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slimano/core/persistence/models/nst.py | ATNoG/5gcontact | 1 | 123562 | from persistence.models.models_base import Base
from sqlalchemy import Column, Integer, String
class Nst(Base):
__tablename__ = 'nst'
id = Column(String(40), primary_key=True)
name = Column(String(16))
template = Column(String(10000))
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scripts/init.py | LCAS/spqrel_tools | 9 | 80923 | #!/usr/bin/env python
import qi
import argparse
import sys
import time
import os
import webinit, postureinit, behaviorinit, manage_BG_behaviors, tmuxinit
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--pip", type=str, default=os.getenv('PEPPER_IP'),
help="Robot IP address. On robot or Local Naoqi: use '127.0.0.1'.")
parser.add_argument("--pport", type=int, default=9559,
help="Naoqi port number")
args = parser.parse_args()
pip = args.pip
pport = args.pport
try:
connection_url = "tcp://" + pip + ":" + str(pport)
print "Connecting to ", connection_url
app = qi.Application(["Init", "--qi-url=" + connection_url ])
except RuntimeError:
print ("Can't connect to Naoqi at ip \"" + pip + "\" on port " + str(pport) +".\n"
"Please check your script arguments. Run with -h option for help.")
sys.exit(1)
app.start()
session = app.session
tts_service = session.service("ALTextToSpeech")
tts_service.say("Initialization started.")
tts_service.setParameter("speed", 80)
time.sleep(1)
#webinit.do_init(session)
#time.sleep(1)
postureinit.do_init(session)
time.sleep(3)
manage_BG_behaviors.stop_behavior(session, 'boot-config'):
time.sleep(3)
manage_BG_behaviors.start_behaviors(session,pip,pport)
tts_service.say("Initialization completed.")
tmuxinit.do_init()
tts_service.say("I am ready.")
if __name__ == "__main__":
print "Waiting 15 seconds before starting ..."
time.sleep(15)
main()
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disturbance/migrations/0006_auto_20180618_1556.py | wilsonc86/ledger | 0 | 66528 | # -*- coding: utf-8 -*-
# Generated by Django 1.10.8 on 2018-06-18 07:56
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('disturbance', '0005_auto_20180618_1123'),
]
operations = [
migrations.RemoveField(
model_name='proposalapprovergroup',
name='activities',
),
migrations.RemoveField(
model_name='proposalapprovergroup',
name='regions',
),
migrations.RemoveField(
model_name='proposalassessorgroup',
name='activities',
),
migrations.RemoveField(
model_name='proposalassessorgroup',
name='regions',
),
]
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time_management/main.py | AyushRawal/time-management | 1 | 187021 | <gh_stars>1-10
from interface_mode import run_menu_loop_mode
from facade import DatabaseFacade
import os
def main():
print("Welcome to Time Management!\n\n")
database = os.path.join(os.path.dirname(__file__), "time_management.db")
database_facade = DatabaseFacade(database)
run_menu_loop_mode(database_facade)
if __name__ == "__main__":
main()
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ssplanner/coresetup/models.py | AravinthKannan/Bharathi | 0 | 81921 | <reponame>AravinthKannan/Bharathi
# -*- coding: utf-8 -*-
# python manage.py make migrations your_app_label
# python manage.py migrate --fake-initial your_app_label
from __future__ import unicode_literals
from django.db import models
#from django.contrib.auth.models import User
from django.contrib.auth.models import (
AbstractUser,
BaseUserManager
)
from django.utils import timezone
from datetime import date, datetime
from django.contrib.auth import get_user_model
from django.conf import settings
# accounts.models.py
from django.db import models
from django.contrib.auth.models import User
# accounts.models.py
from django.db import models
from django.contrib.auth.models import (
BaseUserManager, AbstractBaseUser
)
class ContactManager(BaseUserManager):
"""Summary
"""
def create_user(self, mobile_number, password=None):
"""
Creates and saves a User with the given mobile_number and password.
Args:
mobile_number (TYPE): Description
password (None, optional): Description
Returns:
TYPE: Description
Raises:
ValueError: Description
"""
if not mobile_number:
raise ValueError('Users must have an mobile_number address')
user = self.model(
mobile_number=self.normalize_mobile_number(mobile_number),
)
user.set_password(password)
user.save(using=self._db)
return user
def create_staffuser(self, mobile_number, password):
"""
Creates and saves a staff user with the given mobile_number and password.
Args:
mobile_number (TYPE): Description
password (TYPE): Description
Returns:
TYPE: Description
"""
user = self.create_user(
mobile_number,
password=password,
)
user.staff = True
user.save(using=self._db)
return user
def create_superuser(self, mobile_number, password):
"""
Creates and saves a superuser with the given mobile_number and password.
Args:
mobile_number (TYPE): Description
password (TYPE): Description
Returns:
TYPE: Description
"""
user = self.create_user(
mobile_number,
password=password,
)
user.staff = True
user.admin = True
user.save(using=self._db)
return user
class Contact(AbstractBaseUser):
"""Summary
Attributes:
mobile_number (TYPE): Description
objects (TYPE): Description
"""
objects = ContactManager()
mobile_number = models.IntegerField(unique=True)
USERNAME_FIELD = 'mobile_number'
class Topic(models.Model):
"""Topic based on share is created
Attributes:
created_at (TYPE): Description
created_by (TYPE): Description
split_number (TYPE): Description
total_amount (TYPE): Description
updated_at (TYPE): Description
updated_by (TYPE): Description
"""
total_amount = models.IntegerField()
split_number = models.IntegerField()
created_by = models.ForeignKey(
settings.AUTH_USER_MODEL,
related_name= 'topic_created',
on_delete=models.CASCADE
)
updated_by = models.ForeignKey(
settings.AUTH_USER_MODEL,
related_name= 'topic_updated',
on_delete=models.CASCADE
)
created_at = models.DateTimeField(auto_now_add=True)
updated_at = models.DateTimeField(auto_now=True)
class SplitAmountLedger(models.Model):
"""List of splitted amount to each user under same topic
Attributes:
created_at (TYPE): Description
created_by (TYPE): Description
splitted_amount (TYPE): Description
splitted_user (TYPE): Description
updated_at (TYPE): Description
updated_by (TYPE): Description
"""
splitted_user = models.ForeignKey(
settings.AUTH_USER_MODEL,
related_name= 'sa_ledger_user',
on_delete=models.CASCADE
)
splitted_amount = models.IntegerField()
created_by = models.ForeignKey(
settings.AUTH_USER_MODEL,
related_name= 'sa_ledger_created',
on_delete=models.CASCADE
)
updated_by = models.ForeignKey(
settings.AUTH_USER_MODEL,
related_name= 'sa_ledger_updated',
on_delete=models.CASCADE
)
created_at = models.DateTimeField(auto_now_add=True)
updated_at = models.DateTimeField(auto_now=True)
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] |
Packs/Pcysys/Integrations/Pcysys/Pcysys_test.py | diCagri/content | 799 | 158790 | import demistomock as demisto
import jwt
from Pcysys import Client, pentera_run_template_command, pentera_get_task_run_status_command, \
pentera_get_task_run_full_action_report_command, pentera_authentication
MOCK_PENTERA_FULL_ACTION_REPORT = 'penterascan-5e4530961deb8eda82b08730.csv'
MOCK_CSV = open('TestData/mock_csv_file', 'r').read()
MOCK_AUTHENTICATION = {
"token": "TOKEN",
"tgt": "TGT"
}
MOCK_AUTHENTICATION_EXP = 1579763364
MOCK_RUN_TEMPLATE = {
"taskRuns": [
{
"status": "Running",
"taskRunId": "5e41923cf24e1f99979b1cb4",
"taskRunName": "Test mock task run name",
"startTime": 1581348380358.0,
"endTime": 1581349123973.0,
}
],
}
MOCK_TASK_RUN_STATS = {
"taskRuns": [
{
"taskRunId": "5e41923cf24e1f99979b1cb4",
"taskRunName": "Test mock task run name",
"startTime": 1581348380358.0,
"endTime": 1581349123973.0,
"status": "Warning"
}
]
}
def test_pentera_get_task_run_full_action_report(mocker, requests_mock):
mocker.patch.object(demisto, 'params', return_value={
'url': 'https://pentera.com',
'port': '8181'
})
mocker.patch.object(demisto, 'getIntegrationContext', return_value={
'base_url': 'https://pentera.com',
'tgt': 'omgNewTGT',
'accessToken': '<PASSWORD>',
'expiry': MOCK_AUTHENTICATION_EXP
})
mocker.patch.object(demisto, 'args', return_value={
'task_run_id': '5e4530961deb8eda82b08730'
})
requests_mock.get('https://pentera.com:8181/api/v1/taskRun/5e4530961deb8eda82b08730/fullActionReportCSV',
text=MOCK_CSV)
client_id = demisto.params().get('clientId')
tgt = demisto.params().get('tgt')
base_url = demisto.params()['url'].rstrip('/') + ':' + demisto.params()['port']
verify_certificate = not demisto.params().get('insecure', False)
proxy = demisto.params().get('proxy', False)
args = demisto.args()
client = Client(
base_url=base_url,
tgt=tgt,
verify=verify_certificate,
client_id=client_id,
proxy=proxy,
headers={'Accept': 'application/json'})
entries = pentera_get_task_run_full_action_report_command(client, args)
raw_csv_file_name = entries[0]['File']
assert raw_csv_file_name == MOCK_PENTERA_FULL_ACTION_REPORT
task_run_id = entries[1]['EntryContext']['Pentera.TaskRun(val.ID == obj.ID)']['ID']
assert task_run_id == '5e4530961deb8eda82b08730'
operation_type = entries[1]['EntryContext']['Pentera.TaskRun(val.ID == obj.ID)']['FullActionReport'][0][
'Operation Type']
assert operation_type == 'BlueKeep (CVE-2019-0708) Vulnerability Discovery'
def test_pentera_get_task_run_stats(mocker, requests_mock):
mocker.patch.object(demisto, 'params', return_value={
'url': 'https://pentera.com',
'port': '8181'
})
mocker.patch.object(demisto, 'getIntegrationContext', return_value={
'base_url': 'https://pentera.com',
'tgt': 'omgNewTGT',
'accessToken': 'omg<PASSWORD>',
'expiry': MOCK_AUTHENTICATION_EXP
})
mocker.patch.object(demisto, 'args', return_value={
'task_run_id': '5e41923cf24e1f99979b1cb4'
})
requests_mock.get('https://pentera.com:8181/api/v1/taskRun/5e41923cf24e1f99979b1cb4',
json=MOCK_RUN_TEMPLATE)
client_id = demisto.params().get('clientId')
tgt = demisto.params().get('tgt')
base_url = demisto.params()['url'].rstrip('/') + ':' + demisto.params()['port']
verify_certificate = not demisto.params().get('insecure', False)
proxy = demisto.params().get('proxy', False)
args = demisto.args()
client = Client(
base_url=base_url,
tgt=tgt,
verify=verify_certificate,
client_id=client_id,
proxy=proxy,
headers={'Accept': 'application/json'})
readable, parsed, raw = pentera_get_task_run_status_command(client, args)
assert parsed['Pentera.TaskRun(val.ID == obj.ID)']['ID'] == MOCK_TASK_RUN_STATS['taskRuns'][0]['taskRunId']
def test_pentera_run_template(mocker, requests_mock):
mocker.patch.object(demisto, 'params', return_value={
'url': 'https://pentera.com',
'port': '8181'
})
mocker.patch.object(demisto, 'getIntegrationContext', return_value={
'base_url': 'https://pentera.com',
'tgt': 'omgNewTGT',
'accessToken': 'omgNewSecret',
'expiry': MOCK_AUTHENTICATION_EXP
})
mocker.patch.object(demisto, 'args', return_value={
'template_name': 'omgRunThisTemplate'
})
requests_mock.post('https://pentera.com:8181/api/v1/template/runBulk', json=MOCK_RUN_TEMPLATE)
client_id = demisto.params().get('clientId')
tgt = demisto.params().get('tgt')
base_url = demisto.params()['url'].rstrip('/') + ':' + demisto.params()['port']
verify_certificate = not demisto.params().get('insecure', False)
proxy = demisto.params().get('proxy', False)
args = demisto.args()
client = Client(
base_url=base_url,
tgt=tgt,
verify=verify_certificate,
client_id=client_id,
proxy=proxy,
headers={'Accept': 'application/json'})
readable, parsed, raw = pentera_run_template_command(client, args)
assert parsed['Pentera.TaskRun(val.ID == obj.ID)']['Status'] == MOCK_RUN_TEMPLATE['taskRuns'][0]['status']
def test_pentera_authentication(mocker, requests_mock):
mocker.patch.object(demisto, 'params', return_value={
'clientId': 'mmtzv',
'tgt': 'omgSecretsWow',
'url': 'https://pentera.com',
'port': '8181'
})
mocker.patch.object(jwt, 'get_unverified_header',
return_value={'alg': 'HS256', 'exp': 1579763364, 'iat': 1579762464})
requests_mock.post('https://pentera.com:8181/auth/token', json=MOCK_AUTHENTICATION)
mocker.patch.object(demisto, 'args', return_value={})
mocker.patch.object(demisto, 'setIntegrationContext')
client_id = demisto.params().get('clientId')
tgt = demisto.params().get('tgt')
base_url = demisto.params()['url'].rstrip('/') + ':' + demisto.params()['port']
verify_certificate = not demisto.params().get('insecure', False)
proxy = demisto.params().get('proxy', False)
client = Client(
base_url=base_url,
tgt=tgt,
verify=verify_certificate,
client_id=client_id,
proxy=proxy,
headers={'Accept': 'application/json'})
pentera_authentication(client)
assert demisto.setIntegrationContext.call_count == 1
integration_context = demisto.setIntegrationContext.call_args[0][0]
assert isinstance(integration_context, dict)
assert integration_context['expiry'] == MOCK_AUTHENTICATION_EXP
assert integration_context['accessToken'] == MOCK_AUTHENTICATION['token']
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src/python/weblyzard_api/client/openrdf/__init__.py | PhilippKuntschik/weblyzard_api | 9 | 94646 | <reponame>PhilippKuntschik/weblyzard_api<gh_stars>1-10
#!/usr/bin/python
# -*- coding: utf8 -*-
'''
Created on 19.12.2013
@author: heinz-peterlang
For details: `check Sesame REST API<http://openrdf.callimachus.net/sesame/2.7/docs/system.docbook?view#The_Sesame_REST_HTTP_Protocol>`_
http://www.csee.umbc.edu/courses/graduate/691/spring14/01/examples/sesame/openrdf-sesame-2.6.10/docs/system/ch08.html
'''
from __future__ import print_function
from __future__ import unicode_literals
from future import standard_library
standard_library.install_aliases()
from builtins import object
import ast
import httplib2
import json
import os
import requests
import urllib.request, urllib.parse, urllib.error
from SPARQLWrapper import SPARQLWrapper, JSON
from collections import namedtuple
from pprint import pprint
try:
from urllib.parse import urlencode
except ImportError:
from urllib import urlencode
QUERIES = {
'configured_profiles': '''
PREFIX rdfs:<http://www.w3.org/2000/01/rdf-schema#>
PREFIX re: <http://www.semanticlab.net/prj/recognize/voc/>
SELECT ?s ?profile_name ?analyzer
WHERE {
?s rdfs:label ?profile_name .
?s re:analyzer ?analyzer .
