad = clc(info_planta_piloto[index1:index2])
index1 = info_planta_piloto.find('Institución financiadora:') + 25
index2 = info_planta_piloto.find('Autores:', index1, len(info_planta_piloto))
institucion = clc(info_planta_piloto[index1:index2])
index1 = info_planta_piloto.find('Autores:', index2, len(info_planta_piloto)) + 9
index2 = info_planta_piloto.find('/br', index1, len(info_planta_piloto))
autores = clc(info_planta_piloto[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "'" + nombreplanta + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ nombreplanta +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Plantas Piloto Asociadas')
contplanta_piloto = [COD_PRODUCTO]
def otros_productos_tecnicosextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contotros_productos_tecnicos
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaotros_productos_tecnicos = containers[a].td
#print(buscaotros_productos_tecnicos)
try:
if buscaotros_productos_tecnicos.text == "Otros productos tecnológicos":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_otros_productos_tecnicos = cont.text
index1 = info_otros_productos_tecnicos.find("- ") + 2
index2 = info_otros_productos_tecnicos.find(':')
tipo = clc(info_otros_productos_tecnicos[index1:index2])
#Tipo Artículo
if tipo.strip() == "Gen Clonado":
tipo = "36"
elif tipo.strip() == "Coleccion biologica de referencia con informacion sistematizada":
tipo = "37"
elif tipo.strip() == "Otro":
tipo = "38"
elif tipo.strip() == "Base de datos de referencia para investigacion":
tipo = "39"
else:
logging.critical('Añadir: ' + tipo + ' a otros_productos_tecnicos')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_otros_productos_tecnicos.find('\n ', index1, len(info_otros_productos_tecnicos))
nombreart = clc(info_otros_productos_tecnicos[index1:index2])
index1 = index2 + 17
index2 = info_otros_productos_tecnicos.find(',', index1, len(info_otros_productos_tecnicos))
lugar = clc(info_otros_productos_tecnicos[index1:index2])
index1 = index2 + 2
index2 = info_otros_productos_tecnicos.find(',', index1, len(info_otros_productos_tecnicos))
anopub = clc(info_otros_productos_tecnicos[index1:index2])
index1 = info_otros_productos_tecnicos.find('Nombre comercial:') + 17
index2 = info_otros_productos_tecnicos.find('Institución financiadora:', index1, len(info_otros_productos_tecnicos))
nombreplanta = clc(info_otros_productos_tecnicos[index1:index2])
index1 = info_otros_productos_tecnicos.find('Disponibilidad:') + 15
index2 = info_otros_productos_tecnicos.find(',', index1, len(info_otros_productos_tecnicos))
disponibilidad = clc(info_otros_productos_tecnicos[index1:index2])
index1 = info_otros_productos_tecnicos.find('Institución financiadora:') + 25
index2 = info_otros_productos_tecnicos.find('Autores:', index1, len(info_otros_productos_tecnicos))
institucion = clc(info_otros_productos_tecnicos[index1:index2])
index1 = info_otros_productos_tecnicos.find('Autores:', index2, len(info_otros_productos_tecnicos)) + 9
index2 = info_otros_productos_tecnicos.find('/br', index1, len(info_otros_productos_tecnicos))
autores = clc(info_otros_productos_tecnicos[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "'" + nombreplanta + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ nombreplanta +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Plantas Piloto Asociadas')
contotros_productos_tecnicos = [COD_PRODUCTO]
def regulaciones_normasextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contregulaciones_normas
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaregulaciones_normas = containers[a].td
#print(buscaregulaciones_normas)
try:
if buscaregulaciones_normas.text == "Regulaciones y Normas":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_regulaciones_normas = cont.text
index1 = info_regulaciones_normas.find("- ") + 2
index2 = info_regulaciones_normas.find(':')
tipo = clc(info_regulaciones_normas[index1:index2])
#Tipo Artículo
if tipo.strip() == "Ambiental o de Salud":
tipo = "61"
elif tipo.strip() == "Educativa":
tipo = "62"
elif tipo.strip() == "Social":
tipo = "63"
elif tipo.strip() == "Técnica":
tipo = "64"
elif tipo.strip() == "Guía de práctica clínica":
tipo = "65"
elif tipo.strip() == "Proyecto de ley":
tipo = "66"
elif tipo.strip() == "Básica":
tipo = "74"
elif tipo.strip() == "Ensayo":
tipo = "75"
elif tipo.strip() == "Proceso":
tipo = "77"
else:
logging.critical('Añadir: ' + tipo + ' a regulaciones_normas')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_regulaciones_normas.find('\n ', index1, len(info_regulaciones_normas))
nombreart = clc(info_regulaciones_normas[index1:index2])
index1 = index2 + 17
index2 = info_regulaciones_normas.find(',', index1, len(info_regulaciones_normas))
lugar = clc(info_regulaciones_normas[index1:index2])
index1 = index2 + 2
index2 = info_regulaciones_normas.find(',', index1, len(info_regulaciones_normas))
anopub = clc(info_regulaciones_normas[index1:index2])
index1 = info_regulaciones_normas.find('Ambito:') + 7
index2 = info_regulaciones_normas.find(',', index1, len(info_regulaciones_normas))
ambito = clc(info_regulaciones_normas[index1:index2])
index1 = info_regulaciones_normas.find('Disponibilidad:') + 15
index2 = info_regulaciones_normas.find(',', index1, len(info_regulaciones_normas))
disponibilidad = clc(info_regulaciones_normas[index1:index2])
index1 = info_regulaciones_normas.find('Objeto:') + 7
index2 = info_regulaciones_normas.find('Institución financiadora:', index1, len(info_regulaciones_normas))
objeto = clc(info_regulaciones_normas[index1:index2])
index1 = info_regulaciones_normas.find('Fecha de publicación:') + 21
index2 = info_regulaciones_normas.find(',', index1, len(info_regulaciones_normas))
fecha = clc(info_regulaciones_normas[index1:index2])
index1 = info_regulaciones_normas.find('Institución financiadora:') + 25
index2 = info_regulaciones_normas.find('Autores:', index1, len(info_regulaciones_normas))
institucion = clc(info_regulaciones_normas[index1:index2])
index1 = info_regulaciones_normas.find('Autores:', index2, len(info_regulaciones_normas)) + 9
index2 = info_regulaciones_normas.find('/br', index1, len(info_regulaciones_normas))
autores = clc(info_regulaciones_normas[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + ambito + "'," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ ambito +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + objeto + "'," \
+ "'" + fecha + "'," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ objeto +";" \
+ fecha +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Plantas Piloto Asociadas')
contregulaciones_normas = [COD_PRODUCTO]
def guias_clinicasextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contguias_clinicas
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaguias_clinicas = containers[a].td
#print(buscaguias_clinicas)
try:
if buscaguias_clinicas.text == "Guias de práctica clínica":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(2, len(container)):
cont = container[x]
info_guias_clinicas = cont.text
index1 = info_guias_clinicas.find("- ") + 2
index2 = info_guias_clinicas.find(':')
tipo = clc(info_guias_clinicas[index1:index2])
#Tipo Artículo
if tipo.strip() == "Ambiental o de Salud":
tipo = "61"
elif tipo.strip() == "Educativa":
tipo = "62"
elif tipo.strip() == "Social":
tipo = "63"
elif tipo.strip() == "Técnica":
tipo = "64"
elif tipo.strip() == "Guía de práctica clínica":
tipo = "65"
elif tipo.strip() == "Proyecto de ley":
tipo = "66"
elif tipo.strip() == "Técnica - Básica":
tipo = "74"
elif tipo.strip() == "Técnica - Ensayo":
tipo = "75"
elif tipo.strip() == "Técnica - Proceso":
tipo = "77"
else:
logging.critical('Añadir: ' + tipo + ' a guias_clinicas' )
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_guias_clinicas.find('\n ', index1, len(info_guias_clinicas))
nombreart = clc(info_guias_clinicas[index1:index2])
index1 = index2 + 17
index2 = info_guias_clinicas.find(',', index1, len(info_guias_clinicas))
lugar = clc(info_guias_clinicas[index1:index2])
index1 = index2 + 2
index2 = info_guias_clinicas.find(',', index1, len(info_guias_clinicas))
anopub = clc(info_guias_clinicas[index1:index2])
index1 = info_guias_clinicas.find('Ambito:') + 7
index2 = info_guias_clinicas.find(',', index1, len(info_guias_clinicas))
ambito = clc(info_guias_clinicas[index1:index2])
index1 = info_guias_clinicas.find('Disponibilidad:') + 15
index2 = info_guias_clinicas.find(',', index1, len(info_guias_clinicas))
disponibilidad = clc(info_guias_clinicas[index1:index2])
index1 = info_guias_clinicas.find('Objeto:') + 7
index2 = info_guias_clinicas.find('Institución financiadora:', index1, len(info_guias_clinicas))
objeto = clc(info_guias_clinicas[index1:index2])
index1 = info_guias_clinicas.find('Fecha de publicación:') + 21
index2 = info_guias_clinicas.find(',', index1, len(info_guias_clinicas))
fecha = clc(info_guias_clinicas[index1:index2])
index1 = info_guias_clinicas.find('Institución financiadora:') + 25
index2 = info_guias_clinicas.find('Autores:', index1, len(info_guias_clinicas))
institucion = clc(info_guias_clinicas[index1:index2])
index1 = info_guias_clinicas.find('Autores:', index2, len(info_guias_clinicas)) + 9
index2 = info_guias_clinicas.find('/br', index1, len(info_guias_clinicas))
autores = clc(info_guias_clinicas[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + ambito + "'," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ ambito +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + objeto + "'," \
+ "'" + fecha + "'," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ objeto +";" \
+ fecha +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Plantas Piloto Asociadas')
contguias_clinicas = [COD_PRODUCTO]
def prototiposextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contprototipos
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaprototipos = containers[a].td
#print(buscaprototipos)
try:
if buscaprototipos.text == "Prototipos":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_prototipos = cont.text
index1 = info_prototipos.find("- ") + 2
index2 = info_prototipos.find(':')
tipo = clc(info_prototipos[index1:index2])
#Tipo Artículo
if tipo.strip() == "Servicios":
tipo = "92"
elif tipo.strip() == "Industrial":
tipo = "94"
else:
logging.critical('Añadir: ' + tipo + ' a prototipos')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_prototipos.find('\n ', index1, len(info_prototipos))
nombreart = clc(info_prototipos[index1:index2])
index1 = index2 + 17
index2 = info_prototipos.find(',', index1, len(info_prototipos))
lugar = clc(info_prototipos[index1:index2])
index1 = index2 + 2
index2 = info_prototipos.find(',', index1, len(info_prototipos))
anopub = clc(info_prototipos[index1:index2])
index1 = info_prototipos.find('Disponibilidad:') + 15
index2 = info_prototipos.find(',', index1, len(info_prototipos))
disponibilidad = clc(info_prototipos[index1:index2])
index1 = info_prototipos.find('Institución financiadora:') + 25
index2 = info_prototipos.find('Autores:', index1, len(info_prototipos))
institucion = clc(info_prototipos[index1:index2])
index1 = info_prototipos.find('Autores:', index2, len(info_prototipos)) + 9
index2 = info_prototipos.find('/br', index1, len(info_prototipos))
autores = clc(info_prototipos[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Esquemas de Cirduitos Trazados Asociados')
contprototipos = [COD_PRODUCTO]
def reglamentos_tecnicosextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contreglamentos_tecnicos
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscareglamentos_tecnicos = containers[a].td
#print(buscareglamentos_tecnicos)
try:
if buscareglamentos_tecnicos.text == "Reglamentos técnicos":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_reglamentos_tecnicos = cont.text
index1 = info_reglamentos_tecnicos.find("- ") + 2
index2 = info_reglamentos_tecnicos.find(':')
tipo = clc(info_reglamentos_tecnicos[index1:index2])
#Tipo Artículo
if tipo.strip() == "Reglamento Técnico":
tipo = "67"
else:
logging.critical('Añadir: ' + tipo + ' a reglamentos_tecnicos')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_reglamentos_tecnicos.find('\n ', index1, len(info_reglamentos_tecnicos))
nombreart = clc(info_reglamentos_tecnicos[index1:index2])
index1 = index2 + 17
index2 = info_reglamentos_tecnicos.find(',', index1, len(info_reglamentos_tecnicos))
lugar = clc(info_reglamentos_tecnicos[index1:index2])
index1 = index2 + 2
index2 = info_reglamentos_tecnicos.find(',', index1, len(info_reglamentos_tecnicos))
anopub = clc(info_reglamentos_tecnicos[index1:index2])
index1 = info_reglamentos_tecnicos.find('Ambito:') + 7
index2 = info_reglamentos_tecnicos.find(',', index1, len(info_reglamentos_tecnicos))
ambito = clc(info_reglamentos_tecnicos[index1:index2])
index1 = info_reglamentos_tecnicos.find('Sitio web:') + 10
index2 = info_reglamentos_tecnicos.find('Institución financiadora:', index1, len(info_reglamentos_tecnicos))
DOI = clc(info_reglamentos_tecnicos[index1:index2])
index1 = info_reglamentos_tecnicos.find('Disponibilidad:') + 15
index2 = info_reglamentos_tecnicos.find(',', index1, len(info_reglamentos_tecnicos))
disponibilidad = clc(info_reglamentos_tecnicos[index1:index2])
index1 = info_reglamentos_tecnicos.find('Objeto:') + 7
index2 = info_reglamentos_tecnicos.find('Institución financiadora:', index1, len(info_reglamentos_tecnicos))
objeto = clc(info_reglamentos_tecnicos[index1:index2])
index1 = info_reglamentos_tecnicos.find('Fecha de publicación:') + 21
index2 = info_reglamentos_tecnicos.find(',', index1, len(info_reglamentos_tecnicos))
fecha = clc(info_reglamentos_tecnicos[index1:index2])
index1 = info_reglamentos_tecnicos.find('Institución financiadora:') + 25
index2 = info_reglamentos_tecnicos.find('Autores:', index1, len(info_reglamentos_tecnicos))
institucion = clc(info_reglamentos_tecnicos[index1:index2])
index1 = info_reglamentos_tecnicos.find('Autores:', index2, len(info_reglamentos_tecnicos)) + 9
index2 = info_reglamentos_tecnicos.find('/br', index1, len(info_reglamentos_tecnicos))
autores = clc(info_reglamentos_tecnicos[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + DOI + "'," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ DOI +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Esquemas de Cirduitos Trazados Asociados')
contreglamentos_tecnicos = [COD_PRODUCTO]
def signos_distintivosextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contsignos_distintivos
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscasignos_distintivos = containers[a].td
#print(buscasignos_distintivos)
try:
if buscasignos_distintivos.text == "Signos distintivos ":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_signos_distintivos = cont.text
index1 = info_signos_distintivos.find("- ") + 2
index2 = info_signos_distintivos.find(':')
tipo = clc(info_signos_distintivos[index1:index2])
#Tipo Artículo
if tipo.strip() == "Signos distintivos":
tipo = "71"
elif tipo.strip() == "Marcas":
tipo = "95"
elif tipo.strip() == "Nombres comerciales":
tipo = "96"
else:
logging.critical('Añadir: ' + tipo + ' a signos_distintivos')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_signos_distintivos.find('\n ', index1, len(info_signos_distintivos))
nombreart = clc(info_signos_distintivos[index1:index2])
index1 = index2 + 17
index2 = info_signos_distintivos.find(',', index1, len(info_signos_distintivos))
lugar = clc(info_signos_distintivos[index1:index2])
index1 = index2 + 2
index2 = info_signos_distintivos.find(',', index1, len(info_signos_distintivos))
anopub = clc(info_signos_distintivos[index1:index2])
index1 = info_signos_distintivos.find('Ambito:') + 7
index2 = info_signos_distintivos.find(',', index1, len(info_signos_distintivos))
ambito = clc(info_signos_distintivos[index1:index2])
index1 = info_signos_distintivos.find('Sitio web:') + 10
index2 = info_signos_distintivos.find('Institución financiadora:', index1, len(info_signos_distintivos))
DOI = clc(info_signos_distintivos[index1:index2])
index1 = info_signos_distintivos.find('Disponibilidad:') + 15
index2 = info_signos_distintivos.find(',', index1, len(info_signos_distintivos))
disponibilidad = clc(info_signos_distintivos[index1:index2])
index1 = info_signos_distintivos.find('Objeto:') + 7
index2 = info_signos_distintivos.find('Institución financiadora:', index1, len(info_signos_distintivos))
objeto = clc(info_signos_distintivos[index1:index2])
index1 = info_signos_distintivos.find('Fecha de publicación:') + 21
index2 = info_signos_distintivos.find(',', index1, len(info_signos_distintivos))
fecha = clc(info_signos_distintivos[index1:index2])
index1 = info_signos_distintivos.find('Institución financiadora:') + 25
index2 = info_signos_distintivos.find('Autores:', index1, len(info_signos_distintivos))
institucion = clc(info_signos_distintivos[index1:index2])
index1 = info_signos_distintivos.find('Número del registro:') + 20
index2 = info_signos_distintivos.find(',', index1, len(info_signos_distintivos))
contrato = clc(info_signos_distintivos[index1:index2])
index1 = info_signos_distintivos.find('Nombre del titular:') + 19
index2 = info_signos_distintivos.find('\n', index1, len(info_signos_distintivos))
autores = clc(info_signos_distintivos[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + contrato + "'," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ contrato +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Esquemas de Cirduitos Trazados Asociados')
contsignos_distintivos = [COD_PRODUCTO]
def empresas_base_tecextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contempresas_base_tec
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaempresas_base_tec = containers[a].td
#print(buscaempresas_base_tec)
try:
if buscaempresas_base_tec.text == "Empresas de base tecnológica ":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_empresas_base_tec = cont.text
index1 = info_empresas_base_tec.find("- ") + 2
index2 = info_empresas_base_tec.find(':')
tipo = clc(info_empresas_base_tec[index1:index2])
#Tipo Artículo
if tipo.strip() == "Spin-off":
tipo = "68"
elif tipo.strip() == "Start-up":
tipo = "69"
else:
logging.critical('Añadir: ' + tipo + ' a empresas_base_tec')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_empresas_base_tec.find('\n ', index1, len(info_empresas_base_tec))
nombreart = clc(info_empresas_base_tec[index1:index2])
index1 = index2 + 17
index2 = info_empresas_base_tec.find(',', index1, len(info_empresas_base_tec))
fecha_publica = clc(info_empresas_base_tec[index1:index2])
index1 = index2 - 5
index2 = info_empresas_base_tec.find(',', index1, len(info_empresas_base_tec))
anopub = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Ambito:') + 7
index2 = info_empresas_base_tec.find(',', index1, len(info_empresas_base_tec))
ambito = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('NIT:') + 4
index2 = info_empresas_base_tec.find(',', index1, len(info_empresas_base_tec))
nit = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Fecha de registro ante cámara:') + 30
index2 = info_empresas_base_tec.find('\n', index1, len(info_empresas_base_tec))
registrocamara = clc(info_empresas_base_tec[index1:index2])
index1 = index2 +2
index2 = info_empresas_base_tec.find('\n', index1, len(info_empresas_base_tec))
productos = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Sitio web:') + 10
index2 = info_empresas_base_tec.find('Institución financiadora:', index1, len(info_empresas_base_tec))
DOI = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Disponibilidad:') + 15
index2 = info_empresas_base_tec.find(',', index1, len(info_empresas_base_tec))
disponibilidad = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Objeto:') + 7
index2 = info_empresas_base_tec.find('Institución financiadora:', index1, len(info_empresas_base_tec))
objeto = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Institución financiadora:') + 25
index2 = info_empresas_base_tec.find('Autores:', index1, len(info_empresas_base_tec))
institucion = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Número del registro:') + 20
index2 = info_empresas_base_tec.find(',', index1, len(info_empresas_base_tec))
contrato = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Nombre del titular:') + 19
index2 = info_empresas_base_tec.find('\n', index1, len(info_empresas_base_tec))
titular = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Nombre del proyecto:') + 20
index2 = info_empresas_base_tec.find('Institución financiadora:', index1, len(info_empresas_base_tec))
proyecto = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Nombre comercial:') + 17
index2 = info_empresas_base_tec.find('Nombre del proyecto:', index1, len(info_empresas_base_tec))
comercial = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Sitio web:') + 10
index2 = info_empresas_base_tec.find('Nombre comercial:', index1, len(info_empresas_base_tec))
DOI = clc(info_empresas_base_tec[index1:index2])
index1 = info_empresas_base_tec.find('Autores:') + 9
index2 = info_empresas_base_tec.find('/n', index1, len(info_empresas_base_tec))
autores = clc(info_empresas_base_tec[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "null" + "," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ "" +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + nit + "'," \
+ "'" + registrocamara + "'," \
+ "'" + productos + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ nit +";" \
+ registrocamara +";" \
+ productos +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Esquemas de Cirduitos Trazados Asociados')
contempresas_base_tec = [COD_PRODUCTO]
def software_registradoextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contsoftware_registrado
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscasoftware_registrado = containers[a].td
#print(buscasoftware_registrado)
try:
if buscasoftware_registrado.text == "Softwares ":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(1, len(container)):
cont = container[x]
info_software_registrado = cont.text
index1 = info_software_registrado.find("- ") + 2
index2 = info_software_registrado.find(':')
tipo = clc(info_software_registrado[index1:index2])
#Tipo Artículo
if tipo.strip() == "Computacional":
tipo = "35"
elif tipo.strip() == "Multimedia":
tipo = "72"
elif tipo.strip() == "Otra":
tipo = "73"
else:
logging.critical('Añadir: ' + tipo + ' a software_registrado')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_software_registrado.find('\n ', index1, len(info_software_registrado))
nombreart = clc(info_software_registrado[index1:index2])
index1 = index2 + 17
index2 = info_software_registrado.find(',', index1, len(info_software_registrado))
lugar = clc(info_software_registrado[index1:index2])
index1 = index2 + 2
index2 = info_software_registrado.find(',', index1, len(info_software_registrado))
anopub = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Ambito:') + 7
index2 = info_software_registrado.find(',', index1, len(info_software_registrado))
ambito = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Sitio web:') + 10
index2 = info_software_registrado.find('Institución financiadora:', index1, len(info_software_registrado))
DOI = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Disponibilidad:') + 15
index2 = info_software_registrado.find(',', index1, len(info_software_registrado))
disponibilidad = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Objeto:') + 7
index2 = info_software_registrado.find('Institución financiadora:', index1, len(info_software_registrado))
objeto = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Fecha de publicación:') + 21
index2 = info_software_registrado.find(',', index1, len(info_software_registrado))
fecha = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Institución financiadora:') + 25
index2 = info_software_registrado.find('Autores:', index1, len(info_software_registrado))
institucion = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Número del registro:') + 20
index2 = info_software_registrado.find(',', index1, len(info_software_registrado))
contrato = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Nombre del titular:') + 19
index2 = info_software_registrado.find('\n', index1, len(info_software_registrado))
titular = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Nombre del proyecto:') + 20
index2 = info_software_registrado.find('Institución financiadora:', index1, len(info_software_registrado))
proyecto = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Nombre comercial:') + 17
index2 = info_software_registrado.find('Nombre del proyecto:', index1, len(info_software_registrado))
comercial = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Sitio web:') + 10
index2 = info_software_registrado.find('Nombre comercial:', index1, len(info_software_registrado))
DOI = clc(info_software_registrado[index1:index2])
index1 = info_software_registrado.find('Autores:', index2, len(info_software_registrado)) + 9
index2 = info_software_registrado.find('/br', index1, len(info_software_registrado))
autores = clc(info_software_registrado[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "'" + lugar + "'," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + DOI + "'," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ lugar +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ DOI +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "'" + comercial + "'," \
+ "'" + proyecto + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + disponibilidad + "'," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ comercial +";" \
+ proyecto +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ disponibilidad +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Esquemas de Cirduitos Trazados Asociados')
contsoftware_registrado = [COD_PRODUCTO]
def proyectos_leyextract():
from settings import my_url, coduapa, codhermes, codcolciencias, nombregi, dnilider, my_url, COD_PRODUCTO
import bs4, logging, sys, re, init
global contproyectos_ley
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG,
format = "%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
page_soup = soup(page_html,"html.parser")
containers = page_soup.findAll("table")
for a in range(0,len(containers)):
buscaproyectos_ley = containers[a].td
#print(buscaproyectos_ley)
try:
if buscaproyectos_ley.text == "Proyectos de ley":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("tr")
for x in range(2, len(container)):
cont = container[x]
info_proyectos_ley = cont.text
index1 = info_proyectos_ley.find("- ") + 2
index2 = info_proyectos_ley.find(':')
tipo = clc(info_proyectos_ley[index1:index2])
#Tipo Artículo
if tipo.strip() == "Ambiental o de Salud":
tipo = "61"
elif tipo.strip() == "Educativa":
tipo = "62"
elif tipo.strip() == "Social":
tipo = "63"
elif tipo.strip() == "Técnica":
tipo = "64"
elif tipo.strip() == "Guía de práctica clínica":
tipo = "65"
elif tipo.strip() == "Proyecto de ley":
tipo = "66"
elif tipo.strip() == "Técnica - Básica":
tipo = "74"
elif tipo.strip() == "Técnica - Ensayo":
tipo = "75"
elif tipo.strip() == "Técnica - Proceso":
tipo = "77"
else:
logging.critical('Añadir: ' + tipo + ' a proyectos_ley')
print ("ALERTA: Revisar el archivo Registros.log")
index1 = index2 + 2
index2 = info_proyectos_ley.find('\n ', index1, len(info_proyectos_ley))
nombreart = clc(info_proyectos_ley[index1:index2])
index1 = index2 + 17
index2 = info_proyectos_ley.find(',', index1, len(info_proyectos_ley))
lugar = clc(info_proyectos_ley[index1:index2])
index1 = index2 + 2
index2 = info_proyectos_ley.find(',', index1, len(info_proyectos_ley))
anopub = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Ambito:') + 7
index2 = info_proyectos_ley.find(',', index1, len(info_proyectos_ley))
ambito = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Sitio web:') + 10
index2 = info_proyectos_ley.find('Institución financiadora:', index1, len(info_proyectos_ley))
DOI = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Disponibilidad:') + 15
index2 = info_proyectos_ley.find(',', index1, len(info_proyectos_ley))
disponibilidad = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Objeto:') + 7
index2 = info_proyectos_ley.find('Institución financiadora:', index1, len(info_proyectos_ley))
objeto = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Fecha de publicación:') + 21
index2 = info_proyectos_ley.find(',', index1, len(info_proyectos_ley))
fecha = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Institución financiadora:') + 25
index2 = info_proyectos_ley.find('Autores:', index1, len(info_proyectos_ley))
institucion = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Número del registro:') + 20
index2 = info_proyectos_ley.find(',', index1, len(info_proyectos_ley))
contrato = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Nombre del titular:') + 19
index2 = info_proyectos_ley.find('\n', index1, len(info_proyectos_ley))
titular = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Nombre del proyecto:') + 20
index2 = info_proyectos_ley.find('Institución financiadora:', index1, len(info_proyectos_ley))
proyecto = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Nombre comercial:') + 17
index2 = info_proyectos_ley.find('Nombre del proyecto:', index1, len(info_proyectos_ley))
comercial = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Sitio web:') + 10
index2 = info_proyectos_ley.find('Nombre comercial:', index1, len(info_proyectos_ley))
DOI = clc(info_proyectos_ley[index1:index2])
index1 = info_proyectos_ley.find('Autores:') + 9
index2 = info_proyectos_ley.find('/n', index1, len(info_proyectos_ley))
autores = clc(info_proyectos_ley[index1:index2])
init.REL_GRUPO_PRODUCTO.append( \
"REPLACE INTO `uapa_db`.`REL_GRUPO_PRODUCTO`(`CODGP_PROD`,`CODGP`,`GP_TIPO_PROD`,`Nombre_Producto`,`Lugar`,`Año`,`Idioma`,`Páginas`,`Volumen`,`Editorial`,`Ambito`,`DOI`,`Descripción`,`Instituciones`,`Tipo_Vincula_Institu`,`Autores`) VALUES"
+ "('" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + "'," \
+ tipo + "," \
+ "'" + nombreart + "'," \
+ "null" + "," \
+ anopub + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + institucion + "'," \
+ "'Financiadora'," \
+ "'" + autores + "'" \
+ ");\n")
init.REL_GRUPO_PRODUCTO_CSV.append(str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) +";" \
+ tipo +";" \
+ nombreart +";" \
+ "" +";" \
+ anopub +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ institucion +";" \
+ "Financiadora" +";" \
+ autores +";" \
+ "\n")
init.GP_PROD_TEC.append( \
"REPLACE INTO `uapa_db`.`GP_PROD_TEC`(`CODGP_PROD_TEC`,`CODGP_PROD`,`Tema`,`Nombre_Comerial`,`Nombre_Proyecto`,`Tipo_de_Ciclo`,`NIT`,`Fecha_de_Registro`,`Tiene_Productos`,`Disponibilidad`,`Objeto`,`Fecha_Publicación`,`Número_de_Contrato`,`Acto_Administrativo`) VALUES"
+ "('" + str(codcolciencias) + "T" + str(COD_PRODUCTO) + "',"\
+ "'" + str(codcolciencias) + str(COD_PRODUCTO) + "',"\
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "null" + "," \
+ "'" + objeto + "'," \
+ "'" + fecha + "'," \
+ "null" + "," \
+ "null" \
+ ");\n")
init.GP_PROD_TEC_CSV.append(str(codcolciencias) + "T" + str(COD_PRODUCTO) +";" \
+ str(codcolciencias) + str(COD_PRODUCTO) +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ "" +";" \
+ objeto + ";" \
+ fecha + ";" \
+ "" +";" \
+ "" +";" \
+ "\n")
COD_PRODUCTO += 1
else:
logging.info(' El Grupo: ' + nombregi + 'no tiene Esquemas de Cirduitos Trazados Asociados')
contproyectos_ley = [COD_PRODUCTO]
| 45.301933
| 280
| 0.512259
| 11,605
| 128,884
| 5.477036
| 0.039638
| 0.031592
| 0.037381
| 0.038011
| 0.884646
| 0.84094
| 0.79168
| 0.764557
| 0.736725
| 0.715769
| 0
| 0.017837
| 0.328381
| 128,884
| 2,844
| 281
| 45.317862
| 0.716454
| 0.011693
| 0
| 0.78343
| 0
| 0.013081
| 0.165067
| 0.071825
| 0
| 0
| 0
| 0
| 0
| 1
| 0.006904
| false
| 0.006541
| 0.026526
| 0
| 0.033794
| 0.006177
| 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
|
32759f5a80ac6a47408688272b03567e1c979029
| 9,733
|
py
|
Python
|
2021/solutions/day16.py
|
rsizem2/aoc_2020
|
aa2dbf72a4c44930755bd9cc132ad7854f742f09
|
[
"MIT"
] | null | null | null |
2021/solutions/day16.py
|
rsizem2/aoc_2020
|
aa2dbf72a4c44930755bd9cc132ad7854f742f09
|
[
"MIT"
] | null | null | null |
2021/solutions/day16.py
|
rsizem2/aoc_2020
|
aa2dbf72a4c44930755bd9cc132ad7854f742f09
|
[
"MIT"
] | null | null | null |
import numpy as np
from collections import deque, Counter
from functools import reduce
def read_file(test = True):
if test:
filename = '../tests/day16.txt'
else:
filename = '../input/day16.txt'
with open(filename) as file:
temp = list()
for line in file:
temp = list(line.strip())
return temp
convert = {
'0' : '0000',
'1' : '0001',
'2' : '0010',
'3' : '0011',
'4' : '0100',
'5' : '0101',
'6' : '0110',
'7' : '0111',
'8' : '1000',
'9' : '1001',
'A' : '1010',
'B' : '1011',
'C' : '1100',
'D' : '1101',
'E' : '1110',
'F' : '1111',
}
def pop(packet, n):
temp = list()
for i in range(n):
temp.append(packet.popleft())
return packet, ''.join(temp),
def parse_outer(packet):
# Version number
packet, version = pop(packet, 3)
version = int(version,2)
count = version
# Type ID
packet, type_id = pop(packet, 3)
type_id = int(type_id,2)
if type_id == 4:
# Literal
#print('Literal')
#print(version, count)
literal = list()
packet, temp = pop(packet, 1)
while temp == '1':
packet, temp = pop(packet, 4)
literal.append(temp)
packet, temp = pop(packet, 1)
# remaining bits
packet, temp = pop(packet, 4)
literal.append(temp)
literal = int(''.join(literal), 2)
else:
#print('Operator')
#print(version, count)
# Operator
packet, temp = pop(packet, 1)
if temp == '0':
# find length of subpackets
packet, temp = pop(packet, 15)
subpacket_length = int(temp,2)
packet, temp = pop(packet, subpacket_length)
# Parse subpackets
#print('subpackets:', subpacket_length, 'bits:')
temp = deque(temp)
while temp:
temp, count = parse_inner(temp, count)
elif temp == '1':
# find number of subpackets
packet, temp = pop(packet, 11)
subpackets = int(temp,2)
#print(f'{subpackets} sub packets:')
# Parse subpackets
for i in range(subpackets):
packet, count = parse_inner(packet, count)
#print(packet)
return count
def parse_inner(packet, count):
current = list()
# Version number
packet, version = pop(packet, 3)
current.append(version)
version = int(version,2)
count += version
# Type ID
packet, type_id = pop(packet, 3)
current.append(type_id)
type_id = int(type_id,2)
if type_id == 4:
# Literal
#print('Literal')
#print(version, count)
literal = list()
packet, temp = pop(packet, 1)
current.append(temp)
while temp == '1':
packet, temp = pop(packet, 4)
literal.append(temp)
current.append(temp)
packet, temp = pop(packet, 1)
current.append(temp)
# remaining bits
packet, temp = pop(packet, 4)
current.append(temp)
literal.append(temp)
literal = int(''.join(literal), 2)
#print(''.join(current))
else:
#print('Operator')
#print(version, count)
# Operator
packet, temp = pop(packet, 1)
current.append(temp)
if temp == '0':
# find length of subpackets
packet, temp = pop(packet, 15)
current.append(temp)
subpacket_length = int(temp,2)
packet, temp = pop(packet, subpacket_length)
current.append(temp)
# Parse subpackets
#print('subpackets:', subpacket_length, 'bits:')
temp = deque(temp)
while temp:
temp, count = parse_inner(temp, count)
elif temp == '1':
# find number of subpackets
packet, temp = pop(packet, 11)
current.append(temp)
subpackets = int(temp,2)
#print(f'{subpackets} sub packets:')
# Parse subpackets
for i in range(subpackets):
packet, count = parse_inner(packet, count)
#print(''.join(current))
return packet, count
def puzzle1(test = True):
temp = ''.join(list(map(lambda x: convert[x], read_file(test))))
temp = deque(temp)
count = parse_outer(temp)
print(count)
def parse_outer2(packet):
# Version number
packet, version = pop(packet, 3)
version = int(version,2)
# Type ID
packet, type_id = pop(packet, 3)
type_id = int(type_id,2)
if type_id == 4:
# Literal
#print('Literal')
#print(version, count)
literal = list()
packet, temp = pop(packet, 1)
while temp == '1':
packet, temp = pop(packet, 4)
literal.append(temp)
packet, temp = pop(packet, 1)
# remaining bits
packet, temp = pop(packet, 4)
literal.append(temp)
literal = int(''.join(literal), 2)
return literal
else:
#print('Operator')
#print(version, count)
# Operator
packet, temp = pop(packet, 1)
if temp == '0':
# find length of subpackets
packet, temp = pop(packet, 15)
subpacket_length = int(temp,2)
packet, temp = pop(packet, subpacket_length)
# Parse subpackets
#print('subpackets:', subpacket_length, 'bits:')
temp = deque(temp)
values = list()
while temp:
temp, value = parse_inner2(temp)
values.append(value)
elif temp == '1':
# find number of subpackets
packet, temp = pop(packet, 11)
subpackets = int(temp,2)
#print(f'{subpackets} sub packets:')
# Parse subpackets
values = list()
for i in range(subpackets):
packet, value = parse_inner2(packet)
values.append(value)
#print(packet)
if type_id == 0:
# sum
return reduce(lambda x,y: x+y, values)
elif type_id == 1:
# product
return reduce(lambda x,y: x*y, values)
elif type_id == 2:
# minimum
return min(values)
elif type_id == 3:
# maximum
return max(values)
elif type_id == 5:
# greater than
assert len(values) == 2
if values[0] > values[1]:
return 1
else:
return 0
elif type_id == 6:
# less than
assert len(values) == 2
if values[0] < values[1]:
return 1
else:
return 0
elif type_id == 7:
# equal to
assert len(values) == 2
if values[0] == values[1]:
return 1
else:
return 0
def parse_inner2(packet):
# Version number
packet, version = pop(packet, 3)
version = int(version,2)
# Type ID
packet, type_id = pop(packet, 3)
type_id = int(type_id,2)
if type_id == 4:
# Literal
#print('Literal')
#print(version, count)
literal = list()
packet, temp = pop(packet, 1)
while temp == '1':
packet, temp = pop(packet, 4)
literal.append(temp)
packet, temp = pop(packet, 1)
# remaining bits
packet, temp = pop(packet, 4)
literal.append(temp)
literal = int(''.join(literal), 2)
return packet, literal
else:
#print('Operator')
#print(version, count)
# Operator
packet, temp = pop(packet, 1)
if temp == '0':
# find length of subpackets
packet, temp = pop(packet, 15)
subpacket_length = int(temp,2)
packet, temp = pop(packet, subpacket_length)
# Parse subpackets
#print('subpackets:', subpacket_length, 'bits:')
temp = deque(temp)
values = list()
while temp:
temp, value = parse_inner2(temp)
values.append(value)
elif temp == '1':
# find number of subpackets
packet, temp = pop(packet, 11)
subpackets = int(temp,2)
#print(f'{subpackets} sub packets:')
# Parse subpackets
values = list()
for i in range(subpackets):
packet, value = parse_inner2(packet)
values.append(value)
#print(packet)
if type_id == 0:
# sum
return packet, reduce(lambda x,y: x+y, values)
elif type_id == 1:
# product
return packet, reduce(lambda x,y: x*y, values)
elif type_id == 2:
# minimum
return packet, min(values)
elif type_id == 3:
# maximum
return packet, max(values)
elif type_id == 5:
# greater than
assert len(values) == 2
if values[0] > values[1]:
return packet, 1
else:
return packet, 0
elif type_id == 6:
# less than
assert len(values) == 2
if values[0] < values[1]:
return packet, 1
else:
return packet, 0
elif type_id == 7:
# equal to
assert len(values) == 2
if values[0] == values[1]:
return packet, 1
else:
return packet, 0
def puzzle2(test = True):
temp = ''.join(list(map(lambda x: convert[x], read_file(test))))
temp = deque(temp)
count = parse_outer2(temp)
print(count)
puzzle1(False)
puzzle2(False)
| 28.048991
| 68
| 0.507346
| 1,096
| 9,733
| 4.45073
| 0.111314
| 0.075646
| 0.085281
| 0.124641
| 0.858959
| 0.850554
| 0.850554
| 0.834358
| 0.798278
| 0.798278
| 0
| 0.035021
| 0.375116
| 9,733
| 346
| 69
| 28.130058
| 0.767017
| 0.14343
| 0
| 0.751037
| 0
| 0
| 0.015502
| 0
| 0
| 0
| 0
| 0
| 0.024896
| 1
| 0.033195
| false
| 0
| 0.012448
| 0
| 0.153527
| 0.008299
| 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
|
08adfd3ca33dd506a0e40f92c1f24b3ed652c518
| 51,724
|
py
|
Python
|
api/chalicelib/core/insights.py
|
levkov/openreplay
|
8e85d62b823dbf72085afff3f2f1fa9fa3975ed3
|
[
"MIT"
] | 2
|
2022-02-08T23:57:53.000Z
|
2022-02-17T06:17:21.000Z
|
api/chalicelib/core/insights.py
|
tares003/openreplay
|
098a0675286710f261425a2aece51644c86e1900
|
[
"MIT"
] | null | null | null |
api/chalicelib/core/insights.py
|
tares003/openreplay
|
098a0675286710f261425a2aece51644c86e1900
|
[
"MIT"
] | null | null | null |
import schemas
from chalicelib.core import sessions_metas
from chalicelib.utils import helper, dev
from chalicelib.utils import pg_client
from chalicelib.utils.TimeUTC import TimeUTC
from chalicelib.utils.metrics_helper import __get_step_size
import math
from chalicelib.core.dashboard import __get_constraints, __get_constraint_values
def __transform_journey(rows):
nodes = []
links = []
for r in rows:
source = r["source_event"][r["source_event"].index("_") + 1:]
target = r["target_event"][r["target_event"].index("_") + 1:]
if source not in nodes:
nodes.append(source)
if target not in nodes:
nodes.append(target)
links.append({"source": nodes.index(source), "target": nodes.index(target), "value": r["value"]})
return {"nodes": nodes, "links": sorted(links, key=lambda x: x["value"], reverse=True)}
JOURNEY_DEPTH = 5
JOURNEY_TYPES = {
"PAGES": {"table": "events.pages", "column": "base_path", "table_id": "message_id"},
"CLICK": {"table": "events.clicks", "column": "label", "table_id": "message_id"},
# "VIEW": {"table": "events_ios.views", "column": "name", "table_id": "seq_index"}, TODO: enable this for SAAS only
"EVENT": {"table": "events_common.customs", "column": "name", "table_id": "seq_index"}
}
@dev.timed
def journey(project_id, startTimestamp=TimeUTC.now(delta_days=-1), endTimestamp=TimeUTC.now(), filters=[], **args):
pg_sub_query_subset = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
event_start = None
event_table = JOURNEY_TYPES["PAGES"]["table"]
event_column = JOURNEY_TYPES["PAGES"]["column"]
event_table_id = JOURNEY_TYPES["PAGES"]["table_id"]
extra_values = {}
for f in filters:
if f["type"] == "START_POINT":
event_start = f["value"]
elif f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_table = JOURNEY_TYPES[f["value"]]["table"]
event_column = JOURNEY_TYPES[f["value"]]["column"]
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query_subset.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT source_event,
target_event,
count(*) AS value
FROM (SELECT event_number || '_' || value as target_event,
LAG(event_number || '_' || value, 1) OVER ( PARTITION BY session_rank ) AS source_event
FROM (SELECT value,
session_rank,
message_id,
ROW_NUMBER() OVER ( PARTITION BY session_rank ORDER BY timestamp ) AS event_number
{f"FROM (SELECT * FROM (SELECT *, MIN(mark) OVER ( PARTITION BY session_id , session_rank ORDER BY timestamp ) AS max FROM (SELECT *, CASE WHEN value = %(event_start)s THEN timestamp ELSE NULL END as mark"
if event_start else ""}
FROM (SELECT session_id,
message_id,
timestamp,
value,
SUM(new_session) OVER (ORDER BY session_id, timestamp) AS session_rank
FROM (SELECT *,
CASE
WHEN source_timestamp IS NULL THEN 1
ELSE 0 END AS new_session
FROM (SELECT session_id,
{event_table_id} AS message_id,
timestamp,
{event_column} AS value,
LAG(timestamp)
OVER (PARTITION BY session_id ORDER BY timestamp) AS source_timestamp
FROM {event_table} INNER JOIN public.sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query_subset)}
) AS related_events) AS ranked_events) AS processed
{") AS marked) AS maxed WHERE timestamp >= max) AS filtered" if event_start else ""}
) AS sorted_events
WHERE event_number <= %(JOURNEY_DEPTH)s) AS final
WHERE source_event IS NOT NULL
and target_event IS NOT NULL
GROUP BY source_event, target_event
ORDER BY value DESC
LIMIT 20;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, "event_start": event_start, "JOURNEY_DEPTH": JOURNEY_DEPTH,
**__get_constraint_values(args), **extra_values}
# print(cur.mogrify(pg_query, params))
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
return __transform_journey(rows)
def __compute_weekly_percentage(rows):
if rows is None or len(rows) == 0:
return rows
t = -1
for r in rows:
if r["week"] == 0:
t = r["usersCount"]
r["percentage"] = r["usersCount"] / t
return rows
def __complete_retention(rows, start_date, end_date=None):
if rows is None:
return []
max_week = 10
for i in range(max_week):
if end_date is not None and start_date + i * TimeUTC.MS_WEEK >= end_date:
break
neutral = {
"firstConnexionWeek": start_date,
"week": i,
"usersCount": 0,
"connectedUsers": [],
"percentage": 0
}
if i < len(rows) \
and i != rows[i]["week"]:
rows.insert(i, neutral)
elif i >= len(rows):
rows.append(neutral)
return rows
def __complete_acquisition(rows, start_date, end_date=None):
if rows is None:
return []
max_week = 10
week = 0
delta_date = 0
while max_week > 0:
start_date += TimeUTC.MS_WEEK
if end_date is not None and start_date >= end_date:
break
delta = 0
if delta_date + week >= len(rows) \
or delta_date + week < len(rows) and rows[delta_date + week]["firstConnexionWeek"] > start_date:
for i in range(max_week):
if end_date is not None and start_date + i * TimeUTC.MS_WEEK >= end_date:
break
neutral = {
"firstConnexionWeek": start_date,
"week": i,
"usersCount": 0,
"connectedUsers": [],
"percentage": 0
}
rows.insert(delta_date + week + i, neutral)
delta = i
else:
for i in range(max_week):
if end_date is not None and start_date + i * TimeUTC.MS_WEEK >= end_date:
break
neutral = {
"firstConnexionWeek": start_date,
"week": i,
"usersCount": 0,
"connectedUsers": [],
"percentage": 0
}
if delta_date + week + i < len(rows) \
and i != rows[delta_date + week + i]["week"]:
rows.insert(delta_date + week + i, neutral)
elif delta_date + week + i >= len(rows):
rows.append(neutral)
delta = i
week += delta
max_week -= 1
delta_date += 1
return rows
@dev.timed
def users_retention(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(), filters=[],
**args):
startTimestamp = TimeUTC.trunc_week(startTimestamp)
endTimestamp = startTimestamp + 10 * TimeUTC.MS_WEEK
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
pg_sub_query.append("user_id IS NOT NULL")
pg_sub_query.append("DATE_TRUNC('week', to_timestamp(start_ts / 1000)) = to_timestamp(%(startTimestamp)s / 1000)")
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT FLOOR(DATE_PART('day', connexion_week - DATE_TRUNC('week', to_timestamp(%(startTimestamp)s / 1000)::timestamp)) / 7)::integer AS week,
COUNT(DISTINCT connexions_list.user_id) AS users_count,
ARRAY_AGG(DISTINCT connexions_list.user_id) AS connected_users
FROM (SELECT DISTINCT user_id
FROM sessions
WHERE {" AND ".join(pg_sub_query)}
AND DATE_PART('week', to_timestamp((sessions.start_ts - %(startTimestamp)s)/1000)) = 1
AND NOT EXISTS((SELECT 1
FROM sessions AS bsess
WHERE bsess.start_ts < %(startTimestamp)s
AND project_id = %(project_id)s
AND bsess.user_id = sessions.user_id
LIMIT 1))
) AS users_list
LEFT JOIN LATERAL (SELECT DATE_TRUNC('week', to_timestamp(start_ts / 1000)::timestamp) AS connexion_week,
user_id
FROM sessions
WHERE users_list.user_id = sessions.user_id
AND %(startTimestamp)s <=sessions.start_ts
AND sessions.project_id = %(project_id)s
AND sessions.start_ts < (%(endTimestamp)s - 1)
GROUP BY connexion_week, user_id
) AS connexions_list ON (TRUE)
GROUP BY week
ORDER BY week;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args)}
print(cur.mogrify(pg_query, params))
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
rows = __compute_weekly_percentage(helper.list_to_camel_case(rows))
return {
"startTimestamp": startTimestamp,
"chart": __complete_retention(rows=rows, start_date=startTimestamp, end_date=TimeUTC.now())
}
@dev.timed
def users_acquisition(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[],
**args):
startTimestamp = TimeUTC.trunc_week(startTimestamp)
endTimestamp = startTimestamp + 10 * TimeUTC.MS_WEEK
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
pg_sub_query.append("user_id IS NOT NULL")
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT EXTRACT(EPOCH FROM first_connexion_week::date)::bigint*1000 AS first_connexion_week,
FLOOR(DATE_PART('day', connexion_week - first_connexion_week) / 7)::integer AS week,
COUNT(DISTINCT connexions_list.user_id) AS users_count,
ARRAY_AGG(DISTINCT connexions_list.user_id) AS connected_users
FROM (SELECT user_id, MIN(DATE_TRUNC('week', to_timestamp(start_ts / 1000))) AS first_connexion_week
FROM sessions
WHERE {" AND ".join(pg_sub_query)}
AND NOT EXISTS((SELECT 1
FROM sessions AS bsess
WHERE bsess.start_ts<%(startTimestamp)s
AND project_id = %(project_id)s
AND bsess.user_id = sessions.user_id
LIMIT 1))
GROUP BY user_id) AS users_list
LEFT JOIN LATERAL (SELECT DATE_TRUNC('week', to_timestamp(start_ts / 1000)::timestamp) AS connexion_week,
user_id
FROM sessions
WHERE users_list.user_id = sessions.user_id
AND first_connexion_week <=
DATE_TRUNC('week', to_timestamp(sessions.start_ts / 1000)::timestamp)
AND sessions.project_id = %(project_id)s
AND sessions.start_ts < (%(endTimestamp)s - 1)
GROUP BY connexion_week, user_id) AS connexions_list ON (TRUE)
GROUP BY first_connexion_week, week
ORDER BY first_connexion_week, week;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args)}
print(cur.mogrify(pg_query, params))
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
rows = __compute_weekly_percentage(helper.list_to_camel_case(rows))
return {
"startTimestamp": startTimestamp,
"chart": __complete_acquisition(rows=rows, start_date=startTimestamp, end_date=TimeUTC.now())
}
@dev.timed
def feature_retention(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[],
**args):
startTimestamp = TimeUTC.trunc_week(startTimestamp)
endTimestamp = startTimestamp + 10 * TimeUTC.MS_WEEK
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
pg_sub_query.append("user_id IS NOT NULL")
pg_sub_query.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query.append("feature.timestamp < %(endTimestamp)s")
event_type = "PAGES"
event_value = "/"
extra_values = {}
default = True
for f in filters:
if f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_type = f["value"]
elif f["type"] == "EVENT_VALUE":
event_value = f["value"]
default = False
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
event_table = JOURNEY_TYPES[event_type]["table"]
event_column = JOURNEY_TYPES[event_type]["column"]
pg_sub_query.append(f"feature.{event_column} = %(value)s")
with pg_client.PostgresClient() as cur:
if default:
# get most used value
pg_query = f"""SELECT {event_column} AS value, COUNT(*) AS count
FROM {event_table} AS feature INNER JOIN public.sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query[:-1])}
AND length({event_column}) > 2
GROUP BY value
ORDER BY count DESC
LIMIT 1;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
cur.execute(cur.mogrify(pg_query, params))
row = cur.fetchone()
if row is not None:
event_value = row["value"]
extra_values["value"] = event_value
if len(event_value) > 2:
pg_sub_query.append(f"length({event_column})>2")
pg_query = f"""SELECT FLOOR(DATE_PART('day', connexion_week - to_timestamp(%(startTimestamp)s/1000)) / 7)::integer AS week,
COUNT(DISTINCT connexions_list.user_id) AS users_count,
ARRAY_AGG(DISTINCT connexions_list.user_id) AS connected_users
FROM (SELECT DISTINCT user_id
FROM sessions INNER JOIN {event_table} AS feature USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
AND DATE_PART('week', to_timestamp((sessions.start_ts - %(startTimestamp)s)/1000)) = 1
AND NOT EXISTS((SELECT 1
FROM sessions AS bsess INNER JOIN {event_table} AS bfeature USING (session_id)
WHERE bsess.start_ts<%(startTimestamp)s
AND project_id = %(project_id)s
AND bsess.user_id = sessions.user_id
AND bfeature.timestamp<%(startTimestamp)s
AND bfeature.{event_column}=%(value)s
LIMIT 1))
GROUP BY user_id) AS users_list
LEFT JOIN LATERAL (SELECT DATE_TRUNC('week', to_timestamp(start_ts / 1000)::timestamp) AS connexion_week,
user_id
FROM sessions INNER JOIN {event_table} AS feature USING (session_id)
WHERE users_list.user_id = sessions.user_id
AND %(startTimestamp)s <= sessions.start_ts
AND sessions.project_id = %(project_id)s
AND sessions.start_ts < (%(endTimestamp)s - 1)
AND feature.timestamp >= %(startTimestamp)s
AND feature.timestamp < %(endTimestamp)s
AND feature.{event_column} = %(value)s
GROUP BY connexion_week, user_id) AS connexions_list ON (TRUE)
GROUP BY week
ORDER BY week;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
print(cur.mogrify(pg_query, params))
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
rows = __compute_weekly_percentage(helper.list_to_camel_case(rows))
return {
"startTimestamp": startTimestamp,
"filters": [{"type": "EVENT_TYPE", "value": event_type}, {"type": "EVENT_VALUE", "value": event_value}],
"chart": __complete_retention(rows=rows, start_date=startTimestamp, end_date=TimeUTC.now())
}
@dev.timed
def feature_acquisition(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[],
**args):
startTimestamp = TimeUTC.trunc_week(startTimestamp)
endTimestamp = startTimestamp + 10 * TimeUTC.MS_WEEK
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
pg_sub_query.append("user_id IS NOT NULL")
pg_sub_query.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query.append("feature.timestamp < %(endTimestamp)s")
event_type = "PAGES"
event_value = "/"
extra_values = {}
default = True
for f in filters:
if f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_type = f["value"]
elif f["type"] == "EVENT_VALUE":
event_value = f["value"]
default = False
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
event_table = JOURNEY_TYPES[event_type]["table"]
event_column = JOURNEY_TYPES[event_type]["column"]
pg_sub_query.append(f"feature.{event_column} = %(value)s")
with pg_client.PostgresClient() as cur:
if default:
# get most used value
pg_query = f"""SELECT {event_column} AS value, COUNT(*) AS count
FROM {event_table} AS feature INNER JOIN public.sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query[:-1])}
AND length({event_column}) > 2
GROUP BY value
ORDER BY count DESC
LIMIT 1;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
cur.execute(cur.mogrify(pg_query, params))
row = cur.fetchone()
if row is not None:
event_value = row["value"]
extra_values["value"] = event_value
if len(event_value) > 2:
pg_sub_query.append(f"length({event_column})>2")
pg_query = f"""SELECT EXTRACT(EPOCH FROM first_connexion_week::date)::bigint*1000 AS first_connexion_week,
FLOOR(DATE_PART('day', connexion_week - first_connexion_week) / 7)::integer AS week,
COUNT(DISTINCT connexions_list.user_id) AS users_count,
ARRAY_AGG(DISTINCT connexions_list.user_id) AS connected_users
FROM (SELECT user_id, DATE_TRUNC('week', to_timestamp(first_connexion_week / 1000)) AS first_connexion_week
FROM(SELECT DISTINCT user_id, MIN(start_ts) AS first_connexion_week
FROM sessions INNER JOIN {event_table} AS feature USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
AND NOT EXISTS((SELECT 1
FROM sessions AS bsess INNER JOIN {event_table} AS bfeature USING (session_id)
WHERE bsess.start_ts<%(startTimestamp)s
AND project_id = %(project_id)s
AND bsess.user_id = sessions.user_id
AND bfeature.timestamp<%(startTimestamp)s
AND bfeature.{event_column}=%(value)s
LIMIT 1))
GROUP BY user_id) AS raw_users_list) AS users_list
LEFT JOIN LATERAL (SELECT DATE_TRUNC('week', to_timestamp(start_ts / 1000)::timestamp) AS connexion_week,
user_id
FROM sessions INNER JOIN {event_table} AS feature USING(session_id)
WHERE users_list.user_id = sessions.user_id
AND first_connexion_week <=
DATE_TRUNC('week', to_timestamp(sessions.start_ts / 1000)::timestamp)
AND sessions.project_id = %(project_id)s
AND sessions.start_ts < (%(endTimestamp)s - 1)
AND feature.timestamp >= %(startTimestamp)s
AND feature.timestamp < %(endTimestamp)s
AND feature.{event_column} = %(value)s
GROUP BY connexion_week, user_id) AS connexions_list ON (TRUE)
GROUP BY first_connexion_week, week
ORDER BY first_connexion_week, week;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
print(cur.mogrify(pg_query, params))
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
rows = __compute_weekly_percentage(helper.list_to_camel_case(rows))
return {
"startTimestamp": startTimestamp,
"filters": [{"type": "EVENT_TYPE", "value": event_type}, {"type": "EVENT_VALUE", "value": event_value}],
"chart": __complete_acquisition(rows=rows, start_date=startTimestamp, end_date=TimeUTC.now())
}
@dev.timed
def feature_popularity_frequency(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[],
**args):
startTimestamp = TimeUTC.trunc_week(startTimestamp)
endTimestamp = startTimestamp + 10 * TimeUTC.MS_WEEK
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
event_table = JOURNEY_TYPES["CLICK"]["table"]
event_column = JOURNEY_TYPES["CLICK"]["column"]
extra_values = {}
for f in filters:
if f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_table = JOURNEY_TYPES[f["value"]]["table"]
event_column = JOURNEY_TYPES[f["value"]]["column"]
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT COUNT(DISTINCT user_id) AS count
FROM sessions
WHERE {" AND ".join(pg_sub_query)}
AND user_id IS NOT NULL;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
# print(cur.mogrify(pg_query, params))
# print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
all_user_count = cur.fetchone()["count"]
if all_user_count == 0:
return []
pg_sub_query.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query.append("feature.timestamp < %(endTimestamp)s")
pg_sub_query.append(f"length({event_column})>2")
pg_query = f"""SELECT {event_column} AS value, COUNT(DISTINCT user_id) AS count
FROM {event_table} AS feature INNER JOIN sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
AND user_id IS NOT NULL
GROUP BY value
ORDER BY count DESC
LIMIT 7;"""
# TODO: solve full scan
print(cur.mogrify(pg_query, params))
print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
popularity = cur.fetchall()
pg_query = f"""SELECT {event_column} AS value, COUNT(session_id) AS count
FROM {event_table} AS feature INNER JOIN sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
GROUP BY value;"""
# TODO: solve full scan
print(cur.mogrify(pg_query, params))
print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
frequencies = cur.fetchall()
total_usage = sum([f["count"] for f in frequencies])
frequencies = {f["value"]: f["count"] for f in frequencies}
for p in popularity:
p["popularity"] = p.pop("count") / all_user_count
p["frequency"] = frequencies[p["value"]] / total_usage
return popularity
@dev.timed
def feature_adoption(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[],
**args):
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
event_type = "CLICK"
event_value = '/'
extra_values = {}
default = True
for f in filters:
if f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_type = f["value"]
elif f["type"] == "EVENT_VALUE":
event_value = f["value"]
default = False
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
event_table = JOURNEY_TYPES[event_type]["table"]
event_column = JOURNEY_TYPES[event_type]["column"]
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT COUNT(DISTINCT user_id) AS count
FROM sessions
WHERE {" AND ".join(pg_sub_query)}
AND user_id IS NOT NULL;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
# print(cur.mogrify(pg_query, params))
# print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
all_user_count = cur.fetchone()["count"]
if all_user_count == 0:
return {"adoption": 0, "target": 0, "filters": [{"type": "EVENT_TYPE", "value": event_type},
{"type": "EVENT_VALUE", "value": event_value}], }
pg_sub_query.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query.append("feature.timestamp < %(endTimestamp)s")
if default:
# get most used value
pg_query = f"""SELECT {event_column} AS value, COUNT(*) AS count
FROM {event_table} AS feature INNER JOIN public.sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query[:-1])}
AND length({event_column}) > 2
GROUP BY value
ORDER BY count DESC
LIMIT 1;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
cur.execute(cur.mogrify(pg_query, params))
row = cur.fetchone()
if row is not None:
event_value = row["value"]
extra_values["value"] = event_value
if len(event_value) > 2:
pg_sub_query.append(f"length({event_column})>2")
pg_sub_query.append(f"feature.{event_column} = %(value)s")
pg_query = f"""SELECT COUNT(DISTINCT user_id) AS count
FROM {event_table} AS feature INNER JOIN sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
AND user_id IS NOT NULL;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
# print(cur.mogrify(pg_query, params))
# print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
adoption = cur.fetchone()["count"] / all_user_count
return {"target": all_user_count, "adoption": adoption,
"filters": [{"type": "EVENT_TYPE", "value": event_type}, {"type": "EVENT_VALUE", "value": event_value}]}
@dev.timed
def feature_adoption_top_users(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[], **args):
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
pg_sub_query.append("user_id IS NOT NULL")
event_type = "CLICK"
event_value = '/'
extra_values = {}
default = True
for f in filters:
if f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_type = f["value"]
elif f["type"] == "EVENT_VALUE":
event_value = f["value"]
default = False
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
event_table = JOURNEY_TYPES[event_type]["table"]
event_column = JOURNEY_TYPES[event_type]["column"]
with pg_client.PostgresClient() as cur:
pg_sub_query.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query.append("feature.timestamp < %(endTimestamp)s")
if default:
# get most used value
pg_query = f"""SELECT {event_column} AS value, COUNT(*) AS count
FROM {event_table} AS feature INNER JOIN public.sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query[:-1])}
AND length({event_column}) > 2
GROUP BY value
ORDER BY count DESC
LIMIT 1;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
cur.execute(cur.mogrify(pg_query, params))
row = cur.fetchone()
if row is not None:
event_value = row["value"]
extra_values["value"] = event_value
if len(event_value) > 2:
pg_sub_query.append(f"length({event_column})>2")
pg_sub_query.append(f"feature.{event_column} = %(value)s")
pg_query = f"""SELECT user_id, COUNT(DISTINCT session_id) AS count
FROM {event_table} AS feature
INNER JOIN sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
GROUP BY 1
ORDER BY 2 DESC
LIMIT 10;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
# print(cur.mogrify(pg_query, params))
# print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
return {"users": helper.list_to_camel_case(rows),
"filters": [{"type": "EVENT_TYPE", "value": event_type}, {"type": "EVENT_VALUE", "value": event_value}]}
@dev.timed
def feature_adoption_daily_usage(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[], **args):
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
pg_sub_query_chart = __get_constraints(project_id=project_id, time_constraint=True,
chart=True, data=args)
event_type = "CLICK"
event_value = '/'
extra_values = {}
default = True
for f in filters:
if f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_type = f["value"]
elif f["type"] == "EVENT_VALUE":
event_value = f["value"]
default = False
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query_chart.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
event_table = JOURNEY_TYPES[event_type]["table"]
event_column = JOURNEY_TYPES[event_type]["column"]
with pg_client.PostgresClient() as cur:
pg_sub_query_chart.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query_chart.append("feature.timestamp < %(endTimestamp)s")
pg_sub_query.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query.append("feature.timestamp < %(endTimestamp)s")
if default:
# get most used value
pg_query = f"""SELECT {event_column} AS value, COUNT(*) AS count
FROM {event_table} AS feature INNER JOIN public.sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
AND length({event_column})>2
GROUP BY value
ORDER BY count DESC
LIMIT 1;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
cur.execute(cur.mogrify(pg_query, params))
row = cur.fetchone()
if row is not None:
event_value = row["value"]
extra_values["value"] = event_value
if len(event_value) > 2:
pg_sub_query.append(f"length({event_column})>2")
pg_sub_query_chart.append(f"feature.{event_column} = %(value)s")
pg_query = f"""SELECT generated_timestamp AS timestamp,
COALESCE(COUNT(session_id), 0) AS count
FROM generate_series(%(startTimestamp)s, %(endTimestamp)s, %(step_size)s) AS generated_timestamp
LEFT JOIN LATERAL ( SELECT DISTINCT session_id
FROM {event_table} AS feature INNER JOIN public.sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query_chart)}
) AS users ON (TRUE)
GROUP BY generated_timestamp
ORDER BY generated_timestamp;"""
params = {"step_size": TimeUTC.MS_DAY, "project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
print(cur.mogrify(pg_query, params))
print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
return {"chart": helper.list_to_camel_case(rows),
"filters": [{"type": "EVENT_TYPE", "value": event_type}, {"type": "EVENT_VALUE", "value": event_value}]}
@dev.timed
def feature_intensity(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[],
**args):
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
pg_sub_query.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query.append("feature.timestamp < %(endTimestamp)s")
event_table = JOURNEY_TYPES["CLICK"]["table"]
event_column = JOURNEY_TYPES["CLICK"]["column"]
extra_values = {}
for f in filters:
if f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_table = JOURNEY_TYPES[f["value"]]["table"]
event_column = JOURNEY_TYPES[f["value"]]["column"]
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
pg_sub_query.append(f"length({event_column})>2")
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT {event_column} AS value, AVG(DISTINCT session_id) AS avg
FROM {event_table} AS feature INNER JOIN sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
GROUP BY value
ORDER BY avg DESC
LIMIT 7;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
# TODO: solve full scan issue
print(cur.mogrify(pg_query, params))
print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
return rows
@dev.timed
def users_active(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[],
**args):
pg_sub_query_chart = __get_constraints(project_id=project_id, time_constraint=True,
chart=True, data=args)
pg_sub_query_chart.append("user_id IS NOT NULL")
period = "DAY"
extra_values = {}
for f in filters:
if f["type"] == "PERIOD" and f["value"] in ["DAY", "WEEK"]:
period = f["value"]
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query_chart.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT AVG(count) AS avg, JSONB_AGG(chart) AS chart
FROM (SELECT generated_timestamp AS timestamp,
COALESCE(COUNT(users), 0) AS count
FROM generate_series(%(startTimestamp)s, %(endTimestamp)s, %(step_size)s) AS generated_timestamp
LEFT JOIN LATERAL ( SELECT DISTINCT user_id
FROM public.sessions
WHERE {" AND ".join(pg_sub_query_chart)}
) AS users ON (TRUE)
GROUP BY generated_timestamp
ORDER BY generated_timestamp) AS chart;"""
params = {"step_size": TimeUTC.MS_DAY if period == "DAY" else TimeUTC.MS_WEEK,
"project_id": project_id,
"startTimestamp": TimeUTC.trunc_day(startTimestamp) if period == "DAY" else TimeUTC.trunc_week(
startTimestamp),
"endTimestamp": endTimestamp, **__get_constraint_values(args),
**extra_values}
# print(cur.mogrify(pg_query, params))
# print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
row_users = cur.fetchone()
return row_users
@dev.timed
def users_power(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[], **args):
pg_sub_query = __get_constraints(project_id=project_id, time_constraint=True, chart=False, data=args)
pg_sub_query.append("user_id IS NOT NULL")
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT AVG(count) AS avg, JSONB_AGG(day_users_partition) AS partition
FROM (SELECT number_of_days, COUNT(user_id) AS count
FROM (SELECT user_id, COUNT(DISTINCT DATE_TRUNC('day', to_timestamp(start_ts / 1000))) AS number_of_days
FROM sessions
WHERE {" AND ".join(pg_sub_query)}
GROUP BY 1) AS users_connexions
GROUP BY number_of_days
ORDER BY number_of_days) AS day_users_partition;"""
params = {"project_id": project_id,
"startTimestamp": startTimestamp, "endTimestamp": endTimestamp, **__get_constraint_values(args)}
# print(cur.mogrify(pg_query, params))
# print("---------------------")
cur.execute(cur.mogrify(pg_query, params))
row_users = cur.fetchone()
return helper.dict_to_camel_case(row_users)
@dev.timed
def users_slipping(project_id, startTimestamp=TimeUTC.now(delta_days=-70), endTimestamp=TimeUTC.now(),
filters=[], **args):
pg_sub_query = __get_constraints(project_id=project_id, data=args, duration=True, main_table="sessions",
time_constraint=True)
pg_sub_query.append("user_id IS NOT NULL")
pg_sub_query.append("feature.timestamp >= %(startTimestamp)s")
pg_sub_query.append("feature.timestamp < %(endTimestamp)s")
event_type = "PAGES"
event_value = "/"
extra_values = {}
default = True
for f in filters:
if f["type"] == "EVENT_TYPE" and JOURNEY_TYPES.get(f["value"]):
event_type = f["value"]
elif f["type"] == "EVENT_VALUE":
event_value = f["value"]
default = False
elif f["type"] in [schemas.FilterType.user_id, schemas.FilterType.user_id_ios]:
pg_sub_query.append(f"sessions.user_id = %(user_id)s")
extra_values["user_id"] = f["value"]
event_table = JOURNEY_TYPES[event_type]["table"]
event_column = JOURNEY_TYPES[event_type]["column"]
pg_sub_query.append(f"feature.{event_column} = %(value)s")
with pg_client.PostgresClient() as cur:
if default:
# get most used value
pg_query = f"""SELECT {event_column} AS value, COUNT(*) AS count
FROM {event_table} AS feature INNER JOIN public.sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query[:-1])}
AND length({event_column}) > 2
GROUP BY value
ORDER BY count DESC
LIMIT 1;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
cur.execute(cur.mogrify(pg_query, params))
row = cur.fetchone()
if row is not None:
event_value = row["value"]
extra_values["value"] = event_value
if len(event_value) > 2:
pg_sub_query.append(f"length({event_column})>2")
pg_query = f"""SELECT user_id, last_time, interactions_count, MIN(start_ts) AS first_seen, MAX(start_ts) AS last_seen
FROM (SELECT user_id, MAX(timestamp) AS last_time, COUNT(DISTINCT session_id) AS interactions_count
FROM {event_table} AS feature INNER JOIN sessions USING (session_id)
WHERE {" AND ".join(pg_sub_query)}
GROUP BY user_id) AS user_last_usage
INNER JOIN sessions USING (user_id)
WHERE EXTRACT(EPOCH FROM now()) * 1000 - last_time > 7 * 24 * 60 * 60 * 1000
GROUP BY user_id, last_time,interactions_count;"""
params = {"project_id": project_id, "startTimestamp": startTimestamp,
"endTimestamp": endTimestamp, **__get_constraint_values(args), **extra_values}
# print(cur.mogrify(pg_query, params))
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
return {
"startTimestamp": startTimestamp,
"filters": [{"type": "EVENT_TYPE", "value": event_type}, {"type": "EVENT_VALUE", "value": event_value}],
"list": helper.list_to_camel_case(rows)
}
@dev.timed
def search(text, feature_type, project_id, platform=None):
if not feature_type:
resource_type = "ALL"
data = search(text=text, feature_type=resource_type, project_id=project_id, platform=platform)
return data
pg_sub_query = __get_constraints(project_id=project_id, time_constraint=True, duration=True,
data={} if platform is None else {"platform": platform})
params = {"startTimestamp": TimeUTC.now() - 2 * TimeUTC.MS_MONTH,
"endTimestamp": TimeUTC.now(),
"project_id": project_id,
"value": helper.string_to_sql_like(text.lower()),
"platform_0": platform}
if feature_type == "ALL":
with pg_client.PostgresClient() as cur:
sub_queries = []
for e in JOURNEY_TYPES:
sub_queries.append(f"""(SELECT DISTINCT {JOURNEY_TYPES[e]["column"]} AS value, '{e}' AS "type"
FROM {JOURNEY_TYPES[e]["table"]} INNER JOIN public.sessions USING(session_id)
WHERE {" AND ".join(pg_sub_query)} AND {JOURNEY_TYPES[e]["column"]} ILIKE %(value)s
LIMIT 10)""")
pg_query = "UNION ALL".join(sub_queries)
# print(cur.mogrify(pg_query, params))
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
elif JOURNEY_TYPES.get(feature_type) is not None:
with pg_client.PostgresClient() as cur:
pg_query = f"""SELECT DISTINCT {JOURNEY_TYPES[feature_type]["column"]} AS value, '{feature_type}' AS "type"
FROM {JOURNEY_TYPES[feature_type]["table"]} INNER JOIN public.sessions USING(session_id)
WHERE {" AND ".join(pg_sub_query)} AND {JOURNEY_TYPES[feature_type]["column"]} ILIKE %(value)s
LIMIT 10;"""
# print(cur.mogrify(pg_query, params))
cur.execute(cur.mogrify(pg_query, params))
rows = cur.fetchall()
else:
return []
return [helper.dict_to_camel_case(row) for row in rows]
| 55.438371
| 241
| 0.536095
| 5,496
| 51,724
| 4.789665
| 0.046761
| 0.026212
| 0.034189
| 0.03077
| 0.863053
| 0.837145
| 0.808502
| 0.797485
| 0.789014
| 0.777389
| 0
| 0.006423
| 0.358866
| 51,724
| 933
| 242
| 55.438371
| 0.787377
| 0.016646
| 0
| 0.744958
| 0
| 0.007117
| 0.491709
| 0.054586
| 0
| 0
| 0
| 0.001072
| 0
| 1
| 0.021352
| false
| 0
| 0.00949
| 0
| 0.060498
| 0.014235
| 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
|
3e95b14dfcc25d672e1ccc7f070abf8dfced66df
| 817
|
py
|
Python
|
ex009.py
|
CarlosEduardoAS/Python-exercicios
|
c0063660191a86e83f25708239b62b6764a51670
|
[
"MIT"
] | null | null | null |
ex009.py
|
CarlosEduardoAS/Python-exercicios
|
c0063660191a86e83f25708239b62b6764a51670
|
[
"MIT"
] | null | null | null |
ex009.py
|
CarlosEduardoAS/Python-exercicios
|
c0063660191a86e83f25708239b62b6764a51670
|
[
"MIT"
] | null | null | null |
n = int(input('Digite um número inteiro: '))
print('A tabuada de \033[1;30m{}\033[m é:'.format(n))
print('\033[1;30;41m {} x 1 = \033[1;30;45m {} \033[m'.format(n, n))
print('\033[1;30;41m {} x 2 = \033[1;30;45m {} \033[m'.format(n, n*2))
print('\033[1;30;41m {} x 3 = \033[1;30;45m {} \033[m'.format(n, n*3))
print('\033[1;30;41m {} x 4 = \033[1;30;45m {} \033[m'.format(n, n*4))
print('\033[1;30;41m {} x 5 = \033[1;30;45m {} \033[m'.format(n, n*5))
print('\033[1;30;41m {} x 6 = \033[1;30;45m {} \033[m'.format(n, n*6))
print('\033[1;30;41m {} x 7 = \033[1;30;45m {} \033[m'.format(n, n*7))
print('\033[1;30;41m {} x 8 = \033[1;30;45m {} \033[m'.format(n, n*8))
print('\033[1;30;41m {} x 9 = \033[1;30;45m {} \033[m'.format(n, n*9))
print('\033[1;30;41m {} x 10 = \033[1;30;45m {} \033[m'.format(n, n*10))
| 68.083333
| 72
| 0.544676
| 188
| 817
| 2.367021
| 0.159574
| 0.188764
| 0.269663
| 0.247191
| 0.811236
| 0.811236
| 0.541573
| 0.47191
| 0.47191
| 0
| 0
| 0.311174
| 0.134639
| 817
| 12
| 72
| 68.083333
| 0.318246
| 0
| 0
| 0
| 0
| 0.833333
| 0.647922
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.916667
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 9
|
3ea6753152671030a9baeaa545db9661cba3da89
| 2,525
|
py
|
Python
|
skidl/libs/graphic_sklib.py
|
arjenroodselaar/skidl
|
0bf801bd3b74e6ef94bd9aa1b68eef756b568276
|
[
"MIT"
] | 700
|
2016-08-16T21:12:50.000Z
|
2021-10-10T02:15:18.000Z
|
skidl/libs/graphic_sklib.py
|
0dvictor/skidl
|
458709a10b28a864d25ae2c2b44c6103d4ddb291
|
[
"MIT"
] | 118
|
2016-08-16T20:51:05.000Z
|
2021-10-10T08:07:18.000Z
|
skidl/libs/graphic_sklib.py
|
0dvictor/skidl
|
458709a10b28a864d25ae2c2b44c6103d4ddb291
|
[
"MIT"
] | 94
|
2016-08-25T14:02:28.000Z
|
2021-09-12T05:17:08.000Z
|
from skidl import SKIDL, TEMPLATE, Part, Pin, SchLib
SKIDL_lib_version = '0.0.1'
graphic = SchLib(tool=SKIDL).add_parts(*[
Part(name='ARROW1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='ARROW2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='ARROW3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='ARROW4',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='BOX1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='BOX2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='BOX3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='BOX4',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='C1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='CIRCLE1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='CIRCLE2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='CIRCLE3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='CIRCLE4',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='DIAMOND1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='DIAMOND2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='DIAMOND3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='DIAMOND4',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FARROW1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FARROW2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FARROW3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FARROW4',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FBOX1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FBOX2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FBOX3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FBOX4',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FDIAMOND1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FDIAMOND2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FDIAMOND3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FDIAMOND4',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FSQUARE1',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FSQUARE2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FSQUARE3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='FSQUARE4',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='SQUARE2',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='SQUARE3',dest=TEMPLATE,tool=SKIDL,do_erc=True),
Part(name='SQUARE4',dest=TEMPLATE,tool=SKIDL,do_erc=True)])
| 60.119048
| 68
| 0.687129
| 380
| 2,525
| 4.463158
| 0.147368
| 0.196344
| 0.339623
| 0.445755
| 0.801887
| 0.801887
| 0.801887
| 0.784198
| 0.784198
| 0
| 0
| 0.017849
| 0.134653
| 2,525
| 41
| 69
| 61.585366
| 0.758352
| 0
| 0
| 0
| 0
| 0
| 0.096634
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.025641
| 0
| 0.025641
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 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
|
3eae15a010e6ceef0a63537aace2f3534b5adb7a
| 95
|
py
|
Python
|
exercícios/EX_CursoEmVideo/ex037.py
|
jose-carlos-code/CursoEmvideo-python
|
8c9b82db2c2b906f6d8f2359a680b9b3af25da43
|
[
"MIT"
] | 1
|
2021-01-11T15:10:36.000Z
|
2021-01-11T15:10:36.000Z
|
exercícios/EX_CursoEmVideo/ex037.py
|
jose-carlos-code/CursoEmvideo-python
|
8c9b82db2c2b906f6d8f2359a680b9b3af25da43
|
[
"MIT"
] | null | null | null |
exercícios/EX_CursoEmVideo/ex037.py
|
jose-carlos-code/CursoEmvideo-python
|
8c9b82db2c2b906f6d8f2359a680b9b3af25da43
|
[
"MIT"
] | null | null | null |
a = 3
b = 5
print ('os valores sao \033[1;31;45m{}\033[m e \033[1;32;46m{}\033[m'.format(a, b))
| 31.666667
| 83
| 0.589474
| 24
| 95
| 2.333333
| 0.708333
| 0.142857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.292683
| 0.136842
| 95
| 3
| 83
| 31.666667
| 0.390244
| 0
| 0
| 0
| 0
| 0.333333
| 0.625
| 0.4375
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
3eaf89e6be8c6487ef1676e77b8bbfe5a1fa6988
| 36,360
|
py
|
Python
|
python/ngsi_v2/ngsi_v2/api/registrations_api.py
|
orchestracities/sdk
|
9dd1e618d6c013ab916f3880df84c7882f6beec6
|
[
"Apache-2.0"
] | 2
|
2019-12-22T01:01:34.000Z
|
2021-07-03T20:30:03.000Z
|
python/ngsi_v2/ngsi_v2/api/registrations_api.py
|
orchestracities/sdk
|
9dd1e618d6c013ab916f3880df84c7882f6beec6
|
[
"Apache-2.0"
] | 2
|
2019-06-06T05:45:45.000Z
|
2019-06-06T09:03:10.000Z
|
python/ngsi_v2/ngsi_v2/api/registrations_api.py
|
orchestracities/sdk
|
9dd1e618d6c013ab916f3880df84c7882f6beec6
|
[
"Apache-2.0"
] | 2
|
2021-07-03T20:30:06.000Z
|
2021-11-30T21:55:02.000Z
|
# coding: utf-8
"""
ngsi_v2
NGSI V2 API RC-2018.07 # noqa: E501
The version of the OpenAPI document: 0.2.2
Contact: info@orchestracities.com
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from ngsi_v2.api_client import ApiClient
from ngsi_v2.exceptions import (
ApiTypeError,
ApiValueError
)
class RegistrationsApi(object):
"""NOTE: This class is auto generated by OpenAPI Generator
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def create_registrations(self, registration_body, **kwargs): # noqa: E501
"""create_registrations # noqa: E501
Creates a new context provider registration. This is typically used for binding context sources as providers of certain data. The registration is represented by a JSON object as described at the beginning of this section. Response: * Successful operation uses 201 Created * Errors use a non-2xx and (optionally) an error payload. See subsection on [Error Responses](https://fiware.github.io/specifications/ngsiv2/stable) for more details. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_registrations(registration_body, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param RegistrationBody registration_body: (required)
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
return self.create_registrations_with_http_info(registration_body, **kwargs) # noqa: E501
def create_registrations_with_http_info(self, registration_body, **kwargs): # noqa: E501
"""create_registrations # noqa: E501
Creates a new context provider registration. This is typically used for binding context sources as providers of certain data. The registration is represented by a JSON object as described at the beginning of this section. Response: * Successful operation uses 201 Created * Errors use a non-2xx and (optionally) an error payload. See subsection on [Error Responses](https://fiware.github.io/specifications/ngsiv2/stable) for more details. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_registrations_with_http_info(registration_body, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param RegistrationBody registration_body: (required)
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['registration_body', 'fiware_service', 'fiware_service_path'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise ApiTypeError(
"Got an unexpected keyword argument '%s'"
" to method create_registrations" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'registration_body' is set
if ('registration_body' not in local_var_params or
local_var_params['registration_body'] is None):
raise ApiValueError("Missing the required parameter `registration_body` when calling `create_registrations`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
if 'fiware_service' in local_var_params:
header_params['Fiware-Service'] = local_var_params['fiware_service'] # noqa: E501
if 'fiware_service_path' in local_var_params:
header_params['Fiware-ServicePath'] = local_var_params['fiware_service_path'] # noqa: E501
form_params = []
local_var_files = {}
body_params = None
if 'registration_body' in local_var_params:
body_params = local_var_params['registration_body']
# 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']) # noqa: E501
# Authentication setting
auth_settings = ['ApiKeyAuth', 'BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/registrations', '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=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def delete_registration(self, registration_id, **kwargs): # noqa: E501
"""delete_registration # noqa: E501
Cancels a context provider registration. Response: * Successful operation uses 204 No Content * Errors use a non-2xx and (optionally) an error payload. See subsection on [Error Responses](https://fiware.github.io/specifications/ngsiv2/stable) for more details. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_registration(registration_id, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str registration_id: registration Id. (required)
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
return self.delete_registration_with_http_info(registration_id, **kwargs) # noqa: E501
def delete_registration_with_http_info(self, registration_id, **kwargs): # noqa: E501
"""delete_registration # noqa: E501
Cancels a context provider registration. Response: * Successful operation uses 204 No Content * Errors use a non-2xx and (optionally) an error payload. See subsection on [Error Responses](https://fiware.github.io/specifications/ngsiv2/stable) for more details. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_registration_with_http_info(registration_id, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str registration_id: registration Id. (required)
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['registration_id', 'fiware_service', 'fiware_service_path'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise ApiTypeError(
"Got an unexpected keyword argument '%s'"
" to method delete_registration" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'registration_id' is set
if ('registration_id' not in local_var_params or
local_var_params['registration_id'] is None):
raise ApiValueError("Missing the required parameter `registration_id` when calling `delete_registration`") # noqa: E501
collection_formats = {}
path_params = {}
if 'registration_id' in local_var_params:
path_params['registrationId'] = local_var_params['registration_id'] # noqa: E501
query_params = []
header_params = {}
if 'fiware_service' in local_var_params:
header_params['Fiware-Service'] = local_var_params['fiware_service'] # noqa: E501
if 'fiware_service_path' in local_var_params:
header_params['Fiware-ServicePath'] = local_var_params['fiware_service_path'] # noqa: E501
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 = ['ApiKeyAuth', 'BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/registrations/{registrationId}', '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=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def retrieve_registration(self, registration_id, **kwargs): # noqa: E501
"""retrieve_registration # noqa: E501
The response is the registration represented by a JSON object as described at the beginning of this section. Response: * Successful operation uses 200 OK * Errors use a non-2xx and (optionally) an error payload. See subsection on [Error Responses](https://fiware.github.io/specifications/ngsiv2/stable) for more details. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.retrieve_registration(registration_id, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str registration_id: registration Id. (required)
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: Registration
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
return self.retrieve_registration_with_http_info(registration_id, **kwargs) # noqa: E501
def retrieve_registration_with_http_info(self, registration_id, **kwargs): # noqa: E501
"""retrieve_registration # noqa: E501
The response is the registration represented by a JSON object as described at the beginning of this section. Response: * Successful operation uses 200 OK * Errors use a non-2xx and (optionally) an error payload. See subsection on [Error Responses](https://fiware.github.io/specifications/ngsiv2/stable) for more details. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.retrieve_registration_with_http_info(registration_id, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str registration_id: registration Id. (required)
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(Registration, status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['registration_id', 'fiware_service', 'fiware_service_path'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise ApiTypeError(
"Got an unexpected keyword argument '%s'"
" to method retrieve_registration" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'registration_id' is set
if ('registration_id' not in local_var_params or
local_var_params['registration_id'] is None):
raise ApiValueError("Missing the required parameter `registration_id` when calling `retrieve_registration`") # noqa: E501
collection_formats = {}
path_params = {}
if 'registration_id' in local_var_params:
path_params['registrationId'] = local_var_params['registration_id'] # noqa: E501
query_params = []
header_params = {}
if 'fiware_service' in local_var_params:
header_params['Fiware-Service'] = local_var_params['fiware_service'] # noqa: E501
if 'fiware_service_path' in local_var_params:
header_params['Fiware-ServicePath'] = local_var_params['fiware_service_path'] # noqa: E501
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 = ['ApiKeyAuth', 'BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/registrations/{registrationId}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Registration', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def retrieve_registrations(self, **kwargs): # noqa: E501
"""retrieve_registrations # noqa: E501
Lists all the context provider registrations present in the system. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.retrieve_registrations(async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param int limit: Limit the number of types to be retrieved
:param int offset: Skip a number of records
:param str options: Options dictionary
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: list[Registration]
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
return self.retrieve_registrations_with_http_info(**kwargs) # noqa: E501
def retrieve_registrations_with_http_info(self, **kwargs): # noqa: E501
"""retrieve_registrations # noqa: E501
Lists all the context provider registrations present in the system. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.retrieve_registrations_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param int limit: Limit the number of types to be retrieved
:param int offset: Skip a number of records
:param str options: Options dictionary
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(list[Registration], status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['fiware_service', 'fiware_service_path', 'limit', 'offset', 'options'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise ApiTypeError(
"Got an unexpected keyword argument '%s'"
" to method retrieve_registrations" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
if 'limit' in local_var_params:
query_params.append(('limit', local_var_params['limit'])) # noqa: E501
if 'offset' in local_var_params:
query_params.append(('offset', local_var_params['offset'])) # noqa: E501
if 'options' in local_var_params:
query_params.append(('options', local_var_params['options'])) # noqa: E501
header_params = {}
if 'fiware_service' in local_var_params:
header_params['Fiware-Service'] = local_var_params['fiware_service'] # noqa: E501
if 'fiware_service_path' in local_var_params:
header_params['Fiware-ServicePath'] = local_var_params['fiware_service_path'] # noqa: E501
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 = ['ApiKeyAuth', 'BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/registrations', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='list[Registration]', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def update_registration(self, registration_id, registration_body, **kwargs): # noqa: E501
"""update_registration # noqa: E501
Creates a new context provider registration. This is typically used for binding context sources as providers of certain data. The registration is represented by a JSON object as described at the beginning of this section. Response: * Successful operation uses 201 Created * Errors use a non-2xx and (optionally) an error payload. See subsection on [Error Responses](https://fiware.github.io/specifications/ngsiv2/stable) for more details. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_registration(registration_id, registration_body, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str registration_id: registration Id. (required)
:param RegistrationBody registration_body: (required)
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
return self.update_registration_with_http_info(registration_id, registration_body, **kwargs) # noqa: E501
def update_registration_with_http_info(self, registration_id, registration_body, **kwargs): # noqa: E501
"""update_registration # noqa: E501
Creates a new context provider registration. This is typically used for binding context sources as providers of certain data. The registration is represented by a JSON object as described at the beginning of this section. Response: * Successful operation uses 201 Created * Errors use a non-2xx and (optionally) an error payload. See subsection on [Error Responses](https://fiware.github.io/specifications/ngsiv2/stable) for more details. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_registration_with_http_info(registration_id, registration_body, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str registration_id: registration Id. (required)
:param RegistrationBody registration_body: (required)
:param str fiware_service: When \"-multiservice\" is used, Orion uses the \"Fiware-Service\" HTTP header in the request to identify the service/tenant. If the header is not present in the HTTP request, the default service/tenant is used..
:param str fiware_service_path: Fiware-ServicePath is an optional header. It is assumed that all the entities created without Fiware-ServicePath (or that don't include service path information in the database) belongs to a root scope \"/\" implicitely.
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['registration_id', 'registration_body', 'fiware_service', 'fiware_service_path'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise ApiTypeError(
"Got an unexpected keyword argument '%s'"
" to method update_registration" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'registration_id' is set
if ('registration_id' not in local_var_params or
local_var_params['registration_id'] is None):
raise ApiValueError("Missing the required parameter `registration_id` when calling `update_registration`") # noqa: E501
# verify the required parameter 'registration_body' is set
if ('registration_body' not in local_var_params or
local_var_params['registration_body'] is None):
raise ApiValueError("Missing the required parameter `registration_body` when calling `update_registration`") # noqa: E501
collection_formats = {}
path_params = {}
if 'registration_id' in local_var_params:
path_params['registrationId'] = local_var_params['registration_id'] # noqa: E501
query_params = []
header_params = {}
if 'fiware_service' in local_var_params:
header_params['Fiware-Service'] = local_var_params['fiware_service'] # noqa: E501
if 'fiware_service_path' in local_var_params:
header_params['Fiware-ServicePath'] = local_var_params['fiware_service_path'] # noqa: E501
form_params = []
local_var_files = {}
body_params = None
if 'registration_body' in local_var_params:
body_params = local_var_params['registration_body']
# 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']) # noqa: E501
# Authentication setting
auth_settings = ['ApiKeyAuth', 'BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/registrations/{registrationId}', 'PATCH',
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=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
| 56.901408
| 464
| 0.653438
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| 0.052602
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| 0
| 0.012391
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| 36,360
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| 1
| 0
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| 0.039644
| 0
| 0
| 0
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| 0
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| 0.038869
| false
| 0
| 0.017668
| 0
| 0.095406
| 0
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| null | 0
| 0
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0
| 8
|
3ed8e51c97f4de799146e50c5750b939ae300a5b
| 702,500
|
py
|
Python
|
epytope/EpitopePrediction/External.py
|
jonasscheid/epytope
|
4bc846b8486a7ddf17dc6419de60ad4df8d677ef
|
[
"BSD-3-Clause"
] | 7
|
2021-02-01T18:11:28.000Z
|
2022-01-31T19:14:07.000Z
|
epytope/EpitopePrediction/External.py
|
jonasscheid/epytope
|
4bc846b8486a7ddf17dc6419de60ad4df8d677ef
|
[
"BSD-3-Clause"
] | 22
|
2021-01-02T15:25:23.000Z
|
2022-03-14T11:32:53.000Z
|
epytope/EpitopePrediction/External.py
|
jonasscheid/epytope
|
4bc846b8486a7ddf17dc6419de60ad4df8d677ef
|
[
"BSD-3-Clause"
] | 4
|
2021-05-28T08:50:38.000Z
|
2022-03-14T11:45:32.000Z
|
# This code is part of the epytope distribution and governed by its
# license. Please see the LICENSE file that should have been included
# as part of this package.
"""
.. module:: EpitopePrediction.ANN
:synopsis: This module contains all classes for ANN-based epitope prediction methods.
.. moduleauthor:: schubert, walzer
"""
import abc
import itertools
import warnings
import logging
import pandas
import subprocess
import csv
import os
import math
from collections import defaultdict
from epytope.Core.Allele import Allele, CombinedAllele, MouseAllele
from epytope.Core.Peptide import Peptide
from epytope.Core.Result import EpitopePredictionResult
from epytope.Core.Base import AEpitopePrediction, AExternal
from tempfile import NamedTemporaryFile, mkstemp
class AExternalEpitopePrediction(AEpitopePrediction, AExternal):
"""
Abstract class representing an external prediction function. Implementations shall wrap external binaries by
following the given abstraction.
"""
@abc.abstractmethod
def prepare_input(self, input, file):
"""
Prepares input for external tools
and writes them to _file in the specific format
NO return value!
:param: list(str) _input: The :class:`~epytope.Core.Peptide.Peptide` sequences to write into file
:param File file: File-handler to input file for external tool
"""
return NotImplementedError
def predict(self, peptides, alleles=None, command=None, options=None, **kwargs):
"""
Overwrites AEpitopePrediction.predict
:param peptides: A list of or a single :class:`~epytope.Core.Peptide.Peptide` object
:type peptides: list(:class:`~epytope.Core.Peptide.Peptide`) or :class:`~epytope.Core.Peptide.Peptide`
:param alleles: A list of or a single :class:`~epytope.Core.Allele.Allele` object. If no
:class:`~epytope.Core.Allele.Allele` are provided, predictions are made for all
:class:`~epytope.Core.Allele.Allele` supported by the prediction method
:type alleles: list(:class:`~epytope.Core.Allele.Allele`)/:class:`~epytope.Core.Allele.Allele`
:param str command: The path to a alternative binary (can be used if binary is not globally executable)
:param str options: A string of additional options directly past to the external tool.
:keyword chunksize: denotes the chunksize in which the number of peptides are bulk processed
:return: A :class:`~epytope.Core.Result.EpitopePredictionResult` object
:rtype: :class:`~epytope.Core.Result.EpitopePredictionResult`
"""
if not self.is_in_path() and command is None:
raise RuntimeError("{name} {version} could not be found in PATH".format(name=self.name,
version=self.version))
external_version = self.get_external_version(path=command)
if self.version != external_version and external_version is not None:
raise RuntimeError("Internal version {internal_version} does "
"not match external version {external_version}".format(internal_version=self.version,
external_version=external_version))
if isinstance(peptides, Peptide):
pep_seqs = {str(peptides): peptides}
else:
pep_seqs = {}
for p in peptides:
if not isinstance(p, Peptide):
raise ValueError("Input is not of type Protein or Peptide")
pep_seqs[str(p)] = p
chunksize = len(pep_seqs)
if 'chunks' in kwargs:
chunksize = kwargs['chunks']
if alleles is None:
al = [Allele(a) for a in self.supportedAlleles]
allales_string = {conv_a: a for conv_a, a in zip(self.convert_alleles(al), al)}
else:
if isinstance(alleles, Allele):
alleles = [alleles]
if any(not isinstance(p, Allele) for p in alleles):
raise ValueError("Input is not of type Allele")
allales_string = {conv_a: a for conv_a, a in zip(self.convert_alleles(alleles), alleles)}
result = defaultdict(defaultdict)
# group alleles in blocks of 80 alleles (NetMHC can't deal with more)
_MAX_ALLELES = 50
# allow custom executable specification
if command is not None:
exe = self.command.split()[0]
_command = self.command.replace(exe, command)
else:
_command = self.command
allele_groups = []
c_a = 0
allele_group = []
for a in allales_string.keys():
if c_a >= _MAX_ALLELES:
c_a = 0
allele_groups.append(allele_group)
if str(allales_string[a]) not in self.supportedAlleles:
logging.warning("Allele %s is not supported by %s" % (str(allales_string[a]), self.name))
allele_group = []
continue
allele_group = [a]
else:
if str(allales_string[a]) not in self.supportedAlleles:
logging.warning("Allele %s is not supported by %s" % (str(allales_string[a]), self.name))
continue
allele_group.append(a)
c_a += 1
if len(allele_group) > 0:
allele_groups.append(allele_group)
# export peptides to peptide list
pep_groups = list(pep_seqs.keys())
pep_groups.sort(key=len)
for length, peps in itertools.groupby(pep_groups, key=len):
if length not in self.supportedLength:
logging.warning("Peptide length must be at least %i or at most %i for %s but is %i" % (min(self.supportedLength), max(self.supportedLength),
self.name, length))
continue
peps = list(peps)
for i in range(0, len(peps), chunksize):
# Create a temporary file for subprocess to write to. The
# handle is not needed on the python end, as only the path will
# be passed to the subprocess.
_, tmp_out_path = mkstemp()
# Create a temporary file to be used for the peptide input
tmp_file = NamedTemporaryFile(mode="r+", delete=False)
self.prepare_input(peps[i:i+chunksize], tmp_file)
tmp_file.close()
# generate cmd command
for allele_group in allele_groups:
try:
stdo = None
stde = None
cmd = _command.format(peptides=tmp_file.name, alleles=",".join(allele_group),
options="" if options is None else options, out=tmp_out_path, length=str(length))
p = subprocess.Popen(cmd, shell=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
stdo, stde = p.communicate()
stdr = p.returncode
if stdr > 0:
raise RuntimeError("Unsuccessful execution of " + cmd + " (EXIT!=0) with output:\n" + stdo.decode())
if os.path.getsize(tmp_out_path) == 0:
raise RuntimeError("Unsuccessful execution of " + cmd + " (empty output file) with output:\n" + stdo.decode())
except Exception as e:
raise RuntimeError(e)
res_tmp = self.parse_external_result(tmp_out_path)
for al, ep_dict in res_tmp.items():
for p, v in ep_dict.items():
result[allales_string[al]][pep_seqs[p]] = v
os.remove(tmp_file.name)
os.remove(tmp_out_path)
if not result:
raise ValueError("No predictions could be made with " + self.name +
" for given input. Check your epitope length and HLA allele combination.")
df_result = EpitopePredictionResult.from_dict(result)
df_result.index = pandas.MultiIndex.from_tuples([tuple((i, self.name)) for i in df_result.index],
names=['Seq', 'Method'])
return df_result
class NetMHC_3_4(AExternalEpitopePrediction):
"""
Implements the NetMHC binding (in current form for netMHC3.4).
.. note::
NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides
of length 8-11. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M.
Nucleic Acids Res. 1;36(Web Server issue):W509-12. 2008
Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using
prediction tools trained on 9mers. Lundegaard C, Lund O, Nielsen M. Bioinformatics, 24(11):1397-98, 2008.
"""
__alleles = frozenset(['HLA-A*01:01', 'HLA-A*02:01', 'HLA-A*02:02', 'HLA-A*02:03', 'HLA-A*02:06', 'HLA-A*02:11', 'HLA-A*02:12', 'HLA-A*02:16',
'HLA-A*02:17', 'HLA-A*02:19', 'HLA-A*02:50', 'HLA-A*03:01', 'HLA-A*11:01', 'HLA-A*23:01', 'HLA-A*24:02', 'HLA-A*24:03',
'HLA-A*25:01', 'HLA-A*26:01', 'HLA-A*26:02', 'HLA-A*26:03', 'HLA-A*29:02', 'HLA-A*30:01', 'HLA-A*30:02', 'HLA-A*31:01',
'HLA-A*32:01', 'HLA-A*32:07', 'HLA-A*32:15', 'HLA-A*33:01', 'HLA-A*66:01', 'HLA-A*68:01', 'HLA-A*68:02', 'HLA-A*68:23',
'HLA-A*69:01', 'HLA-A*80:01', 'HLA-B*07:02', 'HLA-B*08:01', 'HLA-B*08:02', 'HLA-B*08:03', 'HLA-B*14:02', 'HLA-B*15:01',
'HLA-B*15:02', 'HLA-B*15:03', 'HLA-B*15:09', 'HLA-B*15:17', 'HLA-B*18:01', 'HLA-B*27:05', 'HLA-B*27:20', 'HLA-B*35:01',
'HLA-B*35:03', 'HLA-B*38:01', 'HLA-B*39:01', 'HLA-B*40:01', 'HLA-B*40:02', 'HLA-B*40:13', 'HLA-B*42:01', 'HLA-B*44:02',
'HLA-B*44:03', 'HLA-B*45:01', 'HLA-B*46:01', 'HLA-B*48:01', 'HLA-B*51:01', 'HLA-B*53:01', 'HLA-B*54:01', 'HLA-B*57:01',
'HLA-B*58:01', 'HLA-B*73:01', 'HLA-B*83:01', 'HLA-C*03:03', 'HLA-C*04:01', 'HLA-C*05:01', 'HLA-C*06:02', 'HLA-C*07:01',
'HLA-C*07:02', 'HLA-C*08:02', 'HLA-C*12:03', 'HLA-C*14:02', 'HLA-C*15:02', 'HLA-E*01:01',
'H2-Db', 'H2-Dd', 'H2-Kb', 'H2-Kd', 'H2-Kk', 'H2-Ld'])
__supported_length = frozenset([8, 9, 10, 11])
__name = "netmhc"
__command = "netMHC -p {peptides} -a {alleles} -x {out} {options}"
__version = "3.4"
@property
def version(self):
"""The version of the predictor"""
return self.__version
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
else:
return "HLA-%s%s:%s" % (allele.locus, allele.supertype, allele.subtype)
def convert_alleles(self, alleles):
"""
Converts :class:`~epytope.Core.Allele.Allele` into the internal :class:`~epytope.Core.Allele.Allele` representation
of the predictor and returns a string representation
:param alleles: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: Returns a string representation of the input :class:`~epytope.Core.Allele.Allele`
:rtype: list(str)
"""
return [self._represent(a) for a in alleles]
@property
def supportedAlleles(self):
"""
A list of valid allele models
"""
return self.__alleles
@property
def name(self):
"""The name of the predictor"""
return self.__name
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
f = csv.reader(open(file, "r"), delimiter='\t')
next(f)
next(f)
alleles = [x.split()[0] for x in f.next()[3:]]
for l in f:
if not l:
continue
pep_seq = l[2]
for ic_50, a in zip(l[3:], alleles):
sc = 1.0 - math.log(float(ic_50), 50000)
result[a][pep_seq] = sc if sc > 0.0 else 0.0
return dict(result)
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`self.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: dict
"""
return super(NetMHC_3_4, self).get_external_version()
def prepare_input(self, input, file):
"""
Prepares input for external tools
and writes them to file in the specific format
NO return value!
:param: list(str) input: The : sequences to write into _file
:param File file: File-handler to input file for external tool
"""
file.write("\n".join(input))
class NetMHC_3_0(NetMHC_3_4):
"""
Implements the NetMHC binding (for netMHC3.0)::
.. note::
NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides
of length 8-11. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M.
Nucleic Acids Res. 1;36(Web Server issue):W509-12. 2008
Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11
using prediction tools trained on 9mers. Lundegaard C, Lund O, Nielsen M. Bioinformatics, 24(11):1397-98, 2008.
"""
__alleles = frozenset(['HLA-A*01:01', 'HLA-A*02:01', 'HLA-A*02:02', 'HLA-A*02:03', 'HLA-A*02:04', 'HLA-A*02:06', 'HLA-A*02:11', 'HLA-A*02:12',
'HLA-A*02:16', 'HLA-A*02:19', 'HLA-A*03:01', 'HLA-A*11:01', 'HLA-A*23:01', 'HLA-A*24:02', 'HLA-A*24:03', 'HLA-A*26:01',
'HLA-A*26:02', 'HLA-A*29:02', 'HLA-A*30:01', 'HLA-A*30:02', 'HLA-A*31:01', 'HLA-A*33:01', 'HLA-A*68:01', 'HLA-A*68:02',
'HLA-A*69:01', 'HLA-B*07:02', 'HLA-B*08:01', 'HLA-B*08:02', 'HLA-B*15:01', 'HLA-B*18:01', 'HLA-B*27:05', 'HLA-B*35:01',
'HLA-B*39:01', 'HLA-B*40:01', 'HLA-B*40:02', 'HLA-B*44:02', 'HLA-B*44:03', 'HLA-B*45:01', 'HLA-B*51:01', 'HLA-B*53:01',
'HLA-B*54:01', 'HLA-B*57:01', 'HLA-B*58:01',
'H2-Db', 'H2-Dd', 'H2-Kb', 'H2-Kd', 'H2-Kk', 'H2-Ld']) # no PSSM predictors
__supported_length = frozenset([8, 9, 10, 11])
__name = "netmhc"
__version = "3.0a"
__command = "netMHC-3.0 -p {peptides} -a {alleles} -x {out} -l {length} {options}"
@property
def version(self):
"""The version of the predictor"""
return self.__version
@property
def name(self):
"""The name of the predictor"""
return self.__name
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedAlleles(self):
"""
A list of valid :class:`~epytope.Core.Allele.Allele` models
"""
return self.__alleles
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
else:
return "HLA-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(dict)
with open(file, 'r') as f:
next(f, None) # skip first line with logging stuff
next(f, None) # skip first line with nothing
csvr = csv.reader(f, delimiter='\t')
alleles = [x.split()[0] for x in csvr.next()[3:]]
for l in csvr:
if not l:
continue
pep_seq = l[2]
for ic_50, a in zip(l[3:], alleles):
sc = 1.0 - math.log(float(ic_50), 50000)
result[a][pep_seq] = sc if sc > 0.0 else 0.0
if 'Average' in result:
result.pop('Average')
return dict(result)
class NetMHC_4_0(NetMHC_3_4):
"""
Implements the NetMHC 4.0 binding
.. note::
Andreatta M, Nielsen M. Gapped sequence alignment using artificial neural networks:
application to the MHC class I system. Bioinformatics (2016) Feb 15;32(4):511-7
"""
__command = "netMHC -p {peptides} -a {alleles} -xls -xlsfile {out} {options}"
__version = "4.0"
@property
def version(self):
"""The version of the predictor"""
return self.__version
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
else:
return "HLA-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
f = csv.reader(open(file, "r"), delimiter='\t')
pos_factor = 3
# alleles = map(lambda x: x.split()[0], filter(lambda x: x.strip() != "", f.next()))
# f.next()
alleles = [x.split()[0] for x in [x for x in next(f) if x.strip() != ""]]
next(f)
for l in f:
if not l:
continue
pep_seq = l[1]
for i, a in enumerate(alleles):
ic_50 = l[(i+1)*pos_factor]
sc = 1.0 - math.log(float(ic_50), 50000)
result[a][pep_seq] = sc if sc > 0.0 else 0.0
return dict(result)
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`self.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: str
"""
# can not be determined netmhcpan does not support --version or similar
return None
class NetMHCpan_2_4(AExternalEpitopePrediction):
"""
Implements the NetMHC binding (in current form for netMHCpan 2.4).
Supported MHC alleles currently only restricted to HLA alleles.
.. note::
Nielsen, Morten, et al. "NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and-B
locus protein of known sequence." PloS one 2.8 (2007): e796.
"""
__supported_length = frozenset([8, 9, 10, 11])
__name = "netmhcpan"
__command = "netMHCpan-2.4 -p {peptides} -a {alleles} {options} -ic50 -xls -xlsfile {out}"
__alleles = frozenset(
['HLA-A*01:01', 'HLA-A*01:02', 'HLA-A*01:03', 'HLA-A*01:06', 'HLA-A*01:07', 'HLA-A*01:08', 'HLA-A*01:09', 'HLA-A*01:10', 'HLA-A*01:12',
'HLA-A*01:13', 'HLA-A*01:14', 'HLA-A*01:17', 'HLA-A*01:19', 'HLA-A*01:20', 'HLA-A*01:21', 'HLA-A*01:23', 'HLA-A*01:24', 'HLA-A*01:25',
'HLA-A*01:26', 'HLA-A*01:28', 'HLA-A*01:29', 'HLA-A*01:30', 'HLA-A*01:32', 'HLA-A*01:33', 'HLA-A*01:35', 'HLA-A*01:36', 'HLA-A*01:37',
'HLA-A*01:38', 'HLA-A*01:39', 'HLA-A*01:40', 'HLA-A*01:41', 'HLA-A*01:42', 'HLA-A*01:43', 'HLA-A*01:44', 'HLA-A*01:45', 'HLA-A*01:46',
'HLA-A*01:47', 'HLA-A*01:48', 'HLA-A*01:49', 'HLA-A*01:50', 'HLA-A*01:51', 'HLA-A*01:54', 'HLA-A*01:55', 'HLA-A*01:58', 'HLA-A*01:59',
'HLA-A*01:60', 'HLA-A*01:61', 'HLA-A*01:62', 'HLA-A*01:63', 'HLA-A*01:64', 'HLA-A*01:65', 'HLA-A*01:66', 'HLA-A*02:01', 'HLA-A*02:02',
'HLA-A*02:03', 'HLA-A*02:04', 'HLA-A*02:05', 'HLA-A*02:06', 'HLA-A*02:07', 'HLA-A*02:08', 'HLA-A*02:09', 'HLA-A*02:10', 'HLA-A*02:101',
'HLA-A*02:102', 'HLA-A*02:103', 'HLA-A*02:104', 'HLA-A*02:105', 'HLA-A*02:106', 'HLA-A*02:107', 'HLA-A*02:108', 'HLA-A*02:109',
'HLA-A*02:11', 'HLA-A*02:110', 'HLA-A*02:111', 'HLA-A*02:112', 'HLA-A*02:114', 'HLA-A*02:115', 'HLA-A*02:116', 'HLA-A*02:117',
'HLA-A*02:118', 'HLA-A*02:119', 'HLA-A*02:12', 'HLA-A*02:120', 'HLA-A*02:121', 'HLA-A*02:122', 'HLA-A*02:123', 'HLA-A*02:124',
'HLA-A*02:126', 'HLA-A*02:127', 'HLA-A*02:128', 'HLA-A*02:129', 'HLA-A*02:13', 'HLA-A*02:130', 'HLA-A*02:131', 'HLA-A*02:132',
'HLA-A*02:133', 'HLA-A*02:134', 'HLA-A*02:135', 'HLA-A*02:136', 'HLA-A*02:137', 'HLA-A*02:138', 'HLA-A*02:139', 'HLA-A*02:14',
'HLA-A*02:140', 'HLA-A*02:141', 'HLA-A*02:142', 'HLA-A*02:143', 'HLA-A*02:144', 'HLA-A*02:145', 'HLA-A*02:146', 'HLA-A*02:147',
'HLA-A*02:148', 'HLA-A*02:149', 'HLA-A*02:150', 'HLA-A*02:151', 'HLA-A*02:152', 'HLA-A*02:153', 'HLA-A*02:154', 'HLA-A*02:155',
'HLA-A*02:156', 'HLA-A*02:157', 'HLA-A*02:158', 'HLA-A*02:159', 'HLA-A*02:16', 'HLA-A*02:160', 'HLA-A*02:161', 'HLA-A*02:162',
'HLA-A*02:163', 'HLA-A*02:164', 'HLA-A*02:165', 'HLA-A*02:166', 'HLA-A*02:167', 'HLA-A*02:168', 'HLA-A*02:169', 'HLA-A*02:17',
'HLA-A*02:170', 'HLA-A*02:171', 'HLA-A*02:172', 'HLA-A*02:173', 'HLA-A*02:174', 'HLA-A*02:175', 'HLA-A*02:176', 'HLA-A*02:177',
'HLA-A*02:178', 'HLA-A*02:179', 'HLA-A*02:18', 'HLA-A*02:180', 'HLA-A*02:181', 'HLA-A*02:182', 'HLA-A*02:183', 'HLA-A*02:184',
'HLA-A*02:185', 'HLA-A*02:186', 'HLA-A*02:187', 'HLA-A*02:188', 'HLA-A*02:189', 'HLA-A*02:19', 'HLA-A*02:190', 'HLA-A*02:191',
'HLA-A*02:192', 'HLA-A*02:193', 'HLA-A*02:194', 'HLA-A*02:195', 'HLA-A*02:196', 'HLA-A*02:197', 'HLA-A*02:198', 'HLA-A*02:199',
'HLA-A*02:20', 'HLA-A*02:200', 'HLA-A*02:201', 'HLA-A*02:202', 'HLA-A*02:203', 'HLA-A*02:204', 'HLA-A*02:205', 'HLA-A*02:206',
'HLA-A*02:207', 'HLA-A*02:208', 'HLA-A*02:209', 'HLA-A*02:21', 'HLA-A*02:210', 'HLA-A*02:211', 'HLA-A*02:212', 'HLA-A*02:213',
'HLA-A*02:214', 'HLA-A*02:215', 'HLA-A*02:216', 'HLA-A*02:217', 'HLA-A*02:218', 'HLA-A*02:219', 'HLA-A*02:22', 'HLA-A*02:220',
'HLA-A*02:221', 'HLA-A*02:224', 'HLA-A*02:228', 'HLA-A*02:229', 'HLA-A*02:230', 'HLA-A*02:231', 'HLA-A*02:232', 'HLA-A*02:233',
'HLA-A*02:234', 'HLA-A*02:235', 'HLA-A*02:236', 'HLA-A*02:237', 'HLA-A*02:238', 'HLA-A*02:239', 'HLA-A*02:24', 'HLA-A*02:240',
'HLA-A*02:241', 'HLA-A*02:242', 'HLA-A*02:243', 'HLA-A*02:244', 'HLA-A*02:245', 'HLA-A*02:246', 'HLA-A*02:247', 'HLA-A*02:248',
'HLA-A*02:249', 'HLA-A*02:25', 'HLA-A*02:251', 'HLA-A*02:252', 'HLA-A*02:253', 'HLA-A*02:254', 'HLA-A*02:255', 'HLA-A*02:256',
'HLA-A*02:257', 'HLA-A*02:258', 'HLA-A*02:259', 'HLA-A*02:26', 'HLA-A*02:260', 'HLA-A*02:261', 'HLA-A*02:262', 'HLA-A*02:263',
'HLA-A*02:264', 'HLA-A*02:265', 'HLA-A*02:266', 'HLA-A*02:27', 'HLA-A*02:28', 'HLA-A*02:29', 'HLA-A*02:30', 'HLA-A*02:31', 'HLA-A*02:33',
'HLA-A*02:34', 'HLA-A*02:35', 'HLA-A*02:36', 'HLA-A*02:37', 'HLA-A*02:38', 'HLA-A*02:39', 'HLA-A*02:40', 'HLA-A*02:41', 'HLA-A*02:42',
'HLA-A*02:44', 'HLA-A*02:45', 'HLA-A*02:46', 'HLA-A*02:47', 'HLA-A*02:48', 'HLA-A*02:49', 'HLA-A*02:50', 'HLA-A*02:51', 'HLA-A*02:52',
'HLA-A*02:54', 'HLA-A*02:55', 'HLA-A*02:56', 'HLA-A*02:57', 'HLA-A*02:58', 'HLA-A*02:59', 'HLA-A*02:60', 'HLA-A*02:61', 'HLA-A*02:62',
'HLA-A*02:63', 'HLA-A*02:64', 'HLA-A*02:65', 'HLA-A*02:66', 'HLA-A*02:67', 'HLA-A*02:68', 'HLA-A*02:69', 'HLA-A*02:70', 'HLA-A*02:71',
'HLA-A*02:72', 'HLA-A*02:73', 'HLA-A*02:74', 'HLA-A*02:75', 'HLA-A*02:76', 'HLA-A*02:77', 'HLA-A*02:78', 'HLA-A*02:79', 'HLA-A*02:80',
'HLA-A*02:81', 'HLA-A*02:84', 'HLA-A*02:85', 'HLA-A*02:86', 'HLA-A*02:87', 'HLA-A*02:89', 'HLA-A*02:90', 'HLA-A*02:91', 'HLA-A*02:92',
'HLA-A*02:93', 'HLA-A*02:95', 'HLA-A*02:96', 'HLA-A*02:97', 'HLA-A*02:99', 'HLA-A*03:01', 'HLA-A*03:02', 'HLA-A*03:04', 'HLA-A*03:05',
'HLA-A*03:06', 'HLA-A*03:07', 'HLA-A*03:08', 'HLA-A*03:09', 'HLA-A*03:10', 'HLA-A*03:12', 'HLA-A*03:13', 'HLA-A*03:14', 'HLA-A*03:15',
'HLA-A*03:16', 'HLA-A*03:17', 'HLA-A*03:18', 'HLA-A*03:19', 'HLA-A*03:20', 'HLA-A*03:22', 'HLA-A*03:23', 'HLA-A*03:24', 'HLA-A*03:25',
'HLA-A*03:26', 'HLA-A*03:27', 'HLA-A*03:28', 'HLA-A*03:29', 'HLA-A*03:30', 'HLA-A*03:31', 'HLA-A*03:32', 'HLA-A*03:33', 'HLA-A*03:34',
'HLA-A*03:35', 'HLA-A*03:37', 'HLA-A*03:38', 'HLA-A*03:39', 'HLA-A*03:40', 'HLA-A*03:41', 'HLA-A*03:42', 'HLA-A*03:43', 'HLA-A*03:44',
'HLA-A*03:45', 'HLA-A*03:46', 'HLA-A*03:47', 'HLA-A*03:48', 'HLA-A*03:49', 'HLA-A*03:50', 'HLA-A*03:51', 'HLA-A*03:52', 'HLA-A*03:53',
'HLA-A*03:54', 'HLA-A*03:55', 'HLA-A*03:56', 'HLA-A*03:57', 'HLA-A*03:58', 'HLA-A*03:59', 'HLA-A*03:60', 'HLA-A*03:61', 'HLA-A*03:62',
'HLA-A*03:63', 'HLA-A*03:64', 'HLA-A*03:65', 'HLA-A*03:66', 'HLA-A*03:67', 'HLA-A*03:70', 'HLA-A*03:71', 'HLA-A*03:72', 'HLA-A*03:73',
'HLA-A*03:74', 'HLA-A*03:75', 'HLA-A*03:76', 'HLA-A*03:77', 'HLA-A*03:78', 'HLA-A*03:79', 'HLA-A*03:80', 'HLA-A*03:81', 'HLA-A*03:82',
'HLA-A*11:01', 'HLA-A*11:02', 'HLA-A*11:03', 'HLA-A*11:04', 'HLA-A*11:05', 'HLA-A*11:06', 'HLA-A*11:07', 'HLA-A*11:08', 'HLA-A*11:09',
'HLA-A*11:10', 'HLA-A*11:11', 'HLA-A*11:12', 'HLA-A*11:13', 'HLA-A*11:14', 'HLA-A*11:15', 'HLA-A*11:16', 'HLA-A*11:17', 'HLA-A*11:18',
'HLA-A*11:19', 'HLA-A*11:20', 'HLA-A*11:22', 'HLA-A*11:23', 'HLA-A*11:24', 'HLA-A*11:25', 'HLA-A*11:26', 'HLA-A*11:27', 'HLA-A*11:29',
'HLA-A*11:30', 'HLA-A*11:31', 'HLA-A*11:32', 'HLA-A*11:33', 'HLA-A*11:34', 'HLA-A*11:35', 'HLA-A*11:36', 'HLA-A*11:37', 'HLA-A*11:38',
'HLA-A*11:39', 'HLA-A*11:40', 'HLA-A*11:41', 'HLA-A*11:42', 'HLA-A*11:43', 'HLA-A*11:44', 'HLA-A*11:45', 'HLA-A*11:46', 'HLA-A*11:47',
'HLA-A*11:48', 'HLA-A*11:49', 'HLA-A*11:51', 'HLA-A*11:53', 'HLA-A*11:54', 'HLA-A*11:55', 'HLA-A*11:56', 'HLA-A*11:57', 'HLA-A*11:58',
'HLA-A*11:59', 'HLA-A*11:60', 'HLA-A*11:61', 'HLA-A*11:62', 'HLA-A*11:63', 'HLA-A*11:64', 'HLA-A*23:01', 'HLA-A*23:02', 'HLA-A*23:03',
'HLA-A*23:04', 'HLA-A*23:05', 'HLA-A*23:06', 'HLA-A*23:09', 'HLA-A*23:10', 'HLA-A*23:12', 'HLA-A*23:13', 'HLA-A*23:14', 'HLA-A*23:15',
'HLA-A*23:16', 'HLA-A*23:17', 'HLA-A*23:18', 'HLA-A*23:20', 'HLA-A*23:21', 'HLA-A*23:22', 'HLA-A*23:23', 'HLA-A*23:24', 'HLA-A*23:25',
'HLA-A*23:26', 'HLA-A*24:02', 'HLA-A*24:03', 'HLA-A*24:04', 'HLA-A*24:05', 'HLA-A*24:06', 'HLA-A*24:07', 'HLA-A*24:08', 'HLA-A*24:10',
'HLA-A*24:100', 'HLA-A*24:101', 'HLA-A*24:102', 'HLA-A*24:103', 'HLA-A*24:104', 'HLA-A*24:105', 'HLA-A*24:106', 'HLA-A*24:107',
'HLA-A*24:108', 'HLA-A*24:109', 'HLA-A*24:110', 'HLA-A*24:111', 'HLA-A*24:112', 'HLA-A*24:113', 'HLA-A*24:114', 'HLA-A*24:115',
'HLA-A*24:116', 'HLA-A*24:117', 'HLA-A*24:118', 'HLA-A*24:119', 'HLA-A*24:120', 'HLA-A*24:121', 'HLA-A*24:122', 'HLA-A*24:123',
'HLA-A*24:124', 'HLA-A*24:125', 'HLA-A*24:126', 'HLA-A*24:127', 'HLA-A*24:128', 'HLA-A*24:129', 'HLA-A*24:13', 'HLA-A*24:130',
'HLA-A*24:131', 'HLA-A*24:133', 'HLA-A*24:134', 'HLA-A*24:135', 'HLA-A*24:136', 'HLA-A*24:137', 'HLA-A*24:138', 'HLA-A*24:139',
'HLA-A*24:14', 'HLA-A*24:140', 'HLA-A*24:141', 'HLA-A*24:142', 'HLA-A*24:143', 'HLA-A*24:144', 'HLA-A*24:15', 'HLA-A*24:17', 'HLA-A*24:18',
'HLA-A*24:19', 'HLA-A*24:20', 'HLA-A*24:21', 'HLA-A*24:22', 'HLA-A*24:23', 'HLA-A*24:24', 'HLA-A*24:25', 'HLA-A*24:26', 'HLA-A*24:27',
'HLA-A*24:28', 'HLA-A*24:29', 'HLA-A*24:30', 'HLA-A*24:31', 'HLA-A*24:32', 'HLA-A*24:33', 'HLA-A*24:34', 'HLA-A*24:35', 'HLA-A*24:37',
'HLA-A*24:38', 'HLA-A*24:39', 'HLA-A*24:41', 'HLA-A*24:42', 'HLA-A*24:43', 'HLA-A*24:44', 'HLA-A*24:46', 'HLA-A*24:47', 'HLA-A*24:49',
'HLA-A*24:50', 'HLA-A*24:51', 'HLA-A*24:52', 'HLA-A*24:53', 'HLA-A*24:54', 'HLA-A*24:55', 'HLA-A*24:56', 'HLA-A*24:57', 'HLA-A*24:58',
'HLA-A*24:59', 'HLA-A*24:61', 'HLA-A*24:62', 'HLA-A*24:63', 'HLA-A*24:64', 'HLA-A*24:66', 'HLA-A*24:67', 'HLA-A*24:68', 'HLA-A*24:69',
'HLA-A*24:70', 'HLA-A*24:71', 'HLA-A*24:72', 'HLA-A*24:73', 'HLA-A*24:74', 'HLA-A*24:75', 'HLA-A*24:76', 'HLA-A*24:77', 'HLA-A*24:78',
'HLA-A*24:79', 'HLA-A*24:80', 'HLA-A*24:81', 'HLA-A*24:82', 'HLA-A*24:85', 'HLA-A*24:87', 'HLA-A*24:88', 'HLA-A*24:89', 'HLA-A*24:91',
'HLA-A*24:92', 'HLA-A*24:93', 'HLA-A*24:94', 'HLA-A*24:95', 'HLA-A*24:96', 'HLA-A*24:97', 'HLA-A*24:98', 'HLA-A*24:99', 'HLA-A*25:01',
'HLA-A*25:02', 'HLA-A*25:03', 'HLA-A*25:04', 'HLA-A*25:05', 'HLA-A*25:06', 'HLA-A*25:07', 'HLA-A*25:08', 'HLA-A*25:09', 'HLA-A*25:10',
'HLA-A*25:11', 'HLA-A*25:13', 'HLA-A*26:01', 'HLA-A*26:02', 'HLA-A*26:03', 'HLA-A*26:04', 'HLA-A*26:05', 'HLA-A*26:06', 'HLA-A*26:07',
'HLA-A*26:08', 'HLA-A*26:09', 'HLA-A*26:10', 'HLA-A*26:12', 'HLA-A*26:13', 'HLA-A*26:14', 'HLA-A*26:15', 'HLA-A*26:16', 'HLA-A*26:17',
'HLA-A*26:18', 'HLA-A*26:19', 'HLA-A*26:20', 'HLA-A*26:21', 'HLA-A*26:22', 'HLA-A*26:23', 'HLA-A*26:24', 'HLA-A*26:26', 'HLA-A*26:27',
'HLA-A*26:28', 'HLA-A*26:29', 'HLA-A*26:30', 'HLA-A*26:31', 'HLA-A*26:32', 'HLA-A*26:33', 'HLA-A*26:34', 'HLA-A*26:35', 'HLA-A*26:36',
'HLA-A*26:37', 'HLA-A*26:38', 'HLA-A*26:39', 'HLA-A*26:40', 'HLA-A*26:41', 'HLA-A*26:42', 'HLA-A*26:43', 'HLA-A*26:45', 'HLA-A*26:46',
'HLA-A*26:47', 'HLA-A*26:48', 'HLA-A*26:49', 'HLA-A*26:50', 'HLA-A*29:01', 'HLA-A*29:02', 'HLA-A*29:03', 'HLA-A*29:04', 'HLA-A*29:05',
'HLA-A*29:06', 'HLA-A*29:07', 'HLA-A*29:09', 'HLA-A*29:10', 'HLA-A*29:11', 'HLA-A*29:12', 'HLA-A*29:13', 'HLA-A*29:14', 'HLA-A*29:15',
'HLA-A*29:16', 'HLA-A*29:17', 'HLA-A*29:18', 'HLA-A*29:19', 'HLA-A*29:20', 'HLA-A*29:21', 'HLA-A*29:22', 'HLA-A*30:01', 'HLA-A*30:02',
'HLA-A*30:03', 'HLA-A*30:04', 'HLA-A*30:06', 'HLA-A*30:07', 'HLA-A*30:08', 'HLA-A*30:09', 'HLA-A*30:10', 'HLA-A*30:11', 'HLA-A*30:12',
'HLA-A*30:13', 'HLA-A*30:15', 'HLA-A*30:16', 'HLA-A*30:17', 'HLA-A*30:18', 'HLA-A*30:19', 'HLA-A*30:20', 'HLA-A*30:22', 'HLA-A*30:23',
'HLA-A*30:24', 'HLA-A*30:25', 'HLA-A*30:26', 'HLA-A*30:28', 'HLA-A*30:29', 'HLA-A*30:30', 'HLA-A*30:31', 'HLA-A*30:32', 'HLA-A*30:33',
'HLA-A*30:34', 'HLA-A*30:35', 'HLA-A*30:36', 'HLA-A*30:37', 'HLA-A*30:38', 'HLA-A*30:39', 'HLA-A*30:40', 'HLA-A*30:41', 'HLA-A*31:01',
'HLA-A*31:02', 'HLA-A*31:03', 'HLA-A*31:04', 'HLA-A*31:05', 'HLA-A*31:06', 'HLA-A*31:07', 'HLA-A*31:08', 'HLA-A*31:09', 'HLA-A*31:10',
'HLA-A*31:11', 'HLA-A*31:12', 'HLA-A*31:13', 'HLA-A*31:15', 'HLA-A*31:16', 'HLA-A*31:17', 'HLA-A*31:18', 'HLA-A*31:19', 'HLA-A*31:20',
'HLA-A*31:21', 'HLA-A*31:22', 'HLA-A*31:23', 'HLA-A*31:24', 'HLA-A*31:25', 'HLA-A*31:26', 'HLA-A*31:27', 'HLA-A*31:28', 'HLA-A*31:29',
'HLA-A*31:30', 'HLA-A*31:31', 'HLA-A*31:32', 'HLA-A*31:33', 'HLA-A*31:34', 'HLA-A*31:35', 'HLA-A*31:36', 'HLA-A*31:37', 'HLA-A*32:01',
'HLA-A*32:02', 'HLA-A*32:03', 'HLA-A*32:04', 'HLA-A*32:05', 'HLA-A*32:06', 'HLA-A*32:07', 'HLA-A*32:08', 'HLA-A*32:09', 'HLA-A*32:10',
'HLA-A*32:12', 'HLA-A*32:13', 'HLA-A*32:14', 'HLA-A*32:15', 'HLA-A*32:16', 'HLA-A*32:17', 'HLA-A*32:18', 'HLA-A*32:20', 'HLA-A*32:21',
'HLA-A*32:22', 'HLA-A*32:23', 'HLA-A*32:24', 'HLA-A*32:25', 'HLA-A*33:01', 'HLA-A*33:03', 'HLA-A*33:04', 'HLA-A*33:05', 'HLA-A*33:06',
'HLA-A*33:07', 'HLA-A*33:08', 'HLA-A*33:09', 'HLA-A*33:10', 'HLA-A*33:11', 'HLA-A*33:12', 'HLA-A*33:13', 'HLA-A*33:14', 'HLA-A*33:15',
'HLA-A*33:16', 'HLA-A*33:17', 'HLA-A*33:18', 'HLA-A*33:19', 'HLA-A*33:20', 'HLA-A*33:21', 'HLA-A*33:22', 'HLA-A*33:23', 'HLA-A*33:24',
'HLA-A*33:25', 'HLA-A*33:26', 'HLA-A*33:27', 'HLA-A*33:28', 'HLA-A*33:29', 'HLA-A*33:30', 'HLA-A*33:31', 'HLA-A*34:01', 'HLA-A*34:02',
'HLA-A*34:03', 'HLA-A*34:04', 'HLA-A*34:05', 'HLA-A*34:06', 'HLA-A*34:07', 'HLA-A*34:08', 'HLA-A*36:01', 'HLA-A*36:02', 'HLA-A*36:03',
'HLA-A*36:04', 'HLA-A*36:05', 'HLA-A*43:01', 'HLA-A*66:01', 'HLA-A*66:02', 'HLA-A*66:03', 'HLA-A*66:04', 'HLA-A*66:05', 'HLA-A*66:06',
'HLA-A*66:07', 'HLA-A*66:08', 'HLA-A*66:09', 'HLA-A*66:10', 'HLA-A*66:11', 'HLA-A*66:12', 'HLA-A*66:13', 'HLA-A*66:14', 'HLA-A*66:15',
'HLA-A*68:01', 'HLA-A*68:02', 'HLA-A*68:03', 'HLA-A*68:04', 'HLA-A*68:05', 'HLA-A*68:06', 'HLA-A*68:07', 'HLA-A*68:08', 'HLA-A*68:09',
'HLA-A*68:10', 'HLA-A*68:12', 'HLA-A*68:13', 'HLA-A*68:14', 'HLA-A*68:15', 'HLA-A*68:16', 'HLA-A*68:17', 'HLA-A*68:19', 'HLA-A*68:20',
'HLA-A*68:21', 'HLA-A*68:22', 'HLA-A*68:23', 'HLA-A*68:24', 'HLA-A*68:25', 'HLA-A*68:26', 'HLA-A*68:27', 'HLA-A*68:28', 'HLA-A*68:29',
'HLA-A*68:30', 'HLA-A*68:31', 'HLA-A*68:32', 'HLA-A*68:33', 'HLA-A*68:34', 'HLA-A*68:35', 'HLA-A*68:36', 'HLA-A*68:37', 'HLA-A*68:38',
'HLA-A*68:39', 'HLA-A*68:40', 'HLA-A*68:41', 'HLA-A*68:42', 'HLA-A*68:43', 'HLA-A*68:44', 'HLA-A*68:45', 'HLA-A*68:46', 'HLA-A*68:47',
'HLA-A*68:48', 'HLA-A*68:50', 'HLA-A*68:51', 'HLA-A*68:52', 'HLA-A*68:53', 'HLA-A*68:54', 'HLA-A*69:01', 'HLA-A*74:01', 'HLA-A*74:02',
'HLA-A*74:03', 'HLA-A*74:04', 'HLA-A*74:05', 'HLA-A*74:06', 'HLA-A*74:07', 'HLA-A*74:08', 'HLA-A*74:09', 'HLA-A*74:10', 'HLA-A*74:11',
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'HLA-B*07:105', 'HLA-B*07:106', 'HLA-B*07:107', 'HLA-B*07:108', 'HLA-B*07:109', 'HLA-B*07:11', 'HLA-B*07:110', 'HLA-B*07:112',
'HLA-B*07:113', 'HLA-B*07:114', 'HLA-B*07:115', 'HLA-B*07:12', 'HLA-B*07:13', 'HLA-B*07:14', 'HLA-B*07:15', 'HLA-B*07:16', 'HLA-B*07:17',
'HLA-B*07:18', 'HLA-B*07:19', 'HLA-B*07:20', 'HLA-B*07:21', 'HLA-B*07:22', 'HLA-B*07:23', 'HLA-B*07:24', 'HLA-B*07:25', 'HLA-B*07:26',
'HLA-B*07:27', 'HLA-B*07:28', 'HLA-B*07:29', 'HLA-B*07:30', 'HLA-B*07:31', 'HLA-B*07:32', 'HLA-B*07:33', 'HLA-B*07:34', 'HLA-B*07:35',
'HLA-B*07:36', 'HLA-B*07:37', 'HLA-B*07:38', 'HLA-B*07:39', 'HLA-B*07:40', 'HLA-B*07:41', 'HLA-B*07:42', 'HLA-B*07:43', 'HLA-B*07:44',
'HLA-B*07:45', 'HLA-B*07:46', 'HLA-B*07:47', 'HLA-B*07:48', 'HLA-B*07:50', 'HLA-B*07:51', 'HLA-B*07:52', 'HLA-B*07:53', 'HLA-B*07:54',
'HLA-B*07:55', 'HLA-B*07:56', 'HLA-B*07:57', 'HLA-B*07:58', 'HLA-B*07:59', 'HLA-B*07:60', 'HLA-B*07:61', 'HLA-B*07:62', 'HLA-B*07:63',
'HLA-B*07:64', 'HLA-B*07:65', 'HLA-B*07:66', 'HLA-B*07:68', 'HLA-B*07:69', 'HLA-B*07:70', 'HLA-B*07:71', 'HLA-B*07:72', 'HLA-B*07:73',
'HLA-B*07:74', 'HLA-B*07:75', 'HLA-B*07:76', 'HLA-B*07:77', 'HLA-B*07:78', 'HLA-B*07:79', 'HLA-B*07:80', 'HLA-B*07:81', 'HLA-B*07:82',
'HLA-B*07:83', 'HLA-B*07:84', 'HLA-B*07:85', 'HLA-B*07:86', 'HLA-B*07:87', 'HLA-B*07:88', 'HLA-B*07:89', 'HLA-B*07:90', 'HLA-B*07:91',
'HLA-B*07:92', 'HLA-B*07:93', 'HLA-B*07:94', 'HLA-B*07:95', 'HLA-B*07:96', 'HLA-B*07:97', 'HLA-B*07:98', 'HLA-B*07:99', 'HLA-B*08:01',
'HLA-B*08:02', 'HLA-B*08:03', 'HLA-B*08:04', 'HLA-B*08:05', 'HLA-B*08:07', 'HLA-B*08:09', 'HLA-B*08:10', 'HLA-B*08:11', 'HLA-B*08:12',
'HLA-B*08:13', 'HLA-B*08:14', 'HLA-B*08:15', 'HLA-B*08:16', 'HLA-B*08:17', 'HLA-B*08:18', 'HLA-B*08:20', 'HLA-B*08:21', 'HLA-B*08:22',
'HLA-B*08:23', 'HLA-B*08:24', 'HLA-B*08:25', 'HLA-B*08:26', 'HLA-B*08:27', 'HLA-B*08:28', 'HLA-B*08:29', 'HLA-B*08:31', 'HLA-B*08:32',
'HLA-B*08:33', 'HLA-B*08:34', 'HLA-B*08:35', 'HLA-B*08:36', 'HLA-B*08:37', 'HLA-B*08:38', 'HLA-B*08:39', 'HLA-B*08:40', 'HLA-B*08:41',
'HLA-B*08:42', 'HLA-B*08:43', 'HLA-B*08:44', 'HLA-B*08:45', 'HLA-B*08:46', 'HLA-B*08:47', 'HLA-B*08:48', 'HLA-B*08:49', 'HLA-B*08:50',
'HLA-B*08:51', 'HLA-B*08:52', 'HLA-B*08:53', 'HLA-B*08:54', 'HLA-B*08:55', 'HLA-B*08:56', 'HLA-B*08:57', 'HLA-B*08:58', 'HLA-B*08:59',
'HLA-B*08:60', 'HLA-B*08:61', 'HLA-B*08:62', 'HLA-B*13:01', 'HLA-B*13:02', 'HLA-B*13:03', 'HLA-B*13:04', 'HLA-B*13:06', 'HLA-B*13:09',
'HLA-B*13:10', 'HLA-B*13:11', 'HLA-B*13:12', 'HLA-B*13:13', 'HLA-B*13:14', 'HLA-B*13:15', 'HLA-B*13:16', 'HLA-B*13:17', 'HLA-B*13:18',
'HLA-B*13:19', 'HLA-B*13:20', 'HLA-B*13:21', 'HLA-B*13:22', 'HLA-B*13:23', 'HLA-B*13:25', 'HLA-B*13:26', 'HLA-B*13:27', 'HLA-B*13:28',
'HLA-B*13:29', 'HLA-B*13:30', 'HLA-B*13:31', 'HLA-B*13:32', 'HLA-B*13:33', 'HLA-B*13:34', 'HLA-B*13:35', 'HLA-B*13:36', 'HLA-B*13:37',
'HLA-B*13:38', 'HLA-B*13:39', 'HLA-B*14:01', 'HLA-B*14:02', 'HLA-B*14:03', 'HLA-B*14:04', 'HLA-B*14:05', 'HLA-B*14:06', 'HLA-B*14:08',
'HLA-B*14:09', 'HLA-B*14:10', 'HLA-B*14:11', 'HLA-B*14:12', 'HLA-B*14:13', 'HLA-B*14:14', 'HLA-B*14:15', 'HLA-B*14:16', 'HLA-B*14:17',
'HLA-B*14:18', 'HLA-B*15:01', 'HLA-B*15:02', 'HLA-B*15:03', 'HLA-B*15:04', 'HLA-B*15:05', 'HLA-B*15:06', 'HLA-B*15:07', 'HLA-B*15:08',
'HLA-B*15:09', 'HLA-B*15:10', 'HLA-B*15:101', 'HLA-B*15:102', 'HLA-B*15:103', 'HLA-B*15:104', 'HLA-B*15:105', 'HLA-B*15:106',
'HLA-B*15:107', 'HLA-B*15:108', 'HLA-B*15:109', 'HLA-B*15:11', 'HLA-B*15:110', 'HLA-B*15:112', 'HLA-B*15:113', 'HLA-B*15:114',
'HLA-B*15:115', 'HLA-B*15:116', 'HLA-B*15:117', 'HLA-B*15:118', 'HLA-B*15:119', 'HLA-B*15:12', 'HLA-B*15:120', 'HLA-B*15:121',
'HLA-B*15:122', 'HLA-B*15:123', 'HLA-B*15:124', 'HLA-B*15:125', 'HLA-B*15:126', 'HLA-B*15:127', 'HLA-B*15:128', 'HLA-B*15:129',
'HLA-B*15:13', 'HLA-B*15:131', 'HLA-B*15:132', 'HLA-B*15:133', 'HLA-B*15:134', 'HLA-B*15:135', 'HLA-B*15:136', 'HLA-B*15:137',
'HLA-B*15:138', 'HLA-B*15:139', 'HLA-B*15:14', 'HLA-B*15:140', 'HLA-B*15:141', 'HLA-B*15:142', 'HLA-B*15:143', 'HLA-B*15:144',
'HLA-B*15:145', 'HLA-B*15:146', 'HLA-B*15:147', 'HLA-B*15:148', 'HLA-B*15:15', 'HLA-B*15:150', 'HLA-B*15:151', 'HLA-B*15:152',
'HLA-B*15:153', 'HLA-B*15:154', 'HLA-B*15:155', 'HLA-B*15:156', 'HLA-B*15:157', 'HLA-B*15:158', 'HLA-B*15:159', 'HLA-B*15:16',
'HLA-B*15:160', 'HLA-B*15:161', 'HLA-B*15:162', 'HLA-B*15:163', 'HLA-B*15:164', 'HLA-B*15:165', 'HLA-B*15:166', 'HLA-B*15:167',
'HLA-B*15:168', 'HLA-B*15:169', 'HLA-B*15:17', 'HLA-B*15:170', 'HLA-B*15:171', 'HLA-B*15:172', 'HLA-B*15:173', 'HLA-B*15:174',
'HLA-B*15:175', 'HLA-B*15:176', 'HLA-B*15:177', 'HLA-B*15:178', 'HLA-B*15:179', 'HLA-B*15:18', 'HLA-B*15:180', 'HLA-B*15:183',
'HLA-B*15:184', 'HLA-B*15:185', 'HLA-B*15:186', 'HLA-B*15:187', 'HLA-B*15:188', 'HLA-B*15:189', 'HLA-B*15:19', 'HLA-B*15:191',
'HLA-B*15:192', 'HLA-B*15:193', 'HLA-B*15:194', 'HLA-B*15:195', 'HLA-B*15:196', 'HLA-B*15:197', 'HLA-B*15:198', 'HLA-B*15:199',
'HLA-B*15:20', 'HLA-B*15:200', 'HLA-B*15:201', 'HLA-B*15:202', 'HLA-B*15:21', 'HLA-B*15:23', 'HLA-B*15:24', 'HLA-B*15:25', 'HLA-B*15:27',
'HLA-B*15:28', 'HLA-B*15:29', 'HLA-B*15:30', 'HLA-B*15:31', 'HLA-B*15:32', 'HLA-B*15:33', 'HLA-B*15:34', 'HLA-B*15:35', 'HLA-B*15:36',
'HLA-B*15:37', 'HLA-B*15:38', 'HLA-B*15:39', 'HLA-B*15:40', 'HLA-B*15:42', 'HLA-B*15:43', 'HLA-B*15:44', 'HLA-B*15:45', 'HLA-B*15:46',
'HLA-B*15:47', 'HLA-B*15:48', 'HLA-B*15:49', 'HLA-B*15:50', 'HLA-B*15:51', 'HLA-B*15:52', 'HLA-B*15:53', 'HLA-B*15:54', 'HLA-B*15:55',
'HLA-B*15:56', 'HLA-B*15:57', 'HLA-B*15:58', 'HLA-B*15:60', 'HLA-B*15:61', 'HLA-B*15:62', 'HLA-B*15:63', 'HLA-B*15:64', 'HLA-B*15:65',
'HLA-B*15:66', 'HLA-B*15:67', 'HLA-B*15:68', 'HLA-B*15:69', 'HLA-B*15:70', 'HLA-B*15:71', 'HLA-B*15:72', 'HLA-B*15:73', 'HLA-B*15:74',
'HLA-B*15:75', 'HLA-B*15:76', 'HLA-B*15:77', 'HLA-B*15:78', 'HLA-B*15:80', 'HLA-B*15:81', 'HLA-B*15:82', 'HLA-B*15:83', 'HLA-B*15:84',
'HLA-B*15:85', 'HLA-B*15:86', 'HLA-B*15:87', 'HLA-B*15:88', 'HLA-B*15:89', 'HLA-B*15:90', 'HLA-B*15:91', 'HLA-B*15:92', 'HLA-B*15:93',
'HLA-B*15:95', 'HLA-B*15:96', 'HLA-B*15:97', 'HLA-B*15:98', 'HLA-B*15:99', 'HLA-B*18:01', 'HLA-B*18:02', 'HLA-B*18:03', 'HLA-B*18:04',
'HLA-B*18:05', 'HLA-B*18:06', 'HLA-B*18:07', 'HLA-B*18:08', 'HLA-B*18:09', 'HLA-B*18:10', 'HLA-B*18:11', 'HLA-B*18:12', 'HLA-B*18:13',
'HLA-B*18:14', 'HLA-B*18:15', 'HLA-B*18:18', 'HLA-B*18:19', 'HLA-B*18:20', 'HLA-B*18:21', 'HLA-B*18:22', 'HLA-B*18:24', 'HLA-B*18:25',
'HLA-B*18:26', 'HLA-B*18:27', 'HLA-B*18:28', 'HLA-B*18:29', 'HLA-B*18:30', 'HLA-B*18:31', 'HLA-B*18:32', 'HLA-B*18:33', 'HLA-B*18:34',
'HLA-B*18:35', 'HLA-B*18:36', 'HLA-B*18:37', 'HLA-B*18:38', 'HLA-B*18:39', 'HLA-B*18:40', 'HLA-B*18:41', 'HLA-B*18:42', 'HLA-B*18:43',
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'HLA-B*54:11', 'HLA-B*54:12', 'HLA-B*54:13', 'HLA-B*54:14', 'HLA-B*54:15', 'HLA-B*54:16', 'HLA-B*54:17', 'HLA-B*54:18', 'HLA-B*54:19',
'HLA-B*54:20', 'HLA-B*54:21', 'HLA-B*54:22', 'HLA-B*54:23', 'HLA-B*55:01', 'HLA-B*55:02', 'HLA-B*55:03', 'HLA-B*55:04', 'HLA-B*55:05',
'HLA-B*55:07', 'HLA-B*55:08', 'HLA-B*55:09', 'HLA-B*55:10', 'HLA-B*55:11', 'HLA-B*55:12', 'HLA-B*55:13', 'HLA-B*55:14', 'HLA-B*55:15',
'HLA-B*55:16', 'HLA-B*55:17', 'HLA-B*55:18', 'HLA-B*55:19', 'HLA-B*55:20', 'HLA-B*55:21', 'HLA-B*55:22', 'HLA-B*55:23', 'HLA-B*55:24',
'HLA-B*55:25', 'HLA-B*55:26', 'HLA-B*55:27', 'HLA-B*55:28', 'HLA-B*55:29', 'HLA-B*55:30', 'HLA-B*55:31', 'HLA-B*55:32', 'HLA-B*55:33',
'HLA-B*55:34', 'HLA-B*55:35', 'HLA-B*55:36', 'HLA-B*55:37', 'HLA-B*55:38', 'HLA-B*55:39', 'HLA-B*55:40', 'HLA-B*55:41', 'HLA-B*55:42',
'HLA-B*55:43', 'HLA-B*56:01', 'HLA-B*56:02', 'HLA-B*56:03', 'HLA-B*56:04', 'HLA-B*56:05', 'HLA-B*56:06', 'HLA-B*56:07', 'HLA-B*56:08',
'HLA-B*56:09', 'HLA-B*56:10', 'HLA-B*56:11', 'HLA-B*56:12', 'HLA-B*56:13', 'HLA-B*56:14', 'HLA-B*56:15', 'HLA-B*56:16', 'HLA-B*56:17',
'HLA-B*56:18', 'HLA-B*56:20', 'HLA-B*56:21', 'HLA-B*56:22', 'HLA-B*56:23', 'HLA-B*56:24', 'HLA-B*56:25', 'HLA-B*56:26', 'HLA-B*56:27',
'HLA-B*56:29', 'HLA-B*57:01', 'HLA-B*57:02', 'HLA-B*57:03', 'HLA-B*57:04', 'HLA-B*57:05', 'HLA-B*57:06', 'HLA-B*57:07', 'HLA-B*57:08',
'HLA-B*57:09', 'HLA-B*57:10', 'HLA-B*57:11', 'HLA-B*57:12', 'HLA-B*57:13', 'HLA-B*57:14', 'HLA-B*57:15', 'HLA-B*57:16', 'HLA-B*57:17',
'HLA-B*57:18', 'HLA-B*57:19', 'HLA-B*57:20', 'HLA-B*57:21', 'HLA-B*57:22', 'HLA-B*57:23', 'HLA-B*57:24', 'HLA-B*57:25', 'HLA-B*57:26',
'HLA-B*57:27', 'HLA-B*57:29', 'HLA-B*57:30', 'HLA-B*57:31', 'HLA-B*57:32', 'HLA-B*58:01', 'HLA-B*58:02', 'HLA-B*58:04', 'HLA-B*58:05',
'HLA-B*58:06', 'HLA-B*58:07', 'HLA-B*58:08', 'HLA-B*58:09', 'HLA-B*58:11', 'HLA-B*58:12', 'HLA-B*58:13', 'HLA-B*58:14', 'HLA-B*58:15',
'HLA-B*58:16', 'HLA-B*58:18', 'HLA-B*58:19', 'HLA-B*58:20', 'HLA-B*58:21', 'HLA-B*58:22', 'HLA-B*58:23', 'HLA-B*58:24', 'HLA-B*58:25',
'HLA-B*58:26', 'HLA-B*58:27', 'HLA-B*58:28', 'HLA-B*58:29', 'HLA-B*58:30', 'HLA-B*59:01', 'HLA-B*59:02', 'HLA-B*59:03', 'HLA-B*59:04',
'HLA-B*59:05', 'HLA-B*67:01', 'HLA-B*67:02', 'HLA-B*73:01', 'HLA-B*73:02', 'HLA-B*78:01', 'HLA-B*78:02', 'HLA-B*78:03', 'HLA-B*78:04',
'HLA-B*78:05', 'HLA-B*78:06', 'HLA-B*78:07', 'HLA-B*81:01', 'HLA-B*81:02', 'HLA-B*81:03', 'HLA-B*81:05', 'HLA-B*82:01', 'HLA-B*82:02',
'HLA-B*82:03', 'HLA-B*83:01', 'HLA-C*01:02', 'HLA-C*01:03', 'HLA-C*01:04', 'HLA-C*01:05', 'HLA-C*01:06', 'HLA-C*01:07', 'HLA-C*01:08',
'HLA-C*01:09', 'HLA-C*01:10', 'HLA-C*01:11', 'HLA-C*01:12', 'HLA-C*01:13', 'HLA-C*01:14', 'HLA-C*01:15', 'HLA-C*01:16', 'HLA-C*01:17',
'HLA-C*01:18', 'HLA-C*01:19', 'HLA-C*01:20', 'HLA-C*01:21', 'HLA-C*01:22', 'HLA-C*01:23', 'HLA-C*01:24', 'HLA-C*01:25', 'HLA-C*01:26',
'HLA-C*01:27', 'HLA-C*01:28', 'HLA-C*01:29', 'HLA-C*01:30', 'HLA-C*01:31', 'HLA-C*01:32', 'HLA-C*01:33', 'HLA-C*01:34', 'HLA-C*01:35',
'HLA-C*01:36', 'HLA-C*01:38', 'HLA-C*01:39', 'HLA-C*01:40', 'HLA-C*02:02', 'HLA-C*02:03', 'HLA-C*02:04', 'HLA-C*02:05', 'HLA-C*02:06',
'HLA-C*02:07', 'HLA-C*02:08', 'HLA-C*02:09', 'HLA-C*02:10', 'HLA-C*02:11', 'HLA-C*02:12', 'HLA-C*02:13', 'HLA-C*02:14', 'HLA-C*02:15',
'HLA-C*02:16', 'HLA-C*02:17', 'HLA-C*02:18', 'HLA-C*02:19', 'HLA-C*02:20', 'HLA-C*02:21', 'HLA-C*02:22', 'HLA-C*02:23', 'HLA-C*02:24',
'HLA-C*02:26', 'HLA-C*02:27', 'HLA-C*02:28', 'HLA-C*02:29', 'HLA-C*02:30', 'HLA-C*02:31', 'HLA-C*02:32', 'HLA-C*02:33', 'HLA-C*02:34',
'HLA-C*02:35', 'HLA-C*02:36', 'HLA-C*02:37', 'HLA-C*02:39', 'HLA-C*02:40', 'HLA-C*03:01', 'HLA-C*03:02', 'HLA-C*03:03', 'HLA-C*03:04',
'HLA-C*03:05', 'HLA-C*03:06', 'HLA-C*03:07', 'HLA-C*03:08', 'HLA-C*03:09', 'HLA-C*03:10', 'HLA-C*03:11', 'HLA-C*03:12', 'HLA-C*03:13',
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'HLA-C*03:25', 'HLA-C*03:26', 'HLA-C*03:27', 'HLA-C*03:28', 'HLA-C*03:29', 'HLA-C*03:30', 'HLA-C*03:31', 'HLA-C*03:32', 'HLA-C*03:33',
'HLA-C*03:34', 'HLA-C*03:35', 'HLA-C*03:36', 'HLA-C*03:37', 'HLA-C*03:38', 'HLA-C*03:39', 'HLA-C*03:40', 'HLA-C*03:41', 'HLA-C*03:42',
'HLA-C*03:43', 'HLA-C*03:44', 'HLA-C*03:45', 'HLA-C*03:46', 'HLA-C*03:47', 'HLA-C*03:48', 'HLA-C*03:49', 'HLA-C*03:50', 'HLA-C*03:51',
'HLA-C*03:52', 'HLA-C*03:53', 'HLA-C*03:54', 'HLA-C*03:55', 'HLA-C*03:56', 'HLA-C*03:57', 'HLA-C*03:58', 'HLA-C*03:59', 'HLA-C*03:60',
'HLA-C*03:61', 'HLA-C*03:62', 'HLA-C*03:63', 'HLA-C*03:64', 'HLA-C*03:65', 'HLA-C*03:66', 'HLA-C*03:67', 'HLA-C*03:68', 'HLA-C*03:69',
'HLA-C*03:70', 'HLA-C*03:71', 'HLA-C*03:72', 'HLA-C*03:73', 'HLA-C*03:74', 'HLA-C*03:75', 'HLA-C*03:76', 'HLA-C*03:77', 'HLA-C*03:78',
'HLA-C*03:79', 'HLA-C*03:80', 'HLA-C*03:81', 'HLA-C*03:82', 'HLA-C*03:83', 'HLA-C*03:84', 'HLA-C*03:85', 'HLA-C*03:86', 'HLA-C*03:87',
'HLA-C*03:88', 'HLA-C*03:89', 'HLA-C*03:90', 'HLA-C*03:91', 'HLA-C*03:92', 'HLA-C*03:93', 'HLA-C*03:94', 'HLA-C*04:01', 'HLA-C*04:03',
'HLA-C*04:04', 'HLA-C*04:05', 'HLA-C*04:06', 'HLA-C*04:07', 'HLA-C*04:08', 'HLA-C*04:10', 'HLA-C*04:11', 'HLA-C*04:12', 'HLA-C*04:13',
'HLA-C*04:14', 'HLA-C*04:15', 'HLA-C*04:16', 'HLA-C*04:17', 'HLA-C*04:18', 'HLA-C*04:19', 'HLA-C*04:20', 'HLA-C*04:23', 'HLA-C*04:24',
'HLA-C*04:25', 'HLA-C*04:26', 'HLA-C*04:27', 'HLA-C*04:28', 'HLA-C*04:29', 'HLA-C*04:30', 'HLA-C*04:31', 'HLA-C*04:32', 'HLA-C*04:33',
'HLA-C*04:34', 'HLA-C*04:35', 'HLA-C*04:36', 'HLA-C*04:37', 'HLA-C*04:38', 'HLA-C*04:39', 'HLA-C*04:40', 'HLA-C*04:41', 'HLA-C*04:42',
'HLA-C*04:43', 'HLA-C*04:44', 'HLA-C*04:45', 'HLA-C*04:46', 'HLA-C*04:47', 'HLA-C*04:48', 'HLA-C*04:49', 'HLA-C*04:50', 'HLA-C*04:51',
'HLA-C*04:52', 'HLA-C*04:53', 'HLA-C*04:54', 'HLA-C*04:55', 'HLA-C*04:56', 'HLA-C*04:57', 'HLA-C*04:58', 'HLA-C*04:60', 'HLA-C*04:61',
'HLA-C*04:62', 'HLA-C*04:63', 'HLA-C*04:64', 'HLA-C*04:65', 'HLA-C*04:66', 'HLA-C*04:67', 'HLA-C*04:68', 'HLA-C*04:69', 'HLA-C*04:70',
'HLA-C*05:01', 'HLA-C*05:03', 'HLA-C*05:04', 'HLA-C*05:05', 'HLA-C*05:06', 'HLA-C*05:08', 'HLA-C*05:09', 'HLA-C*05:10', 'HLA-C*05:11',
'HLA-C*05:12', 'HLA-C*05:13', 'HLA-C*05:14', 'HLA-C*05:15', 'HLA-C*05:16', 'HLA-C*05:17', 'HLA-C*05:18', 'HLA-C*05:19', 'HLA-C*05:20',
'HLA-C*05:21', 'HLA-C*05:22', 'HLA-C*05:23', 'HLA-C*05:24', 'HLA-C*05:25', 'HLA-C*05:26', 'HLA-C*05:27', 'HLA-C*05:28', 'HLA-C*05:29',
'HLA-C*05:30', 'HLA-C*05:31', 'HLA-C*05:32', 'HLA-C*05:33', 'HLA-C*05:34', 'HLA-C*05:35', 'HLA-C*05:36', 'HLA-C*05:37', 'HLA-C*05:38',
'HLA-C*05:39', 'HLA-C*05:40', 'HLA-C*05:41', 'HLA-C*05:42', 'HLA-C*05:43', 'HLA-C*05:44', 'HLA-C*05:45', 'HLA-C*06:02', 'HLA-C*06:03',
'HLA-C*06:04', 'HLA-C*06:05', 'HLA-C*06:06', 'HLA-C*06:07', 'HLA-C*06:08', 'HLA-C*06:09', 'HLA-C*06:10', 'HLA-C*06:11', 'HLA-C*06:12',
'HLA-C*06:13', 'HLA-C*06:14', 'HLA-C*06:15', 'HLA-C*06:17', 'HLA-C*06:18', 'HLA-C*06:19', 'HLA-C*06:20', 'HLA-C*06:21', 'HLA-C*06:22',
'HLA-C*06:23', 'HLA-C*06:24', 'HLA-C*06:25', 'HLA-C*06:26', 'HLA-C*06:27', 'HLA-C*06:28', 'HLA-C*06:29', 'HLA-C*06:30', 'HLA-C*06:31',
'HLA-C*06:32', 'HLA-C*06:33', 'HLA-C*06:34', 'HLA-C*06:35', 'HLA-C*06:36', 'HLA-C*06:37', 'HLA-C*06:38', 'HLA-C*06:39', 'HLA-C*06:40',
'HLA-C*06:41', 'HLA-C*06:42', 'HLA-C*06:43', 'HLA-C*06:44', 'HLA-C*06:45', 'HLA-C*07:01', 'HLA-C*07:02', 'HLA-C*07:03', 'HLA-C*07:04',
'HLA-C*07:05', 'HLA-C*07:06', 'HLA-C*07:07', 'HLA-C*07:08', 'HLA-C*07:09', 'HLA-C*07:10', 'HLA-C*07:100', 'HLA-C*07:101', 'HLA-C*07:102',
'HLA-C*07:103', 'HLA-C*07:105', 'HLA-C*07:106', 'HLA-C*07:107', 'HLA-C*07:108', 'HLA-C*07:109', 'HLA-C*07:11', 'HLA-C*07:110',
'HLA-C*07:111', 'HLA-C*07:112', 'HLA-C*07:113', 'HLA-C*07:114', 'HLA-C*07:115', 'HLA-C*07:116', 'HLA-C*07:117', 'HLA-C*07:118',
'HLA-C*07:119', 'HLA-C*07:12', 'HLA-C*07:120', 'HLA-C*07:122', 'HLA-C*07:123', 'HLA-C*07:124', 'HLA-C*07:125', 'HLA-C*07:126',
'HLA-C*07:127', 'HLA-C*07:128', 'HLA-C*07:129', 'HLA-C*07:13', 'HLA-C*07:130', 'HLA-C*07:131', 'HLA-C*07:132', 'HLA-C*07:133',
'HLA-C*07:134', 'HLA-C*07:135', 'HLA-C*07:136', 'HLA-C*07:137', 'HLA-C*07:138', 'HLA-C*07:139', 'HLA-C*07:14', 'HLA-C*07:140',
'HLA-C*07:141', 'HLA-C*07:142', 'HLA-C*07:143', 'HLA-C*07:144', 'HLA-C*07:145', 'HLA-C*07:146', 'HLA-C*07:147', 'HLA-C*07:148',
'HLA-C*07:149', 'HLA-C*07:15', 'HLA-C*07:16', 'HLA-C*07:17', 'HLA-C*07:18', 'HLA-C*07:19', 'HLA-C*07:20', 'HLA-C*07:21', 'HLA-C*07:22',
'HLA-C*07:23', 'HLA-C*07:24', 'HLA-C*07:25', 'HLA-C*07:26', 'HLA-C*07:27', 'HLA-C*07:28', 'HLA-C*07:29', 'HLA-C*07:30', 'HLA-C*07:31',
'HLA-C*07:35', 'HLA-C*07:36', 'HLA-C*07:37', 'HLA-C*07:38', 'HLA-C*07:39', 'HLA-C*07:40', 'HLA-C*07:41', 'HLA-C*07:42', 'HLA-C*07:43',
'HLA-C*07:44', 'HLA-C*07:45', 'HLA-C*07:46', 'HLA-C*07:47', 'HLA-C*07:48', 'HLA-C*07:49', 'HLA-C*07:50', 'HLA-C*07:51', 'HLA-C*07:52',
'HLA-C*07:53', 'HLA-C*07:54', 'HLA-C*07:56', 'HLA-C*07:57', 'HLA-C*07:58', 'HLA-C*07:59', 'HLA-C*07:60', 'HLA-C*07:62', 'HLA-C*07:63',
'HLA-C*07:64', 'HLA-C*07:65', 'HLA-C*07:66', 'HLA-C*07:67', 'HLA-C*07:68', 'HLA-C*07:69', 'HLA-C*07:70', 'HLA-C*07:71', 'HLA-C*07:72',
'HLA-C*07:73', 'HLA-C*07:74', 'HLA-C*07:75', 'HLA-C*07:76', 'HLA-C*07:77', 'HLA-C*07:78', 'HLA-C*07:79', 'HLA-C*07:80', 'HLA-C*07:81',
'HLA-C*07:82', 'HLA-C*07:83', 'HLA-C*07:84', 'HLA-C*07:85', 'HLA-C*07:86', 'HLA-C*07:87', 'HLA-C*07:88', 'HLA-C*07:89', 'HLA-C*07:90',
'HLA-C*07:91', 'HLA-C*07:92', 'HLA-C*07:93', 'HLA-C*07:94', 'HLA-C*07:95', 'HLA-C*07:96', 'HLA-C*07:97', 'HLA-C*07:99', 'HLA-C*08:01',
'HLA-C*08:02', 'HLA-C*08:03', 'HLA-C*08:04', 'HLA-C*08:05', 'HLA-C*08:06', 'HLA-C*08:07', 'HLA-C*08:08', 'HLA-C*08:09', 'HLA-C*08:10',
'HLA-C*08:11', 'HLA-C*08:12', 'HLA-C*08:13', 'HLA-C*08:14', 'HLA-C*08:15', 'HLA-C*08:16', 'HLA-C*08:17', 'HLA-C*08:18', 'HLA-C*08:19',
'HLA-C*08:20', 'HLA-C*08:21', 'HLA-C*08:22', 'HLA-C*08:23', 'HLA-C*08:24', 'HLA-C*08:25', 'HLA-C*08:27', 'HLA-C*08:28', 'HLA-C*08:29',
'HLA-C*08:30', 'HLA-C*08:31', 'HLA-C*08:32', 'HLA-C*08:33', 'HLA-C*08:34', 'HLA-C*08:35', 'HLA-C*12:02', 'HLA-C*12:03', 'HLA-C*12:04',
'HLA-C*12:05', 'HLA-C*12:06', 'HLA-C*12:07', 'HLA-C*12:08', 'HLA-C*12:09', 'HLA-C*12:10', 'HLA-C*12:11', 'HLA-C*12:12', 'HLA-C*12:13',
'HLA-C*12:14', 'HLA-C*12:15', 'HLA-C*12:16', 'HLA-C*12:17', 'HLA-C*12:18', 'HLA-C*12:19', 'HLA-C*12:20', 'HLA-C*12:21', 'HLA-C*12:22',
'HLA-C*12:23', 'HLA-C*12:24', 'HLA-C*12:25', 'HLA-C*12:26', 'HLA-C*12:27', 'HLA-C*12:28', 'HLA-C*12:29', 'HLA-C*12:30', 'HLA-C*12:31',
'HLA-C*12:32', 'HLA-C*12:33', 'HLA-C*12:34', 'HLA-C*12:35', 'HLA-C*12:36', 'HLA-C*12:37', 'HLA-C*12:38', 'HLA-C*12:40', 'HLA-C*12:41',
'HLA-C*12:43', 'HLA-C*12:44', 'HLA-C*14:02', 'HLA-C*14:03', 'HLA-C*14:04', 'HLA-C*14:05', 'HLA-C*14:06', 'HLA-C*14:08', 'HLA-C*14:09',
'HLA-C*14:10', 'HLA-C*14:11', 'HLA-C*14:12', 'HLA-C*14:13', 'HLA-C*14:14', 'HLA-C*14:15', 'HLA-C*14:16', 'HLA-C*14:17', 'HLA-C*14:18',
'HLA-C*14:19', 'HLA-C*14:20', 'HLA-C*15:02', 'HLA-C*15:03', 'HLA-C*15:04', 'HLA-C*15:05', 'HLA-C*15:06', 'HLA-C*15:07', 'HLA-C*15:08',
'HLA-C*15:09', 'HLA-C*15:10', 'HLA-C*15:11', 'HLA-C*15:12', 'HLA-C*15:13', 'HLA-C*15:15', 'HLA-C*15:16', 'HLA-C*15:17', 'HLA-C*15:18',
'HLA-C*15:19', 'HLA-C*15:20', 'HLA-C*15:21', 'HLA-C*15:22', 'HLA-C*15:23', 'HLA-C*15:24', 'HLA-C*15:25', 'HLA-C*15:26', 'HLA-C*15:27',
'HLA-C*15:28', 'HLA-C*15:29', 'HLA-C*15:30', 'HLA-C*15:31', 'HLA-C*15:33', 'HLA-C*15:34', 'HLA-C*15:35', 'HLA-C*16:01', 'HLA-C*16:02',
'HLA-C*16:04', 'HLA-C*16:06', 'HLA-C*16:07', 'HLA-C*16:08', 'HLA-C*16:09', 'HLA-C*16:10', 'HLA-C*16:11', 'HLA-C*16:12', 'HLA-C*16:13',
'HLA-C*16:14', 'HLA-C*16:15', 'HLA-C*16:17', 'HLA-C*16:18', 'HLA-C*16:19', 'HLA-C*16:20', 'HLA-C*16:21', 'HLA-C*16:22', 'HLA-C*16:23',
'HLA-C*16:24', 'HLA-C*16:25', 'HLA-C*16:26', 'HLA-C*17:01', 'HLA-C*17:02', 'HLA-C*17:03', 'HLA-C*17:04', 'HLA-C*17:05', 'HLA-C*17:06',
'HLA-C*17:07', 'HLA-C*18:01', 'HLA-C*18:02', 'HLA-C*18:03', 'HLA-E*01:01', 'HLA-G*01:01', 'HLA-G*01:02', 'HLA-G*01:03', 'HLA-G*01:04',
'HLA-G*01:06', 'HLA-G*01:07', 'HLA-G*01:08', 'HLA-G*01:09',
'H2-Db', 'H2-Dd', 'H2-Kb', 'H2-Kd', 'H2-Kk', 'H2-Ld'])
__version = "2.4"
@property
def version(self):
"""The version of the predictor"""
return self.__version
@property
def supportedAlleles(self):
"""
A list of valid :class:`~epytope.Core.Allele.Allele` models
"""
return self.__alleles
@property
def name(self):
"""The name of the predictor"""
return self.__name
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
else:
return "HLA-%s%s:%s" % (allele.locus, allele.supertype, allele.subtype)
def convert_alleles(self, alleles):
"""
Converts :class:`~epytope.Core.Allele.Allele` into the internal :class:`~epytope.Core.Allele.Allele` representation
of the predictor and returns a string representation
:param alleles: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: Returns a string representation of the input :class:`~epytope.Core.Allele.Allele`
:rtype: list(str)
"""
return [self._represent(a) for a in alleles]
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(dict)
with open(file, "r") as f:
f = csv.reader(f, delimiter='\t')
alleles = f.next()[3:-1]
ic_pos = 3
for row in f:
pep_seq = row[1]
for i, a in enumerate(alleles):
result[a][pep_seq] = float(row[ic_pos + i])
return result
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`self.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: str
"""
# can not be determined netmhcpan does not support --version or similar
return None
def prepare_input(self, input, file):
"""
Prepares input for external tools and writes them to file in the specific format
NO return value!