}''',
'all_subjects': '''
select distinct ?s where {?s ?p ?o}
'''
}
RepositoryDetail = namedtuple('RepositoryDetail', ['id', 'uri', 'title'])
class OpenRdfClient(object):
DEFAULT_HEADERS = {'Accept': 'application/sparql-results+json'}
URL_MAPPING = {'get_repositories': ('/repositories', 'GET'),
'fetch_statements_repository': ('', 'GET')}
def __init__(self, server_uri):
''' initializes the client
:param server_uri: URL of the server
'''
plain_server_uri = server_uri
if not 'openrdf-sesame' in server_uri:
server_uri = '%s/openrdf-sesame' % server_uri
self.server_uri = server_uri
self.repository_url_tmplt = self.server_uri + '/repositories/%s'
server_update_uri = '%s/openrdf-workbench' % plain_server_uri
self.repository_url_update_tmplt = server_update_uri + \
'/repositories/%s/update'
def run_query(self, repository_name, query):
sparql = SPARQLWrapper(self.repository_url_tmplt % repository_name)
sparql.setQuery(query.strip())
sparql.setReturnFormat(JSON)
results = sparql.query().convert()
for result in results['results']['bindings']:
yield result
def update_query(self, repository_name, query):
sparql = SPARQLWrapper(
self.repository_url_update_tmplt % repository_name)
sparql.setQuery(query.strip())
sparql.setMethod('POST')
sparql.query()
def cleanup_config(self):
''' '''
for orphan in self.get_orphaned_analyzers():
self.delete_statements(self.config_repository,
subj='_:%s' % orphan,
delete=True)
def get_orphaned_analyzers(self):
profiles = self.get_profiles()
configured = []
for profile in profiles.values():
configured.extend(profile['analyzers'])
orphaned = []
query = QUERIES['all_subjects']
for result in self.run_query(self.config_repository, query):
name = result['s']['value']
if name.startswith('genid'):
if name in configured:
pass
else:
orphaned.append(name)
return orphaned
def get_profiles(self):
''' returns a dictionary (subject_uri, profile_name) for all profiles
configured in the config repositoriy
'''
self.check_config_repo()
query = QUERIES['configured_profiles']
profiles = {}
for result in self.run_query(self.config_repository, query):
profile = {}
profile_name = result['profile_name']['value']
profile['subject_uri'] = result['s']['value']
profile['analyzers'] = [result['analyzer']['value']]
if profile_name in profiles:
profiles[profile_name]['analyzers'].extend(
profile['analyzers'])
else:
profiles[profile_name] = profile
return profiles
def remove_profile(self, profile_name):
''' Removes a given profile name '''
subject_uris = []
profiles = self.get_profiles()
if profile_name in profiles:
profile = profiles[profile_name]
if not profile_name.startswith('pr:'):
profile_name = 'pr:%s' % profile_name
subject_uris.extend(
['<%s>' % analyzer for analyzer in profile['analyzers']])
subject_uris.append('<%s>' % profile['subject_uri'])
if len(subject_uris):
# if not subject_uri.startswith('pr:'):
# subject_uri = 'pr:%s' % subject_uri
# if not subject_uri.endswith('>'):
# subject_uri = '%s>' % subject_uri
for subject_uri in subject_uris:
try:
self.delete_statements(self.config_repository,
subj=subject_uri,
delete=True)
except Exception as e:
print(e)
def update_profile(self, profile_name, profile_definition):
''' Updates the given profile on the server '''
profiles = self.get_profiles()
if profile_name in profiles:
subject_uri = profiles[profile_name]['subject_uri']
if not subject_uri.endswith('>'):
subject_uri = '%s>' % subject_uri
self.delete_statements(self.config_repository,
subj=subject_uri,
delete=True)
self.upload_statement(content=profile_definition,
context='config.weblyzard.com',
target_repository=self.config_repository)
def check_config_repo(self):
repositories = self.get_repositories()
if not self.config_repository in repositories:
print('warning config repo "{}" does not exist'.format(
self.config_repository))
def request(self, function, data=None, params=None, delete=False,
content_type='applicatoni/rdf+json',
accept='application/sparql-results+json'):
''' executes the requests to the TripleStores
:param function: function (path) to request
:param data: data to add to the POST request
:returns: result of the server
:rtype: json encoded dict
'''
print('{}/{}'.format(self.server_uri, function))
if data:
method = 'POST'
headers = {'content-type': content_type}
else:
if delete:
method = 'DELETE'
else:
method = 'GET'
headers = {'Accept': accept}
if params:
function = '%s?%s' % (function, params)
print(method, '%{}/{}'.format(self.server_uri, function))
r = requests.request(method,
'%s/%s' % (self.server_uri, function),
data=data,
headers=headers)
text = r.text
try:
return json.loads(r.text) if r.text else r.text
except Exception as e:
print(text)
return text
def get_repo_size(self, repo_id):
''' '''
result = self.request('repositories/%s/size' % repo_id)
print('get_repo_size', result)
def get_repositories(self):
''' '''
result = self.request('repositories')
repositories = {}
if 'results' in result and 'bindings' in result['results']:
for repo in result['results']['bindings']:
repo_id = repo['id']['value']
repositories[repo_id] = RepositoryDetail(repo_id,
repo['uri']['value'],
repo['title']['value'])
return repositories
def repository_exists(self, repository_name):
return repository_name in self.get_repositories()
def get_all_statements(self, repository_name):
result = self.request('repositories/%s/statements' % repository_name)
pprint(result)
def delete_statements(self, repository_name, subj=None, pred=None, obj=None,
delete=False):
function = 'repositories/%s/statements' % repository_name
params = {}
if subj:
params['subj'] = subj
if pred:
params['pred'] = pred
if obj:
params['obj'] = obj
if params:
params = '&'.join(['%s=%s' % (k, v)
for k, v in params.items()])
else:
params = None
return self.request(function, params=params, delete=delete)
def upload_statement(self, content, context, target_repository):
''' '''
print('uploading to {}'.format(target_repository))
params = 'context=%s' % context
function = 'repositories/%s/statements' % target_repository
self.request(function, content, params, delete=False,
content_type='application/x-turtle;charset=UTF-8')
def check_exists(self, object, repository):
''' '''
query = 'describe <{}>'.format(object)
endpoint = "{}/repositories/{}" .format(self.server_uri, repository)
# print("POSTing SPARQL query to {}".format(endpoint))
params = {'query': query}
headers = {
'content-type': 'application/x-www-form-urlencoded',
# 'accept': 'application/sparql-results+json'
}
(response, content) = httplib2.Http().request(endpoint,
'POST',
urllib.parse.urlencode(params),
headers=headers)
# print("Response %s" % response.status)
return (response, content)
def execute_query(self, query, repository):
''' '''
params = {'query': query}
headers = {
'content-type': 'application/x-www-form-urlencoded',
'accept': 'application/sparql-results+json'
}
endpoint = "{}/{}/statements".format(self.server_uri, repository)
print(endpoint)
(response, content) = httplib2.Http().request(endpoint, 'POST',
urlencode(params),
headers=headers)
return (response, ast.literal_eval(content))
def execute_update(self, query, repository):
''' '''
params = {'update': query}
headers = {
'content-type': 'application/x-www-form-urlencoded',
'accept': 'application/sparql-results+json'
}
repository_url = self.repository_url_tmplt % repository
endpoint = "%s/statements" % (repository_url)
(response, content) = httplib2.Http().request(endpoint, 'POST',
urlencode(params),
headers=headers)
response = response['status']
return(response)
def delete_triples_by_types(self, repository, types):
''' '''
for rdf_type in types:
query = 'DELETE ?s WHERE {?s ?p ?o FILTER(?s = <%s>)}' % rdf_type
self.execute_update(query, repository)
def upload_repo_from_file(self, filename, repository):
''' '''
base_fn = os.path.basename(filename)
assert base_fn.endswith('ttl')
graph = 'file://%s' % base_fn
params = {'context': '<' + graph + '>'}
endpoint = "%s/%s/statements?%s" % (self.server_uri, repository,
urlencode(params))
print("Loading %s into %s in Sesame" % (filename, endpoint))
data = open(filename, 'r').read()
(response, content) = httplib2.Http().request(endpoint, 'PUT',
body=data,
headers={'content-type': 'application/x-turtle'})
print("Response %s" % response.status)
print(content)
class RecognizeOpenRdfClient(OpenRdfClient):
def __init__(self, server_uri, config_repository='config.weblyzard.com'):
OpenRdfClient.__init__(self, server_uri)
self.config_repository = config_repository
def cleanup_config(self):
''' '''
for orphan in self.get_orphaned_analyzers():
self.delete_statements(self.config_repository,
subj='_:%s' % orphan,
delete=True)
def get_orphaned_analyzers(self):
''' '''
profiles = self.get_profiles()
configured = []
for profile in profiles.values():
configured.extend(profile['analyzers'])
orphaned = []
query = QUERIES['all_subjects']
for result in self.run_query(self.config_repository, query):
name = result['s']['value']
if name.startswith('genid'):
if name in configured:
pass
else:
orphaned.append(name)
return orphaned
def get_profiles(self):
''' returns a dictionary (subject_uri, profile_name) for all profiles
configured in the config repositoriy
'''
self.check_config_repo()
query = QUERIES['configured_profiles']
profiles = {}
for result in self.run_query(self.config_repository, query):
profile = {}
profile_name = result['profile_name']['value']
profile['subject_uri'] = result['s']['value']
profile['analyzers'] = [result['analyzer']['value']]
if profile_name in profiles:
profiles[profile_name]['analyzers'].extend(
profile['analyzers'])
else:
profiles[profile_name] = profile
return profiles
def remove_profile(self, profile_name):
''' Removes a given profile name '''
subject_uris = []
profiles = self.get_profiles()
if profile_name in profiles:
profile = profiles[profile_name]
if not profile_name.startswith('pr:'):
profile_name = 'pr:%s' % profile_name
subject_uris.extend(
['<%s>' % analyzer for analyzer in profile['analyzers']])
subject_uris.append('<%s>' % profile['subject_uri'])
if len(subject_uris):
# if not subject_uri.startswith('pr:'):
# subject_uri = 'pr:%s' % subject_uri
# if not subject_uri.endswith('>'):
# subject_uri = '%s>' % subject_uri
for subject_uri in subject_uris:
try:
self.delete_statements(self.config_repository,
subj=subject_uri,
delete=True)
except (Exception) as e:
print(e)
def update_profile(self, profile_name, profile_definition):
''' Updates the given profile on the server '''
profiles = self.get_profiles()
if profile_name in profiles:
print(profile_name)
subject_uri = profiles[profile_name]['subject_uri']
# TODO: check why we need to fix this????
if not subject_uri.endswith('>'):
subject_uri = '%s>' % subject_uri
self.delete_statements(self.config_repository,
subj=subject_uri,
delete=True)
self.upload_statement(content=profile_definition,
context='config.weblyzard.com',
target_repository=self.config_repository)
def check_config_repo(self):
''' '''
repositories = self.get_repositories()
if not self.config_repository in repositories:
print('warning config repo "{}" does not exist'.format(
self.config_repository)
)
def create_template(self, entity, entity_type, language='en'):
''' '''
if entity_type.lower() == 'person':
names = entity.split('/')[-1].split('_')
surname = names[-1]
first_names = names[:len(names) - 1]
first_name = ' '.join(first_names)
tuples = [
'<{}> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://dbpedia.org/ontology/Person> .'.format(
entity),
'<{}> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person> .'.format(
entity),
'<{}> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://schema.org/Person> .'.format(
entity),
'<{}> <http://dbpedia.org/property/name> "{}, {}"@{} .'.format(
entity, surname, first_name, language),
'<{}> <http://xmlns.com/foaf/0.1/givenName> "{}"@{} .'.format(
entity, first_name, language),
'<{}> <http://xmlns.com/foaf/0.1/surname> "{}"@{} .'.format(
entity, surname, language),
'<{}> <http://www.w3.org/2000/01/rdf-schema#label> "{} {}"@{} . '.format(
entity, first_name, surname, language)
]
return '\n'.join(tuples)
def add_dbpedia_entity_to_repository(self, repository, label, entity_type,
language=None):
'''
http://de.dbpedia.org/page/Matthias_Strolz?output=text%2Fplain
'''
base_url = 'http://dbpedia.org/page/'
# if language and language != 'en':
# base_url = 'http://{}.dbpedia.org/page/'.format(language)
format_suffix = '?output=text%2Fplain'
label = label.replace(' ', '_')
entity = ''.join([base_url, label])
# entity = entity.format(entity.replace('page', 'resource'))
# content = self.create_template(entity, type, language)
(result, content) = self.check_exists(entity, repository)
# print(result.status, entity, content)
# print(result)
if result.status and len(content):
print('Skipping: {} already exists in repository {}'.format(
entity, repository))
return None
# else:
# url = ''.join([base_url, label, format_suffix])
# dbpedia_url = 'http://dbpedia.org/sparql?default-graph-uri=http%3A%2F%2Fdbpedia.org&query=DESCRIBE%20%3Chttp%3A%2F%2Fdbpedia.org%2Fresource%2F{}%3E&format=text%2Fx-html-script-turtle'.format(
# label)
#
# context = ''
# data = requests.get(dbpedia_url)
# content = data.content
# if not len(content):
content = self.create_template(entity, entity_type, language)
print(content)
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homeassistant/components/sensor/verisure.py | beschouten/home-assistant | 1 | 16894 | """
Interfaces with Verisure sensors.
For more details about this platform, please refer to the documentation at
documentation at https://home-assistant.io/components/verisure/
"""
import logging
from homeassistant.components.verisure import HUB as hub
from homeassistant.const import TEMP_CELSIUS
from homeassistant.helpers.entity import Entity
_LOGGER = logging.getLogger(__name__)
def setup_platform(hass, config, add_devices, discovery_info=None):
"""Setup the Verisure platform."""
sensors = []
if int(hub.config.get('thermometers', '1')):
hub.update_climate()
sensors.extend([
VerisureThermometer(value.id)
for value in hub.climate_status.values()
if hasattr(value, 'temperature') and value.temperature
])
if int(hub.config.get('hygrometers', '1')):
hub.update_climate()
sensors.extend([
VerisureHygrometer(value.id)
for value in hub.climate_status.values()
if hasattr(value, 'humidity') and value.humidity
])
if int(hub.config.get('mouse', '1')):
hub.update_mousedetection()
sensors.extend([
VerisureMouseDetection(value.deviceLabel)
for value in hub.mouse_status.values()
# is this if needed?
if hasattr(value, 'amountText') and value.amountText
])
add_devices(sensors)
class VerisureThermometer(Entity):
"""Representation of a Verisure thermometer."""
def __init__(self, device_id):
"""Initialize the sensor."""
self._id = device_id
@property
def name(self):
"""Return the name of the device."""
return '{} {}'.format(
hub.climate_status[self._id].location,
"Temperature")
@property
def state(self):
"""Return the state of the device."""
# Remove ° character
return hub.climate_status[self._id].temperature[:-1]
@property
def available(self):
"""Return True if entity is available."""
return hub.available
@property
def unit_of_measurement(self):
"""Return the unit of measurement of this entity."""
return TEMP_CELSIUS
def update(self):
"""Update the sensor."""
hub.update_climate()
class VerisureHygrometer(Entity):
"""Representation of a Verisure hygrometer."""
def __init__(self, device_id):
"""Initialize the sensor."""
self._id = device_id
@property
def name(self):
"""Return the name of the sensor."""
return '{} {}'.format(
hub.climate_status[self._id].location,
"Humidity")
@property
def state(self):
"""Return the state of the sensor."""