:param: list(str) input: The :class:`~epytope.Core.Peptide.Peptide` sequences to write into file
:param File file: File-handler to input file for external tool
"""
file.write("\n".join(input))
class NetMHCpan_2_8(AExternalEpitopePrediction):
"""
Implements the NetMHC binding (in current form for netMHCpan 2.8).
Supported MHC alleles currently only restricted to HLA alleles.
.. note::
Nielsen, Morten, et al. "NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and-B
locus protein of known sequence." PloS one 2.8 (2007): e796.
"""
__version = "2.8"
__supported_length = frozenset([8, 9, 10, 11, 12, 13, 14])
__name = "netmhcpan"
__command = "netMHCpan -p {peptides} -a {alleles} {options} -ic50 -xls -xlsfile {out}"
__alleles = frozenset(
['HLA-A*01:01', 'HLA-A*01:02', 'HLA-A*01:03', 'HLA-A*01:06', 'HLA-A*01:07', 'HLA-A*01:08', 'HLA-A*01:09', 'HLA-A*01:10', 'HLA-A*01:12',
'HLA-A*01:13', 'HLA-A*01:14', 'HLA-A*01:17', 'HLA-A*01:19', 'HLA-A*01:20', 'HLA-A*01:21', 'HLA-A*01:23', 'HLA-A*01:24', 'HLA-A*01:25',
'HLA-A*01:26', 'HLA-A*01:28', 'HLA-A*01:29', 'HLA-A*01:30', 'HLA-A*01:32', 'HLA-A*01:33', 'HLA-A*01:35', 'HLA-A*01:36', 'HLA-A*01:37',
'HLA-A*01:38', 'HLA-A*01:39', 'HLA-A*01:40', 'HLA-A*01:41', 'HLA-A*01:42', 'HLA-A*01:43', 'HLA-A*01:44', 'HLA-A*01:45', 'HLA-A*01:46',
'HLA-A*01:47', 'HLA-A*01:48', 'HLA-A*01:49', 'HLA-A*01:50', 'HLA-A*01:51', 'HLA-A*01:54', 'HLA-A*01:55', 'HLA-A*01:58', 'HLA-A*01:59',
'HLA-A*01:60', 'HLA-A*01:61', 'HLA-A*01:62', 'HLA-A*01:63', 'HLA-A*01:64', 'HLA-A*01:65', 'HLA-A*01:66', 'HLA-A*02:01', 'HLA-A*02:02',
'HLA-A*02:03', 'HLA-A*02:04', 'HLA-A*02:05', 'HLA-A*02:06', 'HLA-A*02:07', 'HLA-A*02:08', 'HLA-A*02:09', 'HLA-A*02:10', 'HLA-A*02:101',
'HLA-A*02:102', 'HLA-A*02:103', 'HLA-A*02:104', 'HLA-A*02:105', 'HLA-A*02:106', 'HLA-A*02:107', 'HLA-A*02:108', 'HLA-A*02:109',
'HLA-A*02:11', 'HLA-A*02:110', 'HLA-A*02:111', 'HLA-A*02:112', 'HLA-A*02:114', 'HLA-A*02:115', 'HLA-A*02:116', 'HLA-A*02:117',
'HLA-A*02:118', 'HLA-A*02:119', 'HLA-A*02:12', 'HLA-A*02:120', 'HLA-A*02:121', 'HLA-A*02:122', 'HLA-A*02:123', 'HLA-A*02:124',
'HLA-A*02:126', 'HLA-A*02:127', 'HLA-A*02:128', 'HLA-A*02:129', 'HLA-A*02:13', 'HLA-A*02:130', 'HLA-A*02:131', 'HLA-A*02:132',
'HLA-A*02:133', 'HLA-A*02:134', 'HLA-A*02:135', 'HLA-A*02:136', 'HLA-A*02:137', 'HLA-A*02:138', 'HLA-A*02:139', 'HLA-A*02:14',
'HLA-A*02:140', 'HLA-A*02:141', 'HLA-A*02:142', 'HLA-A*02:143', 'HLA-A*02:144', 'HLA-A*02:145', 'HLA-A*02:146', 'HLA-A*02:147',
'HLA-A*02:148', 'HLA-A*02:149', 'HLA-A*02:150', 'HLA-A*02:151', 'HLA-A*02:152', 'HLA-A*02:153', 'HLA-A*02:154', 'HLA-A*02:155',
'HLA-A*02:156', 'HLA-A*02:157', 'HLA-A*02:158', 'HLA-A*02:159', 'HLA-A*02:16', 'HLA-A*02:160', 'HLA-A*02:161', 'HLA-A*02:162',
'HLA-A*02:163', 'HLA-A*02:164', 'HLA-A*02:165', 'HLA-A*02:166', 'HLA-A*02:167', 'HLA-A*02:168', 'HLA-A*02:169', 'HLA-A*02:17',
'HLA-A*02:170', 'HLA-A*02:171', 'HLA-A*02:172', 'HLA-A*02:173', 'HLA-A*02:174', 'HLA-A*02:175', 'HLA-A*02:176', 'HLA-A*02:177',
'HLA-A*02:178', 'HLA-A*02:179', 'HLA-A*02:18', 'HLA-A*02:180', 'HLA-A*02:181', 'HLA-A*02:182', 'HLA-A*02:183', 'HLA-A*02:184',
'HLA-A*02:185', 'HLA-A*02:186', 'HLA-A*02:187', 'HLA-A*02:188', 'HLA-A*02:189', 'HLA-A*02:19', 'HLA-A*02:190', 'HLA-A*02:191',
'HLA-A*02:192', 'HLA-A*02:193', 'HLA-A*02:194', 'HLA-A*02:195', 'HLA-A*02:196', 'HLA-A*02:197', 'HLA-A*02:198', 'HLA-A*02:199',
'HLA-A*02:20', 'HLA-A*02:200', 'HLA-A*02:201', 'HLA-A*02:202', 'HLA-A*02:203', 'HLA-A*02:204', 'HLA-A*02:205', 'HLA-A*02:206',
'HLA-A*02:207', 'HLA-A*02:208', 'HLA-A*02:209', 'HLA-A*02:21', 'HLA-A*02:210', 'HLA-A*02:211', 'HLA-A*02:212', 'HLA-A*02:213',
'HLA-A*02:214', 'HLA-A*02:215', 'HLA-A*02:216', 'HLA-A*02:217', 'HLA-A*02:218', 'HLA-A*02:219', 'HLA-A*02:22', 'HLA-A*02:220',
'HLA-A*02:221', 'HLA-A*02:224', 'HLA-A*02:228', 'HLA-A*02:229', 'HLA-A*02:230', 'HLA-A*02:231', 'HLA-A*02:232', 'HLA-A*02:233',
'HLA-A*02:234', 'HLA-A*02:235', 'HLA-A*02:236', 'HLA-A*02:237', 'HLA-A*02:238', 'HLA-A*02:239', 'HLA-A*02:24', 'HLA-A*02:240',
'HLA-A*02:241', 'HLA-A*02:242', 'HLA-A*02:243', 'HLA-A*02:244', 'HLA-A*02:245', 'HLA-A*02:246', 'HLA-A*02:247', 'HLA-A*02:248',
'HLA-A*02:249', 'HLA-A*02:25', 'HLA-A*02:251', 'HLA-A*02:252', 'HLA-A*02:253', 'HLA-A*02:254', 'HLA-A*02:255', 'HLA-A*02:256',
'HLA-A*02:257', 'HLA-A*02:258', 'HLA-A*02:259', 'HLA-A*02:26', 'HLA-A*02:260', 'HLA-A*02:261', 'HLA-A*02:262', 'HLA-A*02:263',
'HLA-A*02:264', 'HLA-A*02:265', 'HLA-A*02:266', 'HLA-A*02:27', 'HLA-A*02:28', 'HLA-A*02:29', 'HLA-A*02:30', 'HLA-A*02:31', 'HLA-A*02:33',
'HLA-A*02:34', 'HLA-A*02:35', 'HLA-A*02:36', 'HLA-A*02:37', 'HLA-A*02:38', 'HLA-A*02:39', 'HLA-A*02:40', 'HLA-A*02:41', 'HLA-A*02:42',
'HLA-A*02:44', 'HLA-A*02:45', 'HLA-A*02:46', 'HLA-A*02:47', 'HLA-A*02:48', 'HLA-A*02:49', 'HLA-A*02:50', 'HLA-A*02:51', 'HLA-A*02:52',
'HLA-A*02:54', 'HLA-A*02:55', 'HLA-A*02:56', 'HLA-A*02:57', 'HLA-A*02:58', 'HLA-A*02:59', 'HLA-A*02:60', 'HLA-A*02:61', 'HLA-A*02:62',
'HLA-A*02:63', 'HLA-A*02:64', 'HLA-A*02:65', 'HLA-A*02:66', 'HLA-A*02:67', 'HLA-A*02:68', 'HLA-A*02:69', 'HLA-A*02:70', 'HLA-A*02:71',
'HLA-A*02:72', 'HLA-A*02:73', 'HLA-A*02:74', 'HLA-A*02:75', 'HLA-A*02:76', 'HLA-A*02:77', 'HLA-A*02:78', 'HLA-A*02:79', 'HLA-A*02:80',
'HLA-A*02:81', 'HLA-A*02:84', 'HLA-A*02:85', 'HLA-A*02:86', 'HLA-A*02:87', 'HLA-A*02:89', 'HLA-A*02:90', 'HLA-A*02:91', 'HLA-A*02:92',
'HLA-A*02:93', 'HLA-A*02:95', 'HLA-A*02:96', 'HLA-A*02:97', 'HLA-A*02:99', 'HLA-A*03:01', 'HLA-A*03:02', 'HLA-A*03:04', 'HLA-A*03:05',
'HLA-A*03:06', 'HLA-A*03:07', 'HLA-A*03:08', 'HLA-A*03:09', 'HLA-A*03:10', 'HLA-A*03:12', 'HLA-A*03:13', 'HLA-A*03:14', 'HLA-A*03:15',
'HLA-A*03:16', 'HLA-A*03:17', 'HLA-A*03:18', 'HLA-A*03:19', 'HLA-A*03:20', 'HLA-A*03:22', 'HLA-A*03:23', 'HLA-A*03:24', 'HLA-A*03:25',
'HLA-A*03:26', 'HLA-A*03:27', 'HLA-A*03:28', 'HLA-A*03:29', 'HLA-A*03:30', 'HLA-A*03:31', 'HLA-A*03:32', 'HLA-A*03:33', 'HLA-A*03:34',
'HLA-A*03:35', 'HLA-A*03:37', 'HLA-A*03:38', 'HLA-A*03:39', 'HLA-A*03:40', 'HLA-A*03:41', 'HLA-A*03:42', 'HLA-A*03:43', 'HLA-A*03:44',
'HLA-A*03:45', 'HLA-A*03:46', 'HLA-A*03:47', 'HLA-A*03:48', 'HLA-A*03:49', 'HLA-A*03:50', 'HLA-A*03:51', 'HLA-A*03:52', 'HLA-A*03:53',
'HLA-A*03:54', 'HLA-A*03:55', 'HLA-A*03:56', 'HLA-A*03:57', 'HLA-A*03:58', 'HLA-A*03:59', 'HLA-A*03:60', 'HLA-A*03:61', 'HLA-A*03:62',
'HLA-A*03:63', 'HLA-A*03:64', 'HLA-A*03:65', 'HLA-A*03:66', 'HLA-A*03:67', 'HLA-A*03:70', 'HLA-A*03:71', 'HLA-A*03:72', 'HLA-A*03:73',
'HLA-A*03:74', 'HLA-A*03:75', 'HLA-A*03:76', 'HLA-A*03:77', 'HLA-A*03:78', 'HLA-A*03:79', 'HLA-A*03:80', 'HLA-A*03:81', 'HLA-A*03:82',
'HLA-A*11:01', 'HLA-A*11:02', 'HLA-A*11:03', 'HLA-A*11:04', 'HLA-A*11:05', 'HLA-A*11:06', 'HLA-A*11:07', 'HLA-A*11:08', 'HLA-A*11:09',
'HLA-A*11:10', 'HLA-A*11:11', 'HLA-A*11:12', 'HLA-A*11:13', 'HLA-A*11:14', 'HLA-A*11:15', 'HLA-A*11:16', 'HLA-A*11:17', 'HLA-A*11:18',
'HLA-A*11:19', 'HLA-A*11:20', 'HLA-A*11:22', 'HLA-A*11:23', 'HLA-A*11:24', 'HLA-A*11:25', 'HLA-A*11:26', 'HLA-A*11:27', 'HLA-A*11:29',
'HLA-A*11:30', 'HLA-A*11:31', 'HLA-A*11:32', 'HLA-A*11:33', 'HLA-A*11:34', 'HLA-A*11:35', 'HLA-A*11:36', 'HLA-A*11:37', 'HLA-A*11:38',
'HLA-A*11:39', 'HLA-A*11:40', 'HLA-A*11:41', 'HLA-A*11:42', 'HLA-A*11:43', 'HLA-A*11:44', 'HLA-A*11:45', 'HLA-A*11:46', 'HLA-A*11:47',
'HLA-A*11:48', 'HLA-A*11:49', 'HLA-A*11:51', 'HLA-A*11:53', 'HLA-A*11:54', 'HLA-A*11:55', 'HLA-A*11:56', 'HLA-A*11:57', 'HLA-A*11:58',
'HLA-A*11:59', 'HLA-A*11:60', 'HLA-A*11:61', 'HLA-A*11:62', 'HLA-A*11:63', 'HLA-A*11:64', 'HLA-A*23:01', 'HLA-A*23:02', 'HLA-A*23:03',
'HLA-A*23:04', 'HLA-A*23:05', 'HLA-A*23:06', 'HLA-A*23:09', 'HLA-A*23:10', 'HLA-A*23:12', 'HLA-A*23:13', 'HLA-A*23:14', 'HLA-A*23:15',
'HLA-A*23:16', 'HLA-A*23:17', 'HLA-A*23:18', 'HLA-A*23:20', 'HLA-A*23:21', 'HLA-A*23:22', 'HLA-A*23:23', 'HLA-A*23:24', 'HLA-A*23:25',
'HLA-A*23:26', 'HLA-A*24:02', 'HLA-A*24:03', 'HLA-A*24:04', 'HLA-A*24:05', 'HLA-A*24:06', 'HLA-A*24:07', 'HLA-A*24:08', 'HLA-A*24:10',
'HLA-A*24:100', 'HLA-A*24:101', 'HLA-A*24:102', 'HLA-A*24:103', 'HLA-A*24:104', 'HLA-A*24:105', 'HLA-A*24:106', 'HLA-A*24:107',
'HLA-A*24:108', 'HLA-A*24:109', 'HLA-A*24:110', 'HLA-A*24:111', 'HLA-A*24:112', 'HLA-A*24:113', 'HLA-A*24:114', 'HLA-A*24:115',
'HLA-A*24:116', 'HLA-A*24:117', 'HLA-A*24:118', 'HLA-A*24:119', 'HLA-A*24:120', 'HLA-A*24:121', 'HLA-A*24:122', 'HLA-A*24:123',
'HLA-A*24:124', 'HLA-A*24:125', 'HLA-A*24:126', 'HLA-A*24:127', 'HLA-A*24:128', 'HLA-A*24:129', 'HLA-A*24:13', 'HLA-A*24:130',
'HLA-A*24:131', 'HLA-A*24:133', 'HLA-A*24:134', 'HLA-A*24:135', 'HLA-A*24:136', 'HLA-A*24:137', 'HLA-A*24:138', 'HLA-A*24:139',
'HLA-A*24:14', 'HLA-A*24:140', 'HLA-A*24:141', 'HLA-A*24:142', 'HLA-A*24:143', 'HLA-A*24:144', 'HLA-A*24:15', 'HLA-A*24:17', 'HLA-A*24:18',
'HLA-A*24:19', 'HLA-A*24:20', 'HLA-A*24:21', 'HLA-A*24:22', 'HLA-A*24:23', 'HLA-A*24:24', 'HLA-A*24:25', 'HLA-A*24:26', 'HLA-A*24:27',
'HLA-A*24:28', 'HLA-A*24:29', 'HLA-A*24:30', 'HLA-A*24:31', 'HLA-A*24:32', 'HLA-A*24:33', 'HLA-A*24:34', 'HLA-A*24:35', 'HLA-A*24:37',
'HLA-A*24:38', 'HLA-A*24:39', 'HLA-A*24:41', 'HLA-A*24:42', 'HLA-A*24:43', 'HLA-A*24:44', 'HLA-A*24:46', 'HLA-A*24:47', 'HLA-A*24:49',
'HLA-A*24:50', 'HLA-A*24:51', 'HLA-A*24:52', 'HLA-A*24:53', 'HLA-A*24:54', 'HLA-A*24:55', 'HLA-A*24:56', 'HLA-A*24:57', 'HLA-A*24:58',
'HLA-A*24:59', 'HLA-A*24:61', 'HLA-A*24:62', 'HLA-A*24:63', 'HLA-A*24:64', 'HLA-A*24:66', 'HLA-A*24:67', 'HLA-A*24:68', 'HLA-A*24:69',
'HLA-A*24:70', 'HLA-A*24:71', 'HLA-A*24:72', 'HLA-A*24:73', 'HLA-A*24:74', 'HLA-A*24:75', 'HLA-A*24:76', 'HLA-A*24:77', 'HLA-A*24:78',
'HLA-A*24:79', 'HLA-A*24:80', 'HLA-A*24:81', 'HLA-A*24:82', 'HLA-A*24:85', 'HLA-A*24:87', 'HLA-A*24:88', 'HLA-A*24:89', 'HLA-A*24:91',
'HLA-A*24:92', 'HLA-A*24:93', 'HLA-A*24:94', 'HLA-A*24:95', 'HLA-A*24:96', 'HLA-A*24:97', 'HLA-A*24:98', 'HLA-A*24:99', 'HLA-A*25:01',
'HLA-A*25:02', 'HLA-A*25:03', 'HLA-A*25:04', 'HLA-A*25:05', 'HLA-A*25:06', 'HLA-A*25:07', 'HLA-A*25:08', 'HLA-A*25:09', 'HLA-A*25:10',
'HLA-A*25:11', 'HLA-A*25:13', 'HLA-A*26:01', 'HLA-A*26:02', 'HLA-A*26:03', 'HLA-A*26:04', 'HLA-A*26:05', 'HLA-A*26:06', 'HLA-A*26:07',
'HLA-A*26:08', 'HLA-A*26:09', 'HLA-A*26:10', 'HLA-A*26:12', 'HLA-A*26:13', 'HLA-A*26:14', 'HLA-A*26:15', 'HLA-A*26:16', 'HLA-A*26:17',
'HLA-A*26:18', 'HLA-A*26:19', 'HLA-A*26:20', 'HLA-A*26:21', 'HLA-A*26:22', 'HLA-A*26:23', 'HLA-A*26:24', 'HLA-A*26:26', 'HLA-A*26:27',
'HLA-A*26:28', 'HLA-A*26:29', 'HLA-A*26:30', 'HLA-A*26:31', 'HLA-A*26:32', 'HLA-A*26:33', 'HLA-A*26:34', 'HLA-A*26:35', 'HLA-A*26:36',
'HLA-A*26:37', 'HLA-A*26:38', 'HLA-A*26:39', 'HLA-A*26:40', 'HLA-A*26:41', 'HLA-A*26:42', 'HLA-A*26:43', 'HLA-A*26:45', 'HLA-A*26:46',
'HLA-A*26:47', 'HLA-A*26:48', 'HLA-A*26:49', 'HLA-A*26:50', 'HLA-A*29:01', 'HLA-A*29:02', 'HLA-A*29:03', 'HLA-A*29:04', 'HLA-A*29:05',
'HLA-A*29:06', 'HLA-A*29:07', 'HLA-A*29:09', 'HLA-A*29:10', 'HLA-A*29:11', 'HLA-A*29:12', 'HLA-A*29:13', 'HLA-A*29:14', 'HLA-A*29:15',
'HLA-A*29:16', 'HLA-A*29:17', 'HLA-A*29:18', 'HLA-A*29:19', 'HLA-A*29:20', 'HLA-A*29:21', 'HLA-A*29:22', 'HLA-A*30:01', 'HLA-A*30:02',
'HLA-A*30:03', 'HLA-A*30:04', 'HLA-A*30:06', 'HLA-A*30:07', 'HLA-A*30:08', 'HLA-A*30:09', 'HLA-A*30:10', 'HLA-A*30:11', 'HLA-A*30:12',
'HLA-A*30:13', 'HLA-A*30:15', 'HLA-A*30:16', 'HLA-A*30:17', 'HLA-A*30:18', 'HLA-A*30:19', 'HLA-A*30:20', 'HLA-A*30:22', 'HLA-A*30:23',
'HLA-A*30:24', 'HLA-A*30:25', 'HLA-A*30:26', 'HLA-A*30:28', 'HLA-A*30:29', 'HLA-A*30:30', 'HLA-A*30:31', 'HLA-A*30:32', 'HLA-A*30:33',
'HLA-A*30:34', 'HLA-A*30:35', 'HLA-A*30:36', 'HLA-A*30:37', 'HLA-A*30:38', 'HLA-A*30:39', 'HLA-A*30:40', 'HLA-A*30:41', 'HLA-A*31:01',
'HLA-A*31:02', 'HLA-A*31:03', 'HLA-A*31:04', 'HLA-A*31:05', 'HLA-A*31:06', 'HLA-A*31:07', 'HLA-A*31:08', 'HLA-A*31:09', 'HLA-A*31:10',
'HLA-A*31:11', 'HLA-A*31:12', 'HLA-A*31:13', 'HLA-A*31:15', 'HLA-A*31:16', 'HLA-A*31:17', 'HLA-A*31:18', 'HLA-A*31:19', 'HLA-A*31:20',
'HLA-A*31:21', 'HLA-A*31:22', 'HLA-A*31:23', 'HLA-A*31:24', 'HLA-A*31:25', 'HLA-A*31:26', 'HLA-A*31:27', 'HLA-A*31:28', 'HLA-A*31:29',
'HLA-A*31:30', 'HLA-A*31:31', 'HLA-A*31:32', 'HLA-A*31:33', 'HLA-A*31:34', 'HLA-A*31:35', 'HLA-A*31:36', 'HLA-A*31:37', 'HLA-A*32:01',
'HLA-A*32:02', 'HLA-A*32:03', 'HLA-A*32:04', 'HLA-A*32:05', 'HLA-A*32:06', 'HLA-A*32:07', 'HLA-A*32:08', 'HLA-A*32:09', 'HLA-A*32:10',
'HLA-A*32:12', 'HLA-A*32:13', 'HLA-A*32:14', 'HLA-A*32:15', 'HLA-A*32:16', 'HLA-A*32:17', 'HLA-A*32:18', 'HLA-A*32:20', 'HLA-A*32:21',
'HLA-A*32:22', 'HLA-A*32:23', 'HLA-A*32:24', 'HLA-A*32:25', 'HLA-A*33:01', 'HLA-A*33:03', 'HLA-A*33:04', 'HLA-A*33:05', 'HLA-A*33:06',
'HLA-A*33:07', 'HLA-A*33:08', 'HLA-A*33:09', 'HLA-A*33:10', 'HLA-A*33:11', 'HLA-A*33:12', 'HLA-A*33:13', 'HLA-A*33:14', 'HLA-A*33:15',
'HLA-A*33:16', 'HLA-A*33:17', 'HLA-A*33:18', 'HLA-A*33:19', 'HLA-A*33:20', 'HLA-A*33:21', 'HLA-A*33:22', 'HLA-A*33:23', 'HLA-A*33:24',
'HLA-A*33:25', 'HLA-A*33:26', 'HLA-A*33:27', 'HLA-A*33:28', 'HLA-A*33:29', 'HLA-A*33:30', 'HLA-A*33:31', 'HLA-A*34:01', 'HLA-A*34:02',
'HLA-A*34:03', 'HLA-A*34:04', 'HLA-A*34:05', 'HLA-A*34:06', 'HLA-A*34:07', 'HLA-A*34:08', 'HLA-A*36:01', 'HLA-A*36:02', 'HLA-A*36:03',
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'HLA-A*66:07', 'HLA-A*66:08', 'HLA-A*66:09', 'HLA-A*66:10', 'HLA-A*66:11', 'HLA-A*66:12', 'HLA-A*66:13', 'HLA-A*66:14', 'HLA-A*66:15',
'HLA-A*68:01', 'HLA-A*68:02', 'HLA-A*68:03', 'HLA-A*68:04', 'HLA-A*68:05', 'HLA-A*68:06', 'HLA-A*68:07', 'HLA-A*68:08', 'HLA-A*68:09',
'HLA-A*68:10', 'HLA-A*68:12', 'HLA-A*68:13', 'HLA-A*68:14', 'HLA-A*68:15', 'HLA-A*68:16', 'HLA-A*68:17', 'HLA-A*68:19', 'HLA-A*68:20',
'HLA-A*68:21', 'HLA-A*68:22', 'HLA-A*68:23', 'HLA-A*68:24', 'HLA-A*68:25', 'HLA-A*68:26', 'HLA-A*68:27', 'HLA-A*68:28', 'HLA-A*68:29',
'HLA-A*68:30', 'HLA-A*68:31', 'HLA-A*68:32', 'HLA-A*68:33', 'HLA-A*68:34', 'HLA-A*68:35', 'HLA-A*68:36', 'HLA-A*68:37', 'HLA-A*68:38',
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'HLA-A*68:48', 'HLA-A*68:50', 'HLA-A*68:51', 'HLA-A*68:52', 'HLA-A*68:53', 'HLA-A*68:54', 'HLA-A*69:01', 'HLA-A*74:01', 'HLA-A*74:02',
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'HLA-B*07:105', 'HLA-B*07:106', 'HLA-B*07:107', 'HLA-B*07:108', 'HLA-B*07:109', 'HLA-B*07:11', 'HLA-B*07:110', 'HLA-B*07:112',
'HLA-B*07:113', 'HLA-B*07:114', 'HLA-B*07:115', 'HLA-B*07:12', 'HLA-B*07:13', 'HLA-B*07:14', 'HLA-B*07:15', 'HLA-B*07:16', 'HLA-B*07:17',
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'HLA-B*07:36', 'HLA-B*07:37', 'HLA-B*07:38', 'HLA-B*07:39', 'HLA-B*07:40', 'HLA-B*07:41', 'HLA-B*07:42', 'HLA-B*07:43', 'HLA-B*07:44',
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'HLA-B*07:55', 'HLA-B*07:56', 'HLA-B*07:57', 'HLA-B*07:58', 'HLA-B*07:59', 'HLA-B*07:60', 'HLA-B*07:61', 'HLA-B*07:62', 'HLA-B*07:63',
'HLA-B*07:64', 'HLA-B*07:65', 'HLA-B*07:66', 'HLA-B*07:68', 'HLA-B*07:69', 'HLA-B*07:70', 'HLA-B*07:71', 'HLA-B*07:72', 'HLA-B*07:73',
'HLA-B*07:74', 'HLA-B*07:75', 'HLA-B*07:76', 'HLA-B*07:77', 'HLA-B*07:78', 'HLA-B*07:79', 'HLA-B*07:80', 'HLA-B*07:81', 'HLA-B*07:82',
'HLA-B*07:83', 'HLA-B*07:84', 'HLA-B*07:85', 'HLA-B*07:86', 'HLA-B*07:87', 'HLA-B*07:88', 'HLA-B*07:89', 'HLA-B*07:90', 'HLA-B*07:91',
'HLA-B*07:92', 'HLA-B*07:93', 'HLA-B*07:94', 'HLA-B*07:95', 'HLA-B*07:96', 'HLA-B*07:97', 'HLA-B*07:98', 'HLA-B*07:99', 'HLA-B*08:01',
'HLA-B*08:02', 'HLA-B*08:03', 'HLA-B*08:04', 'HLA-B*08:05', 'HLA-B*08:07', 'HLA-B*08:09', 'HLA-B*08:10', 'HLA-B*08:11', 'HLA-B*08:12',
'HLA-B*08:13', 'HLA-B*08:14', 'HLA-B*08:15', 'HLA-B*08:16', 'HLA-B*08:17', 'HLA-B*08:18', 'HLA-B*08:20', 'HLA-B*08:21', 'HLA-B*08:22',
'HLA-B*08:23', 'HLA-B*08:24', 'HLA-B*08:25', 'HLA-B*08:26', 'HLA-B*08:27', 'HLA-B*08:28', 'HLA-B*08:29', 'HLA-B*08:31', 'HLA-B*08:32',
'HLA-B*08:33', 'HLA-B*08:34', 'HLA-B*08:35', 'HLA-B*08:36', 'HLA-B*08:37', 'HLA-B*08:38', 'HLA-B*08:39', 'HLA-B*08:40', 'HLA-B*08:41',
'HLA-B*08:42', 'HLA-B*08:43', 'HLA-B*08:44', 'HLA-B*08:45', 'HLA-B*08:46', 'HLA-B*08:47', 'HLA-B*08:48', 'HLA-B*08:49', 'HLA-B*08:50',
'HLA-B*08:51', 'HLA-B*08:52', 'HLA-B*08:53', 'HLA-B*08:54', 'HLA-B*08:55', 'HLA-B*08:56', 'HLA-B*08:57', 'HLA-B*08:58', 'HLA-B*08:59',
'HLA-B*08:60', 'HLA-B*08:61', 'HLA-B*08:62', 'HLA-B*13:01', 'HLA-B*13:02', 'HLA-B*13:03', 'HLA-B*13:04', 'HLA-B*13:06', 'HLA-B*13:09',
'HLA-B*13:10', 'HLA-B*13:11', 'HLA-B*13:12', 'HLA-B*13:13', 'HLA-B*13:14', 'HLA-B*13:15', 'HLA-B*13:16', 'HLA-B*13:17', 'HLA-B*13:18',
'HLA-B*13:19', 'HLA-B*13:20', 'HLA-B*13:21', 'HLA-B*13:22', 'HLA-B*13:23', 'HLA-B*13:25', 'HLA-B*13:26', 'HLA-B*13:27', 'HLA-B*13:28',
'HLA-B*13:29', 'HLA-B*13:30', 'HLA-B*13:31', 'HLA-B*13:32', 'HLA-B*13:33', 'HLA-B*13:34', 'HLA-B*13:35', 'HLA-B*13:36', 'HLA-B*13:37',
'HLA-B*13:38', 'HLA-B*13:39', 'HLA-B*14:01', 'HLA-B*14:02', 'HLA-B*14:03', 'HLA-B*14:04', 'HLA-B*14:05', 'HLA-B*14:06', 'HLA-B*14:08',
'HLA-B*14:09', 'HLA-B*14:10', 'HLA-B*14:11', 'HLA-B*14:12', 'HLA-B*14:13', 'HLA-B*14:14', 'HLA-B*14:15', 'HLA-B*14:16', 'HLA-B*14:17',
'HLA-B*14:18', 'HLA-B*15:01', 'HLA-B*15:02', 'HLA-B*15:03', 'HLA-B*15:04', 'HLA-B*15:05', 'HLA-B*15:06', 'HLA-B*15:07', 'HLA-B*15:08',
'HLA-B*15:09', 'HLA-B*15:10', 'HLA-B*15:101', 'HLA-B*15:102', 'HLA-B*15:103', 'HLA-B*15:104', 'HLA-B*15:105', 'HLA-B*15:106',
'HLA-B*15:107', 'HLA-B*15:108', 'HLA-B*15:109', 'HLA-B*15:11', 'HLA-B*15:110', 'HLA-B*15:112', 'HLA-B*15:113', 'HLA-B*15:114',
'HLA-B*15:115', 'HLA-B*15:116', 'HLA-B*15:117', 'HLA-B*15:118', 'HLA-B*15:119', 'HLA-B*15:12', 'HLA-B*15:120', 'HLA-B*15:121',
'HLA-B*15:122', 'HLA-B*15:123', 'HLA-B*15:124', 'HLA-B*15:125', 'HLA-B*15:126', 'HLA-B*15:127', 'HLA-B*15:128', 'HLA-B*15:129',
'HLA-B*15:13', 'HLA-B*15:131', 'HLA-B*15:132', 'HLA-B*15:133', 'HLA-B*15:134', 'HLA-B*15:135', 'HLA-B*15:136', 'HLA-B*15:137',
'HLA-B*15:138', 'HLA-B*15:139', 'HLA-B*15:14', 'HLA-B*15:140', 'HLA-B*15:141', 'HLA-B*15:142', 'HLA-B*15:143', 'HLA-B*15:144',
'HLA-B*15:145', 'HLA-B*15:146', 'HLA-B*15:147', 'HLA-B*15:148', 'HLA-B*15:15', 'HLA-B*15:150', 'HLA-B*15:151', 'HLA-B*15:152',
'HLA-B*15:153', 'HLA-B*15:154', 'HLA-B*15:155', 'HLA-B*15:156', 'HLA-B*15:157', 'HLA-B*15:158', 'HLA-B*15:159', 'HLA-B*15:16',
'HLA-B*15:160', 'HLA-B*15:161', 'HLA-B*15:162', 'HLA-B*15:163', 'HLA-B*15:164', 'HLA-B*15:165', 'HLA-B*15:166', 'HLA-B*15:167',
'HLA-B*15:168', 'HLA-B*15:169', 'HLA-B*15:17', 'HLA-B*15:170', 'HLA-B*15:171', 'HLA-B*15:172', 'HLA-B*15:173', 'HLA-B*15:174',
'HLA-B*15:175', 'HLA-B*15:176', 'HLA-B*15:177', 'HLA-B*15:178', 'HLA-B*15:179', 'HLA-B*15:18', 'HLA-B*15:180', 'HLA-B*15:183',
'HLA-B*15:184', 'HLA-B*15:185', 'HLA-B*15:186', 'HLA-B*15:187', 'HLA-B*15:188', 'HLA-B*15:189', 'HLA-B*15:19', 'HLA-B*15:191',
'HLA-B*15:192', 'HLA-B*15:193', 'HLA-B*15:194', 'HLA-B*15:195', 'HLA-B*15:196', 'HLA-B*15:197', 'HLA-B*15:198', 'HLA-B*15:199',
'HLA-B*15:20', 'HLA-B*15:200', 'HLA-B*15:201', 'HLA-B*15:202', 'HLA-B*15:21', 'HLA-B*15:23', 'HLA-B*15:24', 'HLA-B*15:25', 'HLA-B*15:27',
'HLA-B*15:28', 'HLA-B*15:29', 'HLA-B*15:30', 'HLA-B*15:31', 'HLA-B*15:32', 'HLA-B*15:33', 'HLA-B*15:34', 'HLA-B*15:35', 'HLA-B*15:36',
'HLA-B*15:37', 'HLA-B*15:38', 'HLA-B*15:39', 'HLA-B*15:40', 'HLA-B*15:42', 'HLA-B*15:43', 'HLA-B*15:44', 'HLA-B*15:45', 'HLA-B*15:46',
'HLA-B*15:47', 'HLA-B*15:48', 'HLA-B*15:49', 'HLA-B*15:50', 'HLA-B*15:51', 'HLA-B*15:52', 'HLA-B*15:53', 'HLA-B*15:54', 'HLA-B*15:55',
'HLA-B*15:56', 'HLA-B*15:57', 'HLA-B*15:58', 'HLA-B*15:60', 'HLA-B*15:61', 'HLA-B*15:62', 'HLA-B*15:63', 'HLA-B*15:64', 'HLA-B*15:65',
'HLA-B*15:66', 'HLA-B*15:67', 'HLA-B*15:68', 'HLA-B*15:69', 'HLA-B*15:70', 'HLA-B*15:71', 'HLA-B*15:72', 'HLA-B*15:73', 'HLA-B*15:74',
'HLA-B*15:75', 'HLA-B*15:76', 'HLA-B*15:77', 'HLA-B*15:78', 'HLA-B*15:80', 'HLA-B*15:81', 'HLA-B*15:82', 'HLA-B*15:83', 'HLA-B*15:84',
'HLA-B*15:85', 'HLA-B*15:86', 'HLA-B*15:87', 'HLA-B*15:88', 'HLA-B*15:89', 'HLA-B*15:90', 'HLA-B*15:91', 'HLA-B*15:92', 'HLA-B*15:93',
'HLA-B*15:95', 'HLA-B*15:96', 'HLA-B*15:97', 'HLA-B*15:98', 'HLA-B*15:99', 'HLA-B*18:01', 'HLA-B*18:02', 'HLA-B*18:03', 'HLA-B*18:04',
'HLA-B*18:05', 'HLA-B*18:06', 'HLA-B*18:07', 'HLA-B*18:08', 'HLA-B*18:09', 'HLA-B*18:10', 'HLA-B*18:11', 'HLA-B*18:12', 'HLA-B*18:13',
'HLA-B*18:14', 'HLA-B*18:15', 'HLA-B*18:18', 'HLA-B*18:19', 'HLA-B*18:20', 'HLA-B*18:21', 'HLA-B*18:22', 'HLA-B*18:24', 'HLA-B*18:25',
'HLA-B*18:26', 'HLA-B*18:27', 'HLA-B*18:28', 'HLA-B*18:29', 'HLA-B*18:30', 'HLA-B*18:31', 'HLA-B*18:32', 'HLA-B*18:33', 'HLA-B*18:34',
'HLA-B*18:35', 'HLA-B*18:36', 'HLA-B*18:37', 'HLA-B*18:38', 'HLA-B*18:39', 'HLA-B*18:40', 'HLA-B*18:41', 'HLA-B*18:42', 'HLA-B*18:43',
'HLA-B*18:44', 'HLA-B*18:45', 'HLA-B*18:46', 'HLA-B*18:47', 'HLA-B*18:48', 'HLA-B*18:49', 'HLA-B*18:50', 'HLA-B*27:01', 'HLA-B*27:02',
'HLA-B*27:03', 'HLA-B*27:04', 'HLA-B*27:05', 'HLA-B*27:06', 'HLA-B*27:07', 'HLA-B*27:08', 'HLA-B*27:09', 'HLA-B*27:10', 'HLA-B*27:11',
'HLA-B*27:12', 'HLA-B*27:13', 'HLA-B*27:14', 'HLA-B*27:15', 'HLA-B*27:16', 'HLA-B*27:17', 'HLA-B*27:18', 'HLA-B*27:19', 'HLA-B*27:20',
'HLA-B*27:21', 'HLA-B*27:23', 'HLA-B*27:24', 'HLA-B*27:25', 'HLA-B*27:26', 'HLA-B*27:27', 'HLA-B*27:28', 'HLA-B*27:29', 'HLA-B*27:30',
'HLA-B*27:31', 'HLA-B*27:32', 'HLA-B*27:33', 'HLA-B*27:34', 'HLA-B*27:35', 'HLA-B*27:36', 'HLA-B*27:37', 'HLA-B*27:38', 'HLA-B*27:39',
'HLA-B*27:40', 'HLA-B*27:41', 'HLA-B*27:42', 'HLA-B*27:43', 'HLA-B*27:44', 'HLA-B*27:45', 'HLA-B*27:46', 'HLA-B*27:47', 'HLA-B*27:48',
'HLA-B*27:49', 'HLA-B*27:50', 'HLA-B*27:51', 'HLA-B*27:52', 'HLA-B*27:53', 'HLA-B*27:54', 'HLA-B*27:55', 'HLA-B*27:56', 'HLA-B*27:57',
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'HLA-B*55:34', 'HLA-B*55:35', 'HLA-B*55:36', 'HLA-B*55:37', 'HLA-B*55:38', 'HLA-B*55:39', 'HLA-B*55:40', 'HLA-B*55:41', 'HLA-B*55:42',
'HLA-B*55:43', 'HLA-B*56:01', 'HLA-B*56:02', 'HLA-B*56:03', 'HLA-B*56:04', 'HLA-B*56:05', 'HLA-B*56:06', 'HLA-B*56:07', 'HLA-B*56:08',
'HLA-B*56:09', 'HLA-B*56:10', 'HLA-B*56:11', 'HLA-B*56:12', 'HLA-B*56:13', 'HLA-B*56:14', 'HLA-B*56:15', 'HLA-B*56:16', 'HLA-B*56:17',
'HLA-B*56:18', 'HLA-B*56:20', 'HLA-B*56:21', 'HLA-B*56:22', 'HLA-B*56:23', 'HLA-B*56:24', 'HLA-B*56:25', 'HLA-B*56:26', 'HLA-B*56:27',
'HLA-B*56:29', 'HLA-B*57:01', 'HLA-B*57:02', 'HLA-B*57:03', 'HLA-B*57:04', 'HLA-B*57:05', 'HLA-B*57:06', 'HLA-B*57:07', 'HLA-B*57:08',
'HLA-B*57:09', 'HLA-B*57:10', 'HLA-B*57:11', 'HLA-B*57:12', 'HLA-B*57:13', 'HLA-B*57:14', 'HLA-B*57:15', 'HLA-B*57:16', 'HLA-B*57:17',
'HLA-B*57:18', 'HLA-B*57:19', 'HLA-B*57:20', 'HLA-B*57:21', 'HLA-B*57:22', 'HLA-B*57:23', 'HLA-B*57:24', 'HLA-B*57:25', 'HLA-B*57:26',
'HLA-B*57:27', 'HLA-B*57:29', 'HLA-B*57:30', 'HLA-B*57:31', 'HLA-B*57:32', 'HLA-B*58:01', 'HLA-B*58:02', 'HLA-B*58:04', 'HLA-B*58:05',
'HLA-B*58:06', 'HLA-B*58:07', 'HLA-B*58:08', 'HLA-B*58:09', 'HLA-B*58:11', 'HLA-B*58:12', 'HLA-B*58:13', 'HLA-B*58:14', 'HLA-B*58:15',
'HLA-B*58:16', 'HLA-B*58:18', 'HLA-B*58:19', 'HLA-B*58:20', 'HLA-B*58:21', 'HLA-B*58:22', 'HLA-B*58:23', 'HLA-B*58:24', 'HLA-B*58:25',
'HLA-B*58:26', 'HLA-B*58:27', 'HLA-B*58:28', 'HLA-B*58:29', 'HLA-B*58:30', 'HLA-B*59:01', 'HLA-B*59:02', 'HLA-B*59:03', 'HLA-B*59:04',
'HLA-B*59:05', 'HLA-B*67:01', 'HLA-B*67:02', 'HLA-B*73:01', 'HLA-B*73:02', 'HLA-B*78:01', 'HLA-B*78:02', 'HLA-B*78:03', 'HLA-B*78:04',
'HLA-B*78:05', 'HLA-B*78:06', 'HLA-B*78:07', 'HLA-B*81:01', 'HLA-B*81:02', 'HLA-B*81:03', 'HLA-B*81:05', 'HLA-B*82:01', 'HLA-B*82:02',
'HLA-B*82:03', 'HLA-B*83:01', 'HLA-C*01:02', 'HLA-C*01:03', 'HLA-C*01:04', 'HLA-C*01:05', 'HLA-C*01:06', 'HLA-C*01:07', 'HLA-C*01:08',
'HLA-C*01:09', 'HLA-C*01:10', 'HLA-C*01:11', 'HLA-C*01:12', 'HLA-C*01:13', 'HLA-C*01:14', 'HLA-C*01:15', 'HLA-C*01:16', 'HLA-C*01:17',
'HLA-C*01:18', 'HLA-C*01:19', 'HLA-C*01:20', 'HLA-C*01:21', 'HLA-C*01:22', 'HLA-C*01:23', 'HLA-C*01:24', 'HLA-C*01:25', 'HLA-C*01:26',
'HLA-C*01:27', 'HLA-C*01:28', 'HLA-C*01:29', 'HLA-C*01:30', 'HLA-C*01:31', 'HLA-C*01:32', 'HLA-C*01:33', 'HLA-C*01:34', 'HLA-C*01:35',
'HLA-C*01:36', 'HLA-C*01:38', 'HLA-C*01:39', 'HLA-C*01:40', 'HLA-C*02:02', 'HLA-C*02:03', 'HLA-C*02:04', 'HLA-C*02:05', 'HLA-C*02:06',
'HLA-C*02:07', 'HLA-C*02:08', 'HLA-C*02:09', 'HLA-C*02:10', 'HLA-C*02:11', 'HLA-C*02:12', 'HLA-C*02:13', 'HLA-C*02:14', 'HLA-C*02:15',
'HLA-C*02:16', 'HLA-C*02:17', 'HLA-C*02:18', 'HLA-C*02:19', 'HLA-C*02:20', 'HLA-C*02:21', 'HLA-C*02:22', 'HLA-C*02:23', 'HLA-C*02:24',
'HLA-C*02:26', 'HLA-C*02:27', 'HLA-C*02:28', 'HLA-C*02:29', 'HLA-C*02:30', 'HLA-C*02:31', 'HLA-C*02:32', 'HLA-C*02:33', 'HLA-C*02:34',
'HLA-C*02:35', 'HLA-C*02:36', 'HLA-C*02:37', 'HLA-C*02:39', 'HLA-C*02:40', 'HLA-C*03:01', 'HLA-C*03:02', 'HLA-C*03:03', 'HLA-C*03:04',
'HLA-C*03:05', 'HLA-C*03:06', 'HLA-C*03:07', 'HLA-C*03:08', 'HLA-C*03:09', 'HLA-C*03:10', 'HLA-C*03:11', 'HLA-C*03:12', 'HLA-C*03:13',
'HLA-C*03:14', 'HLA-C*03:15', 'HLA-C*03:16', 'HLA-C*03:17', 'HLA-C*03:18', 'HLA-C*03:19', 'HLA-C*03:21', 'HLA-C*03:23', 'HLA-C*03:24',
'HLA-C*03:25', 'HLA-C*03:26', 'HLA-C*03:27', 'HLA-C*03:28', 'HLA-C*03:29', 'HLA-C*03:30', 'HLA-C*03:31', 'HLA-C*03:32', 'HLA-C*03:33',
'HLA-C*03:34', 'HLA-C*03:35', 'HLA-C*03:36', 'HLA-C*03:37', 'HLA-C*03:38', 'HLA-C*03:39', 'HLA-C*03:40', 'HLA-C*03:41', 'HLA-C*03:42',
'HLA-C*03:43', 'HLA-C*03:44', 'HLA-C*03:45', 'HLA-C*03:46', 'HLA-C*03:47', 'HLA-C*03:48', 'HLA-C*03:49', 'HLA-C*03:50', 'HLA-C*03:51',
'HLA-C*03:52', 'HLA-C*03:53', 'HLA-C*03:54', 'HLA-C*03:55', 'HLA-C*03:56', 'HLA-C*03:57', 'HLA-C*03:58', 'HLA-C*03:59', 'HLA-C*03:60',
'HLA-C*03:61', 'HLA-C*03:62', 'HLA-C*03:63', 'HLA-C*03:64', 'HLA-C*03:65', 'HLA-C*03:66', 'HLA-C*03:67', 'HLA-C*03:68', 'HLA-C*03:69',
'HLA-C*03:70', 'HLA-C*03:71', 'HLA-C*03:72', 'HLA-C*03:73', 'HLA-C*03:74', 'HLA-C*03:75', 'HLA-C*03:76', 'HLA-C*03:77', 'HLA-C*03:78',
'HLA-C*03:79', 'HLA-C*03:80', 'HLA-C*03:81', 'HLA-C*03:82', 'HLA-C*03:83', 'HLA-C*03:84', 'HLA-C*03:85', 'HLA-C*03:86', 'HLA-C*03:87',
'HLA-C*03:88', 'HLA-C*03:89', 'HLA-C*03:90', 'HLA-C*03:91', 'HLA-C*03:92', 'HLA-C*03:93', 'HLA-C*03:94', 'HLA-C*04:01', 'HLA-C*04:03',
'HLA-C*04:04', 'HLA-C*04:05', 'HLA-C*04:06', 'HLA-C*04:07', 'HLA-C*04:08', 'HLA-C*04:10', 'HLA-C*04:11', 'HLA-C*04:12', 'HLA-C*04:13',
'HLA-C*04:14', 'HLA-C*04:15', 'HLA-C*04:16', 'HLA-C*04:17', 'HLA-C*04:18', 'HLA-C*04:19', 'HLA-C*04:20', 'HLA-C*04:23', 'HLA-C*04:24',
'HLA-C*04:25', 'HLA-C*04:26', 'HLA-C*04:27', 'HLA-C*04:28', 'HLA-C*04:29', 'HLA-C*04:30', 'HLA-C*04:31', 'HLA-C*04:32', 'HLA-C*04:33',
'HLA-C*04:34', 'HLA-C*04:35', 'HLA-C*04:36', 'HLA-C*04:37', 'HLA-C*04:38', 'HLA-C*04:39', 'HLA-C*04:40', 'HLA-C*04:41', 'HLA-C*04:42',
'HLA-C*04:43', 'HLA-C*04:44', 'HLA-C*04:45', 'HLA-C*04:46', 'HLA-C*04:47', 'HLA-C*04:48', 'HLA-C*04:49', 'HLA-C*04:50', 'HLA-C*04:51',
'HLA-C*04:52', 'HLA-C*04:53', 'HLA-C*04:54', 'HLA-C*04:55', 'HLA-C*04:56', 'HLA-C*04:57', 'HLA-C*04:58', 'HLA-C*04:60', 'HLA-C*04:61',
'HLA-C*04:62', 'HLA-C*04:63', 'HLA-C*04:64', 'HLA-C*04:65', 'HLA-C*04:66', 'HLA-C*04:67', 'HLA-C*04:68', 'HLA-C*04:69', 'HLA-C*04:70',
'HLA-C*05:01', 'HLA-C*05:03', 'HLA-C*05:04', 'HLA-C*05:05', 'HLA-C*05:06', 'HLA-C*05:08', 'HLA-C*05:09', 'HLA-C*05:10', 'HLA-C*05:11',
'HLA-C*05:12', 'HLA-C*05:13', 'HLA-C*05:14', 'HLA-C*05:15', 'HLA-C*05:16', 'HLA-C*05:17', 'HLA-C*05:18', 'HLA-C*05:19', 'HLA-C*05:20',
'HLA-C*05:21', 'HLA-C*05:22', 'HLA-C*05:23', 'HLA-C*05:24', 'HLA-C*05:25', 'HLA-C*05:26', 'HLA-C*05:27', 'HLA-C*05:28', 'HLA-C*05:29',
'HLA-C*05:30', 'HLA-C*05:31', 'HLA-C*05:32', 'HLA-C*05:33', 'HLA-C*05:34', 'HLA-C*05:35', 'HLA-C*05:36', 'HLA-C*05:37', 'HLA-C*05:38',
'HLA-C*05:39', 'HLA-C*05:40', 'HLA-C*05:41', 'HLA-C*05:42', 'HLA-C*05:43', 'HLA-C*05:44', 'HLA-C*05:45', 'HLA-C*06:02', 'HLA-C*06:03',
'HLA-C*06:04', 'HLA-C*06:05', 'HLA-C*06:06', 'HLA-C*06:07', 'HLA-C*06:08', 'HLA-C*06:09', 'HLA-C*06:10', 'HLA-C*06:11', 'HLA-C*06:12',
'HLA-C*06:13', 'HLA-C*06:14', 'HLA-C*06:15', 'HLA-C*06:17', 'HLA-C*06:18', 'HLA-C*06:19', 'HLA-C*06:20', 'HLA-C*06:21', 'HLA-C*06:22',
'HLA-C*06:23', 'HLA-C*06:24', 'HLA-C*06:25', 'HLA-C*06:26', 'HLA-C*06:27', 'HLA-C*06:28', 'HLA-C*06:29', 'HLA-C*06:30', 'HLA-C*06:31',
'HLA-C*06:32', 'HLA-C*06:33', 'HLA-C*06:34', 'HLA-C*06:35', 'HLA-C*06:36', 'HLA-C*06:37', 'HLA-C*06:38', 'HLA-C*06:39', 'HLA-C*06:40',
'HLA-C*06:41', 'HLA-C*06:42', 'HLA-C*06:43', 'HLA-C*06:44', 'HLA-C*06:45', 'HLA-C*07:01', 'HLA-C*07:02', 'HLA-C*07:03', 'HLA-C*07:04',
'HLA-C*07:05', 'HLA-C*07:06', 'HLA-C*07:07', 'HLA-C*07:08', 'HLA-C*07:09', 'HLA-C*07:10', 'HLA-C*07:100', 'HLA-C*07:101', 'HLA-C*07:102',
'HLA-C*07:103', 'HLA-C*07:105', 'HLA-C*07:106', 'HLA-C*07:107', 'HLA-C*07:108', 'HLA-C*07:109', 'HLA-C*07:11', 'HLA-C*07:110',
'HLA-C*07:111', 'HLA-C*07:112', 'HLA-C*07:113', 'HLA-C*07:114', 'HLA-C*07:115', 'HLA-C*07:116', 'HLA-C*07:117', 'HLA-C*07:118',
'HLA-C*07:119', 'HLA-C*07:12', 'HLA-C*07:120', 'HLA-C*07:122', 'HLA-C*07:123', 'HLA-C*07:124', 'HLA-C*07:125', 'HLA-C*07:126',
'HLA-C*07:127', 'HLA-C*07:128', 'HLA-C*07:129', 'HLA-C*07:13', 'HLA-C*07:130', 'HLA-C*07:131', 'HLA-C*07:132', 'HLA-C*07:133',
'HLA-C*07:134', 'HLA-C*07:135', 'HLA-C*07:136', 'HLA-C*07:137', 'HLA-C*07:138', 'HLA-C*07:139', 'HLA-C*07:14', 'HLA-C*07:140',
'HLA-C*07:141', 'HLA-C*07:142', 'HLA-C*07:143', 'HLA-C*07:144', 'HLA-C*07:145', 'HLA-C*07:146', 'HLA-C*07:147', 'HLA-C*07:148',
'HLA-C*07:149', 'HLA-C*07:15', 'HLA-C*07:16', 'HLA-C*07:17', 'HLA-C*07:18', 'HLA-C*07:19', 'HLA-C*07:20', 'HLA-C*07:21', 'HLA-C*07:22',
'HLA-C*07:23', 'HLA-C*07:24', 'HLA-C*07:25', 'HLA-C*07:26', 'HLA-C*07:27', 'HLA-C*07:28', 'HLA-C*07:29', 'HLA-C*07:30', 'HLA-C*07:31',
'HLA-C*07:35', 'HLA-C*07:36', 'HLA-C*07:37', 'HLA-C*07:38', 'HLA-C*07:39', 'HLA-C*07:40', 'HLA-C*07:41', 'HLA-C*07:42', 'HLA-C*07:43',
'HLA-C*07:44', 'HLA-C*07:45', 'HLA-C*07:46', 'HLA-C*07:47', 'HLA-C*07:48', 'HLA-C*07:49', 'HLA-C*07:50', 'HLA-C*07:51', 'HLA-C*07:52',
'HLA-C*07:53', 'HLA-C*07:54', 'HLA-C*07:56', 'HLA-C*07:57', 'HLA-C*07:58', 'HLA-C*07:59', 'HLA-C*07:60', 'HLA-C*07:62', 'HLA-C*07:63',
'HLA-C*07:64', 'HLA-C*07:65', 'HLA-C*07:66', 'HLA-C*07:67', 'HLA-C*07:68', 'HLA-C*07:69', 'HLA-C*07:70', 'HLA-C*07:71', 'HLA-C*07:72',
'HLA-C*07:73', 'HLA-C*07:74', 'HLA-C*07:75', 'HLA-C*07:76', 'HLA-C*07:77', 'HLA-C*07:78', 'HLA-C*07:79', 'HLA-C*07:80', 'HLA-C*07:81',
'HLA-C*07:82', 'HLA-C*07:83', 'HLA-C*07:84', 'HLA-C*07:85', 'HLA-C*07:86', 'HLA-C*07:87', 'HLA-C*07:88', 'HLA-C*07:89', 'HLA-C*07:90',
'HLA-C*07:91', 'HLA-C*07:92', 'HLA-C*07:93', 'HLA-C*07:94', 'HLA-C*07:95', 'HLA-C*07:96', 'HLA-C*07:97', 'HLA-C*07:99', 'HLA-C*08:01',
'HLA-C*08:02', 'HLA-C*08:03', 'HLA-C*08:04', 'HLA-C*08:05', 'HLA-C*08:06', 'HLA-C*08:07', 'HLA-C*08:08', 'HLA-C*08:09', 'HLA-C*08:10',
'HLA-C*08:11', 'HLA-C*08:12', 'HLA-C*08:13', 'HLA-C*08:14', 'HLA-C*08:15', 'HLA-C*08:16', 'HLA-C*08:17', 'HLA-C*08:18', 'HLA-C*08:19',
'HLA-C*08:20', 'HLA-C*08:21', 'HLA-C*08:22', 'HLA-C*08:23', 'HLA-C*08:24', 'HLA-C*08:25', 'HLA-C*08:27', 'HLA-C*08:28', 'HLA-C*08:29',
'HLA-C*08:30', 'HLA-C*08:31', 'HLA-C*08:32', 'HLA-C*08:33', 'HLA-C*08:34', 'HLA-C*08:35', 'HLA-C*12:02', 'HLA-C*12:03', 'HLA-C*12:04',
'HLA-C*12:05', 'HLA-C*12:06', 'HLA-C*12:07', 'HLA-C*12:08', 'HLA-C*12:09', 'HLA-C*12:10', 'HLA-C*12:11', 'HLA-C*12:12', 'HLA-C*12:13',
'HLA-C*12:14', 'HLA-C*12:15', 'HLA-C*12:16', 'HLA-C*12:17', 'HLA-C*12:18', 'HLA-C*12:19', 'HLA-C*12:20', 'HLA-C*12:21', 'HLA-C*12:22',
'HLA-C*12:23', 'HLA-C*12:24', 'HLA-C*12:25', 'HLA-C*12:26', 'HLA-C*12:27', 'HLA-C*12:28', 'HLA-C*12:29', 'HLA-C*12:30', 'HLA-C*12:31',
'HLA-C*12:32', 'HLA-C*12:33', 'HLA-C*12:34', 'HLA-C*12:35', 'HLA-C*12:36', 'HLA-C*12:37', 'HLA-C*12:38', 'HLA-C*12:40', 'HLA-C*12:41',
'HLA-C*12:43', 'HLA-C*12:44', 'HLA-C*14:02', 'HLA-C*14:03', 'HLA-C*14:04', 'HLA-C*14:05', 'HLA-C*14:06', 'HLA-C*14:08', 'HLA-C*14:09',
'HLA-C*14:10', 'HLA-C*14:11', 'HLA-C*14:12', 'HLA-C*14:13', 'HLA-C*14:14', 'HLA-C*14:15', 'HLA-C*14:16', 'HLA-C*14:17', 'HLA-C*14:18',
'HLA-C*14:19', 'HLA-C*14:20', 'HLA-C*15:02', 'HLA-C*15:03', 'HLA-C*15:04', 'HLA-C*15:05', 'HLA-C*15:06', 'HLA-C*15:07', 'HLA-C*15:08',
'HLA-C*15:09', 'HLA-C*15:10', 'HLA-C*15:11', 'HLA-C*15:12', 'HLA-C*15:13', 'HLA-C*15:15', 'HLA-C*15:16', 'HLA-C*15:17', 'HLA-C*15:18',
'HLA-C*15:19', 'HLA-C*15:20', 'HLA-C*15:21', 'HLA-C*15:22', 'HLA-C*15:23', 'HLA-C*15:24', 'HLA-C*15:25', 'HLA-C*15:26', 'HLA-C*15:27',
'HLA-C*15:28', 'HLA-C*15:29', 'HLA-C*15:30', 'HLA-C*15:31', 'HLA-C*15:33', 'HLA-C*15:34', 'HLA-C*15:35', 'HLA-C*16:01', 'HLA-C*16:02',
'HLA-C*16:04', 'HLA-C*16:06', 'HLA-C*16:07', 'HLA-C*16:08', 'HLA-C*16:09', 'HLA-C*16:10', 'HLA-C*16:11', 'HLA-C*16:12', 'HLA-C*16:13',
'HLA-C*16:14', 'HLA-C*16:15', 'HLA-C*16:17', 'HLA-C*16:18', 'HLA-C*16:19', 'HLA-C*16:20', 'HLA-C*16:21', 'HLA-C*16:22', 'HLA-C*16:23',
'HLA-C*16:24', 'HLA-C*16:25', 'HLA-C*16:26', 'HLA-C*17:01', 'HLA-C*17:02', 'HLA-C*17:03', 'HLA-C*17:04', 'HLA-C*17:05', 'HLA-C*17:06',
'HLA-C*17:07', 'HLA-C*18:01', 'HLA-C*18:02', 'HLA-C*18:03', 'HLA-E*01:01', 'HLA-G*01:01', 'HLA-G*01:02', 'HLA-G*01:03', 'HLA-G*01:04',
'HLA-G*01:06', 'HLA-G*01:07', 'HLA-G*01:08', 'HLA-G*01:09',
'H2-Db', 'H2-Dd', 'H2-Kb', 'H2-Kd', 'H2-Kk', 'H2-Ld', "H2-Qa1", "H2-Qa2"])
@property
def version(self):
"""The version of the predictor"""
return self.__version
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
else:
return "HLA-%s%s:%s" % (allele.locus, allele.supertype, allele.subtype)
def convert_alleles(self, alleles):
"""
Converts :class:`~epytope.Core.Allele.Allele` into the internal :class:`~epytope.Core.Allele.Allele` representation
of the predictor and returns a string representation
:param alleles: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: Returns a string representation of the input :class:`~epytope.Core.Allele.Allele`
:rtype: list(str)
"""
return [self._represent(a) for a in alleles]
@property
def supportedAlleles(self):
"""A list of valid :class:`~epytope.Core.Allele.Allele` models"""
return self.__alleles
@property
def name(self):
"""The name of the predictor"""
return self.__name
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`self.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: str
"""
return None
def prepare_input(self, input, file):
"""
Prepares input for external tools
and writes them to file in the specific format
No return value!
:param: list(str) input: The :class:`~epytope.Core.Peptide.Peptide` sequences to write into file
:param File file: File-handler to input file for external tool
"""
file.write("\n".join(input))
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
f = csv.reader(open(file, "r"), delimiter='\t')
alleles = [x for x in next(f) if x != ""]
next(f)
ic_pos = 3
for row in f:
pep_seq = row[1]
for i, a in enumerate(alleles):
result[a][pep_seq] = float(row[ic_pos + i * 3])
return result
class NetMHCpan_3_0(NetMHCpan_2_8):
"""
Implements the NetMHC binding version 3.0
Supported MHC alleles currently only restricted to HLA alleles.
.. note::
Nielsen, M., & Andreatta, M. (2016).
NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple
receptor and peptide length datasets. Genome Medicine, 8(1), 1.
"""
__version = "3.0"
__command = "netMHCpan -p {peptides} -a {alleles} {options} -xls -xlsfile {out}"
@property
def version(self):
return self.__version
@property
def command(self):
return self.__command
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
f = csv.reader(open(file, "r"), delimiter='\t')
alleles = [x for x in next(f) if x != ""]
next(f)
ic_pos = 4
for row in f:
pep_seq = row[1]
for i, a in enumerate(alleles):
result[a][pep_seq] = float(row[ic_pos + i * 4])
return result
class NetMHCpan_4_0(NetMHCpan_3_0):
"""
Implements the NetMHC binding version 4.0
Supported MHC alleles currently only restricted to HLA alleles.