# remove % character
return hub.climate_status[self._id].humidity[:-1]
@property
def available(self):
"""Return True if entity is available."""
return hub.available
@property
def unit_of_measurement(self):
"""Return the unit of measurement of this sensor."""
return "%"
def update(self):
"""Update the sensor."""
hub.update_climate()
class VerisureMouseDetection(Entity):
"""Representation of a Verisure mouse detector."""
def __init__(self, device_id):
"""Initialize the sensor."""
self._id = device_id
@property
def name(self):
"""Return the name of the sensor."""
return '{} {}'.format(
hub.mouse_status[self._id].location,
"Mouse")
@property
def state(self):
"""Return the state of the sensor."""
return hub.mouse_status[self._id].count
@property
def available(self):
"""Return True if entity is available."""
return hub.available
@property
def unit_of_measurement(self):
"""Return the unit of measurement of this sensor."""
return "Mice"
def update(self):
"""Update the sensor."""
hub.update_mousedetection()
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13,
13,
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822,
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29898,
1311,
1125,
13,
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9995,
6422,
278,
23530,
1213,
15945,
13,
4706,
19766,
29889,
5504,
29918,
29885,
26165,
2650,
428,
580,
13,
2
] |
src/solutions/188.py | bshankar/euler | 0 | 124994 | <reponame>bshankar/euler<filename>src/solutions/188.py
def hyperpower(n, k):
n_ = n
for i in range(k-1):
n_ = n**n_ % 100
return n_
print hyperpower(1777, 1855)
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29945,
29897,
13,
2
] |
source_code/day021/snake.py | Zapdos26-Forks/100daysofcode | 0 | 1608085 | <filename>source_code/day021/snake.py
from turtle import Turtle
import math
class Snake:
def __init__(self):
self.segments = []
self.starting_position = [
(0, 0), (-20, 0), (-40, 0)]
self.move_distance = 20
self.directions = {'up': 90, 'down': 270, 'left': 180, 'right': 0}
self.create_snake()
self._head = self.segments[0]
@property
def head(self):
return self._head
def create_snake(self):
for position in self.starting_position:
self.add_segment(position)
def add_segment(self, position):
new_segment = Turtle("square")
new_segment.penup()
new_segment.goto(position)
self.segments.append(new_segment)
self.update_color()
def extend(self):
self.add_segment(self.segments[-1].position())
def update_color(self):
for i in range(len(self.segments)):
self.segments[i].color(
int((math.sin((.3 * i) + 0) * 127) + 127.5),
int((math.sin((.3 * i) + 2) * 127) + 127.5),
int((math.sin((.3 * i) + 4) * 127) + 127.5)
)
def move(self):
for seg_num in range(len(self.segments) - 1, 0, -1):
new_x = self.segments[seg_num - 1].xcor()
new_y = self.segments[seg_num - 1].ycor()
self.segments[seg_num].goto(new_x, new_y)
self._head.forward(self.move_distance)
def up(self):
if self._head.heading() != self.directions['down']:
self._head.setheading(self.directions['up'])
def down(self):
if self._head.heading() != self.directions['up']:
self._head.setheading(self.directions['down'])
def left(self):
if self._head.heading() != self.directions['right']:
self._head.setheading((self.directions['left']))
def right(self):
if self._head.heading() != self.directions['left']:
self._head.setheading(self.directions['right'])
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1266,
2033,
29901,
13,
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1583,
3032,
2813,
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842,
2813,
292,
3552,
1311,
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1839,
1563,
25901,
13,
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842,
2813,
292,
29898,
1311,
29889,
20146,
1953,
1839,
1266,
11287,
13,
2
] |
src/while_exit.py | Alex9808/py101 | 25 | 16150 | <reponame>Alex9808/py101<gh_stars>10-100
#!/usr/bin/env python
''' Este programa se repetirá 3 veces o hasta que se ingrese
la palabra "despedida" y desplegará sólo el número de intentos
fallidos hasta que cualquiera de los eventos ocurentradara. Al
ingresar la palabra "termina" el programa se detendrá.'''
entrada = ""
suma = 0
while suma < 3:
entrada = input("Clave:")
if entrada == "despedida":
break
elif entrada == "termina":
exit()
suma = suma + 1
print("Intento %d. \n " % suma)
print("Tuviste %d intentos fallidos." % suma)
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320,
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376,
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2533,
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8443,
13,
2158,
703,
23215,
1730,
371,
1273,
29881,
7609,
359,
6416,
4396,
1213,
1273,
2533,
29874,
8443,
13,
2
] |
easy-receptive-fields-pytorch/receptivefield/tests/test_pytorch.py | Swinsie/cv-rep-fork | 0 | 29989 | <filename>easy-receptive-fields-pytorch/receptivefield/tests/test_pytorch.py
import pytest
import torch.nn as nn
from numpy.testing import assert_allclose
from receptivefield.pytorch import PytorchReceptiveField
from receptivefield.image import get_default_image
from receptivefield.types import ImageShape
class Linear(nn.Module):
"""An identity activation function"""
def forward(self, x):
return x
class SimpleVGG(nn.Module):
def __init__(self, disable_activations: bool = False):
super(SimpleVGG, self).__init__()
self.blocks = self._build_blocks(disable_activations)
self.feature_maps = None
def forward(self, x):
self.feature_maps = []
for block in self.blocks:
for layer in block:
x = layer(x)
self.feature_maps.append(x)
return x
def _build_blocks(self, disable_activations: bool):
activation = lambda: Linear() if disable_activations else nn.ReLU()
block1 = [
nn.Conv2d(3, 64, kernel_size=3),
activation(),
nn.Conv2d(64, 64, kernel_size=3),
activation(),
nn.AvgPool2d(kernel_size=2, stride=2),
]
block2 = [
nn.Conv2d(64, 128, kernel_size=3),
activation(),
nn.Conv2d(128, 128, kernel_size=3),
activation(),
nn.AvgPool2d(kernel_size=2, stride=2),
]
block3 = [
nn.Conv2d(128, 256, kernel_size=3),
activation(),
nn.Conv2d(256, 256, kernel_size=3),
activation(),
nn.AvgPool2d(kernel_size=2, stride=2),
]
return [nn.Sequential(*block1), nn.Sequential(*block2), nn.Sequential(*block3)]
def model_fn() -> nn.Module:
model = SimpleVGG(disable_activations=True)
model.eval()
return model
def get_test_image(shape=(64, 64), tile_factor=0):
image = get_default_image(shape=shape, tile_factor=tile_factor)
return image
def test_example_network():
input_shape = [96, 96, 3]
rf = PytorchReceptiveField(model_fn)
rf_params = rf.compute(input_shape=ImageShape(*input_shape))
assert_allclose(rf_params[0].rf.size, (6, 6))
assert_allclose(rf_params[0].rf.stride, (2, 2))
rs = 6 + (2 + 2 + 1) * 2
assert_allclose(rf_params[1].rf.size, (rs, rs))
assert_allclose(rf_params[1].rf.stride, (4, 4))
rs = 6 + (2 + 2 + 1) * 2 + (2 + 2 + 1) * 4
assert_allclose(rf_params[2].rf.size, (rs, rs))
assert_allclose(rf_params[2].rf.stride, (8, 8))
if __name__ == "__main__":
pytest.main([__file__])
| [
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setup.py | anthonyvallee/bettejpeg | 1 | 35798 | <reponame>anthonyvallee/bettejpeg<gh_stars>1-10
from setuptools import (find_packages, setup)
from rap import betterjpeg
setup(
name=betterjpeg.__pkgname__,
description=betterjpeg.__description__,
version=betterjpeg.__version__,
packages=["rap.betterjpeg"],
entry_points="""
[console_scripts]
betterjpeg=rap.betterjpeg.betterjpeg:cli
"""
)
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a10sdk/core/ip/ip_as_path.py | deepfield/a10sdk-python | 16 | 73003 | <filename>a10sdk/core/ip/ip_as_path.py
from a10sdk.common.A10BaseClass import A10BaseClass
class AsPath(A10BaseClass):
"""Class Description::
Configure an AS-path list for BGP.
Class as-path supports CRUD Operations and inherits from `common/A10BaseClass`.
This class is the `"PARENT"` class for this module.`
:param access_list: {"description": "Specify an access list name (Regular expression access-list name)", "format": "string", "minLength": 1, "optional": false, "maxLength": 128, "type": "string"}
:param action: {"optional": false, "enum": ["deny", "permit"], "type": "string", "description": "'deny': Specify packets to reject; 'permit': Specify packets to forward; ", "format": "enum"}
:param uuid: {"description": "uuid of the object", "format": "string", "minLength": 1, "modify-not-allowed": 1, "optional": true, "maxLength": 64, "type": "string"}
:param value: {"optional": false, "type": "string", "description": "A regular-expression to match the BGP AS paths", "format": "string-rlx"}
:param DeviceProxy: The device proxy for REST operations and session handling. Refer to `common/device_proxy.py`
URL for this object::
`https://<Hostname|Ip address>//axapi/v3/ip/as-path/{access_list}+{action}+{value}`.
"""
def __init__(self, **kwargs):
self.ERROR_MSG = ""
self.required = [ "access_list","action","value"]
self.b_key = "as-path"
self.a10_url="/axapi/v3/ip/as-path/{access_list}+{action}+{value}"
self.DeviceProxy = ""
self.access_list = ""
self.action = ""
self.uuid = ""
self.value = ""
for keys, value in kwargs.items():
setattr(self,keys, value)
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] |
asyncapi/events/backends/gcloud_pubsub.py | dutradda/doodle | 34 | 137471 | import asyncio
import functools
import secrets
from concurrent.futures import ThreadPoolExecutor
from concurrent.futures import TimeoutError as FutureTimeoutError
from logging import Logger, getLogger
from typing import TYPE_CHECKING, Any, Dict, Tuple
from urllib.parse import urlparse
from broadcaster._backends.base import BroadcastBackend
from google.cloud import pubsub_v1
from google.cloud.pubsub_v1.types import PullResponse, ReceivedMessage
from asyncapi import (
GCloudPubSubConsumerDisconnectError,
GCloudPubSubPublishTimeoutError,
)
from .. import Event
if TYPE_CHECKING:
AsyncFutureHint = asyncio.Future[PullResponse]
else:
AsyncFutureHint = asyncio.Future
class GCloudPubSubBackend(BroadcastBackend):
def __init__(
self,
url: str,
bindings: Dict[str, str] = {},
logger: Logger = getLogger(__name__),
):
url_parsed = urlparse(url, scheme='gcloud-pubsub')
self._project = url_parsed.netloc
self._consumer_channels: Dict[str, str] = {}
self._producer_channels: Dict[str, str] = {}
self._channel_index = 0
self._logger = logger
self._set_consumer_config(bindings)
self._disconnected = True
self._executor = ThreadPoolExecutor(self._consumer_max_workers)
async def connect(self) -> None:
self._producer = pubsub_v1.PublisherClient()
self._consumer = pubsub_v1.SubscriberClient()
self._disconnected = False
async def disconnect(self) -> None:
self._disconnected = True
self._producer.stop()
self._consumer.close()
del self._producer
del self._consumer
async def subscribe(self, channel: str) -> None:
pubsub_channel = self._consumer.subscription_path(
self._project, channel
)
self._consumer_channels[channel] = pubsub_channel
async def unsubscribe(self, channel: str) -> None:
self._consumer_channels.pop(channel)
async def publish(
self, channel: str, message: Any, retries_counter: int = 1
) -> None:
producer_channel = self._producer_channels.get(channel)
if not producer_channel:
producer_channel = self._producer.topic_path(
self._project, channel
)
self._producer_channels[channel] = producer_channel
future = self._producer.publish(producer_channel, message.encode())
try:
future.result(timeout=self._publish_timeout)
except FutureTimeoutError:
if retries_counter >= self._publish_retries:
raise GCloudPubSubPublishTimeoutError(
f'publish timeout; channel={channel}; '
f'message={message[:100]}...'
)
else:
await self.publish(channel, message, retries_counter + 1)
async def next_published(self) -> Event:
(
received_message,
channel_id,
pubsub_channel,
) = await self._pull_message_from_consumer()
event = Event(channel_id, received_message.message.data.decode())
if self._consumer_ack_messages:
await self.wait_ack(received_message, pubsub_channel)
else:
event.context['ack_func'] = functools.partial(
self.wait_ack, received_message, pubsub_channel,
)
return event
async def _pull_message_from_consumer(
self,
) -> Tuple[ReceivedMessage, str, str]:
channel_index = (
secrets.choice(range(len(self._consumer_channels)))
if self._consumer_channels
else 0
)
while not self._disconnected:
channels = list(self._consumer_channels.items())
if not len(channels):
await asyncio.sleep(self._consumer_wait_time)
continue
if channel_index >= len(channels):
channel_index = 0
channel_id, pubsub_channel = channels[channel_index]
pull_message_future: AsyncFutureHint
pull_message_future = asyncio.get_running_loop().run_in_executor( # type: ignore
self._executor,
functools.partial(
self._consumer.pull,
pubsub_channel,
max_messages=1,
return_immediately=True,
),
)
try:
response = await asyncio.wait_for(
pull_message_future, self._consumer_pull_message_timeout
)
except asyncio.TimeoutError:
channel_index += 1
await asyncio.sleep(self._consumer_wait_time)
continue
else:
if not response.received_messages:
channel_index += 1
await asyncio.sleep(self._consumer_wait_time)
continue
await asyncio.sleep(self._pull_message_wait_time)
return (
response.received_messages[0],
channel_id,
pubsub_channel,
)
raise GCloudPubSubConsumerDisconnectError()
async def wait_ack(
self,
message: ReceivedMessage,
pubsub_channel: str,
retries_counter: int = 1,
) -> None:
future = asyncio.get_running_loop().run_in_executor(
self._executor,
functools.partial(
self._consumer.acknowledge, pubsub_channel, [message.ack_id],
),
)
try:
await asyncio.wait_for(future, timeout=self._consumer_ack_timeout)
except asyncio.TimeoutError:
if retries_counter >= self._consumer_ack_retries:
self._logger.warning(
f'ack timeout {self._consumer_ack_timeout}; '
f'message={message.message.data.decode()[:100]}...'
)
else:
await self.wait_ack(
message, pubsub_channel, retries_counter + 1
)
except asyncio.CancelledError:
self._logger.warning(
'ack cancelled; '
f'message={message.message.data.decode()[:100]}...'