"""
__version = "4.0"
__command = "netMHCpan -p {peptides} -a {alleles} {options} -xls -xlsfile {out}"
@property
def version(self):
return self.__version
@property
def command(self):
return self.__command
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
f = csv.reader(open(file, "r"), delimiter='\t')
alleles = [x for x in next(f) if x != ""]
next(f)
ic_pos = 5
for row in f:
pep_seq = row[1]
for i, a in enumerate(alleles):
result[a][pep_seq] = float(row[ic_pos + i * 5])
return result
class NetMHCstabpan_1_0(AExternalEpitopePrediction):
"""
Implements a wrapper to NetMHCstabpan 1.0
.. note:
Pan-specific prediction of peptide-MHC-I complex stability; a correlate of T cell immunogenicity
M Rasmussen, E Fenoy, M Nielsen, Buus S, Accepted JI June, 2016
"""
__name = "netMHCstabpan"
__length = frozenset([8, 9, 10, 11])
__version = "1.0"
__command = "netMHCstabpan -p {peptides} -a {alleles} {options} -xls -xlsfile {out}"
__alleles = frozenset(['HLA-A*01:01', 'HLA-A*01:02', 'HLA-A*01:03', 'HLA-A*01:06', 'HLA-A*01:07', 'HLA-A*01:08', 'HLA-A*01:09', 'HLA-A*01:10', 'HLA-A*01:12',
'HLA-A*01:13', 'HLA-A*01:14', 'HLA-A*01:17', 'HLA-A*01:19', 'HLA-A*01:20', 'HLA-A*01:21', 'HLA-A*01:23', 'HLA-A*01:24',
'HLA-A*01:25', 'HLA-A*01:26', 'HLA-A*01:28', 'HLA-A*01:29', 'HLA-A*01:30', 'HLA-A*01:32', 'HLA-A*01:33', 'HLA-A*01:35',
'HLA-A*01:36', 'HLA-A*01:37', 'HLA-A*01:38', 'HLA-A*01:39', 'HLA-A*01:40', 'HLA-A*01:41', 'HLA-A*01:42', 'HLA-A*01:43',
'HLA-A*01:44', 'HLA-A*01:45', 'HLA-A*01:46', 'HLA-A*01:47', 'HLA-A*01:48', 'HLA-A*01:49', 'HLA-A*01:50', 'HLA-A*01:51',
'HLA-A*01:54', 'HLA-A*01:55', 'HLA-A*01:58', 'HLA-A*01:59', 'HLA-A*01:60', 'HLA-A*01:61', 'HLA-A*01:62', 'HLA-A*01:63',
'HLA-A*01:64', 'HLA-A*01:65', 'HLA-A*01:66', 'HLA-A*02:01', 'HLA-A*02:02', 'HLA-A*02:03', 'HLA-A*02:04', 'HLA-A*02:05',
'HLA-A*02:06', 'HLA-A*02:07', 'HLA-A*02:08', 'HLA-A*02:09', 'HLA-A*02:10', 'HLA-A*02:11', 'HLA-A*02:12', 'HLA-A*02:13',
'HLA-A*02:14', 'HLA-A*02:16', 'HLA-A*02:17', 'HLA-A*02:18', 'HLA-A*02:19', 'HLA-A*02:20', 'HLA-A*02:21', 'HLA-A*02:22',
'HLA-A*02:24', 'HLA-A*02:25', 'HLA-A*02:26', 'HLA-A*02:27', 'HLA-A*02:28', 'HLA-A*02:29', 'HLA-A*02:30', 'HLA-A*02:31',
'HLA-A*02:33', 'HLA-A*02:34', 'HLA-A*02:35', 'HLA-A*02:36', 'HLA-A*02:37', 'HLA-A*02:38', 'HLA-A*02:39', 'HLA-A*02:40',
'HLA-A*02:41', 'HLA-A*02:42', 'HLA-A*02:44', 'HLA-A*02:45', 'HLA-A*02:46', 'HLA-A*02:47', 'HLA-A*02:48', 'HLA-A*02:49',
'HLA-A*02:50', 'HLA-A*02:51', 'HLA-A*02:52', 'HLA-A*02:54', 'HLA-A*02:55', 'HLA-A*02:56', 'HLA-A*02:57', 'HLA-A*02:58',
'HLA-A*02:59', 'HLA-A*02:60', 'HLA-A*02:61', 'HLA-A*02:62', 'HLA-A*02:63', 'HLA-A*02:64', 'HLA-A*02:65', 'HLA-A*02:66',
'HLA-A*02:67', 'HLA-A*02:68', 'HLA-A*02:69', 'HLA-A*02:70', 'HLA-A*02:71', 'HLA-A*02:72', 'HLA-A*02:73', 'HLA-A*02:74',
'HLA-A*02:75', 'HLA-A*02:76', 'HLA-A*02:77', 'HLA-A*02:78', 'HLA-A*02:79', 'HLA-A*02:80', 'HLA-A*02:81', 'HLA-A*02:84',
'HLA-A*02:85', 'HLA-A*02:86', 'HLA-A*02:87', 'HLA-A*02:89', 'HLA-A*02:90', 'HLA-A*02:91', 'HLA-A*02:92', 'HLA-A*02:93',
'HLA-A*02:95', 'HLA-A*02:96', 'HLA-A*02:97', 'HLA-A*02:99', 'HLA-A*02:101', 'HLA-A*02:102', 'HLA-A*02:103', 'HLA-A*02:104',
'HLA-A*02:105', 'HLA-A*02:106', 'HLA-A*02:107', 'HLA-A*02:108', 'HLA-A*02:109', 'HLA-A*02:110', 'HLA-A*02:111',
'HLA-A*02:112', 'HLA-A*02:114', 'HLA-A*02:115', 'HLA-A*02:116', 'HLA-A*02:117', 'HLA-A*02:118', 'HLA-A*02:119',
'HLA-A*02:120', 'HLA-A*02:121', 'HLA-A*02:122', 'HLA-A*02:123', 'HLA-A*02:124', 'HLA-A*02:126', 'HLA-A*02:127',
'HLA-A*02:128', 'HLA-A*02:129', 'HLA-A*02:130', 'HLA-A*02:131', 'HLA-A*02:132', 'HLA-A*02:133', 'HLA-A*02:134',
'HLA-A*02:135', 'HLA-A*02:136', 'HLA-A*02:137', 'HLA-A*02:138', 'HLA-A*02:139', 'HLA-A*02:140', 'HLA-A*02:141',
'HLA-A*02:142', 'HLA-A*02:143', 'HLA-A*02:144', 'HLA-A*02:145', 'HLA-A*02:146', 'HLA-A*02:147', 'HLA-A*02:148',
'HLA-A*02:149', 'HLA-A*02:150', 'HLA-A*02:151', 'HLA-A*02:152', 'HLA-A*02:153', 'HLA-A*02:154', 'HLA-A*02:155',
'HLA-A*02:156', 'HLA-A*02:157', 'HLA-A*02:158', 'HLA-A*02:159', 'HLA-A*02:160', 'HLA-A*02:161', 'HLA-A*02:162',
'HLA-A*02:163', 'HLA-A*02:164', 'HLA-A*02:165', 'HLA-A*02:166', 'HLA-A*02:167', 'HLA-A*02:168', 'HLA-A*02:169',
'HLA-A*02:170', 'HLA-A*02:171', 'HLA-A*02:172', 'HLA-A*02:173', 'HLA-A*02:174', 'HLA-A*02:175', 'HLA-A*02:176',
'HLA-A*02:177', 'HLA-A*02:178', 'HLA-A*02:179', 'HLA-A*02:180', 'HLA-A*02:181', 'HLA-A*02:182', 'HLA-A*02:183',
'HLA-A*02:184', 'HLA-A*02:185', 'HLA-A*02:186', 'HLA-A*02:187', 'HLA-A*02:188', 'HLA-A*02:189', 'HLA-A*02:190',
'HLA-A*02:191', 'HLA-A*02:192', 'HLA-A*02:193', 'HLA-A*02:194', 'HLA-A*02:195', 'HLA-A*02:196', 'HLA-A*02:197',
'HLA-A*02:198', 'HLA-A*02:199', 'HLA-A*02:200', 'HLA-A*02:201', 'HLA-A*02:202', 'HLA-A*02:203', 'HLA-A*02:204',
'HLA-A*02:205', 'HLA-A*02:206', 'HLA-A*02:207', 'HLA-A*02:208', 'HLA-A*02:209', 'HLA-A*02:210', 'HLA-A*02:211',
'HLA-A*02:212', 'HLA-A*02:213', 'HLA-A*02:214', 'HLA-A*02:215', 'HLA-A*02:216', 'HLA-A*02:217', 'HLA-A*02:218',
'HLA-A*02:219', 'HLA-A*02:220', 'HLA-A*02:221', 'HLA-A*02:224', 'HLA-A*02:228', 'HLA-A*02:229', 'HLA-A*02:230',
'HLA-A*02:231', 'HLA-A*02:232', 'HLA-A*02:233', 'HLA-A*02:234', 'HLA-A*02:235', 'HLA-A*02:236', 'HLA-A*02:237',
'HLA-A*02:238', 'HLA-A*02:239', 'HLA-A*02:240', 'HLA-A*02:241', 'HLA-A*02:242', 'HLA-A*02:243', 'HLA-A*02:244',
'HLA-A*02:245', 'HLA-A*02:246', 'HLA-A*02:247', 'HLA-A*02:248', 'HLA-A*02:249', 'HLA-A*02:251', 'HLA-A*02:252',
'HLA-A*02:253', 'HLA-A*02:254', 'HLA-A*02:255', 'HLA-A*02:256', 'HLA-A*02:257', 'HLA-A*02:258', 'HLA-A*02:259',
'HLA-A*02:260', 'HLA-A*02:261', 'HLA-A*02:262', 'HLA-A*02:263', 'HLA-A*02:264', 'HLA-A*02:265', 'HLA-A*02:266',
'HLA-A*03:01', 'HLA-A*03:02', 'HLA-A*03:04', 'HLA-A*03:05', 'HLA-A*03:06', 'HLA-A*03:07', 'HLA-A*03:08', 'HLA-A*03:09',
'HLA-A*03:10', 'HLA-A*03:12', 'HLA-A*03:13', 'HLA-A*03:14', 'HLA-A*03:15', 'HLA-A*03:16', 'HLA-A*03:17', 'HLA-A*03:18',
'HLA-A*03:19', 'HLA-A*03:20', 'HLA-A*03:22', 'HLA-A*03:23', 'HLA-A*03:24', 'HLA-A*03:25', 'HLA-A*03:26', 'HLA-A*03:27',
'HLA-A*03:28', 'HLA-A*03:29', 'HLA-A*03:30', 'HLA-A*03:31', 'HLA-A*03:32', 'HLA-A*03:33', 'HLA-A*03:34', 'HLA-A*03:35',
'HLA-A*03:37', 'HLA-A*03:38', 'HLA-A*03:39', 'HLA-A*03:40', 'HLA-A*03:41', 'HLA-A*03:42', 'HLA-A*03:43', 'HLA-A*03:44',
'HLA-A*03:45', 'HLA-A*03:46', 'HLA-A*03:47', 'HLA-A*03:48', 'HLA-A*03:49', 'HLA-A*03:50', 'HLA-A*03:51', 'HLA-A*03:52',
'HLA-A*03:53', 'HLA-A*03:54', 'HLA-A*03:55', 'HLA-A*03:56', 'HLA-A*03:57', 'HLA-A*03:58', 'HLA-A*03:59', 'HLA-A*03:60',
'HLA-A*03:61', 'HLA-A*03:62', 'HLA-A*03:63', 'HLA-A*03:64', 'HLA-A*03:65', 'HLA-A*03:66', 'HLA-A*03:67', 'HLA-A*03:70',
'HLA-A*03:71', 'HLA-A*03:72', 'HLA-A*03:73', 'HLA-A*03:74', 'HLA-A*03:75', 'HLA-A*03:76', 'HLA-A*03:77', 'HLA-A*03:78',
'HLA-A*03:79', 'HLA-A*03:80', 'HLA-A*03:81', 'HLA-A*03:82', 'HLA-A*11:01', 'HLA-A*11:02', 'HLA-A*11:03', 'HLA-A*11:04',
'HLA-A*11:05', 'HLA-A*11:06', 'HLA-A*11:07', 'HLA-A*11:08', 'HLA-A*11:09', 'HLA-A*11:10', 'HLA-A*11:11', 'HLA-A*11:12',
'HLA-A*11:13', 'HLA-A*11:14', 'HLA-A*11:15', 'HLA-A*11:16', 'HLA-A*11:17', 'HLA-A*11:18', 'HLA-A*11:19', 'HLA-A*11:20',
'HLA-A*11:22', 'HLA-A*11:23', 'HLA-A*11:24', 'HLA-A*11:25', 'HLA-A*11:26', 'HLA-A*11:27', 'HLA-A*11:29', 'HLA-A*11:30',
'HLA-A*11:31', 'HLA-A*11:32', 'HLA-A*11:33', 'HLA-A*11:34', 'HLA-A*11:35', 'HLA-A*11:36', 'HLA-A*11:37', 'HLA-A*11:38',
'HLA-A*11:39', 'HLA-A*11:40', 'HLA-A*11:41', 'HLA-A*11:42', 'HLA-A*11:43', 'HLA-A*11:44', 'HLA-A*11:45', 'HLA-A*11:46',
'HLA-A*11:47', 'HLA-A*11:48', 'HLA-A*11:49', 'HLA-A*11:51', 'HLA-A*11:53', 'HLA-A*11:54', 'HLA-A*11:55', 'HLA-A*11:56',
'HLA-A*11:57', 'HLA-A*11:58', 'HLA-A*11:59', 'HLA-A*11:60', 'HLA-A*11:61', 'HLA-A*11:62', 'HLA-A*11:63', 'HLA-A*11:64',
'HLA-A*23:01', 'HLA-A*23:02', 'HLA-A*23:03', 'HLA-A*23:04', 'HLA-A*23:05', 'HLA-A*23:06', 'HLA-A*23:09', 'HLA-A*23:10',
'HLA-A*23:12', 'HLA-A*23:13', 'HLA-A*23:14', 'HLA-A*23:15', 'HLA-A*23:16', 'HLA-A*23:17', 'HLA-A*23:18', 'HLA-A*23:20',
'HLA-A*23:21', 'HLA-A*23:22', 'HLA-A*23:23', 'HLA-A*23:24', 'HLA-A*23:25', 'HLA-A*23:26', 'HLA-A*24:02', 'HLA-A*24:03',
'HLA-A*24:04', 'HLA-A*24:05', 'HLA-A*24:06', 'HLA-A*24:07', 'HLA-A*24:08', 'HLA-A*24:10', 'HLA-A*24:13', 'HLA-A*24:14',
'HLA-A*24:15', 'HLA-A*24:17', 'HLA-A*24:18', 'HLA-A*24:19', 'HLA-A*24:20', 'HLA-A*24:21', 'HLA-A*24:22', 'HLA-A*24:23',
'HLA-A*24:24', 'HLA-A*24:25', 'HLA-A*24:26', 'HLA-A*24:27', 'HLA-A*24:28', 'HLA-A*24:29', 'HLA-A*24:30', 'HLA-A*24:31',
'HLA-A*24:32', 'HLA-A*24:33', 'HLA-A*24:34', 'HLA-A*24:35', 'HLA-A*24:37', 'HLA-A*24:38', 'HLA-A*24:39', 'HLA-A*24:41',
'HLA-A*24:42', 'HLA-A*24:43', 'HLA-A*24:44', 'HLA-A*24:46', 'HLA-A*24:47', 'HLA-A*24:49', 'HLA-A*24:50', 'HLA-A*24:51',
'HLA-A*24:52', 'HLA-A*24:53', 'HLA-A*24:54', 'HLA-A*24:55', 'HLA-A*24:56', 'HLA-A*24:57', 'HLA-A*24:58', 'HLA-A*24:59',
'HLA-A*24:61', 'HLA-A*24:62', 'HLA-A*24:63', 'HLA-A*24:64', 'HLA-A*24:66', 'HLA-A*24:67', 'HLA-A*24:68', 'HLA-A*24:69',
'HLA-A*24:70', 'HLA-A*24:71', 'HLA-A*24:72', 'HLA-A*24:73', 'HLA-A*24:74', 'HLA-A*24:75', 'HLA-A*24:76', 'HLA-A*24:77',
'HLA-A*24:78', 'HLA-A*24:79', 'HLA-A*24:80', 'HLA-A*24:81', 'HLA-A*24:82', 'HLA-A*24:85', 'HLA-A*24:87', 'HLA-A*24:88',
'HLA-A*24:89', 'HLA-A*24:91', 'HLA-A*24:92', 'HLA-A*24:93', 'HLA-A*24:94', 'HLA-A*24:95', 'HLA-A*24:96', 'HLA-A*24:97',
'HLA-A*24:98', 'HLA-A*24:99', 'HLA-A*24:100', 'HLA-A*24:101', 'HLA-A*24:102', 'HLA-A*24:103', 'HLA-A*24:104',
'HLA-A*24:105', 'HLA-A*24:106', 'HLA-A*24:107', 'HLA-A*24:108', 'HLA-A*24:109', 'HLA-A*24:110', 'HLA-A*24:111',
'HLA-A*24:112', 'HLA-A*24:113', 'HLA-A*24:114', 'HLA-A*24:115', 'HLA-A*24:116', 'HLA-A*24:117', 'HLA-A*24:118',
'HLA-A*24:119', 'HLA-A*24:120', 'HLA-A*24:121', 'HLA-A*24:122', 'HLA-A*24:123', 'HLA-A*24:124', 'HLA-A*24:125',
'HLA-A*24:126', 'HLA-A*24:127', 'HLA-A*24:128', 'HLA-A*24:129', 'HLA-A*24:130', 'HLA-A*24:131', 'HLA-A*24:133',
'HLA-A*24:134', 'HLA-A*24:135', 'HLA-A*24:136', 'HLA-A*24:137', 'HLA-A*24:138', 'HLA-A*24:139', 'HLA-A*24:140',
'HLA-A*24:141', 'HLA-A*24:142', 'HLA-A*24:143', 'HLA-A*24:144', 'HLA-A*25:01', 'HLA-A*25:02', 'HLA-A*25:03', 'HLA-A*25:04',
'HLA-A*25:05', 'HLA-A*25:06', 'HLA-A*25:07', 'HLA-A*25:08', 'HLA-A*25:09', 'HLA-A*25:10', 'HLA-A*25:11', 'HLA-A*25:13',
'HLA-A*26:01', 'HLA-A*26:02', 'HLA-A*26:03', 'HLA-A*26:04', 'HLA-A*26:05', 'HLA-A*26:06', 'HLA-A*26:07', 'HLA-A*26:08',
'HLA-A*26:09', 'HLA-A*26:10', 'HLA-A*26:12', 'HLA-A*26:13', 'HLA-A*26:14', 'HLA-A*26:15', 'HLA-A*26:16', 'HLA-A*26:17',
'HLA-A*26:18', 'HLA-A*26:19', 'HLA-A*26:20', 'HLA-A*26:21', 'HLA-A*26:22', 'HLA-A*26:23', 'HLA-A*26:24', 'HLA-A*26:26',
'HLA-A*26:27', 'HLA-A*26:28', 'HLA-A*26:29', 'HLA-A*26:30', 'HLA-A*26:31', 'HLA-A*26:32', 'HLA-A*26:33', 'HLA-A*26:34',
'HLA-A*26:35', 'HLA-A*26:36', 'HLA-A*26:37', 'HLA-A*26:38', 'HLA-A*26:39', 'HLA-A*26:40', 'HLA-A*26:41', 'HLA-A*26:42',
'HLA-A*26:43', 'HLA-A*26:45', 'HLA-A*26:46', 'HLA-A*26:47', 'HLA-A*26:48', 'HLA-A*26:49', 'HLA-A*26:50', 'HLA-A*29:01',
'HLA-A*29:02', 'HLA-A*29:03', 'HLA-A*29:04', 'HLA-A*29:05', 'HLA-A*29:06', 'HLA-A*29:07', 'HLA-A*29:09', 'HLA-A*29:10',
'HLA-A*29:11', 'HLA-A*29:12', 'HLA-A*29:13', 'HLA-A*29:14', 'HLA-A*29:15', 'HLA-A*29:16', 'HLA-A*29:17', 'HLA-A*29:18',
'HLA-A*29:19', 'HLA-A*29:20', 'HLA-A*29:21', 'HLA-A*29:22', 'HLA-A*30:01', 'HLA-A*30:02', 'HLA-A*30:03', 'HLA-A*30:04',
'HLA-A*30:06', 'HLA-A*30:07', 'HLA-A*30:08', 'HLA-A*30:09', 'HLA-A*30:10', 'HLA-A*30:11', 'HLA-A*30:12', 'HLA-A*30:13',
'HLA-A*30:15', 'HLA-A*30:16', 'HLA-A*30:17', 'HLA-A*30:18', 'HLA-A*30:19', 'HLA-A*30:20', 'HLA-A*30:22', 'HLA-A*30:23',
'HLA-A*30:24', 'HLA-A*30:25', 'HLA-A*30:26', 'HLA-A*30:28', 'HLA-A*30:29', 'HLA-A*30:30', 'HLA-A*30:31', 'HLA-A*30:32',
'HLA-A*30:33', 'HLA-A*30:34', 'HLA-A*30:35', 'HLA-A*30:36', 'HLA-A*30:37', 'HLA-A*30:38', 'HLA-A*30:39', 'HLA-A*30:40',
'HLA-A*30:41', 'HLA-A*31:01', 'HLA-A*31:02', 'HLA-A*31:03', 'HLA-A*31:04', 'HLA-A*31:05', 'HLA-A*31:06', 'HLA-A*31:07',
'HLA-A*31:08', 'HLA-A*31:09', 'HLA-A*31:10', 'HLA-A*31:11', 'HLA-A*31:12', 'HLA-A*31:13', 'HLA-A*31:15', 'HLA-A*31:16',
'HLA-A*31:17', 'HLA-A*31:18', 'HLA-A*31:19', 'HLA-A*31:20', 'HLA-A*31:21', 'HLA-A*31:22', 'HLA-A*31:23', 'HLA-A*31:24',
'HLA-A*31:25', 'HLA-A*31:26', 'HLA-A*31:27', 'HLA-A*31:28', 'HLA-A*31:29', 'HLA-A*31:30', 'HLA-A*31:31', 'HLA-A*31:32',
'HLA-A*31:33', 'HLA-A*31:34', 'HLA-A*31:35', 'HLA-A*31:36', 'HLA-A*31:37', 'HLA-A*32:01', 'HLA-A*32:02', 'HLA-A*32:03',
'HLA-A*32:04', 'HLA-A*32:05', 'HLA-A*32:06', 'HLA-A*32:07', 'HLA-A*32:08', 'HLA-A*32:09', 'HLA-A*32:10', 'HLA-A*32:12',
'HLA-A*32:13', 'HLA-A*32:14', 'HLA-A*32:15', 'HLA-A*32:16', 'HLA-A*32:17', 'HLA-A*32:18', 'HLA-A*32:20', 'HLA-A*32:21',
'HLA-A*32:22', 'HLA-A*32:23', 'HLA-A*32:24', 'HLA-A*32:25', 'HLA-A*33:01', 'HLA-A*33:03', 'HLA-A*33:04', 'HLA-A*33:05',
'HLA-A*33:06', 'HLA-A*33:07', 'HLA-A*33:08', 'HLA-A*33:09', 'HLA-A*33:10', 'HLA-A*33:11', 'HLA-A*33:12', 'HLA-A*33:13',
'HLA-A*33:14', 'HLA-A*33:15', 'HLA-A*33:16', 'HLA-A*33:17', 'HLA-A*33:18', 'HLA-A*33:19', 'HLA-A*33:20', 'HLA-A*33:21',
'HLA-A*33:22', 'HLA-A*33:23', 'HLA-A*33:24', 'HLA-A*33:25', 'HLA-A*33:26', 'HLA-A*33:27', 'HLA-A*33:28', 'HLA-A*33:29',
'HLA-A*33:30', 'HLA-A*33:31', 'HLA-A*34:01', 'HLA-A*34:02', 'HLA-A*34:03', 'HLA-A*34:04', 'HLA-A*34:05', 'HLA-A*34:06',
'HLA-A*34:07', 'HLA-A*34:08', 'HLA-A*36:01', 'HLA-A*36:02', 'HLA-A*36:03', 'HLA-A*36:04', 'HLA-A*36:05', 'HLA-A*43:01',
'HLA-A*66:01', 'HLA-A*66:02', 'HLA-A*66:03', 'HLA-A*66:04', 'HLA-A*66:05', 'HLA-A*66:06', 'HLA-A*66:07', 'HLA-A*66:08',
'HLA-A*66:09', 'HLA-A*66:10', 'HLA-A*66:11', 'HLA-A*66:12', 'HLA-A*66:13', 'HLA-A*66:14', 'HLA-A*66:15', 'HLA-A*68:01',
'HLA-A*68:02', 'HLA-A*68:03', 'HLA-A*68:04', 'HLA-A*68:05', 'HLA-A*68:06', 'HLA-A*68:07', 'HLA-A*68:08', 'HLA-A*68:09',
'HLA-A*68:10', 'HLA-A*68:12', 'HLA-A*68:13', 'HLA-A*68:14', 'HLA-A*68:15', 'HLA-A*68:16', 'HLA-A*68:17', 'HLA-A*68:19',
'HLA-A*68:20', 'HLA-A*68:21', 'HLA-A*68:22', 'HLA-A*68:23', 'HLA-A*68:24', 'HLA-A*68:25', 'HLA-A*68:26', 'HLA-A*68:27',
'HLA-A*68:28', 'HLA-A*68:29', 'HLA-A*68:30', 'HLA-A*68:31', 'HLA-A*68:32', 'HLA-A*68:33', 'HLA-A*68:34', 'HLA-A*68:35',
'HLA-A*68:36', 'HLA-A*68:37', 'HLA-A*68:38', 'HLA-A*68:39', 'HLA-A*68:40', 'HLA-A*68:41', 'HLA-A*68:42', 'HLA-A*68:43',
'HLA-A*68:44', 'HLA-A*68:45', 'HLA-A*68:46', 'HLA-A*68:47', 'HLA-A*68:48', 'HLA-A*68:50', 'HLA-A*68:51', 'HLA-A*68:52',
'HLA-A*68:53', 'HLA-A*68:54', 'HLA-A*69:01', 'HLA-A*74:01', 'HLA-A*74:02', 'HLA-A*74:03', 'HLA-A*74:04', 'HLA-A*74:05',
'HLA-A*74:06', 'HLA-A*74:07', 'HLA-A*74:08', 'HLA-A*74:09', 'HLA-A*74:10', 'HLA-A*74:11', 'HLA-A*74:13', 'HLA-A*80:01',
'HLA-A*80:02', 'HLA-B*07:02', 'HLA-B*07:03', 'HLA-B*07:04', 'HLA-B*07:05', 'HLA-B*07:06', 'HLA-B*07:07', 'HLA-B*07:08',
'HLA-B*07:09', 'HLA-B*07:10', 'HLA-B*07:11', 'HLA-B*07:12', 'HLA-B*07:13', 'HLA-B*07:14', 'HLA-B*07:15', 'HLA-B*07:16',
'HLA-B*07:17', 'HLA-B*07:18', 'HLA-B*07:19', 'HLA-B*07:20', 'HLA-B*07:21', 'HLA-B*07:22', 'HLA-B*07:23', 'HLA-B*07:24',
'HLA-B*07:25', 'HLA-B*07:26', 'HLA-B*07:27', 'HLA-B*07:28', 'HLA-B*07:29', 'HLA-B*07:30', 'HLA-B*07:31', 'HLA-B*07:32',
'HLA-B*07:33', 'HLA-B*07:34', 'HLA-B*07:35', 'HLA-B*07:36', 'HLA-B*07:37', 'HLA-B*07:38', 'HLA-B*07:39', 'HLA-B*07:40',
'HLA-B*07:41', 'HLA-B*07:42', 'HLA-B*07:43', 'HLA-B*07:44', 'HLA-B*07:45', 'HLA-B*07:46', 'HLA-B*07:47', 'HLA-B*07:48',
'HLA-B*07:50', 'HLA-B*07:51', 'HLA-B*07:52', 'HLA-B*07:53', 'HLA-B*07:54', 'HLA-B*07:55', 'HLA-B*07:56', 'HLA-B*07:57',
'HLA-B*07:58', 'HLA-B*07:59', 'HLA-B*07:60', 'HLA-B*07:61', 'HLA-B*07:62', 'HLA-B*07:63', 'HLA-B*07:64', 'HLA-B*07:65',
'HLA-B*07:66', 'HLA-B*07:68', 'HLA-B*07:69', 'HLA-B*07:70', 'HLA-B*07:71', 'HLA-B*07:72', 'HLA-B*07:73', 'HLA-B*07:74',
'HLA-B*07:75', 'HLA-B*07:76', 'HLA-B*07:77', 'HLA-B*07:78', 'HLA-B*07:79', 'HLA-B*07:80', 'HLA-B*07:81', 'HLA-B*07:82',
'HLA-B*07:83', 'HLA-B*07:84', 'HLA-B*07:85', 'HLA-B*07:86', 'HLA-B*07:87', 'HLA-B*07:88', 'HLA-B*07:89', 'HLA-B*07:90',
'HLA-B*07:91', 'HLA-B*07:92', 'HLA-B*07:93', 'HLA-B*07:94', 'HLA-B*07:95', 'HLA-B*07:96', 'HLA-B*07:97', 'HLA-B*07:98',
'HLA-B*07:99', 'HLA-B*07:100', 'HLA-B*07:101', 'HLA-B*07:102', 'HLA-B*07:103', 'HLA-B*07:104', 'HLA-B*07:105',
'HLA-B*07:106', 'HLA-B*07:107', 'HLA-B*07:108', 'HLA-B*07:109', 'HLA-B*07:110', 'HLA-B*07:112', 'HLA-B*07:113',
'HLA-B*07:114', 'HLA-B*07:115', 'HLA-B*08:01', 'HLA-B*08:02', 'HLA-B*08:03', 'HLA-B*08:04', 'HLA-B*08:05', 'HLA-B*08:07',
'HLA-B*08:09', 'HLA-B*08:10', 'HLA-B*08:11', 'HLA-B*08:12', 'HLA-B*08:13', 'HLA-B*08:14', 'HLA-B*08:15', 'HLA-B*08:16',
'HLA-B*08:17', 'HLA-B*08:18', 'HLA-B*08:20', 'HLA-B*08:21', 'HLA-B*08:22', 'HLA-B*08:23', 'HLA-B*08:24', 'HLA-B*08:25',
'HLA-B*08:26', 'HLA-B*08:27', 'HLA-B*08:28', 'HLA-B*08:29', 'HLA-B*08:31', 'HLA-B*08:32', 'HLA-B*08:33', 'HLA-B*08:34',
'HLA-B*08:35', 'HLA-B*08:36', 'HLA-B*08:37', 'HLA-B*08:38', 'HLA-B*08:39', 'HLA-B*08:40', 'HLA-B*08:41', 'HLA-B*08:42',
'HLA-B*08:43', 'HLA-B*08:44', 'HLA-B*08:45', 'HLA-B*08:46', 'HLA-B*08:47', 'HLA-B*08:48', 'HLA-B*08:49', 'HLA-B*08:50',
'HLA-B*08:51', 'HLA-B*08:52', 'HLA-B*08:53', 'HLA-B*08:54', 'HLA-B*08:55', 'HLA-B*08:56', 'HLA-B*08:57', 'HLA-B*08:58',
'HLA-B*08:59', 'HLA-B*08:60', 'HLA-B*08:61', 'HLA-B*08:62', 'HLA-B*13:01', 'HLA-B*13:02', 'HLA-B*13:03', 'HLA-B*13:04',
'HLA-B*13:06', 'HLA-B*13:09', 'HLA-B*13:10', 'HLA-B*13:11', 'HLA-B*13:12', 'HLA-B*13:13', 'HLA-B*13:14', 'HLA-B*13:15',
'HLA-B*13:16', 'HLA-B*13:17', 'HLA-B*13:18', 'HLA-B*13:19', 'HLA-B*13:20', 'HLA-B*13:21', 'HLA-B*13:22', 'HLA-B*13:23',
'HLA-B*13:25', 'HLA-B*13:26', 'HLA-B*13:27', 'HLA-B*13:28', 'HLA-B*13:29', 'HLA-B*13:30', 'HLA-B*13:31', 'HLA-B*13:32',
'HLA-B*13:33', 'HLA-B*13:34', 'HLA-B*13:35', 'HLA-B*13:36', 'HLA-B*13:37', 'HLA-B*13:38', 'HLA-B*13:39', 'HLA-B*14:01',
'HLA-B*14:02', 'HLA-B*14:03', 'HLA-B*14:04', 'HLA-B*14:05', 'HLA-B*14:06', 'HLA-B*14:08', 'HLA-B*14:09', 'HLA-B*14:10',
'HLA-B*14:11', 'HLA-B*14:12', 'HLA-B*14:13', 'HLA-B*14:14', 'HLA-B*14:15', 'HLA-B*14:16', 'HLA-B*14:17', 'HLA-B*14:18',
'HLA-B*15:01', 'HLA-B*15:02', 'HLA-B*15:03', 'HLA-B*15:04', 'HLA-B*15:05', 'HLA-B*15:06', 'HLA-B*15:07', 'HLA-B*15:08',
'HLA-B*15:09', 'HLA-B*15:10', 'HLA-B*15:11', 'HLA-B*15:12', 'HLA-B*15:13', 'HLA-B*15:14', 'HLA-B*15:15', 'HLA-B*15:16',
'HLA-B*15:17', 'HLA-B*15:18', 'HLA-B*15:19', 'HLA-B*15:20', 'HLA-B*15:21', 'HLA-B*15:23', 'HLA-B*15:24', 'HLA-B*15:25',
'HLA-B*15:27', 'HLA-B*15:28', 'HLA-B*15:29', 'HLA-B*15:30', 'HLA-B*15:31', 'HLA-B*15:32', 'HLA-B*15:33', 'HLA-B*15:34',
'HLA-B*15:35', 'HLA-B*15:36', 'HLA-B*15:37', 'HLA-B*15:38', 'HLA-B*15:39', 'HLA-B*15:40', 'HLA-B*15:42', 'HLA-B*15:43',
'HLA-B*15:44', 'HLA-B*15:45', 'HLA-B*15:46', 'HLA-B*15:47', 'HLA-B*15:48', 'HLA-B*15:49', 'HLA-B*15:50', 'HLA-B*15:51',
'HLA-B*15:52', 'HLA-B*15:53', 'HLA-B*15:54', 'HLA-B*15:55', 'HLA-B*15:56', 'HLA-B*15:57', 'HLA-B*15:58', 'HLA-B*15:60',
'HLA-B*15:61', 'HLA-B*15:62', 'HLA-B*15:63', 'HLA-B*15:64', 'HLA-B*15:65', 'HLA-B*15:66', 'HLA-B*15:67', 'HLA-B*15:68',
'HLA-B*15:69', 'HLA-B*15:70', 'HLA-B*15:71', 'HLA-B*15:72', 'HLA-B*15:73', 'HLA-B*15:74', 'HLA-B*15:75', 'HLA-B*15:76',
'HLA-B*15:77', 'HLA-B*15:78', 'HLA-B*15:80', 'HLA-B*15:81', 'HLA-B*15:82', 'HLA-B*15:83', 'HLA-B*15:84', 'HLA-B*15:85',
'HLA-B*15:86', 'HLA-B*15:87', 'HLA-B*15:88', 'HLA-B*15:89', 'HLA-B*15:90', 'HLA-B*15:91', 'HLA-B*15:92', 'HLA-B*15:93',
'HLA-B*15:95', 'HLA-B*15:96', 'HLA-B*15:97', 'HLA-B*15:98', 'HLA-B*15:99', 'HLA-B*15:101', 'HLA-B*15:102', 'HLA-B*15:103',
'HLA-B*15:104', 'HLA-B*15:105', 'HLA-B*15:106', 'HLA-B*15:107', 'HLA-B*15:108', 'HLA-B*15:109', 'HLA-B*15:110',
'HLA-B*15:112', 'HLA-B*15:113', 'HLA-B*15:114', 'HLA-B*15:115', 'HLA-B*15:116', 'HLA-B*15:117', 'HLA-B*15:118',
'HLA-B*15:119', 'HLA-B*15:120', 'HLA-B*15:121', 'HLA-B*15:122', 'HLA-B*15:123', 'HLA-B*15:124', 'HLA-B*15:125',
'HLA-B*15:126', 'HLA-B*15:127', 'HLA-B*15:128', 'HLA-B*15:129', 'HLA-B*15:131', 'HLA-B*15:132', 'HLA-B*15:133',
'HLA-B*15:134', 'HLA-B*15:135', 'HLA-B*15:136', 'HLA-B*15:137', 'HLA-B*15:138', 'HLA-B*15:139', 'HLA-B*15:140',
'HLA-B*15:141', 'HLA-B*15:142', 'HLA-B*15:143', 'HLA-B*15:144', 'HLA-B*15:145', 'HLA-B*15:146', 'HLA-B*15:147',
'HLA-B*15:148', 'HLA-B*15:150', 'HLA-B*15:151', 'HLA-B*15:152', 'HLA-B*15:153', 'HLA-B*15:154', 'HLA-B*15:155',
'HLA-B*15:156', 'HLA-B*15:157', 'HLA-B*15:158', 'HLA-B*15:159', 'HLA-B*15:160', 'HLA-B*15:161', 'HLA-B*15:162',
'HLA-B*15:163', 'HLA-B*15:164', 'HLA-B*15:165', 'HLA-B*15:166', 'HLA-B*15:167', 'HLA-B*15:168', 'HLA-B*15:169',
'HLA-B*15:170', 'HLA-B*15:171', 'HLA-B*15:172', 'HLA-B*15:173', 'HLA-B*15:174', 'HLA-B*15:175', 'HLA-B*15:176',
'HLA-B*15:177', 'HLA-B*15:178', 'HLA-B*15:179', 'HLA-B*15:180', 'HLA-B*15:183', 'HLA-B*15:184', 'HLA-B*15:185',
'HLA-B*15:186', 'HLA-B*15:187', 'HLA-B*15:188', 'HLA-B*15:189', 'HLA-B*15:191', 'HLA-B*15:192', 'HLA-B*15:193',
'HLA-B*15:194', 'HLA-B*15:195', 'HLA-B*15:196', 'HLA-B*15:197', 'HLA-B*15:198', 'HLA-B*15:199', 'HLA-B*15:200',
'HLA-B*15:201', 'HLA-B*15:202', 'HLA-B*18:01', 'HLA-B*18:02', 'HLA-B*18:03', 'HLA-B*18:04', 'HLA-B*18:05', 'HLA-B*18:06',
'HLA-B*18:07', 'HLA-B*18:08', 'HLA-B*18:09', 'HLA-B*18:10', 'HLA-B*18:11', 'HLA-B*18:12', 'HLA-B*18:13', 'HLA-B*18:14',
'HLA-B*18:15', 'HLA-B*18:18', 'HLA-B*18:19', 'HLA-B*18:20', 'HLA-B*18:21', 'HLA-B*18:22', 'HLA-B*18:24', 'HLA-B*18:25',
'HLA-B*18:26', 'HLA-B*18:27', 'HLA-B*18:28', 'HLA-B*18:29', 'HLA-B*18:30', 'HLA-B*18:31', 'HLA-B*18:32', 'HLA-B*18:33',
'HLA-B*18:34', 'HLA-B*18:35', 'HLA-B*18:36', 'HLA-B*18:37', 'HLA-B*18:38', 'HLA-B*18:39', 'HLA-B*18:40', 'HLA-B*18:41',
'HLA-B*18:42', 'HLA-B*18:43', 'HLA-B*18:44', 'HLA-B*18:45', 'HLA-B*18:46', 'HLA-B*18:47', 'HLA-B*18:48', 'HLA-B*18:49',
'HLA-B*18:50', 'HLA-B*27:01', 'HLA-B*27:02', 'HLA-B*27:03', 'HLA-B*27:04', 'HLA-B*27:05', 'HLA-B*27:06', 'HLA-B*27:07',
'HLA-B*27:08', 'HLA-B*27:09', 'HLA-B*27:10', 'HLA-B*27:11', 'HLA-B*27:12', 'HLA-B*27:13', 'HLA-B*27:14', 'HLA-B*27:15',
'HLA-B*27:16', 'HLA-B*27:17', 'HLA-B*27:18', 'HLA-B*27:19', 'HLA-B*27:20', 'HLA-B*27:21', 'HLA-B*27:23', 'HLA-B*27:24',
'HLA-B*27:25', 'HLA-B*27:26', 'HLA-B*27:27', 'HLA-B*27:28', 'HLA-B*27:29', 'HLA-B*27:30', 'HLA-B*27:31', 'HLA-B*27:32',
'HLA-B*27:33', 'HLA-B*27:34', 'HLA-B*27:35', 'HLA-B*27:36', 'HLA-B*27:37', 'HLA-B*27:38', 'HLA-B*27:39', 'HLA-B*27:40',
'HLA-B*27:41', 'HLA-B*27:42', 'HLA-B*27:43', 'HLA-B*27:44', 'HLA-B*27:45', 'HLA-B*27:46', 'HLA-B*27:47', 'HLA-B*27:48',
'HLA-B*27:49', 'HLA-B*27:50', 'HLA-B*27:51', 'HLA-B*27:52', 'HLA-B*27:53', 'HLA-B*27:54', 'HLA-B*27:55', 'HLA-B*27:56',
'HLA-B*27:57', 'HLA-B*27:58', 'HLA-B*27:60', 'HLA-B*27:61', 'HLA-B*27:62', 'HLA-B*27:63', 'HLA-B*27:67', 'HLA-B*27:68',
'HLA-B*27:69', 'HLA-B*35:01', 'HLA-B*35:02', 'HLA-B*35:03', 'HLA-B*35:04', 'HLA-B*35:05', 'HLA-B*35:06', 'HLA-B*35:07',
'HLA-B*35:08', 'HLA-B*35:09', 'HLA-B*35:10', 'HLA-B*35:11', 'HLA-B*35:12', 'HLA-B*35:13', 'HLA-B*35:14', 'HLA-B*35:15',
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'HLA-B*56:14', 'HLA-B*56:15', 'HLA-B*56:16', 'HLA-B*56:17', 'HLA-B*56:18', 'HLA-B*56:20', 'HLA-B*56:21', 'HLA-B*56:22',
'HLA-B*56:23', 'HLA-B*56:24', 'HLA-B*56:25', 'HLA-B*56:26', 'HLA-B*56:27', 'HLA-B*56:29', 'HLA-B*57:01', 'HLA-B*57:02',
'HLA-B*57:03', 'HLA-B*57:04', 'HLA-B*57:05', 'HLA-B*57:06', 'HLA-B*57:07', 'HLA-B*57:08', 'HLA-B*57:09', 'HLA-B*57:10',
'HLA-B*57:11', 'HLA-B*57:12', 'HLA-B*57:13', 'HLA-B*57:14', 'HLA-B*57:15', 'HLA-B*57:16', 'HLA-B*57:17', 'HLA-B*57:18',
'HLA-B*57:19', 'HLA-B*57:20', 'HLA-B*57:21', 'HLA-B*57:22', 'HLA-B*57:23', 'HLA-B*57:24', 'HLA-B*57:25', 'HLA-B*57:26',
'HLA-B*57:27', 'HLA-B*57:29', 'HLA-B*57:30', 'HLA-B*57:31', 'HLA-B*57:32', 'HLA-B*58:01', 'HLA-B*58:02', 'HLA-B*58:04',
'HLA-B*58:05', 'HLA-B*58:06', 'HLA-B*58:07', 'HLA-B*58:08', 'HLA-B*58:09', 'HLA-B*58:11', 'HLA-B*58:12', 'HLA-B*58:13',
'HLA-B*58:14', 'HLA-B*58:15', 'HLA-B*58:16', 'HLA-B*58:18', 'HLA-B*58:19', 'HLA-B*58:20', 'HLA-B*58:21', 'HLA-B*58:22',
'HLA-B*58:23', 'HLA-B*58:24', 'HLA-B*58:25', 'HLA-B*58:26', 'HLA-B*58:27', 'HLA-B*58:28', 'HLA-B*58:29', 'HLA-B*58:30',
'HLA-B*59:01', 'HLA-B*59:02', 'HLA-B*59:03', 'HLA-B*59:04', 'HLA-B*59:05', 'HLA-B*67:01', 'HLA-B*67:02', 'HLA-B*73:01',
'HLA-B*73:02', 'HLA-B*78:01', 'HLA-B*78:02', 'HLA-B*78:03', 'HLA-B*78:04', 'HLA-B*78:05', 'HLA-B*78:06', 'HLA-B*78:07',
'HLA-B*81:01', 'HLA-B*81:02', 'HLA-B*81:03', 'HLA-B*81:05', 'HLA-B*82:01', 'HLA-B*82:02', 'HLA-B*82:03', 'HLA-B*83:01',
'HLA-C*01:02', 'HLA-C*01:03', 'HLA-C*01:04', 'HLA-C*01:05', 'HLA-C*01:06', 'HLA-C*01:07', 'HLA-C*01:08', 'HLA-C*01:09',
'HLA-C*01:10', 'HLA-C*01:11', 'HLA-C*01:12', 'HLA-C*01:13', 'HLA-C*01:14', 'HLA-C*01:15', 'HLA-C*01:16', 'HLA-C*01:17',
'HLA-C*01:18', 'HLA-C*01:19', 'HLA-C*01:20', 'HLA-C*01:21', 'HLA-C*01:22', 'HLA-C*01:23', 'HLA-C*01:24', 'HLA-C*01:25',
'HLA-C*01:26', 'HLA-C*01:27', 'HLA-C*01:28', 'HLA-C*01:29', 'HLA-C*01:30', 'HLA-C*01:31', 'HLA-C*01:32', 'HLA-C*01:33',
'HLA-C*01:34', 'HLA-C*01:35', 'HLA-C*01:36', 'HLA-C*01:38', 'HLA-C*01:39', 'HLA-C*01:40', 'HLA-C*02:02', 'HLA-C*02:03',
'HLA-C*02:04', 'HLA-C*02:05', 'HLA-C*02:06', 'HLA-C*02:07', 'HLA-C*02:08', 'HLA-C*02:09', 'HLA-C*02:10', 'HLA-C*02:11',
'HLA-C*02:12', 'HLA-C*02:13', 'HLA-C*02:14', 'HLA-C*02:15', 'HLA-C*02:16', 'HLA-C*02:17', 'HLA-C*02:18', 'HLA-C*02:19',
'HLA-C*02:20', 'HLA-C*02:21', 'HLA-C*02:22', 'HLA-C*02:23', 'HLA-C*02:24', 'HLA-C*02:26', 'HLA-C*02:27', 'HLA-C*02:28',
'HLA-C*02:29', 'HLA-C*02:30', 'HLA-C*02:31', 'HLA-C*02:32', 'HLA-C*02:33', 'HLA-C*02:34', 'HLA-C*02:35', 'HLA-C*02:36',
'HLA-C*02:37', 'HLA-C*02:39', 'HLA-C*02:40', 'HLA-C*03:01', 'HLA-C*03:02', 'HLA-C*03:03', 'HLA-C*03:04', 'HLA-C*03:05',
'HLA-C*03:06', 'HLA-C*03:07', 'HLA-C*03:08', 'HLA-C*03:09', 'HLA-C*03:10', 'HLA-C*03:11', 'HLA-C*03:12', 'HLA-C*03:13',
'HLA-C*03:14', 'HLA-C*03:15', 'HLA-C*03:16', 'HLA-C*03:17', 'HLA-C*03:18', 'HLA-C*03:19', 'HLA-C*03:21', 'HLA-C*03:23',
'HLA-C*03:24', 'HLA-C*03:25', 'HLA-C*03:26', 'HLA-C*03:27', 'HLA-C*03:28', 'HLA-C*03:29', 'HLA-C*03:30', 'HLA-C*03:31',
'HLA-C*03:32', 'HLA-C*03:33', 'HLA-C*03:34', 'HLA-C*03:35', 'HLA-C*03:36', 'HLA-C*03:37', 'HLA-C*03:38', 'HLA-C*03:39',
'HLA-C*03:40', 'HLA-C*03:41', 'HLA-C*03:42', 'HLA-C*03:43', 'HLA-C*03:44', 'HLA-C*03:45', 'HLA-C*03:46', 'HLA-C*03:47',
'HLA-C*03:48', 'HLA-C*03:49', 'HLA-C*03:50', 'HLA-C*03:51', 'HLA-C*03:52', 'HLA-C*03:53', 'HLA-C*03:54', 'HLA-C*03:55',
'HLA-C*03:56', 'HLA-C*03:57', 'HLA-C*03:58', 'HLA-C*03:59', 'HLA-C*03:60', 'HLA-C*03:61', 'HLA-C*03:62', 'HLA-C*03:63',
'HLA-C*03:64', 'HLA-C*03:65', 'HLA-C*03:66', 'HLA-C*03:67', 'HLA-C*03:68', 'HLA-C*03:69', 'HLA-C*03:70', 'HLA-C*03:71',
'HLA-C*03:72', 'HLA-C*03:73', 'HLA-C*03:74', 'HLA-C*03:75', 'HLA-C*03:76', 'HLA-C*03:77', 'HLA-C*03:78', 'HLA-C*03:79',
'HLA-C*03:80', 'HLA-C*03:81', 'HLA-C*03:82', 'HLA-C*03:83', 'HLA-C*03:84', 'HLA-C*03:85', 'HLA-C*03:86', 'HLA-C*03:87',
'HLA-C*03:88', 'HLA-C*03:89', 'HLA-C*03:90', 'HLA-C*03:91', 'HLA-C*03:92', 'HLA-C*03:93', 'HLA-C*03:94', 'HLA-C*04:01',
'HLA-C*04:03', 'HLA-C*04:04', 'HLA-C*04:05', 'HLA-C*04:06', 'HLA-C*04:07', 'HLA-C*04:08', 'HLA-C*04:10', 'HLA-C*04:11',
'HLA-C*04:12', 'HLA-C*04:13', 'HLA-C*04:14', 'HLA-C*04:15', 'HLA-C*04:16', 'HLA-C*04:17', 'HLA-C*04:18', 'HLA-C*04:19',
'HLA-C*04:20', 'HLA-C*04:23', 'HLA-C*04:24', 'HLA-C*04:25', 'HLA-C*04:26', 'HLA-C*04:27', 'HLA-C*04:28', 'HLA-C*04:29',
'HLA-C*04:30', 'HLA-C*04:31', 'HLA-C*04:32', 'HLA-C*04:33', 'HLA-C*04:34', 'HLA-C*04:35', 'HLA-C*04:36', 'HLA-C*04:37',
'HLA-C*04:38', 'HLA-C*04:39', 'HLA-C*04:40', 'HLA-C*04:41', 'HLA-C*04:42', 'HLA-C*04:43', 'HLA-C*04:44', 'HLA-C*04:45',
'HLA-C*04:46', 'HLA-C*04:47', 'HLA-C*04:48', 'HLA-C*04:49', 'HLA-C*04:50', 'HLA-C*04:51', 'HLA-C*04:52', 'HLA-C*04:53',
'HLA-C*04:54', 'HLA-C*04:55', 'HLA-C*04:56', 'HLA-C*04:57', 'HLA-C*04:58', 'HLA-C*04:60', 'HLA-C*04:61', 'HLA-C*04:62',
'HLA-C*04:63', 'HLA-C*04:64', 'HLA-C*04:65', 'HLA-C*04:66', 'HLA-C*04:67', 'HLA-C*04:68', 'HLA-C*04:69', 'HLA-C*04:70',
'HLA-C*05:01', 'HLA-C*05:03', 'HLA-C*05:04', 'HLA-C*05:05', 'HLA-C*05:06', 'HLA-C*05:08', 'HLA-C*05:09', 'HLA-C*05:10',
'HLA-C*05:11', 'HLA-C*05:12', 'HLA-C*05:13', 'HLA-C*05:14', 'HLA-C*05:15', 'HLA-C*05:16', 'HLA-C*05:17', 'HLA-C*05:18',
'HLA-C*05:19', 'HLA-C*05:20', 'HLA-C*05:21', 'HLA-C*05:22', 'HLA-C*05:23', 'HLA-C*05:24', 'HLA-C*05:25', 'HLA-C*05:26',
'HLA-C*05:27', 'HLA-C*05:28', 'HLA-C*05:29', 'HLA-C*05:30', 'HLA-C*05:31', 'HLA-C*05:32', 'HLA-C*05:33', 'HLA-C*05:34',
'HLA-C*05:35', 'HLA-C*05:36', 'HLA-C*05:37', 'HLA-C*05:38', 'HLA-C*05:39', 'HLA-C*05:40', 'HLA-C*05:41', 'HLA-C*05:42',
'HLA-C*05:43', 'HLA-C*05:44', 'HLA-C*05:45', 'HLA-C*06:02', 'HLA-C*06:03', 'HLA-C*06:04', 'HLA-C*06:05', 'HLA-C*06:06',
'HLA-C*06:07', 'HLA-C*06:08', 'HLA-C*06:09', 'HLA-C*06:10', 'HLA-C*06:11', 'HLA-C*06:12', 'HLA-C*06:13', 'HLA-C*06:14',
'HLA-C*06:15', 'HLA-C*06:17', 'HLA-C*06:18', 'HLA-C*06:19', 'HLA-C*06:20', 'HLA-C*06:21', 'HLA-C*06:22', 'HLA-C*06:23',
'HLA-C*06:24', 'HLA-C*06:25', 'HLA-C*06:26', 'HLA-C*06:27', 'HLA-C*06:28', 'HLA-C*06:29', 'HLA-C*06:30', 'HLA-C*06:31',
'HLA-C*06:32', 'HLA-C*06:33', 'HLA-C*06:34', 'HLA-C*06:35', 'HLA-C*06:36', 'HLA-C*06:37', 'HLA-C*06:38', 'HLA-C*06:39',
'HLA-C*06:40', 'HLA-C*06:41', 'HLA-C*06:42', 'HLA-C*06:43', 'HLA-C*06:44', 'HLA-C*06:45', 'HLA-C*07:01', 'HLA-C*07:02',
'HLA-C*07:03', 'HLA-C*07:04', 'HLA-C*07:05', 'HLA-C*07:06', 'HLA-C*07:07', 'HLA-C*07:08', 'HLA-C*07:09', 'HLA-C*07:10',
'HLA-C*07:11', 'HLA-C*07:12', 'HLA-C*07:13', 'HLA-C*07:14', 'HLA-C*07:15', 'HLA-C*07:16', 'HLA-C*07:17', 'HLA-C*07:18',
'HLA-C*07:19', 'HLA-C*07:20', 'HLA-C*07:21', 'HLA-C*07:22', 'HLA-C*07:23', 'HLA-C*07:24', 'HLA-C*07:25', 'HLA-C*07:26',
'HLA-C*07:27', 'HLA-C*07:28', 'HLA-C*07:29', 'HLA-C*07:30', 'HLA-C*07:31', 'HLA-C*07:35', 'HLA-C*07:36', 'HLA-C*07:37',
'HLA-C*07:38', 'HLA-C*07:39', 'HLA-C*07:40', 'HLA-C*07:41', 'HLA-C*07:42', 'HLA-C*07:43', 'HLA-C*07:44', 'HLA-C*07:45',
'HLA-C*07:46', 'HLA-C*07:47', 'HLA-C*07:48', 'HLA-C*07:49', 'HLA-C*07:50', 'HLA-C*07:51', 'HLA-C*07:52', 'HLA-C*07:53',
'HLA-C*07:54', 'HLA-C*07:56', 'HLA-C*07:57', 'HLA-C*07:58', 'HLA-C*07:59', 'HLA-C*07:60', 'HLA-C*07:62', 'HLA-C*07:63',
'HLA-C*07:64', 'HLA-C*07:65', 'HLA-C*07:66', 'HLA-C*07:67', 'HLA-C*07:68', 'HLA-C*07:69', 'HLA-C*07:70', 'HLA-C*07:71',
'HLA-C*07:72', 'HLA-C*07:73', 'HLA-C*07:74', 'HLA-C*07:75', 'HLA-C*07:76', 'HLA-C*07:77', 'HLA-C*07:78', 'HLA-C*07:79',
'HLA-C*07:80', 'HLA-C*07:81', 'HLA-C*07:82', 'HLA-C*07:83', 'HLA-C*07:84', 'HLA-C*07:85', 'HLA-C*07:86', 'HLA-C*07:87',
'HLA-C*07:88', 'HLA-C*07:89', 'HLA-C*07:90', 'HLA-C*07:91', 'HLA-C*07:92', 'HLA-C*07:93', 'HLA-C*07:94', 'HLA-C*07:95',
'HLA-C*07:96', 'HLA-C*07:97', 'HLA-C*07:99', 'HLA-C*07:100', 'HLA-C*07:101', 'HLA-C*07:102', 'HLA-C*07:103', 'HLA-C*07:105',
'HLA-C*07:106', 'HLA-C*07:107', 'HLA-C*07:108', 'HLA-C*07:109', 'HLA-C*07:110', 'HLA-C*07:111', 'HLA-C*07:112',
'HLA-C*07:113', 'HLA-C*07:114', 'HLA-C*07:115', 'HLA-C*07:116', 'HLA-C*07:117', 'HLA-C*07:118', 'HLA-C*07:119',
'HLA-C*07:120', 'HLA-C*07:122', 'HLA-C*07:123', 'HLA-C*07:124', 'HLA-C*07:125', 'HLA-C*07:126', 'HLA-C*07:127',
'HLA-C*07:128', 'HLA-C*07:129', 'HLA-C*07:130', 'HLA-C*07:131', 'HLA-C*07:132', 'HLA-C*07:133', 'HLA-C*07:134',
'HLA-C*07:135', 'HLA-C*07:136', 'HLA-C*07:137', 'HLA-C*07:138', 'HLA-C*07:139', 'HLA-C*07:140', 'HLA-C*07:141',
'HLA-C*07:142', 'HLA-C*07:143', 'HLA-C*07:144', 'HLA-C*07:145', 'HLA-C*07:146', 'HLA-C*07:147', 'HLA-C*07:148',
'HLA-C*07:149', 'HLA-C*08:01', 'HLA-C*08:02', 'HLA-C*08:03', 'HLA-C*08:04', 'HLA-C*08:05', 'HLA-C*08:06', 'HLA-C*08:07',
'HLA-C*08:08', 'HLA-C*08:09', 'HLA-C*08:10', 'HLA-C*08:11', 'HLA-C*08:12', 'HLA-C*08:13', 'HLA-C*08:14', 'HLA-C*08:15',
'HLA-C*08:16', 'HLA-C*08:17', 'HLA-C*08:18', 'HLA-C*08:19', 'HLA-C*08:20', 'HLA-C*08:21', 'HLA-C*08:22', 'HLA-C*08:23',
'HLA-C*08:24', 'HLA-C*08:25', 'HLA-C*08:27', 'HLA-C*08:28', 'HLA-C*08:29', 'HLA-C*08:30', 'HLA-C*08:31', 'HLA-C*08:32',
'HLA-C*08:33', 'HLA-C*08:34', 'HLA-C*08:35', 'HLA-C*12:02', 'HLA-C*12:03', 'HLA-C*12:04', 'HLA-C*12:05', 'HLA-C*12:06',
'HLA-C*12:07', 'HLA-C*12:08', 'HLA-C*12:09', 'HLA-C*12:10', 'HLA-C*12:11', 'HLA-C*12:12', 'HLA-C*12:13', 'HLA-C*12:14',
'HLA-C*12:15', 'HLA-C*12:16', 'HLA-C*12:17', 'HLA-C*12:18', 'HLA-C*12:19', 'HLA-C*12:20', 'HLA-C*12:21', 'HLA-C*12:22',
'HLA-C*12:23', 'HLA-C*12:24', 'HLA-C*12:25', 'HLA-C*12:26', 'HLA-C*12:27', 'HLA-C*12:28', 'HLA-C*12:29', 'HLA-C*12:30',
'HLA-C*12:31', 'HLA-C*12:32', 'HLA-C*12:33', 'HLA-C*12:34', 'HLA-C*12:35', 'HLA-C*12:36', 'HLA-C*12:37', 'HLA-C*12:38',
'HLA-C*12:40', 'HLA-C*12:41', 'HLA-C*12:43', 'HLA-C*12:44', 'HLA-C*14:02', 'HLA-C*14:03', 'HLA-C*14:04', 'HLA-C*14:05',
'HLA-C*14:06', 'HLA-C*14:08', 'HLA-C*14:09', 'HLA-C*14:10', 'HLA-C*14:11', 'HLA-C*14:12', 'HLA-C*14:13', 'HLA-C*14:14',
'HLA-C*14:15', 'HLA-C*14:16', 'HLA-C*14:17', 'HLA-C*14:18', 'HLA-C*14:19', 'HLA-C*14:20', 'HLA-C*15:02', 'HLA-C*15:03',
'HLA-C*15:04', 'HLA-C*15:05', 'HLA-C*15:06', 'HLA-C*15:07', 'HLA-C*15:08', 'HLA-C*15:09', 'HLA-C*15:10', 'HLA-C*15:11',
'HLA-C*15:12', 'HLA-C*15:13', 'HLA-C*15:15', 'HLA-C*15:16', 'HLA-C*15:17', 'HLA-C*15:18', 'HLA-C*15:19', 'HLA-C*15:20',
'HLA-C*15:21', 'HLA-C*15:22', 'HLA-C*15:23', 'HLA-C*15:24', 'HLA-C*15:25', 'HLA-C*15:26', 'HLA-C*15:27', 'HLA-C*15:28',
'HLA-C*15:29', 'HLA-C*15:30', 'HLA-C*15:31', 'HLA-C*15:33', 'HLA-C*15:34', 'HLA-C*15:35', 'HLA-C*16:01', 'HLA-C*16:02',
'HLA-C*16:04', 'HLA-C*16:06', 'HLA-C*16:07', 'HLA-C*16:08', 'HLA-C*16:09', 'HLA-C*16:10', 'HLA-C*16:11', 'HLA-C*16:12',
'HLA-C*16:13', 'HLA-C*16:14', 'HLA-C*16:15', 'HLA-C*16:17', 'HLA-C*16:18', 'HLA-C*16:19', 'HLA-C*16:20', 'HLA-C*16:21',
'HLA-C*16:22', 'HLA-C*16:23', 'HLA-C*16:24', 'HLA-C*16:25', 'HLA-C*16:26', 'HLA-C*17:01', 'HLA-C*17:02', 'HLA-C*17:03',
'HLA-C*17:04', 'HLA-C*17:05', 'HLA-C*17:06', 'HLA-C*17:07', 'HLA-C*18:01', 'HLA-C*18:02', 'HLA-C*18:03', 'HLA-G*01:01',
'HLA-G*01:02', 'HLA-G*01:03', 'HLA-G*01:04', 'HLA-G*01:06', 'HLA-G*01:07', 'HLA-G*01:08', 'HLA-G*01:09', 'HLA-E*01:01'])
@property
def command(self):
return self.__command
@property
def name(self):
return self.__name
@property
def version(self):
return self.__version
@property
def supportedAlleles(self):
return self.__alleles
@property
def supportedLength(self):
return self.__length
def convert_alleles(self, alleles):
"""
Converts :class:`~epytope.Core.Allele.Allele` into the internal allele representation of the predictor
and returns a string representation
:param alleles: The :class:`~epytope.Core.Allele.Allele` for which the
internal predictor representation is needed
:type alleles: list(:class:`~epytope.Core.Allele.Allele`)
:return: Returns a string representation of the input :class:`~epytope.Core.Allele.Allele`
:rtype: list(str)
"""
return ["HLA-%s%s:%s" % (a.locus, a.supertype, a.subtype) for a in alleles]
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(dict)
with open(file, "r") as f:
f = csv.reader(f, delimiter='\t')
alleles = [x for x in next(f) if x.strip() != ""]
logging.warning(alleles)
ic_pos = 4
offset = 3
header = next(f)
logging.warning("\t".join(header))
if "Aff(nM)" in header:
ic_pos = 9
offset = 8
for row in f:
logging.warning("\t".join(row))
pep_seq = row[1]
for i, a in enumerate(alleles):
result[a][pep_seq] = float(row[ic_pos +i*offset])
return result
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`self.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: str
"""
# can not be determined netmhcpan does not support --version or similar
return None
def prepare_input(self, input, file):
"""
Prepares input for external tools and writes them to file in the specific format
NO return value!
:param: list(str) input: The :class:`~epytope.Core.Peptide.Peptide` sequences to write into file
:param File file: File-handler to input file for external tool
"""
file.write("\n".join(input))
class NetMHCII_2_2(AExternalEpitopePrediction):
"""
Implements a wrapper for NetMHCII
.. note::
Nielsen, M., & Lund, O. (2009). NN-align. An artificial neural network-based alignment algorithm for MHC class
II peptide binding prediction. BMC Bioinformatics, 10(1), 296.
Nielsen, M., Lundegaard, C., & Lund, O. (2007). Prediction of MHC class II binding affinity using SMM-align,
a novel stabilization matrix alignment method. BMC Bioinformatics, 8(1), 238.
"""
__supported_length = frozenset([15])
__name = "netmhcII"
__command = 'netMHCII {peptides} -a {alleles} {options} | grep -v "#" > {out}'
__alleles = frozenset(
['HLA-DRB1*01:01', 'HLA-DRB1*03:01', 'HLA-DRB1*04:01', 'HLA-DRB1*04:04', 'HLA-DRB1*04:05', 'HLA-DRB1*07:01', 'HLA-DRB1*08:02', 'HLA-DRB1*09:01',
'HLA-DRB1*11:01', 'HLA-DRB1*13:02', 'HLA-DRB1*15:01', 'HLA-DRB3*01:01', 'HLA-DRB4*01:01', 'HLA-DRB5*01:01',
'H2-IAb', 'H2-IAd'])
__version = "2.2"
@property
def version(self):
"""The version of the predictor"""
return self.__version
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
@property
def supportedAlleles(self):
"""A list of valid :class:`~epytope.Core.Allele.Allele` models"""
return self.__alleles
@property
def name(self):
"""The name of the predictor"""
return self.__name
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
else:
return "HLA-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
def convert_alleles(self, alleles):
"""
Converts :class:`~epytope.Core.Allele.Allele` into the internal :class:`~epytope.Core.Allele.Allele` representation
of the predictor and returns a string representation
:param alleles: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: Returns a string representation of the input :class:`~epytope.Core.Allele.Allele`
:rtype: list(str)
"""
return [self._represent(a) for a in alleles]
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
f = csv.reader(open(file, "r"), delimiter='\t')
for r in f:
if not r:
continue
row = r[0].split()
if not len(row):
continue
if "HLA-" not in row[0]:
continue
result[row[0]][row[2]] = float(row[4])
return result
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`self.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: str
"""
return None
def prepare_input(self, input, file):
"""
Prepares input for external tools
and writes them to _file in the specific format
No return value!
:param: list(str) input: The :class:`~epytope.Core.Peptide.Peptide` sequences to write into file
:param File file: File-handler to input file for external tool
"""
file.write("\n".join(">pepe_%i\n%s" % (i, p) for i, p in enumerate(input)))
class NetMHCIIpan_3_0(AExternalEpitopePrediction):
"""
Implements a wrapper for NetMHCIIpan.
.. note::
Andreatta, M., Karosiene, E., Rasmussen, M., Stryhn, A., Buus, S., & Nielsen, M. (2015).
Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding
core identification. Immunogenetics, 1-10.
"""
__supported_length = frozenset([9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20])
__name = "netmhcIIpan"
__command = "netMHCIIpan -f {peptides} -inptype 1 -a {alleles} {options} -xls -xlsfile {out}"
__alleles = frozenset(
['HLA-DRB1*01:01', 'HLA-DRB1*01:02', 'HLA-DRB1*01:03', 'HLA-DRB1*01:04', 'HLA-DRB1*01:05', 'HLA-DRB1*01:06',
'HLA-DRB1*01:07', 'HLA-DRB1*01:08', 'HLA-DRB1*01:09', 'HLA-DRB1*01:10', 'HLA-DRB1*01:11', 'HLA-DRB1*01:12',
'HLA-DRB1*01:13', 'HLA-DRB1*01:14', 'HLA-DRB1*01:15', 'HLA-DRB1*01:16', 'HLA-DRB1*01:17', 'HLA-DRB1*01:18',
'HLA-DRB1*01:19', 'HLA-DRB1*01:20', 'HLA-DRB1*01:21', 'HLA-DRB1*01:22', 'HLA-DRB1*01:23', 'HLA-DRB1*01:24',
'HLA-DRB1*01:25', 'HLA-DRB1*01:26', 'HLA-DRB1*01:27', 'HLA-DRB1*01:28', 'HLA-DRB1*01:29', 'HLA-DRB1*01:30',
'HLA-DRB1*01:31', 'HLA-DRB1*01:32', 'HLA-DRB1*03:01', 'HLA-DRB1*03:02', 'HLA-DRB1*03:03', 'HLA-DRB1*03:04',
'HLA-DRB1*03:05', 'HLA-DRB1*03:06', 'HLA-DRB1*03:07', 'HLA-DRB1*03:08', 'HLA-DRB1*03:10', 'HLA-DRB1*03:11',
'HLA-DRB1*03:13', 'HLA-DRB1*03:14', 'HLA-DRB1*03:15', 'HLA-DRB1*03:17', 'HLA-DRB1*03:18', 'HLA-DRB1*03:19',
'HLA-DRB1*03:20', 'HLA-DRB1*03:21', 'HLA-DRB1*03:22', 'HLA-DRB1*03:23', 'HLA-DRB1*03:24', 'HLA-DRB1*03:25',
'HLA-DRB1*03:26', 'HLA-DRB1*03:27', 'HLA-DRB1*03:28', 'HLA-DRB1*03:29', 'HLA-DRB1*03:30', 'HLA-DRB1*03:31',
'HLA-DRB1*03:32', 'HLA-DRB1*03:33', 'HLA-DRB1*03:34', 'HLA-DRB1*03:35', 'HLA-DRB1*03:36', 'HLA-DRB1*03:37',
'HLA-DRB1*03:38', 'HLA-DRB1*03:39', 'HLA-DRB1*03:40', 'HLA-DRB1*03:41', 'HLA-DRB1*03:42', 'HLA-DRB1*03:43',
'HLA-DRB1*03:44', 'HLA-DRB1*03:45', 'HLA-DRB1*03:46', 'HLA-DRB1*03:47', 'HLA-DRB1*03:48', 'HLA-DRB1*03:49',
'HLA-DRB1*03:50', 'HLA-DRB1*03:51', 'HLA-DRB1*03:52', 'HLA-DRB1*03:53', 'HLA-DRB1*03:54', 'HLA-DRB1*03:55',
'HLA-DRB1*04:01', 'HLA-DRB1*04:02', 'HLA-DRB1*04:03', 'HLA-DRB1*04:04', 'HLA-DRB1*04:05', 'HLA-DRB1*04:06',
'HLA-DRB1*04:07', 'HLA-DRB1*04:08', 'HLA-DRB1*04:09', 'HLA-DRB1*04:10', 'HLA-DRB1*04:11', 'HLA-DRB1*04:12',
'HLA-DRB1*04:13', 'HLA-DRB1*04:14', 'HLA-DRB1*04:15', 'HLA-DRB1*04:16', 'HLA-DRB1*04:17', 'HLA-DRB1*04:18',
'HLA-DRB1*04:19', 'HLA-DRB1*04:21', 'HLA-DRB1*04:22', 'HLA-DRB1*04:23', 'HLA-DRB1*04:24', 'HLA-DRB1*04:26',
'HLA-DRB1*04:27', 'HLA-DRB1*04:28', 'HLA-DRB1*04:29', 'HLA-DRB1*04:30', 'HLA-DRB1*04:31', 'HLA-DRB1*04:33',
'HLA-DRB1*04:34', 'HLA-DRB1*04:35', 'HLA-DRB1*04:36', 'HLA-DRB1*04:37', 'HLA-DRB1*04:38', 'HLA-DRB1*04:39',
'HLA-DRB1*04:40', 'HLA-DRB1*04:41', 'HLA-DRB1*04:42', 'HLA-DRB1*04:43', 'HLA-DRB1*04:44', 'HLA-DRB1*04:45',
'HLA-DRB1*04:46', 'HLA-DRB1*04:47', 'HLA-DRB1*04:48', 'HLA-DRB1*04:49', 'HLA-DRB1*04:50', 'HLA-DRB1*04:51',
'HLA-DRB1*04:52', 'HLA-DRB1*04:53', 'HLA-DRB1*04:54', 'HLA-DRB1*04:55', 'HLA-DRB1*04:56', 'HLA-DRB1*04:57',
'HLA-DRB1*04:58', 'HLA-DRB1*04:59', 'HLA-DRB1*04:60', 'HLA-DRB1*04:61', 'HLA-DRB1*04:62', 'HLA-DRB1*04:63',
'HLA-DRB1*04:64', 'HLA-DRB1*04:65', 'HLA-DRB1*04:66', 'HLA-DRB1*04:67', 'HLA-DRB1*04:68', 'HLA-DRB1*04:69',
'HLA-DRB1*04:70', 'HLA-DRB1*04:71', 'HLA-DRB1*04:72', 'HLA-DRB1*04:73', 'HLA-DRB1*04:74', 'HLA-DRB1*04:75',
'HLA-DRB1*04:76', 'HLA-DRB1*04:77', 'HLA-DRB1*04:78', 'HLA-DRB1*04:79', 'HLA-DRB1*04:80', 'HLA-DRB1*04:82',
'HLA-DRB1*04:83', 'HLA-DRB1*04:84', 'HLA-DRB1*04:85', 'HLA-DRB1*04:86', 'HLA-DRB1*04:87', 'HLA-DRB1*04:88',
'HLA-DRB1*04:89', 'HLA-DRB1*04:91', 'HLA-DRB1*07:01', 'HLA-DRB1*07:03', 'HLA-DRB1*07:04', 'HLA-DRB1*07:05',
'HLA-DRB1*07:06', 'HLA-DRB1*07:07', 'HLA-DRB1*07:08', 'HLA-DRB1*07:09', 'HLA-DRB1*07:11', 'HLA-DRB1*07:12',
'HLA-DRB1*07:13', 'HLA-DRB1*07:14', 'HLA-DRB1*07:15', 'HLA-DRB1*07:16', 'HLA-DRB1*07:17', 'HLA-DRB1*07:19',
'HLA-DRB1*08:01', 'HLA-DRB1*08:02', 'HLA-DRB1*08:03', 'HLA-DRB1*08:04', 'HLA-DRB1*08:05', 'HLA-DRB1*08:06',
'HLA-DRB1*08:07', 'HLA-DRB1*08:08', 'HLA-DRB1*08:09', 'HLA-DRB1*08:10', 'HLA-DRB1*08:11', 'HLA-DRB1*08:12',
'HLA-DRB1*08:13', 'HLA-DRB1*08:14', 'HLA-DRB1*08:15', 'HLA-DRB1*08:16', 'HLA-DRB1*08:18', 'HLA-DRB1*08:19',
'HLA-DRB1*08:20', 'HLA-DRB1*08:21', 'HLA-DRB1*08:22', 'HLA-DRB1*08:23', 'HLA-DRB1*08:24', 'HLA-DRB1*08:25',
'HLA-DRB1*08:26', 'HLA-DRB1*08:27', 'HLA-DRB1*08:28', 'HLA-DRB1*08:29', 'HLA-DRB1*08:30', 'HLA-DRB1*08:31',
'HLA-DRB1*08:32', 'HLA-DRB1*08:33', 'HLA-DRB1*08:34', 'HLA-DRB1*08:35', 'HLA-DRB1*08:36', 'HLA-DRB1*08:37',
'HLA-DRB1*08:38', 'HLA-DRB1*08:39', 'HLA-DRB1*08:40', 'HLA-DRB1*09:01', 'HLA-DRB1*09:02', 'HLA-DRB1*09:03',
'HLA-DRB1*09:04', 'HLA-DRB1*09:05', 'HLA-DRB1*09:06', 'HLA-DRB1*09:07', 'HLA-DRB1*09:08', 'HLA-DRB1*09:09',
'HLA-DRB1*10:01', 'HLA-DRB1*10:02', 'HLA-DRB1*10:03', 'HLA-DRB1*11:01', 'HLA-DRB1*11:02', 'HLA-DRB1*11:03',
'HLA-DRB1*11:04', 'HLA-DRB1*11:05', 'HLA-DRB1*11:06', 'HLA-DRB1*11:07', 'HLA-DRB1*11:08', 'HLA-DRB1*11:09',
'HLA-DRB1*11:10', 'HLA-DRB1*11:11', 'HLA-DRB1*11:12', 'HLA-DRB1*11:13', 'HLA-DRB1*11:14', 'HLA-DRB1*11:15',
'HLA-DRB1*11:16', 'HLA-DRB1*11:17', 'HLA-DRB1*11:18', 'HLA-DRB1*11:19', 'HLA-DRB1*11:20', 'HLA-DRB1*11:21',
'HLA-DRB1*11:24', 'HLA-DRB1*11:25', 'HLA-DRB1*11:27', 'HLA-DRB1*11:28', 'HLA-DRB1*11:29', 'HLA-DRB1*11:30',
'HLA-DRB1*11:31', 'HLA-DRB1*11:32', 'HLA-DRB1*11:33', 'HLA-DRB1*11:34', 'HLA-DRB1*11:35', 'HLA-DRB1*11:36',
'HLA-DRB1*11:37', 'HLA-DRB1*11:38', 'HLA-DRB1*11:39', 'HLA-DRB1*11:41', 'HLA-DRB1*11:42', 'HLA-DRB1*11:43',
'HLA-DRB1*11:44', 'HLA-DRB1*11:45', 'HLA-DRB1*11:46', 'HLA-DRB1*11:47', 'HLA-DRB1*11:48', 'HLA-DRB1*11:49',
'HLA-DRB1*11:50', 'HLA-DRB1*11:51', 'HLA-DRB1*11:52', 'HLA-DRB1*11:53', 'HLA-DRB1*11:54', 'HLA-DRB1*11:55',
'HLA-DRB1*11:56', 'HLA-DRB1*11:57', 'HLA-DRB1*11:58', 'HLA-DRB1*11:59', 'HLA-DRB1*11:60', 'HLA-DRB1*11:61',
'HLA-DRB1*11:62', 'HLA-DRB1*11:63', 'HLA-DRB1*11:64', 'HLA-DRB1*11:65', 'HLA-DRB1*11:66', 'HLA-DRB1*11:67',
'HLA-DRB1*11:68', 'HLA-DRB1*11:69', 'HLA-DRB1*11:70', 'HLA-DRB1*11:72', 'HLA-DRB1*11:73', 'HLA-DRB1*11:74',
'HLA-DRB1*11:75', 'HLA-DRB1*11:76', 'HLA-DRB1*11:77', 'HLA-DRB1*11:78', 'HLA-DRB1*11:79', 'HLA-DRB1*11:80',
'HLA-DRB1*11:81', 'HLA-DRB1*11:82', 'HLA-DRB1*11:83', 'HLA-DRB1*11:84', 'HLA-DRB1*11:85', 'HLA-DRB1*11:86',
'HLA-DRB1*11:87', 'HLA-DRB1*11:88', 'HLA-DRB1*11:89', 'HLA-DRB1*11:90', 'HLA-DRB1*11:91', 'HLA-DRB1*11:92',
'HLA-DRB1*11:93', 'HLA-DRB1*11:94', 'HLA-DRB1*11:95', 'HLA-DRB1*11:96', 'HLA-DRB1*12:01', 'HLA-DRB1*12:02',
'HLA-DRB1*12:03', 'HLA-DRB1*12:04', 'HLA-DRB1*12:05', 'HLA-DRB1*12:06', 'HLA-DRB1*12:07', 'HLA-DRB1*12:08',
'HLA-DRB1*12:09', 'HLA-DRB1*12:10', 'HLA-DRB1*12:11', 'HLA-DRB1*12:12', 'HLA-DRB1*12:13', 'HLA-DRB1*12:14',
'HLA-DRB1*12:15', 'HLA-DRB1*12:16', 'HLA-DRB1*12:17', 'HLA-DRB1*12:18', 'HLA-DRB1*12:19', 'HLA-DRB1*12:20',
'HLA-DRB1*12:21', 'HLA-DRB1*12:22', 'HLA-DRB1*12:23', 'HLA-DRB1*13:01', 'HLA-DRB1*13:02', 'HLA-DRB1*13:03',
'HLA-DRB1*13:04', 'HLA-DRB1*13:05', 'HLA-DRB1*13:06', 'HLA-DRB1*13:07', 'HLA-DRB1*13:08', 'HLA-DRB1*13:09',
'HLA-DRB1*13:10', 'HLA-DRB1*13:100', 'HLA-DRB1*13:101', 'HLA-DRB1*13:11', 'HLA-DRB1*13:12', 'HLA-DRB1*13:13',
'HLA-DRB1*13:14', 'HLA-DRB1*13:15', 'HLA-DRB1*13:16', 'HLA-DRB1*13:17', 'HLA-DRB1*13:18', 'HLA-DRB1*13:19',
'HLA-DRB1*13:20', 'HLA-DRB1*13:21', 'HLA-DRB1*13:22', 'HLA-DRB1*13:23', 'HLA-DRB1*13:24', 'HLA-DRB1*13:26',
'HLA-DRB1*13:27', 'HLA-DRB1*13:29', 'HLA-DRB1*13:30', 'HLA-DRB1*13:31', 'HLA-DRB1*13:32', 'HLA-DRB1*13:33',
'HLA-DRB1*13:34', 'HLA-DRB1*13:35', 'HLA-DRB1*13:36', 'HLA-DRB1*13:37', 'HLA-DRB1*13:38', 'HLA-DRB1*13:39',
'HLA-DRB1*13:41', 'HLA-DRB1*13:42', 'HLA-DRB1*13:43', 'HLA-DRB1*13:44', 'HLA-DRB1*13:46', 'HLA-DRB1*13:47',
'HLA-DRB1*13:48', 'HLA-DRB1*13:49', 'HLA-DRB1*13:50', 'HLA-DRB1*13:51', 'HLA-DRB1*13:52', 'HLA-DRB1*13:53',
'HLA-DRB1*13:54', 'HLA-DRB1*13:55', 'HLA-DRB1*13:56', 'HLA-DRB1*13:57', 'HLA-DRB1*13:58', 'HLA-DRB1*13:59',
'HLA-DRB1*13:60', 'HLA-DRB1*13:61', 'HLA-DRB1*13:62', 'HLA-DRB1*13:63', 'HLA-DRB1*13:64', 'HLA-DRB1*13:65',
'HLA-DRB1*13:66', 'HLA-DRB1*13:67', 'HLA-DRB1*13:68', 'HLA-DRB1*13:69', 'HLA-DRB1*13:70', 'HLA-DRB1*13:71',
'HLA-DRB1*13:72', 'HLA-DRB1*13:73', 'HLA-DRB1*13:74', 'HLA-DRB1*13:75', 'HLA-DRB1*13:76', 'HLA-DRB1*13:77',
'HLA-DRB1*13:78', 'HLA-DRB1*13:79', 'HLA-DRB1*13:80', 'HLA-DRB1*13:81', 'HLA-DRB1*13:82', 'HLA-DRB1*13:83',
'HLA-DRB1*13:84', 'HLA-DRB1*13:85', 'HLA-DRB1*13:86', 'HLA-DRB1*13:87', 'HLA-DRB1*13:88', 'HLA-DRB1*13:89',
'HLA-DRB1*13:90', 'HLA-DRB1*13:91', 'HLA-DRB1*13:92', 'HLA-DRB1*13:93', 'HLA-DRB1*13:94', 'HLA-DRB1*13:95',
'HLA-DRB1*13:96', 'HLA-DRB1*13:97', 'HLA-DRB1*13:98', 'HLA-DRB1*13:99', 'HLA-DRB1*14:01', 'HLA-DRB1*14:02',
'HLA-DRB1*14:03', 'HLA-DRB1*14:04', 'HLA-DRB1*14:05', 'HLA-DRB1*14:06', 'HLA-DRB1*14:07', 'HLA-DRB1*14:08',
'HLA-DRB1*14:09', 'HLA-DRB1*14:10', 'HLA-DRB1*14:11', 'HLA-DRB1*14:12', 'HLA-DRB1*14:13', 'HLA-DRB1*14:14',
'HLA-DRB1*14:15', 'HLA-DRB1*14:16', 'HLA-DRB1*14:17', 'HLA-DRB1*14:18', 'HLA-DRB1*14:19', 'HLA-DRB1*14:20',
'HLA-DRB1*14:21', 'HLA-DRB1*14:22', 'HLA-DRB1*14:23', 'HLA-DRB1*14:24', 'HLA-DRB1*14:25', 'HLA-DRB1*14:26',
'HLA-DRB1*14:27', 'HLA-DRB1*14:28', 'HLA-DRB1*14:29', 'HLA-DRB1*14:30', 'HLA-DRB1*14:31', 'HLA-DRB1*14:32',
'HLA-DRB1*14:33', 'HLA-DRB1*14:34', 'HLA-DRB1*14:35', 'HLA-DRB1*14:36', 'HLA-DRB1*14:37', 'HLA-DRB1*14:38',
'HLA-DRB1*14:39', 'HLA-DRB1*14:40', 'HLA-DRB1*14:41', 'HLA-DRB1*14:42', 'HLA-DRB1*14:43', 'HLA-DRB1*14:44',
'HLA-DRB1*14:45', 'HLA-DRB1*14:46', 'HLA-DRB1*14:47', 'HLA-DRB1*14:48', 'HLA-DRB1*14:49', 'HLA-DRB1*14:50',
'HLA-DRB1*14:51', 'HLA-DRB1*14:52', 'HLA-DRB1*14:53', 'HLA-DRB1*14:54', 'HLA-DRB1*14:55', 'HLA-DRB1*14:56',
'HLA-DRB1*14:57', 'HLA-DRB1*14:58', 'HLA-DRB1*14:59', 'HLA-DRB1*14:60', 'HLA-DRB1*14:61', 'HLA-DRB1*14:62',
'HLA-DRB1*14:63', 'HLA-DRB1*14:64', 'HLA-DRB1*14:65', 'HLA-DRB1*14:67', 'HLA-DRB1*14:68', 'HLA-DRB1*14:69',
'HLA-DRB1*14:70', 'HLA-DRB1*14:71', 'HLA-DRB1*14:72', 'HLA-DRB1*14:73', 'HLA-DRB1*14:74', 'HLA-DRB1*14:75',
'HLA-DRB1*14:76', 'HLA-DRB1*14:77', 'HLA-DRB1*14:78', 'HLA-DRB1*14:79', 'HLA-DRB1*14:80', 'HLA-DRB1*14:81',
'HLA-DRB1*14:82', 'HLA-DRB1*14:83', 'HLA-DRB1*14:84', 'HLA-DRB1*14:85', 'HLA-DRB1*14:86', 'HLA-DRB1*14:87',
'HLA-DRB1*14:88', 'HLA-DRB1*14:89', 'HLA-DRB1*14:90', 'HLA-DRB1*14:91', 'HLA-DRB1*14:93', 'HLA-DRB1*14:94',
'HLA-DRB1*14:95', 'HLA-DRB1*14:96', 'HLA-DRB1*14:97', 'HLA-DRB1*14:98', 'HLA-DRB1*14:99', 'HLA-DRB1*15:01',
'HLA-DRB1*15:02', 'HLA-DRB1*15:03', 'HLA-DRB1*15:04', 'HLA-DRB1*15:05', 'HLA-DRB1*15:06', 'HLA-DRB1*15:07',
'HLA-DRB1*15:08', 'HLA-DRB1*15:09', 'HLA-DRB1*15:10', 'HLA-DRB1*15:11', 'HLA-DRB1*15:12', 'HLA-DRB1*15:13',
'HLA-DRB1*15:14', 'HLA-DRB1*15:15', 'HLA-DRB1*15:16', 'HLA-DRB1*15:18', 'HLA-DRB1*15:19', 'HLA-DRB1*15:20',
'HLA-DRB1*15:21', 'HLA-DRB1*15:22', 'HLA-DRB1*15:23', 'HLA-DRB1*15:24', 'HLA-DRB1*15:25', 'HLA-DRB1*15:26',
'HLA-DRB1*15:27', 'HLA-DRB1*15:28', 'HLA-DRB1*15:29', 'HLA-DRB1*15:30', 'HLA-DRB1*15:31', 'HLA-DRB1*15:32',
'HLA-DRB1*15:33', 'HLA-DRB1*15:34', 'HLA-DRB1*15:35', 'HLA-DRB1*15:36', 'HLA-DRB1*15:37', 'HLA-DRB1*15:38',
'HLA-DRB1*15:39', 'HLA-DRB1*15:40', 'HLA-DRB1*15:41', 'HLA-DRB1*15:42', 'HLA-DRB1*15:43', 'HLA-DRB1*15:44',
'HLA-DRB1*15:45', 'HLA-DRB1*15:46', 'HLA-DRB1*15:47', 'HLA-DRB1*15:48', 'HLA-DRB1*15:49', 'HLA-DRB1*16:01',
'HLA-DRB1*16:02', 'HLA-DRB1*16:03', 'HLA-DRB1*16:04', 'HLA-DRB1*16:05', 'HLA-DRB1*16:07', 'HLA-DRB1*16:08',
'HLA-DRB1*16:09', 'HLA-DRB1*16:10', 'HLA-DRB1*16:11', 'HLA-DRB1*16:12', 'HLA-DRB1*16:14', 'HLA-DRB1*16:15',
'HLA-DRB1*16:16', 'HLA-DRB3*01:01', 'HLA-DRB3*01:04', 'HLA-DRB3*01:05', 'HLA-DRB3*01:08', 'HLA-DRB3*01:09',
'HLA-DRB3*01:11', 'HLA-DRB3*01:12', 'HLA-DRB3*01:13', 'HLA-DRB3*01:14', 'HLA-DRB3*02:01', 'HLA-DRB3*02:02',
'HLA-DRB3*02:04', 'HLA-DRB3*02:05', 'HLA-DRB3*02:09', 'HLA-DRB3*02:10', 'HLA-DRB3*02:11', 'HLA-DRB3*02:12',
'HLA-DRB3*02:13', 'HLA-DRB3*02:14', 'HLA-DRB3*02:15', 'HLA-DRB3*02:16', 'HLA-DRB3*02:17', 'HLA-DRB3*02:18',
'HLA-DRB3*02:19', 'HLA-DRB3*02:20', 'HLA-DRB3*02:21', 'HLA-DRB3*02:22', 'HLA-DRB3*02:23', 'HLA-DRB3*02:24',
'HLA-DRB3*02:25', 'HLA-DRB3*03:01', 'HLA-DRB3*03:03', 'HLA-DRB4*01:01', 'HLA-DRB4*01:03', 'HLA-DRB4*01:04',
'HLA-DRB4*01:06', 'HLA-DRB4*01:07', 'HLA-DRB4*01:08', 'HLA-DRB5*01:01', 'HLA-DRB5*01:02', 'HLA-DRB5*01:03',
'HLA-DRB5*01:04', 'HLA-DRB5*01:05', 'HLA-DRB5*01:06', 'HLA-DRB5*01:08N', 'HLA-DRB5*01:11', 'HLA-DRB5*01:12',
'HLA-DRB5*01:13', 'HLA-DRB5*01:14', 'HLA-DRB5*02:02', 'HLA-DRB5*02:03', 'HLA-DRB5*02:04', 'HLA-DRB5*02:05',
'HLA-DPA1*01:03-HLA-DPB1*01:01', 'HLA-DPA1*01:03-HLA-DPB1*02:01', 'HLA-DPA1*01:03-HLA-DPB1*02:02', 'HLA-DPA1*01:03-HLA-DPB1*03:01',
'HLA-DPA1*01:03-HLA-DPB1*04:01', 'HLA-DPA1*01:03-HLA-DPB1*04:02', 'HLA-DPA1*01:03-HLA-DPB1*05:01', 'HLA-DPA1*01:03-HLA-DPB1*06:01',
'HLA-DPA1*01:03-HLA-DPB1*08:01', 'HLA-DPA1*01:03-HLA-DPB1*09:01', 'HLA-DPA1*01:03-HLA-DPB1*10:001', 'HLA-DPA1*01:03-HLA-DPB1*10:01',
'HLA-DPA1*01:03-HLA-DPB1*10:101', 'HLA-DPA1*01:03-HLA-DPB1*10:201',
'HLA-DPA1*01:03-HLA-DPB1*10:301', 'HLA-DPA1*01:03-HLA-DPB1*10:401',
'HLA-DPA1*01:03-HLA-DPB1*10:501', 'HLA-DPA1*01:03-HLA-DPB1*10:601', 'HLA-DPA1*01:03-HLA-DPB1*10:701', 'HLA-DPA1*01:03-HLA-DPB1*10:801',
'HLA-DPA1*01:03-HLA-DPB1*10:901', 'HLA-DPA1*01:03-HLA-DPB1*11:001',
'HLA-DPA1*01:03-HLA-DPB1*11:01', 'HLA-DPA1*01:03-HLA-DPB1*11:101', 'HLA-DPA1*01:03-HLA-DPB1*11:201', 'HLA-DPA1*01:03-HLA-DPB1*11:301',
'HLA-DPA1*01:03-HLA-DPB1*11:401', 'HLA-DPA1*01:03-HLA-DPB1*11:501',
'HLA-DPA1*01:03-HLA-DPB1*11:601', 'HLA-DPA1*01:03-HLA-DPB1*11:701', 'HLA-DPA1*01:03-HLA-DPB1*11:801', 'HLA-DPA1*01:03-HLA-DPB1*11:901',
'HLA-DPA1*01:03-HLA-DPB1*12:101', 'HLA-DPA1*01:03-HLA-DPB1*12:201',
'HLA-DPA1*01:03-HLA-DPB1*12:301', 'HLA-DPA1*01:03-HLA-DPB1*12:401', 'HLA-DPA1*01:03-HLA-DPB1*12:501', 'HLA-DPA1*01:03-HLA-DPB1*12:601',
'HLA-DPA1*01:03-HLA-DPB1*12:701', 'HLA-DPA1*01:03-HLA-DPB1*12:801',
'HLA-DPA1*01:03-HLA-DPB1*12:901', 'HLA-DPA1*01:03-HLA-DPB1*13:001', 'HLA-DPA1*01:03-HLA-DPB1*13:01', 'HLA-DPA1*01:03-HLA-DPB1*13:101',
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'HLA-DPA1*01:03-HLA-DPB1*17:01', 'HLA-DPA1*01:03-HLA-DPB1*18:01',
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'HLA-DPA1*01:03-HLA-DPB1*23:01', 'HLA-DPA1*01:03-HLA-DPB1*24:01',
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'HLA-DPA1*01:03-HLA-DPB1*29:01', 'HLA-DPA1*01:03-HLA-DPB1*30:01',
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'HLA-DPA1*01:03-HLA-DPB1*35:01', 'HLA-DPA1*01:03-HLA-DPB1*36:01',
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'HLA-DPA1*01:03-HLA-DPB1*41:01', 'HLA-DPA1*01:03-HLA-DPB1*44:01',
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'HLA-DPA1*01:03-HLA-DPB1*49:01', 'HLA-DPA1*01:03-HLA-DPB1*50:01',
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'HLA-DPA1*01:03-HLA-DPB1*55:01', 'HLA-DPA1*01:03-HLA-DPB1*56:01',
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'HLA-DPA1*01:03-HLA-DPB1*63:01', 'HLA-DPA1*01:03-HLA-DPB1*65:01',
'HLA-DPA1*01:03-HLA-DPB1*66:01', 'HLA-DPA1*01:03-HLA-DPB1*67:01', 'HLA-DPA1*01:03-HLA-DPB1*68:01', 'HLA-DPA1*01:03-HLA-DPB1*69:01',
'HLA-DPA1*01:03-HLA-DPB1*70:01', 'HLA-DPA1*01:03-HLA-DPB1*71:01',
'HLA-DPA1*01:03-HLA-DPB1*72:01', 'HLA-DPA1*01:03-HLA-DPB1*73:01', 'HLA-DPA1*01:03-HLA-DPB1*74:01', 'HLA-DPA1*01:03-HLA-DPB1*75:01',
'HLA-DPA1*01:03-HLA-DPB1*76:01', 'HLA-DPA1*01:03-HLA-DPB1*77:01',
'HLA-DPA1*01:03-HLA-DPB1*78:01', 'HLA-DPA1*01:03-HLA-DPB1*79:01', 'HLA-DPA1*01:03-HLA-DPB1*80:01', 'HLA-DPA1*01:03-HLA-DPB1*81:01',
'HLA-DPA1*01:03-HLA-DPB1*82:01', 'HLA-DPA1*01:03-HLA-DPB1*83:01',
'HLA-DPA1*01:03-HLA-DPB1*84:01', 'HLA-DPA1*01:03-HLA-DPB1*85:01', 'HLA-DPA1*01:03-HLA-DPB1*86:01', 'HLA-DPA1*01:03-HLA-DPB1*87:01',
'HLA-DPA1*01:03-HLA-DPB1*88:01', 'HLA-DPA1*01:03-HLA-DPB1*89:01',
'HLA-DPA1*01:03-HLA-DPB1*90:01', 'HLA-DPA1*01:03-HLA-DPB1*91:01', 'HLA-DPA1*01:03-HLA-DPB1*92:01', 'HLA-DPA1*01:03-HLA-DPB1*93:01',
'HLA-DPA1*01:03-HLA-DPB1*94:01', 'HLA-DPA1*01:03-HLA-DPB1*95:01',
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'HLA-DPA1*01:04-HLA-DPB1*01:01', 'HLA-DPA1*01:04-HLA-DPB1*02:01',
'HLA-DPA1*01:04-HLA-DPB1*02:02', 'HLA-DPA1*01:04-HLA-DPB1*03:01', 'HLA-DPA1*01:04-HLA-DPB1*04:01', 'HLA-DPA1*01:04-HLA-DPB1*04:02',
'HLA-DPA1*01:04-HLA-DPB1*05:01', 'HLA-DPA1*01:04-HLA-DPB1*06:01',
'HLA-DPA1*01:04-HLA-DPB1*08:01', 'HLA-DPA1*01:04-HLA-DPB1*09:01', 'HLA-DPA1*01:04-HLA-DPB1*10:001', 'HLA-DPA1*01:04-HLA-DPB1*10:01',
'HLA-DPA1*01:04-HLA-DPB1*10:101', 'HLA-DPA1*01:04-HLA-DPB1*10:201',
'HLA-DPA1*01:04-HLA-DPB1*10:301', 'HLA-DPA1*01:04-HLA-DPB1*10:401', 'HLA-DPA1*01:04-HLA-DPB1*10:501', 'HLA-DPA1*01:04-HLA-DPB1*10:601',
'HLA-DPA1*01:04-HLA-DPB1*10:701', 'HLA-DPA1*01:04-HLA-DPB1*10:801',
'HLA-DPA1*01:04-HLA-DPB1*10:901', 'HLA-DPA1*01:04-HLA-DPB1*11:001', 'HLA-DPA1*01:04-HLA-DPB1*11:01', 'HLA-DPA1*01:04-HLA-DPB1*11:101',
'HLA-DPA1*01:04-HLA-DPB1*11:201', 'HLA-DPA1*01:04-HLA-DPB1*11:301',
'HLA-DPA1*01:04-HLA-DPB1*11:401', 'HLA-DPA1*01:04-HLA-DPB1*11:501', 'HLA-DPA1*01:04-HLA-DPB1*11:601', 'HLA-DPA1*01:04-HLA-DPB1*11:701',
'HLA-DPA1*01:04-HLA-DPB1*11:801', 'HLA-DPA1*01:04-HLA-DPB1*11:901',
'HLA-DPA1*01:04-HLA-DPB1*12:101', 'HLA-DPA1*01:04-HLA-DPB1*12:201', 'HLA-DPA1*01:04-HLA-DPB1*12:301', 'HLA-DPA1*01:04-HLA-DPB1*12:401',
'HLA-DPA1*01:04-HLA-DPB1*12:501', 'HLA-DPA1*01:04-HLA-DPB1*12:601',
'HLA-DPA1*01:04-HLA-DPB1*12:701', 'HLA-DPA1*01:04-HLA-DPB1*12:801', 'HLA-DPA1*01:04-HLA-DPB1*12:901', 'HLA-DPA1*01:04-HLA-DPB1*13:001',
'HLA-DPA1*01:04-HLA-DPB1*13:01', 'HLA-DPA1*01:04-HLA-DPB1*13:101',
'HLA-DPA1*01:04-HLA-DPB1*13:201', 'HLA-DPA1*01:04-HLA-DPB1*13:301', 'HLA-DPA1*01:04-HLA-DPB1*13:401', 'HLA-DPA1*01:04-HLA-DPB1*14:01',
'HLA-DPA1*01:04-HLA-DPB1*15:01', 'HLA-DPA1*01:04-HLA-DPB1*16:01',
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'HLA-DPA1*01:04-HLA-DPB1*21:01', 'HLA-DPA1*01:04-HLA-DPB1*22:01',
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'HLA-DPA1*01:04-HLA-DPB1*27:01', 'HLA-DPA1*01:04-HLA-DPB1*28:01',
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'HLA-DPA1*01:04-HLA-DPB1*33:01', 'HLA-DPA1*01:04-HLA-DPB1*34:01',
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'HLA-DQA1*05:11-HLA-DQB1*03:19', 'HLA-DQA1*05:11-HLA-DQB1*03:20', 'HLA-DQA1*05:11-HLA-DQB1*03:21', 'HLA-DQA1*05:11-HLA-DQB1*03:22',
'HLA-DQA1*05:11-HLA-DQB1*03:23', 'HLA-DQA1*05:11-HLA-DQB1*03:24',
'HLA-DQA1*05:11-HLA-DQB1*03:25', 'HLA-DQA1*05:11-HLA-DQB1*03:26', 'HLA-DQA1*05:11-HLA-DQB1*03:27', 'HLA-DQA1*05:11-HLA-DQB1*03:28',
'HLA-DQA1*05:11-HLA-DQB1*03:29', 'HLA-DQA1*05:11-HLA-DQB1*03:30',
'HLA-DQA1*05:11-HLA-DQB1*03:31', 'HLA-DQA1*05:11-HLA-DQB1*03:32', 'HLA-DQA1*05:11-HLA-DQB1*03:33', 'HLA-DQA1*05:11-HLA-DQB1*03:34',
'HLA-DQA1*05:11-HLA-DQB1*03:35', 'HLA-DQA1*05:11-HLA-DQB1*03:36',
'HLA-DQA1*05:11-HLA-DQB1*03:37', 'HLA-DQA1*05:11-HLA-DQB1*03:38', 'HLA-DQA1*05:11-HLA-DQB1*04:01', 'HLA-DQA1*05:11-HLA-DQB1*04:02',
'HLA-DQA1*05:11-HLA-DQB1*04:03', 'HLA-DQA1*05:11-HLA-DQB1*04:04',
'HLA-DQA1*05:11-HLA-DQB1*04:05', 'HLA-DQA1*05:11-HLA-DQB1*04:06', 'HLA-DQA1*05:11-HLA-DQB1*04:07', 'HLA-DQA1*05:11-HLA-DQB1*04:08',
'HLA-DQA1*05:11-HLA-DQB1*05:01', 'HLA-DQA1*05:11-HLA-DQB1*05:02',
'HLA-DQA1*05:11-HLA-DQB1*05:03', 'HLA-DQA1*05:11-HLA-DQB1*05:05', 'HLA-DQA1*05:11-HLA-DQB1*05:06', 'HLA-DQA1*05:11-HLA-DQB1*05:07',
'HLA-DQA1*05:11-HLA-DQB1*05:08', 'HLA-DQA1*05:11-HLA-DQB1*05:09',
'HLA-DQA1*05:11-HLA-DQB1*05:10', 'HLA-DQA1*05:11-HLA-DQB1*05:11', 'HLA-DQA1*05:11-HLA-DQB1*05:12', 'HLA-DQA1*05:11-HLA-DQB1*05:13',
'HLA-DQA1*05:11-HLA-DQB1*05:14', 'HLA-DQA1*05:11-HLA-DQB1*06:01',
'HLA-DQA1*05:11-HLA-DQB1*06:02', 'HLA-DQA1*05:11-HLA-DQB1*06:03', 'HLA-DQA1*05:11-HLA-DQB1*06:04', 'HLA-DQA1*05:11-HLA-DQB1*06:07',
'HLA-DQA1*05:11-HLA-DQB1*06:08', 'HLA-DQA1*05:11-HLA-DQB1*06:09',
'HLA-DQA1*05:11-HLA-DQB1*06:10', 'HLA-DQA1*05:11-HLA-DQB1*06:11', 'HLA-DQA1*05:11-HLA-DQB1*06:12', 'HLA-DQA1*05:11-HLA-DQB1*06:14',
'HLA-DQA1*05:11-HLA-DQB1*06:15', 'HLA-DQA1*05:11-HLA-DQB1*06:16',
'HLA-DQA1*05:11-HLA-DQB1*06:17', 'HLA-DQA1*05:11-HLA-DQB1*06:18', 'HLA-DQA1*05:11-HLA-DQB1*06:19', 'HLA-DQA1*05:11-HLA-DQB1*06:21',
'HLA-DQA1*05:11-HLA-DQB1*06:22', 'HLA-DQA1*05:11-HLA-DQB1*06:23',
'HLA-DQA1*05:11-HLA-DQB1*06:24', 'HLA-DQA1*05:11-HLA-DQB1*06:25', 'HLA-DQA1*05:11-HLA-DQB1*06:27', 'HLA-DQA1*05:11-HLA-DQB1*06:28',
'HLA-DQA1*05:11-HLA-DQB1*06:29', 'HLA-DQA1*05:11-HLA-DQB1*06:30',
'HLA-DQA1*05:11-HLA-DQB1*06:31', 'HLA-DQA1*05:11-HLA-DQB1*06:32', 'HLA-DQA1*05:11-HLA-DQB1*06:33', 'HLA-DQA1*05:11-HLA-DQB1*06:34',
'HLA-DQA1*05:11-HLA-DQB1*06:35', 'HLA-DQA1*05:11-HLA-DQB1*06:36',
'HLA-DQA1*05:11-HLA-DQB1*06:37', 'HLA-DQA1*05:11-HLA-DQB1*06:38', 'HLA-DQA1*05:11-HLA-DQB1*06:39', 'HLA-DQA1*05:11-HLA-DQB1*06:40',
'HLA-DQA1*05:11-HLA-DQB1*06:41', 'HLA-DQA1*05:11-HLA-DQB1*06:42',
'HLA-DQA1*05:11-HLA-DQB1*06:43', 'HLA-DQA1*05:11-HLA-DQB1*06:44', 'HLA-DQA1*06:01-HLA-DQB1*02:01', 'HLA-DQA1*06:01-HLA-DQB1*02:02',
'HLA-DQA1*06:01-HLA-DQB1*02:03', 'HLA-DQA1*06:01-HLA-DQB1*02:04',
'HLA-DQA1*06:01-HLA-DQB1*02:05', 'HLA-DQA1*06:01-HLA-DQB1*02:06', 'HLA-DQA1*06:01-HLA-DQB1*03:01', 'HLA-DQA1*06:01-HLA-DQB1*03:02',
'HLA-DQA1*06:01-HLA-DQB1*03:03', 'HLA-DQA1*06:01-HLA-DQB1*03:04',
'HLA-DQA1*06:01-HLA-DQB1*03:05', 'HLA-DQA1*06:01-HLA-DQB1*03:06', 'HLA-DQA1*06:01-HLA-DQB1*03:07', 'HLA-DQA1*06:01-HLA-DQB1*03:08',
'HLA-DQA1*06:01-HLA-DQB1*03:09', 'HLA-DQA1*06:01-HLA-DQB1*03:10',
'HLA-DQA1*06:01-HLA-DQB1*03:11', 'HLA-DQA1*06:01-HLA-DQB1*03:12', 'HLA-DQA1*06:01-HLA-DQB1*03:13', 'HLA-DQA1*06:01-HLA-DQB1*03:14',
'HLA-DQA1*06:01-HLA-DQB1*03:15', 'HLA-DQA1*06:01-HLA-DQB1*03:16',
'HLA-DQA1*06:01-HLA-DQB1*03:17', 'HLA-DQA1*06:01-HLA-DQB1*03:18', 'HLA-DQA1*06:01-HLA-DQB1*03:19', 'HLA-DQA1*06:01-HLA-DQB1*03:20',
'HLA-DQA1*06:01-HLA-DQB1*03:21', 'HLA-DQA1*06:01-HLA-DQB1*03:22',
'HLA-DQA1*06:01-HLA-DQB1*03:23', 'HLA-DQA1*06:01-HLA-DQB1*03:24', 'HLA-DQA1*06:01-HLA-DQB1*03:25', 'HLA-DQA1*06:01-HLA-DQB1*03:26',
'HLA-DQA1*06:01-HLA-DQB1*03:27', 'HLA-DQA1*06:01-HLA-DQB1*03:28',
'HLA-DQA1*06:01-HLA-DQB1*03:29', 'HLA-DQA1*06:01-HLA-DQB1*03:30', 'HLA-DQA1*06:01-HLA-DQB1*03:31', 'HLA-DQA1*06:01-HLA-DQB1*03:32',
'HLA-DQA1*06:01-HLA-DQB1*03:33', 'HLA-DQA1*06:01-HLA-DQB1*03:34',
'HLA-DQA1*06:01-HLA-DQB1*03:35', 'HLA-DQA1*06:01-HLA-DQB1*03:36', 'HLA-DQA1*06:01-HLA-DQB1*03:37', 'HLA-DQA1*06:01-HLA-DQB1*03:38',
'HLA-DQA1*06:01-HLA-DQB1*04:01', 'HLA-DQA1*06:01-HLA-DQB1*04:02',
'HLA-DQA1*06:01-HLA-DQB1*04:03', 'HLA-DQA1*06:01-HLA-DQB1*04:04', 'HLA-DQA1*06:01-HLA-DQB1*04:05', 'HLA-DQA1*06:01-HLA-DQB1*04:06',
'HLA-DQA1*06:01-HLA-DQB1*04:07', 'HLA-DQA1*06:01-HLA-DQB1*04:08',
'HLA-DQA1*06:01-HLA-DQB1*05:01', 'HLA-DQA1*06:01-HLA-DQB1*05:02', 'HLA-DQA1*06:01-HLA-DQB1*05:03', 'HLA-DQA1*06:01-HLA-DQB1*05:05',
'HLA-DQA1*06:01-HLA-DQB1*05:06', 'HLA-DQA1*06:01-HLA-DQB1*05:07',
'HLA-DQA1*06:01-HLA-DQB1*05:08', 'HLA-DQA1*06:01-HLA-DQB1*05:09', 'HLA-DQA1*06:01-HLA-DQB1*05:10', 'HLA-DQA1*06:01-HLA-DQB1*05:11',
'HLA-DQA1*06:01-HLA-DQB1*05:12', 'HLA-DQA1*06:01-HLA-DQB1*05:13',
'HLA-DQA1*06:01-HLA-DQB1*05:14', 'HLA-DQA1*06:01-HLA-DQB1*06:01', 'HLA-DQA1*06:01-HLA-DQB1*06:02', 'HLA-DQA1*06:01-HLA-DQB1*06:03',
'HLA-DQA1*06:01-HLA-DQB1*06:04', 'HLA-DQA1*06:01-HLA-DQB1*06:07',
'HLA-DQA1*06:01-HLA-DQB1*06:08', 'HLA-DQA1*06:01-HLA-DQB1*06:09', 'HLA-DQA1*06:01-HLA-DQB1*06:10', 'HLA-DQA1*06:01-HLA-DQB1*06:11',
'HLA-DQA1*06:01-HLA-DQB1*06:12', 'HLA-DQA1*06:01-HLA-DQB1*06:14',
'HLA-DQA1*06:01-HLA-DQB1*06:15', 'HLA-DQA1*06:01-HLA-DQB1*06:16', 'HLA-DQA1*06:01-HLA-DQB1*06:17', 'HLA-DQA1*06:01-HLA-DQB1*06:18',
'HLA-DQA1*06:01-HLA-DQB1*06:19', 'HLA-DQA1*06:01-HLA-DQB1*06:21',
'HLA-DQA1*06:01-HLA-DQB1*06:22', 'HLA-DQA1*06:01-HLA-DQB1*06:23', 'HLA-DQA1*06:01-HLA-DQB1*06:24', 'HLA-DQA1*06:01-HLA-DQB1*06:25',
'HLA-DQA1*06:01-HLA-DQB1*06:27', 'HLA-DQA1*06:01-HLA-DQB1*06:28',
'HLA-DQA1*06:01-HLA-DQB1*06:29', 'HLA-DQA1*06:01-HLA-DQB1*06:30', 'HLA-DQA1*06:01-HLA-DQB1*06:31', 'HLA-DQA1*06:01-HLA-DQB1*06:32',
'HLA-DQA1*06:01-HLA-DQB1*06:33', 'HLA-DQA1*06:01-HLA-DQB1*06:34',
'HLA-DQA1*06:01-HLA-DQB1*06:35', 'HLA-DQA1*06:01-HLA-DQB1*06:36', 'HLA-DQA1*06:01-HLA-DQB1*06:37', 'HLA-DQA1*06:01-HLA-DQB1*06:38',
'HLA-DQA1*06:01-HLA-DQB1*06:39', 'HLA-DQA1*06:01-HLA-DQB1*06:40',
'HLA-DQA1*06:01-HLA-DQB1*06:41', 'HLA-DQA1*06:01-HLA-DQB1*06:42', 'HLA-DQA1*06:01-HLA-DQB1*06:43', 'HLA-DQA1*06:01-HLA-DQB1*06:44',
'HLA-DQA1*06:02-HLA-DQB1*02:01', 'HLA-DQA1*06:02-HLA-DQB1*02:02',
'HLA-DQA1*06:02-HLA-DQB1*02:03', 'HLA-DQA1*06:02-HLA-DQB1*02:04', 'HLA-DQA1*06:02-HLA-DQB1*02:05', 'HLA-DQA1*06:02-HLA-DQB1*02:06',
'HLA-DQA1*06:02-HLA-DQB1*03:01', 'HLA-DQA1*06:02-HLA-DQB1*03:02',
'HLA-DQA1*06:02-HLA-DQB1*03:03', 'HLA-DQA1*06:02-HLA-DQB1*03:04', 'HLA-DQA1*06:02-HLA-DQB1*03:05', 'HLA-DQA1*06:02-HLA-DQB1*03:06',
'HLA-DQA1*06:02-HLA-DQB1*03:07', 'HLA-DQA1*06:02-HLA-DQB1*03:08',
'HLA-DQA1*06:02-HLA-DQB1*03:09', 'HLA-DQA1*06:02-HLA-DQB1*03:10', 'HLA-DQA1*06:02-HLA-DQB1*03:11', 'HLA-DQA1*06:02-HLA-DQB1*03:12',
'HLA-DQA1*06:02-HLA-DQB1*03:13', 'HLA-DQA1*06:02-HLA-DQB1*03:14',
'HLA-DQA1*06:02-HLA-DQB1*03:15', 'HLA-DQA1*06:02-HLA-DQB1*03:16', 'HLA-DQA1*06:02-HLA-DQB1*03:17', 'HLA-DQA1*06:02-HLA-DQB1*03:18',
'HLA-DQA1*06:02-HLA-DQB1*03:19', 'HLA-DQA1*06:02-HLA-DQB1*03:20',
'HLA-DQA1*06:02-HLA-DQB1*03:21', 'HLA-DQA1*06:02-HLA-DQB1*03:22', 'HLA-DQA1*06:02-HLA-DQB1*03:23', 'HLA-DQA1*06:02-HLA-DQB1*03:24',
'HLA-DQA1*06:02-HLA-DQB1*03:25', 'HLA-DQA1*06:02-HLA-DQB1*03:26',
'HLA-DQA1*06:02-HLA-DQB1*03:27', 'HLA-DQA1*06:02-HLA-DQB1*03:28', 'HLA-DQA1*06:02-HLA-DQB1*03:29', 'HLA-DQA1*06:02-HLA-DQB1*03:30',
'HLA-DQA1*06:02-HLA-DQB1*03:31', 'HLA-DQA1*06:02-HLA-DQB1*03:32',
'HLA-DQA1*06:02-HLA-DQB1*03:33', 'HLA-DQA1*06:02-HLA-DQB1*03:34', 'HLA-DQA1*06:02-HLA-DQB1*03:35', 'HLA-DQA1*06:02-HLA-DQB1*03:36',
'HLA-DQA1*06:02-HLA-DQB1*03:37', 'HLA-DQA1*06:02-HLA-DQB1*03:38',
'HLA-DQA1*06:02-HLA-DQB1*04:01', 'HLA-DQA1*06:02-HLA-DQB1*04:02', 'HLA-DQA1*06:02-HLA-DQB1*04:03', 'HLA-DQA1*06:02-HLA-DQB1*04:04',
'HLA-DQA1*06:02-HLA-DQB1*04:05', 'HLA-DQA1*06:02-HLA-DQB1*04:06',
'HLA-DQA1*06:02-HLA-DQB1*04:07', 'HLA-DQA1*06:02-HLA-DQB1*04:08', 'HLA-DQA1*06:02-HLA-DQB1*05:01', 'HLA-DQA1*06:02-HLA-DQB1*05:02',
'HLA-DQA1*06:02-HLA-DQB1*05:03', 'HLA-DQA1*06:02-HLA-DQB1*05:05',
'HLA-DQA1*06:02-HLA-DQB1*05:06', 'HLA-DQA1*06:02-HLA-DQB1*05:07', 'HLA-DQA1*06:02-HLA-DQB1*05:08', 'HLA-DQA1*06:02-HLA-DQB1*05:09',
'HLA-DQA1*06:02-HLA-DQB1*05:10', 'HLA-DQA1*06:02-HLA-DQB1*05:11',
'HLA-DQA1*06:02-HLA-DQB1*05:12', 'HLA-DQA1*06:02-HLA-DQB1*05:13', 'HLA-DQA1*06:02-HLA-DQB1*05:14', 'HLA-DQA1*06:02-HLA-DQB1*06:01',
'HLA-DQA1*06:02-HLA-DQB1*06:02', 'HLA-DQA1*06:02-HLA-DQB1*06:03',
'HLA-DQA1*06:02-HLA-DQB1*06:04', 'HLA-DQA1*06:02-HLA-DQB1*06:07', 'HLA-DQA1*06:02-HLA-DQB1*06:08', 'HLA-DQA1*06:02-HLA-DQB1*06:09',
'HLA-DQA1*06:02-HLA-DQB1*06:10', 'HLA-DQA1*06:02-HLA-DQB1*06:11',
'HLA-DQA1*06:02-HLA-DQB1*06:12', 'HLA-DQA1*06:02-HLA-DQB1*06:14', 'HLA-DQA1*06:02-HLA-DQB1*06:15', 'HLA-DQA1*06:02-HLA-DQB1*06:16',
'HLA-DQA1*06:02-HLA-DQB1*06:17', 'HLA-DQA1*06:02-HLA-DQB1*06:18',
'HLA-DQA1*06:02-HLA-DQB1*06:19', 'HLA-DQA1*06:02-HLA-DQB1*06:21', 'HLA-DQA1*06:02-HLA-DQB1*06:22', 'HLA-DQA1*06:02-HLA-DQB1*06:23',
'HLA-DQA1*06:02-HLA-DQB1*06:24', 'HLA-DQA1*06:02-HLA-DQB1*06:25',
'HLA-DQA1*06:02-HLA-DQB1*06:27', 'HLA-DQA1*06:02-HLA-DQB1*06:28', 'HLA-DQA1*06:02-HLA-DQB1*06:29', 'HLA-DQA1*06:02-HLA-DQB1*06:30',
'HLA-DQA1*06:02-HLA-DQB1*06:31', 'HLA-DQA1*06:02-HLA-DQB1*06:32',
'HLA-DQA1*06:02-HLA-DQB1*06:33', 'HLA-DQA1*06:02-HLA-DQB1*06:34', 'HLA-DQA1*06:02-HLA-DQB1*06:35', 'HLA-DQA1*06:02-HLA-DQB1*06:36',
'HLA-DQA1*06:02-HLA-DQB1*06:37', 'HLA-DQA1*06:02-HLA-DQB1*06:38',
'HLA-DQA1*06:02-HLA-DQB1*06:39', 'HLA-DQA1*06:02-HLA-DQB1*06:40', 'HLA-DQA1*06:02-HLA-DQB1*06:41', 'HLA-DQA1*06:02-HLA-DQB1*06:42',
'HLA-DQA1*06:02-HLA-DQB1*06:43', 'HLA-DQA1*06:02-HLA-DQB1*06:44',
'H2-IAb', 'H2-IAd'])
__version = "3.0"
@property
def version(self):
"""The version of the predictor"""
return self.__version
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
@property
def supportedAlleles(self):
"""A list of valid :class:`~epytope.Core.Allele.Allele` models"""
return self.__alleles
@property
def name(self):
"""The name of the predictor"""
return self.__name
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
elif isinstance(allele, CombinedAllele):
return "HLA-%s%s%s-%s%s%s" % (allele.alpha_locus, allele.alpha_supertype, allele.alpha_subtype,
allele.beta_locus, allele.beta_supertype, allele.beta_subtype)
else:
return "%s_%s%s" % (allele.locus, allele.supertype, allele.subtype)
def convert_alleles(self, alleles):
"""
Converts :class:`~epytope.Core.Allele.Allele` into the internal :class:`~epytope.Core.Allele.Allele` representation
of the predictor and returns a string representation
:param alleles: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: Returns a string representation of the input :class:`~epytope.Core.Allele.Allele`
:rtype: list(str)
"""
return [self._represent(a) for a in alleles]
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
f = csv.reader(open(file, "r"), delimiter='\t')
alleles = [x.replace("*", "_").replace(":", "") for x in set([x for x in next(f) if x != ""])]
next(f)
ic_pos = 3
for row in f:
pep_seq = row[1]
for i, a in enumerate(alleles):
result[a][pep_seq] = float(row[ic_pos + i * 3])
return result
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`self.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: str
"""
return None
def prepare_input(self, input, file):
"""
Prepares input for external tools
and writes them to _file in the specific format
No return value!
:param: list(str) input: The :class:`~epytope.Core.Peptide.Peptide` sequences to write into file
:param File file: File-handler to input file for external tool
"""
file.write("\n".join(input))
class NetMHCIIpan_3_1(NetMHCIIpan_3_0):
"""
Implementation of NetMHCIIpan 3.1 adapter.
.. note::
Andreatta, M., Karosiene, E., Rasmussen, M., Stryhn, A., Buus, S., & Nielsen, M. (2015). Accurate pan-specific
prediction of peptide-MHC class II binding affinity with improved binding core identification.
Immunogenetics, 1-10.
"""
__supported_length = frozenset([9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20])
__name = "netmhcIIpan"
__command = "netMHCIIpan -f {peptides} -inptype 1 -a {alleles} {options} -xls -xlsfile {out}"
__alleles = frozenset(
['HLA-DRB1*01:01', 'HLA-DRB1*01:02', 'HLA-DRB1*01:03', 'HLA-DRB1*01:04', 'HLA-DRB1*01:05', 'HLA-DRB1*01:06',
'HLA-DRB1*01:07', 'HLA-DRB1*01:08', 'HLA-DRB1*01:09', 'HLA-DRB1*01:10', 'HLA-DRB1*01:11', 'HLA-DRB1*01:12',
'HLA-DRB1*01:13', 'HLA-DRB1*01:14', 'HLA-DRB1*01:15', 'HLA-DRB1*01:16', 'HLA-DRB1*01:17', 'HLA-DRB1*01:18',
'HLA-DRB1*01:19', 'HLA-DRB1*01:20', 'HLA-DRB1*01:21', 'HLA-DRB1*01:22', 'HLA-DRB1*01:23', 'HLA-DRB1*01:24',
'HLA-DRB1*01:25', 'HLA-DRB1*01:26', 'HLA-DRB1*01:27', 'HLA-DRB1*01:28', 'HLA-DRB1*01:29', 'HLA-DRB1*01:30',
'HLA-DRB1*01:31', 'HLA-DRB1*01:32', 'HLA-DRB1*03:01', 'HLA-DRB1*03:02', 'HLA-DRB1*03:03', 'HLA-DRB1*03:04',
'HLA-DRB1*03:05', 'HLA-DRB1*03:06', 'HLA-DRB1*03:07', 'HLA-DRB1*03:08', 'HLA-DRB1*03:10', 'HLA-DRB1*03:11',
'HLA-DRB1*03:13', 'HLA-DRB1*03:14', 'HLA-DRB1*03:15', 'HLA-DRB1*03:17', 'HLA-DRB1*03:18', 'HLA-DRB1*03:19',
'HLA-DRB1*03:20', 'HLA-DRB1*03:21', 'HLA-DRB1*03:22', 'HLA-DRB1*03:23', 'HLA-DRB1*03:24', 'HLA-DRB1*03:25',
'HLA-DRB1*03:26', 'HLA-DRB1*03:27', 'HLA-DRB1*03:28', 'HLA-DRB1*03:29', 'HLA-DRB1*03:30', 'HLA-DRB1*03:31',
'HLA-DRB1*03:32', 'HLA-DRB1*03:33', 'HLA-DRB1*03:34', 'HLA-DRB1*03:35', 'HLA-DRB1*03:36', 'HLA-DRB1*03:37',
'HLA-DRB1*03:38', 'HLA-DRB1*03:39', 'HLA-DRB1*03:40', 'HLA-DRB1*03:41', 'HLA-DRB1*03:42', 'HLA-DRB1*03:43',
'HLA-DRB1*03:44', 'HLA-DRB1*03:45', 'HLA-DRB1*03:46', 'HLA-DRB1*03:47', 'HLA-DRB1*03:48', 'HLA-DRB1*03:49',
'HLA-DRB1*03:50', 'HLA-DRB1*03:51', 'HLA-DRB1*03:52', 'HLA-DRB1*03:53', 'HLA-DRB1*03:54', 'HLA-DRB1*03:55',
'HLA-DRB1*04:01', 'HLA-DRB1*04:02', 'HLA-DRB1*04:03', 'HLA-DRB1*04:04', 'HLA-DRB1*04:05', 'HLA-DRB1*04:06',
'HLA-DRB1*04:07', 'HLA-DRB1*04:08', 'HLA-DRB1*04:09', 'HLA-DRB1*04:10', 'HLA-DRB1*04:11', 'HLA-DRB1*04:12',
'HLA-DRB1*04:13', 'HLA-DRB1*04:14', 'HLA-DRB1*04:15', 'HLA-DRB1*04:16', 'HLA-DRB1*04:17', 'HLA-DRB1*04:18',
'HLA-DRB1*04:19', 'HLA-DRB1*04:21', 'HLA-DRB1*04:22', 'HLA-DRB1*04:23', 'HLA-DRB1*04:24', 'HLA-DRB1*04:26',
'HLA-DRB1*04:27', 'HLA-DRB1*04:28', 'HLA-DRB1*04:29', 'HLA-DRB1*04:30', 'HLA-DRB1*04:31', 'HLA-DRB1*04:33',
'HLA-DRB1*04:34', 'HLA-DRB1*04:35', 'HLA-DRB1*04:36', 'HLA-DRB1*04:37', 'HLA-DRB1*04:38', 'HLA-DRB1*04:39',
'HLA-DRB1*04:40', 'HLA-DRB1*04:41', 'HLA-DRB1*04:42', 'HLA-DRB1*04:43', 'HLA-DRB1*04:44', 'HLA-DRB1*04:45',
'HLA-DRB1*04:46', 'HLA-DRB1*04:47', 'HLA-DRB1*04:48', 'HLA-DRB1*04:49', 'HLA-DRB1*04:50', 'HLA-DRB1*04:51',
'HLA-DRB1*04:52', 'HLA-DRB1*04:53', 'HLA-DRB1*04:54', 'HLA-DRB1*04:55', 'HLA-DRB1*04:56', 'HLA-DRB1*04:57',
'HLA-DRB1*04:58', 'HLA-DRB1*04:59', 'HLA-DRB1*04:60', 'HLA-DRB1*04:61', 'HLA-DRB1*04:62', 'HLA-DRB1*04:63',
'HLA-DRB1*04:64', 'HLA-DRB1*04:65', 'HLA-DRB1*04:66', 'HLA-DRB1*04:67', 'HLA-DRB1*04:68', 'HLA-DRB1*04:69',
'HLA-DRB1*04:70', 'HLA-DRB1*04:71', 'HLA-DRB1*04:72', 'HLA-DRB1*04:73', 'HLA-DRB1*04:74', 'HLA-DRB1*04:75',
'HLA-DRB1*04:76', 'HLA-DRB1*04:77', 'HLA-DRB1*04:78', 'HLA-DRB1*04:79', 'HLA-DRB1*04:80', 'HLA-DRB1*04:82',
'HLA-DRB1*04:83', 'HLA-DRB1*04:84', 'HLA-DRB1*04:85', 'HLA-DRB1*04:86', 'HLA-DRB1*04:87', 'HLA-DRB1*04:88',
'HLA-DRB1*04:89', 'HLA-DRB1*04:91', 'HLA-DRB1*07:01', 'HLA-DRB1*07:03', 'HLA-DRB1*07:04', 'HLA-DRB1*07:05',
'HLA-DRB1*07:06', 'HLA-DRB1*07:07', 'HLA-DRB1*07:08', 'HLA-DRB1*07:09', 'HLA-DRB1*07:11', 'HLA-DRB1*07:12',
'HLA-DRB1*07:13', 'HLA-DRB1*07:14', 'HLA-DRB1*07:15', 'HLA-DRB1*07:16', 'HLA-DRB1*07:17', 'HLA-DRB1*07:19',
'HLA-DRB1*08:01', 'HLA-DRB1*08:02', 'HLA-DRB1*08:03', 'HLA-DRB1*08:04', 'HLA-DRB1*08:05', 'HLA-DRB1*08:06',
'HLA-DRB1*08:07', 'HLA-DRB1*08:08', 'HLA-DRB1*08:09', 'HLA-DRB1*08:10', 'HLA-DRB1*08:11', 'HLA-DRB1*08:12',
'HLA-DRB1*08:13', 'HLA-DRB1*08:14', 'HLA-DRB1*08:15', 'HLA-DRB1*08:16', 'HLA-DRB1*08:18', 'HLA-DRB1*08:19',
'HLA-DRB1*08:20', 'HLA-DRB1*08:21', 'HLA-DRB1*08:22', 'HLA-DRB1*08:23', 'HLA-DRB1*08:24', 'HLA-DRB1*08:25',
'HLA-DRB1*08:26', 'HLA-DRB1*08:27', 'HLA-DRB1*08:28', 'HLA-DRB1*08:29', 'HLA-DRB1*08:30', 'HLA-DRB1*08:31',
'HLA-DRB1*08:32', 'HLA-DRB1*08:33', 'HLA-DRB1*08:34', 'HLA-DRB1*08:35', 'HLA-DRB1*08:36', 'HLA-DRB1*08:37',
'HLA-DRB1*08:38', 'HLA-DRB1*08:39', 'HLA-DRB1*08:40', 'HLA-DRB1*09:01', 'HLA-DRB1*09:02', 'HLA-DRB1*09:03',
'HLA-DRB1*09:04', 'HLA-DRB1*09:05', 'HLA-DRB1*09:06', 'HLA-DRB1*09:07', 'HLA-DRB1*09:08', 'HLA-DRB1*09:09',
'HLA-DRB1*10:01', 'HLA-DRB1*10:02', 'HLA-DRB1*10:03', 'HLA-DRB1*11:01', 'HLA-DRB1*11:02', 'HLA-DRB1*11:03',
'HLA-DRB1*11:04', 'HLA-DRB1*11:05', 'HLA-DRB1*11:06', 'HLA-DRB1*11:07', 'HLA-DRB1*11:08', 'HLA-DRB1*11:09',
'HLA-DRB1*11:10', 'HLA-DRB1*11:11', 'HLA-DRB1*11:12', 'HLA-DRB1*11:13', 'HLA-DRB1*11:14', 'HLA-DRB1*11:15',
'HLA-DRB1*11:16', 'HLA-DRB1*11:17', 'HLA-DRB1*11:18', 'HLA-DRB1*11:19', 'HLA-DRB1*11:20', 'HLA-DRB1*11:21',
'HLA-DRB1*11:24', 'HLA-DRB1*11:25', 'HLA-DRB1*11:27', 'HLA-DRB1*11:28', 'HLA-DRB1*11:29', 'HLA-DRB1*11:30',
'HLA-DRB1*11:31', 'HLA-DRB1*11:32', 'HLA-DRB1*11:33', 'HLA-DRB1*11:34', 'HLA-DRB1*11:35', 'HLA-DRB1*11:36',
'HLA-DRB1*11:37', 'HLA-DRB1*11:38', 'HLA-DRB1*11:39', 'HLA-DRB1*11:41', 'HLA-DRB1*11:42', 'HLA-DRB1*11:43',
'HLA-DRB1*11:44', 'HLA-DRB1*11:45', 'HLA-DRB1*11:46', 'HLA-DRB1*11:47', 'HLA-DRB1*11:48', 'HLA-DRB1*11:49',
'HLA-DRB1*11:50', 'HLA-DRB1*11:51', 'HLA-DRB1*11:52', 'HLA-DRB1*11:53', 'HLA-DRB1*11:54', 'HLA-DRB1*11:55',
'HLA-DRB1*11:56', 'HLA-DRB1*11:57', 'HLA-DRB1*11:58', 'HLA-DRB1*11:59', 'HLA-DRB1*11:60', 'HLA-DRB1*11:61',
'HLA-DRB1*11:62', 'HLA-DRB1*11:63', 'HLA-DRB1*11:64', 'HLA-DRB1*11:65', 'HLA-DRB1*11:66', 'HLA-DRB1*11:67',
'HLA-DRB1*11:68', 'HLA-DRB1*11:69', 'HLA-DRB1*11:70', 'HLA-DRB1*11:72', 'HLA-DRB1*11:73', 'HLA-DRB1*11:74',
'HLA-DRB1*11:75', 'HLA-DRB1*11:76', 'HLA-DRB1*11:77', 'HLA-DRB1*11:78', 'HLA-DRB1*11:79', 'HLA-DRB1*11:80',
'HLA-DRB1*11:81', 'HLA-DRB1*11:82', 'HLA-DRB1*11:83', 'HLA-DRB1*11:84', 'HLA-DRB1*11:85', 'HLA-DRB1*11:86',
'HLA-DRB1*11:87', 'HLA-DRB1*11:88', 'HLA-DRB1*11:89', 'HLA-DRB1*11:90', 'HLA-DRB1*11:91', 'HLA-DRB1*11:92',
'HLA-DRB1*11:93', 'HLA-DRB1*11:94', 'HLA-DRB1*11:95', 'HLA-DRB1*11:96', 'HLA-DRB1*12:01', 'HLA-DRB1*12:02',
'HLA-DRB1*12:03', 'HLA-DRB1*12:04', 'HLA-DRB1*12:05', 'HLA-DRB1*12:06', 'HLA-DRB1*12:07', 'HLA-DRB1*12:08',
'HLA-DRB1*12:09', 'HLA-DRB1*12:10', 'HLA-DRB1*12:11', 'HLA-DRB1*12:12', 'HLA-DRB1*12:13', 'HLA-DRB1*12:14',
'HLA-DRB1*12:15', 'HLA-DRB1*12:16', 'HLA-DRB1*12:17', 'HLA-DRB1*12:18', 'HLA-DRB1*12:19', 'HLA-DRB1*12:20',
'HLA-DRB1*12:21', 'HLA-DRB1*12:22', 'HLA-DRB1*12:23', 'HLA-DRB1*13:01', 'HLA-DRB1*13:02', 'HLA-DRB1*13:03',
'HLA-DRB1*13:04', 'HLA-DRB1*13:05', 'HLA-DRB1*13:06', 'HLA-DRB1*13:07', 'HLA-DRB1*13:08', 'HLA-DRB1*13:09',
'HLA-DRB1*13:10', 'HLA-DRB1*13:100', 'HLA-DRB1*13:101', 'HLA-DRB1*13:11', 'HLA-DRB1*13:12', 'HLA-DRB1*13:13',
'HLA-DRB1*13:14', 'HLA-DRB1*13:15', 'HLA-DRB1*13:16', 'HLA-DRB1*13:17', 'HLA-DRB1*13:18', 'HLA-DRB1*13:19',
'HLA-DRB1*13:20', 'HLA-DRB1*13:21', 'HLA-DRB1*13:22', 'HLA-DRB1*13:23', 'HLA-DRB1*13:24', 'HLA-DRB1*13:26',
'HLA-DRB1*13:27', 'HLA-DRB1*13:29', 'HLA-DRB1*13:30', 'HLA-DRB1*13:31', 'HLA-DRB1*13:32', 'HLA-DRB1*13:33',
'HLA-DRB1*13:34', 'HLA-DRB1*13:35', 'HLA-DRB1*13:36', 'HLA-DRB1*13:37', 'HLA-DRB1*13:38', 'HLA-DRB1*13:39',
'HLA-DRB1*13:41', 'HLA-DRB1*13:42', 'HLA-DRB1*13:43', 'HLA-DRB1*13:44', 'HLA-DRB1*13:46', 'HLA-DRB1*13:47',
'HLA-DRB1*13:48', 'HLA-DRB1*13:49', 'HLA-DRB1*13:50', 'HLA-DRB1*13:51', 'HLA-DRB1*13:52', 'HLA-DRB1*13:53',
'HLA-DRB1*13:54', 'HLA-DRB1*13:55', 'HLA-DRB1*13:56', 'HLA-DRB1*13:57', 'HLA-DRB1*13:58', 'HLA-DRB1*13:59',
'HLA-DRB1*13:60', 'HLA-DRB1*13:61', 'HLA-DRB1*13:62', 'HLA-DRB1*13:63', 'HLA-DRB1*13:64', 'HLA-DRB1*13:65',
'HLA-DRB1*13:66', 'HLA-DRB1*13:67', 'HLA-DRB1*13:68', 'HLA-DRB1*13:69', 'HLA-DRB1*13:70', 'HLA-DRB1*13:71',
'HLA-DRB1*13:72', 'HLA-DRB1*13:73', 'HLA-DRB1*13:74', 'HLA-DRB1*13:75', 'HLA-DRB1*13:76', 'HLA-DRB1*13:77',
'HLA-DRB1*13:78', 'HLA-DRB1*13:79', 'HLA-DRB1*13:80', 'HLA-DRB1*13:81', 'HLA-DRB1*13:82', 'HLA-DRB1*13:83',
'HLA-DRB1*13:84', 'HLA-DRB1*13:85', 'HLA-DRB1*13:86', 'HLA-DRB1*13:87', 'HLA-DRB1*13:88', 'HLA-DRB1*13:89',
'HLA-DRB1*13:90', 'HLA-DRB1*13:91', 'HLA-DRB1*13:92', 'HLA-DRB1*13:93', 'HLA-DRB1*13:94', 'HLA-DRB1*13:95',
'HLA-DRB1*13:96', 'HLA-DRB1*13:97', 'HLA-DRB1*13:98', 'HLA-DRB1*13:99', 'HLA-DRB1*14:01', 'HLA-DRB1*14:02',
'HLA-DRB1*14:03', 'HLA-DRB1*14:04', 'HLA-DRB1*14:05', 'HLA-DRB1*14:06', 'HLA-DRB1*14:07', 'HLA-DRB1*14:08',
'HLA-DRB1*14:09', 'HLA-DRB1*14:10', 'HLA-DRB1*14:11', 'HLA-DRB1*14:12', 'HLA-DRB1*14:13', 'HLA-DRB1*14:14',
'HLA-DRB1*14:15', 'HLA-DRB1*14:16', 'HLA-DRB1*14:17', 'HLA-DRB1*14:18', 'HLA-DRB1*14:19', 'HLA-DRB1*14:20',
'HLA-DRB1*14:21', 'HLA-DRB1*14:22', 'HLA-DRB1*14:23', 'HLA-DRB1*14:24', 'HLA-DRB1*14:25', 'HLA-DRB1*14:26',
'HLA-DRB1*14:27', 'HLA-DRB1*14:28', 'HLA-DRB1*14:29', 'HLA-DRB1*14:30', 'HLA-DRB1*14:31', 'HLA-DRB1*14:32',
'HLA-DRB1*14:33', 'HLA-DRB1*14:34', 'HLA-DRB1*14:35', 'HLA-DRB1*14:36', 'HLA-DRB1*14:37', 'HLA-DRB1*14:38',
'HLA-DRB1*14:39', 'HLA-DRB1*14:40', 'HLA-DRB1*14:41', 'HLA-DRB1*14:42', 'HLA-DRB1*14:43', 'HLA-DRB1*14:44',
'HLA-DRB1*14:45', 'HLA-DRB1*14:46', 'HLA-DRB1*14:47', 'HLA-DRB1*14:48', 'HLA-DRB1*14:49', 'HLA-DRB1*14:50',
'HLA-DRB1*14:51', 'HLA-DRB1*14:52', 'HLA-DRB1*14:53', 'HLA-DRB1*14:54', 'HLA-DRB1*14:55', 'HLA-DRB1*14:56',
'HLA-DRB1*14:57', 'HLA-DRB1*14:58', 'HLA-DRB1*14:59', 'HLA-DRB1*14:60', 'HLA-DRB1*14:61', 'HLA-DRB1*14:62',
'HLA-DRB1*14:63', 'HLA-DRB1*14:64', 'HLA-DRB1*14:65', 'HLA-DRB1*14:67', 'HLA-DRB1*14:68', 'HLA-DRB1*14:69',
'HLA-DRB1*14:70', 'HLA-DRB1*14:71', 'HLA-DRB1*14:72', 'HLA-DRB1*14:73', 'HLA-DRB1*14:74', 'HLA-DRB1*14:75',
'HLA-DRB1*14:76', 'HLA-DRB1*14:77', 'HLA-DRB1*14:78', 'HLA-DRB1*14:79', 'HLA-DRB1*14:80', 'HLA-DRB1*14:81',
'HLA-DRB1*14:82', 'HLA-DRB1*14:83', 'HLA-DRB1*14:84', 'HLA-DRB1*14:85', 'HLA-DRB1*14:86', 'HLA-DRB1*14:87',
'HLA-DRB1*14:88', 'HLA-DRB1*14:89', 'HLA-DRB1*14:90', 'HLA-DRB1*14:91', 'HLA-DRB1*14:93', 'HLA-DRB1*14:94',
'HLA-DRB1*14:95', 'HLA-DRB1*14:96', 'HLA-DRB1*14:97', 'HLA-DRB1*14:98', 'HLA-DRB1*14:99', 'HLA-DRB1*15:01',
'HLA-DRB1*15:02', 'HLA-DRB1*15:03', 'HLA-DRB1*15:04', 'HLA-DRB1*15:05', 'HLA-DRB1*15:06', 'HLA-DRB1*15:07',
'HLA-DRB1*15:08', 'HLA-DRB1*15:09', 'HLA-DRB1*15:10', 'HLA-DRB1*15:11', 'HLA-DRB1*15:12', 'HLA-DRB1*15:13',
'HLA-DRB1*15:14', 'HLA-DRB1*15:15', 'HLA-DRB1*15:16', 'HLA-DRB1*15:18', 'HLA-DRB1*15:19', 'HLA-DRB1*15:20',
'HLA-DRB1*15:21', 'HLA-DRB1*15:22', 'HLA-DRB1*15:23', 'HLA-DRB1*15:24', 'HLA-DRB1*15:25', 'HLA-DRB1*15:26',
'HLA-DRB1*15:27', 'HLA-DRB1*15:28', 'HLA-DRB1*15:29', 'HLA-DRB1*15:30', 'HLA-DRB1*15:31', 'HLA-DRB1*15:32',
'HLA-DRB1*15:33', 'HLA-DRB1*15:34', 'HLA-DRB1*15:35', 'HLA-DRB1*15:36', 'HLA-DRB1*15:37', 'HLA-DRB1*15:38',
'HLA-DRB1*15:39', 'HLA-DRB1*15:40', 'HLA-DRB1*15:41', 'HLA-DRB1*15:42', 'HLA-DRB1*15:43', 'HLA-DRB1*15:44',
'HLA-DRB1*15:45', 'HLA-DRB1*15:46', 'HLA-DRB1*15:47', 'HLA-DRB1*15:48', 'HLA-DRB1*15:49', 'HLA-DRB1*16:01',
'HLA-DRB1*16:02', 'HLA-DRB1*16:03', 'HLA-DRB1*16:04', 'HLA-DRB1*16:05', 'HLA-DRB1*16:07', 'HLA-DRB1*16:08',
'HLA-DRB1*16:09', 'HLA-DRB1*16:10', 'HLA-DRB1*16:11', 'HLA-DRB1*16:12', 'HLA-DRB1*16:14', 'HLA-DRB1*16:15',
'HLA-DRB1*16:16', 'HLA-DRB3*01:01', 'HLA-DRB3*01:04', 'HLA-DRB3*01:05', 'HLA-DRB3*01:08', 'HLA-DRB3*01:09',
'HLA-DRB3*01:11', 'HLA-DRB3*01:12', 'HLA-DRB3*01:13', 'HLA-DRB3*01:14', 'HLA-DRB3*02:01', 'HLA-DRB3*02:02',
'HLA-DRB3*02:04', 'HLA-DRB3*02:05', 'HLA-DRB3*02:09', 'HLA-DRB3*02:10', 'HLA-DRB3*02:11', 'HLA-DRB3*02:12',
'HLA-DRB3*02:13', 'HLA-DRB3*02:14', 'HLA-DRB3*02:15', 'HLA-DRB3*02:16', 'HLA-DRB3*02:17', 'HLA-DRB3*02:18',
'HLA-DRB3*02:19', 'HLA-DRB3*02:20', 'HLA-DRB3*02:21', 'HLA-DRB3*02:22', 'HLA-DRB3*02:23', 'HLA-DRB3*02:24',
'HLA-DRB3*02:25', 'HLA-DRB3*03:01', 'HLA-DRB3*03:03', 'HLA-DRB4*01:01', 'HLA-DRB4*01:03', 'HLA-DRB4*01:04',
'HLA-DRB4*01:06', 'HLA-DRB4*01:07', 'HLA-DRB4*01:08', 'HLA-DRB5*01:01', 'HLA-DRB5*01:02', 'HLA-DRB5*01:03',
'HLA-DRB5*01:04', 'HLA-DRB5*01:05', 'HLA-DRB5*01:06', 'HLA-DRB5*01:08N', 'HLA-DRB5*01:11', 'HLA-DRB5*01:12',
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'HLA-DQA1*05:11-HLA-DQB1*06:35', 'HLA-DQA1*05:11-HLA-DQB1*06:36',
'HLA-DQA1*05:11-HLA-DQB1*06:37', 'HLA-DQA1*05:11-HLA-DQB1*06:38', 'HLA-DQA1*05:11-HLA-DQB1*06:39', 'HLA-DQA1*05:11-HLA-DQB1*06:40',
'HLA-DQA1*05:11-HLA-DQB1*06:41', 'HLA-DQA1*05:11-HLA-DQB1*06:42',
'HLA-DQA1*05:11-HLA-DQB1*06:43', 'HLA-DQA1*05:11-HLA-DQB1*06:44', 'HLA-DQA1*06:01-HLA-DQB1*02:01', 'HLA-DQA1*06:01-HLA-DQB1*02:02',
'HLA-DQA1*06:01-HLA-DQB1*02:03', 'HLA-DQA1*06:01-HLA-DQB1*02:04',
'HLA-DQA1*06:01-HLA-DQB1*02:05', 'HLA-DQA1*06:01-HLA-DQB1*02:06', 'HLA-DQA1*06:01-HLA-DQB1*03:01', 'HLA-DQA1*06:01-HLA-DQB1*03:02',
'HLA-DQA1*06:01-HLA-DQB1*03:03', 'HLA-DQA1*06:01-HLA-DQB1*03:04',
'HLA-DQA1*06:01-HLA-DQB1*03:05', 'HLA-DQA1*06:01-HLA-DQB1*03:06', 'HLA-DQA1*06:01-HLA-DQB1*03:07', 'HLA-DQA1*06:01-HLA-DQB1*03:08',
'HLA-DQA1*06:01-HLA-DQB1*03:09', 'HLA-DQA1*06:01-HLA-DQB1*03:10',
'HLA-DQA1*06:01-HLA-DQB1*03:11', 'HLA-DQA1*06:01-HLA-DQB1*03:12', 'HLA-DQA1*06:01-HLA-DQB1*03:13', 'HLA-DQA1*06:01-HLA-DQB1*03:14',
'HLA-DQA1*06:01-HLA-DQB1*03:15', 'HLA-DQA1*06:01-HLA-DQB1*03:16',
'HLA-DQA1*06:01-HLA-DQB1*03:17', 'HLA-DQA1*06:01-HLA-DQB1*03:18', 'HLA-DQA1*06:01-HLA-DQB1*03:19', 'HLA-DQA1*06:01-HLA-DQB1*03:20',
'HLA-DQA1*06:01-HLA-DQB1*03:21', 'HLA-DQA1*06:01-HLA-DQB1*03:22',
'HLA-DQA1*06:01-HLA-DQB1*03:23', 'HLA-DQA1*06:01-HLA-DQB1*03:24', 'HLA-DQA1*06:01-HLA-DQB1*03:25', 'HLA-DQA1*06:01-HLA-DQB1*03:26',
'HLA-DQA1*06:01-HLA-DQB1*03:27', 'HLA-DQA1*06:01-HLA-DQB1*03:28',
'HLA-DQA1*06:01-HLA-DQB1*03:29', 'HLA-DQA1*06:01-HLA-DQB1*03:30', 'HLA-DQA1*06:01-HLA-DQB1*03:31', 'HLA-DQA1*06:01-HLA-DQB1*03:32',
'HLA-DQA1*06:01-HLA-DQB1*03:33', 'HLA-DQA1*06:01-HLA-DQB1*03:34',
'HLA-DQA1*06:01-HLA-DQB1*03:35', 'HLA-DQA1*06:01-HLA-DQB1*03:36', 'HLA-DQA1*06:01-HLA-DQB1*03:37', 'HLA-DQA1*06:01-HLA-DQB1*03:38',
'HLA-DQA1*06:01-HLA-DQB1*04:01', 'HLA-DQA1*06:01-HLA-DQB1*04:02',
'HLA-DQA1*06:01-HLA-DQB1*04:03', 'HLA-DQA1*06:01-HLA-DQB1*04:04', 'HLA-DQA1*06:01-HLA-DQB1*04:05', 'HLA-DQA1*06:01-HLA-DQB1*04:06',
'HLA-DQA1*06:01-HLA-DQB1*04:07', 'HLA-DQA1*06:01-HLA-DQB1*04:08',
'HLA-DQA1*06:01-HLA-DQB1*05:01', 'HLA-DQA1*06:01-HLA-DQB1*05:02', 'HLA-DQA1*06:01-HLA-DQB1*05:03', 'HLA-DQA1*06:01-HLA-DQB1*05:05',
'HLA-DQA1*06:01-HLA-DQB1*05:06', 'HLA-DQA1*06:01-HLA-DQB1*05:07',
'HLA-DQA1*06:01-HLA-DQB1*05:08', 'HLA-DQA1*06:01-HLA-DQB1*05:09', 'HLA-DQA1*06:01-HLA-DQB1*05:10', 'HLA-DQA1*06:01-HLA-DQB1*05:11',
'HLA-DQA1*06:01-HLA-DQB1*05:12', 'HLA-DQA1*06:01-HLA-DQB1*05:13',
'HLA-DQA1*06:01-HLA-DQB1*05:14', 'HLA-DQA1*06:01-HLA-DQB1*06:01', 'HLA-DQA1*06:01-HLA-DQB1*06:02', 'HLA-DQA1*06:01-HLA-DQB1*06:03',
'HLA-DQA1*06:01-HLA-DQB1*06:04', 'HLA-DQA1*06:01-HLA-DQB1*06:07',
'HLA-DQA1*06:01-HLA-DQB1*06:08', 'HLA-DQA1*06:01-HLA-DQB1*06:09', 'HLA-DQA1*06:01-HLA-DQB1*06:10', 'HLA-DQA1*06:01-HLA-DQB1*06:11',
'HLA-DQA1*06:01-HLA-DQB1*06:12', 'HLA-DQA1*06:01-HLA-DQB1*06:14',
'HLA-DQA1*06:01-HLA-DQB1*06:15', 'HLA-DQA1*06:01-HLA-DQB1*06:16', 'HLA-DQA1*06:01-HLA-DQB1*06:17', 'HLA-DQA1*06:01-HLA-DQB1*06:18',
'HLA-DQA1*06:01-HLA-DQB1*06:19', 'HLA-DQA1*06:01-HLA-DQB1*06:21',
'HLA-DQA1*06:01-HLA-DQB1*06:22', 'HLA-DQA1*06:01-HLA-DQB1*06:23', 'HLA-DQA1*06:01-HLA-DQB1*06:24', 'HLA-DQA1*06:01-HLA-DQB1*06:25',
'HLA-DQA1*06:01-HLA-DQB1*06:27', 'HLA-DQA1*06:01-HLA-DQB1*06:28',
'HLA-DQA1*06:01-HLA-DQB1*06:29', 'HLA-DQA1*06:01-HLA-DQB1*06:30', 'HLA-DQA1*06:01-HLA-DQB1*06:31', 'HLA-DQA1*06:01-HLA-DQB1*06:32',
'HLA-DQA1*06:01-HLA-DQB1*06:33', 'HLA-DQA1*06:01-HLA-DQB1*06:34',
'HLA-DQA1*06:01-HLA-DQB1*06:35', 'HLA-DQA1*06:01-HLA-DQB1*06:36', 'HLA-DQA1*06:01-HLA-DQB1*06:37', 'HLA-DQA1*06:01-HLA-DQB1*06:38',
'HLA-DQA1*06:01-HLA-DQB1*06:39', 'HLA-DQA1*06:01-HLA-DQB1*06:40',
'HLA-DQA1*06:01-HLA-DQB1*06:41', 'HLA-DQA1*06:01-HLA-DQB1*06:42', 'HLA-DQA1*06:01-HLA-DQB1*06:43', 'HLA-DQA1*06:01-HLA-DQB1*06:44',
'HLA-DQA1*06:02-HLA-DQB1*02:01', 'HLA-DQA1*06:02-HLA-DQB1*02:02',
'HLA-DQA1*06:02-HLA-DQB1*02:03', 'HLA-DQA1*06:02-HLA-DQB1*02:04', 'HLA-DQA1*06:02-HLA-DQB1*02:05', 'HLA-DQA1*06:02-HLA-DQB1*02:06',
'HLA-DQA1*06:02-HLA-DQB1*03:01', 'HLA-DQA1*06:02-HLA-DQB1*03:02',
'HLA-DQA1*06:02-HLA-DQB1*03:03', 'HLA-DQA1*06:02-HLA-DQB1*03:04', 'HLA-DQA1*06:02-HLA-DQB1*03:05', 'HLA-DQA1*06:02-HLA-DQB1*03:06',
'HLA-DQA1*06:02-HLA-DQB1*03:07', 'HLA-DQA1*06:02-HLA-DQB1*03:08',
'HLA-DQA1*06:02-HLA-DQB1*03:09', 'HLA-DQA1*06:02-HLA-DQB1*03:10', 'HLA-DQA1*06:02-HLA-DQB1*03:11', 'HLA-DQA1*06:02-HLA-DQB1*03:12',
'HLA-DQA1*06:02-HLA-DQB1*03:13', 'HLA-DQA1*06:02-HLA-DQB1*03:14',
'HLA-DQA1*06:02-HLA-DQB1*03:15', 'HLA-DQA1*06:02-HLA-DQB1*03:16', 'HLA-DQA1*06:02-HLA-DQB1*03:17', 'HLA-DQA1*06:02-HLA-DQB1*03:18',
'HLA-DQA1*06:02-HLA-DQB1*03:19', 'HLA-DQA1*06:02-HLA-DQB1*03:20',
'HLA-DQA1*06:02-HLA-DQB1*03:21', 'HLA-DQA1*06:02-HLA-DQB1*03:22', 'HLA-DQA1*06:02-HLA-DQB1*03:23', 'HLA-DQA1*06:02-HLA-DQB1*03:24',
'HLA-DQA1*06:02-HLA-DQB1*03:25', 'HLA-DQA1*06:02-HLA-DQB1*03:26',
'HLA-DQA1*06:02-HLA-DQB1*03:27', 'HLA-DQA1*06:02-HLA-DQB1*03:28', 'HLA-DQA1*06:02-HLA-DQB1*03:29', 'HLA-DQA1*06:02-HLA-DQB1*03:30',
'HLA-DQA1*06:02-HLA-DQB1*03:31', 'HLA-DQA1*06:02-HLA-DQB1*03:32',
'HLA-DQA1*06:02-HLA-DQB1*03:33', 'HLA-DQA1*06:02-HLA-DQB1*03:34', 'HLA-DQA1*06:02-HLA-DQB1*03:35', 'HLA-DQA1*06:02-HLA-DQB1*03:36',
'HLA-DQA1*06:02-HLA-DQB1*03:37', 'HLA-DQA1*06:02-HLA-DQB1*03:38',
'HLA-DQA1*06:02-HLA-DQB1*04:01', 'HLA-DQA1*06:02-HLA-DQB1*04:02', 'HLA-DQA1*06:02-HLA-DQB1*04:03', 'HLA-DQA1*06:02-HLA-DQB1*04:04',
'HLA-DQA1*06:02-HLA-DQB1*04:05', 'HLA-DQA1*06:02-HLA-DQB1*04:06',
'HLA-DQA1*06:02-HLA-DQB1*04:07', 'HLA-DQA1*06:02-HLA-DQB1*04:08', 'HLA-DQA1*06:02-HLA-DQB1*05:01', 'HLA-DQA1*06:02-HLA-DQB1*05:02',
'HLA-DQA1*06:02-HLA-DQB1*05:03', 'HLA-DQA1*06:02-HLA-DQB1*05:05',
'HLA-DQA1*06:02-HLA-DQB1*05:06', 'HLA-DQA1*06:02-HLA-DQB1*05:07', 'HLA-DQA1*06:02-HLA-DQB1*05:08', 'HLA-DQA1*06:02-HLA-DQB1*05:09',
'HLA-DQA1*06:02-HLA-DQB1*05:10', 'HLA-DQA1*06:02-HLA-DQB1*05:11',
'HLA-DQA1*06:02-HLA-DQB1*05:12', 'HLA-DQA1*06:02-HLA-DQB1*05:13', 'HLA-DQA1*06:02-HLA-DQB1*05:14', 'HLA-DQA1*06:02-HLA-DQB1*06:01',
'HLA-DQA1*06:02-HLA-DQB1*06:02', 'HLA-DQA1*06:02-HLA-DQB1*06:03',
'HLA-DQA1*06:02-HLA-DQB1*06:04', 'HLA-DQA1*06:02-HLA-DQB1*06:07', 'HLA-DQA1*06:02-HLA-DQB1*06:08', 'HLA-DQA1*06:02-HLA-DQB1*06:09',
'HLA-DQA1*06:02-HLA-DQB1*06:10', 'HLA-DQA1*06:02-HLA-DQB1*06:11',
'HLA-DQA1*06:02-HLA-DQB1*06:12', 'HLA-DQA1*06:02-HLA-DQB1*06:14', 'HLA-DQA1*06:02-HLA-DQB1*06:15', 'HLA-DQA1*06:02-HLA-DQB1*06:16',
'HLA-DQA1*06:02-HLA-DQB1*06:17', 'HLA-DQA1*06:02-HLA-DQB1*06:18',
'HLA-DQA1*06:02-HLA-DQB1*06:19', 'HLA-DQA1*06:02-HLA-DQB1*06:21', 'HLA-DQA1*06:02-HLA-DQB1*06:22', 'HLA-DQA1*06:02-HLA-DQB1*06:23',
'HLA-DQA1*06:02-HLA-DQB1*06:24', 'HLA-DQA1*06:02-HLA-DQB1*06:25',
'HLA-DQA1*06:02-HLA-DQB1*06:27', 'HLA-DQA1*06:02-HLA-DQB1*06:28', 'HLA-DQA1*06:02-HLA-DQB1*06:29', 'HLA-DQA1*06:02-HLA-DQB1*06:30',
'HLA-DQA1*06:02-HLA-DQB1*06:31', 'HLA-DQA1*06:02-HLA-DQB1*06:32',
'HLA-DQA1*06:02-HLA-DQB1*06:33', 'HLA-DQA1*06:02-HLA-DQB1*06:34', 'HLA-DQA1*06:02-HLA-DQB1*06:35', 'HLA-DQA1*06:02-HLA-DQB1*06:36',
'HLA-DQA1*06:02-HLA-DQB1*06:37', 'HLA-DQA1*06:02-HLA-DQB1*06:38',
'HLA-DQA1*06:02-HLA-DQB1*06:39', 'HLA-DQA1*06:02-HLA-DQB1*06:40', 'HLA-DQA1*06:02-HLA-DQB1*06:41', 'HLA-DQA1*06:02-HLA-DQB1*06:42',
'HLA-DQA1*06:02-HLA-DQB1*06:43', 'HLA-DQA1*06:02-HLA-DQB1*06:44',
'H2-IAd', 'H2-IAb'])
__version = "3.1"
@property
def version(self):
"""The version of the predictor"""
return self.__version
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
@property
def supportedAlleles(self):
"""A list of valid :class:`~epytope.Core.Allele.Allele` models"""
return self.__alleles
@property
def name(self):
"""The name of the predictor"""
return self.__name
class PickPocket_1_1(AExternalEpitopePrediction):
"""
Implementation of PickPocket adapter.
.. note::
Zhang, H., Lund, O., & Nielsen, M. (2009). The PickPocket method for predicting binding specificities
for receptors based on receptor pocket similarities: application to MHC-peptide binding.
Bioinformatics, 25(10), 1293-1299.
"""
__name = "pickpocket"
__supported_length = frozenset([8, 9, 10, 11])
__command = 'PickPocket -p {peptides} -a {alleles} {options} | grep -v "#" > {out}'
__supported_alleles = frozenset(['HLA-A*01:01', 'HLA-A*01:02', 'HLA-A*01:03', 'HLA-A*01:06', 'HLA-A*01:07', 'HLA-A*01:08', 'HLA-A*01:09',
'HLA-A*01:10', 'HLA-A*01:12', 'HLA-A*01:13', 'HLA-A*01:14', 'HLA-A*01:17', 'HLA-A*01:19', 'HLA-A*01:20',
'HLA-A*01:21', 'HLA-A*01:23', 'HLA-A*01:24',
'HLA-A*01:25', 'HLA-A*01:26', 'HLA-A*01:28', 'HLA-A*01:29', 'HLA-A*01:30', 'HLA-A*01:32', 'HLA-A*01:33',
'HLA-A*01:35', 'HLA-A*01:36', 'HLA-A*01:37',
'HLA-A*01:38', 'HLA-A*01:39', 'HLA-A*01:40', 'HLA-A*01:41', 'HLA-A*01:42', 'HLA-A*01:43', 'HLA-A*01:44',
'HLA-A*01:45', 'HLA-A*01:46', 'HLA-A*01:47',
'HLA-A*01:48', 'HLA-A*01:49', 'HLA-A*01:50', 'HLA-A*01:51', 'HLA-A*01:54', 'HLA-A*01:55', 'HLA-A*01:58',
'HLA-A*01:59', 'HLA-A*01:60', 'HLA-A*01:61',
'HLA-A*01:62', 'HLA-A*01:63', 'HLA-A*01:64', 'HLA-A*01:65', 'HLA-A*01:66', 'HLA-A*02:01', 'HLA-A*02:02',
'HLA-A*02:03', 'HLA-A*02:04', 'HLA-A*02:05',
'HLA-A*02:06', 'HLA-A*02:07', 'HLA-A*02:08', 'HLA-A*02:09', 'HLA-A*02:10', 'HLA-A*02:11', 'HLA-A*02:12',
'HLA-A*02:13', 'HLA-A*02:14', 'HLA-A*02:16',
'HLA-A*02:17', 'HLA-A*02:18', 'HLA-A*02:19', 'HLA-A*02:20', 'HLA-A*02:21', 'HLA-A*02:22', 'HLA-A*02:24',
'HLA-A*02:25', 'HLA-A*02:26', 'HLA-A*02:27',
'HLA-A*02:28', 'HLA-A*02:29', 'HLA-A*02:30', 'HLA-A*02:31', 'HLA-A*02:33', 'HLA-A*02:34', 'HLA-A*02:35',
'HLA-A*02:36', 'HLA-A*02:37', 'HLA-A*02:38',
'HLA-A*02:39', 'HLA-A*02:40', 'HLA-A*02:41', 'HLA-A*02:42', 'HLA-A*02:44', 'HLA-A*02:45', 'HLA-A*02:46',
'HLA-A*02:47', 'HLA-A*02:48', 'HLA-A*02:49',
'HLA-A*02:50', 'HLA-A*02:51', 'HLA-A*02:52', 'HLA-A*02:54', 'HLA-A*02:55', 'HLA-A*02:56', 'HLA-A*02:57',
'HLA-A*02:58', 'HLA-A*02:59', 'HLA-A*02:60',
'HLA-A*02:61', 'HLA-A*02:62', 'HLA-A*02:63', 'HLA-A*02:64', 'HLA-A*02:65', 'HLA-A*02:66', 'HLA-A*02:67',
'HLA-A*02:68', 'HLA-A*02:69', 'HLA-A*02:70',
'HLA-A*02:71', 'HLA-A*02:72', 'HLA-A*02:73', 'HLA-A*02:74', 'HLA-A*02:75', 'HLA-A*02:76', 'HLA-A*02:77',
'HLA-A*02:78', 'HLA-A*02:79', 'HLA-A*02:80',
'HLA-A*02:81', 'HLA-A*02:84', 'HLA-A*02:85', 'HLA-A*02:86', 'HLA-A*02:87', 'HLA-A*02:89', 'HLA-A*02:90',
'HLA-A*02:91', 'HLA-A*02:92', 'HLA-A*02:93',
'HLA-A*02:95', 'HLA-A*02:96', 'HLA-A*02:97', 'HLA-A*02:99', 'HLA-A*02:101', 'HLA-A*02:102', 'HLA-A*02:103',
'HLA-A*02:104', 'HLA-A*02:105',
'HLA-A*02:106', 'HLA-A*02:107', 'HLA-A*02:108', 'HLA-A*02:109', 'HLA-A*02:110', 'HLA-A*02:111', 'HLA-A*02:112',
'HLA-A*02:114', 'HLA-A*02:115',
'HLA-A*02:116', 'HLA-A*02:117', 'HLA-A*02:118', 'HLA-A*02:119', 'HLA-A*02:120', 'HLA-A*02:121', 'HLA-A*02:122',
'HLA-A*02:123', 'HLA-A*02:124',
'HLA-A*02:126', 'HLA-A*02:127', 'HLA-A*02:128', 'HLA-A*02:129', 'HLA-A*02:130', 'HLA-A*02:131', 'HLA-A*02:132',
'HLA-A*02:133', 'HLA-A*02:134',
'HLA-A*02:135', 'HLA-A*02:136', 'HLA-A*02:137', 'HLA-A*02:138', 'HLA-A*02:139', 'HLA-A*02:140', 'HLA-A*02:141',
'HLA-A*02:142', 'HLA-A*02:143',
'HLA-A*02:144', 'HLA-A*02:145', 'HLA-A*02:146', 'HLA-A*02:147', 'HLA-A*02:148', 'HLA-A*02:149', 'HLA-A*02:150',
'HLA-A*02:151', 'HLA-A*02:152',
'HLA-A*02:153', 'HLA-A*02:154', 'HLA-A*02:155', 'HLA-A*02:156', 'HLA-A*02:157', 'HLA-A*02:158', 'HLA-A*02:159',
'HLA-A*02:160', 'HLA-A*02:161',
'HLA-A*02:162', 'HLA-A*02:163', 'HLA-A*02:164', 'HLA-A*02:165', 'HLA-A*02:166', 'HLA-A*02:167', 'HLA-A*02:168',
'HLA-A*02:169', 'HLA-A*02:170',
'HLA-A*02:171', 'HLA-A*02:172', 'HLA-A*02:173', 'HLA-A*02:174', 'HLA-A*02:175', 'HLA-A*02:176', 'HLA-A*02:177',
'HLA-A*02:178', 'HLA-A*02:179',
'HLA-A*02:180', 'HLA-A*02:181', 'HLA-A*02:182', 'HLA-A*02:183', 'HLA-A*02:184', 'HLA-A*02:185', 'HLA-A*02:186',
'HLA-A*02:187', 'HLA-A*02:188',
'HLA-A*02:189', 'HLA-A*02:190', 'HLA-A*02:191', 'HLA-A*02:192', 'HLA-A*02:193', 'HLA-A*02:194', 'HLA-A*02:195',
'HLA-A*02:196', 'HLA-A*02:197',
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'HLA-C*05:23', 'HLA-C*05:24', 'HLA-C*05:25', 'HLA-C*05:26', 'HLA-C*05:27', 'HLA-C*05:28', 'HLA-C*05:29',
'HLA-C*05:30', 'HLA-C*05:31', 'HLA-C*05:32',
'HLA-C*05:33', 'HLA-C*05:34', 'HLA-C*05:35', 'HLA-C*05:36', 'HLA-C*05:37', 'HLA-C*05:38', 'HLA-C*05:39',
'HLA-C*05:40', 'HLA-C*05:41', 'HLA-C*05:42',
'HLA-C*05:43', 'HLA-C*05:44', 'HLA-C*05:45', 'HLA-C*06:02', 'HLA-C*06:03', 'HLA-C*06:04', 'HLA-C*06:05',
'HLA-C*06:06', 'HLA-C*06:07', 'HLA-C*06:08',
'HLA-C*06:09', 'HLA-C*06:10', 'HLA-C*06:11', 'HLA-C*06:12', 'HLA-C*06:13', 'HLA-C*06:14', 'HLA-C*06:15',
'HLA-C*06:17', 'HLA-C*06:18', 'HLA-C*06:19',
'HLA-C*06:20', 'HLA-C*06:21', 'HLA-C*06:22', 'HLA-C*06:23', 'HLA-C*06:24', 'HLA-C*06:25', 'HLA-C*06:26',
'HLA-C*06:27', 'HLA-C*06:28', 'HLA-C*06:29',
'HLA-C*06:30', 'HLA-C*06:31', 'HLA-C*06:32', 'HLA-C*06:33', 'HLA-C*06:34', 'HLA-C*06:35', 'HLA-C*06:36',
'HLA-C*06:37', 'HLA-C*06:38', 'HLA-C*06:39',
'HLA-C*06:40', 'HLA-C*06:41', 'HLA-C*06:42', 'HLA-C*06:43', 'HLA-C*06:44', 'HLA-C*06:45', 'HLA-C*07:01',
'HLA-C*07:02', 'HLA-C*07:03', 'HLA-C*07:04',
'HLA-C*07:05', 'HLA-C*07:06', 'HLA-C*07:07', 'HLA-C*07:08', 'HLA-C*07:09', 'HLA-C*07:10', 'HLA-C*07:11',
'HLA-C*07:12', 'HLA-C*07:13', 'HLA-C*07:14',
'HLA-C*07:15', 'HLA-C*07:16', 'HLA-C*07:17', 'HLA-C*07:18', 'HLA-C*07:19', 'HLA-C*07:20', 'HLA-C*07:21',
'HLA-C*07:22', 'HLA-C*07:23', 'HLA-C*07:24',
'HLA-C*07:25', 'HLA-C*07:26', 'HLA-C*07:27', 'HLA-C*07:28', 'HLA-C*07:29', 'HLA-C*07:30', 'HLA-C*07:31',
'HLA-C*07:35', 'HLA-C*07:36', 'HLA-C*07:37',
'HLA-C*07:38', 'HLA-C*07:39', 'HLA-C*07:40', 'HLA-C*07:41', 'HLA-C*07:42', 'HLA-C*07:43', 'HLA-C*07:44',
'HLA-C*07:45', 'HLA-C*07:46', 'HLA-C*07:47',
'HLA-C*07:48', 'HLA-C*07:49', 'HLA-C*07:50', 'HLA-C*07:51', 'HLA-C*07:52', 'HLA-C*07:53', 'HLA-C*07:54',
'HLA-C*07:56', 'HLA-C*07:57', 'HLA-C*07:58',
'HLA-C*07:59', 'HLA-C*07:60', 'HLA-C*07:62', 'HLA-C*07:63', 'HLA-C*07:64', 'HLA-C*07:65', 'HLA-C*07:66',
'HLA-C*07:67', 'HLA-C*07:68', 'HLA-C*07:69',
'HLA-C*07:70', 'HLA-C*07:71', 'HLA-C*07:72', 'HLA-C*07:73', 'HLA-C*07:74', 'HLA-C*07:75', 'HLA-C*07:76',
'HLA-C*07:77', 'HLA-C*07:78', 'HLA-C*07:79',
'HLA-C*07:80', 'HLA-C*07:81', 'HLA-C*07:82', 'HLA-C*07:83', 'HLA-C*07:84', 'HLA-C*07:85', 'HLA-C*07:86',
'HLA-C*07:87', 'HLA-C*07:88', 'HLA-C*07:89',
'HLA-C*07:90', 'HLA-C*07:91', 'HLA-C*07:92', 'HLA-C*07:93', 'HLA-C*07:94', 'HLA-C*07:95', 'HLA-C*07:96',
'HLA-C*07:97', 'HLA-C*07:99', 'HLA-C*07:100',
'HLA-C*07:101', 'HLA-C*07:102', 'HLA-C*07:103', 'HLA-C*07:105', 'HLA-C*07:106', 'HLA-C*07:107', 'HLA-C*07:108',
'HLA-C*07:109', 'HLA-C*07:110',
'HLA-C*07:111', 'HLA-C*07:112', 'HLA-C*07:113', 'HLA-C*07:114', 'HLA-C*07:115', 'HLA-C*07:116', 'HLA-C*07:117',
'HLA-C*07:118', 'HLA-C*07:119',
'HLA-C*07:120', 'HLA-C*07:122', 'HLA-C*07:123', 'HLA-C*07:124', 'HLA-C*07:125', 'HLA-C*07:126', 'HLA-C*07:127',
'HLA-C*07:128', 'HLA-C*07:129',
'HLA-C*07:130', 'HLA-C*07:131', 'HLA-C*07:132', 'HLA-C*07:133', 'HLA-C*07:134', 'HLA-C*07:135', 'HLA-C*07:136',
'HLA-C*07:137', 'HLA-C*07:138',
'HLA-C*07:139', 'HLA-C*07:140', 'HLA-C*07:141', 'HLA-C*07:142', 'HLA-C*07:143', 'HLA-C*07:144', 'HLA-C*07:145',
'HLA-C*07:146', 'HLA-C*07:147',
'HLA-C*07:148', 'HLA-C*07:149', 'HLA-C*08:01', 'HLA-C*08:02', 'HLA-C*08:03', 'HLA-C*08:04', 'HLA-C*08:05',
'HLA-C*08:06', 'HLA-C*08:07', 'HLA-C*08:08',
'HLA-C*08:09', 'HLA-C*08:10', 'HLA-C*08:11', 'HLA-C*08:12', 'HLA-C*08:13', 'HLA-C*08:14', 'HLA-C*08:15',
'HLA-C*08:16', 'HLA-C*08:17', 'HLA-C*08:18',
'HLA-C*08:19', 'HLA-C*08:20', 'HLA-C*08:21', 'HLA-C*08:22', 'HLA-C*08:23', 'HLA-C*08:24', 'HLA-C*08:25',
'HLA-C*08:27', 'HLA-C*08:28', 'HLA-C*08:29',
'HLA-C*08:30', 'HLA-C*08:31', 'HLA-C*08:32', 'HLA-C*08:33', 'HLA-C*08:34', 'HLA-C*08:35', 'HLA-C*12:02',
'HLA-C*12:03', 'HLA-C*12:04', 'HLA-C*12:05',
'HLA-C*12:06', 'HLA-C*12:07', 'HLA-C*12:08', 'HLA-C*12:09', 'HLA-C*12:10', 'HLA-C*12:11', 'HLA-C*12:12',
'HLA-C*12:13', 'HLA-C*12:14', 'HLA-C*12:15',
'HLA-C*12:16', 'HLA-C*12:17', 'HLA-C*12:18', 'HLA-C*12:19', 'HLA-C*12:20', 'HLA-C*12:21', 'HLA-C*12:22',
'HLA-C*12:23', 'HLA-C*12:24', 'HLA-C*12:25',
'HLA-C*12:26', 'HLA-C*12:27', 'HLA-C*12:28', 'HLA-C*12:29', 'HLA-C*12:30', 'HLA-C*12:31', 'HLA-C*12:32',
'HLA-C*12:33', 'HLA-C*12:34', 'HLA-C*12:35',
'HLA-C*12:36', 'HLA-C*12:37', 'HLA-C*12:38', 'HLA-C*12:40', 'HLA-C*12:41', 'HLA-C*12:43', 'HLA-C*12:44',
'HLA-C*14:02', 'HLA-C*14:03', 'HLA-C*14:04',
'HLA-C*14:05', 'HLA-C*14:06', 'HLA-C*14:08', 'HLA-C*14:09', 'HLA-C*14:10', 'HLA-C*14:11', 'HLA-C*14:12',
'HLA-C*14:13', 'HLA-C*14:14', 'HLA-C*14:15',
'HLA-C*14:16', 'HLA-C*14:17', 'HLA-C*14:18', 'HLA-C*14:19', 'HLA-C*14:20', 'HLA-C*15:02', 'HLA-C*15:03',
'HLA-C*15:04', 'HLA-C*15:05', 'HLA-C*15:06',
'HLA-C*15:07', 'HLA-C*15:08', 'HLA-C*15:09', 'HLA-C*15:10', 'HLA-C*15:11', 'HLA-C*15:12', 'HLA-C*15:13',
'HLA-C*15:15', 'HLA-C*15:16', 'HLA-C*15:17',
'HLA-C*15:18', 'HLA-C*15:19', 'HLA-C*15:20', 'HLA-C*15:21', 'HLA-C*15:22', 'HLA-C*15:23', 'HLA-C*15:24',
'HLA-C*15:25', 'HLA-C*15:26', 'HLA-C*15:27',
'HLA-C*15:28', 'HLA-C*15:29', 'HLA-C*15:30', 'HLA-C*15:31', 'HLA-C*15:33', 'HLA-C*15:34', 'HLA-C*15:35',
'HLA-C*16:01', 'HLA-C*16:02', 'HLA-C*16:04',
'HLA-C*16:06', 'HLA-C*16:07', 'HLA-C*16:08', 'HLA-C*16:09', 'HLA-C*16:10', 'HLA-C*16:11', 'HLA-C*16:12',
'HLA-C*16:13', 'HLA-C*16:14', 'HLA-C*16:15',
'HLA-C*16:17', 'HLA-C*16:18', 'HLA-C*16:19', 'HLA-C*16:20', 'HLA-C*16:21', 'HLA-C*16:22', 'HLA-C*16:23',
'HLA-C*16:24', 'HLA-C*16:25', 'HLA-C*16:26',
'HLA-C*17:01', 'HLA-C*17:02', 'HLA-C*17:03', 'HLA-C*17:04', 'HLA-C*17:05', 'HLA-C*17:06', 'HLA-C*17:07',
'HLA-C*18:01', 'HLA-C*18:02', 'HLA-C*18:03',
'HLA-G*01:01', 'HLA-G*01:02', 'HLA-G*01:03', 'HLA-G*01:04', 'HLA-G*01:06', 'HLA-G*01:07', 'HLA-G*01:08',
'HLA-G*01:09', 'HLA-E*01:01',
'H2-Db', 'H2-Dd', 'H2-Kb', 'H2-Kd', 'H2-Kk', 'H2-Ld'])
__version = "1.1"
@property
def version(self):
"""The version of the predictor"""
return self.__version
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
@property
def supportedAlleles(self):
"""
A list of supported :class:`~epytope.Core.Allele.Allele`
"""
return self.__supported_alleles
@property
def name(self):
"""The name of the predictor"""
return self.__name
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
else:
return "HLA-%s%s:%s" % (allele.locus, allele.supertype, allele.subtype)
def convert_alleles(self, alleles):
"""
Converts :class:`~epytope.Core.Allele.Allele` into the internal :class:`~epytope.Core.Allele.Allele` representation
of the predictor and returns a string representation
:param alleles: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: Returns a string representation of the input :class:`~epytope.Core.Allele.Allele`
:rtype: list(str)
"""
return [self._represent(a) for a in alleles]
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
with open(file, "r") as f:
for row in f:
if row[0] in ["#", "-"] or row.strip() == "" or "pos" in row:
continue
else:
s = row.split()
result[s[1].replace("*", "")][s[2]] = float(s[4])
return result
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`elf.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: str
"""
return None
def prepare_input(self, input, file):
"""
Prepares input for external tools and writes them to file in the specific format
No return value!