)
def _set_consumer_config(self, bindings: Dict[str, str]) -> None:
consumer_wait_time = 1.0
consumer_ack_messages = False
consumer_ack_timeout = 1.0
consumer_ack_retries = 3
consumer_pull_message_timeout = 1.0
consumer_max_workers = 10
publish_timeout = 5.0
publish_retries = 3
pull_message_wait_time = 0.1
for config_name, config_value in bindings.items():
if config_name == 'consumer_wait_time':
consumer_wait_time = float(config_value)
elif config_name == 'consumer_ack_messages':
consumer_ack_messages = config_value in (
'1',
'true',
't',
'True',
'y',
'yes',
)
elif config_name == 'consumer_ack_timeout':
consumer_ack_timeout = float(config_value)
elif config_name == 'consumer_ack_retries':
consumer_ack_retries = int(config_value)
elif config_name == 'consumer_max_workers':
consumer_max_workers = int(config_value)
elif config_name == 'consumer_pull_message_timeout':
consumer_pull_message_timeout = float(config_value)
elif config_name == 'publish_timeout':
publish_timeout = float(config_value)
elif config_name == 'publish_retries':
publish_retries = int(config_value)
elif config_name == 'pull_message_wait_time':
pull_message_wait_time = float(config_value)
self._consumer_wait_time = consumer_wait_time
self._consumer_ack_messages = consumer_ack_messages
self._consumer_ack_timeout = consumer_ack_timeout
self._consumer_ack_retries = consumer_ack_retries
self._consumer_pull_message_timeout = consumer_pull_message_timeout
self._consumer_max_workers = consumer_max_workers
self._publish_timeout = publish_timeout
self._publish_retries = publish_retries
self._pull_message_wait_time = pull_message_wait_time
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] |
Yellow_Pages_Lithuania/unit_tests.py | Jay4C/Web-Scraping | 1 | 70 | <gh_stars>1-10
import time
from bs4 import BeautifulSoup
import requests
import pymysql.cursors
import unittest
class UnitTestsDataMinerYellowPagesLithuania(unittest.TestCase):
def test_extract_one_email(self):
url = "https://www.visalietuva.lt/en/company/astorija-hotel-uab"
# Request the content of a page from the url
html = requests.get(url)
# Parse the content of html_doc
soup = BeautifulSoup(html.content, 'html.parser')
if soup.find('a', {'itemprop': 'email'}) is not None:
email = "info@" + soup.find('a', {'itemprop': 'email'}).text.split("@")[1]
print('email : ' + email)
else:
print('no email business')
def test_extract_emails_from_all_page_of_results_for_one_activity_and_capital(self):
activity = "hotel"
city = "vilniuje"
url_search = "https://www.visalietuva.lt/en/search/" + activity + "/" + city
html_search = requests.get(url_search)
soup_search = BeautifulSoup(html_search.content, 'html.parser')
number_of_pages = 0
if soup_search.find('div', {'class': 'search_count f_left'}) is not None:
number_of_pages_with_coma = int(soup_search
.find('div', {'class': 'search_count f_left'})
.find('span').text
)/20
if int(str(number_of_pages_with_coma).split(".")[1][:1]) < 5:
number_of_pages += round(number_of_pages_with_coma) + 1
print('number_of_pages : ' + str(number_of_pages))
elif int(str(number_of_pages_with_coma).split(".")[1][:1]) >= 5:
number_of_pages += round(number_of_pages_with_coma)
print('number_of_pages : ' + str(number_of_pages))
i_1 = 0
if soup_search.find('div', {'class': 'company_list'}) is not None:
print(url_search)
for result_item in soup_search \
.find('div', {'class': 'company_list'}) \
.find_all('div', {'class': 'item'}):
i_1 += 1
url_result = result_item.find('a', {'class': 'company-item-title'}).get('href')
time.sleep(2)
# Request the content of a page from the url
html_result = requests.get(url_result)
# Parse the content of html_doc
soup_result = BeautifulSoup(html_result.content, 'html.parser')
if soup_result.find('a', {'itemprop': 'email'}) is not None:
email = "info@" + soup_result.find('a', {'itemprop': 'email'}).text.split("@")[1]
print(str(i_1) + ' email : ' + email)
else:
print(str(i_1) + ' no email business')
else:
print('sorry there is nothing')
if number_of_pages > 1:
for i in range(2, number_of_pages+1):
url_of_one_page_of_results = url_search + "/" + str(i)
print(url_of_one_page_of_results)
time.sleep(2)
html_of_one_page_of_results = requests.get(url_of_one_page_of_results)
soup_of_one_page_of_results = BeautifulSoup(html_of_one_page_of_results.content, 'html.parser')
if soup_of_one_page_of_results.find('div', {'class': 'company_list'}) is not None:
for result_item in soup_of_one_page_of_results\
.find('div', {'class': 'company_list'})\
.find_all('div', {'class': 'item'}):
i_1 += 1
url_result = result_item.find('a', {'class': 'company-item-title'}).get('href')
# Request the content of a page from the url
html_result = requests.get(url_result)
# Parse the content of html_doc
soup_result = BeautifulSoup(html_result.content, 'html.parser')
if soup_result.find('a', {'itemprop': 'email'}) is not None:
email = "info@" + soup_result.find('a', {'itemprop': 'email'}).text.split("@")[1]
print(str(i_1) + ' email : ' + email)
else:
print(str(i_1) + ' no email business')
else:
print('sorry there is nothing')
def test_extract_emails_from_all_page_of_results_for_all_activities_and_capitals(self):
activites = [
# {'id': '1', 'url': 'labour'}
#{'id': '2', 'url': 'real+estate'},
#{'id': '3', 'url': 'recruitment'},
#{'id': '4', 'url': 'software'},
#{'id': '5', 'url': 'hotel'},
#{'id': '6', 'url': 'landlord'},
#{'id': '7', 'url': 'cleaning'},
#{'id': '8', 'url': 'association'},
#{'id': '9', 'url': 'financial'},
#{'id': '10', 'url': 'restaurant'},
#{'id': '11', 'url': 'building'},
#{'id': '12', 'url': 'hairdresser'},
#{'id': '13', 'url': 'florist'},
#{'id': '14', 'url': 'locksmith'},
#{'id': '15', 'url': 'bakery'},
#{'id': '16', 'url': 'insurance'},
#{'id': '17', 'url': 'pharmacy'},
#{'id': '18', 'url': 'moving'},
#{'id': '19', 'url': 'electricity'},
#{'id': '20', 'url': 'plumbing'},
#{'id': '21', 'url': 'security'},
#{'id': '22', 'url': 'lawyer'},
#{'id': '23', 'url': 'bank'},
#{'id': '24', 'url': 'garage'},
#{'id': '25', 'url': 'dentist'},
#{'id': '26', 'url': 'doctor'},
#{'id': '27', 'url': 'accounting'},
#{'id': '28', 'url': 'store'},
#{'id': '29', 'url': 'notary'},
#{'id': '30', 'url': 'jeweller'},
#{'id': '31', 'url': 'tailor'},
#{'id': '32', 'url': 'meat'},
#{'id': '33', 'url': 'library'},
#{'id': '34', 'url': 'architect'}
]
capitales_du_monde = [
{'id': '183', 'nom': 'akmeneje'},#Akmenė
{'id': '184', 'nom': 'alytuje'},#Alytus
{'id': '185', 'nom': 'anyksciuose'},#Anykščiai
{'id': '186', 'nom': 'birstone'},#Birštonas
{'id': '187', 'nom': 'birzuose'},#Biržai
{'id': '188', 'nom': 'druskininkuose'},#Druskininkai
{'id': '189', 'nom': 'elektrenuose'},#Elektrėnai
{'id': '190', 'nom': 'ignalinoje'},#Ignalina
{'id': '191', 'nom': 'jonavoje'},#Jonava
{'id': '192', 'nom': 'joniskyje'},#Joniškis
{'id': '193', 'nom': 'jurbarke'},#Jurbarkas
{'id': '194', 'nom': 'kaisiadoryse'},#Kaišiadorys
{'id': '195', 'nom': 'kalvarijoje'},#Kalvarija
{'id': '196', 'nom': 'kaune'},#Kaunas
{'id': '197', 'nom': 'kazlu-rudoje'},#Kazlų Rūda
{'id': '198', 'nom': 'kedainiuose'},#Kėdainiai
{'id': '199', 'nom': 'kelmeje'},#Kelmė
{'id': '200', 'nom': 'klaipedoje'},#Klaipėda
{'id': '201', 'nom': 'kretingoje'},#Kretinga
{'id': '202', 'nom': 'kupiskyje'},#Kupiškis
{'id': '203', 'nom': 'lazdijuose'},#Lazdijai
{'id': '204', 'nom': 'marijampoleje'},#Marijampolė
{'id': '205', 'nom': 'mazeikiuose'},#Mažeikiai
{'id': '206', 'nom': 'moletuose'},#Molėtai
{'id': '207', 'nom': 'neringoje'},#Neringa
{'id': '208', 'nom': 'pagegiuose'},#Pagėgiai
{'id': '209', 'nom': 'pakruojyje'},#Pakruojis
{'id': '210', 'nom': 'palangoje'},#Palanga
{'id': '211', 'nom': 'panevezyje'},#Panevėžys
{'id': '212', 'nom': 'pasvalyje'},#Pasvalys
{'id': '213', 'nom': 'plungeje'},#Plungė
{'id': '214', 'nom': 'prienuose'},#Prienai
{'id': '215', 'nom': 'radviliskyje'},#Radviliškis
{'id': '216', 'nom': 'raseiniuose'},#Raseiniai
{'id': '217', 'nom': 'rietave'},#Rietavas
{'id': '218', 'nom': 'rokiskyje'},#Rokiškis
{'id': '219', 'nom': 'sakiuose'},#Šakiai
{'id': '220', 'nom': 'salcininkuose'},#Šalčininkai
{'id': '221', 'nom': 'siauliuose'},#Šiauliai
{'id': '222', 'nom': 'silaleje'},#Šilalė
{'id': '223', 'nom': 'siluteje'},#Šilutė
{'id': '224', 'nom': 'sirvintose'},#Širvintos
{'id': '225', 'nom': 'skuode'},#Skuodas
{'id': '226', 'nom': 'svencionyse'},#Švenčionys
{'id': '227', 'nom': 'taurageje'},#Tauragė
{'id': '228', 'nom': 'telsiuose'},#Telšiai
{'id': '229', 'nom': 'trakuose'},#Trakai
{'id': '230', 'nom': 'ukmergeje'},#Ukmergė
{'id': '231', 'nom': 'utenoje'},#Utena
{'id': '232', 'nom': 'varenoje'},#Varėna
{'id': '233', 'nom': 'vilkaviskyje'},#Vilkaviškis
{'id': '234', 'nom': 'vilniuje'},#Vilnius
{'id': '235', 'nom': 'visagine'},#Visaginas
{'id': '236', 'nom': 'zarasuose'}#Zarasai
]
try:
for capitale in capitales_du_monde:
for activite in activites:
try:
activity = activite.get("url")
city = capitale.get("nom")
url_search = "https://www.visalietuva.lt/en/search/" + activity + "/" + city
html_search = requests.get(url_search)
soup_search = BeautifulSoup(html_search.content, 'html.parser')
number_of_pages = 0
if soup_search.find('div', {'class': 'search_count f_left'}) is not None:
number_of_pages_with_coma = int(soup_search
.find('div', {'class': 'search_count f_left'})
.find('span').text
) / 20
if int(str(number_of_pages_with_coma).split(".")[1][:1]) < 5:
number_of_pages += round(number_of_pages_with_coma) + 1
print('number_of_pages : ' + str(number_of_pages))
elif int(str(number_of_pages_with_coma).split(".")[1][:1]) >= 5:
number_of_pages += round(number_of_pages_with_coma)
print('number_of_pages : ' + str(number_of_pages))
i_1 = 0
if soup_search.find('div', {'class': 'company_list'}) is not None:
print(url_search)
for result_item in soup_search \
.find('div', {'class': 'company_list'}) \
.find_all('div', {'class': 'item'}):
i_1 += 1
url_result = result_item.find('a', {'class': 'company-item-title'}).get('href')
time.sleep(2)
# Request the content of a page from the url
html_result = requests.get(url_result)
# Parse the content of html_doc
soup_result = BeautifulSoup(html_result.content, 'html.parser')
if soup_result.find('a', {'itemprop': 'email'}) is not None:
email = "info@" + soup_result.find('a', {'itemprop': 'email'}).text.split("@")[1]
try:
connection = pymysql.connect(
host='localhost',
port=3306,
user='',
password='',
db='contacts_professionnels',
charset='utf8mb4',
cursorclass=pymysql.cursors.DictCursor
)
with connection.cursor() as cursor:
try:
sql = "INSERT INTO `emails` (" \
"`id_activite`, " \
"`id_capitale_du_monde`, " \
"`email`) VALUE (%s, %s, %s)"
cursor.execute(sql, (
activite.get('id'),
capitale.get('id'),
email))
connection.commit()
print(str(i_1) + " The record is stored : " + email)
connection.close()
except:
print(str(i_1) + " The record already exists : " + email)
connection.close()
except Exception as e:
print(str(i_1) + " An error with the email : " + email + " " + str(e))
else:
print(str(i_1) + ' no email business')
else:
print('sorry there is nothing')
if number_of_pages > 1:
for i in range(2, number_of_pages + 1):
url_of_one_page_of_results = url_search + "/" + str(i)
print(url_of_one_page_of_results)
time.sleep(2)
html_of_one_page_of_results = requests.get(url_of_one_page_of_results)
soup_of_one_page_of_results = BeautifulSoup(html_of_one_page_of_results.content,
'html.parser')
if soup_of_one_page_of_results.find('div', {'class': 'company_list'}) is not None:
for result_item in soup_of_one_page_of_results \
.find('div', {'class': 'company_list'}) \
.find_all('div', {'class': 'item'}):
i_1 += 1
url_result = result_item.find('a', {'class': 'company-item-title'}).get('href')
# Request the content of a page from the url
html_result = requests.get(url_result)
# Parse the content of html_doc
soup_result = BeautifulSoup(html_result.content, 'html.parser')
if soup_result.find('a', {'itemprop': 'email'}) is not None:
email = "info@" + \
soup_result.find('a', {'itemprop': 'email'}).text.split("@")[1]
try:
connection = pymysql.connect(
host='localhost',
port=3306,
user='',
password='',
db='contacts_professionnels',
charset='utf8mb4',
cursorclass=pymysql.cursors.DictCursor
)
with connection.cursor() as cursor:
try:
sql = "INSERT INTO `emails` (" \
"`id_activite`, " \
"`id_capitale_du_monde`, " \
"`email`) VALUE (%s, %s, %s)"
cursor.execute(sql, (
activite.get('id'),
capitale.get('id'),
email))
connection.commit()
print(str(i_1) + " The record is stored : " + email)
connection.close()
except:
print(str(i_1) + " The record already exists : " + email)
connection.close()
except Exception as e:
print(str(i_1) + " An error with the email : " + email + " " + str(e))
else:
print(str(i_1) + ' no email business')
else:
print('sorry there is nothing')
except Exception as e:
print("There is an error connection at url : " + str(e))
finally:
print('done')
if __name__ == '__main__':
unittest.main()
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] |
beancount_gmail/debug_handling.py | kubauk/beancount-import-gmail | 1 | 184069 | <reponame>kubauk/beancount-import-gmail
import datetime
from os import PathLike
from typing import Union, AnyStr, Callable, IO, Optional
import jsonpickle
import os
from mailbox import Message
from beancount_gmail.email_parser_protocol import EmailParser
from beancount_gmail.receipt import Receipt
DEBUGGING_DATA_DIR: str = "debugging"
EXCLUDED_DATA_DIR: str = "excluded"
WRITE_DEBUG: bool = False
def write_email_to_file(reason: Optional[str], extension: str, message_date: datetime,
message: Message, file_dir: Union[AnyStr, PathLike]) -> None:
def data_handler(out):
if isinstance(message, Message):
out.write(message.as_string())
else:
out.write(message)
write_data_to_file(reason, extension, message_date, data_handler, file_dir)
def write_receipts_to_file(receipts: list[Receipt], message_date: datetime) -> None:
def data_handler(out):
encode = jsonpickle.encode(receipts, unpicklable=True, indent=2)
out.write(encode)
write_data_to_file(None, "json", message_date, data_handler, DEBUGGING_DATA_DIR)
def write_data_to_file(reason: Optional[str], extension: str, message_date: datetime,
data_handler: Callable[[IO], None], file_dir: Union[AnyStr, PathLike]) -> None:
if not os.path.exists(file_dir):
os.mkdir(file_dir)
file = os.path.join(file_dir, "%s.%s.%s" % (message_date, reason, extension))
with open(file, "w") as out:
data_handler(out)
def maybe_write_debugging(fn: Callable[[EmailParser, datetime, Message], list[Receipt]],
extension: str, parser: EmailParser,
message_date: datetime.datetime, message: Message) -> list[Receipt]:
if WRITE_DEBUG:
write_email_to_file(None, extension, message_date, message, os.path.join(os.getcwd(), DEBUGGING_DATA_DIR))
receipts = write_email_file_on_exception(fn, extension, parser, message_date, message)
if WRITE_DEBUG:
write_receipts_to_file(receipts, message_date)
return receipts
def write_email_file_on_exception(fn: Callable[[EmailParser, datetime, Message], list[Receipt]],
extension: str, parser: EmailParser,
message_date: datetime.datetime, message: Message) -> list[Receipt]:
try:
return fn(parser, message_date, message)
except Exception as e:
write_email_to_file(e.__class__.__name__, extension, message_date, message,
os.path.join(os.getcwd(), EXCLUDED_DATA_DIR))
raise e
| [
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] |
Slide21/calculadora_python.py | yuutognr/MiniCursoPython2020 | 2 | 31118 | a = 2 ** 50
b = 2 ** 50 * 3
c = 2 ** 50 * 3 - 1000
d = 400 / 2 ** 50 + 50
print(a,b,c,d) | [
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4_vrf_verification/main.py | gve-sw/gve_devnet_dnac_automation_workshop | 0 | 87213 | <gh_stars>0
""" Copyright (c) 2022 Cisco and/or its affiliates.
This software is licensed to you under the terms of the Cisco Sample
Code License, Version 1.1 (the "License"). You may obtain a copy of the
License at
https://developer.cisco.com/docs/licenses
All use of the material herein must be in accordance with the terms of
the License. All rights not expressly granted by the License are
reserved. Unless required by applicable law or agreed to separately in
writing, software distributed under the License is distributed on an "AS
IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
or implied.
__author__ = "<NAME> <<EMAIL>>"
__copyright__ = "Copyright (c) 2022 Cisco and/or its affiliates."
__license__ = "Cisco Sample Code License, Version 1.1"
"""
# Import Section
from dotenv import load_dotenv
import os
import requests
from requests.auth import HTTPBasicAuth
import urllib3
from urllib3.exceptions import InsecureRequestWarning
import json
import time
from pyats_genie_command_parse import GenieCommandParse
from tabulate import tabulate
# Disable warnings
urllib3.disable_warnings(InsecureRequestWarning)
# load all environment variables
load_dotenv()
DNAC_BASE_URL = os.getenv('DNAC_BASE_URL')
DNAC_USERNAME = os.getenv("DNAC_USERNAME")
DNAC_PASSWORD = os.getenv("DNAC_PASSWORD")
# Helper functions
def get_auth_token():
"""
Create the authorization token required to access DNAC
Call to DNAC - /api/system/v1/auth/login
Documentation: https://developer.cisco.com/docs/dna-center/#!authentication-api
:return: DNAC Authentication token
"""
url = f'{DNAC_BASE_URL}/dna/system/api/v1/auth/token'
headers = {
'Content-Type': 'application/json'
}
response = requests.post(
url=url,
auth=HTTPBasicAuth(DNAC_USERNAME, DNAC_PASSWORD),
headers=headers,
verify=False)
token = response.json()['Token']
return token
def get_device_list(dnac_token, params={}):
"""
API call to get a list of network devices based on filter criteria such as management IP address, mac address, hostname, etc.
Documentation: https://developer.cisco.com/docs/dna-center/#!get-device-list-1
:param dnac_token: String with DNAC Authentication token
:param params: A dictionary where you can specify search parameters
:return: List of JSON objects with device details
"""
url = f'{DNAC_BASE_URL}/dna/intent/api/v1/network-device'
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-auth-token': dnac_token
}
response = requests.get(
url=url,
headers=headers,
params=params,
verify=False
)
response.raise_for_status()
return response.json()['response']
def post_command_runner_request(dnac_token, payload):
"""
API call to post read only commands on devices to get their real time configuration. A payload neds to be sent in the post request with
the commands that the user would like to execute on the CLI of the device.
Call to DNAC - /dna/intent/api/v1/network-device-poller/cli/read-request
Documentation: https://developer.cisco.com/docs/dna-center/#!run-read-only-commands-on-devices-to-get-their-real-time-configuration
:param dnac_token: String with DNAC Authentication token
:param payload: A dictionary with a list of commands, the device UUIDs and a timeout
:return: A string with the task ID
"""
url = f'{DNAC_BASE_URL}/dna/intent/api/v1/network-device-poller/cli/read-request'
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-auth-token': dnac_token
}
response = requests.post(
url=url,
data=json.dumps(payload),
headers=headers,
verify=False
)
print(response.text)
response.raise_for_status()
task_id = response.json()['response']['taskId']
return task_id
def get_file_id(dnac_token, task_id):
"""
API call to return a task by specified id.
Call to DNAC - /dna/intent/api/v1/task/{taskId}
Documentation: https://developer.cisco.com/docs/dna-center/#!get-task-by-id
:param dnac_token: String with DNAC Authentication token
:param task_id: String with the task ID that was returned by the command runner API
:return: String with the file_id
"""
url = f'{DNAC_BASE_URL}/dna/intent/api/v1/task/{task_id}'
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-auth-token': dnac_token
}
response = requests.get(
url=url,
headers=headers,
verify=False
)
response.raise_for_status()
print("get_file_id response:")
print(json.dumps(response.json(), indent=2))
progress_json = json.loads(response.json()['response']['progress'])
file_id = progress_json['fileId']
return file_id
def get_file(dnac_token, file_id):
"""
API call to download a file specified by fileId
Call to DNAC - /dna/intent/api/v1/file/{fileId}
Documentation: https://developer.cisco.com/docs/dna-center/#!download-a-file-by-file-id
:param dnac_token: String with DNAC Authentication token
:param file_id: String with the file ID that was returned by the task API
:return: String with the file
"""
url = f'{DNAC_BASE_URL}/dna/intent/api/v1/file/{file_id}'
headers = {
'Content-Type': 'application/json',
'Accept': 'application/json',
'x-auth-token': dnac_token
}
response = requests.get(
url=url,
headers=headers,
verify=False
)
response.raise_for_status()
return response.json()
if __name__ == "__main__":
# # Step 1: Uncomment the following code block
# # Obtain DNA Center authentication token
# token = get_auth_token()
# print("You DNAC token: ", token)
# # Step 2: Uncomment the following code block
# # Get a filtered list of devices
# params_filter_devices = {"family": "Switches and Hubs"}
# devices = get_device_list(token, params_filter_devices)
# print(json.dumps(devices, indent=2))
# # Step 3: Uncomment the following code block
# # Extract the device IDs of each device
# device_ids = []
# for device in devices:
# device_ids.append(device["id"])
# print(device_ids)
# # Step 4: Uncomment the following code block
# # Send a number of commands to the command runner API
# commands = [
# "show vrf"
# ]
# payload = {
# "commands": commands,
# "deviceUuids": device_ids,
# "timeout": 0
# }
# task_id = post_command_runner_request(token, payload)
# print(task_id)
#
# # Let's wait 30 seconds after executing the commands
# time.sleep(30)
# # Step 5: Uncomment the following code block
# # We use the task_id to obtain a file_id
# file_id = get_file_id(token, task_id)
# # Obtain a file using the file_id
# file = get_file(token, file_id)
# print(file)
# # Step 6: Uncomment the following code block
# results = []
# for device in file:
# device_uuid = device['deviceUuid']
# for command in commands:
# if device['commandResponses']['SUCCESS']:
# # Print the raw output
# command_output = device['commandResponses']['SUCCESS'][command]
# print(command_output)
# print(' ')
# # Parse the raw output
# parser = GenieCommandParse(nos='ios')
# parsed_output = parser.parse_string(show_command=command, show_output_data=command_output)
# # Print the parsed output
# print(json.dumps(parsed_output, indent=2))
# print(' ')
# if command == "show vrf":
# #####################
# ## Golden Config ##
# #####################
# # Insert golden config of show vrf
# # Below is just an example
# golden_config_show_vrf = {
# "vrf": {
# "Mgmt-vrf": {
# "protocols": [
# "ipv4",
# "ipv6"
# ],
# "interfaces": [
# "GigabitEthernet0/0"
# ]
# }
# }
# }
# #####################
# # Verify if the vrf config is correct, by default false
# correct_vrf_config = False
# if golden_config_show_vrf == parsed_output:
# correct_vrf_config = True
# # Add the result to the list of results
# results.append([device_uuid, correct_vrf_config])
# print(' ')
# print('The results of the VRF verification:')
# print(' ')
# # Print a table of the output
# print(tabulate(results, headers=['Device UUIDs', 'Correct VRF Config']))
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] |
src/test_ptmod.py | LuDubies/Differender | 4 | 147508 | <filename>src/test_ptmod.py<gh_stars>1-10
import torch
from torch.autograd import gradcheck
from torchvtk.datasets import TorchDataset
import matplotlib.pyplot as plt
from transfer_functions import get_tf
from pytorch_module import Raycaster
from torchvision.utils import save_image
tf = torch.from_numpy(get_tf('tf1', 128)).permute(1, 0).float().contiguous()
vol_ds = TorchDataset('/run/media/dome/Data/data/torchvtk/CQ500_128')
vol = vol_ds[0]['vol'].float()
look_from = torch.tensor([0.0, 1.0, -2.5])
r = Raycaster((128, 128, 128), (240, 240), 128, jitter=False)
print(f'{vol.shape=}, {vol.min()=}, {vol.max()=}')
print(f'{tf.shape=}, {tf.min()=}, {tf.max()=}')
if __name__ == '__main__':
# vol += torch.randn_like(vol) * 0.1
vol = vol.to('cuda').float().requires_grad_(True)
tf = tf.to('cuda').float().requires_grad_(True)
look_from = look_from.to('cuda').float().requires_grad_(False)
target = torch.load('target.pt').float().to('cuda')
# test = gradcheck(r, [vol, tf, look_from], eps=1e-3, atol=1e-3, check_forward_ad=False, fast_mode=True, raise_exception=True, nondet_tol=1e-2)
# print(test)
res_single = r(vol, tf, look_from)
print(f'{res_single.shape=}')
res_batched = r(torch.stack([vol] * 2), torch.stack([tf] * 2), torch.stack([look_from, look_from + 1.0]))
print(f'{res_batched.shape=}')
print(f'Equal?{(res_single == res_batched.squeeze(0)).all()}')
# save_image(res_single, 'res_single.png')
# save_image(res_batched[0], 'res_batched0.png')
# save_image(res_batched[1],'res_batched1.png')
opt = torch.optim.Adam([vol, tf])
opt.zero_grad()
res = r(vol, tf, look_from)
loss = torch.nn.functional.mse_loss(res, target)
loss.backward()
print(f'SINGLE ----------------------------------')
print(f'{loss=}')
print(f'{vol.grad.shape=}, {vol.grad.abs().max()=}')
print(f'{tf.grad.shape=}, {tf.grad.abs().max()=}')
vol_grad = vol.grad.clone()
tf_grad = tf.grad.clone()
opt.zero_grad()
res = r(torch.stack([vol] * 4), torch.stack([tf] * 4), torch.stack([look_from] * 4))
loss = torch.nn.functional.mse_loss(res, torch.stack([target] * 4))
loss.backward()
print(f'BATCHED ----------------------------------')
print(f'{loss=}')
print(f'{vol.grad.shape=}, {vol.grad.abs().max()=}')
print(f'{tf.grad.shape=}, {tf.grad.abs().max()=}')
print(f'COMPARE ----------------------------------')
print(f'Vol Gradients equal? {torch.allclose(vol.grad, vol_grad, atol=1e-5, rtol=1e-3)}')
print(f'TF Gradients equal? {torch.allclose(tf.grad, tf_grad, atol=1e-5, rtol=1e-3)}')
# opt = torch.optim.Adam([vol, tf])
# for i in range(100):
# opt.zero_grad()
# res = r(vol, tf, look_from)
# loss = torch.nn.functional.mse_loss(res, target)
# loss.backward()
# save_image(res, f'test/render_{i:03d}.png')
# print(f'Step {i:03d} ----------------------------------')
# print(f'{loss=}')
# print(f'{vol.grad.abs().max()=}')
# print(f'{tf.grad.abs().max()=}')
# opt.step()
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268,
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] |
eots/serializers.py | lextoumbourou/eyeofthestorm | 0 | 93132 | <reponame>lextoumbourou/eyeofthestorm<filename>eots/serializers.py
"""
Eventually we'll probably want to add some decent serialization support.
For now - this is a pass through. Patches accepted :)
"""
class Serializer(object):
def serialize(cls, obj):
return obj
def is_valid(self):
return True
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StatM/__init__.py | Blaizzy/Boring_weekends | 3 | 107040 | from StatM import Bisection, Regula_Falsi, Secant
| [
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util.py | mobarski/smash | 0 | 176152 | import re
def flag(value):
"convert value to integer bool type"
s = str(value).strip().lower()
is_true = s in "yes y true t on 1".split(' ')
return int(is_true)
def join(lst,dlm='',fmt="{0}",strip=True):
if strip:
lst = [x.strip() if hasattr(x,"strip") else x for x in lst]
return dlm.join([fmt.format(x) for x in lst])
# TODO pipetools clone NEW SANDBOX
class pipe(object):
def __pipe__(self,*args,**kwargs):
print("__pipe__",args,kwargs)
def __call__(self,*args,**kwargs):
print("__call__",args,kwargs)
###
def _sub(x,fmt):
a = re.subn('[$][$]','_#D0LaR#_',fmt)[0]
b = re.subn('[$]',x,a)[0]
c = re.subn('_#D0LaR#_','$',b)[0]
return c
def get(name,split=None,join=None,fmt=None):
raw = "1 2 \r\n 3 4" # TODO
if split == None:
after_split = raw
elif callable(split):
after_split = split(raw)
elif type(split) == str:
after_split = re.split(split, raw)
else:
raise
if fmt == None:
after_fmt = after_split
else:
after_fmt = [_sub(x,fmt) for x in after_split]
if join == None:
after_join = after_fmt
else:
after_join = join.join(after_fmt)
return after_join
if __name__=="__main__":
#print(get('x','\s+','\n,','string(s.$) as new_$'))
#print(flag('off'))
pass
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lib/datamanager/samplerbase.py | chenyanghungry/person-reid-lib | 81 | 62305 | <reponame>chenyanghungry/person-reid-lib<gh_stars>10-100
from torch.utils.data.sampler import Sampler
import numpy as np
class SamplerBase(Sampler):
def __init__(self, data_info, instance_num, sample_num, sample_len, npr):
super().__init__(data_info)
self.npr = npr
self.data_info = data_info.copy()
self.person_num = np.unique(self.data_info[:, 0]).size
self.frames_len_min = np.min(self.data_info[:, 4])
self.frames_len_max = np.max(self.data_info[:, 4])
self.instance_num = instance_num
self.sample_num = sample_num
self.sample_len = sample_len
if self.frames_len_max == 1 and self.frames_len_min == 1:
self._process_raw_data = self._process_raw_image_data
else:
self._process_raw_data = self._process_raw_video_data
self.init()
def init(self):
raise NotImplementedError
def _process_raw_image_data(self, tracklet):
output = []
for track_i in tracklet:
track_info = [track_i[0], track_i[1], track_i[2]] # person id, cam_id, img_idx
output.append(track_info)
return output
def _process_raw_video_data(self, tracklet):
output = []
for track_i in tracklet:
track_info = [track_i[0], track_i[1]] # person id, cam_id
track_i_begin = track_i[2]
track_i_raw_len = track_i[4]
track_i_sample_len = min(track_i_raw_len, self.sample_len)
track_i_start_id = self.npr.random_integers(0, track_i_raw_len - track_i_sample_len)
track_i_sample_begin = track_i_begin + track_i_start_id
track_i_sample_end = track_i_begin + track_i_start_id + track_i_sample_len
track_info.extend(list(range(track_i_sample_begin, track_i_sample_end)))
output.append(track_info)
return output
def __len__(self):
return self._len
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components/shelly/sensor.py | tefinger/hass | 0 | 191331 | """
Shelly platform for the sensor component.
For more details about this platform, please refer to the documentation
https://home-assistant.io/components/shelly/
"""
import logging
from homeassistant.const import (DEVICE_CLASS_HUMIDITY,
DEVICE_CLASS_TEMPERATURE,
TEMP_CELSIUS, POWER_WATT)
from homeassistant.helpers.entity import Entity
from . import (CONF_OBJECT_ID_PREFIX, SHELLY_CONFIG,
ShellyDevice, get_device_from_hass,
ShellyBlock, get_block_from_hass)
_LOGGER = logging.getLogger(__name__)
SENSOR_TYPE_TEMPERATURE = 'temp'
SENSOR_TYPE_HUMIDITY = 'humidity'
SENSOR_TYPE_POWER = 'watt'
SENSOR_TYPE_RSSI = 'rssi'
SENSOR_TYPE_UPTIME = 'uptime'
SENSOR_TYPE_BATTERY = 'battery'
SENSOR_TYPES = {
SENSOR_TYPE_TEMPERATURE:
['Temperature', TEMP_CELSIUS, None, DEVICE_CLASS_TEMPERATURE],
SENSOR_TYPE_HUMIDITY:
['Humidity', '%', None, DEVICE_CLASS_HUMIDITY],
SENSOR_TYPE_POWER:
['Power', POWER_WATT, None, None],
SENSOR_TYPE_RSSI:
['RSSI', 'dB', 'mdi:wifi', None],
SENSOR_TYPE_UPTIME:
['Uptime', 's', 'mdi:timer', None],
SENSOR_TYPE_BATTERY:
['Battery', '%', 'mdi:battery-50', None]
}
def setup_platform(hass, _config, add_devices, discovery_info=None):
"""Setup the Shelly Sensor platform."""
if 'version' in discovery_info:
add_devices([ShellyVersion(hass, discovery_info.get('version'),
discovery_info.get('pyShellyVersion'))])
return
if 'rssi' in discovery_info:
block = get_block_from_hass(hass, discovery_info)
add_devices([
ShellyInfoSensor(block, hass, SENSOR_TYPE_RSSI, 'rssi')
])
return
if 'uptime' in discovery_info:
block = get_block_from_hass(hass, discovery_info)
add_devices([
ShellyInfoSensor(block, hass, SENSOR_TYPE_UPTIME, 'uptime')
])
return
dev = get_device_from_hass(hass, discovery_info)
if dev.device_type == "POWERMETER":
add_devices([
ShellySensor(dev, hass, SENSOR_TYPE_POWER, 'watt'),
])
elif dev.device_type == "SENSOR":
add_devices([
ShellySensor(dev, hass, SENSOR_TYPE_TEMPERATURE, 'temperature'),
ShellySensor(dev, hass, SENSOR_TYPE_HUMIDITY, 'humidity'),
ShellySensor(dev, hass, SENSOR_TYPE_BATTERY, 'battery')
])
class ShellySensor(ShellyDevice, Entity):
"""Representation of a Shelly Sensor."""
def __init__(self, dev, hass, sensor_type, sensor_name):
"""Initialize an ShellySwitch."""