:param: list(str) input: The :class:`~epytope.Core.Peptide.Peptide` sequences to write into _file
:param File file: File-handler to input file for external tool
"""
file.write("\n".join(input))
class NetCTLpan_1_1(AExternalEpitopePrediction):
"""
Interface for NetCTLpan 1.1.
.. note::
NetCTLpan - Pan-specific MHC class I epitope predictions Stranzl T., Larsen M. V., Lundegaard C., Nielsen M.
Immunogenetics. 2010 Apr 9. [Epub ahead of print]
"""
__name = "netctlpan"
__command = "netCTLpan -f {peptides} -a {alleles} {options} > {out}"
__supported_length = frozenset([8, 9, 10, 11])
__alleles = frozenset(
['HLA-A*01:01', 'HLA-A*01:02', 'HLA-A*01:03', 'HLA-A*01:06', 'HLA-A*01:07', 'HLA-A*01:08', 'HLA-A*01:09', 'HLA-A*01:10', 'HLA-A*01:12',
'HLA-A*01:13', 'HLA-A*01:14', 'HLA-A*01:17', 'HLA-A*01:19', 'HLA-A*01:20', 'HLA-A*01:21', 'HLA-A*01:23', 'HLA-A*01:24', 'HLA-A*01:25',
'HLA-A*01:26', 'HLA-A*01:28', 'HLA-A*01:29', 'HLA-A*01:30', 'HLA-A*01:32', 'HLA-A*01:33', 'HLA-A*01:35', 'HLA-A*01:36', 'HLA-A*01:37',
'HLA-A*01:38', 'HLA-A*01:39', 'HLA-A*01:40', 'HLA-A*01:41', 'HLA-A*01:42', 'HLA-A*01:43', 'HLA-A*01:44', 'HLA-A*01:45', 'HLA-A*01:46',
'HLA-A*01:47', 'HLA-A*01:48', 'HLA-A*01:49', 'HLA-A*01:50', 'HLA-A*01:51', 'HLA-A*01:54', 'HLA-A*01:55', 'HLA-A*01:58', 'HLA-A*01:59',
'HLA-A*01:60', 'HLA-A*01:61', 'HLA-A*01:62', 'HLA-A*01:63', 'HLA-A*01:64', 'HLA-A*01:65', 'HLA-A*01:66', 'HLA-A*02:01', 'HLA-A*02:02',
'HLA-A*02:03', 'HLA-A*02:04', 'HLA-A*02:05', 'HLA-A*02:06', 'HLA-A*02:07', 'HLA-A*02:08', 'HLA-A*02:09', 'HLA-A*02:10', 'HLA-A*02:101',
'HLA-A*02:102', 'HLA-A*02:103', 'HLA-A*02:104', 'HLA-A*02:105', 'HLA-A*02:106', 'HLA-A*02:107', 'HLA-A*02:108', 'HLA-A*02:109',
'HLA-A*02:11', 'HLA-A*02:110', 'HLA-A*02:111', 'HLA-A*02:112', 'HLA-A*02:114', 'HLA-A*02:115', 'HLA-A*02:116', 'HLA-A*02:117',
'HLA-A*02:118', 'HLA-A*02:119', 'HLA-A*02:12', 'HLA-A*02:120', 'HLA-A*02:121', 'HLA-A*02:122', 'HLA-A*02:123', 'HLA-A*02:124',
'HLA-A*02:126', 'HLA-A*02:127', 'HLA-A*02:128', 'HLA-A*02:129', 'HLA-A*02:13', 'HLA-A*02:130', 'HLA-A*02:131', 'HLA-A*02:132',
'HLA-A*02:133', 'HLA-A*02:134', 'HLA-A*02:135', 'HLA-A*02:136', 'HLA-A*02:137', 'HLA-A*02:138', 'HLA-A*02:139', 'HLA-A*02:14',
'HLA-A*02:140', 'HLA-A*02:141', 'HLA-A*02:142', 'HLA-A*02:143', 'HLA-A*02:144', 'HLA-A*02:145', 'HLA-A*02:146', 'HLA-A*02:147',
'HLA-A*02:148', 'HLA-A*02:149', 'HLA-A*02:150', 'HLA-A*02:151', 'HLA-A*02:152', 'HLA-A*02:153', 'HLA-A*02:154', 'HLA-A*02:155',
'HLA-A*02:156', 'HLA-A*02:157', 'HLA-A*02:158', 'HLA-A*02:159', 'HLA-A*02:16', 'HLA-A*02:160', 'HLA-A*02:161', 'HLA-A*02:162',
'HLA-A*02:163', 'HLA-A*02:164', 'HLA-A*02:165', 'HLA-A*02:166', 'HLA-A*02:167', 'HLA-A*02:168', 'HLA-A*02:169', 'HLA-A*02:17',
'HLA-A*02:170', 'HLA-A*02:171', 'HLA-A*02:172', 'HLA-A*02:173', 'HLA-A*02:174', 'HLA-A*02:175', 'HLA-A*02:176', 'HLA-A*02:177',
'HLA-A*02:178', 'HLA-A*02:179', 'HLA-A*02:18', 'HLA-A*02:180', 'HLA-A*02:181', 'HLA-A*02:182', 'HLA-A*02:183', 'HLA-A*02:184',
'HLA-A*02:185', 'HLA-A*02:186', 'HLA-A*02:187', 'HLA-A*02:188', 'HLA-A*02:189', 'HLA-A*02:19', 'HLA-A*02:190', 'HLA-A*02:191',
'HLA-A*02:192', 'HLA-A*02:193', 'HLA-A*02:194', 'HLA-A*02:195', 'HLA-A*02:196', 'HLA-A*02:197', 'HLA-A*02:198', 'HLA-A*02:199',
'HLA-A*02:20', 'HLA-A*02:200', 'HLA-A*02:201', 'HLA-A*02:202', 'HLA-A*02:203', 'HLA-A*02:204', 'HLA-A*02:205', 'HLA-A*02:206',
'HLA-A*02:207', 'HLA-A*02:208', 'HLA-A*02:209', 'HLA-A*02:21', 'HLA-A*02:210', 'HLA-A*02:211', 'HLA-A*02:212', 'HLA-A*02:213',
'HLA-A*02:214', 'HLA-A*02:215', 'HLA-A*02:216', 'HLA-A*02:217', 'HLA-A*02:218', 'HLA-A*02:219', 'HLA-A*02:22', 'HLA-A*02:220',
'HLA-A*02:221', 'HLA-A*02:224', 'HLA-A*02:228', 'HLA-A*02:229', 'HLA-A*02:230', 'HLA-A*02:231', 'HLA-A*02:232', 'HLA-A*02:233',
'HLA-A*02:234', 'HLA-A*02:235', 'HLA-A*02:236', 'HLA-A*02:237', 'HLA-A*02:238', 'HLA-A*02:239', 'HLA-A*02:24', 'HLA-A*02:240',
'HLA-A*02:241', 'HLA-A*02:242', 'HLA-A*02:243', 'HLA-A*02:244', 'HLA-A*02:245', 'HLA-A*02:246', 'HLA-A*02:247', 'HLA-A*02:248',
'HLA-A*02:249', 'HLA-A*02:25', 'HLA-A*02:251', 'HLA-A*02:252', 'HLA-A*02:253', 'HLA-A*02:254', 'HLA-A*02:255', 'HLA-A*02:256',
'HLA-A*02:257', 'HLA-A*02:258', 'HLA-A*02:259', 'HLA-A*02:26', 'HLA-A*02:260', 'HLA-A*02:261', 'HLA-A*02:262', 'HLA-A*02:263',
'HLA-A*02:264', 'HLA-A*02:265', 'HLA-A*02:266', 'HLA-A*02:27', 'HLA-A*02:28', 'HLA-A*02:29', 'HLA-A*02:30', 'HLA-A*02:31', 'HLA-A*02:33',
'HLA-A*02:34', 'HLA-A*02:35', 'HLA-A*02:36', 'HLA-A*02:37', 'HLA-A*02:38', 'HLA-A*02:39', 'HLA-A*02:40', 'HLA-A*02:41', 'HLA-A*02:42',
'HLA-A*02:44', 'HLA-A*02:45', 'HLA-A*02:46', 'HLA-A*02:47', 'HLA-A*02:48', 'HLA-A*02:49', 'HLA-A*02:50', 'HLA-A*02:51', 'HLA-A*02:52',
'HLA-A*02:54', 'HLA-A*02:55', 'HLA-A*02:56', 'HLA-A*02:57', 'HLA-A*02:58', 'HLA-A*02:59', 'HLA-A*02:60', 'HLA-A*02:61', 'HLA-A*02:62',
'HLA-A*02:63', 'HLA-A*02:64', 'HLA-A*02:65', 'HLA-A*02:66', 'HLA-A*02:67', 'HLA-A*02:68', 'HLA-A*02:69', 'HLA-A*02:70', 'HLA-A*02:71',
'HLA-A*02:72', 'HLA-A*02:73', 'HLA-A*02:74', 'HLA-A*02:75', 'HLA-A*02:76', 'HLA-A*02:77', 'HLA-A*02:78', 'HLA-A*02:79', 'HLA-A*02:80',
'HLA-A*02:81', 'HLA-A*02:84', 'HLA-A*02:85', 'HLA-A*02:86', 'HLA-A*02:87', 'HLA-A*02:89', 'HLA-A*02:90', 'HLA-A*02:91', 'HLA-A*02:92',
'HLA-A*02:93', 'HLA-A*02:95', 'HLA-A*02:96', 'HLA-A*02:97', 'HLA-A*02:99', 'HLA-A*03:01', 'HLA-A*03:02', 'HLA-A*03:04', 'HLA-A*03:05',
'HLA-A*03:06', 'HLA-A*03:07', 'HLA-A*03:08', 'HLA-A*03:09', 'HLA-A*03:10', 'HLA-A*03:12', 'HLA-A*03:13', 'HLA-A*03:14', 'HLA-A*03:15',
'HLA-A*03:16', 'HLA-A*03:17', 'HLA-A*03:18', 'HLA-A*03:19', 'HLA-A*03:20', 'HLA-A*03:22', 'HLA-A*03:23', 'HLA-A*03:24', 'HLA-A*03:25',
'HLA-A*03:26', 'HLA-A*03:27', 'HLA-A*03:28', 'HLA-A*03:29', 'HLA-A*03:30', 'HLA-A*03:31', 'HLA-A*03:32', 'HLA-A*03:33', 'HLA-A*03:34',
'HLA-A*03:35', 'HLA-A*03:37', 'HLA-A*03:38', 'HLA-A*03:39', 'HLA-A*03:40', 'HLA-A*03:41', 'HLA-A*03:42', 'HLA-A*03:43', 'HLA-A*03:44',
'HLA-A*03:45', 'HLA-A*03:46', 'HLA-A*03:47', 'HLA-A*03:48', 'HLA-A*03:49', 'HLA-A*03:50', 'HLA-A*03:51', 'HLA-A*03:52', 'HLA-A*03:53',
'HLA-A*03:54', 'HLA-A*03:55', 'HLA-A*03:56', 'HLA-A*03:57', 'HLA-A*03:58', 'HLA-A*03:59', 'HLA-A*03:60', 'HLA-A*03:61', 'HLA-A*03:62',
'HLA-A*03:63', 'HLA-A*03:64', 'HLA-A*03:65', 'HLA-A*03:66', 'HLA-A*03:67', 'HLA-A*03:70', 'HLA-A*03:71', 'HLA-A*03:72', 'HLA-A*03:73',
'HLA-A*03:74', 'HLA-A*03:75', 'HLA-A*03:76', 'HLA-A*03:77', 'HLA-A*03:78', 'HLA-A*03:79', 'HLA-A*03:80', 'HLA-A*03:81', 'HLA-A*03:82',
'HLA-A*11:01', 'HLA-A*11:02', 'HLA-A*11:03', 'HLA-A*11:04', 'HLA-A*11:05', 'HLA-A*11:06', 'HLA-A*11:07', 'HLA-A*11:08', 'HLA-A*11:09',
'HLA-A*11:10', 'HLA-A*11:11', 'HLA-A*11:12', 'HLA-A*11:13', 'HLA-A*11:14', 'HLA-A*11:15', 'HLA-A*11:16', 'HLA-A*11:17', 'HLA-A*11:18',
'HLA-A*11:19', 'HLA-A*11:20', 'HLA-A*11:22', 'HLA-A*11:23', 'HLA-A*11:24', 'HLA-A*11:25', 'HLA-A*11:26', 'HLA-A*11:27', 'HLA-A*11:29',
'HLA-A*11:30', 'HLA-A*11:31', 'HLA-A*11:32', 'HLA-A*11:33', 'HLA-A*11:34', 'HLA-A*11:35', 'HLA-A*11:36', 'HLA-A*11:37', 'HLA-A*11:38',
'HLA-A*11:39', 'HLA-A*11:40', 'HLA-A*11:41', 'HLA-A*11:42', 'HLA-A*11:43', 'HLA-A*11:44', 'HLA-A*11:45', 'HLA-A*11:46', 'HLA-A*11:47',
'HLA-A*11:48', 'HLA-A*11:49', 'HLA-A*11:51', 'HLA-A*11:53', 'HLA-A*11:54', 'HLA-A*11:55', 'HLA-A*11:56', 'HLA-A*11:57', 'HLA-A*11:58',
'HLA-A*11:59', 'HLA-A*11:60', 'HLA-A*11:61', 'HLA-A*11:62', 'HLA-A*11:63', 'HLA-A*11:64', 'HLA-A*23:01', 'HLA-A*23:02', 'HLA-A*23:03',
'HLA-A*23:04', 'HLA-A*23:05', 'HLA-A*23:06', 'HLA-A*23:09', 'HLA-A*23:10', 'HLA-A*23:12', 'HLA-A*23:13', 'HLA-A*23:14', 'HLA-A*23:15',
'HLA-A*23:16', 'HLA-A*23:17', 'HLA-A*23:18', 'HLA-A*23:20', 'HLA-A*23:21', 'HLA-A*23:22', 'HLA-A*23:23', 'HLA-A*23:24', 'HLA-A*23:25',
'HLA-A*23:26', 'HLA-A*24:02', 'HLA-A*24:03', 'HLA-A*24:04', 'HLA-A*24:05', 'HLA-A*24:06', 'HLA-A*24:07', 'HLA-A*24:08', 'HLA-A*24:10',
'HLA-A*24:100', 'HLA-A*24:101', 'HLA-A*24:102', 'HLA-A*24:103', 'HLA-A*24:104', 'HLA-A*24:105', 'HLA-A*24:106', 'HLA-A*24:107',
'HLA-A*24:108', 'HLA-A*24:109', 'HLA-A*24:110', 'HLA-A*24:111', 'HLA-A*24:112', 'HLA-A*24:113', 'HLA-A*24:114', 'HLA-A*24:115',
'HLA-A*24:116', 'HLA-A*24:117', 'HLA-A*24:118', 'HLA-A*24:119', 'HLA-A*24:120', 'HLA-A*24:121', 'HLA-A*24:122', 'HLA-A*24:123',
'HLA-A*24:124', 'HLA-A*24:125', 'HLA-A*24:126', 'HLA-A*24:127', 'HLA-A*24:128', 'HLA-A*24:129', 'HLA-A*24:13', 'HLA-A*24:130',
'HLA-A*24:131', 'HLA-A*24:133', 'HLA-A*24:134', 'HLA-A*24:135', 'HLA-A*24:136', 'HLA-A*24:137', 'HLA-A*24:138', 'HLA-A*24:139',
'HLA-A*24:14', 'HLA-A*24:140', 'HLA-A*24:141', 'HLA-A*24:142', 'HLA-A*24:143', 'HLA-A*24:144', 'HLA-A*24:15', 'HLA-A*24:17', 'HLA-A*24:18',
'HLA-A*24:19', 'HLA-A*24:20', 'HLA-A*24:21', 'HLA-A*24:22', 'HLA-A*24:23', 'HLA-A*24:24', 'HLA-A*24:25', 'HLA-A*24:26', 'HLA-A*24:27',
'HLA-A*24:28', 'HLA-A*24:29', 'HLA-A*24:30', 'HLA-A*24:31', 'HLA-A*24:32', 'HLA-A*24:33', 'HLA-A*24:34', 'HLA-A*24:35', 'HLA-A*24:37',
'HLA-A*24:38', 'HLA-A*24:39', 'HLA-A*24:41', 'HLA-A*24:42', 'HLA-A*24:43', 'HLA-A*24:44', 'HLA-A*24:46', 'HLA-A*24:47', 'HLA-A*24:49',
'HLA-A*24:50', 'HLA-A*24:51', 'HLA-A*24:52', 'HLA-A*24:53', 'HLA-A*24:54', 'HLA-A*24:55', 'HLA-A*24:56', 'HLA-A*24:57', 'HLA-A*24:58',
'HLA-A*24:59', 'HLA-A*24:61', 'HLA-A*24:62', 'HLA-A*24:63', 'HLA-A*24:64', 'HLA-A*24:66', 'HLA-A*24:67', 'HLA-A*24:68', 'HLA-A*24:69',
'HLA-A*24:70', 'HLA-A*24:71', 'HLA-A*24:72', 'HLA-A*24:73', 'HLA-A*24:74', 'HLA-A*24:75', 'HLA-A*24:76', 'HLA-A*24:77', 'HLA-A*24:78',
'HLA-A*24:79', 'HLA-A*24:80', 'HLA-A*24:81', 'HLA-A*24:82', 'HLA-A*24:85', 'HLA-A*24:87', 'HLA-A*24:88', 'HLA-A*24:89', 'HLA-A*24:91',
'HLA-A*24:92', 'HLA-A*24:93', 'HLA-A*24:94', 'HLA-A*24:95', 'HLA-A*24:96', 'HLA-A*24:97', 'HLA-A*24:98', 'HLA-A*24:99', 'HLA-A*25:01',
'HLA-A*25:02', 'HLA-A*25:03', 'HLA-A*25:04', 'HLA-A*25:05', 'HLA-A*25:06', 'HLA-A*25:07', 'HLA-A*25:08', 'HLA-A*25:09', 'HLA-A*25:10',
'HLA-A*25:11', 'HLA-A*25:13', 'HLA-A*26:01', 'HLA-A*26:02', 'HLA-A*26:03', 'HLA-A*26:04', 'HLA-A*26:05', 'HLA-A*26:06', 'HLA-A*26:07',
'HLA-A*26:08', 'HLA-A*26:09', 'HLA-A*26:10', 'HLA-A*26:12', 'HLA-A*26:13', 'HLA-A*26:14', 'HLA-A*26:15', 'HLA-A*26:16', 'HLA-A*26:17',
'HLA-A*26:18', 'HLA-A*26:19', 'HLA-A*26:20', 'HLA-A*26:21', 'HLA-A*26:22', 'HLA-A*26:23', 'HLA-A*26:24', 'HLA-A*26:26', 'HLA-A*26:27',
'HLA-A*26:28', 'HLA-A*26:29', 'HLA-A*26:30', 'HLA-A*26:31', 'HLA-A*26:32', 'HLA-A*26:33', 'HLA-A*26:34', 'HLA-A*26:35', 'HLA-A*26:36',
'HLA-A*26:37', 'HLA-A*26:38', 'HLA-A*26:39', 'HLA-A*26:40', 'HLA-A*26:41', 'HLA-A*26:42', 'HLA-A*26:43', 'HLA-A*26:45', 'HLA-A*26:46',
'HLA-A*26:47', 'HLA-A*26:48', 'HLA-A*26:49', 'HLA-A*26:50', 'HLA-A*29:01', 'HLA-A*29:02', 'HLA-A*29:03', 'HLA-A*29:04', 'HLA-A*29:05',
'HLA-A*29:06', 'HLA-A*29:07', 'HLA-A*29:09', 'HLA-A*29:10', 'HLA-A*29:11', 'HLA-A*29:12', 'HLA-A*29:13', 'HLA-A*29:14', 'HLA-A*29:15',
'HLA-A*29:16', 'HLA-A*29:17', 'HLA-A*29:18', 'HLA-A*29:19', 'HLA-A*29:20', 'HLA-A*29:21', 'HLA-A*29:22', 'HLA-A*30:01', 'HLA-A*30:02',
'HLA-A*30:03', 'HLA-A*30:04', 'HLA-A*30:06', 'HLA-A*30:07', 'HLA-A*30:08', 'HLA-A*30:09', 'HLA-A*30:10', 'HLA-A*30:11', 'HLA-A*30:12',
'HLA-A*30:13', 'HLA-A*30:15', 'HLA-A*30:16', 'HLA-A*30:17', 'HLA-A*30:18', 'HLA-A*30:19', 'HLA-A*30:20', 'HLA-A*30:22', 'HLA-A*30:23',
'HLA-A*30:24', 'HLA-A*30:25', 'HLA-A*30:26', 'HLA-A*30:28', 'HLA-A*30:29', 'HLA-A*30:30', 'HLA-A*30:31', 'HLA-A*30:32', 'HLA-A*30:33',
'HLA-A*30:34', 'HLA-A*30:35', 'HLA-A*30:36', 'HLA-A*30:37', 'HLA-A*30:38', 'HLA-A*30:39', 'HLA-A*30:40', 'HLA-A*30:41', 'HLA-A*31:01',
'HLA-A*31:02', 'HLA-A*31:03', 'HLA-A*31:04', 'HLA-A*31:05', 'HLA-A*31:06', 'HLA-A*31:07', 'HLA-A*31:08', 'HLA-A*31:09', 'HLA-A*31:10',
'HLA-A*31:11', 'HLA-A*31:12', 'HLA-A*31:13', 'HLA-A*31:15', 'HLA-A*31:16', 'HLA-A*31:17', 'HLA-A*31:18', 'HLA-A*31:19', 'HLA-A*31:20',
'HLA-A*31:21', 'HLA-A*31:22', 'HLA-A*31:23', 'HLA-A*31:24', 'HLA-A*31:25', 'HLA-A*31:26', 'HLA-A*31:27', 'HLA-A*31:28', 'HLA-A*31:29',
'HLA-A*31:30', 'HLA-A*31:31', 'HLA-A*31:32', 'HLA-A*31:33', 'HLA-A*31:34', 'HLA-A*31:35', 'HLA-A*31:36', 'HLA-A*31:37', 'HLA-A*32:01',
'HLA-A*32:02', 'HLA-A*32:03', 'HLA-A*32:04', 'HLA-A*32:05', 'HLA-A*32:06', 'HLA-A*32:07', 'HLA-A*32:08', 'HLA-A*32:09', 'HLA-A*32:10',
'HLA-A*32:12', 'HLA-A*32:13', 'HLA-A*32:14', 'HLA-A*32:15', 'HLA-A*32:16', 'HLA-A*32:17', 'HLA-A*32:18', 'HLA-A*32:20', 'HLA-A*32:21',
'HLA-A*32:22', 'HLA-A*32:23', 'HLA-A*32:24', 'HLA-A*32:25', 'HLA-A*33:01', 'HLA-A*33:03', 'HLA-A*33:04', 'HLA-A*33:05', 'HLA-A*33:06',
'HLA-A*33:07', 'HLA-A*33:08', 'HLA-A*33:09', 'HLA-A*33:10', 'HLA-A*33:11', 'HLA-A*33:12', 'HLA-A*33:13', 'HLA-A*33:14', 'HLA-A*33:15',
'HLA-A*33:16', 'HLA-A*33:17', 'HLA-A*33:18', 'HLA-A*33:19', 'HLA-A*33:20', 'HLA-A*33:21', 'HLA-A*33:22', 'HLA-A*33:23', 'HLA-A*33:24',
'HLA-A*33:25', 'HLA-A*33:26', 'HLA-A*33:27', 'HLA-A*33:28', 'HLA-A*33:29', 'HLA-A*33:30', 'HLA-A*33:31', 'HLA-A*34:01', 'HLA-A*34:02',
'HLA-A*34:03', 'HLA-A*34:04', 'HLA-A*34:05', 'HLA-A*34:06', 'HLA-A*34:07', 'HLA-A*34:08', 'HLA-A*36:01', 'HLA-A*36:02', 'HLA-A*36:03',
'HLA-A*36:04', 'HLA-A*36:05', 'HLA-A*43:01', 'HLA-A*66:01', 'HLA-A*66:02', 'HLA-A*66:03', 'HLA-A*66:04', 'HLA-A*66:05', 'HLA-A*66:06',
'HLA-A*66:07', 'HLA-A*66:08', 'HLA-A*66:09', 'HLA-A*66:10', 'HLA-A*66:11', 'HLA-A*66:12', 'HLA-A*66:13', 'HLA-A*66:14', 'HLA-A*66:15',
'HLA-A*68:01', 'HLA-A*68:02', 'HLA-A*68:03', 'HLA-A*68:04', 'HLA-A*68:05', 'HLA-A*68:06', 'HLA-A*68:07', 'HLA-A*68:08', 'HLA-A*68:09',
'HLA-A*68:10', 'HLA-A*68:12', 'HLA-A*68:13', 'HLA-A*68:14', 'HLA-A*68:15', 'HLA-A*68:16', 'HLA-A*68:17', 'HLA-A*68:19', 'HLA-A*68:20',
'HLA-A*68:21', 'HLA-A*68:22', 'HLA-A*68:23', 'HLA-A*68:24', 'HLA-A*68:25', 'HLA-A*68:26', 'HLA-A*68:27', 'HLA-A*68:28', 'HLA-A*68:29',
'HLA-A*68:30', 'HLA-A*68:31', 'HLA-A*68:32', 'HLA-A*68:33', 'HLA-A*68:34', 'HLA-A*68:35', 'HLA-A*68:36', 'HLA-A*68:37', 'HLA-A*68:38',
'HLA-A*68:39', 'HLA-A*68:40', 'HLA-A*68:41', 'HLA-A*68:42', 'HLA-A*68:43', 'HLA-A*68:44', 'HLA-A*68:45', 'HLA-A*68:46', 'HLA-A*68:47',
'HLA-A*68:48', 'HLA-A*68:50', 'HLA-A*68:51', 'HLA-A*68:52', 'HLA-A*68:53', 'HLA-A*68:54', 'HLA-A*69:01', 'HLA-A*74:01', 'HLA-A*74:02',
'HLA-A*74:03', 'HLA-A*74:04', 'HLA-A*74:05', 'HLA-A*74:06', 'HLA-A*74:07', 'HLA-A*74:08', 'HLA-A*74:09', 'HLA-A*74:10', 'HLA-A*74:11',
'HLA-A*74:13', 'HLA-A*80:01', 'HLA-A*80:02', 'HLA-B*07:02', 'HLA-B*07:03', 'HLA-B*07:04', 'HLA-B*07:05', 'HLA-B*07:06', 'HLA-B*07:07',
'HLA-B*07:08', 'HLA-B*07:09', 'HLA-B*07:10', 'HLA-B*07:100', 'HLA-B*07:101', 'HLA-B*07:102', 'HLA-B*07:103', 'HLA-B*07:104',
'HLA-B*07:105', 'HLA-B*07:106', 'HLA-B*07:107', 'HLA-B*07:108', 'HLA-B*07:109', 'HLA-B*07:11', 'HLA-B*07:110', 'HLA-B*07:112',
'HLA-B*07:113', 'HLA-B*07:114', 'HLA-B*07:115', 'HLA-B*07:12', 'HLA-B*07:13', 'HLA-B*07:14', 'HLA-B*07:15', 'HLA-B*07:16', 'HLA-B*07:17',
'HLA-B*07:18', 'HLA-B*07:19', 'HLA-B*07:20', 'HLA-B*07:21', 'HLA-B*07:22', 'HLA-B*07:23', 'HLA-B*07:24', 'HLA-B*07:25', 'HLA-B*07:26',
'HLA-B*07:27', 'HLA-B*07:28', 'HLA-B*07:29', 'HLA-B*07:30', 'HLA-B*07:31', 'HLA-B*07:32', 'HLA-B*07:33', 'HLA-B*07:34', 'HLA-B*07:35',
'HLA-B*07:36', 'HLA-B*07:37', 'HLA-B*07:38', 'HLA-B*07:39', 'HLA-B*07:40', 'HLA-B*07:41', 'HLA-B*07:42', 'HLA-B*07:43', 'HLA-B*07:44',
'HLA-B*07:45', 'HLA-B*07:46', 'HLA-B*07:47', 'HLA-B*07:48', 'HLA-B*07:50', 'HLA-B*07:51', 'HLA-B*07:52', 'HLA-B*07:53', 'HLA-B*07:54',
'HLA-B*07:55', 'HLA-B*07:56', 'HLA-B*07:57', 'HLA-B*07:58', 'HLA-B*07:59', 'HLA-B*07:60', 'HLA-B*07:61', 'HLA-B*07:62', 'HLA-B*07:63',
'HLA-B*07:64', 'HLA-B*07:65', 'HLA-B*07:66', 'HLA-B*07:68', 'HLA-B*07:69', 'HLA-B*07:70', 'HLA-B*07:71', 'HLA-B*07:72', 'HLA-B*07:73',
'HLA-B*07:74', 'HLA-B*07:75', 'HLA-B*07:76', 'HLA-B*07:77', 'HLA-B*07:78', 'HLA-B*07:79', 'HLA-B*07:80', 'HLA-B*07:81', 'HLA-B*07:82',
'HLA-B*07:83', 'HLA-B*07:84', 'HLA-B*07:85', 'HLA-B*07:86', 'HLA-B*07:87', 'HLA-B*07:88', 'HLA-B*07:89', 'HLA-B*07:90', 'HLA-B*07:91',
'HLA-B*07:92', 'HLA-B*07:93', 'HLA-B*07:94', 'HLA-B*07:95', 'HLA-B*07:96', 'HLA-B*07:97', 'HLA-B*07:98', 'HLA-B*07:99', 'HLA-B*08:01',
'HLA-B*08:02', 'HLA-B*08:03', 'HLA-B*08:04', 'HLA-B*08:05', 'HLA-B*08:07', 'HLA-B*08:09', 'HLA-B*08:10', 'HLA-B*08:11', 'HLA-B*08:12',
'HLA-B*08:13', 'HLA-B*08:14', 'HLA-B*08:15', 'HLA-B*08:16', 'HLA-B*08:17', 'HLA-B*08:18', 'HLA-B*08:20', 'HLA-B*08:21', 'HLA-B*08:22',
'HLA-B*08:23', 'HLA-B*08:24', 'HLA-B*08:25', 'HLA-B*08:26', 'HLA-B*08:27', 'HLA-B*08:28', 'HLA-B*08:29', 'HLA-B*08:31', 'HLA-B*08:32',
'HLA-B*08:33', 'HLA-B*08:34', 'HLA-B*08:35', 'HLA-B*08:36', 'HLA-B*08:37', 'HLA-B*08:38', 'HLA-B*08:39', 'HLA-B*08:40', 'HLA-B*08:41',
'HLA-B*08:42', 'HLA-B*08:43', 'HLA-B*08:44', 'HLA-B*08:45', 'HLA-B*08:46', 'HLA-B*08:47', 'HLA-B*08:48', 'HLA-B*08:49', 'HLA-B*08:50',
'HLA-B*08:51', 'HLA-B*08:52', 'HLA-B*08:53', 'HLA-B*08:54', 'HLA-B*08:55', 'HLA-B*08:56', 'HLA-B*08:57', 'HLA-B*08:58', 'HLA-B*08:59',
'HLA-B*08:60', 'HLA-B*08:61', 'HLA-B*08:62', 'HLA-B*13:01', 'HLA-B*13:02', 'HLA-B*13:03', 'HLA-B*13:04', 'HLA-B*13:06', 'HLA-B*13:09',
'HLA-B*13:10', 'HLA-B*13:11', 'HLA-B*13:12', 'HLA-B*13:13', 'HLA-B*13:14', 'HLA-B*13:15', 'HLA-B*13:16', 'HLA-B*13:17', 'HLA-B*13:18',
'HLA-B*13:19', 'HLA-B*13:20', 'HLA-B*13:21', 'HLA-B*13:22', 'HLA-B*13:23', 'HLA-B*13:25', 'HLA-B*13:26', 'HLA-B*13:27', 'HLA-B*13:28',
'HLA-B*13:29', 'HLA-B*13:30', 'HLA-B*13:31', 'HLA-B*13:32', 'HLA-B*13:33', 'HLA-B*13:34', 'HLA-B*13:35', 'HLA-B*13:36', 'HLA-B*13:37',
'HLA-B*13:38', 'HLA-B*13:39', 'HLA-B*14:01', 'HLA-B*14:02', 'HLA-B*14:03', 'HLA-B*14:04', 'HLA-B*14:05', 'HLA-B*14:06', 'HLA-B*14:08',
'HLA-B*14:09', 'HLA-B*14:10', 'HLA-B*14:11', 'HLA-B*14:12', 'HLA-B*14:13', 'HLA-B*14:14', 'HLA-B*14:15', 'HLA-B*14:16', 'HLA-B*14:17',
'HLA-B*14:18', 'HLA-B*15:01', 'HLA-B*15:02', 'HLA-B*15:03', 'HLA-B*15:04', 'HLA-B*15:05', 'HLA-B*15:06', 'HLA-B*15:07', 'HLA-B*15:08',
'HLA-B*15:09', 'HLA-B*15:10', 'HLA-B*15:101', 'HLA-B*15:102', 'HLA-B*15:103', 'HLA-B*15:104', 'HLA-B*15:105', 'HLA-B*15:106',
'HLA-B*15:107', 'HLA-B*15:108', 'HLA-B*15:109', 'HLA-B*15:11', 'HLA-B*15:110', 'HLA-B*15:112', 'HLA-B*15:113', 'HLA-B*15:114',
'HLA-B*15:115', 'HLA-B*15:116', 'HLA-B*15:117', 'HLA-B*15:118', 'HLA-B*15:119', 'HLA-B*15:12', 'HLA-B*15:120', 'HLA-B*15:121',
'HLA-B*15:122', 'HLA-B*15:123', 'HLA-B*15:124', 'HLA-B*15:125', 'HLA-B*15:126', 'HLA-B*15:127', 'HLA-B*15:128', 'HLA-B*15:129',
'HLA-B*15:13', 'HLA-B*15:131', 'HLA-B*15:132', 'HLA-B*15:133', 'HLA-B*15:134', 'HLA-B*15:135', 'HLA-B*15:136', 'HLA-B*15:137',
'HLA-B*15:138', 'HLA-B*15:139', 'HLA-B*15:14', 'HLA-B*15:140', 'HLA-B*15:141', 'HLA-B*15:142', 'HLA-B*15:143', 'HLA-B*15:144',
'HLA-B*15:145', 'HLA-B*15:146', 'HLA-B*15:147', 'HLA-B*15:148', 'HLA-B*15:15', 'HLA-B*15:150', 'HLA-B*15:151', 'HLA-B*15:152',
'HLA-B*15:153', 'HLA-B*15:154', 'HLA-B*15:155', 'HLA-B*15:156', 'HLA-B*15:157', 'HLA-B*15:158', 'HLA-B*15:159', 'HLA-B*15:16',
'HLA-B*15:160', 'HLA-B*15:161', 'HLA-B*15:162', 'HLA-B*15:163', 'HLA-B*15:164', 'HLA-B*15:165', 'HLA-B*15:166', 'HLA-B*15:167',
'HLA-B*15:168', 'HLA-B*15:169', 'HLA-B*15:17', 'HLA-B*15:170', 'HLA-B*15:171', 'HLA-B*15:172', 'HLA-B*15:173', 'HLA-B*15:174',
'HLA-B*15:175', 'HLA-B*15:176', 'HLA-B*15:177', 'HLA-B*15:178', 'HLA-B*15:179', 'HLA-B*15:18', 'HLA-B*15:180', 'HLA-B*15:183',
'HLA-B*15:184', 'HLA-B*15:185', 'HLA-B*15:186', 'HLA-B*15:187', 'HLA-B*15:188', 'HLA-B*15:189', 'HLA-B*15:19', 'HLA-B*15:191',
'HLA-B*15:192', 'HLA-B*15:193', 'HLA-B*15:194', 'HLA-B*15:195', 'HLA-B*15:196', 'HLA-B*15:197', 'HLA-B*15:198', 'HLA-B*15:199',
'HLA-B*15:20', 'HLA-B*15:200', 'HLA-B*15:201', 'HLA-B*15:202', 'HLA-B*15:21', 'HLA-B*15:23', 'HLA-B*15:24', 'HLA-B*15:25', 'HLA-B*15:27',
'HLA-B*15:28', 'HLA-B*15:29', 'HLA-B*15:30', 'HLA-B*15:31', 'HLA-B*15:32', 'HLA-B*15:33', 'HLA-B*15:34', 'HLA-B*15:35', 'HLA-B*15:36',
'HLA-B*15:37', 'HLA-B*15:38', 'HLA-B*15:39', 'HLA-B*15:40', 'HLA-B*15:42', 'HLA-B*15:43', 'HLA-B*15:44', 'HLA-B*15:45', 'HLA-B*15:46',
'HLA-B*15:47', 'HLA-B*15:48', 'HLA-B*15:49', 'HLA-B*15:50', 'HLA-B*15:51', 'HLA-B*15:52', 'HLA-B*15:53', 'HLA-B*15:54', 'HLA-B*15:55',
'HLA-B*15:56', 'HLA-B*15:57', 'HLA-B*15:58', 'HLA-B*15:60', 'HLA-B*15:61', 'HLA-B*15:62', 'HLA-B*15:63', 'HLA-B*15:64', 'HLA-B*15:65',
'HLA-B*15:66', 'HLA-B*15:67', 'HLA-B*15:68', 'HLA-B*15:69', 'HLA-B*15:70', 'HLA-B*15:71', 'HLA-B*15:72', 'HLA-B*15:73', 'HLA-B*15:74',
'HLA-B*15:75', 'HLA-B*15:76', 'HLA-B*15:77', 'HLA-B*15:78', 'HLA-B*15:80', 'HLA-B*15:81', 'HLA-B*15:82', 'HLA-B*15:83', 'HLA-B*15:84',
'HLA-B*15:85', 'HLA-B*15:86', 'HLA-B*15:87', 'HLA-B*15:88', 'HLA-B*15:89', 'HLA-B*15:90', 'HLA-B*15:91', 'HLA-B*15:92', 'HLA-B*15:93',
'HLA-B*15:95', 'HLA-B*15:96', 'HLA-B*15:97', 'HLA-B*15:98', 'HLA-B*15:99', 'HLA-B*18:01', 'HLA-B*18:02', 'HLA-B*18:03', 'HLA-B*18:04',
'HLA-B*18:05', 'HLA-B*18:06', 'HLA-B*18:07', 'HLA-B*18:08', 'HLA-B*18:09', 'HLA-B*18:10', 'HLA-B*18:11', 'HLA-B*18:12', 'HLA-B*18:13',
'HLA-B*18:14', 'HLA-B*18:15', 'HLA-B*18:18', 'HLA-B*18:19', 'HLA-B*18:20', 'HLA-B*18:21', 'HLA-B*18:22', 'HLA-B*18:24', 'HLA-B*18:25',
'HLA-B*18:26', 'HLA-B*18:27', 'HLA-B*18:28', 'HLA-B*18:29', 'HLA-B*18:30', 'HLA-B*18:31', 'HLA-B*18:32', 'HLA-B*18:33', 'HLA-B*18:34',
'HLA-B*18:35', 'HLA-B*18:36', 'HLA-B*18:37', 'HLA-B*18:38', 'HLA-B*18:39', 'HLA-B*18:40', 'HLA-B*18:41', 'HLA-B*18:42', 'HLA-B*18:43',
'HLA-B*18:44', 'HLA-B*18:45', 'HLA-B*18:46', 'HLA-B*18:47', 'HLA-B*18:48', 'HLA-B*18:49', 'HLA-B*18:50', 'HLA-B*27:01', 'HLA-B*27:02',
'HLA-B*27:03', 'HLA-B*27:04', 'HLA-B*27:05', 'HLA-B*27:06', 'HLA-B*27:07', 'HLA-B*27:08', 'HLA-B*27:09', 'HLA-B*27:10', 'HLA-B*27:11',
'HLA-B*27:12', 'HLA-B*27:13', 'HLA-B*27:14', 'HLA-B*27:15', 'HLA-B*27:16', 'HLA-B*27:17', 'HLA-B*27:18', 'HLA-B*27:19', 'HLA-B*27:20',
'HLA-B*27:21', 'HLA-B*27:23', 'HLA-B*27:24', 'HLA-B*27:25', 'HLA-B*27:26', 'HLA-B*27:27', 'HLA-B*27:28', 'HLA-B*27:29', 'HLA-B*27:30',
'HLA-B*27:31', 'HLA-B*27:32', 'HLA-B*27:33', 'HLA-B*27:34', 'HLA-B*27:35', 'HLA-B*27:36', 'HLA-B*27:37', 'HLA-B*27:38', 'HLA-B*27:39',
'HLA-B*27:40', 'HLA-B*27:41', 'HLA-B*27:42', 'HLA-B*27:43', 'HLA-B*27:44', 'HLA-B*27:45', 'HLA-B*27:46', 'HLA-B*27:47', 'HLA-B*27:48',
'HLA-B*27:49', 'HLA-B*27:50', 'HLA-B*27:51', 'HLA-B*27:52', 'HLA-B*27:53', 'HLA-B*27:54', 'HLA-B*27:55', 'HLA-B*27:56', 'HLA-B*27:57',
'HLA-B*27:58', 'HLA-B*27:60', 'HLA-B*27:61', 'HLA-B*27:62', 'HLA-B*27:63', 'HLA-B*27:67', 'HLA-B*27:68', 'HLA-B*27:69', 'HLA-B*35:01',
'HLA-B*35:02', 'HLA-B*35:03', 'HLA-B*35:04', 'HLA-B*35:05', 'HLA-B*35:06', 'HLA-B*35:07', 'HLA-B*35:08', 'HLA-B*35:09', 'HLA-B*35:10',
'HLA-B*35:100', 'HLA-B*35:101', 'HLA-B*35:102', 'HLA-B*35:103', 'HLA-B*35:104', 'HLA-B*35:105', 'HLA-B*35:106', 'HLA-B*35:107',
'HLA-B*35:108', 'HLA-B*35:109', 'HLA-B*35:11', 'HLA-B*35:110', 'HLA-B*35:111', 'HLA-B*35:112', 'HLA-B*35:113', 'HLA-B*35:114',
'HLA-B*35:115', 'HLA-B*35:116', 'HLA-B*35:117', 'HLA-B*35:118', 'HLA-B*35:119', 'HLA-B*35:12', 'HLA-B*35:120', 'HLA-B*35:121',
'HLA-B*35:122', 'HLA-B*35:123', 'HLA-B*35:124', 'HLA-B*35:125', 'HLA-B*35:126', 'HLA-B*35:127', 'HLA-B*35:128', 'HLA-B*35:13',
'HLA-B*35:131', 'HLA-B*35:132', 'HLA-B*35:133', 'HLA-B*35:135', 'HLA-B*35:136', 'HLA-B*35:137', 'HLA-B*35:138', 'HLA-B*35:139',
'HLA-B*35:14', 'HLA-B*35:140', 'HLA-B*35:141', 'HLA-B*35:142', 'HLA-B*35:143', 'HLA-B*35:144', 'HLA-B*35:15', 'HLA-B*35:16', 'HLA-B*35:17',
'HLA-B*35:18', 'HLA-B*35:19', 'HLA-B*35:20', 'HLA-B*35:21', 'HLA-B*35:22', 'HLA-B*35:23', 'HLA-B*35:24', 'HLA-B*35:25', 'HLA-B*35:26',
'HLA-B*35:27', 'HLA-B*35:28', 'HLA-B*35:29', 'HLA-B*35:30', 'HLA-B*35:31', 'HLA-B*35:32', 'HLA-B*35:33', 'HLA-B*35:34', 'HLA-B*35:35',
'HLA-B*35:36', 'HLA-B*35:37', 'HLA-B*35:38', 'HLA-B*35:39', 'HLA-B*35:41', 'HLA-B*35:42', 'HLA-B*35:43', 'HLA-B*35:44', 'HLA-B*35:45',
'HLA-B*35:46', 'HLA-B*35:47', 'HLA-B*35:48', 'HLA-B*35:49', 'HLA-B*35:50', 'HLA-B*35:51', 'HLA-B*35:52', 'HLA-B*35:54', 'HLA-B*35:55',
'HLA-B*35:56', 'HLA-B*35:57', 'HLA-B*35:58', 'HLA-B*35:59', 'HLA-B*35:60', 'HLA-B*35:61', 'HLA-B*35:62', 'HLA-B*35:63', 'HLA-B*35:64',
'HLA-B*35:66', 'HLA-B*35:67', 'HLA-B*35:68', 'HLA-B*35:69', 'HLA-B*35:70', 'HLA-B*35:71', 'HLA-B*35:72', 'HLA-B*35:74', 'HLA-B*35:75',
'HLA-B*35:76', 'HLA-B*35:77', 'HLA-B*35:78', 'HLA-B*35:79', 'HLA-B*35:80', 'HLA-B*35:81', 'HLA-B*35:82', 'HLA-B*35:83', 'HLA-B*35:84',
'HLA-B*35:85', 'HLA-B*35:86', 'HLA-B*35:87', 'HLA-B*35:88', 'HLA-B*35:89', 'HLA-B*35:90', 'HLA-B*35:91', 'HLA-B*35:92', 'HLA-B*35:93',
'HLA-B*35:94', 'HLA-B*35:95', 'HLA-B*35:96', 'HLA-B*35:97', 'HLA-B*35:98', 'HLA-B*35:99', 'HLA-B*37:01', 'HLA-B*37:02', 'HLA-B*37:04',
'HLA-B*37:05', 'HLA-B*37:06', 'HLA-B*37:07', 'HLA-B*37:08', 'HLA-B*37:09', 'HLA-B*37:10', 'HLA-B*37:11', 'HLA-B*37:12', 'HLA-B*37:13',
'HLA-B*37:14', 'HLA-B*37:15', 'HLA-B*37:17', 'HLA-B*37:18', 'HLA-B*37:19', 'HLA-B*37:20', 'HLA-B*37:21', 'HLA-B*37:22', 'HLA-B*37:23',
'HLA-B*38:01', 'HLA-B*38:02', 'HLA-B*38:03', 'HLA-B*38:04', 'HLA-B*38:05', 'HLA-B*38:06', 'HLA-B*38:07', 'HLA-B*38:08', 'HLA-B*38:09',
'HLA-B*38:10', 'HLA-B*38:11', 'HLA-B*38:12', 'HLA-B*38:13', 'HLA-B*38:14', 'HLA-B*38:15', 'HLA-B*38:16', 'HLA-B*38:17', 'HLA-B*38:18',
'HLA-B*38:19', 'HLA-B*38:20', 'HLA-B*38:21', 'HLA-B*38:22', 'HLA-B*38:23', 'HLA-B*39:01', 'HLA-B*39:02', 'HLA-B*39:03', 'HLA-B*39:04',
'HLA-B*39:05', 'HLA-B*39:06', 'HLA-B*39:07', 'HLA-B*39:08', 'HLA-B*39:09', 'HLA-B*39:10', 'HLA-B*39:11', 'HLA-B*39:12', 'HLA-B*39:13',
'HLA-B*39:14', 'HLA-B*39:15', 'HLA-B*39:16', 'HLA-B*39:17', 'HLA-B*39:18', 'HLA-B*39:19', 'HLA-B*39:20', 'HLA-B*39:22', 'HLA-B*39:23',
'HLA-B*39:24', 'HLA-B*39:26', 'HLA-B*39:27', 'HLA-B*39:28', 'HLA-B*39:29', 'HLA-B*39:30', 'HLA-B*39:31', 'HLA-B*39:32', 'HLA-B*39:33',
'HLA-B*39:34', 'HLA-B*39:35', 'HLA-B*39:36', 'HLA-B*39:37', 'HLA-B*39:39', 'HLA-B*39:41', 'HLA-B*39:42', 'HLA-B*39:43', 'HLA-B*39:44',
'HLA-B*39:45', 'HLA-B*39:46', 'HLA-B*39:47', 'HLA-B*39:48', 'HLA-B*39:49', 'HLA-B*39:50', 'HLA-B*39:51', 'HLA-B*39:52', 'HLA-B*39:53',
'HLA-B*39:54', 'HLA-B*39:55', 'HLA-B*39:56', 'HLA-B*39:57', 'HLA-B*39:58', 'HLA-B*39:59', 'HLA-B*39:60', 'HLA-B*40:01', 'HLA-B*40:02',
'HLA-B*40:03', 'HLA-B*40:04', 'HLA-B*40:05', 'HLA-B*40:06', 'HLA-B*40:07', 'HLA-B*40:08', 'HLA-B*40:09', 'HLA-B*40:10', 'HLA-B*40:100',
'HLA-B*40:101', 'HLA-B*40:102', 'HLA-B*40:103', 'HLA-B*40:104', 'HLA-B*40:105', 'HLA-B*40:106', 'HLA-B*40:107', 'HLA-B*40:108',
'HLA-B*40:109', 'HLA-B*40:11', 'HLA-B*40:110', 'HLA-B*40:111', 'HLA-B*40:112', 'HLA-B*40:113', 'HLA-B*40:114', 'HLA-B*40:115',
'HLA-B*40:116', 'HLA-B*40:117', 'HLA-B*40:119', 'HLA-B*40:12', 'HLA-B*40:120', 'HLA-B*40:121', 'HLA-B*40:122', 'HLA-B*40:123',
'HLA-B*40:124', 'HLA-B*40:125', 'HLA-B*40:126', 'HLA-B*40:127', 'HLA-B*40:128', 'HLA-B*40:129', 'HLA-B*40:13', 'HLA-B*40:130',
'HLA-B*40:131', 'HLA-B*40:132', 'HLA-B*40:134', 'HLA-B*40:135', 'HLA-B*40:136', 'HLA-B*40:137', 'HLA-B*40:138', 'HLA-B*40:139',
'HLA-B*40:14', 'HLA-B*40:140', 'HLA-B*40:141', 'HLA-B*40:143', 'HLA-B*40:145', 'HLA-B*40:146', 'HLA-B*40:147', 'HLA-B*40:15',
'HLA-B*40:16', 'HLA-B*40:18', 'HLA-B*40:19', 'HLA-B*40:20', 'HLA-B*40:21', 'HLA-B*40:23', 'HLA-B*40:24', 'HLA-B*40:25', 'HLA-B*40:26',
'HLA-B*40:27', 'HLA-B*40:28', 'HLA-B*40:29', 'HLA-B*40:30', 'HLA-B*40:31', 'HLA-B*40:32', 'HLA-B*40:33', 'HLA-B*40:34', 'HLA-B*40:35',
'HLA-B*40:36', 'HLA-B*40:37', 'HLA-B*40:38', 'HLA-B*40:39', 'HLA-B*40:40', 'HLA-B*40:42', 'HLA-B*40:43', 'HLA-B*40:44', 'HLA-B*40:45',
'HLA-B*40:46', 'HLA-B*40:47', 'HLA-B*40:48', 'HLA-B*40:49', 'HLA-B*40:50', 'HLA-B*40:51', 'HLA-B*40:52', 'HLA-B*40:53', 'HLA-B*40:54',
'HLA-B*40:55', 'HLA-B*40:56', 'HLA-B*40:57', 'HLA-B*40:58', 'HLA-B*40:59', 'HLA-B*40:60', 'HLA-B*40:61', 'HLA-B*40:62', 'HLA-B*40:63',
'HLA-B*40:64', 'HLA-B*40:65', 'HLA-B*40:66', 'HLA-B*40:67', 'HLA-B*40:68', 'HLA-B*40:69', 'HLA-B*40:70', 'HLA-B*40:71', 'HLA-B*40:72',
'HLA-B*40:73', 'HLA-B*40:74', 'HLA-B*40:75', 'HLA-B*40:76', 'HLA-B*40:77', 'HLA-B*40:78', 'HLA-B*40:79', 'HLA-B*40:80', 'HLA-B*40:81',
'HLA-B*40:82', 'HLA-B*40:83', 'HLA-B*40:84', 'HLA-B*40:85', 'HLA-B*40:86', 'HLA-B*40:87', 'HLA-B*40:88', 'HLA-B*40:89', 'HLA-B*40:90',
'HLA-B*40:91', 'HLA-B*40:92', 'HLA-B*40:93', 'HLA-B*40:94', 'HLA-B*40:95', 'HLA-B*40:96', 'HLA-B*40:97', 'HLA-B*40:98', 'HLA-B*40:99',
'HLA-B*41:01', 'HLA-B*41:02', 'HLA-B*41:03', 'HLA-B*41:04', 'HLA-B*41:05', 'HLA-B*41:06', 'HLA-B*41:07', 'HLA-B*41:08', 'HLA-B*41:09',
'HLA-B*41:10', 'HLA-B*41:11', 'HLA-B*41:12', 'HLA-B*42:01', 'HLA-B*42:02', 'HLA-B*42:04', 'HLA-B*42:05', 'HLA-B*42:06', 'HLA-B*42:07',
'HLA-B*42:08', 'HLA-B*42:09', 'HLA-B*42:10', 'HLA-B*42:11', 'HLA-B*42:12', 'HLA-B*42:13', 'HLA-B*42:14', 'HLA-B*44:02', 'HLA-B*44:03',
'HLA-B*44:04', 'HLA-B*44:05', 'HLA-B*44:06', 'HLA-B*44:07', 'HLA-B*44:08', 'HLA-B*44:09', 'HLA-B*44:10', 'HLA-B*44:100', 'HLA-B*44:101',
'HLA-B*44:102', 'HLA-B*44:103', 'HLA-B*44:104', 'HLA-B*44:105', 'HLA-B*44:106', 'HLA-B*44:107', 'HLA-B*44:109', 'HLA-B*44:11',
'HLA-B*44:110', 'HLA-B*44:12', 'HLA-B*44:13', 'HLA-B*44:14', 'HLA-B*44:15', 'HLA-B*44:16', 'HLA-B*44:17', 'HLA-B*44:18', 'HLA-B*44:20',
'HLA-B*44:21', 'HLA-B*44:22', 'HLA-B*44:24', 'HLA-B*44:25', 'HLA-B*44:26', 'HLA-B*44:27', 'HLA-B*44:28', 'HLA-B*44:29', 'HLA-B*44:30',
'HLA-B*44:31', 'HLA-B*44:32', 'HLA-B*44:33', 'HLA-B*44:34', 'HLA-B*44:35', 'HLA-B*44:36', 'HLA-B*44:37', 'HLA-B*44:38', 'HLA-B*44:39',
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'HLA-C*04:14', 'HLA-C*04:15', 'HLA-C*04:16', 'HLA-C*04:17', 'HLA-C*04:18', 'HLA-C*04:19', 'HLA-C*04:20', 'HLA-C*04:23', 'HLA-C*04:24',
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'HLA-C*04:34', 'HLA-C*04:35', 'HLA-C*04:36', 'HLA-C*04:37', 'HLA-C*04:38', 'HLA-C*04:39', 'HLA-C*04:40', 'HLA-C*04:41', 'HLA-C*04:42',
'HLA-C*04:43', 'HLA-C*04:44', 'HLA-C*04:45', 'HLA-C*04:46', 'HLA-C*04:47', 'HLA-C*04:48', 'HLA-C*04:49', 'HLA-C*04:50', 'HLA-C*04:51',
'HLA-C*04:52', 'HLA-C*04:53', 'HLA-C*04:54', 'HLA-C*04:55', 'HLA-C*04:56', 'HLA-C*04:57', 'HLA-C*04:58', 'HLA-C*04:60', 'HLA-C*04:61',
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'HLA-C*05:01', 'HLA-C*05:03', 'HLA-C*05:04', 'HLA-C*05:05', 'HLA-C*05:06', 'HLA-C*05:08', 'HLA-C*05:09', 'HLA-C*05:10', 'HLA-C*05:11',
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'HLA-C*05:30', 'HLA-C*05:31', 'HLA-C*05:32', 'HLA-C*05:33', 'HLA-C*05:34', 'HLA-C*05:35', 'HLA-C*05:36', 'HLA-C*05:37', 'HLA-C*05:38',
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'HLA-C*07:05', 'HLA-C*07:06', 'HLA-C*07:07', 'HLA-C*07:08', 'HLA-C*07:09', 'HLA-C*07:10', 'HLA-C*07:100', 'HLA-C*07:101', 'HLA-C*07:102',
'HLA-C*07:103', 'HLA-C*07:105', 'HLA-C*07:106', 'HLA-C*07:107', 'HLA-C*07:108', 'HLA-C*07:109', 'HLA-C*07:11', 'HLA-C*07:110',
'HLA-C*07:111', 'HLA-C*07:112', 'HLA-C*07:113', 'HLA-C*07:114', 'HLA-C*07:115', 'HLA-C*07:116', 'HLA-C*07:117', 'HLA-C*07:118',
'HLA-C*07:119', 'HLA-C*07:12', 'HLA-C*07:120', 'HLA-C*07:122', 'HLA-C*07:123', 'HLA-C*07:124', 'HLA-C*07:125', 'HLA-C*07:126',
'HLA-C*07:127', 'HLA-C*07:128', 'HLA-C*07:129', 'HLA-C*07:13', 'HLA-C*07:130', 'HLA-C*07:131', 'HLA-C*07:132', 'HLA-C*07:133',
'HLA-C*07:134', 'HLA-C*07:135', 'HLA-C*07:136', 'HLA-C*07:137', 'HLA-C*07:138', 'HLA-C*07:139', 'HLA-C*07:14', 'HLA-C*07:140',
'HLA-C*07:141', 'HLA-C*07:142', 'HLA-C*07:143', 'HLA-C*07:144', 'HLA-C*07:145', 'HLA-C*07:146', 'HLA-C*07:147', 'HLA-C*07:148',
'HLA-C*07:149', 'HLA-C*07:15', 'HLA-C*07:16', 'HLA-C*07:17', 'HLA-C*07:18', 'HLA-C*07:19', 'HLA-C*07:20', 'HLA-C*07:21', 'HLA-C*07:22',
'HLA-C*07:23', 'HLA-C*07:24', 'HLA-C*07:25', 'HLA-C*07:26', 'HLA-C*07:27', 'HLA-C*07:28', 'HLA-C*07:29', 'HLA-C*07:30', 'HLA-C*07:31',
'HLA-C*07:35', 'HLA-C*07:36', 'HLA-C*07:37', 'HLA-C*07:38', 'HLA-C*07:39', 'HLA-C*07:40', 'HLA-C*07:41', 'HLA-C*07:42', 'HLA-C*07:43',
'HLA-C*07:44', 'HLA-C*07:45', 'HLA-C*07:46', 'HLA-C*07:47', 'HLA-C*07:48', 'HLA-C*07:49', 'HLA-C*07:50', 'HLA-C*07:51', 'HLA-C*07:52',
'HLA-C*07:53', 'HLA-C*07:54', 'HLA-C*07:56', 'HLA-C*07:57', 'HLA-C*07:58', 'HLA-C*07:59', 'HLA-C*07:60', 'HLA-C*07:62', 'HLA-C*07:63',
'HLA-C*07:64', 'HLA-C*07:65', 'HLA-C*07:66', 'HLA-C*07:67', 'HLA-C*07:68', 'HLA-C*07:69', 'HLA-C*07:70', 'HLA-C*07:71', 'HLA-C*07:72',
'HLA-C*07:73', 'HLA-C*07:74', 'HLA-C*07:75', 'HLA-C*07:76', 'HLA-C*07:77', 'HLA-C*07:78', 'HLA-C*07:79', 'HLA-C*07:80', 'HLA-C*07:81',
'HLA-C*07:82', 'HLA-C*07:83', 'HLA-C*07:84', 'HLA-C*07:85', 'HLA-C*07:86', 'HLA-C*07:87', 'HLA-C*07:88', 'HLA-C*07:89', 'HLA-C*07:90',
'HLA-C*07:91', 'HLA-C*07:92', 'HLA-C*07:93', 'HLA-C*07:94', 'HLA-C*07:95', 'HLA-C*07:96', 'HLA-C*07:97', 'HLA-C*07:99', 'HLA-C*08:01',
'HLA-C*08:02', 'HLA-C*08:03', 'HLA-C*08:04', 'HLA-C*08:05', 'HLA-C*08:06', 'HLA-C*08:07', 'HLA-C*08:08', 'HLA-C*08:09', 'HLA-C*08:10',
'HLA-C*08:11', 'HLA-C*08:12', 'HLA-C*08:13', 'HLA-C*08:14', 'HLA-C*08:15', 'HLA-C*08:16', 'HLA-C*08:17', 'HLA-C*08:18', 'HLA-C*08:19',
'HLA-C*08:20', 'HLA-C*08:21', 'HLA-C*08:22', 'HLA-C*08:23', 'HLA-C*08:24', 'HLA-C*08:25', 'HLA-C*08:27', 'HLA-C*08:28', 'HLA-C*08:29',
'HLA-C*08:30', 'HLA-C*08:31', 'HLA-C*08:32', 'HLA-C*08:33', 'HLA-C*08:34', 'HLA-C*08:35', 'HLA-C*12:02', 'HLA-C*12:03', 'HLA-C*12:04',
'HLA-C*12:05', 'HLA-C*12:06', 'HLA-C*12:07', 'HLA-C*12:08', 'HLA-C*12:09', 'HLA-C*12:10', 'HLA-C*12:11', 'HLA-C*12:12', 'HLA-C*12:13',
'HLA-C*12:14', 'HLA-C*12:15', 'HLA-C*12:16', 'HLA-C*12:17', 'HLA-C*12:18', 'HLA-C*12:19', 'HLA-C*12:20', 'HLA-C*12:21', 'HLA-C*12:22',
'HLA-C*12:23', 'HLA-C*12:24', 'HLA-C*12:25', 'HLA-C*12:26', 'HLA-C*12:27', 'HLA-C*12:28', 'HLA-C*12:29', 'HLA-C*12:30', 'HLA-C*12:31',
'HLA-C*12:32', 'HLA-C*12:33', 'HLA-C*12:34', 'HLA-C*12:35', 'HLA-C*12:36', 'HLA-C*12:37', 'HLA-C*12:38', 'HLA-C*12:40', 'HLA-C*12:41',
'HLA-C*12:43', 'HLA-C*12:44', 'HLA-C*14:02', 'HLA-C*14:03', 'HLA-C*14:04', 'HLA-C*14:05', 'HLA-C*14:06', 'HLA-C*14:08', 'HLA-C*14:09',
'HLA-C*14:10', 'HLA-C*14:11', 'HLA-C*14:12', 'HLA-C*14:13', 'HLA-C*14:14', 'HLA-C*14:15', 'HLA-C*14:16', 'HLA-C*14:17', 'HLA-C*14:18',
'HLA-C*14:19', 'HLA-C*14:20', 'HLA-C*15:02', 'HLA-C*15:03', 'HLA-C*15:04', 'HLA-C*15:05', 'HLA-C*15:06', 'HLA-C*15:07', 'HLA-C*15:08',
'HLA-C*15:09', 'HLA-C*15:10', 'HLA-C*15:11', 'HLA-C*15:12', 'HLA-C*15:13', 'HLA-C*15:15', 'HLA-C*15:16', 'HLA-C*15:17', 'HLA-C*15:18',
'HLA-C*15:19', 'HLA-C*15:20', 'HLA-C*15:21', 'HLA-C*15:22', 'HLA-C*15:23', 'HLA-C*15:24', 'HLA-C*15:25', 'HLA-C*15:26', 'HLA-C*15:27',
'HLA-C*15:28', 'HLA-C*15:29', 'HLA-C*15:30', 'HLA-C*15:31', 'HLA-C*15:33', 'HLA-C*15:34', 'HLA-C*15:35', 'HLA-C*16:01', 'HLA-C*16:02',
'HLA-C*16:04', 'HLA-C*16:06', 'HLA-C*16:07', 'HLA-C*16:08', 'HLA-C*16:09', 'HLA-C*16:10', 'HLA-C*16:11', 'HLA-C*16:12', 'HLA-C*16:13',
'HLA-C*16:14', 'HLA-C*16:15', 'HLA-C*16:17', 'HLA-C*16:18', 'HLA-C*16:19', 'HLA-C*16:20', 'HLA-C*16:21', 'HLA-C*16:22', 'HLA-C*16:23',
'HLA-C*16:24', 'HLA-C*16:25', 'HLA-C*16:26', 'HLA-C*17:01', 'HLA-C*17:02', 'HLA-C*17:03', 'HLA-C*17:04', 'HLA-C*17:05', 'HLA-C*17:06',
'HLA-C*17:07', 'HLA-C*18:01', 'HLA-C*18:02', 'HLA-C*18:03', 'HLA-E*01:01', 'HLA-G*01:01', 'HLA-G*01:02', 'HLA-G*01:03', 'HLA-G*01:04',
'HLA-G*01:06', 'HLA-G*01:07', 'HLA-G*01:08', 'HLA-G*01:09',
'H2-Db', 'H2-Dd', 'H2-Kb', 'H2-Kd', 'H2-Kk', 'H2-Ld'])
__version = "1.1"
@property
def version(self):
"""The version of the predictor"""
return self.__version
def _represent(self, allele):
"""
Internal function transforming an allele object into its representative string
:param allele: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: str
"""
if isinstance(allele, MouseAllele):
return "H-2-%s%s%s" % (allele.locus, allele.supertype, allele.subtype)
else:
return "HLA-%s%s:%s" % (allele.locus, allele.supertype, allele.subtype)
def convert_alleles(self, alleles):
"""
Converts :class:`~epytope.Core.Allele.Allele` into the internal :class:`~epytope.Core.Allele.Allele` representation
of the predictor and returns a string representation
:param alleles: The :class:`~epytope.Core.Allele.Allele` for which the internal predictor representation is
needed
:type alleles: :class:`~epytope.Core.Allele.Allele`
:return: Returns a string representation of the input :class:`~epytope.Core.Allele.Allele`
:rtype: list(str)
"""
return [self._represent(a) for a in alleles]
@property
def supportedAlleles(self):
"""
A list of supported :class:`~epytope.Core.Allele.Allele`
"""
return self.__alleles
@property
def name(self):
"""The name of the predictor"""
return self.__name
@property
def command(self):
"""
Defines the commandline call for external tool
"""
return self.__command
@property
def supportedLength(self):
"""
A list of supported :class:`~epytope.Core.Peptide.Peptide` lengths
"""
return self.__supported_length
def parse_external_result(self, file):
"""
Parses external results and returns the result
:param str file: The file path or the external prediction results
:return: A dictionary containing the prediction results
:rtype: dict
"""
result = defaultdict(defaultdict)
with open(file, "r") as f:
for l in f:
if l.startswith("#") or l.startswith("-") or l.strip() == "":
continue
row = l.strip().split()
if not row[0].isdigit():
continue
epitope, allele, comb_score = row[3], row[2], row[7]
result[allele.replace("*", "")][epitope] = float(comb_score)
return result
def get_external_version(self, path=None):
"""
Returns the external version of the tool by executing
>{command} --version
might be dependent on the method and has to be overwritten
therefore it is declared abstract to enforce the user to
overwrite the method. The function in the base class can be called
with super()
:param str path: Optional specification of executable path if deviant from :attr:`self.__command`
:return: The external version of the tool or None if tool does not support versioning
:rtype: str
"""
return None
def prepare_input(self, input, file):
"""
Prepares input for external tools and writes them to file in the specific format
No return value!
:param: list(str) input: The :class:`~epytope.Core.Peptide.Peptide` sequences to write into file
:param File file: File-handler to input file for external tool
"""
file.write("\n".join(">pepe_%i\n%s" % (i, p) for i, p in enumerate(input)))
| 100.948412
| 161
| 0.549893
| 150,109
| 702,500
| 2.569986
| 0.005196
| 0.073732
| 0.068635
| 0.041915
| 0.983431
| 0.981417
| 0.980491
| 0.978516
| 0.978283
| 0.97758
| 0
| 0.287396
| 0.164258
| 702,500
| 6,958
| 162
| 100.96292
| 0.369684
| 0.033227
| 0
| 0.810948
| 0
| 0.001797
| 0.702198
| 0.427779
| 0
| 0
| 0
| 0
| 0
| 1
| 0.016993
| false
| 0
| 0.002451
| 0.001471
| 0.048203
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 12
|
de5894330ed24e49486d9cb26da387b4cc390f1f
| 206
|
py
|
Python
|
tests/integration_tests/boolean_tests/test_operation_type.py
|
skrat/martinez
|
86db48324cb50ecb52be8ab2e4278a6d5cdd562b
|
[
"MIT"
] | 7
|
2020-05-07T08:13:44.000Z
|
2021-12-17T07:33:51.000Z
|
tests/integration_tests/boolean_tests/test_operation_type.py
|
skrat/martinez
|
86db48324cb50ecb52be8ab2e4278a6d5cdd562b
|
[
"MIT"
] | 17
|
2019-11-29T23:17:26.000Z
|
2020-12-20T15:47:17.000Z
|
tests/integration_tests/boolean_tests/test_operation_type.py
|
skrat/martinez
|
86db48324cb50ecb52be8ab2e4278a6d5cdd562b
|
[
"MIT"
] | 1
|
2020-12-17T22:44:21.000Z
|
2020-12-17T22:44:21.000Z
|
from tests.bind_tests.hints import BoundOperationType
from tests.port_tests.hints import PortedOperationType
def test_basic():
assert BoundOperationType.__members__ == PortedOperationType.__members__
| 29.428571
| 76
| 0.849515
| 22
| 206
| 7.454545
| 0.590909
| 0.109756
| 0.195122
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.097087
| 206
| 6
| 77
| 34.333333
| 0.88172
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0.25
| true
| 0
| 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
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
deaa6d7d0924ff6ba6867feee2d99533ae26ed86
| 138
|
py
|
Python
|
test/code_count/python/2.py
|
Silent47/local-code-stat
|
54b215036abad01b0d1c55ba1df08a9820732aca
|
[
"MIT"
] | 1
|
2020-02-28T23:44:28.000Z
|
2020-02-28T23:44:28.000Z
|
test/code_count/python/2.py
|
Silent47/local-code-stat
|
54b215036abad01b0d1c55ba1df08a9820732aca
|
[
"MIT"
] | 1
|
2020-02-29T09:19:13.000Z
|
2020-02-29T09:19:13.000Z
|
test/code_count/python/2.py
|
Silent47/local-code-stat
|
54b215036abad01b0d1c55ba1df08a9820732aca
|
[
"MIT"
] | null | null | null |
""""""
""" """
""" abc " abc """
""" abc "" abc """
""" abc """" abc """
""" abc """""" abc """
""" abc """""""""""""""""" abc """
| 9.857143
| 34
| 0.217391
| 10
| 138
| 3
| 0.1
| 1.8
| 2.4
| 2.8
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0.253623
| 138
| 13
| 35
| 10.615385
| 0.291262
| 0
| 0
| 0
| 0
| 0
| 0.267857
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 11
|
deaf1582ef43484e446dbacd23583a97037b010c
| 2,964
|
py
|
Python
|
T - Sine Wave Rainbow/main.py
|
burningion/critter-and-guitari-etc-programs
|
f18ddaee507547a56b7252ebe27fea90206032d5
|
[
"MIT"
] | 16
|
2018-03-16T04:51:44.000Z
|
2021-11-17T14:59:22.000Z
|
T - Sine Wave Rainbow/main.py
|
burningion/critter-and-guitari-etc-programs
|
f18ddaee507547a56b7252ebe27fea90206032d5
|
[
"MIT"
] | 1
|
2018-07-13T09:09:01.000Z
|
2018-07-13T09:09:01.000Z
|
T - Sine Wave Rainbow/main.py
|
burningion/critter-and-guitari-etc-programs
|
f18ddaee507547a56b7252ebe27fea90206032d5
|
[
"MIT"
] | 3
|
2019-09-22T20:15:39.000Z
|
2022-03-05T15:51:55.000Z
|
import os
import pygame
import random
import time
import math
def setup(screen, etc) :
pass
def draw(screen, etc) :
radius = 50
color = etc.color_picker()
halfSies = list((c // 2 for c in color))
if etc.audio_trig or etc.midi_note_new:
for i in range(int(etc.knob3 * 720)):
x = int(600 - 50 * math.sin(i * etc.knob1 / 10 + time.time()))
radius = int(50 + math.sin(i * etc.knob2 / 10 + time.time()) * 50)
color = (halfSies[0] + int(halfSies[0] * math.sin(i * .01 + time.time())),
halfSies[1] + int(halfSies[1] * math.sin(i * .01 + time.time())),
halfSies[2] + int(halfSies[2] * math.sin(i * .01 + time.time())))
pygame.gfxdraw.filled_circle(screen,
x,
i,
radius,
color)
pygame.gfxdraw.filled_circle(screen,
x - 1280 // 4,
i,
radius,
color)
pygame.gfxdraw.filled_circle(screen,
x + 1280 // 4,
i,
radius,
color)
pygame.gfxdraw.filled_circle(screen,
x,
720 - i,
radius,
color)
pygame.gfxdraw.filled_circle(screen,
x - 1280 // 4,
720 - i,
radius,
color)
pygame.gfxdraw.filled_circle(screen,
x + 1280 // 4,
720 - i,
radius,
color)
else:
for i in range(720):
x = int(600 - 50 * math.sin(i * etc.knob1 / 10 + time.time()))
radius = int(50 + math.sin(i * etc.knob2 / 10 + time.time()) * 50)
color = (halfSies[0] + int(halfSies[0] * math.sin(i * .01 + time.time())),
halfSies[1] + int(halfSies[1] * math.sin(i * .015 + time.time())),
halfSies[2] + int(halfSies[2] * math.sin(i * .021 + time.time())))
pygame.gfxdraw.filled_circle(screen,
x,
i,
radius,
color)
| 39
| 87
| 0.322537
| 246
| 2,964
| 3.841463
| 0.207317
| 0.074074
| 0.084656
| 0.185185
| 0.773545
| 0.773545
| 0.771429
| 0.769312
| 0.769312
| 0.769312
| 0
| 0.077048
| 0.584008
| 2,964
| 75
| 88
| 39.52
| 0.689376
| 0
| 0
| 0.683333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.033333
| false
| 0.016667
| 0.083333
| 0
| 0.116667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 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
|
ded3677218663b978de2e3dcdc2b86afc06e60f8
| 8,128
|
py
|
Python
|
src/moca_modules/moca_counter/MocaCounter.py
|
el-ideal-ideas/MocaTwitterUtils
|
544a260600ade1b8cd4e0a2d2967c2fb6a8f38d3
|
[
"MIT"
] | null | null | null |
src/moca_modules/moca_counter/MocaCounter.py
|
el-ideal-ideas/MocaTwitterUtils
|
544a260600ade1b8cd4e0a2d2967c2fb6a8f38d3
|
[
"MIT"
] | null | null | null |
src/moca_modules/moca_counter/MocaCounter.py
|
el-ideal-ideas/MocaTwitterUtils
|
544a260600ade1b8cd4e0a2d2967c2fb6a8f38d3
|
[
"MIT"
] | null | null | null |
# -- Imports --------------------------------------------------------------------------
from typing import (
Optional, Tuple
)
from .AsyncInMemoryDriver import AsyncInMemoryDriver
from .DriverInterface import DriverInterface
from .InMemoryDriver import InMemoryDriver
from .AsyncInMemoryDriver import AsyncDriverInterface
# -------------------------------------------------------------------------- Imports --
# -- Main Class --------------------------------------------------------------------------
class MocaCounter(object):
"""
-- english --------------------------------------------------------------------------
This is a simple counter module for MocaSystem. Developed by el.ideal-ideas for Moca System.
-- 日本語 --------------------------------------------------------------------------
これはel.ideal-ideasによって開発されたモカシステムのためのシンプルなカウンターモジュールです。
-- 简体中文 --------------------------------------------------------------------------
这是el.ideal-ideas为茉客系统开发的计数器模块。
Attributes
----------
_driver: DriverInterface
the driver of this instance.
"""
def __init__(self, driver: Optional[DriverInterface]):
"""
:param driver: an instance of synchronized driver.
Arise
-----
TypeError: if type of argument is incorrect.
"""
self._driver: DriverInterface
if driver is None:
self._driver = InMemoryDriver()
else:
if isinstance(driver, DriverInterface):
self._driver = driver
else:
raise TypeError("Argument type error."
"Expected driver: Optional[DriverInterface] "
f"But Received: driver: {type(driver)}")
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
def add(self,
key: str,
value: int = 1) -> Tuple[bool, Optional[int], str]:
"""
Add count by key.
:param key: the key of the counter.
:param value: the value to add.
:return: Tuple(status, count, message) If can't get the value of counter, count will be None.
"""
return self._driver.add(key, value)
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
def set(self,
key: str,
value: int) -> Tuple[bool, str]:
"""
Set count by key.
:param key: the key of the counter.
:param value: the value to set.
:return: Tuple(status, message)
"""
return self._driver.set(key, value)
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
def get(self,
key: str,
default: Optional[int] = None) -> Tuple[Optional[int], str]:
"""
Get the count by key.
:param key: the key of the counter.
:param default: the default value.
:return: Tuple(value, message). if some error occurred, the response value will be default value.
"""
return self._driver.get(key, default)
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
def clear(self,
key: str) -> Tuple[bool, str]:
"""
Clear the count by key.
:param key: the key of the counter.
:return: Tuple(status, message)
"""
return self._driver.clear(key)
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
@property
def info(self) -> str:
return self._driver.NAME + ': ' + self._driver.VERSION
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
class MocaAsyncCounter(object):
"""
-- english --------------------------------------------------------------------------
This is a simple counter module for MocaSystem. Developed by el.ideal-ideas for Moca System.
-- 日本語 --------------------------------------------------------------------------
これはel.ideal-ideasによって開発されたモカシステムのためのシンプルなカウンターモジュールです。
-- 简体中文 --------------------------------------------------------------------------
这是el.ideal-ideas为茉客系统开发的计数器模块。
Attributes
----------
self._driver: DriverInterface
the driver of this instance.
"""
def __init__(self, driver: Optional[AsyncDriverInterface]):
"""
:param driver: an instance of synchronized driver.
Arise
-----
TypeError: if type of argument is incorrect.
"""
self._driver: AsyncDriverInterface
if driver is None:
self._driver = AsyncInMemoryDriver()
else:
if isinstance(driver, AsyncDriverInterface):
self._driver = driver
else:
raise TypeError("Argument type error."
"Expected driver: Optional[AsyncDriverInterface] "
f"But Received: driver: {type(driver)}")
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
async def add(self,
key: str,
value: int = 1) -> Tuple[bool, Optional[int], str]:
"""
Add count by key.
:param key: the key of the counter.
:param value: the value to add.
:return: Tuple(status, count, message) If can't get the value of counter, count will be None.
"""
return await self._driver.add(key, value)
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
async def set(self,
key: str,
value: int) -> Tuple[bool, str]:
"""
Set count by key.
:param key: the key of the counter.
:param value: the value to set.
:return: Tuple(status, message)
"""
return await self._driver.set(key, value)
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
async def get(self,
key: str,
default: Optional[int] = None) -> Tuple[Optional[int], str]:
"""
Get the count by key.
:param key: the key of the counter.
:param default: the default value.
:return: Tuple(value, message). if some error occurred, the response value will be default value.
"""
return await self._driver.get(key, default)
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
async def clear(self,
key: str) -> Tuple[bool, str]:
"""
Clear the count by key.
:param key: the key of the counter.
:return: Tuple(status, message)
"""
return await self._driver.clear(key)
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
@property
def info(self) -> str:
return self._driver.NAME + ': ' + self._driver.VERSION
# -------------------------------------------------------------------------- Main Class --
| 38.159624
| 105
| 0.373524
| 582
| 8,128
| 5.168385
| 0.158076
| 0.069814
| 0.026596
| 0.039894
| 0.825798
| 0.789229
| 0.754654
| 0.75133
| 0.744681
| 0.744681
| 0
| 0.000325
| 0.242126
| 8,128
| 212
| 106
| 38.339623
| 0.487987
| 0.495817
| 0
| 0.477612
| 0
| 0
| 0.070624
| 0.018765
| 0
| 0
| 0
| 0
| 0
| 1
| 0.119403
| false
| 0
| 0.074627
| 0.029851
| 0.373134
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
dee6320ced4973c8654e5304811f6af0ecb57353
| 120
|
py
|
Python
|
gsfpy/gsfMBOffsets.py
|
irewolepeter/gsfpy_USM_Implementation
|
c4614ac3f7d833eb86ea38c7708108b130f96612
|
[
"MIT"
] | 7
|
2020-07-01T07:12:19.000Z
|
2022-01-20T20:39:57.000Z
|
gsfpy/gsfMBOffsets.py
|
irewolepeter/gsfpy_USM_Implementation
|
c4614ac3f7d833eb86ea38c7708108b130f96612
|
[
"MIT"
] | 36
|
2020-06-23T09:10:15.000Z
|
2022-03-22T10:27:58.000Z
|
gsfpy/gsfMBOffsets.py
|
irewolepeter/gsfpy_USM_Implementation
|
c4614ac3f7d833eb86ea38c7708108b130f96612
|
[
"MIT"
] | 2
|
2021-02-07T13:21:52.000Z
|
2021-06-24T19:16:16.000Z
|
from gsfpy import mirror_default_gsf_version_submodule
mirror_default_gsf_version_submodule(globals(), "gsfMBOffsets")
| 30
| 63
| 0.883333
| 15
| 120
| 6.533333
| 0.666667
| 0.265306
| 0.326531
| 0.469388
| 0.653061
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058333
| 120
| 3
| 64
| 40
| 0.867257
| 0
| 0
| 0
| 0
| 0
| 0.1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
deea4276dd32a6b4a61f56388fadeaeca9a0abf4
| 1,040
|
py
|
Python
|
Moves/Circle.py
|
rknowlto/PoMoCo
|
3b5f013965c1a06b288e9bbbb74f618027b53f44
|
[
"Unlicense",
"MIT"
] | 1
|
2017-08-26T23:44:14.000Z
|
2017-08-26T23:44:14.000Z
|
Moves/Circle.py
|
rknowlto/PoMoCo
|
3b5f013965c1a06b288e9bbbb74f618027b53f44
|
[
"Unlicense",
"MIT"
] | null | null | null |
Moves/Circle.py
|
rknowlto/PoMoCo
|
3b5f013965c1a06b288e9bbbb74f618027b53f44
|
[
"Unlicense",
"MIT"
] | null | null | null |
import time
# Move: Circle
hexy.RF.pointCircle(centerHipAngle=30,radius=10,orientation=1,stepTime=0.6)
hexy.LF.pointCircle(centerHipAngle=-30,radius=10,orientation=-1,stepTime=0.6)
time.sleep(0.6)
hexy.RF.pointCircle(centerHipAngle=30,radius=20,orientation=1,stepTime=0.6)
hexy.LF.pointCircle(centerHipAngle=-30,radius=20,orientation=-1,stepTime=0.6)
time.sleep(0.6)
hexy.RF.pointCircle(centerHipAngle=30,radius=30,orientation=1,stepTime=0.6)
hexy.LF.pointCircle(centerHipAngle=-30,radius=30,orientation=-1,stepTime=0.6)
time.sleep(0.6)
hexy.RF.pointCircle(centerHipAngle=30,radius=30,orientation=-1,stepTime=0.6)
hexy.LF.pointCircle(centerHipAngle=-30,radius=30,orientation=1,stepTime=0.6)
time.sleep(0.6)
hexy.RF.pointCircle(centerHipAngle=30,radius=20,orientation=-1,stepTime=0.6)
hexy.LF.pointCircle(centerHipAngle=-30,radius=20,orientation=1,stepTime=0.6)
time.sleep(0.6)
hexy.RF.pointCircle(centerHipAngle=30,radius=10,orientation=-1,stepTime=0.6)
hexy.LF.pointCircle(centerHipAngle=-30,radius=10,orientation=1,stepTime=0.6)
| 43.333333
| 77
| 0.799038
| 168
| 1,040
| 4.946429
| 0.113095
| 0.040915
| 0.389892
| 0.476534
| 0.975933
| 0.975933
| 0.975933
| 0.975933
| 0.975933
| 0.975933
| 0
| 0.093162
| 0.029808
| 1,040
| 23
| 78
| 45.217391
| 0.730426
| 0.011538
| 0
| 0.277778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.055556
| 0
| 0.055556
| 0
| 0
| 0
| 0
| null | 0
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
7201ac8111cb13a51e4a37bee0379914a742a47e
| 3,063
|
py
|
Python
|
src/frr/tests/topotests/bgp_rfapi_basic_sanity/scripts/cleanup_all.py
|
zhouhaifeng/vpe
|
9c644ffd561988e5740021ed26e0f7739844353d
|
[
"Apache-2.0"
] | null | null | null |
src/frr/tests/topotests/bgp_rfapi_basic_sanity/scripts/cleanup_all.py
|
zhouhaifeng/vpe
|
9c644ffd561988e5740021ed26e0f7739844353d
|
[
"Apache-2.0"
] | null | null | null |
src/frr/tests/topotests/bgp_rfapi_basic_sanity/scripts/cleanup_all.py
|
zhouhaifeng/vpe
|
9c644ffd561988e5740021ed26e0f7739844353d
|
[
"Apache-2.0"
] | null | null | null |
from lib.lutil import luCommand
luCommand(
"r1",
'vtysh -c "debug rfapi-dev unregister vn 10.0.0.1 un 1.1.1.1 prefix 11.11.11.0/24"',
"",
"none",
"Prefix removed",
)
luCommand(
"r1",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 ",
"wait",
"Local registration removed",
)
luCommand(
"r1",
'vtysh -c "debug rfapi-dev close vn 10.0.0.1 un 1.1.1.1"',
"status 0",
"pass",
"Closed RFAPI",
)
luCommand(
"r3",
'vtysh -c "debug rfapi-dev unregister vn 10.0.0.2 un 2.2.2.2 prefix 22.22.22.0/24"',
"",
"none",
"Prefix removed",
)
luCommand(
"r3",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 ",
"wait",
"Local registration removed",
)
luCommand(
"r3",
'vtysh -c "debug rfapi-dev close vn 10.0.0.2 un 2.2.2.2"',
"status 0",
"pass",
"Closed RFAPI",
)
luCommand(
"r4",
'vtysh -c "debug rfapi-dev unregister vn 10.0.0.3 un 3.3.3.3 prefix 33.33.33.0/24"',
"",
"none",
"Prefix removed",
)
luCommand(
"r4",
'vtysh -c "debug rfapi-dev unregister vn 10.0.0.3 un 3.3.3.3 prefix 11.11.11.0/24"',
"",
"none",
"MP prefix removed",
)
luCommand(
"r4",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 ",
"wait",
"Local registration removed",
)
# luCommand('r4','vtysh -c "debug rfapi-dev close vn 10.0.0.3 un 3.3.3.3"','status 0', 'pass', 'Closed RFAPI')
luCommand("r4", 'vtysh -c "clear vnc nve *"', ".", "pass", "Cleared NVEs")
luCommand(
"r1",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 .* Remotely: *Active: 0",
"wait",
"All registrations cleared",
)
luCommand(
"r3",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 .* Remotely: *Active: 0",
"wait",
"All registrations cleared",
)
luCommand(
"r4",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 .* Remotely: *Active: 0",
"wait",
"All registrations cleared",
)
num = "0 exist"
luCommand("r1", 'vtysh -c "show bgp ipv4 vpn"', num, "pass", "VPN SAFI clear")
luCommand("r2", 'vtysh -c "show bgp ipv4 vpn"', num, "pass", "VPN SAFI clear")
luCommand("r3", 'vtysh -c "show bgp ipv4 vpn"', num, "pass", "VPN SAFI clear")
luCommand("r4", 'vtysh -c "show bgp ipv4 vpn"', num, "pass", "VPN SAFI clear")
luCommand(
"r1",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 .* Remotely: *Active: 0 .*In Holddown: *Active: 0",
"wait",
"No holddowns",
20,
)
luCommand(
"r3",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 .* Remotely: *Active: 0 .*In Holddown: *Active: 0",
"wait",
"No holddowns",
)
luCommand(
"r4",
'vtysh -c "show vnc registrations"',
"Locally: *Active: 0 .* Remotely: *Active: 0 .*In Holddown: *Active: 0",
"wait",
"No holddowns",
)
luCommand("r1", 'vtysh -c "show vnc summary"', ".", "none")
luCommand("r3", 'vtysh -c "show vnc summary"', ".", "none")
luCommand("r4", 'vtysh -c "show vnc summary"', ".", "none")
| 24.504
| 110
| 0.570682
| 426
| 3,063
| 4.103286
| 0.140845
| 0.08238
| 0.091533
| 0.089245
| 0.950801
| 0.94222
| 0.878719
| 0.80778
| 0.802632
| 0.767735
| 0
| 0.064255
| 0.232778
| 3,063
| 124
| 111
| 24.701613
| 0.679574
| 0.03526
| 0
| 0.715517
| 0
| 0.077586
| 0.632916
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.060345
| 0.008621
| 0
| 0.008621
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 9
|
7240dcd63f8763439c5cd9ea510c1d12fbe08d3a
| 81
|
py
|
Python
|
tests/test_test.py
|
reminisce/tensorboard-mxnet-logger
|
ad7d6522e4010deaa3a2a95e93629d8b01751078
|
[
"MIT"
] | 5
|
2018-07-03T18:40:49.000Z
|
2019-04-11T13:58:30.000Z
|
tests/test_test.py
|
avalonstrel/tensorboard-pytorch
|
1cb71ccfe9016578c6ffd1802d13a888dca58a59
|
[
"MIT"
] | null | null | null |
tests/test_test.py
|
avalonstrel/tensorboard-pytorch
|
1cb71ccfe9016578c6ffd1802d13a888dca58a59
|
[
"MIT"
] | 3
|
2018-07-27T01:14:45.000Z
|
2019-04-11T13:58:33.000Z
|
def test_test():
import demo
import demo_graph
import demo_embedding
| 16.2
| 25
| 0.716049
| 11
| 81
| 5
| 0.545455
| 0.545455
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.246914
| 81
| 4
| 26
| 20.25
| 0.901639
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0
| 0.75
| 0
| 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
| 1
| 0
| 1
| 0
|
0
| 7
|
a0cb72e31bd31815f9ada8eeac253ab31e630262
| 1,612
|
py
|
Python
|
web/transiq/driver/migrations/0026_auto_20181016_1633.py
|
manibhushan05/transiq
|
763fafb271ce07d13ac8ce575f2fee653cf39343
|
[
"Apache-2.0"
] | null | null | null |
web/transiq/driver/migrations/0026_auto_20181016_1633.py
|
manibhushan05/transiq
|
763fafb271ce07d13ac8ce575f2fee653cf39343
|
[
"Apache-2.0"
] | 14
|
2020-06-05T23:06:45.000Z
|
2022-03-12T00:00:18.000Z
|
web/transiq/driver/migrations/0026_auto_20181016_1633.py
|
manibhushan05/transiq
|
763fafb271ce07d13ac8ce575f2fee653cf39343
|
[
"Apache-2.0"
] | null | null | null |
# Generated by Django 2.0.5 on 2018-10-16 16:33
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('driver', '0025_auto_20181016_1540'),
]
operations = [
migrations.RemoveField(
model_name='gpsdevice',
name='gps_id',
),
migrations.RemoveField(
model_name='gpsdevice',
name='gps_imei',
),
migrations.RemoveField(
model_name='gpsdevice',
name='inactive_sms_sent_at',
),
migrations.RemoveField(
model_name='gpsdevice',
name='number_verified',
),
migrations.RemoveField(
model_name='gpsdevice',
name='phone',
),
migrations.RemoveField(
model_name='gpsdevice',
name='sim_number',
),
migrations.RemoveField(
model_name='historicalgpsdevice',
name='gps_id',
),
migrations.RemoveField(
model_name='historicalgpsdevice',
name='gps_imei',
),
migrations.RemoveField(
model_name='historicalgpsdevice',
name='inactive_sms_sent_at',
),
migrations.RemoveField(
model_name='historicalgpsdevice',
name='number_verified',
),
migrations.RemoveField(
model_name='historicalgpsdevice',
name='phone',
),
migrations.RemoveField(
model_name='historicalgpsdevice',
name='sim_number',
),
]
| 26
| 47
| 0.534739
| 126
| 1,612
| 6.611111
| 0.31746
| 0.302521
| 0.37455
| 0.432173
| 0.806723
| 0.806723
| 0.569028
| 0.122449
| 0.122449
| 0
| 0
| 0.030068
| 0.360422
| 1,612
| 61
| 48
| 26.42623
| 0.777886
| 0.027916
| 0
| 0.872727
| 1
| 0
| 0.207668
| 0.014696
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.018182
| 0
| 0.072727
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 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
| 7
|
c234be0b681e701c81bac592bda4301ef058f063
| 285
|
py
|
Python
|
data/__init__.py
|
salmank255/ROADSlowFast
|
e939d8f79fe3eb6f3dd32e967a34530d00f45c8e
|
[
"Apache-2.0"
] | null | null | null |
data/__init__.py
|
salmank255/ROADSlowFast
|
e939d8f79fe3eb6f3dd32e967a34530d00f45c8e
|
[
"Apache-2.0"
] | null | null | null |
data/__init__.py
|
salmank255/ROADSlowFast
|
e939d8f79fe3eb6f3dd32e967a34530d00f45c8e
|
[
"Apache-2.0"
] | null | null | null |
# from .inference_dataset import VideoDataset, custum_collate, get_gt_video_list, get_video_tubes
# from .inference_dataset import VideoDataset, custum_collate, get_gt_video_list, get_video_tubes
from .dataset_R import VideoDataset, custum_collate, get_gt_video_list, get_video_tubes
| 57
| 97
| 0.866667
| 42
| 285
| 5.380952
| 0.309524
| 0.238938
| 0.318584
| 0.411504
| 0.964602
| 0.964602
| 0.964602
| 0.964602
| 0.964602
| 0.964602
| 0
| 0
| 0.084211
| 285
| 4
| 98
| 71.25
| 0.8659
| 0.670175
| 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
| 1
| 1
| 1
| 1
| 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
| 13
|
a04ad2349ed9e6b75cc8a1f5d7fd50a56ddde59f
| 248,417
|
py
|
Python
|
Lib/site-packages/numarray/nd_image/test.py
|
raychorn/svn_Python-2.5.1
|
425005b1b489ba44ec0bb989e077297e8953d9be
|
[
"PSF-2.0"
] | null | null | null |
Lib/site-packages/numarray/nd_image/test.py
|
raychorn/svn_Python-2.5.1
|
425005b1b489ba44ec0bb989e077297e8953d9be
|
[
"PSF-2.0"
] | null | null | null |
Lib/site-packages/numarray/nd_image/test.py
|
raychorn/svn_Python-2.5.1
|
425005b1b489ba44ec0bb989e077297e8953d9be
|
[
"PSF-2.0"
] | null | null | null |
# Copyright (C) 2003-2005 Peter J. Verveer
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
#
# 3. The name of the author may not be used to endorse or promote
# products derived from this software without specific prior
# written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS
# OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY
# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE
# GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
# NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import unittest
import math
import numarray
import numarray.nd_image
import numarray.fft
import numarray.numinclude as numinclude
eps = 1e-12
def diff(a, b):
if not isinstance(a, numarray.NumArray):
a = numarray.asarray(a)
if not isinstance(b, numarray.NumArray):
b = numarray.asarray(b)
if (0 in a.shape) and (0 in b.shape):
return 0.0
if (a.type() in [numarray.Complex32, numarray.Complex64] or
b.type() in [numarray.Complex32, numarray.Complex64]):
a = numarray.asarray(a, numarray.Complex64)
b = numarray.asarray(b, numarray.Complex64)
t = ((a.real - b.real)**2).sum() + ((a.imag - b.imag)**2).sum()
else:
a = numarray.asarray(a, numarray.Float64)
b = numarray.asarray(b, numarray.Float64)
t = ((a - b)**2).sum()
return math.sqrt(t)
class NDImageTest(unittest.TestCase):
def setUp(self):
# list of numarray data types
self.types = [numarray.Int8, numarray.UInt8, numarray.Int16,
numarray.UInt16, numarray.Int32, numarray.UInt32,
numarray.Int64, numarray.Float32, numarray.Float64]
if numinclude.hasUInt64:
self.types.append(numarray.UInt64)
# list of boundary modes:
self.modes = ['nearest', 'wrap', 'reflect', 'constant']
def test_correlate01(self):
"correlation 1"
array = numarray.array([1, 2])
weights = numarray.array([2])
true = [2, 4]
output = numarray.nd_image.correlate(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.convolve(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.correlate1d(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.convolve1d(array, weights)
self.failUnless(diff(output, true) < eps)
def test_correlate02(self):
"correlation 2"
array = numarray.array([1, 2, 3])
kernel = numarray.array([1])
output = numarray.nd_image.correlate(array, kernel)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.convolve(array, kernel)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.correlate1d(array, kernel)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.convolve1d(array, kernel)
self.failUnless(diff(array, output) < eps)
def test_correlate03(self):
"correlation 3"
array = numarray.array([1])
weights = numarray.array([1, 1])
true = [2]
output = numarray.nd_image.correlate(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.convolve(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.correlate1d(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.convolve1d(array, weights)
self.failUnless(diff(output, true) < eps)
def test_correlate04(self):
"correlation 4"
array = numarray.array([1, 2])
tcor = [2, 3]
tcov = [3, 4]
weights = numarray.array([1, 1])
output = numarray.nd_image.correlate(array, weights)
self.failUnless(diff(output, tcor) < eps)
output = numarray.nd_image.convolve(array, weights)
self.failUnless(diff(output, tcov) < eps)
output = numarray.nd_image.correlate1d(array, weights)
self.failUnless(diff(output, tcor) < eps)
output = numarray.nd_image.convolve1d(array, weights)
self.failUnless(diff(output, tcov) < eps)
def test_correlate05(self):
"correlation 5"
array = numarray.array([1, 2, 3])
tcor = [2, 3, 5]
tcov = [3, 5, 6]
kernel = numarray.array([1, 1])
output = numarray.nd_image.correlate(array, kernel)
self.failUnless(diff(tcor, output) < eps)
output = numarray.nd_image.convolve(array, kernel)
self.failUnless(diff(tcov, output) < eps)
output = numarray.nd_image.correlate1d(array, kernel)
self.failUnless(diff(tcor, output) < eps)
output = numarray.nd_image.convolve1d(array, kernel)
self.failUnless(diff(tcov, output) < eps)
def test_correlate06(self):
"correlation 6"
array = numarray.array([1, 2, 3])
tcor = [9, 14, 17]
tcov = [7, 10, 15]
weights = numarray.array([1, 2, 3])
output = numarray.nd_image.correlate(array, weights)
self.failUnless(diff(output, tcor) < eps)
output = numarray.nd_image.convolve(array, weights)
self.failUnless(diff(output, tcov) < eps)
output = numarray.nd_image.correlate1d(array, weights)
self.failUnless(diff(output, tcor) < eps)
output = numarray.nd_image.convolve1d(array, weights)
self.failUnless(diff(output, tcov) < eps)
def test_correlate07(self):
"correlation 7"
array = numarray.array([1, 2, 3])
true = [5, 8, 11]
weights = numarray.array([1, 2, 1])
output = numarray.nd_image.correlate(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.convolve(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.correlate1d(array, weights)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.convolve1d(array, weights)
self.failUnless(diff(output, true) < eps)
def test_correlate08(self):
"correlation 8"
array = numarray.array([1, 2, 3])
tcor = [1, 2, 5]
tcov = [3, 6, 7]
weights = numarray.array([1, 2, -1])
output = numarray.nd_image.correlate(array, weights)
self.failUnless(diff(output, tcor) < eps)
output = numarray.nd_image.convolve(array, weights)
self.failUnless(diff(output, tcov) < eps)
output = numarray.nd_image.correlate1d(array, weights)
self.failUnless(diff(output, tcor) < eps)
output = numarray.nd_image.convolve1d(array, weights)
self.failUnless(diff(output, tcov) < eps)
def test_correlate09(self):
"correlation 9"
array = []
kernel = numarray.array([1, 1])
output = numarray.nd_image.correlate(array, kernel)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.convolve(array, kernel)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.correlate1d(array, kernel)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.convolve1d(array, kernel)
self.failUnless(diff(array, output) < eps)
def test_correlate10(self):
"correlation 10"
array = [[]]
kernel = numarray.array([[1, 1]])
output = numarray.nd_image.correlate(array, kernel)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.convolve(array, kernel)
self.failUnless(diff(array, output) < eps)
def test_correlate11(self):
"correlation 11"
array = numarray.array([[1, 2, 3],
[4, 5, 6]])
kernel = numarray.array([[1, 1],
[1, 1]])
output = numarray.nd_image.correlate(array, kernel)
self.failUnless(diff([[4, 6, 10], [10, 12, 16]], output) < eps)
output = numarray.nd_image.convolve(array, kernel)
self.failUnless(diff([[12, 16, 18], [18, 22, 24]], output) < eps)
def test_correlate12(self):
"correlation 12"
array = numarray.array([[1, 2, 3],
[4, 5, 6]])
kernel = numarray.array([[1, 0],
[0, 1]])
output = numarray.nd_image.correlate(array, kernel)
self.failUnless(diff([[2, 3, 5], [5, 6, 8]], output) < eps)
output = numarray.nd_image.convolve(array, kernel)
self.failUnless(diff([[6, 8, 9], [9, 11, 12]], output) < eps)
def test_correlate13(self):
"correlation 13"
kernel = numarray.array([[1, 0],
[0, 1]])
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[4, 5, 6]], type1)
for type2 in self.types:
output = numarray.nd_image.correlate(array, kernel,
output = type2)
error = diff([[2, 3, 5], [5, 6, 8]], output)
self.failUnless(error < eps and output.type() == type2)
output = numarray.nd_image.convolve(array, kernel,
output = type2)
error = diff([[6, 8, 9], [9, 11, 12]], output)
self.failUnless(error < eps and output.type() == type2)
def test_correlate14(self):
"correlation 14"
kernel = numarray.array([[1, 0],
[0, 1]])
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[4, 5, 6]], type1)
for type2 in self.types:
output = numarray.zeros(array.shape, type2)
numarray.nd_image.correlate(array, kernel,
output = output)
error = diff([[2, 3, 5], [5, 6, 8]], output)
self.failUnless(error < eps and output.type() == type2)
numarray.nd_image.convolve(array, kernel, output = output)
error = diff([[6, 8, 9], [9, 11, 12]], output)
self.failUnless(error < eps and output.type() == type2)
def test_correlate15(self):
"correlation 15"
kernel = numarray.array([[1, 0],
[0, 1]])
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[4, 5, 6]], type1)
output = numarray.nd_image.correlate(array, kernel,
output = numarray.Float32)
error = diff([[2, 3, 5], [5, 6, 8]], output)
self.failUnless(error < eps and
output.type() == numarray.Float32)
output = numarray.nd_image.convolve(array, kernel,
output = numarray.Float32)
error = diff([[6, 8, 9], [9, 11, 12]], output)
self.failUnless(error < eps and
output.type() == numarray.Float32)
def test_correlate16(self):
"correlation 16"
kernel = numarray.array([[0.5, 0 ],
[0, 0.5]])
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[4, 5, 6]], type1)
output = numarray.nd_image.correlate(array, kernel,
output = numarray.Float32)
error = diff([[1, 1.5, 2.5], [2.5, 3, 4]], output)
self.failUnless(error < eps and
output.type() == numarray.Float32)
output = numarray.nd_image.convolve(array, kernel,
output = numarray.Float32)
error = diff([[3, 4, 4.5], [4.5, 5.5, 6]], output)
self.failUnless(error < eps and
output.type() == numarray.Float32)
def test_correlate17(self):
"correlation 17"
array = numarray.array([1, 2, 3])
tcor = [3, 5, 6]
tcov = [2, 3, 5]
kernel = numarray.array([1, 1])
output = numarray.nd_image.correlate(array, kernel, origin = -1)
self.failUnless(diff(tcor, output) < eps)
output = numarray.nd_image.convolve(array, kernel, origin = -1)
self.failUnless(diff(tcov, output) < eps)
output = numarray.nd_image.correlate1d(array, kernel, origin = -1)
self.failUnless(diff(tcor, output) < eps)
output = numarray.nd_image.convolve1d(array, kernel, origin = -1)
self.failUnless(diff(tcov, output) < eps)
def test_correlate18(self):
"correlation 18"
kernel = numarray.array([[1, 0],
[0, 1]])
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[4, 5, 6]], type1)
output = numarray.nd_image.correlate(array, kernel,
output = numarray.Float32,
mode = 'nearest', origin = -1)
error = diff([[6, 8, 9], [9, 11, 12]], output)
self.failUnless(error < eps and
output.type() == numarray.Float32)
output = numarray.nd_image.convolve(array, kernel,
output = numarray.Float32, mode = 'nearest', origin = -1)
error = diff([[2, 3, 5], [5, 6, 8]], output)
self.failUnless(error < eps and
output.type() == numarray.Float32)
def test_correlate19(self):
"correlation 19"
kernel = numarray.array([[1, 0],
[0, 1]])
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[4, 5, 6]], type1)
output = numarray.nd_image.correlate(array, kernel,
output = numarray.Float32,
mode = 'nearest', origin = [-1, 0])
error = diff([[5, 6, 8], [8, 9, 11]], output)
self.failUnless(error < eps and
output.type() == numarray.Float32)
output = numarray.nd_image.convolve(array, kernel,
output = numarray.Float32,
mode = 'nearest', origin = [-1, 0])
error = diff([[3, 5, 6], [6, 8, 9]], output)
self.failUnless(error < eps and
output.type() == numarray.Float32)
def test_correlate20(self):
"correlation 20"
weights = numarray.array([1, 2, 1])
true = [[5, 10, 15], [7, 14, 21]]
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[2, 4, 6]], type1)
for type2 in self.types:
output = numarray.zeros((2, 3), type2)
numarray.nd_image.correlate1d(array, weights, axis = 0,
output = output)
self.failUnless(diff(output, true) < eps)
numarray.nd_image.convolve1d(array, weights, axis = 0,
output = output)
self.failUnless(diff(output, true) < eps)
def test_correlate21(self):
"correlation 21"
array = numarray.array([[1, 2, 3],
[2, 4, 6]])
true = [[5, 10, 15], [7, 14, 21]]
weights = numarray.array([1, 2, 1])
output = numarray.nd_image.correlate1d(array, weights, axis = 0)
self.failUnless(diff(output, true) < eps)
output = numarray.nd_image.convolve1d(array, weights, axis = 0)
self.failUnless(diff(output, true) < eps)
def test_correlate22(self):
"correlation 22"
weights = numarray.array([1, 2, 1])
true = [[6, 12, 18], [6, 12, 18]]
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[2, 4, 6]], type1)
for type2 in self.types:
output = numarray.zeros((2, 3), type2)
numarray.nd_image.correlate1d(array, weights, axis = 0,
mode = 'wrap', output = output)
self.failUnless(diff(output, true) < eps)
numarray.nd_image.convolve1d(array, weights, axis = 0,
mode = 'wrap', output = output)
self.failUnless(diff(output, true) < eps)
def test_correlate23(self):
"correlation 23"
weights = numarray.array([1, 2, 1])
true = [[5, 10, 15], [7, 14, 21]]
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[2, 4, 6]], type1)
for type2 in self.types:
output = numarray.zeros((2, 3), type2)
numarray.nd_image.correlate1d(array, weights, axis = 0,
mode = 'nearest', output = output)
self.failUnless(diff(output, true) < eps)
numarray.nd_image.convolve1d(array, weights, axis = 0,
mode = 'nearest', output = output)
self.failUnless(diff(output, true) < eps)
def test_correlate24(self):
"correlation 24"
weights = numarray.array([1, 2, 1])
tcor = [[7, 14, 21], [8, 16, 24]]
tcov = [[4, 8, 12], [5, 10, 15]]
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[2, 4, 6]], type1)
for type2 in self.types:
output = numarray.zeros((2, 3), type2)
numarray.nd_image.correlate1d(array, weights, axis = 0,
mode = 'nearest', output = output, origin = -1)
self.failUnless(diff(output, tcor) < eps)
numarray.nd_image.convolve1d(array, weights, axis = 0,
mode = 'nearest', output = output, origin = -1)
self.failUnless(diff(output, tcov) < eps)
def test_correlate25(self):
"correlation 25"
weights = numarray.array([1, 2, 1])
tcor = [[4, 8, 12], [5, 10, 15]]
tcov = [[7, 14, 21], [8, 16, 24]]
for type1 in self.types:
array = numarray.array([[1, 2, 3],
[2, 4, 6]], type1)
for type2 in self.types:
output = numarray.zeros((2, 3), type2)
numarray.nd_image.correlate1d(array, weights, axis = 0,
mode = 'nearest', output = output, origin = 1)
self.failUnless(diff(output, tcor) < eps)
numarray.nd_image.convolve1d(array, weights, axis = 0,
mode = 'nearest', output = output, origin = 1)
self.failUnless(diff(output, tcov) < eps)
def test_gauss01(self):
"gaussian filter 1"
input = numarray.array([[1, 2, 3],
[2, 4, 6]], numarray.Float32)
output = numarray.nd_image.gaussian_filter(input, 0)
self.failUnless(diff(output, input) < eps)
def test_gauss02(self):
"gaussian filter 2"
input = numarray.array([[1, 2, 3],
[2, 4, 6]], numarray.Float32)
output = numarray.nd_image.gaussian_filter(input, 1.0)
self.failUnless(input.type() == output.type() and
input.shape == output.shape)
def test_gauss03(self):
"gaussian filter 3"
input = numarray.arange(100 * 100).astype(numarray.Float32)
input.shape = (100, 100)
output = numarray.nd_image.gaussian_filter(input, [1.0, 1.0])
self.failUnless(input.type() == output.type() and
input.shape == output.shape and
output.sum() - input.sum() < eps and
diff(input, output) > 1.0)
def test_gauss04(self):
"gaussian filter 4"
input = numarray.arange(100 * 100).astype(numarray.Float32)
input.shape = (100, 100)
otype = numarray.Float64
output = numarray.nd_image.gaussian_filter(input, [1.0, 1.0],
output = otype)
self.failUnless(output.type() == numarray.Float64 and
input.shape == output.shape and
diff(input, output) > 1.0)
def test_gauss05(self):
"gaussian filter 5"
input = numarray.arange(100 * 100).astype(numarray.Float32)
input.shape = (100, 100)
otype = numarray.Float64
output = numarray.nd_image.gaussian_filter(input, [1.0, 1.0],
order = 1, output = otype)
self.failUnless(output.type() == numarray.Float64 and
input.shape == output.shape and
diff(input, output) > 1.0)
def test_gauss06(self):
"gaussian filter 6"
input = numarray.arange(100 * 100).astype(numarray.Float32)
input.shape = (100, 100)
otype = numarray.Float64
output1 = numarray.nd_image.gaussian_filter(input, [1.0, 1.0],
output = otype)
output2 = numarray.nd_image.gaussian_filter(input, 1.0,
output = otype)
self.failUnless(diff(output1, output2) < eps)
def test_prewitt01(self):
"prewitt filter 1"
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
t = numarray.nd_image.correlate1d(array, [-1.0, 0.0, 1.0], 0)
t = numarray.nd_image.correlate1d(t, [1.0, 1.0, 1.0], 1)
output = numarray.nd_image.prewitt(array, 0)
self.failUnless(diff(t, output) < eps)
def test_prewitt02(self):
"prewitt filter 2"
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
t = numarray.nd_image.correlate1d(array, [-1.0, 0.0, 1.0], 0)
t = numarray.nd_image.correlate1d(t, [1.0, 1.0, 1.0], 1)
output = numarray.zeros(array.shape, type)
numarray.nd_image.prewitt(array, 0, output)
self.failUnless(diff(t, output) < eps)
def test_prewitt03(self):
"prewitt filter 3"
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
t = numarray.nd_image.correlate1d(array, [-1.0, 0.0, 1.0], 1)
t = numarray.nd_image.correlate1d(t, [1.0, 1.0, 1.0], 0)
output = numarray.nd_image.prewitt(array, 1)
self.failUnless(diff(t, output) < eps)
def test_prewitt04(self):
"prewitt filter 4"
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
t = numarray.nd_image.prewitt(array, -1)
output = numarray.nd_image.prewitt(array, 1)
self.failUnless(diff(t, output) < eps)
def test_sobel01(self):
"sobel filter 1"
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
t = numarray.nd_image.correlate1d(array, [-1.0, 0.0, 1.0], 0)
t = numarray.nd_image.correlate1d(t, [1.0, 2.0, 1.0], 1)
output = numarray.nd_image.sobel(array, 0)
self.failUnless(diff(t, output) < eps)
def test_sobel02(self):
"sobel filter 2"
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
t = numarray.nd_image.correlate1d(array, [-1.0, 0.0, 1.0], 0)
t = numarray.nd_image.correlate1d(t, [1.0, 2.0, 1.0], 1)
output = numarray.zeros(array.shape, type)
numarray.nd_image.sobel(array, 0, output)
self.failUnless(diff(t, output) < eps)
def test_sobel03(self):
"sobel filter 3"
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
t = numarray.nd_image.correlate1d(array, [-1.0, 0.0, 1.0], 1)
t = numarray.nd_image.correlate1d(t, [1.0, 2.0, 1.0], 0)
output = numarray.zeros(array.shape, type)
output = numarray.nd_image.sobel(array, 1)
self.failUnless(diff(t, output) < eps)
def test_sobel04(self):
"sobel filter 4"
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
t = numarray.nd_image.sobel(array, -1)
output = numarray.nd_image.sobel(array, 1)
self.failUnless(diff(t, output) < eps)
def test_laplace01(self):
"laplace filter 1"
for type in [numarray.Int32, numarray.Float32, numarray.Float64]:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type) * 100
tmp1 = numarray.nd_image.correlate1d(array, [1, -2, 1], 0)
tmp2 = numarray.nd_image.correlate1d(array, [1, -2, 1], 1)
output = numarray.nd_image.laplace(array)
self.failUnless(diff(tmp1 + tmp2, output) < eps)
def test_laplace02(self):
"laplace filter 2"
for type in [numarray.Int32, numarray.Float32, numarray.Float64]:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type) * 100
tmp1 = numarray.nd_image.correlate1d(array, [1, -2, 1], 0)
tmp2 = numarray.nd_image.correlate1d(array, [1, -2, 1], 1)
output = numarray.zeros(array.shape, type)
numarray.nd_image.laplace(array, output = output)
self.failUnless(diff(tmp1 + tmp2, output) < eps)
def test_gaussian_laplace01(self):
"gaussian laplace filter 1"
for type in [numarray.Int32, numarray.Float32, numarray.Float64]:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type) * 100
tmp1 = numarray.nd_image.gaussian_filter(array, 1.0, [2, 0])
tmp2 = numarray.nd_image.gaussian_filter(array, 1.0, [0, 2])
output = numarray.nd_image.gaussian_laplace(array, 1.0)
self.failUnless(diff(tmp1 + tmp2, output) < eps)
def test_gaussian_laplace02(self):
"gaussian laplace filter 2"
for type in [numarray.Int32, numarray.Float32, numarray.Float64]:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type) * 100
tmp1 = numarray.nd_image.gaussian_filter(array, 1.0, [2, 0])
tmp2 = numarray.nd_image.gaussian_filter(array, 1.0, [0, 2])
output = numarray.zeros(array.shape, type)
numarray.nd_image.gaussian_laplace(array, 1.0, output)
self.failUnless(diff(tmp1 + tmp2, output) < eps)
def test_generic_laplace01(self):
"generic laplace filter 1"
def derivative2(input, axis, output, mode, cval, a, b):
sigma = [a, b / 2.0]
input = numarray.asarray(input)
order = [0] * input.rank
order[axis] = 2
return numarray.nd_image.gaussian_filter(input, sigma, order,
output, mode, cval)
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
output = numarray.zeros(array.shape, type)
tmp = numarray.nd_image.generic_laplace(array, derivative2,
extra_arguments = (1.0,), extra_keywords = {'b': 2.0})
numarray.nd_image.gaussian_laplace(array, 1.0, output)
self.failUnless(diff(tmp, output) < eps)
def test_gaussian_gradient_magnitude01(self):
"gaussian gradient magnitude filter 1"
for type in [numarray.Int32, numarray.Float32, numarray.Float64]:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type) * 100
tmp1 = numarray.nd_image.gaussian_filter(array, 1.0, [1, 0])
tmp2 = numarray.nd_image.gaussian_filter(array, 1.0, [0, 1])
output = numarray.nd_image.gaussian_gradient_magnitude(array,
1.0)
true = tmp1 * tmp1 + tmp2 * tmp2
numarray.sqrt(true, true)
self.failUnless(diff(true, output) < eps)
def test_gaussian_gradient_magnitude02(self):
"gaussian gradient magnitude filter 2"
for type in [numarray.Int32, numarray.Float32, numarray.Float64]:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type) * 100
tmp1 = numarray.nd_image.gaussian_filter(array, 1.0, [1, 0])
tmp2 = numarray.nd_image.gaussian_filter(array, 1.0, [0, 1])
output = numarray.zeros(array.shape, type)
numarray.nd_image.gaussian_gradient_magnitude(array, 1.0,
output)
true = tmp1 * tmp1 + tmp2 * tmp2
numarray.sqrt(true, true)
self.failUnless(diff(true, output) < eps)
def test_generic_gradient_magnitude01(self):
"generic gradient magnitude 1"
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], numarray.Float64)
def derivative(input, axis, output, mode, cval, a, b):
sigma = [a, b / 2.0]
input = numarray.asarray(input)
order = [0] * input.rank
order[axis] = 1
return numarray.nd_image.gaussian_filter(input, sigma, order,
output, mode, cval)
tmp1 = numarray.nd_image.gaussian_gradient_magnitude(array, 1.0)
tmp2 = numarray.nd_image.generic_gradient_magnitude(array,
derivative, extra_arguments = (1.0,),
extra_keywords = {'b': 2.0})
self.failUnless(diff(tmp1, tmp2) < eps)
def test_uniform01(self):
"uniform filter 1"
array = numarray.array([2, 4, 6])
size = 2
output = numarray.nd_image.uniform_filter1d(array, size,
origin = -1)
self.failUnless(diff([3, 5, 6], output) < eps)
def test_uniform02(self):
"uniform filter 2"
array = numarray.array([1, 2, 3])
filter_shape = [0]
output = numarray.nd_image.uniform_filter(array, filter_shape)
self.failUnless(diff(array, output) < eps)
def test_uniform03(self):
"uniform filter 3"
array = numarray.array([1, 2, 3])
filter_shape = [1]
output = numarray.nd_image.uniform_filter(array, filter_shape)
self.failUnless(diff(array, output) < eps)
def test_uniform04(self):
"uniform filter 4"
array = numarray.array([2, 4, 6])
filter_shape = [2]
output = numarray.nd_image.uniform_filter(array, filter_shape)
self.failUnless(diff([2, 3, 5], output) < eps)
def test_uniform05(self):
"uniform filter 5"
array = []
filter_shape = [1]
output = numarray.nd_image.uniform_filter(array, filter_shape)
self.failUnless(diff([], output) < eps)
def test_uniform06(self):
"uniform filter 6"
filter_shape = [2, 2]
for type1 in self.types:
array = numarray.array([[4, 8, 12],
[16, 20, 24]], type1)
for type2 in self.types:
output = numarray.nd_image.uniform_filter(array,
filter_shape, output = type2)
error = diff([[4, 6, 10], [10, 12, 16]], output)
self.failUnless(error < eps and output.type() == type2)
def test_minimum_filter01(self):
"minimum filter 1"
array = numarray.array([1, 2, 3, 4, 5])
filter_shape = numarray.array([2])
output = numarray.nd_image.minimum_filter(array, filter_shape)
self.failUnless(diff([1, 1, 2, 3, 4], output) < eps)
def test_minimum_filter02(self):
"minimum filter 2"
array = numarray.array([1, 2, 3, 4, 5])
filter_shape = numarray.array([3])
output = numarray.nd_image.minimum_filter(array, filter_shape)
self.failUnless(diff([1, 1, 2, 3, 4], output) < eps)
def test_minimum_filter03(self):
"minimum filter 3"
array = numarray.array([3, 2, 5, 1, 4])
filter_shape = numarray.array([2])
output = numarray.nd_image.minimum_filter(array, filter_shape)
self.failUnless(diff([3, 2, 2, 1, 1], output) < eps)
def test_minimum_filter04(self):
"minimum filter 4"
array = numarray.array([3, 2, 5, 1, 4])
filter_shape = numarray.array([3])
output = numarray.nd_image.minimum_filter(array, filter_shape)
self.failUnless(diff([2, 2, 1, 1, 1], output) < eps)
def test_minimum_filter05(self):
"minimum filter 5"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
filter_shape = numarray.array([2, 3])
output = numarray.nd_image.minimum_filter(array, filter_shape)
self.failUnless(diff([[2, 2, 1, 1, 1],
[2, 2, 1, 1, 1],
[5, 3, 3, 1, 1]], output) < eps)
def test_minimum_filter06(self):
"minimum filter 6"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 1, 1], [1, 1, 1]]
output = numarray.nd_image.minimum_filter(array,
footprint = footprint)
self.failUnless(diff([[2, 2, 1, 1, 1],
[2, 2, 1, 1, 1],
[5, 3, 3, 1, 1]], output) < eps)
def test_minimum_filter07(self):
"minimum filter 7"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.minimum_filter(array,
footprint = footprint)
self.failUnless(diff([[2, 2, 1, 1, 1],
[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1]], output) < eps)
def test_minimum_filter08(self):
"minimum filter 8"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.minimum_filter(array,
footprint = footprint, origin = -1)
self.failUnless(diff([[3, 1, 3, 1, 1],
[5, 3, 3, 1, 1],
[3, 3, 1, 1, 1]], output) < eps)
def test_minimum_filter09(self):
"minimum filter 9"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.minimum_filter(array,
footprint = footprint, origin = [-1, 0])
self.failUnless(diff([[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1],
[5, 3, 3, 1, 1]], output) < eps)
def test_maximum_filter01(self):
"maximum filter 1"
array = numarray.array([1, 2, 3, 4, 5])
filter_shape = numarray.array([2])
output = numarray.nd_image.maximum_filter(array, filter_shape)
self.failUnless(diff([1, 2, 3, 4, 5], output) < eps)
def test_maximum_filter02(self):
"maximum filter 2"
array = numarray.array([1, 2, 3, 4, 5])
filter_shape = numarray.array([3])
output = numarray.nd_image.maximum_filter(array, filter_shape)
self.failUnless(diff([2, 3, 4, 5, 5], output) < eps)
def test_maximum_filter03(self):
"maximum filter 3"
array = numarray.array([3, 2, 5, 1, 4])
filter_shape = numarray.array([2])
output = numarray.nd_image.maximum_filter(array, filter_shape)
self.failUnless(diff([3, 3, 5, 5, 4], output) < eps)
def test_maximum_filter04(self):
"maximum filter 4"
array = numarray.array([3, 2, 5, 1, 4])
filter_shape = numarray.array([3])
output = numarray.nd_image.maximum_filter(array, filter_shape)
self.failUnless(diff([3, 5, 5, 5, 4], output) < eps)
def test_maximum_filter05(self):
"maximum filter 5"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
filter_shape = numarray.array([2, 3])
output = numarray.nd_image.maximum_filter(array, filter_shape)
self.failUnless(diff([[3, 5, 5, 5, 4],
[7, 9, 9, 9, 5],
[8, 9, 9, 9, 7]], output) < eps)
def test_maximum_filter06(self):
"maximum filter 6"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 1, 1], [1, 1, 1]]
output = numarray.nd_image.maximum_filter(array,
footprint = footprint)
self.failUnless(diff([[3, 5, 5, 5, 4],
[7, 9, 9, 9, 5],
[8, 9, 9, 9, 7]], output) < eps)
def test_maximum_filter07(self):
"maximum filter 7"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.maximum_filter(array,
footprint = footprint)
self.failUnless(diff([[3, 5, 5, 5, 4],
[7, 7, 9, 9, 5],
[7, 9, 8, 9, 7]], output) < eps)
def test_maximum_filter08(self):
"maximum filter 8"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.maximum_filter(array,
footprint = footprint, origin = -1)
self.failUnless(diff([[7, 9, 9, 5, 5],
[9, 8, 9, 7, 5],
[8, 8, 7, 7, 7]], output) < eps)
def test_maximum_filter09(self):
"maximum filter 9"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.maximum_filter(array,
footprint = footprint, origin = [-1, 0])
self.failUnless(diff([[7, 7, 9, 9, 5],
[7, 9, 8, 9, 7],
[8, 8, 8, 7, 7]], output) < eps)
def test_rank01(self):
"rank filter 1"
array = numarray.array([1, 2, 3, 4, 5])
output = numarray.nd_image.rank_filter(array, 1, size = 2)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.percentile_filter(array, 100, size = 2)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.median_filter(array, 2)
self.failUnless(diff(array, output) < eps)
def test_rank02(self):
"rank filter 2"
array = numarray.array([1, 2, 3, 4, 5])
output = numarray.nd_image.rank_filter(array, 1, size = [3])
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.percentile_filter(array, 50, size = 3)
self.failUnless(diff(array, output) < eps)
output = numarray.nd_image.median_filter(array, (3,))
self.failUnless(diff(array, output) < eps)
def test_rank03(self):
"rank filter 3"
array = numarray.array([3, 2, 5, 1, 4])
output = numarray.nd_image.rank_filter(array, 1, size = [2])
self.failUnless(diff([3, 3, 5, 5, 4], output) < eps)
output = numarray.nd_image.percentile_filter(array, 100, size = 2)
self.failUnless(diff([3, 3, 5, 5, 4], output) < eps)
def test_rank04(self):
"rank filter 4"
array = numarray.array([3, 2, 5, 1, 4])
true = [3, 3, 2, 4, 4]
output = numarray.nd_image.rank_filter(array, 1, size = 3)
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.percentile_filter(array, 50, size = 3)
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.median_filter(array, size = 3)
self.failUnless(diff(true, output) < eps)
def test_rank05(self):
"rank filter 5"
array = numarray.array([3, 2, 5, 1, 4])
true = [3, 3, 2, 4, 4]
output = numarray.nd_image.rank_filter(array, -2, size = 3)
self.failUnless(diff(true, output) < eps)
def test_rank06(self):
"rank filter 6"
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]])
true = [[2, 2, 1, 1, 1],
[3, 3, 2, 1, 1],
[5, 5, 3, 3, 1]]
output = numarray.nd_image.rank_filter(array, 1, size = [2, 3])
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.percentile_filter(array, 17,
size = (2, 3))
self.failUnless(diff(true, output) < eps)
def test_rank07(self):
"rank filter 7"
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]])
true = [[3, 5, 5, 5, 4],
[5, 5, 7, 5, 4],
[6, 8, 8, 7, 5]]
output = numarray.nd_image.rank_filter(array, -2, size = [2, 3])
self.failUnless(diff(true, output) < eps)
def test_rank08(self):
"median filter 8"
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]])
true = [[3, 3, 2, 4, 4],
[5, 5, 5, 4, 4],
[5, 6, 7, 5, 5]]
kernel = numarray.array([2, 3])
output = numarray.nd_image.percentile_filter(array, 50.0,
size = (2, 3))
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.rank_filter(array, 3, size = (2, 3))
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.median_filter(array, size = (2, 3))
self.failUnless(diff(true, output) < eps)
def test_rank09(self):
"rank filter 9"
true = [[3, 3, 2, 4, 4],
[3, 5, 2, 5, 1],
[5, 5, 8, 3, 5]]
footprint = [[1, 0, 1], [0, 1, 0]]
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
output = numarray.nd_image.rank_filter(array, 1,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.percentile_filter(array, 35,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
def test_rank10(self):
"rank filter 10"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
true = [[2, 2, 1, 1, 1],
[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1]]
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.rank_filter(array, 0,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.percentile_filter(array, 0.0,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
def test_rank11(self):
"rank filter 11"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
true = [[3, 5, 5, 5, 4],
[7, 7, 9, 9, 5],
[7, 9, 8, 9, 7]]
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.rank_filter(array, -1,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.percentile_filter(array, 100.0,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
def test_rank12(self):
"rank filter 12"
true = [[3, 3, 2, 4, 4],
[3, 5, 2, 5, 1],
[5, 5, 8, 3, 5]]
footprint = [[1, 0, 1], [0, 1, 0]]
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
output = numarray.nd_image.rank_filter(array, 1,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.percentile_filter(array, 50.0,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
output = numarray.nd_image.median_filter(array,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
def test_rank13(self):
"rank filter 13"
true = [[5, 2, 5, 1, 1],
[5, 8, 3, 5, 5],
[6, 6, 5, 5, 5]]
footprint = [[1, 0, 1], [0, 1, 0]]
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
output = numarray.nd_image.rank_filter(array, 1,
footprint = footprint, origin = -1)
self.failUnless(diff(true, output) < eps)
def test_rank14(self):
"rank filter 14"
true = [[3, 5, 2, 5, 1],
[5, 5, 8, 3, 5],
[5, 6, 6, 5, 5]]
footprint = [[1, 0, 1], [0, 1, 0]]
for type in self.types:
array = numarray.array([[3, 2, 5, 1, 4],
[5, 8, 3, 7, 1],
[5, 6, 9, 3, 5]], type)
output = numarray.nd_image.rank_filter(array, 1,
footprint = footprint, origin = [-1, 0])
self.failUnless(diff(true, output) < eps)
def test_generic_filter1d01(self):
"generic 1d filter 1"
weights = numarray.array([1.1, 2.2, 3.3])
def _filter_func(input, output, fltr, total):
fltr = fltr / total
for ii in range(input.shape[0] - 2):
output[ii] = input[ii] * fltr[0]
output[ii] += input[ii + 1] * fltr[1]
output[ii] += input[ii + 2] * fltr[2]
for type in self.types:
a = numarray.arange(12, shape = (3,4), type = type)
r1 = numarray.nd_image.correlate1d(a, weights / weights.sum(), 0,
origin = -1)
r2 = numarray.nd_image.generic_filter1d(a, _filter_func, 3,
axis = 0, origin = -1, extra_arguments = (weights,),
extra_keywords = {'total': weights.sum()})
self.failUnless(diff(r1, r2) < eps)
def test_generic_filter01(self):
"generic filter 1"
filter = numarray.array([[1.0, 2.0], [3.0, 4.0]])
footprint = numarray.array([[1, 0], [0, 1]])
cf = numarray.compress(footprint, filter)
def _filter_func(buffer, weights, total = 1.0):
weights = cf / total
return (buffer * weights).sum()
for type in self.types:
a = numarray.arange(12, shape = (3,4), type = type)
r1 = numarray.nd_image.correlate(a, filter * footprint) / 5
r2 = numarray.nd_image.generic_filter(a, _filter_func,
footprint = footprint, extra_arguments = (cf,),
extra_keywords = {'total': cf.sum()})
self.failUnless(diff(r1, r2) < eps)
def test_extend01(self):
"line extension 1"
array = numarray.array([1, 2, 3])
weights = numarray.array([1, 0])
true_values = [[1, 1, 2],
[3, 1, 2],
[1, 1, 2],
[0, 1, 2]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate1d(array, weights, 0,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend02(self):
"line extension 2"
array = numarray.array([1, 2, 3])
weights = numarray.array([1, 0, 0, 0, 0, 0, 0, 0])
true_values = [[1, 1, 1],
[3, 1, 2],
[3, 3, 2],
[0, 0, 0]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate1d(array, weights, 0,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend03(self):
"line extension 3"
array = numarray.array([1, 2, 3])
weights = numarray.array([0, 0, 1])
true_values = [[2, 3, 3],
[2, 3, 1],
[2, 3, 3],
[2, 3, 0]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate1d(array, weights, 0,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend04(self):
"line extension 4"
array = numarray.array([1, 2, 3])
weights = numarray.array([0, 0, 0, 0, 0, 0, 0, 0, 1])
true_values = [[3, 3, 3],
[2, 3, 1],
[2, 1, 1],
[0, 0, 0]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate1d(array, weights, 0,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend05(self):
"line extension 5"
array = numarray.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
weights = numarray.array([[1, 0], [0, 0]])
true_values = [[[1, 1, 2], [1, 1, 2], [4, 4, 5]],
[[9, 7, 8], [3, 1, 2], [6, 4, 5]],
[[1, 1, 2], [1, 1, 2], [4, 4, 5]],
[[0, 0, 0], [0, 1, 2], [0, 4, 5]]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate(array, weights,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend06(self):
"line extension 6"
array = numarray.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
weights = numarray.array([[0, 0, 0], [0, 0, 0], [0, 0, 1]])
true_values = [[[5, 6, 6], [8, 9, 9], [8, 9, 9]],
[[5, 6, 4], [8, 9, 7], [2, 3, 1]],
[[5, 6, 6], [8, 9, 9], [8, 9, 9]],
[[5, 6, 0], [8, 9, 0], [0, 0, 0]]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate(array, weights,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend07(self):
"line extension 7"
array = numarray.array([1, 2, 3])
weights = numarray.array([0, 0, 0, 0, 0, 0, 0, 0, 1])
true_values = [[3, 3, 3],
[2, 3, 1],
[2, 1, 1],
[0, 0, 0]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate(array, weights,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend08(self):
"line extension 8"
array = numarray.array([[1], [2], [3]])
weights = numarray.array([[0], [0], [0], [0], [0], [0], [0],
[0], [1]])
true_values = [[[3], [3], [3]],
[[2], [3], [1]],
[[2], [1], [1]],
[[0], [0], [0]]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate(array, weights,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend09(self):
"line extension 9"
array = numarray.array([1, 2, 3])
weights = numarray.array([0, 0, 0, 0, 0, 0, 0, 0, 1])
true_values = [[3, 3, 3],
[2, 3, 1],
[2, 1, 1],
[0, 0, 0]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate(array, weights,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_extend10(self):
"line extension 10"
array = numarray.array([[1], [2], [3]])
weights = numarray.array([[0], [0], [0], [0], [0], [0], [0],
[0], [1]])
true_values = [[[3], [3], [3]],
[[2], [3], [1]],
[[2], [1], [1]],
[[0], [0], [0]]]
for mode, true_value in zip(self.modes, true_values):
output = numarray.nd_image.correlate(array, weights,
mode = mode, cval = 0)
self.failUnless(diff(output, true_value) < eps)
def test_fourier_gaussian_real01(self):
"gaussian fourier filter for real transforms 1"
for shape in [(32, 16), (31, 15)]:
for type in [numarray.Float32, numarray.Float64]:
a = numarray.zeros(shape, type)
a[0, 0] = 1.0
a = numarray.fft.real_fft(a, shape[0], 0)
a = numarray.fft.fft(a, shape[1], 1)
a = numarray.nd_image.fourier_gaussian(a, [5.0, 2.5],
shape[0], 0)
a = numarray.fft.inverse_fft(a, shape[1], 1)
a = numarray.fft.inverse_real_fft(a, shape[0], 0)
self.failUnless(diff(numarray.nd_image.sum(a), 1.0) < eps)
def test_fourier_gaussian_complex01(self):
"gaussian fourier filter for complex transforms 1"
for shape in [(32, 16), (31, 15)]:
for type in [numarray.Complex32, numarray.Complex64]:
a = numarray.zeros(shape, type)
a[0, 0] = 1.0
a = numarray.fft.fft(a, shape[0], 0)
a = numarray.fft.fft(a, shape[1], 1)
a = numarray.nd_image.fourier_gaussian(a, [5.0, 2.5], -1,
0)
a = numarray.fft.inverse_fft(a, shape[1], 1)
a = numarray.fft.inverse_fft(a, shape[0], 0)
error = diff(numarray.nd_image.sum(a.real), 1.0)
self.failUnless(error < eps)
def test_fourier_uniform_real01(self):
"uniform fourier filter for real transforms 1"
for shape in [(32, 16), (31, 15)]:
for type in [numarray.Float32, numarray.Float64]:
a = numarray.zeros(shape, type)
a[0, 0] = 1.0
a = numarray.fft.real_fft(a, shape[0], 0)
a = numarray.fft.fft(a, shape[1], 1)
a = numarray.nd_image.fourier_uniform(a, [5.0, 2.5],
shape[0], 0)
a = numarray.fft.inverse_fft(a, shape[1], 1)
a = numarray.fft.inverse_real_fft(a, shape[0], 0)
self.failUnless(diff(numarray.nd_image.sum(a), 1.0) < eps)
def test_fourier_uniform_complex01(self):
"uniform fourier filter for complex transforms 1"
for shape in [(32, 16), (31, 15)]:
for type in [numarray.Complex32, numarray.Complex64]:
a = numarray.zeros(shape, type)
a[0, 0] = 1.0
a = numarray.fft.fft(a, shape[0], 0)
a = numarray.fft.fft(a, shape[1], 1)
a = numarray.nd_image.fourier_uniform(a, [5.0, 2.5], -1, 0)
a = numarray.fft.inverse_fft(a, shape[1], 1)
a = numarray.fft.inverse_fft(a, shape[0], 0)
error = diff(numarray.nd_image.sum(a.real), 1.0)
self.failUnless(error < eps)
def test_fourier_shift_real01(self):
"shift filter for real transforms 1"
for shape in [(32, 16), (31, 15)]:
for type in [numarray.Float32, numarray.Float64]:
true = numarray.arange(shape[0] * shape[1],
shape = shape, type = type)
a = numarray.fft.real_fft(true, shape[0], 0)
a = numarray.fft.fft(a, shape[1], 1)
a = numarray.nd_image.fourier_shift(a, [1, 1], shape[0], 0)
a = numarray.fft.inverse_fft(a, shape[1], 1)
a = numarray.fft.inverse_real_fft(a, shape[0], 0)
error1 = diff(a[1:, 1:], true[:-1, :-1])
error2 = diff(a.imag, numarray.zeros(shape))
self.failUnless(error1 < 1e-10 and error2 < 1e-10)
def test_fourier_shift_complex01(self):
"shift filter for complex transforms 1"
for shape in [(32, 16), (31, 15)]:
for type in [numarray.Complex32, numarray.Complex64]:
true = numarray.arange(shape[0] * shape[1],
shape = shape, type = type)
a = numarray.fft.fft(true, shape[0], 0)
a = numarray.fft.fft(a, shape[1], 1)
a = numarray.nd_image.fourier_shift(a, [1, 1], -1, 0)
a = numarray.fft.inverse_fft(a, shape[1], 1)
a = numarray.fft.inverse_fft(a, shape[0], 0)
error1 = diff(a.real[1:, 1:], true[:-1, :-1])
error2 = diff(a.imag, numarray.zeros(shape))
self.failUnless(error1 < 1e-10 and error2 < 1e-10)
def test_fourier_ellipsoid_real01(self):
"ellipsoid fourier filter for real transforms 1"
for shape in [(32, 16), (31, 15)]:
for type in [numarray.Float32, numarray.Float64]:
a = numarray.zeros(shape, type)
a[0, 0] = 1.0
a = numarray.fft.real_fft(a, shape[0], 0)
a = numarray.fft.fft(a, shape[1], 1)
a = numarray.nd_image.fourier_ellipsoid(a, [5.0, 2.5],
shape[0], 0)
a = numarray.fft.inverse_fft(a, shape[1], 1)
a = numarray.fft.inverse_real_fft(a, shape[0], 0)
self.failUnless(diff(numarray.nd_image.sum(a), 1.0) < eps)
def test_fourier_ellipsoid_complex01(self):
"ellipsoid fourier filter for complex transforms 1"
for shape in [(32, 16), (31, 15)]:
for type in [numarray.Complex32, numarray.Complex64]:
a = numarray.zeros(shape, type)
a[0, 0] = 1.0
a = numarray.fft.fft(a, shape[0], 0)
a = numarray.fft.fft(a, shape[1], 1)
a = numarray.nd_image.fourier_ellipsoid(a, [5.0, 2.5], -1,
0)
a = numarray.fft.inverse_fft(a, shape[1], 1)
a = numarray.fft.inverse_fft(a, shape[0], 0)
error = diff(numarray.nd_image.sum(a.real), 1.0)
self.failUnless(error < eps)
def test_spline01(self):
"spline filter 1"
for type in self.types:
data = numarray.ones([], type)
for order in range(2, 6):
out = numarray.nd_image.spline_filter(data, order = order)
self.failUnless(diff(out, 1)< eps and
out.type() == numarray.Float64)
def test_spline02(self):
"spline filter 2"
for type in self.types:
data = numarray.array([1])
for order in range(2, 6):
out = numarray.nd_image.spline_filter(data, order = order)
self.failUnless(diff(out, [1]) < eps and
out.type() == numarray.Float64)
def test_spline03(self):
"spline filter 3"
for type in self.types:
data = numarray.ones([], type)
for order in range(2, 6):
out = numarray.nd_image.spline_filter(data, order,
output = type)
self.failUnless(diff(out, 1) < eps and
out.type() == type)
def test_spline04(self):
"spline filter 4"
for type in self.types:
data = numarray.ones([4], type)
for order in range(2, 6):
out = numarray.nd_image.spline_filter(data, order)
self.failUnless(diff(out, [1, 1, 1, 1]) < eps)
def test_spline05(self):
"spline filter 5"
for type in self.types:
data = numarray.ones([4, 4], type)
for order in range(2, 6):
out = numarray.nd_image.spline_filter(data, order = order)
self.failUnless(diff(out, [[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]]) < eps)
def test_geometric_transform01(self):
"geometric transform 1"
data = numarray.array([1])
def mapping(x):
return x
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
data.shape,
order=order)
self.failUnless(diff(out, [1]) < eps)
def test_geometric_transform02(self):
"geometric transform 2"
data = numarray.ones([4])
def mapping(x):
return x
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
data.shape, order=order)
self.failUnless(diff(out, [1, 1, 1, 1]) < eps)
def test_geometric_transform03(self):
"geometric transform 3"
data = numarray.ones([4])
def mapping(x):
return (x[0] - 1,)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
data.shape, order=order)
self.failUnless(diff(out, [0, 1, 1, 1]) < eps)
def test_geometric_transform04(self):
"geometric transform 4"
data = numarray.array([4, 1, 3, 2])
def mapping(x):
return (x[0] - 1,)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
data.shape, order=order)
self.failUnless(diff(out, [0, 4, 1, 3]) < eps)
def test_geometric_transform05(self):
"geometric transform 5"
data = numarray.array([[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]])
def mapping(x):
return (x[0], x[1] - 1)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
data.shape, order=order)
self.failUnless(diff(out, [[0, 1, 1, 1],
[0, 1, 1, 1],
[0, 1, 1, 1]]) < eps)
def test_geometric_transform06(self):
"geometric transform 6"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
def mapping(x):
return (x[0], x[1] - 1)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
data.shape, order=order)
self.failUnless(diff(out, [[0, 4, 1, 3],
[0, 7, 6, 8],
[0, 3, 5, 3]]) < eps)
def test_geometric_transform07(self):
"geometric transform 7"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
def mapping(x):
return (x[0] - 1, x[1])
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
data.shape, order=order)
self.failUnless(diff(out, [[0, 0, 0, 0],
[4, 1, 3, 2],
[7, 6, 8, 5]]) < eps)
def test_geometric_transform08(self):
"geometric transform 8"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
def mapping(x):
return (x[0] - 1, x[1] - 1)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
data.shape, order=order)
self.failUnless(diff(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) < eps)
def test_geometric_transform10(self):
"geometric transform 10"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
def mapping(x):
return (x[0] - 1, x[1] - 1)
for order in range(0, 6):
if (order > 1):
filtered = numarray.nd_image.spline_filter(data,
order=order)
else:
filtered = data
out = numarray.nd_image.geometric_transform(filtered, mapping,
data.shape, order=order, prefilter = False)
self.failUnless(diff(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) < eps)
def test_geometric_transform13(self):
"geometric transform 13"
data = numarray.ones([2], numarray.Float64)
def mapping(x):
return (x[0] / 2,)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
[4], order=order)
self.failUnless(diff(out, [1, 1, 1, 1]) < eps)
def test_geometric_transform14(self):
"geometric transform 14"
data = [1, 5, 2, 6, 3, 7, 4, 4]
def mapping(x):
return (2 * x[0],)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
[4], order=order)
self.failUnless(diff(out, [1, 2, 3, 4]) < eps)
def test_geometric_transform15(self):
"geometric transform 15"
data = [1, 2, 3, 4]
def mapping(x):
return (x[0] / 2,)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
[8], order=order)
self.failUnless(diff(out[::2], [1, 2, 3, 4]) < eps)
def test_geometric_transform16(self):
"geometric transform 16"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9.0, 10, 11, 12]]
def mapping(x):
return (x[0], x[1] * 2)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
(3, 2), order=order)
self.failUnless(diff(out, [[1, 3], [5, 7], [9, 11]]) < eps)
def test_geometric_transform17(self):
"geometric transform 17"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
def mapping(x):
return (x[0] * 2, x[1])
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
(1, 4), order=order)
self.failUnless(diff(out, [[1, 2, 3, 4]]) < eps)
def test_geometric_transform18(self):
"geometric transform 18"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
def mapping(x):
return (x[0] * 2, x[1] * 2)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
(1, 2), order=order)
self.failUnless(diff(out, [[1, 3]]) < eps)
def test_geometric_transform19(self):
"geometric transform 19"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
def mapping(x):
return (x[0], x[1] / 2)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
(3, 8), order=order)
self.failUnless(diff(out[..., ::2], data) < eps)
def test_geometric_transform20(self):
"geometric transform 20"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
def mapping(x):
return (x[0] / 2, x[1])
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
(6, 4), order=order)
self.failUnless(diff(out[::2, ...], data) < eps)
def test_geometric_transform21(self):
"geometric transform 21"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
def mapping(x):
return (x[0] / 2, x[1] / 2)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
(6, 8), order=order)
self.failUnless(diff(out[::2, ::2], data) < eps)
def test_geometric_transform22(self):
"geometric transform 22"
data = numarray.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]], numarray.Float64)
def mapping1(x):
return (x[0] / 2, x[1] / 2)
def mapping2(x):
return (x[0] * 2, x[1] * 2)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping1,
(6, 8), order=order)
out = numarray.nd_image.geometric_transform(out, mapping2,
(3, 4), order=order)
error = diff(out, data)
self.failUnless(diff(out, data) < eps)
def test_geometric_transform23(self):
"geometric transform 23"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
def mapping(x):
return (1, x[0] * 2)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
(2,), order=order)
self.failUnless(diff(out, [5, 7]) < eps)
def test_geometric_transform24(self):
"geometric transform 24"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
def mapping(x, a, b):
return (a, x[0] * b)
for order in range(0, 6):
out = numarray.nd_image.geometric_transform(data, mapping,
(2,), order=order, extra_arguments = (1,),
extra_keywords = {'b': 2})
self.failUnless(diff(out, [5, 7]) < eps)
def test_map_coordinates01(self):
"map coordinates 1"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
idx = numarray.indices(data.shape)
idx -= 1
for order in range(0, 6):
out = numarray.nd_image.map_coordinates(data, idx, order=order)
self.failUnless(diff(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) < eps)
def test_map_coordinates02(self):
"map coordinates 2"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
idx = numarray.indices(data.shape, numarray.Float64)
idx -= 0.5
for order in range(0, 6):
out1 = numarray.nd_image.shift(data, 0.5, order=order)
out2 = numarray.nd_image.map_coordinates(data, idx,
order=order)
self.failUnless(diff(out1, out2) < eps)
def test_affine_transform01(self):
"affine_transform 1"
data = numarray.array([1])
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1]],
order=order)
self.failUnless(diff(out, [1]) < eps)
def test_affine_transform02(self):
"affine transform 2"
data = numarray.ones([4])
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1]],
order=order)
self.failUnless(diff(out, [1, 1, 1, 1]) < eps)
def test_affine_transform03(self):
"affine transform 3"
data = numarray.ones([4])
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1]], -1,
order=order)
self.failUnless(diff(out, [0, 1, 1, 1]) < eps)
def test_affine_transform04(self):
"affine transform 4"
data = numarray.array([4, 1, 3, 2])
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1]], -1,
order=order)
self.failUnless(diff(out, [0, 4, 1, 3]) < eps)
def test_affine_transform05(self):
"affine transform 5"
data = numarray.array([[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]])
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1, 0],
[0, 1]],
[0, -1], order=order)
self.failUnless(diff(out, [[0, 1, 1, 1],
[0, 1, 1, 1],
[0, 1, 1, 1]]) < eps)
def test_affine_transform06(self):
"affine transform 6"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1, 0],
[0, 1]],
[0, -1], order=order)
self.failUnless(diff(out, [[0, 4, 1, 3],
[0, 7, 6, 8],
[0, 3, 5, 3]]) < eps)
def test_affine_transform07(self):
"affine transform 7"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1, 0],
[0, 1]],
[-1, 0], order=order)
self.failUnless(diff(out, [[0, 0, 0, 0],
[4, 1, 3, 2],
[7, 6, 8, 5]]) < eps)
def test_affine_transform08(self):
"affine transform 8"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1, 0],
[0, 1]],
[-1, -1], order=order)
self.failUnless(diff(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) < eps)
def test_affine_transform09(self):
"affine transform 9"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
if (order > 1):
filtered = numarray.nd_image.spline_filter(data,
order=order)
else:
filtered = data
out = numarray.nd_image.affine_transform(filtered,[[1, 0],
[0, 1]],
[-1, -1], order=order, prefilter = False)
self.failUnless(diff(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) < eps)
def test_affine_transform10(self):
"affine transform 10"
data = numarray.ones([2], numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[0.5]],
output_shape = (4,), order=order)
self.failUnless(diff(out, [1, 1, 1, 1]) < eps)
def test_affine_transform11(self):
"affine transform 11"
data = [1, 5, 2, 6, 3, 7, 4, 4]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[2]], 0, (4,),
order=order)
self.failUnless(diff(out, [1, 2, 3, 4]) < eps)
def test_affine_transform12(self):
"affine transform 12"
data = [1, 2, 3, 4]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[0.5]], 0,
(8,), order=order)
self.failUnless(diff(out[::2], [1, 2, 3, 4]) < eps)
def test_affine_transform13(self):
"affine transform 13"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9.0, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1, 0],
[0, 2]], 0,
(3, 2), order=order)
self.failUnless(diff(out, [[1, 3], [5, 7], [9, 11]]) < eps)
def test_affine_transform14(self):
"affine transform 14"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[2, 0],
[0, 1]], 0,
(1, 4), order=order)
self.failUnless(diff(out, [[1, 2, 3, 4]]) < eps)
def test_affine_transform15(self):
"affine transform 15"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[2, 0],
[0, 2]], 0,
(1, 2), order=order)
self.failUnless(diff(out, [[1, 3]]) < eps)
def test_affine_transform16(self):
"affine transform 16"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[1, 0.0],
[0, 0.5]], 0,
(3, 8), order=order)
self.failUnless(diff(out[..., ::2], data) < eps)
def test_affine_transform17(self):
"affine transform 17"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[0.5, 0],
[0, 1]], 0,
(6, 4), order=order)
self.failUnless(diff(out[::2, ...], data) < eps)
def test_affine_transform18(self):
"affine transform 18"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data,
[[0.5, 0],
[0, 0.5]], 0,
(6, 8), order=order)
self.failUnless(diff(out[::2, ::2], data) < eps)
def test_affine_transform19(self):
"affine transform 19"
data = numarray.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]], numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data,
[[0.5, 0],
[0, 0.5]], 0,
(6, 8), order=order)
out = numarray.nd_image.affine_transform(out,
[[2.0, 0],
[0, 2.0]], 0,
(3, 4), order=order)
self.failUnless(diff(out, data) < eps)
def test_affine_transform20(self):
"affine transform 20"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[0], [2]], 0,
(2,), order=order)
self.failUnless(diff(out, [1, 3]) < eps)
def test_affine_transform21(self):
"affine transform 21"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [[2], [0]], 0,
(2,), order=order)
self.failUnless(diff(out, [1, 9]) < eps)
def test_shift01(self):
"shift 1"
data = numarray.array([1])
for order in range(0, 6):
out = numarray.nd_image.shift(data, [1], order=order)
self.failUnless(diff(out, [0]) < eps)
def test_shift02(self):
"shift 2"
data = numarray.ones([4])
for order in range(0, 6):
out = numarray.nd_image.shift(data, [1], order=order)
self.failUnless(diff(out, [0, 1, 1, 1]) < eps)
def test_shift03(self):
"shift 3"
data = numarray.ones([4])
for order in range(0, 6):
out = numarray.nd_image.shift(data, -1, order=order)
self.failUnless(diff(out, [1, 1, 1, 0]) < eps)
def test_shift04(self):
"shift 4"
data = numarray.array([4, 1, 3, 2])
for order in range(0, 6):
out = numarray.nd_image.shift(data, 1, order=order)
self.failUnless(diff(out, [0, 4, 1, 3]) < eps)
def test_shift05(self):
"shift 5"
data = numarray.array([[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]])
for order in range(0, 6):
out = numarray.nd_image.shift(data, [0, 1], order=order)
self.failUnless(diff(out, [[0, 1, 1, 1],
[0, 1, 1, 1],
[0, 1, 1, 1]]) < eps)
def test_shift06(self):
"shift 6"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
out = numarray.nd_image.shift(data, [0, 1], order=order)
self.failUnless(diff(out, [[0, 4, 1, 3],
[0, 7, 6, 8],
[0, 3, 5, 3]]) < eps)
def test_shift07(self):
"shift 7"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
out = numarray.nd_image.shift(data, [1, 0], order=order)
self.failUnless(diff(out, [[0, 0, 0, 0],
[4, 1, 3, 2],
[7, 6, 8, 5]]) < eps)
def test_shift08(self):
"shift 8"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
out = numarray.nd_image.shift(data, [1, 1], order=order)
self.failUnless(diff(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) < eps)
def test_shift09(self):
"shift 9"
data = numarray.array([[4, 1, 3, 2],
[7, 6, 8, 5],
[3, 5, 3, 6]])
for order in range(0, 6):
if (order > 1):
filtered = numarray.nd_image.spline_filter(data,
order=order)
else:
filtered = data
out = numarray.nd_image.shift(filtered, [1, 1], order=order,
prefilter = False)
self.failUnless(diff(out, [[0, 0, 0, 0],
[0, 4, 1, 3],
[0, 7, 6, 8]]) < eps)
def test_zoom01(self):
"zoom 1"
data = numarray.ones([2], numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.zoom(data, 2.0, order=order)
self.failUnless(diff(out, [1, 1, 1, 1]) < eps)
def test_zoom02(self):
"zoom 2"
data = [1, 5, 2, 6, 3, 7, 4, 4]
for order in range(0, 6):
out = numarray.nd_image.zoom(data, 0.5, order=order)
self.failUnless(diff(out, [1, 2, 3, 4]) < eps)
def test_zoom03(self):
"zoom 3"
data = [1, 2, 3, 4]
for order in range(0, 6):
out = numarray.nd_image.zoom(data, 2, order=order)
self.failUnless(diff(out[::2], [1, 2, 3, 4]) < eps)
def test_zoom04(self):
"zoom 4"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9.0, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.zoom(data, [1, 0.5], order=order)
self.failUnless(diff(out, [[1, 3], [5, 7], [9, 11]]) < eps)
def test_zoom05(self):
"zoom 5"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.zoom(data, [0.5, 1], order=order)
self.failUnless(diff(out, [[1, 2, 3, 4]]) < eps)
def test_zoom06(self):
"zoom 6"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.zoom(data, [0.5, 0.5], order=order)
self.failUnless(diff(out, [[1, 3]]) < eps)
def test_zoom07(self):
"zoom 7"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.zoom(data, [1, 2], order=order)
self.failUnless(diff(out[..., ::2], data) < eps)
def test_zoom08(self):
"zoom 8"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.zoom(data, [2, 1], order=order)
self.failUnless(diff(out[::2, ...], data) < eps)
def test_zoom09(self):
"zoom 9"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.zoom(data, [2, 2], order=order)
self.failUnless(diff(out[::2, ::2], data) < eps)
def test_zoom10(self):
"zoom 10"
data = numarray.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]], numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.zoom(data, [2, 2], order=order)
out = numarray.nd_image.zoom(out, [0.5, 0.5], order=order)
self.failUnless(diff(out, data) < eps)
def test_zoom_affine01(self):
"zoom by affine transformation 1"
data = [[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]]
for order in range(0, 6):
out = numarray.nd_image.affine_transform(data, [0.5, 0.5], 0,
(6, 8), order=order)
self.failUnless(diff(out[::2, ::2], data) < eps)
def test_rotate01(self):
"rotate 1"
data = numarray.array([[0, 0, 0, 0],
[0, 1, 1, 0],
[0, 0, 0, 0]], type = numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.rotate(data, 0)
self.failUnless(diff(out, data) < eps)
def test_rotate02(self):
"rotate 2"
data = numarray.array([[0, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, 0, 0]], type = numarray.Float64)
true = numarray.array([[0, 0, 0],
[0, 0, 0],
[0, 1, 0],
[0, 0, 0]], type = numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.rotate(data, 90)
self.failUnless(diff(out, true) < eps)
def test_rotate03(self):
"rotate 3"
data = numarray.array([[0, 0, 0, 0, 0],
[0, 1, 1, 0, 0],
[0, 0, 0, 0, 0]], type = numarray.Float64)
true = numarray.array([[0, 0, 0],
[0, 0, 0],
[0, 1, 0],
[0, 1, 0],
[0, 0, 0]], type = numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.rotate(data, 90)
self.failUnless(diff(out, true) < eps)
def test_rotate04(self):
"rotate 4"