ShellyDevice.__init__(self, dev, hass)
self._unique_id += "_" + sensor_name
self.entity_id += "_" + sensor_name
self._sensor_type = sensor_type
self._sensor_name = sensor_name
self._battery = None
self._state = None
self.update()
@property
def state(self):
"""Return the state of the sensor."""
return self._state
@property
def quantity_name(self):
"""Name of quantity."""
return SENSOR_TYPES[self._sensor_type][0] \
if self._sensor_type in SENSOR_TYPES else None
@property
def unit_of_measurement(self):
"""Return the unit of measurement."""
return SENSOR_TYPES[self._sensor_type][1] \
if self._sensor_type in SENSOR_TYPES else None
@property
def icon(self):
"""Return the icon."""
return SENSOR_TYPES[self._sensor_type][2] \
if self._sensor_type in SENSOR_TYPES else None
@property
def device_class(self):
"""Return the device class."""
return SENSOR_TYPES[self._sensor_type][3] \
if self._sensor_type in SENSOR_TYPES else None
def update(self):
"""Fetch new state data for this sensor."""
if self._dev.sensor_values is not None:
self._state = self._dev.sensor_values.get(self._sensor_name, None)
self._battery = self._dev.sensor_values.get('battery', None)
@property
def device_state_attributes(self):
attr = super(ShellySensor, self).device_state_attributes
if self._battery is not None:
attr["battery"] = str(self._battery) + '%'
return attr
class ShellyInfoSensor(ShellyBlock, Entity):
"""Representation of a Shelly Info Sensor."""
def __init__(self, block, hass, sensor_type, sensor_name):
ShellyBlock.__init__(self, block, hass, "_" + sensor_name)
self.entity_id = "sensor" + self.entity_id
self._sensor_name = sensor_name
self._sensor_type = sensor_type
self._state = None
self.update()
def update(self):
"""Fetch new state data for this sensor."""
if self._block.info_values is not None:
self._state = self._block.info_values.get(self._sensor_name, None)
#if self._block.sensor_values is not None:
# self._battery = self._block.sensor_values.get('battery', None)
@property
def state(self):
"""Return the state of the sensor."""
return self._state
def quantity_name(self):
"""Name of quantity."""
return SENSOR_TYPES[self._sensor_type][0] \
if self._sensor_type in SENSOR_TYPES else None
@property
def unit_of_measurement(self):
"""Return the unit of measurement."""
return SENSOR_TYPES[self._sensor_type][1] \
if self._sensor_type in SENSOR_TYPES else None
@property
def icon(self):
"""Return the icon."""
return SENSOR_TYPES[self._sensor_type][2] \
if self._sensor_type in SENSOR_TYPES else None
@property
def device_state_attributes(self):
return None
class ShellyVersion(Entity):
"""Representation of a Shelly version sensor."""
def __init__(self, hass, version, py_shelly_version):
"""Initialize the Version sensor."""
conf = hass.data[SHELLY_CONFIG]
id_prefix = conf.get(CONF_OBJECT_ID_PREFIX)
self._version = version
self._py_shelly_version = py_shelly_version
self.entity_id = "sensor." + id_prefix + "_version"
self._name = "Shelly version"
@property
def name(self):
"""Return the name of the sensor."""
return 'Shelly version'
@property
def state(self):
"""Return the state of the sensor."""
return self._version + "/" + self._py_shelly_version
@property
def device_state_attributes(self):
"""Return attributes for the sensor."""
return {'shelly': self._version, 'pyShelly': self._py_shelly_version}
@property
def icon(self):
"""Return the icon to use in the frontend, if any."""
return None
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evolversFiles/cameraEngine.py | coding-lines/evolvers | 0 | 154408 | #cameraCoords syntax: [x1 (oben links),y1,x2 (unten rechts),y2,zoomLevel]
def moveCamera(cameraCoords, move,worldSize):
if cameraCoords[0]+move[0] <= 1 and move[0] < 0:
cameraCoords[0] -= cameraCoords[0]%1
cameraCoords[2] -= cameraCoords[2]%1
while cameraCoords[0] > 1:
cameraCoords[0] -= 1 #Wenn Kamera x-Koordinaten unter 0 gesetzt werden, werden die Koordinaten proportional angeglichen
cameraCoords[2] -= 1
elif cameraCoords[2]+move[0]+1 >= worldSize[0]:
return cameraCoords
else:
cameraCoords[0] += move[0]
cameraCoords[2] += move[0]#Bewegen (x)
if cameraCoords[1]+move[1] <= 1 and move[1] < 0:
cameraCoords[1] -= cameraCoords[1]%1
cameraCoords[3] -= cameraCoords[3]%1
while cameraCoords[1] > 1:
cameraCoords[1] -= 1#Wenn Kamera y-Koordinaten unter 0 gesetzt werden, werden die Koordinaten proportional angeglichen
cameraCoords[3] -= 1
elif cameraCoords[3]+move[1]+1 >= worldSize[1]:
return cameraCoords
else:
cameraCoords[1] += move[1]
cameraCoords[3] += move[1]#Bewegen (y)
return cameraCoords
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bot/plugins/keyboard/__init__.py | grahamtito/TelegramFiletoCloud | 0 | 17911 | #!/usr/bin/env python3
# This is bot coded by <NAME> and used for educational purposes only
# https://github.com/AbhijithNT
# Copyright <NAME>
# Thank you https://github.com/pyrogram/pyrogram
from pyrogram.types import (
InlineKeyboardMarkup,
InlineKeyboardButton
)
def server_select():
upload_selection = [
[
InlineKeyboardButton(
"transfer.sh",
callback_data="transfersh"
),
InlineKeyboardButton(
"File.io",
callback_data="File.io"
)
],
[
InlineKeyboardButton(
"gofile.io",
callback_data="gofileio"
),
InlineKeyboardButton(
"anonymfiles.com",
callback_data="anonymfiles"
)
],
[
InlineKeyboardButton(
"aparat",
callback_data="aparat"
),
InlineKeyboardButton(
"splus",
callback_data="splus"
)
]
]
return InlineKeyboardMarkup(upload_selection)
def completedKeyboard(dl):
replayMarkup = InlineKeyboardMarkup(
[[
InlineKeyboardButton(
"DOWNLOAD URL",
url=f"{dl}"
)
],
[
InlineKeyboardButton(
"🗂 SOURCE",
url="https://github.com/AbhijithNT/"
)
]])
return replayMarkup
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tests/test_posterior.py | joergdietrich/CredibleIntervals | 0 | 1600703 | <reponame>joergdietrich/CredibleIntervals
import numpy as np
from numpy.testing import assert_almost_equal
from credible_interval import Posterior
def test_posterior():
np.random.seed(20180131)
x = np.random.normal(10, 5, 10000)
posterior = Posterior(x)
assert_almost_equal(9.9243057716556589, posterior.mean)
assert_almost_equal(9.761182264312712, posterior.mode)
assert_almost_equal(5.0345710789483089, posterior.std)
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] |
dice roll project 1.py | anuraag392/How-to-make-a-simple-dice-roll-program | 0 | 95393 | <reponame>anuraag392/How-to-make-a-simple-dice-roll-program<filename>dice roll project 1.py<gh_stars>0
from tkinter import *
import random
root=Tk()
root.title("Dice roll")
root.geometry("500x400")
label=Label(root,font=('helvetica',250,'bold'),text='')
label.pack()
def rolldice():
dice=['\u2680','\u2681','\u2682','\u2683','\u2684','\u2685']
label.configure(text=f'{random.choice(dice)}')
label.pack()
button=Button(root,font=('helvetica',15,'bold'),text='roll dice',command=rolldice)
button.pack()
root.mainloop()
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TweetUpdateThread.py | mrtazz/twsh | 1 | 1601740 | # thread class for updating tweets in the background
import time
import threading
class TweetUpdateThread(threading.Thread):
''' thread class to fetch tweets in the background '''
def __init__(self, cli_object, function, waittime):
''' At initialization some local variables are set:
waittime = the time to wait between tweet fetches
cli = the cli object from which the update cmd is called
function = the update function to call from the cli object
endme = boolean value to determine whether to stop the thread
counter = counting the sleeps until the next update
'''
threading.Thread.__init__(self)
self.waittime = waittime
self.cli = cli_object
self.function = function
self.endme = False
self.counter = 0
def stop(self):
''' stop the thread '''
threading.Thread.__stop(self)
def run(self):
''' The thread is run here until the endme variable is set
to true. While running the thread executes the passed
cli function in intervals of waittime. Time may differ if
this thread is run a long time because of command execution
delays. Has to be tested. The construct with checking the
endme variable every second secures that the user doesn't
have to wait another waittime interval (worst case) until
the thread is ended
'''
while self.endme == False:
if self.counter == self.waittime:
self.counter = 0
self.cli.do_hello("")
else:
self.counter = self.counter + 1
time.sleep(1)
def setend(self):
''' Interface to set the end of the thread '''
self.endme = True | [
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pdfmajor/interpreter/commands/state/PDFGraphicState/PDFColor.py | asosnovsky/pdfmajor | 23 | 36885 | <filename>pdfmajor/interpreter/commands/state/PDFGraphicState/PDFColor.py
from typing import Tuple, Optional
from .PDFColorSpace import PDFColorSpace
class PDFColor:
def __init__(self, color_space: Optional[PDFColorSpace], *values: float):
self.color_space: Optional[PDFColorSpace] = color_space
self.values: Tuple[float, ...] = values
def copy(self):
return self.__class__(
self.color_space,
*self.values
)
def __repr__(self):
return f"""<PDFColor space="{
None if self.color_space is None else self.color_space.name
}" values={self.values}/>"""
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old/am2320.py | eggplant60/airalarm | 0 | 133614 | #!/usr/bin/python
# -*- coding: utf-8 -*-
import smbus
import time
import datetime
import threading
import crc16
ADDRESS = 0x5c # 7bit address (will be left shifted to add the read write bit)
READ_INT = 10 # [sec], each reading interval is to be grater than 2 sec
LOG_INT = 600 # [sec]
DEBUG_MODE = True
#W_ADDR = ADDRESS << 1 + 0x00 # ADDRESS(7bit) + R/W bit(1bit)
#R_ADDR = ADDRESS << 1 + 0x01 # ADDRESS(7bit) + R/W bit(1bit)
# Print a given message with the date
def printDateMsg(msg):
d = datetime.datetime.today()
print d.strftime('%Y/%m/%d %H:%M:%S') + ' [TRMO] ' + msg
# am2320
class Thermo():
def __init__(self):
self.__i2c_bus = smbus.SMBus(1)
self.__hum = 0.0
self.__tmp = 0.0
self.tu = threading.Thread(target=self.__updateValue)
self.tu.setDaemon(True)
self.tu.start()
self.tl = threading.Thread(target=self.__logValue)
self.tl.setDaemon(True)
self.tl.start()
def __updateValue(self):
while True:
try:
self.__i2c_bus.write_i2c_block_data(ADDRESS, 0x00, []) # センサsleep解除
except:
pass # センサはACK が帰ってくるとは限らない仕様
time.sleep(0.001) # Min: 800us
try:
self.__i2c_bus.write_i2c_block_data(ADDRESS,0x03,[0x00,0x04]) # 読み取り命令
except:
if DEBUG_MODE: printDateMsg("[Error] am2320(1) ")
self.__hum = 0.0 # 読み取り失敗時は0.0
self.__tmp = 0.0
time.sleep(READ_INT)
continue
time.sleep(0.002) # Min: 1.5ms
try:
block = self.__i2c_bus.read_i2c_block_data(ADDRESS,0,8) # データ受取
except:
if DEBUG_MODE: printDateMsg("[Error] am2320(2) ")
self.__hum = 0.0 # 読み取り失敗時は0.0
self.__tmp = 0.0
time.sleep(READ_INT)
continue
# # CRC Chech
# #block[0] = 0x03
# print(block)
# crc = crc16.crc16(block[0:6])
# print(crc & 0xFF, crc >> 8)
self.__hum = (block[2] << 8 | block[3])/10.0
self.__tmp = (block[4] << 8 | block[5])/10.0
time.sleep(READ_INT)
def __logValue(self):
while True:
time.sleep(LOG_INT)
printDateMsg(self.stringValue())
def getHum(self):
return self.__hum
def getTmp(self):
return self.__tmp
def stringValue(self):
return "Humidity: " + str(self.getHum()) + "%, " \
+ "Temparature: " + str(self.getTmp()) + "℃"
def displayValue(self):
print self.stringValue()
def main_loop():
while True:
thermo.displayValue()
time.sleep(1)
if __name__ == '__main__':
thermo = Thermo()
try:
main_loop()
except KeyboardInterrupt:
print "Keyboard Interrupt"
# finally:
# thermo.stop()
# ============= EOF ======================
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CoffeeMachine/Config/Services.py | kerusey/FES | 7 | 169385 | from getpass import getpass
import subprocess
from os import system
import pathlib
import string
vncAutostartScript = """
[Desktop Entry]
Type=Application
Name=TightVNC
Exec=vncserver :1
StartupNotify=false
"""
def vncautostart():
system("sudo mkdir /home/" + GLOBALUSERNAME + "")
def getLan(): # OK
import netifaces
interfaces = netifaces.interfaces()
for i in interfaces:
if i == 'lo':
continue
iface = netifaces.ifaddresses(i).get(netifaces.AF_INET)
if iface != None:
for j in iface:
return str(j['addr'])
def initSshServer(): # OK
print("Creating a new user...")
print("Enter new login: ", end="")
userName = str(input())
password = str(<PASSWORD>())
system("sudo /usr/sbin/useradd --groups sudo -m " + userName + " -p " + password)
print("New user has been successfully added.")
''' # Experemental convertation !
print("Converting data between accounts...")
sourcePath = "/home/pi/"
destinationPath = "/home/" + userName
source = listdir(sourcePath)
for item in source:
try:
move(sourcePath + item, destinationPath)
except:
print("exception")
subprocess.call(["sudo", "deluser", "--remove", "pi"])
'''
print("Establishing SSH server...")
system("sudo passwd " + userName)
system("sshpass -p " + password + " ssh " + userName + "@" + getLan())
system("sudo systemctl enable ssh")
system("sudo systemctl start ssh")
return userName
def initVncServer(userName): # OK
print("Enabling VNC protocol...")
password = str(<PASSWORD>())
system("sudo vncserver -p " + password)
autostartPath = "/home/" + userName + "/.config/autostart/"
pathlib.Path(autostartPath).mkdir(parents=True, exist_ok=True)
with open(autostartPath + "tightvnc.desktop", "w") as vncStart: # adding to the autostart
vncStart.write(vncAutostartScript)
with open("autostart.sh", 'a') as vncStart:
vncStart.write("vncserver -p " + password)
system("sudo cp autostart.sh /etc/init.d/autostart.sh")
system("sudo update-rc.d autostart.sh defaults")
system("sudo chmod +x /etc/init.d/autostart.sh")
system("rm autostart.sh")
def initFtpServer(): # OK
print("Establish FTP...")
system("sudo groupadd ftpgroup")
system("sudo useradd ftpuser -g ftpgroup -s /sbin/nologin -d /dev/null")
system("sudo pure-pw useradd upload -u ftpuser -g ftpgroup -d /home/pi -m")
system("sudo pure-pw mkdb")
system("sudo service pure-ftpd restart")
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venv/Lib/site-packages/zmq/tests/test_draft.py | ajayiagbebaku/NFL-Model | 603 | 4103 | # -*- coding: utf8 -*-
# Copyright (C) PyZMQ Developers
# Distributed under the terms of the Modified BSD License.
import os
import platform
import time
import pytest
import zmq
from zmq.tests import BaseZMQTestCase, skip_pypy
class TestDraftSockets(BaseZMQTestCase):
def setUp(self):
if not zmq.DRAFT_API:
raise pytest.skip("draft api unavailable")
super(TestDraftSockets, self).setUp()
def test_client_server(self):
client, server = self.create_bound_pair(zmq.CLIENT, zmq.SERVER)
client.send(b'request')
msg = self.recv(server, copy=False)
assert msg.routing_id is not None
server.send(b'reply', routing_id=msg.routing_id)
reply = self.recv(client)
assert reply == b'reply'
def test_radio_dish(self):
dish, radio = self.create_bound_pair(zmq.DISH, zmq.RADIO)
dish.rcvtimeo = 250
group = 'mygroup'
dish.join(group)
received_count = 0
received = set()
sent = set()
for i in range(10):
msg = str(i).encode('ascii')
sent.add(msg)
radio.send(msg, group=group)
try:
recvd = dish.recv()
except zmq.Again:
time.sleep(0.1)
else:
received.add(recvd)
received_count += 1
# assert that we got *something*
assert len(received.intersection(sent)) >= 5
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report-conf/generate_report.py | sdinot/pytest-executable | 0 | 84558 | #! /usr/bin/env python
# Copyright 2020 CS Systemes d'Information, http://www.c-s.fr
#
# This file is part of pytest-executable
# https://www.github.com/CS-SI/pytest-executable
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""This module generates the test report.