data = numarray.array([[0, 0, 0, 0, 0],
[0, 1, 1, 0, 0],
[0, 0, 0, 0, 0]], type = numarray.Float64)
true = numarray.array([[0, 0, 0, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0]], type = numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.rotate(data, 90, reshape = False)
self.failUnless(diff(out, true) < eps)
def test_rotate05(self):
"rotate 5"
data = numarray.array([[[0, 0, 0, 0, 0],
[0, 1, 1, 0, 0],
[0, 0, 0, 0, 0]]] * 3,
type = numarray.Float64)
true = numarray.array([[[0, 0, 0],
[0, 0, 0],
[0, 1, 0],
[0, 1, 0],
[0, 0, 0]]] * 3, type = numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.rotate(data, 90)
self.failUnless(diff(out, true) < eps)
def test_rotate06(self):
"rotate 6"
data = numarray.array([[[0, 0, 0, 0, 0],
[0, 1, 1, 0, 0],
[0, 0, 0, 0, 0]]] * 3,
type = numarray.Float64)
true = numarray.array([[[0, 0, 0, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0]]] * 3,
type = numarray.Float64)
for order in range(0, 6):
out = numarray.nd_image.rotate(data, 90, reshape = False)
self.failUnless(diff(out, true) < eps)
def test_rotate07(self):
"rotate 7"
data = numarray.array([[[0, 0, 0, 0, 0],
[0, 1, 1, 0, 0],
[0, 0, 0, 0, 0]]] * 2,
type = numarray.Float64)
data.transpose()
true = numarray.array([[[0, 0, 0],
[0, 1, 0],
[0, 1, 0],
[0, 0, 0],
[0, 0, 0]]] * 2, type = numarray.Float64)
true.transpose()
for order in range(0, 6):
out = numarray.nd_image.rotate(data, 90, axes = (0, 1))
self.failUnless(diff(out, true) < eps)
def test_rotate08(self):
"rotate 8"
data = numarray.array([[[0, 0, 0, 0, 0],
[0, 1, 1, 0, 0],
[0, 0, 0, 0, 0]]] * 2,
type = numarray.Float64)
data.transpose()
true = numarray.array([[[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 0, 0, 0]]] * 2,
type = numarray.Float64)
true.transpose()
for order in range(0, 6):
out = numarray.nd_image.rotate(data, 90, axes = (0, 1),
reshape = False)
self.failUnless(diff(out, true) < eps)
def test_watershed_ift01(self):
"watershed_ift 1"
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.UInt8)
markers = numarray.array([[ -1, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 1, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0]],
numarray.Int8)
out = numarray.nd_image.watershed_ift(data, markers,
structure = [[1,1,1],
[1,1,1],
[1,1,1]])
error = diff([[-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, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1]], out)
self.failUnless(error < eps)
def test_watershed_ift02(self):
"watershed_ift 2"
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.UInt8)
markers = numarray.array([[ -1, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 1, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0]],
numarray.Int8)
out = numarray.nd_image.watershed_ift(data, markers)
error = diff([[-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, -1, -1, -1, -1, -1],
[-1, -1, -1, -1, -1, -1, -1]], out)
self.failUnless(error < eps)
def test_watershed_ift03(self):
"watershed_ift 3"
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.UInt8)
markers = numarray.array([[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 2, 0, 3, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, -1]],
numarray.Int8)
out = numarray.nd_image.watershed_ift(data, markers)
error = diff([[-1, -1, -1, -1, -1, -1, -1],
[-1, -1, 2, -1, 3, -1, -1],
[-1, 2, 2, 3, 3, 3, -1],
[-1, 2, 2, 3, 3, 3, -1],
[-1, 2, 2, 3, 3, 3, -1],
[-1, -1, 2, -1, 3, -1, -1],
[-1, -1, -1, -1, -1, -1, -1]], out)
self.failUnless(error < eps)
def test_watershed_ift04(self):
"watershed_ift 4"
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.UInt8)
markers = numarray.array([[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 2, 0, 3, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, -1]],
numarray.Int8)
out = numarray.nd_image.watershed_ift(data, markers,
structure = [[1,1,1],
[1,1,1],
[1,1,1]])
error = diff([[-1, -1, -1, -1, -1, -1, -1],
[-1, 2, 2, 3, 3, 3, -1],
[-1, 2, 2, 3, 3, 3, -1],
[-1, 2, 2, 3, 3, 3, -1],
[-1, 2, 2, 3, 3, 3, -1],
[-1, 2, 2, 3, 3, 3, -1],
[-1, -1, -1, -1, -1, -1, -1]], out)
self.failUnless(error < eps)
def test_watershed_ift05(self):
"watershed_ift 5"
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.UInt8)
markers = numarray.array([[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 3, 0, 2, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, -1]],
numarray.Int8)
out = numarray.nd_image.watershed_ift(data, markers,
structure = [[1,1,1],
[1,1,1],
[1,1,1]])
error = diff([[-1, -1, -1, -1, -1, -1, -1],
[-1, 3, 3, 2, 2, 2, -1],
[-1, 3, 3, 2, 2, 2, -1],
[-1, 3, 3, 2, 2, 2, -1],
[-1, 3, 3, 2, 2, 2, -1],
[-1, 3, 3, 2, 2, 2, -1],
[-1, -1, -1, -1, -1, -1, -1]], out)
self.failUnless(error < eps)
def test_watershed_ift06(self):
"watershed_ift 6"
data = numarray.array([[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.UInt8)
markers = numarray.array([[ -1, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 1, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0]],
numarray.Int8)
out = numarray.nd_image.watershed_ift(data, markers,
structure = [[1,1,1],
[1,1,1],
[1,1,1]])
error = diff([[-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]], out)
self.failUnless(error < eps)
def test_watershed_ift07(self):
"watershed_ift 7"
shape = (7, 6)
data = numarray.zeros(shape, type = numarray.UInt8)
data.transpose()
data[...] = numarray.array([[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.UInt8)
markers = numarray.array([[-1, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 1, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0],
[ 0, 0, 0, 0, 0, 0, 0]],
numarray.Int8)
out = numarray.zeros(shape, type = numarray.Int16)
out.transpose()
numarray.nd_image.watershed_ift(data, markers,
structure = [[1,1,1],
[1,1,1],
[1,1,1]],
output = out)
error = diff([[-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]], out)
self.failUnless(error < eps)
def test_label01(self):
"label 1"
data = numarray.ones([])
out, n = numarray.nd_image.label(data)
self.failUnless(diff(out, 1) < eps and n == 1)
def test_label02(self):
"label 2"
data = numarray.zeros([])
out, n = numarray.nd_image.label(data)
self.failUnless(diff(out, 0) < eps and n == 0)
def test_label03(self):
"label 3"
data = numarray.ones([1])
out, n = numarray.nd_image.label(data)
self.failUnless(diff(out, [1]) < eps and n == 1)
def test_label04(self):
"label 4"
data = numarray.zeros([1])
out, n = numarray.nd_image.label(data)
self.failUnless(diff(out, [0]) < eps and n == 0)
def test_label05(self):
"label 5"
data = numarray.ones([5])
out, n = numarray.nd_image.label(data)
self.failUnless(diff(out, [1, 1, 1, 1, 1]) < eps and n == 1)
def test_label06(self):
"label 6"
data = numarray.array([1, 0, 1, 1, 0, 1])
out, n = numarray.nd_image.label(data)
self.failUnless(diff(out, [1, 0, 2, 2, 0, 3]) < eps and n == 3)
def test_label07(self):
"label 7"
data = numarray.array([[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]])
out, n = numarray.nd_image.label(data)
self.failUnless(diff(out, [[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]]) < eps and n == 0)
def test_label08(self):
"label 8"
data = numarray.array([[1, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0],
[1, 1, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0]])
out, n = numarray.nd_image.label(data)
self.failUnless(diff(out, [[1, 0, 0, 0, 0, 0],
[0, 0, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 0],
[3, 3, 0, 0, 0, 0],
[3, 3, 0, 0, 0, 0],
[0, 0, 0, 4, 4, 0]]) < eps and n == 4)
def test_label09(self):
"label 9"
data = numarray.array([[1, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0],
[1, 1, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0]])
struct = numarray.nd_image.generate_binary_structure(2, 2)
out, n = numarray.nd_image.label(data, struct)
self.failUnless(diff(out, [[1, 0, 0, 0, 0, 0],
[0, 0, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 0],
[2, 2, 0, 0, 0, 0],
[2, 2, 0, 0, 0, 0],
[0, 0, 0, 3, 3, 0]]) < eps and n == 3)
def test_label10(self):
"label 10"
data = numarray.array([[0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0]])
struct = numarray.nd_image.generate_binary_structure(2, 2)
out, n = numarray.nd_image.label(data, struct)
self.failUnless(diff(out, [[0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0]]) < eps and n == 1)
def test_label11(self):
"label 11"
for type in self.types:
data = numarray.array([[1, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0],
[1, 1, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0]], type)
out, n = numarray.nd_image.label(data)
error = diff(out, [[1, 0, 0, 0, 0, 0],
[0, 0, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 0],
[3, 3, 0, 0, 0, 0],
[3, 3, 0, 0, 0, 0],
[0, 0, 0, 4, 4, 0]])
self.failUnless(error < eps and n == 4)
def test_label12(self):
"label 12"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 0, 1],
[0, 0, 1, 0, 1, 1],
[0, 0, 1, 1, 1, 1],
[0, 0, 0, 1, 1, 0]], type)
out, n = numarray.nd_image.label(data)
error = diff(out, [[0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 0, 1],
[0, 0, 1, 0, 1, 1],
[0, 0, 1, 1, 1, 1],
[0, 0, 0, 1, 1, 0]])
self.failUnless(error < eps and n == 1)
def test_label13(self):
"label 13"
for type in self.types:
data = numarray.array([[1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1],
[1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1],
[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]],
type)
out, n = numarray.nd_image.label(data)
error = diff(out, [[1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1],
[1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1],
[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])
self.failUnless(error < eps and n == 1)
def test_find_objects01(self):
"find_objects 1"
data = numarray.ones([])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == [()])
def test_find_objects02(self):
"find_objects 2"
data = numarray.zeros([])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == [])
def test_find_objects03(self):
"find_objects 3"
data = numarray.ones([1])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == [(slice(0, 1, None),)])
def test_find_objects04(self):
"find_objects 4"
data = numarray.zeros([1])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == [])
def test_find_objects05(self):
"find_objects 5"
data = numarray.ones([5])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == [(slice(0, 5, None),)])
def test_find_objects06(self):
"find_objects 6"
data = numarray.array([1, 0, 2, 2, 0, 3])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == [(slice(0, 1, None),),
(slice(2, 4, None),),
(slice(5, 6, None),)])
def test_find_objects07(self):
"find_objects 7"
data = numarray.array([[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == []),
def test_find_objects08(self):
"find_objects 8"
data = numarray.array([[1, 0, 0, 0, 0, 0],
[0, 0, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 0],
[3, 3, 0, 0, 0, 0],
[3, 3, 0, 0, 0, 0],
[0, 0, 0, 4, 4, 0]])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == [(slice(0, 1, None), slice(0, 1, None)),
(slice(1, 3, None), slice(2, 5, None)),
(slice(3, 5, None), slice(0, 2, None)),
(slice(5, 6, None), slice(3, 5, None))])
def test_find_objects09(self):
"find_objects 9"
data = numarray.array([[1, 0, 0, 0, 0, 0],
[0, 0, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 4, 4, 0]])
out = numarray.nd_image.find_objects(data)
self.failUnless(out == [(slice(0, 1, None), slice(0, 1, None)),
(slice(1, 3, None), slice(2, 5, None)),
None,
(slice(5, 6, None), slice(3, 5, None))])
def test_sum01(self):
"sum 1"
for type in self.types:
input = numarray.array([], type)
output = numarray.nd_image.sum(input)
self.failUnless(output == 0.0)
def test_sum02(self):
"sum 2"
for type in self.types:
input = numarray.zeros([0, 4], type)
output = numarray.nd_image.sum(input)
self.failUnless(output == 0.0)
def test_sum03(self):
"sum 3"
for type in self.types:
input = numarray.ones([], type)
output = numarray.nd_image.sum(input)
self.failUnless(output == 1.0)
def test_sum04(self):
"sum 4"
for type in self.types:
input = numarray.array([1, 2], type)
output = numarray.nd_image.sum(input)
self.failUnless(output == 3.0)
def test_sum05(self):
"sum 5"
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.sum(input)
self.failUnless(output == 10.0)
def test_sum06(self):
"sum 6"
labels = numarray.array([], numarray.Bool)
for type in self.types:
input = numarray.array([], type)
output = numarray.nd_image.sum(input, labels = labels)
self.failUnless(output == 0.0)
def test_sum07(self):
"sum 7"
labels = numarray.ones([0, 4], numarray.Bool)
for type in self.types:
input = numarray.zeros([0, 4], type)
output = numarray.nd_image.sum(input, labels = labels)
self.failUnless(output == 0.0)
def test_sum08(self):
"sum 8"
labels = numarray.array([1, 0], numarray.Bool)
for type in self.types:
input = numarray.array([1, 2], type)
output = numarray.nd_image.sum(input, labels = labels)
self.failUnless(output == 1.0)
def test_sum09(self):
"sum 9"
labels = numarray.array([1, 0], numarray.Bool)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.sum(input, labels = labels)
self.failUnless(output == 4.0)
def test_sum10(self):
"sum 10"
labels = numarray.array([1, 0], numarray.Bool)
input = numarray.array([[1, 2], [3, 4]], numarray.Bool)
output = numarray.nd_image.sum(input, labels = labels)
self.failUnless(output == 2.0)
def test_sum11(self):
"sum 11"
labels = numarray.array([1, 2], numarray.Int8)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.sum(input, labels = labels,
index = 2)
self.failUnless(output == 6.0)
def test_sum12(self):
"sum 12"
labels = numarray.array([[1, 2], [2, 4]], numarray.Int8)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.sum(input, labels = labels,
index = [4, 8, 2])
self.failUnless(output == [4.0, 0.0, 5.0])
def test_mean01(self):
"mean 1"
labels = numarray.array([1, 0], numarray.Bool)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.mean(input, labels = labels)
self.failUnless(output == 2.0)
def test_mean02(self):
"mean 2"
labels = numarray.array([1, 0], numarray.Bool)
input = numarray.array([[1, 2], [3, 4]], numarray.Bool)
output = numarray.nd_image.mean(input, labels = labels)
self.failUnless(output == 1.0)
def test_mean03(self):
"mean 3"
labels = numarray.array([1, 2])
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.mean(input, labels = labels,
index = 2)
self.failUnless(output == 3.0)
def test_mean04(self):
"mean 4"
labels = numarray.array([[1, 2], [2, 4]], numarray.Int8)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.mean(input, labels = labels,
index = [4, 8, 2])
self.failUnless(output == [4.0, 0.0, 2.5])
def test_minimum01(self):
"minimum 1"
labels = numarray.array([1, 0], numarray.Bool)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.minimum(input, labels = labels)
self.failUnless(output == 1.0)
def test_minimum02(self):
"minimum 2"
labels = numarray.array([1, 0], numarray.Bool)
input = numarray.array([[2, 2], [2, 4]], numarray.Bool)
output = numarray.nd_image.minimum(input, labels = labels)
self.failUnless(output == 1.0)
def test_minimum03(self):
"minimum 3"
labels = numarray.array([1, 2])
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.minimum(input, labels = labels,
index = 2)
self.failUnless(output == 2.0)
def test_minimum04(self):
"minimum 4"
labels = numarray.array([[1, 2], [2, 3]])
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.minimum(input, labels = labels,
index = [2, 3, 8])
self.failUnless(output == [2.0, 4.0, 0.0])
def test_maximum01(self):
"maximum 1"
labels = numarray.array([1, 0], numarray.Bool)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.maximum(input, labels = labels)
self.failUnless(output == 3.0)
def test_maximum02(self):
"maximum 2"
labels = numarray.array([1, 0], numarray.Bool)
input = numarray.array([[2, 2], [2, 4]], numarray.Bool)
output = numarray.nd_image.maximum(input, labels = labels)
self.failUnless(output == 1.0)
def test_maximum03(self):
"maximum 3"
labels = numarray.array([1, 2])
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.maximum(input, labels = labels,
index = 2)
self.failUnless(output == 4.0)
def test_maximum04(self):
"maximum 4"
labels = numarray.array([[1, 2], [2, 3]])
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.maximum(input, labels = labels,
index = [2, 3, 8])
self.failUnless(output == [3.0, 4.0, 0.0])
def test_variance01(self):
"variance 1"
for type in self.types:
input = numarray.array([], type)
output = numarray.nd_image.variance(input)
self.failUnless(float(output) == 0.0)
def test_variance02(self):
"variance 2"
for type in self.types:
input = numarray.array([1], type)
output = numarray.nd_image.variance(input)
self.failUnless(float(output) == 0.0)
def test_variance03(self):
"variance 3"
for type in self.types:
input = numarray.array([1, 3], type)
output = numarray.nd_image.variance(input)
self.failUnless(output == 2.0)
def test_variance04(self):
"variance 4"
input = numarray.array([1, 0], numarray.Bool)
output = numarray.nd_image.variance(input)
self.failUnless(output == 0.5)
def test_variance05(self):
"variance 5"
labels = [2, 2, 3]
for type in self.types:
input = numarray.array([1, 3, 8], type)
output = numarray.nd_image.variance(input, labels, 2)
self.failUnless(output == 2.0)
def test_variance06(self):
"variance 6"
labels = [2, 2, 3, 3, 4]
for type in self.types:
input = numarray.array([1, 3, 8, 10, 8], type)
output = numarray.nd_image.variance(input, labels, [2, 3, 4])
self.failUnless(output == [2.0, 2.0, 0.0])
def test_standard_deviation01(self):
"standard deviation 1"
for type in self.types:
input = numarray.array([], type)
output = numarray.nd_image.standard_deviation(input)
self.failUnless(float(output) == 0.0)
def test_standard_deviation02(self):
"standard deviation 2"
for type in self.types:
input = numarray.array([1], type)
output = numarray.nd_image.standard_deviation(input)
self.failUnless(float(output) == 0.0)
def test_standard_deviation03(self):
"standard deviation 3"
for type in self.types:
input = numarray.array([1, 3], type)
output = numarray.nd_image.standard_deviation(input)
self.failUnless(output == math.sqrt(2.0))
def test_standard_deviation04(self):
"standard deviation 4"
input = numarray.array([1, 0], numarray.Bool)
output = numarray.nd_image.standard_deviation(input)
self.failUnless(output == math.sqrt(0.5))
def test_standard_deviation05(self):
"standard deviation 5"
labels = [2, 2, 3]
for type in self.types:
input = numarray.array([1, 3, 8], type)
output = numarray.nd_image.standard_deviation(input, labels, 2)
self.failUnless(output == math.sqrt(2.0))
def test_standard_deviation06(self):
"standard deviation 6"
labels = [2, 2, 3, 3, 4]
for type in self.types:
input = numarray.array([1, 3, 8, 10, 8], type)
output = numarray.nd_image.standard_deviation(input, labels,
[2, 3, 4])
self.failUnless(output == [math.sqrt(2.0), math.sqrt(2.0),
0.0])
def test_minimum_position01(self):
"minimum position 1"
labels = numarray.array([1, 0], numarray.Bool)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.minimum_position(input,
labels = labels)
self.failUnless(output == (0, 0))
def test_minimum_position02(self):
"minimum position 2"
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 0, 2],
[1, 5, 1, 1]], type)
output = numarray.nd_image.minimum_position(input)
self.failUnless(output == (1, 2))
def test_minimum_position03(self):
"minimum position 3"
input = numarray.array([[5, 4, 2, 5],
[3, 7, 0, 2],
[1, 5, 1, 1]], numarray.Bool)
output = numarray.nd_image.minimum_position(input)
self.failUnless(output == (1, 2))
def test_minimum_position04(self):
"minimum position 4"
input = numarray.array([[5, 4, 2, 5],
[3, 7, 1, 2],
[1, 5, 1, 1]], numarray.Bool)
output = numarray.nd_image.minimum_position(input)
self.failUnless(output == (0, 0))
def test_minimum_position05(self):
"minimum position 5"
labels = [1, 2, 0, 4]
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 0, 2],
[1, 5, 2, 3]], type)
output = numarray.nd_image.minimum_position(input, labels)
self.failUnless(output == (2, 0))
def test_minimum_position06(self):
"minimum position 6"
labels = [1, 2, 3, 4]
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 0, 2],
[1, 5, 1, 1]], type)
output = numarray.nd_image.minimum_position(input, labels, 2)
self.failUnless(output == (0, 1))
def test_minimum_position07(self):
"minimum position 7"
labels = [1, 2, 3, 4]
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 0, 2],
[1, 5, 1, 1]], type)
output = numarray.nd_image.minimum_position(input, labels,
[2, 3])
self.failUnless(output == [(0, 1), (1, 2)])
def test_maximum_position01(self):
"maximum position 1"
labels = numarray.array([1, 0], numarray.Bool)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output = numarray.nd_image.maximum_position(input,
labels = labels)
self.failUnless(output == (1, 0))
def test_maximum_position02(self):
"maximum position 2"
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 8, 2],
[1, 5, 1, 1]], type)
output = numarray.nd_image.maximum_position(input)
self.failUnless(output == (1, 2))
def test_maximum_position03(self):
"maximum position 3"
input = numarray.array([[5, 4, 2, 5],
[3, 7, 8, 2],
[1, 5, 1, 1]], numarray.Bool)
output = numarray.nd_image.maximum_position(input)
self.failUnless(output == (0, 0))
def test_maximum_position04(self):
"maximum position 4"
labels = [1, 2, 0, 4]
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 8, 2],
[1, 5, 1, 1]], type)
output = numarray.nd_image.maximum_position(input, labels)
self.failUnless(output == (1, 1))
def test_maximum_position05(self):
"maximum position 5"
labels = [1, 2, 0, 4]
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 8, 2],
[1, 5, 1, 1]], type)
output = numarray.nd_image.maximum_position(input, labels, 1)
self.failUnless(output == (0, 0))
def test_maximum_position06(self):
"maximum position 6"
labels = [1, 2, 0, 4]
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 8, 2],
[1, 5, 1, 1]], type)
output = numarray.nd_image.maximum_position(input, labels,
[1, 2])
self.failUnless(output == [(0, 0), (1, 1)])
def test_extrema01(self):
"extrema 1"
labels = numarray.array([1, 0], numarray.Bool)
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output1 = numarray.nd_image.extrema(input, labels = labels)
output2 = numarray.nd_image.minimum(input, labels = labels)
output3 = numarray.nd_image.maximum(input, labels = labels)
output4 = numarray.nd_image.minimum_position(input,
labels = labels)
output5 = numarray.nd_image.maximum_position(input,
labels = labels)
self.failUnless(output1 == (output2, output3, output4,
output5))
def test_extrema02(self):
"extrema 2"
labels = numarray.array([1, 2])
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output1 = numarray.nd_image.extrema(input, labels = labels,
index = 2)
output2 = numarray.nd_image.minimum(input, labels = labels,
index = 2)
output3 = numarray.nd_image.maximum(input, labels = labels,
index = 2)
output4 = numarray.nd_image.minimum_position(input,
labels = labels, index = 2)
output5 = numarray.nd_image.maximum_position(input,
labels = labels, index = 2)
self.failUnless(output1 == (output2, output3, output4,
output5))
def test_extrema03(self):
"extrema 3"
labels = numarray.array([[1, 2], [2, 3]])
for type in self.types:
input = numarray.array([[1, 2], [3, 4]], type)
output1 = numarray.nd_image.extrema(input, labels = labels,
index = [2, 3, 8])
output2 = numarray.nd_image.minimum(input, labels = labels,
index = [2, 3, 8])
output3 = numarray.nd_image.maximum(input, labels = labels,
index = [2, 3, 8])
output4 = numarray.nd_image.minimum_position(input,
labels = labels, index = [2, 3, 8])
output5 = numarray.nd_image.maximum_position(input,
labels = labels, index = [2, 3, 8])
self.failUnless(output1 == (output2, output3, output4,
output5))
def test_extrema04(self):
"extrema 4"
labels = [1, 2, 0, 4]
for type in self.types:
input = numarray.array([[5, 4, 2, 5],
[3, 7, 8, 2],
[1, 5, 1, 1]], type)
output1 = numarray.nd_image.extrema(input, labels, [1, 2])
output2 = numarray.nd_image.minimum(input, labels, [1, 2])
output3 = numarray.nd_image.maximum(input, labels, [1, 2])
output4 = numarray.nd_image.minimum_position(input, labels,
[1, 2])
output5 = numarray.nd_image.maximum_position(input, labels,
[1, 2])
self.failUnless(output1 == (output2, output3, output4,
output5))
def test_center_of_mass01(self):
"center of mass 1"
true = [0.0, 0.0]
for type in self.types:
input = numarray.array([[1, 0], [0, 0]], type)
output = numarray.nd_image.center_of_mass(input)
e = diff(true, output)
self.failUnless(e < eps)
def test_center_of_mass02(self):
"center of mass 2"
true = [1, 0]
for type in self.types:
input = numarray.array([[0, 0], [1, 0]], type)
output = numarray.nd_image.center_of_mass(input)
e = diff(true, output)
self.failUnless(e < eps)
def test_center_of_mass03(self):
"center of mass 3"
true = [0, 1]
for type in self.types:
input = numarray.array([[0, 1], [0, 0]], type)
output = numarray.nd_image.center_of_mass(input)
e = diff(true, output)
self.failUnless(e < eps)
def test_center_of_mass04(self):
"center of mass 4"
true = [1, 1]
for type in self.types:
input = numarray.array([[0, 0], [0, 1]], type)
output = numarray.nd_image.center_of_mass(input)
e = diff(true, output)
self.failUnless(e < eps)
def test_center_of_mass05(self):
"center of mass 5"
true = [0.5, 0.5]
for type in self.types:
input = numarray.array([[1, 1], [1, 1]], type)
output = numarray.nd_image.center_of_mass(input)
e = diff(true, output)
self.failUnless(e < eps)
def test_center_of_mass06(self):
"center of mass 6"
true = [0.5, 0.5]
input = numarray.array([[1, 2], [3, 1]], numarray.Bool)
output = numarray.nd_image.center_of_mass(input)
e = diff(true, output)
self.failUnless(e < eps)
def test_center_of_mass07(self):
"center of mass 7"
labels = [1, 0]
true = [0.5, 0.0]
input = numarray.array([[1, 2], [3, 1]], numarray.Bool)
output = numarray.nd_image.center_of_mass(input, labels)
e = diff(true, output)
self.failUnless(e < eps)
def test_center_of_mass08(self):
"center of mass 8"
labels = [1, 2]
true = [0.5, 1.0]
input = numarray.array([[5, 2], [3, 1]], numarray.Bool)
output = numarray.nd_image.center_of_mass(input, labels, 2)
e = diff(true, output)
self.failUnless(e < eps)
def test_center_of_mass09(self):
"center of mass 9"
labels = [1, 2]
true = [(0.5, 0.0), (0.5, 1.0)]
input = numarray.array([[1, 2], [1, 1]], numarray.Bool)
output = numarray.nd_image.center_of_mass(input, labels, [1, 2])
e = diff(true, output)
self.failUnless(e < eps)
def test_histogram01(self):
"histogram 1"
true = numarray.ones(10)
input = numarray.arange(10)
output = numarray.nd_image.histogram(input, 0, 10, 10)
e = diff(true, output)
self.failUnless(e < eps)
def test_histogram02(self):
"histogram 2"
labels = [1, 1, 1, 1, 2, 2, 2, 2]
true = [0, 2, 0, 1, 0]
input = numarray.array([1, 1, 3, 4, 3, 3, 3, 3])
output = numarray.nd_image.histogram(input, 0, 4, 5, labels, 1)
e = diff(true, output)
self.failUnless(e < eps)
def test_histogram03(self):
"histogram 3"
labels = [1, 0, 1, 1, 2, 2, 2, 2]
true1 = [0, 1, 0, 1, 0]
true2 = [0, 0, 0, 3, 0]
input = numarray.array([1, 1, 3, 4, 3, 5, 3, 3])
output = numarray.nd_image.histogram(input, 0, 4, 5, labels, (1,2))
e1 = diff(true1, output[0])
e2 = diff(true2, output[1])
self.failUnless(e1 < eps and e2 < eps)
def test_distance_transform_bf01(self):
"brute force distance transform 1"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
out, ft = numarray.nd_image.distance_transform_bf(data,
'euclidean', return_indices = True)
error1 = diff([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 2, 4, 2, 1, 0, 0],
[0, 0, 1, 4, 8, 4, 1, 0, 0],
[0, 0, 1, 2, 4, 2, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]],
out * out)
error2 = diff([[[0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 2, 1, 2, 2, 2, 2],
[3, 3, 3, 2, 1, 2, 3, 3, 3],
[4, 4, 4, 4, 6, 4, 4, 4, 4],
[5, 5, 6, 6, 7, 6, 6, 5, 5],
[6, 6, 6, 7, 7, 7, 6, 6, 6],
[7, 7, 7, 7, 7, 7, 7, 7, 7],
[8, 8, 8, 8, 8, 8, 8, 8, 8]],
[[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 2, 4, 6, 6, 7, 8],
[0, 1, 1, 2, 4, 6, 7, 7, 8],
[0, 1, 1, 1, 6, 7, 7, 7, 8],
[0, 1, 2, 2, 4, 6, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8]]], ft)
self.failUnless(error1 < eps and error2 < eps)
def test_distance_transform_bf02(self):
"brute force distance transform 2"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
out, ft = numarray.nd_image.distance_transform_bf(data,
'cityblock', return_indices = True)
error1 = diff([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 2, 2, 2, 1, 0, 0],
[0, 0, 1, 2, 3, 2, 1, 0, 0],
[0, 0, 1, 2, 2, 2, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], out)
error2 = diff([[[0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 2, 1, 2, 2, 2, 2],
[3, 3, 3, 3, 1, 3, 3, 3, 3],
[4, 4, 4, 4, 7, 4, 4, 4, 4],
[5, 5, 6, 7, 7, 7, 6, 5, 5],
[6, 6, 6, 7, 7, 7, 6, 6, 6],
[7, 7, 7, 7, 7, 7, 7, 7, 7],
[8, 8, 8, 8, 8, 8, 8, 8, 8]],
[[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 2, 4, 6, 6, 7, 8],
[0, 1, 1, 1, 4, 7, 7, 7, 8],
[0, 1, 1, 1, 4, 7, 7, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8]]], ft)
self.failUnless(error1 < eps and error2 < eps)
def test_distance_transform_bf03(self):
"brute force distance transform 3"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
out, ft = numarray.nd_image.distance_transform_bf(data,
'chessboard', return_indices = True)
error1 = diff([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 2, 1, 1, 0, 0],
[0, 0, 1, 2, 2, 2, 1, 0, 0],
[0, 0, 1, 1, 2, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], out)
error2 = diff([[[0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 2, 1, 2, 2, 2, 2],
[3, 3, 4, 2, 2, 2, 4, 3, 3],
[4, 4, 5, 6, 6, 6, 5, 4, 4],
[5, 5, 6, 6, 7, 6, 6, 5, 5],
[6, 6, 6, 7, 7, 7, 6, 6, 6],
[7, 7, 7, 7, 7, 7, 7, 7, 7],
[8, 8, 8, 8, 8, 8, 8, 8, 8]],
[[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 2, 5, 6, 6, 7, 8],
[0, 1, 1, 2, 6, 6, 7, 7, 8],
[0, 1, 1, 2, 6, 7, 7, 7, 8],
[0, 1, 2, 2, 6, 6, 7, 7, 8],
[0, 1, 2, 4, 5, 6, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8]]], ft)
self.failUnless(error1 < eps and error2 < eps)
def test_distance_transform_bf04(self):
"brute force distance transform 4"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
tdt, tft = numarray.nd_image.distance_transform_bf(data,
return_indices = 1)
dts = []
fts = []
dt = numarray.zeros(data.shape, type = numarray.Float64)
numarray.nd_image.distance_transform_bf(data, distances = dt)
dts.append(dt)
ft = numarray.nd_image.distance_transform_bf(data,
return_distances = False, return_indices = 1)
fts.append(ft)
ft = numarray.indices(data.shape, type = numarray.Int32)
numarray.nd_image.distance_transform_bf(data,
return_distances = False, return_indices = True, indices = ft)
fts.append(ft)
dt, ft = numarray.nd_image.distance_transform_bf(data,
return_indices = 1)
dts.append(dt)
fts.append(ft)
dt = numarray.zeros(data.shape, type = numarray.Float64)
ft = numarray.nd_image.distance_transform_bf(data, distances = dt,
return_indices = True)
dts.append(dt)
fts.append(ft)
ft = numarray.indices(data.shape, type = numarray.Int32)
dt = numarray.nd_image.distance_transform_bf(data,
return_indices = True, indices = ft)
dts.append(dt)
fts.append(ft)
dt = numarray.zeros(data.shape, type = numarray.Float64)
ft = numarray.indices(data.shape, type = numarray.Int32)
numarray.nd_image.distance_transform_bf(data, distances = dt,
return_indices = True, indices = ft)
dts.append(dt)
fts.append(ft)
for dt in dts:
self.failUnless(diff(tdt, dt) < eps)
for ft in fts:
self.failUnless(diff(tft, ft) < eps)
def test_distance_transform_bf05(self):
"brute force distance transform 5"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
out, ft = numarray.nd_image.distance_transform_bf(data,
'euclidean', return_indices = True, sampling = [2, 2])
error1 = diff([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 4, 4, 4, 0, 0, 0],
[0, 0, 4, 8, 16, 8, 4, 0, 0],
[0, 0, 4, 16, 32, 16, 4, 0, 0],
[0, 0, 4, 8, 16, 8, 4, 0, 0],
[0, 0, 0, 4, 4, 4, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], out * out)
error2 = diff([[[0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 2, 1, 2, 2, 2, 2],
[3, 3, 3, 2, 1, 2, 3, 3, 3],
[4, 4, 4, 4, 6, 4, 4, 4, 4],
[5, 5, 6, 6, 7, 6, 6, 5, 5],
[6, 6, 6, 7, 7, 7, 6, 6, 6],
[7, 7, 7, 7, 7, 7, 7, 7, 7],
[8, 8, 8, 8, 8, 8, 8, 8, 8]],
[[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 2, 4, 6, 6, 7, 8],
[0, 1, 1, 2, 4, 6, 7, 7, 8],
[0, 1, 1, 1, 6, 7, 7, 7, 8],
[0, 1, 2, 2, 4, 6, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8]]], ft)
self.failUnless(error1 < eps and error2 < eps)
def test_distance_transform_bf06(self):
"brute force distance transform 6"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
out, ft = numarray.nd_image.distance_transform_bf(data,
'euclidean', return_indices = True, sampling = [2, 1])
error1 = diff([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 4, 1, 0, 0, 0],
[0, 0, 1, 4, 8, 4, 1, 0, 0],
[0, 0, 1, 4, 9, 4, 1, 0, 0],
[0, 0, 1, 4, 8, 4, 1, 0, 0],
[0, 0, 0, 1, 4, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], out * out)
error2 = diff([[[0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 2, 2, 2, 2, 2, 2],
[3, 3, 3, 3, 2, 3, 3, 3, 3],
[4, 4, 4, 4, 4, 4, 4, 4, 4],
[5, 5, 5, 5, 6, 5, 5, 5, 5],
[6, 6, 6, 6, 7, 6, 6, 6, 6],
[7, 7, 7, 7, 7, 7, 7, 7, 7],
[8, 8, 8, 8, 8, 8, 8, 8, 8]],
[[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 2, 6, 6, 6, 7, 8],
[0, 1, 1, 1, 6, 7, 7, 7, 8],
[0, 1, 1, 1, 7, 7, 7, 7, 8],
[0, 1, 1, 1, 6, 7, 7, 7, 8],
[0, 1, 2, 2, 4, 6, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8]]], ft)
self.failUnless(error1 < eps and error2 < eps)
self.failUnless(error1 < eps and error2 < eps)
def test_distance_transform_cdt01(self):
"chamfer type distance transform 1"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
out, ft = numarray.nd_image.distance_transform_cdt(data,
'cityblock', return_indices = True)
bf = numarray.nd_image.distance_transform_bf(data, 'cityblock')
error1 = diff(bf, out)
error2 = diff([[[0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 1, 1, 1, 2, 2, 2],
[3, 3, 2, 1, 1, 1, 2, 3, 3],
[4, 4, 4, 4, 1, 4, 4, 4, 4],
[5, 5, 5, 5, 7, 7, 6, 5, 5],
[6, 6, 6, 6, 7, 7, 6, 6, 6],
[7, 7, 7, 7, 7, 7, 7, 7, 7],
[8, 8, 8, 8, 8, 8, 8, 8, 8]],
[[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 1, 1, 4, 7, 7, 7, 8],
[0, 1, 1, 1, 4, 5, 6, 7, 8],
[0, 1, 2, 2, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],]], ft)
self.failUnless(error1 < eps and error2 < eps)
def test_distance_transform_cdt02(self):
"chamfer type distance transform 2"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
out, ft = numarray.nd_image.distance_transform_cdt(data,
'chessboard', return_indices = True)
bf = numarray.nd_image.distance_transform_bf(data, 'chessboard')
error1 = diff(bf, out)
error2 = diff([[[0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 1, 1, 1, 2, 2, 2],
[3, 3, 2, 2, 1, 2, 2, 3, 3],
[4, 4, 3, 2, 2, 2, 3, 4, 4],
[5, 5, 4, 6, 7, 6, 4, 5, 5],
[6, 6, 6, 6, 7, 7, 6, 6, 6],
[7, 7, 7, 7, 7, 7, 7, 7, 7],
[8, 8, 8, 8, 8, 8, 8, 8, 8]],
[[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 2, 3, 4, 6, 7, 8],
[0, 1, 1, 2, 2, 6, 6, 7, 8],
[0, 1, 1, 1, 2, 6, 7, 7, 8],
[0, 1, 1, 2, 6, 6, 7, 7, 8],
[0, 1, 2, 2, 5, 6, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],
[0, 1, 2, 3, 4, 5, 6, 7, 8],]], ft)
self.failUnless(error1 < eps and error2 < eps)
def test_distance_transform_cdt03(self):
"chamfer type distance transform 3"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
tdt, tft = numarray.nd_image.distance_transform_cdt(data,
return_indices = True)
dts = []
fts = []
dt = numarray.zeros(data.shape, type = numarray.Int32)
numarray.nd_image.distance_transform_cdt(data, distances = dt)
dts.append(dt)
ft = numarray.nd_image.distance_transform_cdt(data,
return_distances = False, return_indices = True)
fts.append(ft)
ft = numarray.indices(data.shape, type = numarray.Int32)
numarray.nd_image.distance_transform_cdt(data,
return_distances = False, return_indices = True, indices = ft)
fts.append(ft)
dt, ft = numarray.nd_image.distance_transform_cdt(data,
return_indices = True)
dts.append(dt)
fts.append(ft)
dt = numarray.zeros(data.shape, type = numarray.Int32)
ft = numarray.nd_image.distance_transform_cdt(data, distances = dt,
return_indices = True)
dts.append(dt)
fts.append(ft)
ft = numarray.indices(data.shape, type = numarray.Int32)
dt = numarray.nd_image.distance_transform_cdt(data,
return_indices = True, indices = ft)
dts.append(dt)
fts.append(ft)
dt = numarray.zeros(data.shape, type = numarray.Int32)
ft = numarray.indices(data.shape, type = numarray.Int32)
numarray.nd_image.distance_transform_cdt(data, distances = dt,
return_indices = True, indices = ft)
dts.append(dt)
fts.append(ft)
for dt in dts:
self.failUnless(diff(tdt, dt) < eps)
for ft in fts:
self.failUnless(diff(tft, ft) < eps)
def test_distance_transform_edt01(self):
"euclidean distance transform 1"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
out, ft = numarray.nd_image.distance_transform_edt(data,
return_indices = True)
bf = numarray.nd_image.distance_transform_bf(data, 'euclidean')
error1 = diff(bf, out)
dt = ft - numarray.indices(ft.shape[1:], type = ft.type())
dt = dt.astype(numarray.Float64)
numarray.multiply(dt, dt, dt)
dt = numarray.add.reduce(dt, axis = 0)
numarray.sqrt(dt, dt)
error2 = diff(bf, dt)
self.failUnless(error1 < eps and error2 < eps)
def test_distance_transform_edt02(self):
"euclidean distance transform 2"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
tdt, tft = numarray.nd_image.distance_transform_edt(data,
return_indices = True)
dts = []
fts = []
dt = numarray.zeros(data.shape, type = numarray.Float64)
numarray.nd_image.distance_transform_edt(data, distances = dt)
dts.append(dt)
ft = numarray.nd_image.distance_transform_edt(data,
return_distances = 0, return_indices = True)
fts.append(ft)
ft = numarray.indices(data.shape, type = numarray.Int32)
numarray.nd_image.distance_transform_edt(data,
return_distances = False,return_indices = True, indices = ft)
fts.append(ft)
dt, ft = numarray.nd_image.distance_transform_edt(data,
return_indices = True)
dts.append(dt)
fts.append(ft)
dt = numarray.zeros(data.shape, type = numarray.Float64)
ft = numarray.nd_image.distance_transform_edt(data, distances = dt,
return_indices = True)
dts.append(dt)
fts.append(ft)
ft = numarray.indices(data.shape, type = numarray.Int32)
dt = numarray.nd_image.distance_transform_edt(data,
return_indices = True, indices = ft)
dts.append(dt)
fts.append(ft)
dt = numarray.zeros(data.shape, type = numarray.Float64)
ft = numarray.indices(data.shape, type = numarray.Int32)
numarray.nd_image.distance_transform_edt(data, distances = dt,
return_indices = True, indices = ft)
dts.append(dt)
fts.append(ft)
for dt in dts:
self.failUnless(diff(tdt, dt) < eps)
for ft in fts:
self.failUnless(diff(tft, ft) < eps)
def test_distance_transform_edt03(self):
"euclidean distance transform 3"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
ref = numarray.nd_image.distance_transform_bf(data, 'euclidean',
sampling = [2, 2])
out = numarray.nd_image.distance_transform_edt(data,
sampling = [2, 2])
self.failUnless(diff(ref, out) < eps)
def test_distance_transform_edt4(self):
"euclidean distance transform 4"
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]], type)
ref = numarray.nd_image.distance_transform_bf(data, 'euclidean',
sampling = [2, 1])
out = numarray.nd_image.distance_transform_edt(data,
sampling = [2, 1])
self.failUnless(diff(ref, out) < eps)
def test_generate_structure01(self):
"generation of a binary structure 1"
struct = numarray.nd_image.generate_binary_structure(0, 1)
self.failUnless(diff(struct, 1) < eps)
def test_generate_structure02(self):
"generation of a binary structure 2"
struct = numarray.nd_image.generate_binary_structure(1, 1)
self.failUnless(diff(struct, [1, 1, 1]) < eps)
def test_generate_structure03(self):
"generation of a binary structure 3"
struct = numarray.nd_image.generate_binary_structure(2, 1)
self.failUnless(diff(struct, [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]) < eps)
def test_generate_structure04(self):
"generation of a binary structure 4"
struct = numarray.nd_image.generate_binary_structure(2, 2)
self.failUnless(diff(struct, [[1, 1, 1],
[1, 1, 1],
[1, 1, 1]]) < eps)
def test_iterate_structure01(self):
"iterating a structure 1"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
out = numarray.nd_image.iterate_structure(struct, 2)
self.failUnless(diff(out, [[0, 0, 1, 0, 0],
[0, 1, 1, 1, 0],
[1, 1, 1, 1, 1],
[0, 1, 1, 1, 0],
[0, 0, 1, 0, 0]]) < eps)
def test_iterate_structure02(self):
"iterating a structure 2"
struct = [[0, 1],
[1, 1],
[0, 1]]
out = numarray.nd_image.iterate_structure(struct, 2)
self.failUnless(diff(out, [[0, 0, 1],
[0, 1, 1],
[1, 1, 1],
[0, 1, 1],
[0, 0, 1]]) < eps)
def test_iterate_structure03(self):
"iterating a structure 3"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
out = numarray.nd_image.iterate_structure(struct, 2, 1)
error = diff(out[0], [[0, 0, 1, 0, 0],
[0, 1, 1, 1, 0],
[1, 1, 1, 1, 1],
[0, 1, 1, 1, 0],
[0, 0, 1, 0, 0]])
self.failUnless(error < eps and out[1] == [2, 2])
def test_binary_erosion01(self):
"binary erosion 1"
for type in self.types:
data = numarray.ones([], type)
out = numarray.nd_image.binary_erosion(data)
self.failUnless(diff(out, 1) < eps)
def test_binary_erosion02(self):
"binary erosion 2"
for type in self.types:
data = numarray.ones([], type)
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, 1) < eps)
def test_binary_erosion03(self):
"binary erosion 3"
for type in self.types:
data = numarray.ones([1], type)
out = numarray.nd_image.binary_erosion(data)
self.failUnless(diff(out, [0]) < eps)
def test_binary_erosion04(self):
"binary erosion 4"
for type in self.types:
data = numarray.ones([1], type)
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, [1]) < eps)
def test_binary_erosion05(self):
"binary erosion 5"
for type in self.types:
data = numarray.ones([3], type)
out = numarray.nd_image.binary_erosion(data)
self.failUnless(diff(out, [0, 1, 0]) < eps)
def test_binary_erosion06(self):
"binary erosion 6"
for type in self.types:
data = numarray.ones([3], type)
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, [1, 1, 1]) < eps)
def test_binary_erosion07(self):
"binary erosion 7"
for type in self.types:
data = numarray.ones([5], type)
out = numarray.nd_image.binary_erosion(data)
self.failUnless(diff(out, [0, 1, 1, 1, 0]) < eps)
def test_binary_erosion08(self):
"binary erosion 8"
for type in self.types:
data = numarray.ones([5], type)
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, [1, 1, 1, 1, 1]) < eps)
def test_binary_erosion09(self):
"binary erosion 9"
for type in self.types:
data = numarray.ones([5], type)
data[2] = 0
out = numarray.nd_image.binary_erosion(data)
self.failUnless(diff(out, [0, 0, 0, 0, 0]) < eps)
def test_binary_erosion10(self):
"binary erosion 10"
for type in self.types:
data = numarray.ones([5], type)
data[2] = 0
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, [1, 0, 0, 0, 1]) < eps)
def test_binary_erosion11(self):
"binary erosion 11"
for type in self.types:
data = numarray.ones([5], type)
data[2] = 0
struct = [1, 0, 1]
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1)
self.failUnless(diff(out, [1, 0, 1, 0, 1]) < eps)
def test_binary_erosion12(self):
"binary erosion 12"
for type in self.types:
data = numarray.ones([5], type)
data[2] = 0
struct = [1, 0, 1]
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1,
origin = -1)
self.failUnless(diff(out, [0, 1, 0, 1, 1]) < eps)
def test_binary_erosion13(self):
"binary erosion 13"
for type in self.types:
data = numarray.ones([5], type)
data[2] = 0
struct = [1, 0, 1]
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1,
origin = 1)
self.failUnless(diff(out, [1, 1, 0, 1, 0]) < eps)
def test_binary_erosion14(self):
"binary erosion 14"
for type in self.types:
data = numarray.ones([5], type)
data[2] = 0
struct = [1, 1]
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1)
self.failUnless(diff(out, [1, 1, 0, 0, 1]) < eps)
def test_binary_erosion15(self):
"binary erosion 15"
for type in self.types:
data = numarray.ones([5], type)
data[2] = 0
struct = [1, 1]
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1,
origin = -1)
self.failUnless(diff(out, [1, 0, 0, 1, 1]) < eps)
def test_binary_erosion16(self):
"binary erosion 16"
for type in self.types:
data = numarray.ones([1, 1], type)
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, [[1]]) < eps)
def test_binary_erosion17(self):
"binary erosion 17"
for type in self.types:
data = numarray.ones([1, 1], type)
out = numarray.nd_image.binary_erosion(data)
self.failUnless(diff(out, [[0]]) < eps)
def test_binary_erosion18(self):
"binary erosion 18"
for type in self.types:
data = numarray.ones([1, 3], type)
out = numarray.nd_image.binary_erosion(data)
self.failUnless(diff(out, [[0, 0, 0]]) < eps)
def test_binary_erosion19(self):
"binary erosion 19"
for type in self.types:
data = numarray.ones([1, 3], type)
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, [[1, 1, 1]]) < eps)
def test_binary_erosion20(self):
"binary erosion 20"
for type in self.types:
data = numarray.ones([3, 3], type)
out = numarray.nd_image.binary_erosion(data)
self.failUnless(diff(out, [[0, 0, 0],
[0, 1, 0],
[0, 0, 0]]) < eps)
def test_binary_erosion21(self):
"binary erosion 21"
for type in self.types:
data = numarray.ones([3, 3], type)
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, [[1, 1, 1],
[1, 1, 1],
[1, 1, 1]]) < eps)
def test_binary_erosion22(self):
"binary erosion 22"
true = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 1, 1, 1, 1, 1, 1],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_erosion(data, border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion23(self):
"binary erosion 23"
struct = numarray.nd_image.generate_binary_structure(2, 2)
true = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 1, 1, 1, 1, 1, 1],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion24(self):
"binary erosion 24"
struct = [[0, 1],
[1, 1]]
true = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 1, 1, 1, 1, 1, 1],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion25(self):
"binary erosion 25"
struct = [[0, 1, 0],
[1, 0, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 1, 1, 1, 0, 1, 1],
[0, 0, 1, 0, 1, 1, 0, 0],
[0, 1, 0, 1, 1, 1, 1, 0],
[0, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion26(self):
"binary erosion 26"
struct = [[0, 1, 0],
[1, 0, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 1, 0, 0, 1],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 1, 1, 1, 0, 1, 1],
[0, 0, 1, 0, 1, 1, 0, 0],
[0, 1, 0, 1, 1, 1, 1, 0],
[0, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1, origin = (-1, -1))
self.failUnless(diff(out, true) < eps)
def test_binary_erosion27(self):
"binary erosion 27"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1, iterations = 2)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion28(self):
"binary erosion 28"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.zeros(data.shape, numarray.Bool)
numarray.nd_image.binary_erosion(data, struct, border_value = 1,
iterations = 2, output = out)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion29(self):
"binary erosion 29"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1, iterations = 3)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion30(self):
"binary erosion 30"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0]], numarray.Bool)
out = numarray.zeros(data.shape, numarray.Bool)
numarray.nd_image.binary_erosion(data, struct, border_value = 1,
iterations = 3, output = out)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion31(self):
"binary erosion 31"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0, 0],
[1, 1, 1, 1, 1, 0, 1],
[0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 1]]
data = numarray.array([[0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0]], numarray.Bool)
out = numarray.zeros(data.shape, numarray.Bool)
numarray.nd_image.binary_erosion(data, struct, border_value = 1,
iterations = 1, output = out, origin = (-1, -1))
self.failUnless(diff(out, true) < eps)
def test_binary_erosion32(self):
"binary erosion 32"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1, iterations = 2)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion33(self):
"binary erosion 33"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
mask = [[1, 1, 1, 1, 1, 0, 0],
[1, 1, 1, 1, 1, 1, 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]]
data = numarray.array([[0, 0, 0, 0, 0, 1, 1],
[0, 0, 0, 1, 0, 0, 1],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1, mask = mask, iterations = -1)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion34(self):
"binary erosion 34"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
mask = [[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 1, 0, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_erosion(data, struct,
border_value = 1, mask = mask)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion35(self):
"binary erosion 35"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
mask = [[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 1, 0, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 0, 0]], numarray.Bool)
tmp = [[0, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0, 0],
[1, 1, 1, 1, 1, 0, 1],
[0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 1]]
true = numarray.logical_and(tmp, mask)
tmp = numarray.logical_and(data, numarray.logical_not(mask))
true = numarray.logical_or(true, tmp)
out = numarray.zeros(data.shape, numarray.Bool)
numarray.nd_image.binary_erosion(data, struct, border_value = 1,
iterations = 1, output = out,
origin = (-1, -1), mask = mask)
self.failUnless(diff(out, true) < eps)
def test_binary_erosion36(self):
"binary erosion 36"
struct = [[0, 1, 0],
[1, 0, 1],
[0, 1, 0]]
mask = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
tmp = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 1, 0, 0, 1],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1]]
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 1, 1, 1, 0, 1, 1],
[0, 0, 1, 0, 1, 1, 0, 0],
[0, 1, 0, 1, 1, 1, 1, 0],
[0, 1, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]])
true = numarray.logical_and(tmp, mask)
tmp = numarray.logical_and(data, numarray.logical_not(mask))
true = numarray.logical_or(true, tmp)
out = numarray.nd_image.binary_erosion(data, struct, mask = mask,
border_value = 1, origin = (-1, -1))
self.failUnless(diff(out, true) < eps)
def test_binary_dilation01(self):
"binary dilation 1"
for type in self.types:
data = numarray.ones([], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, 1) < eps)
def test_binary_dilation02(self):
"binary dilation 2"
for type in self.types:
data = numarray.zeros([], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, 0) < eps)
def test_binary_dilation03(self):
"binary dilation 3"
for type in self.types:
data = numarray.ones([1], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [1]) < eps)
def test_binary_dilation04(self):
"binary dilation 4"
for type in self.types:
data = numarray.zeros([1], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [0]) < eps)
def test_binary_dilation05(self):
"binary dilation 5"
for type in self.types:
data = numarray.ones([3], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [1, 1, 1]) < eps)
def test_binary_dilation06(self):
"binary dilation 6"
for type in self.types:
data = numarray.zeros([3], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [0, 0, 0]) < eps)
def test_binary_dilation07(self):
"binary dilation 7"
struct = numarray.nd_image.generate_binary_structure(1, 1)
for type in self.types:
data = numarray.zeros([3], type)
data[1] = 1
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [1, 1, 1]) < eps)
def test_binary_dilation08(self):
"binary dilation 8"
for type in self.types:
data = numarray.zeros([5], type)
data[1] = 1
data[3] = 1
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [1, 1, 1, 1, 1]) < eps)
def test_binary_dilation09(self):
"binary dilation 9"
for type in self.types:
data = numarray.zeros([5], type)
data[1] = 1
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [1, 1, 1, 0, 0]) < eps)
def test_binary_dilation10(self):
"binary dilation 10"
for type in self.types:
data = numarray.zeros([5], type)
data[1] = 1
out = numarray.nd_image.binary_dilation(data, origin = -1)
self.failUnless(diff(out, [0, 1, 1, 1, 0]) < eps)
def test_binary_dilation11(self):
"binary dilation 11"
for type in self.types:
data = numarray.zeros([5], type)
data[1] = 1
out = numarray.nd_image.binary_dilation(data, origin = 1)
self.failUnless(diff(out, [1, 1, 0, 0, 0]) < eps)
def test_binary_dilation12(self):
"binary dilation 12"
for type in self.types:
data = numarray.zeros([5], type)
data[1] = 1
struct = [1, 0, 1]
out = numarray.nd_image.binary_dilation(data, struct)
self.failUnless(diff(out, [1, 0, 1, 0, 0]) < eps)
def test_binary_dilation13(self):
"binary dilation 13"
for type in self.types:
data = numarray.zeros([5], type)
data[1] = 1
struct = [1, 0, 1]
out = numarray.nd_image.binary_dilation(data, struct,
border_value = 1)
self.failUnless(diff(out, [1, 0, 1, 0, 1]) < eps)
def test_binary_dilation14(self):
"binary dilation 14"
for type in self.types:
data = numarray.zeros([5], type)
data[1] = 1
struct = [1, 0, 1]
out = numarray.nd_image.binary_dilation(data, struct,
origin = -1)
self.failUnless(diff(out, [0, 1, 0, 1, 0]) < eps)
def test_binary_dilation15(self):
"binary dilation 15"
for type in self.types:
data = numarray.zeros([5], type)
data[1] = 1
struct = [1, 0, 1]
out = numarray.nd_image.binary_dilation(data, struct,
origin = -1, border_value = 1)
self.failUnless(diff(out, [1, 1, 0, 1, 0]) < eps)
def test_binary_dilation16(self):
"binary dilation 16"
for type in self.types:
data = numarray.ones([1, 1], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [[1]]) < eps)
def test_binary_dilation17(self):
"binary dilation 17"
for type in self.types:
data = numarray.zeros([1, 1], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [[0]]) < eps)
def test_binary_dilation18(self):
"binary dilation 18"
for type in self.types:
data = numarray.ones([1, 3], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [[1, 1, 1]]) < eps)
def test_binary_dilation19(self):
"binary dilation 19"
for type in self.types:
data = numarray.ones([3, 3], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [[1, 1, 1],
[1, 1, 1],
[1, 1, 1]]) < eps)
def test_binary_dilation20(self):
"binary dilation 20"
for type in self.types:
data = numarray.zeros([3, 3], type)
data[1, 1] = 1
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]) < eps)
def test_binary_dilation21(self):
"binary dilation 21"
struct = numarray.nd_image.generate_binary_structure(2, 2)
for type in self.types:
data = numarray.zeros([3, 3], type)
data[1, 1] = 1
out = numarray.nd_image.binary_dilation(data, struct)
self.failUnless(diff(out, [[1, 1, 1],
[1, 1, 1],
[1, 1, 1]]) < eps)
def test_binary_dilation22(self):
"binary dilation 22"
true = [[0, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_dilation(data)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation23(self):
"binary dilation 23"
true = [[1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 0, 0, 0, 0, 1],
[1, 1, 0, 0, 0, 1, 0, 1],
[1, 0, 0, 1, 1, 1, 1, 1],
[1, 0, 1, 1, 1, 1, 0, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[1, 0, 1, 0, 0, 1, 0, 1],
[1, 1, 1, 1, 1, 1, 1, 1]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_dilation(data, border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation24(self):
"binary dilation 24"
true = [[1, 1, 0, 0, 0, 0, 0, 0],
[1, 0, 0, 0, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_dilation(data, origin = (1, 1))
self.failUnless(diff(out, true) < eps)
def test_binary_dilation25(self):
"binary dilation 25"
true = [[1, 1, 0, 0, 0, 0, 1, 1],
[1, 0, 0, 0, 1, 0, 1, 1],
[0, 0, 1, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 0, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[0, 1, 0, 0, 1, 0, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_dilation(data, origin = (1, 1),
border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation26(self):
"binary dilation 26"
struct = numarray.nd_image.generate_binary_structure(2, 2)
true = [[1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_dilation(data, struct)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation27(self):
"binary dilation 27"
struct = [[0, 1],
[1, 1]]
true = [[0, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 0, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_dilation(data, struct)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation28(self):
"binary dilation 28"
true = [[1, 1, 1, 1],
[1, 0, 0, 1],
[1, 0, 0, 1],
[1, 1, 1, 1]]
for type in self.types:
data = numarray.array([[0, 0, 0, 0],
[0, 0, 0, 0],
[0, 0, 0, 0],
[0, 0, 0, 0]], type)
out = numarray.nd_image.binary_dilation(data, border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation29(self):
"binary dilation 29"
struct = [[0, 1],
[1, 1]]
true = [[0, 0, 0, 0, 0],
[0, 0, 0, 1, 0],
[0, 0, 1, 1, 0],
[0, 1, 1, 1, 0],
[0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 1, 0],
[0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_dilation(data, struct,
iterations = 2)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation30(self):
"binary dilation 30"
struct = [[0, 1],
[1, 1]]
true = [[0, 0, 0, 0, 0],
[0, 0, 0, 1, 0],
[0, 0, 1, 1, 0],
[0, 1, 1, 1, 0],
[0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 1, 0],
[0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.zeros(data.shape, numarray.Bool)
numarray.nd_image.binary_dilation(data, struct, iterations = 2,
output = out)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation31(self):
"binary dilation 31"
struct = [[0, 1],
[1, 1]]
true = [[0, 0, 0, 1, 0],
[0, 0, 1, 1, 0],
[0, 1, 1, 1, 0],
[1, 1, 1, 1, 0],
[0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 1, 0],
[0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_dilation(data, struct,
iterations = 3)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation32(self):
"binary dilation 32"
struct = [[0, 1],
[1, 1]]
true = [[0, 0, 0, 1, 0],
[0, 0, 1, 1, 0],
[0, 1, 1, 1, 0],
[1, 1, 1, 1, 0],
[0, 0, 0, 0, 0]]
data = numarray.array([[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 1, 0],
[0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.zeros(data.shape, numarray.Bool)
numarray.nd_image.binary_dilation(data, struct, iterations = 3,
output = out)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation33(self):
"binary dilation 33"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 0, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
mask = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 0, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
data = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_dilation(data, struct,
iterations = -1, mask = mask, border_value = 0)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation34(self):
"binary dilation 34"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
mask = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
data = numarray.zeros(mask.shape, numarray.Bool)
out = numarray.nd_image.binary_dilation(data, struct,
iterations = -1, mask = mask, border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_dilation35(self):
"binary dilation 35"
tmp = [[1, 1, 0, 0, 0, 0, 1, 1],
[1, 0, 0, 0, 1, 0, 1, 1],
[0, 0, 1, 1, 1, 1, 1, 1],
[0, 1, 1, 1, 1, 0, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[0, 1, 0, 0, 1, 0, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1]]
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]])
mask = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
true = numarray.logical_and(tmp, mask)
tmp = numarray.logical_and(data, numarray.logical_not(mask))
true = numarray.logical_or(true, tmp)
for type in self.types:
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_dilation(data, mask = mask,
origin = (1, 1), border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_propagation01(self):
"binary propagation 1"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 0, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
mask = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 0, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
data = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_propagation(data, struct,
mask = mask, border_value = 0)
self.failUnless(diff(out, true) < eps)
def test_binary_propagation02(self):
"binary propagation 2"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
mask = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
data = numarray.zeros(mask.shape, numarray.Bool)
out = numarray.nd_image.binary_propagation(data, struct,
mask = mask, border_value = 1)
self.failUnless(diff(out, true) < eps)
def test_binary_opening01(self):
"binary opening 1"
true = [[0, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 1, 1, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 0, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_opening(data)
self.failUnless(diff(out, true) < eps)
def test_binary_opening02(self):
"binary opening 2"
struct = numarray.nd_image.generate_binary_structure(2, 2)
true = [[1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_opening(data, struct)
self.failUnless(diff(out, true) < eps)
def test_binary_closing01(self):
"binary closing 1"
true = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 0, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_closing(data)
self.failUnless(diff(out, true) < eps)
def test_binary_closing02(self):
"binary closing 2"
struct = numarray.nd_image.generate_binary_structure(2, 2)
true = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 0, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_closing(data, struct)
self.failUnless(diff(out, true) < eps)
def test_binary_fill_holes01(self):
"binary fill holes 1"
true = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_fill_holes(data)
self.failUnless(diff(out, true) < eps)
def test_binary_fill_holes02(self):
"binary fill holes 2"
true = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 1, 0, 0, 1, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_fill_holes(data)
self.failUnless(diff(out, true) < eps)
def test_binary_fill_holes03(self):
"binary fill holes 3"
true = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 1, 1],
[0, 1, 1, 1, 0, 1, 1, 1],
[0, 1, 1, 1, 0, 1, 1, 1],
[0, 0, 1, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
data = numarray.array([[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 1, 0, 1, 1, 1],
[0, 1, 0, 1, 0, 1, 0, 1],
[0, 1, 0, 1, 0, 1, 0, 1],
[0, 0, 1, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 0]], numarray.Bool)
out = numarray.nd_image.binary_fill_holes(data)
self.failUnless(diff(out, true) < eps)
def test_grey_erosion01(self):
"grey erosion 1"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
output = numarray.nd_image.grey_erosion(array,
footprint = footprint)
self.failUnless(diff([[2, 2, 1, 1, 1],
[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1]], output) < eps)
def test_grey_erosion02(self):
"grey erosion 2"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
output = numarray.nd_image.grey_erosion(array,
footprint = footprint, structure = structure)
self.failUnless(diff([[2, 2, 1, 1, 1],
[2, 3, 1, 3, 1],
[5, 5, 3, 3, 1]], output) < eps)
def test_grey_erosion03(self):
"grey erosion 3"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[1, 1, 1], [1, 1, 1]]
output = numarray.nd_image.grey_erosion(array,
footprint = footprint, structure = structure)
self.failUnless(diff([[1, 1, 0, 0, 0],
[1, 2, 0, 2, 0],
[4, 4, 2, 2, 0]], output) < eps)
def test_grey_dilation01(self):
"grey dilation 1"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[0, 1, 1], [1, 0, 1]]
output = numarray.nd_image.grey_dilation(array,
footprint = footprint)
self.failUnless(diff([[7, 7, 9, 9, 5],
[7, 9, 8, 9, 7],
[8, 8, 8, 7, 7]], output) < eps)
def test_grey_dilation02(self):
"grey dilation 2"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[0, 1, 1], [1, 0, 1]]
structure = [[0, 0, 0], [0, 0, 0]]
output = numarray.nd_image.grey_dilation(array,
footprint = footprint, structure = structure)
self.failUnless(diff([[7, 7, 9, 9, 5],
[7, 9, 8, 9, 7],
[8, 8, 8, 7, 7]], output) < eps)
def test_grey_dilation03(self):
"grey dilation 3"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[0, 1, 1], [1, 0, 1]]
structure = [[1, 1, 1], [1, 1, 1]]
output = numarray.nd_image.grey_dilation(array,
footprint = footprint, structure = structure)
self.failUnless(diff([[8, 8, 10, 10, 6],
[8, 10, 9, 10, 8],
[9, 9, 9, 8, 8]], output) < eps)
def test_grey_opening01(self):
"grey opening 1"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
tmp = numarray.nd_image.grey_erosion(array, footprint = footprint)
true = numarray.nd_image.grey_dilation(tmp, footprint = footprint)
output = numarray.nd_image.grey_opening(array,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
def test_grey_opening02(self):
"grey opening 2"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp = numarray.nd_image.grey_erosion(array, footprint = footprint,
structure = structure)
true = numarray.nd_image.grey_dilation(tmp, footprint = footprint,
structure = structure)
output = numarray.nd_image.grey_opening(array,
footprint = footprint, structure = structure)
self.failUnless(diff(true, output) < eps)
def test_grey_closing01(self):
"grey closing 1"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
tmp = numarray.nd_image.grey_dilation(array, footprint = footprint)
true = numarray.nd_image.grey_erosion(tmp, footprint = footprint)
output = numarray.nd_image.grey_closing(array,
footprint = footprint)
self.failUnless(diff(true, output) < eps)
def test_grey_closing02(self):
"grey closing 2"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp = numarray.nd_image.grey_dilation(array, footprint = footprint,
structure = structure)
true = numarray.nd_image.grey_erosion(tmp, footprint = footprint,
structure = structure)
output = numarray.nd_image.grey_closing(array,
footprint = footprint, structure = structure)
self.failUnless(diff(true, output) < eps)
def test_morphological_gradient01(self):
"morphological gradient 1"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp1 = numarray.nd_image.grey_dilation(array,
footprint = footprint, structure = structure)
tmp2 = numarray.nd_image.grey_erosion(array, footprint = footprint,
structure = structure)
true = tmp1 - tmp2
output = numarray.zeros(array.shape, array.type())
numarray.nd_image.morphological_gradient(array,
footprint=footprint, structure=structure, output = output)
self.failUnless(diff(true, output) < eps)
def test_morphological_gradient02(self):
"morphological gradient 2"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp1 = numarray.nd_image.grey_dilation(array,
footprint = footprint, structure = structure)
tmp2 = numarray.nd_image.grey_erosion(array, footprint = footprint,
structure = structure)
true = tmp1 - tmp2
output =numarray.nd_image.morphological_gradient(array,
footprint=footprint, structure=structure)
self.failUnless(diff(true, output) < eps)
def test_morphological_laplace01(self):
"morphological laplace 1"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp1 = numarray.nd_image.grey_dilation(array,
footprint = footprint, structure = structure)
tmp2 = numarray.nd_image.grey_erosion(array, footprint = footprint,
structure = structure)
true = tmp1 + tmp2 - 2 * array
output = numarray.zeros(array.shape, array.type())
numarray.nd_image.morphological_laplace(array, footprint=footprint,
structure=structure, output = output)
self.failUnless(diff(true, output) < eps)
def test_morphological_laplace02(self):
"morphological laplace 2"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp1 = numarray.nd_image.grey_dilation(array,
footprint = footprint, structure = structure)
tmp2 = numarray.nd_image.grey_erosion(array, footprint = footprint,
structure = structure)
true = tmp1 + tmp2 - 2 * array
output = numarray.nd_image.morphological_laplace(array,
footprint=footprint, structure=structure)
self.failUnless(diff(true, output) < eps)
def test_white_tophat01(self):
"white tophat 1"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp = numarray.nd_image.grey_opening(array, footprint = footprint,
structure = structure)
true = array - tmp
output = numarray.zeros(array.shape, array.type())
numarray.nd_image.white_tophat(array, footprint=footprint,
structure=structure, output = output)
self.failUnless(diff(true, output) < eps)
def test_white_tophat02(self):
"white tophat 2"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp = numarray.nd_image.grey_opening(array, footprint = footprint,
structure = structure)
true = array - tmp
output = numarray.nd_image.white_tophat(array, footprint=footprint,
structure=structure)
self.failUnless(diff(true, output) < eps)
def test_black_tophat01(self):
"black tophat 1"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp = numarray.nd_image.grey_closing(array, footprint = footprint,
structure = structure)
true = tmp - array
output = numarray.zeros(array.shape, array.type())
numarray.nd_image.black_tophat(array, footprint=footprint,
structure=structure, output = output)
self.failUnless(diff(true, output) < eps)
def test_black_tophat02(self):
"black tophat 2"
array = numarray.array([[3, 2, 5, 1, 4],
[7, 6, 9, 3, 5],
[5, 8, 3, 7, 1]])
footprint = [[1, 0, 1], [1, 1, 0]]
structure = [[0, 0, 0], [0, 0, 0]]
tmp = numarray.nd_image.grey_closing(array, footprint = footprint,
structure = structure)
true = tmp - array
output = numarray.nd_image.black_tophat(array, footprint=footprint,
structure=structure)
self.failUnless(diff(true, output) < eps)
def test_hit_or_miss01(self):
"binary hit-or-miss transform 1"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0],
[0, 1, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 1, 0, 0, 0],
[1, 1, 1, 0, 0],
[0, 1, 0, 1, 1],
[0, 0, 1, 1, 1],
[0, 1, 1, 1, 0],
[0, 1, 1, 1, 1],
[0, 1, 1, 1, 1],
[0, 0, 0, 0, 0]], type)
out = numarray.zeros(data.shape, numarray.Bool)
numarray.nd_image.binary_hit_or_miss(data, struct,
output = out)
self.failUnless(diff(true, out) < eps)
def test_hit_or_miss02(self):
"binary hit-or-miss transform 2"
struct = [[0, 1, 0],
[1, 1, 1],
[0, 1, 0]]
true = [[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 1, 0, 0, 1, 1, 1, 0],
[1, 1, 1, 0, 0, 1, 0, 0],
[0, 1, 0, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_hit_or_miss(data, struct)
self.failUnless(diff(true, out) < eps)
def test_hit_or_miss03(self):
"binary hit-or-miss transform 3"
struct1 = [[0, 0, 0],
[1, 1, 1],
[0, 0, 0]]
struct2 = [[1, 1, 1],
[0, 0, 0],
[1, 1, 1]]
true = [[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]]
for type in self.types:
data = numarray.array([[0, 1, 0, 0, 1, 1, 1, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 0, 1, 1, 0],
[0, 0, 0, 0, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0]], type)
out = numarray.nd_image.binary_hit_or_miss(data, struct1,
struct2)
self.failUnless(diff(true, out) < eps)
class NDImageTestResult(unittest.TestResult):
separator1 = '=' * 70 + '\n'
separator2 = '-' * 70 + '\n'
def __init__(self, stream, verbose):
unittest.TestResult.__init__(self)
self.stream = stream
self.verbose = verbose
def getDescription(self, test):
return test.shortDescription() or str(test)
def startTest(self, test):
unittest.TestResult.startTest(self, test)
if self.verbose:
self.stream.write(self.getDescription(test))
self.stream.write(" ... ")
def addSuccess(self, test):
unittest.TestResult.addSuccess(self, test)
if self.verbose:
self.stream.write("ok\n")
def addError(self, test, err):
unittest.TestResult.addError(self, test, err)
if self.verbose:
self.stream.write("ERROR\n")
def addFailure(self, test, err):
unittest.TestResult.addFailure(self, test, err)
if self.verbose:
self.stream.write("FAIL\n")
def printErrors(self):
self.printErrorList('ERROR', self.errors)
self.printErrorList('FAIL', self.failures)
def printErrorList(self, flavour, errors):
for test, err in errors:
self.stream.write(self.separator1)
description = self.getDescription(test)
self.stream.write("%s: %s\n" % (flavour, description))
self.stream.write(self.separator2)
self.stream.write(err)
def test():
if '-v' in sys.argv[1:]:
verbose = 1
else:
verbose = 0
suite = unittest.TestSuite()
suite.addTest(unittest.makeSuite(NDImageTest))
result = NDImageTestResult(sys.stdout, verbose)
suite(result)
result.printErrors()
return len(result.failures), result.testsRun
if __name__ == '__main__':
unittest.main()
| 45.052049
| 77
| 0.399651
| 31,056
| 248,417
| 3.134724
| 0.024504
| 0.110075
| 0.137501
| 0.155395
| 0.861184
| 0.846403
| 0.829156
| 0.818319
| 0.799562
| 0.777139
| 0
| 0.127555
| 0.457505
| 248,417
| 5,513
| 78
| 45.060221
| 0.594828
| 0.033794
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| 0
| 0
| 0.027695
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.086077
| false
| 0
| 0.001388
| 0.004562
| 0.09401
| 0.019437
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| 0
| 0
|
0
| 7
|
2603a67a919f0c378150a72620ff78ddacb74ce3
| 2,475
|
py
|
Python
|
function/tabtap.py
|
RomanDiachenko/FirstTestRepository
|
f3ef4569b875011c018a0ddcd1a5e3adce78589a
|
[
"Apache-2.0"
] | null | null | null |
function/tabtap.py
|
RomanDiachenko/FirstTestRepository
|
f3ef4569b875011c018a0ddcd1a5e3adce78589a
|
[
"Apache-2.0"
] | null | null | null |
function/tabtap.py
|
RomanDiachenko/FirstTestRepository
|
f3ef4569b875011c018a0ddcd1a5e3adce78589a
|
[
"Apache-2.0"
] | null | null | null |
import time
class TabTap:
def __init__(self, app):
self.app = app
# Switch tab
def tab_test(self):
driver = self.app.driver
driver.find_element_by_xpath("//a[@id='0']//span[@class='sidebar__list-link-name']").click()
time.sleep(0.5)
driver.find_element_by_xpath("//a[@id='10002']//span[@class='sidebar__list-link-name']").click()
time.sleep(0.5)
driver.find_element_by_xpath("//a[@id='10001']//span[@class='sidebar__list-link-name']").click()
time.sleep(0.5)
driver.find_element_by_xpath("//a[@id='10003']//span[@class='sidebar__list-link-name']").click()
time.sleep(0.5)
driver.find_element_by_xpath("//a[@id='10004']//span[@class='sidebar__list-link-name']").click()
time.sleep(0.5)
driver.find_element_by_xpath("//a[@id='unread']//span[@class='sidebar__list-link-name']").click()
time.sleep(0.5)
driver.find_element_by_xpath("//a[@id='marked']//span[@class='sidebar__list-link-name']").click()
time.sleep(0.5)
driver.find_element_by_xpath(
"//a[@class='sidebar__list-link files']//span[@class='sidebar__list-link-name']").click()
time.sleep(1)
# Go to drafts tab
def go_to_drafts(self):
driver = self.app.driver
driver.find_element_by_xpath("//a[@id='10002']//span[@class='sidebar__list-link-name']").click()
time.sleep(0.5)
# Open drafts tab
def open_drafts(self):
driver = self.app.driver
driver.find_element_by_xpath("//a[@class='msglist__row_href']")
time.sleep(1)
# Open send mail
def open_set_mail(self):
driver = self.app.driver
driver.find_element_by_xpath("//a[@id='10001']//span[@class='sidebar__list-link-name']").click()
time.sleep(2)
# Open favorite
def open_send(self):
driver = self.app.driver
driver.find_element_by_xpath(
"//a[@id='10001']//span[@class='sidebar__list-link-name']").click()
time.sleep(1)
def set_favourite(self):
driver = self.app.driver
driver.find_element_by_xpath("/html[1]/body[1]/div[1]/div[2]/div[1]/div[1]/div[2]/section[1]/table[1]/tbody[1]/tr[1]/td[7]/div[1]/span[1]").click()
time.sleep(1)
def open_marker_mail(self):
driver = self.app.driver
driver.find_element_by_xpath("//a[@id='marked']//span[@class='sidebar__list-link-name']").click()
time.sleep(1)
| 38.671875
| 155
| 0.616566
| 361
| 2,475
| 3.99169
| 0.160665
| 0.097155
| 0.165163
| 0.184594
| 0.80569
| 0.778626
| 0.778626
| 0.771686
| 0.771686
| 0.771686
| 0
| 0.035892
| 0.189495
| 2,475
| 63
| 156
| 39.285714
| 0.682453
| 0.029091
| 0
| 0.583333
| 0
| 0.020833
| 0.346683
| 0.346266
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.020833
| 0
| 0.208333
| 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
|
2629d195438b7eb2d264776d5b457ab9f39d0655
| 49
|
py
|
Python
|
instance/config.py
|
BrianTinega/News-Highlights
|
b383cf699572f3cade56d9852e3072e3499f930d
|
[
"MIT"
] | null | null | null |
instance/config.py
|
BrianTinega/News-Highlights
|
b383cf699572f3cade56d9852e3072e3499f930d
|
[
"MIT"
] | null | null | null |
instance/config.py
|
BrianTinega/News-Highlights
|
b383cf699572f3cade56d9852e3072e3499f930d
|
[
"MIT"
] | null | null | null |
NEWS_API_KEY= 'd166dd427c144727bf496805eaeb43a9'
| 24.5
| 48
| 0.897959
| 4
| 49
| 10.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.446809
| 0.040816
| 49
| 2
| 48
| 24.5
| 0.446809
| 0
| 0
| 0
| 0
| 0
| 0.653061
| 0.653061
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
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