It shall be called from the test output root directory where the tests report
database file is (tests_report_db.yaml). Under the output root directory, it
will create a:
- the index.rst file from the index_template.rst,
- the directory named report that contains the generated report.
In the template index, the summary table and the table of content are inserted.
A line of the summary table contains a case:
- path relative to the output root directory,
- test status (passed, failed, error)
- test messages when the status is not passed
The table of content contains the path to the description.rst files relative to
the output root directory.
This module requires the packages tabulate and sphinx, these could be installed
with the command: conda install tabluate sphinx
"""
import subprocess
import textwrap
from pathlib import Path
from typing import List, Tuple
import yaml
from tabulate import tabulate
# indentation used in the toc tree of the index template
TOCTREE_INDENTATION = " "
# name of the directory under the test output directory that will contain the
# generated report
REPORT_OUTPUT_DIRNAME = "report"
# description file name in each test case output directory
DESCRIPTION_FILENAME = "description.rst"
# the directory that contains the current module
DOC_GENERATOR_DIRPATH = Path(__file__).parent
# sphinx documentation builder type
DOC_BUILDER = "html"
# name of the test report database
REPORT_DB_FILENAME = "tests_report_db.yaml"
# template file for creating the index.rst
INDEX_TEMPLATE_RST = "index_template.rst"
def create_summary_table(output_root: Path) -> str:
"""Create the summary table in rst.
The summary table is sorted alphabetically.
Args:
output_root: Path to the test results output directory.
Returns:
The summary table string in rst format.
"""
with (output_root / REPORT_DB_FILENAME).open() as stream:
report_db = yaml.safe_load(stream)
report_data: List[Tuple[str]] = []
for case, data in report_db.items():
messages = "\n".join(data.get("messages", []))
report_data += [(case, data["status"], messages)]
return tabulate(
sorted(report_data), headers=["Case", "Status", "Messages"], tablefmt="rst"
)
def create_index_rst(output_root: Path) -> None:
"""Create the index.rst.
Args:
output_root: Path to the test results output directory.
"""
# check that the output directory exists
output_root = Path(output_root).resolve(True)
# find the paths to the description rst files relatively to the output_root
description_paths: List[Path] = []
for path in output_root.glob(f"**/{DESCRIPTION_FILENAME}"):
description_paths += [path.relative_to(output_root)]
summary_table = create_summary_table(output_root)
# the toc tree is sorted alphabetically like the summary table
toctree_cases = textwrap.indent(
"\n".join(map(str, sorted(description_paths))), TOCTREE_INDENTATION
)
# read the index template
index_template_path = DOC_GENERATOR_DIRPATH / INDEX_TEMPLATE_RST
with index_template_path.open() as stream:
index_rst_template = stream.read()
# replace the placeholders in the template
index_rst = index_rst_template.format(
summary_table=summary_table, toctree_cases=toctree_cases
)
# write the final index.rst
index_path = output_root / "index.rst"
with index_path.open("w") as stream:
stream.write(index_rst)
if __name__ == "__main__":
# common working directory shall be the test output root directory
output_root = Path.cwd()
# create the report index.rst
create_index_rst(output_root)
# command line to build the report
cmd = (
f"sphinx-build -b {DOC_BUILDER} -c {DOC_GENERATOR_DIRPATH} "
f"{output_root} {output_root}/{REPORT_OUTPUT_DIRNAME}"
)
# build the report
subprocess.run(cmd.split(), check=True)
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] |
python/data_sutram/scraper/perform__.py | SayanGhoshBDA/code-backup | 16 | 122263 | <filename>python/data_sutram/scraper/perform__.py<gh_stars>10-100
import json
from selenium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
options = webdriver.ChromeOptions()
#options.binary_location = "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome"
chrome_driver_binary = "../chromedriver"
driver = webdriver.Chrome(chrome_driver_binary, chrome_options=options)
"""
caps = DesiredCapabilities.CHROME
caps['loggingPrefs'] = {'performance': 'ALL'}
driver = webdriver.Chrome(desired_capabilities=caps)
"""
driver.get('https://stackoverflow.com/questions/52633697/selenium-python-how-to-capture-network-traffics-response')
def process_browser_log_entry(entry):
response = json.loads(entry['message'])['message']
return response
browser_log = driver.get_log('performance')
events = [process_browser_log_entry(entry) for entry in browser_log]
events = [event for event in events if 'Network.response' in event['method']]
print(events) | [
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buildchain/buildchain/versions.py | zarumaru/metalk8s | 0 | 73060 | <filename>buildchain/buildchain/versions.py<gh_stars>0
# coding: utf-8
"""Authoritative listing of image and package versions used in the project.
This module MUST be kept valid in a standalone context, since it is intended
for use in tests and documentation as well.
"""
import operator
from collections import namedtuple
from pathlib import Path
from typing import cast, Dict, Optional, Tuple
Image = namedtuple('Image', ('name', 'version', 'digest'))
# Project-wide versions {{{
CALICO_VERSION : str = '3.8.2'
K8S_VERSION : str = '1.15.12'
SALT_VERSION : str = '3000.3'
def load_version_information() -> None:
"""Load version information from `VERSION`."""
to_update = {
'VERSION_MAJOR', 'VERSION_MINOR', 'VERSION_PATCH', 'VERSION_SUFFIX'
}
with VERSION_FILE.open('r', encoding='utf-8') as fp:
for line in fp:
name, _, value = line.strip().partition('=')
# Don't overwrite random variables by trusting an external file.
var = name.strip()
if var in to_update:
globals()[var] = value.strip()
VERSION_FILE = (Path(__file__)/'../../../VERSION').resolve()
# Metalk8s version.
# (Those declarations are not mandatory, but they help pylint and mypy).
VERSION_MAJOR : str
VERSION_MINOR : str
VERSION_PATCH : str
VERSION_SUFFIX : str
load_version_information()
SHORT_VERSION : str = '{}.{}'.format(VERSION_MAJOR, VERSION_MINOR)
VERSION : str = '{}.{}{}'.format(SHORT_VERSION, VERSION_PATCH, VERSION_SUFFIX)
# }}}
# Container images {{{
CENTOS_BASE_IMAGE : str = 'docker.io/centos'
CENTOS_BASE_IMAGE_SHA256 : str = \
'6ae4cddb2b37f889afd576a17a5286b311dcbf10a904409670827f6f9b50065e'
GRAFANA_IMAGE_VERSION : str = '6.7.4'
NGINX_IMAGE_VERSION : str = '1.15.8'
NODEJS_IMAGE_VERSION : str = '10.16.0'
# Current build IDs, to be augmented whenever we rebuild the corresponding
# image, e.g. because the `Dockerfile` is changed, or one of the dependencies
# installed in the image needs to be updated.
# This should be reset to 1 when the service exposed by the container changes
# version.
SALT_MASTER_BUILD_ID = 1
def _version_prefix(version: str, prefix: str = 'v') -> str:
return "{}{}".format(prefix, version)
# Digests are quite a mouthful, so:
# pylint:disable=line-too-long
CONTAINER_IMAGES : Tuple[Image, ...] = (
# Remote images
Image(
name='alertmanager',
version='v0.19.0',
digest='sha256:7dbf4949a317a056d11ed8f379826b04d0665fad5b9334e1d69b23e946056cd3',
),
Image(
name='calico-node',
version=_version_prefix(CALICO_VERSION),
digest='sha256:6679ccc9f19dba3eb084db991c788dc9661ad3b5d5bafaa3379644229dca6b05',
),
Image(
name='calico-kube-controllers',
version=_version_prefix(CALICO_VERSION),
digest='sha256:cf461efd25ee74d1855e1ee26db98fe87de00293f7d039212adb03c91fececcd',
),
Image(
name='configmap-reload',
version='v0.0.1',
digest='sha256:e2fd60ff0ae4500a75b80ebaa30e0e7deba9ad107833e8ca53f0047c42c5a057',
),
Image(
name='coredns',
version='1.3.1',
digest='sha256:02382353821b12c21b062c59184e227e001079bb13ebd01f9d3270ba0fcbf1e4',
),
Image(
name='etcd',
version='3.3.10',
digest='sha256:17da501f5d2a675be46040422a27b7cc21b8a43895ac998b171db1c346f361f7',
),
Image(
name='k8s-sidecar',
version='0.1.20',
digest='sha256:af151f677a63cdfcdfc18a4e3043520ec506d5e116692e5190f6f765dca42a52',
),
Image(
name='kube-apiserver',
version=_version_prefix(K8S_VERSION),
digest='sha256:2168be2ce87258d71beacf2f774ec157dfc28bef991b406e3694077cfc5b9302',
),
Image(
name='kube-controller-manager',
version=_version_prefix(K8S_VERSION),
digest='sha256:1c37052f9efb91d4947f2805d32b81d522f5b8b11a05a5550f9b4dc65c91db7f',
),
Image(
name='kube-proxy',
version=_version_prefix(K8S_VERSION),
digest='sha256:937cc513f162062f8b2642de08ce6e3877cae5cf58e5276830796749e29cab42',
),
Image(
name='kube-scheduler',
version=_version_prefix(K8S_VERSION),
digest='sha256:e2ceb7321239a9587bbb7f3de43743a4b60249c7ed3a953d115217d5dcbbe762',
),
Image(
name='kube-state-metrics',
version='v1.8.0',
digest='sha256:f75c3e5c5c7f65846ddd6883d6187b38f77721a3938f241c9e5d0ebe7beb8e19',
),
Image(
name='nginx',
version=NGINX_IMAGE_VERSION,
digest='sha256:f09fe80eb0e75e97b04b9dfb065ac3fda37a8fac0161f42fca1e6fe4d0977c80',
),
Image(
name='nginx-ingress-controller',
version='0.26.1',
digest='sha256:464db4880861bd9d1e74e67a4a9c975a6e74c1e9968776d8d4cc73492a56dfa5',
),
Image(
name='nginx-ingress-defaultbackend-amd64',
version='1.5',
digest='sha256:4dc5e07c8ca4e23bddb3153737d7b8c556e5fb2f29c4558b7cd6e6df99c512c7',
),
Image(
name='node-exporter',
version='v0.18.1',
digest='sha256:a2f29256e53cc3e0b64d7a472512600b2e9410347d53cdc85b49f659c17e02ee',
),
Image(
name='pause',
version='3.1',
digest='sha256:da86e6ba6ca197bf6bc5e9d900febd906b133eaa4750e6bed647b0fbe50ed43e',
),
Image(
name='prometheus',
version='v2.13.1',
digest='sha256:0a8caa2e9f19907608915db6e62a67383fe44b9876a467b297ee6f64e51dd58a',
),
Image(
name='k8s-prometheus-adapter-amd64',
version='v0.5.0',
digest='sha256:acf4c4dc6aaa51e3004eebdc410b509db45d1a6ebd255457c5745f0b4671678f',
),
Image(
name='prometheus-config-reloader',
version='v0.34.0',
digest='sha256:459bc1b1fc51420cd244b082fe14444f6d8596997c2e40f52c08d1f5a09ab860',
),
Image(
name='prometheus-operator',
version='v0.34.0',
digest='sha256:c0bcb231fe67cd11fd26f7adf5ac1080dfac189ac94705538bd4ab7dd99a98a9',
),
# Local images
Image(
name='grafana',
version=GRAFANA_IMAGE_VERSION,
digest=None,
),
Image(
name='metalk8s-ui',
version=VERSION,
digest=None,
),
Image(
name='metalk8s-utils',
version=VERSION,
digest=None,
),
Image(
name='salt-master',
version='{version}-{build_id}'.format(
version=SALT_VERSION, build_id=SALT_MASTER_BUILD_ID
),
digest=None,
),
Image(
name='storage-operator',
version='latest',
digest=None,
),
)
CONTAINER_IMAGES_MAP = {image.name: image for image in CONTAINER_IMAGES}
# }}}
# Packages {{{
class PackageVersion:
"""A package's authoritative version data.
This class contains version information for a named package, and
provides helper methods for formatting version/release data as well
as version-enriched package name, for all supported OS families.
"""
def __init__(
self,
name: str,
version: Optional[str] = None,
release: Optional[str] = None,
override: Optional[str] = None
):
"""Initializes a package version.
Arguments:
name: the name of the package
version: the version of the package
release: the release of the package
"""
self._name = name
self._version = version
self._release = release
self._override = override
name = property(operator.attrgetter('_name'))
version = property(operator.attrgetter('_version'))
release = property(operator.attrgetter('_release'))
override = property(operator.attrgetter('_override'))
@property
def full_version(self) -> Optional[str]:
"""The full package version string."""
full_version = None
if self.version:
full_version = self.version
if self.release:
full_version = '{}-{}'.format(self.version, self.release)
return full_version
@property
def rpm_full_name(self) -> str:
"""The package's full name in RPM conventions."""
if self.full_version:
return '{}-{}'.format(self.name, self.full_version)
return cast(str, self.name)
@property
def deb_full_name(self) -> str:
"""The package's full name in DEB conventions."""
if self.full_version:
return '{}={}'.format(self.name, self.full_version)
return cast(str, self.name)
# The authoritative list of packages required.
#
# Common packages are packages for which we need not care about OS-specific
# divergences.
#
# In this case, either:
# * the _latest_ version is good enough, and will be the one
# selected by the package managers (so far: apt and yum).
# * we have strict version requirements that span OS families, and the
# version schemes _and_ package names do not diverge
#
# Strict version requirements are notably:
# * kubelet and kubectl which _make_ the K8s version of the cluster
# * salt-minion which _makes_ the Salt version of the cluster
#
# These common packages may be overridden by OS-specific packages if package
# names or version conventions diverge.
#
# Packages that we build ourselves require a version and release as part of
# their build process.
PACKAGES: Dict[str, Tuple[PackageVersion, ...]] = {
'common': (
# Pinned packages
PackageVersion(name='kubectl', version=K8S_VERSION),
PackageVersion(name='kubelet', version=K8S_VERSION),
# Latest packages
PackageVersion(name='containerd'),
PackageVersion(name='coreutils'),
PackageVersion(name='cri-tools'),
PackageVersion(name='e2fsprogs'),
PackageVersion(name='ebtables'),
PackageVersion(name='ethtool'),
PackageVersion(name='genisoimage'),
PackageVersion(name='iproute'),
PackageVersion(name='iptables'),
PackageVersion(name='kubernetes-cni'),
PackageVersion(name='m2crypto'),
PackageVersion(name='runc'),
PackageVersion(name='salt-minion', version=SALT_VERSION),
PackageVersion(name='socat'),
PackageVersion(name='sos'), # TODO download built package dependencies
PackageVersion(name='util-linux'),
PackageVersion(name='xfsprogs'),
),
'redhat': (
PackageVersion(
name='calico-cni-plugin',
version=CALICO_VERSION,
release='1.el7'
),
PackageVersion(name='container-selinux'), # TODO #1710
PackageVersion(
name='metalk8s-sosreport',
version=SHORT_VERSION,
release='1.el7'
),
PackageVersion(name='yum-plugin-versionlock'),
PackageVersion(name='yum-utils'),
),
'debian': (
PackageVersion(
name='calico-cni-plugin',
version=CALICO_VERSION,
release='1'
),
PackageVersion(name='iproute2', override='iproute'),
PackageVersion(
name='metalk8s-sosreport',
version=SHORT_VERSION,
release='1'
),
PackageVersion(name='python-m2crypto', override='m2crypto'),
PackageVersion(name='sosreport', override='sos'),
),
}
def _list_pkgs_for_os_family(os_family: str) -> Tuple[PackageVersion, ...]:
"""List downloaded packages for a given OS family.
Arguments:
os_family: OS_family for which to list packages
"""
common_pkgs = PACKAGES['common']
os_family_pkgs = PACKAGES.get(os_family)
if os_family_pkgs is None:
raise Exception('No packages for OS family: {}'.format(os_family))
os_override_names = [
pkg.override for pkg in os_family_pkgs
if pkg.override is not None
]
overridden = filter(
lambda item: item.name not in os_override_names,
common_pkgs
)
return tuple(overridden) + os_family_pkgs
RPM_PACKAGES = _list_pkgs_for_os_family('redhat')
RPM_PACKAGES_MAP = {pkg.name: pkg for pkg in RPM_PACKAGES}
DEB_PACKAGES = _list_pkgs_for_os_family('debian')
DEB_PACKAGES_MAP = {pkg.name: pkg for pkg in DEB_PACKAGES}
# }}}
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2
] |
pconf/store/env.py | sthagen/pconf | 20 | 107715 | <reponame>sthagen/pconf
import os
import re
from ast import literal_eval
from warnings import warn
class Env(object):
def __init__(
self,
separator=None,
match=None,
whitelist=None,
parse_values=False,
to_lower=False,
convert_underscores=False,
docker_secrets=None,
):
self.separator = separator
self.match = match
self.whitelist = whitelist
self.parse_values = parse_values
self.to_lower = to_lower
self.convert_underscores = convert_underscores
self.docker_secrets = docker_secrets
if self.match is not None:
self.re = re.compile(self.match)
self.__gather_vars()
if self.to_lower:
self.vars = self.__change_keys(self.vars, self.__to_lower)
if self.convert_underscores:
self.vars = self.__change_keys(self.vars, self.__convert_underscores)
def get(self):
return self.vars
def __valid_key(self, key):
if self.match is not None and self.whitelist is not None:
return key in self.whitelist or self.re.search(key) is not None
elif self.match is not None:
return self.re.search(key) is not None
elif self.whitelist is not None:
return key in self.whitelist
else:
return True
def __split_vars(self, env_vars):
keys_to_delete = []
dict_to_add = {}
for key in env_vars.keys():
splits = key.split(self.separator)
splits = list(filter(None, splits))
if len(splits) != 1:
split = self.__split_var(splits, env_vars[key])
keys_to_delete.append(key)
self.__merge_split(split, dict_to_add)
for key in keys_to_delete:
del env_vars[key]
env_vars.update(dict_to_add)
def __split_var(self, keys, value):
if len(keys) == 1:
return {keys[0]: value}
else:
key = keys[0]
del keys[0]
return {key: self.__split_var(keys, value)}
def __merge_split(self, split, env_vars):
key = list(split.keys())[0]
value = list(split.values())[0]
if key not in env_vars:
env_vars[key] = value
return
elif type(value) == dict:
self.__merge_split(value, env_vars[key])
else:
return
def __try_parse(self, env_vars):
for key, value in env_vars.items():
try:
if value.lower() == "true":
env_vars[key] = True
elif value.lower() == "false":
env_vars[key] = False
else:
env_vars[key] = literal_eval(value)
except (ValueError, SyntaxError):
pass
def __handle_docker_secret(self, key, value):
postfix = "_FILE"
if key.endswith(postfix):
try:
with open(value, "r") as f:
self.vars[key[0 : -len(postfix)]] = f.read().strip() # noqa: E203
except IOError:
warn("IOError when opening {}".format(value), UserWarning)
def __gather_vars(self):
self.vars = {}
env_vars = os.environ
for key in env_vars.keys():
if self.__valid_key(key):
if self.docker_secrets is not None and key in self.docker_secrets:
self.__handle_docker_secret(key, env_vars[key])
else:
self.vars[key] = env_vars[key]
if self.parse_values:
self.__try_parse(self.vars)
if self.separator is not None:
self.__split_vars(self.vars)
def __to_lower(self, key):
return key.lower()
def __convert_underscores(self, key):
return key.replace("_", "-")
def __change_keys(self, env_vars, operation):
new_dict = {}
for key, value in env_vars.items():
if type(value) == dict:
new_dict[operation(key)] = self.__change_keys(value, operation)
else:
new_dict[operation(key)] = env_vars[key]
return new_dict
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] |
setup.py | breaks-software/OSCAAR | 0 | 57386 | # -*- coding: utf-8 -*-
"""Made by <NAME> (UL/TUD), with tweaks by <NAME> (NASA GSFC/UMD)"""
import os
import sys
import shutil
import subprocess
import atexit
import urllib2
def internet_on():
refURL = 'http://74.125.228.100' ## One Google IP address (bypass DNS lookup)
try:
response=urllib2.urlopen(refURL,timeout=1)
return True
except urllib2.URLError as err: pass
return False
# Checking for all required packages and if these are recent enough
minimum_numpy_version = "1.6"
minimum_matplotlib_version = "1.0"
minimum_pyfits_version = "3.1.0" # lower versions may work (not tested)
minimum_scipy_version = "0.10" # lower versions may work (not tested)
minimum_wxpython_version = "2.0" # lower versions may work (not tested)
sysplatform = sys.platform
if not hasattr(sys, 'real_prefix'):
# Currently only Python 2.7.x is supported
if sys.version_info[:2] != (2, 7):
raise RuntimeError("must use python 2.7.x")
if not internet_on():
raise RuntimeError("Must be connected to the internet to complete "\
"install. Please connect to the internet and start "\
"the install again.")
# Check if the package dependancies/requirements are fulfilled
try:
from setuptools import setup
except:
raise RuntimeError("Setuptools not found, setup cannot continue without it")
try:
import numpy as np
except:
raise RuntimeError("Numpy not found")
if np.__version__ < minimum_numpy_version:
print("*Error*: NumPy version is lower than needed: %s < %s" %
(np.__version__, minimum_numpy_version))
sys.exit(1)
try:
import scipy
except:
raise RuntimeError("Scipy not found")
if scipy.__version__ < minimum_scipy_version:
print("*Error*: Scipy version is lower than needed: %s < %s" %
(scipy.__version__, minimum_scipy_version))
sys.exit(1)
try:
import matplotlib
except:
raise RuntimeError("matplotlib not found")
if matplotlib.__version__ < minimum_matplotlib_version:
print("*Error*: matplotlib version is lower than needed: %s < %s" %
(matplotlib.__version__, minimum_matplotlib_version))
sys.exit(1)
try:
import pyfits
except:
raise RuntimeError("PyFITS not found")
if pyfits.__version__ < minimum_pyfits_version:
print("*Error*: PyFITS version is lower than needed: %s < %s" %
(pyfits.__version__, minimum_pyfits_version))
sys.exit(1)
try:
if sysplatform == 'darwin' or 'linux2':
import wx
else:
""" (assuming in this case that sysplatform == 'win32' """
import wxPython
except:
raise RuntimeError("wxPython not found")
if wx.__version__ < minimum_wxpython_version:
print("*Error*: wxPython version is lower than needed: %s < %s" %
(wx.__version__, minimum_wxpython_version))
sys.exit(1)
else:
from setuptools import setup
# Walk through the subdirs and add all non-python scripts to MANIFEST.in
def create_manifest():
print 'creating manifest.in'
matches = []
for root, dirnames, filenames in os.walk('oscaar'):
if ('.git' in str(root)) == False:
for filename in filenames:
if filename.endswith(('.py', '.pyc')) == False:
matches.append(os.path.join(root, filename))
for root, dirnames, filenames in os.walk('docs'):
if ('.git' in str(root)) == False:
for filename in filenames:
if filename.endswith(('.py', '.pyc')) == False:
matches.append(os.path.join(root, filename))
# Manually add extra files from the top-level directory
matches.append(os.path.join(os.path.dirname(__file__),'post_setup.py'))
matches.append(os.path.join(os.path.dirname(__file__),'INSTALL.txt'))
matches.append(os.path.join(os.path.dirname(__file__),'LICENSE.txt'))
with open('MANIFEST.in', 'w') as f:
f.writelines(("include %s\n" % l.replace(' ','?') for l in matches))
# To remove the manifest file after installation
def delete_manifest():
if os.path.exists('MANIFEST.in'):
os.remove('MANIFEST.in')
# Create list for Python scripts directories to include
def get_packages():
print 'searching for packages'
matches = []
for root, dirnames, filenames in os.walk('oscaar'):
if ('.git' in str(root)) == False:
for filename in filenames:
if filename.endswith(('.py', '.pyc')) == True:
matches.append(root)
matches = list(set(matches))
return matches
def del_dir(dirname):
if os.path.exists(dirname):
shutil.rmtree(dirname)
# The setup configuration for installing OSCAAR
def setup_package():
create_manifest()
list = ['Numpy>=1.6','Scipy>=0.1','pyfits>=3.1','pyephem>=3.7',\
'matplotlib>=1.2.1']
setup(
name = "OSCAAR",
version = "2.0beta",
author = "Core Developer: <NAME>. Contributors: "+\
"<NAME>, <NAME>, <NAME>",
author_email = "<EMAIL>",
description = ("oscaar is an open source project aimed at "+\
"helping you begin to study transiting extrasolar "+\
"planets with differential photometry."),
license = 'LICENSE.txt',
keywords = "oscaar transit astronomy photometry exoplanets",
url = "https://github.com/OSCAAR/OSCAAR/wiki",
packages=get_packages(),
include_package_data = True,
zip_safe = False,
long_description=open(os.path.join(os.path.dirname(\
os.path.abspath(__file__)),'README')).read(),
download_url='https://github.com/OSCAAR/OSCAAR/archive/master.zip',
install_requires=list,
dependency_links = ['https://downloads.sourceforge.net/project/'+\
'matplotlib/matplotlib/matplotlib-1.2.1/'+\
'matplotlib-1.2.1.tar.gz'],
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: MIT License',
'Operating System :: OS Independent',
'Programming Language :: Python :: 2.7',
'Programming Language :: C',
'Topic :: Scientific/Engineering :: Astronomy',
'Topic :: Scientific/Engineering :: Physics'
],
)
# At exit delete temporary files, and run post setup script if
# argument is 'install'
def to_do_at_exit():
delete_manifest()
#del_dir('build')
#del_dir('OSCAAR.egg-info')
if 'install' in sys.argv:
del_dir('dist')
'Installation finished. Starting DS9 downloader and compile C\n'
subprocess.check_call(['python', 'post_setup.py',sys.argv[-1]])
#Set function to be executed at exit of code (when script is finished)
atexit.register(to_do_at_exit)
if __name__ == '__main__':
setup_package() | [
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users/forms.py | iurykrieger96/alura-django | 0 | 9155 | <filename>users/forms.py
from django import forms
from django.contrib.auth.models import User
from django.forms.utils import ErrorList
class UserForm(forms.Form):
name = forms.CharField(required=True)
email = forms.EmailField(required=True)
password = forms.CharField(required=True)
phone = forms.CharField(required=True)
name_company = forms.CharField(required=True)
def is_valid(self):
valid = True
if not super(UserForm, self).is_valid():
self.add_erro('Por favor, verifique os dados informados')
valid = False
user_exists = User.objects.filter(username=self.data['name']).exists()
if user_exists:
self.add_erro('Usuario ja existente')
valid = False
return valid
def add_erro(self, message):
self._errors.setdefault(forms.forms.NON_FIELD_ERRORS, ErrorList()).append(message)
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beansdbadmin/core/client.py | ariesdevil/beansdbadmin | 11 | 400 | <filename>beansdbadmin/core/client.py
#!/usr/bin/python
# encoding: utf-8
'''a rich client
1. for one server (instead of multi like in libmc.Client)
2. encapsulate @, ?, gc ...
use is instead of libmc.Client
'''
import telnetlib
import logging
import libmc
import string
import urllib
import itertools
import warnings
from collections import defaultdict
from beansdbadmin.core.hint import parse_new_hint_body
from beansdbadmin.core.data import parse_records
from beansdbadmin.core.hash import get_khash64
def get_url_content(url):
return urllib.urlopen(url).read()
def check_bucket(bucket):
assert 0 <= bucket < 16
def dir_to_dict(dir_str):
d = dict()
if dir_str:
for line in [x for x in dir_str.split('\n') if x]:
key_or_bucket, _hash, ver_or_count = line.split(' ')
d[key_or_bucket] = int(_hash) & 0xffff, int(ver_or_count)
return d
def get_bucket_keys_count(store, bucket, depth=1):
cmd = "@"
sub = bucket
if depth == 2:
cmd = "@%x" % (bucket/16)
sub = bucket % 16
result = store.get(cmd)
if result:
lines = result.split('\n')
for line in lines:
if len(line) == 0:
continue
d, _, c = line.split()
if d.endswith('/'):
bucket_ = int(d[0], 16)
if bucket_ == sub:
return int(c)
raise Exception('get %s from %s, reply = [%s], bucket %x not found' % (cmd, store, result, bucket))
def get_buckets_keys_count(store):
""" return dict: buckets -> count """
st = {}
try:
for line in (store.get('@') or '').split('\n'):
if line:
d, _, c = line.split(' ')
if not d.endswith('/'):
continue
st[int(d[0], 16)] = int(c)
return st
except IOError:
raise Exception("cannot get @ from %s" % (store))
def get_primary_buckets(store):
""" return possible primary buckets, might be wrong on temporary nodes,
result is list of buckets in integer
"""
ss = get_buckets_keys_count(store)
bucket_list = ss.items()
bucket_list = [x for x in bucket_list if x[1] > 0]
if not bucket_list:
return None
bucket_list.sort(lambda a, b: cmp(a[1], b[1]), reverse=True)
result = [bucket_list[0]]
for i in bucket_list[1:]:
if result[-1][1] / i[1] >= 2:
break
result.append(i)
return [x[0] for x in result]
def get_key_info_disk(store, key):
'''return ver, vhash, flag, vsz, ts, fid, pos'''
info = store.get('??' + key)
if info:
return [int(x) for x in info.split()]
def is_gc_running(ip, port):
s = get_gc_status(ip, port)
if s and s.find('running') >= 0:
return True
return False
def get_gc_status(ip, port):
t = telnetlib.Telnet(ip, port)
t.write('optimize_stat\r\n')
out = t.read_until('\n')
t.write('quit\r\n')
t.close()
return out.strip("\r\n")
def connect(server, **kwargs):
comp_threshold = kwargs.pop('comp_threshold', 0)
prefix = kwargs.pop('prefix', None)
if prefix is not None:
warnings.warn('"prefix" is deprecated. '
'use douban.wrapper.Prefix instead.')
c = libmc.Client([server],
do_split=0,
comp_threshold=comp_threshold,
prefix=prefix)
c.config(libmc.MC_CONNECT_TIMEOUT, 300) # 0.3s
c.config(libmc.MC_POLL_TIMEOUT, 3000) # 3s
c.config(libmc.MC_RETRY_TIMEOUT, 5) # 5s
return c
class MCStore(object):
IGNORED_LIBMC_RET = frozenset([
libmc.MC_RETURN_OK,
libmc.MC_RETURN_INVALID_KEY_ERR
])
def __init__(self, addr):
self.addr = addr
self.host, port = addr.split(":")
self.port = int(port)
self.mc = connect(addr)
def __repr__(self):
return '<MCStore(addr=%s)>' % repr(self.addr)
def __str__(self):
return self.addr
def set(self, key, data, rev=0):
return bool(self.mc.set(key, data, rev))
def set_raw(self, key, data, rev=0, flag=0):
if rev < 0:
raise Exception(str(rev))
return self.mc.set_raw(key, data, rev, flag)
def set_multi(self, values, return_failure=False):
return self.mc.set_multi(values, return_failure=return_failure)
def _check_last_error(self):
last_err = self.mc.get_last_error()
if last_err not in self.IGNORED_LIBMC_RET:
raise IOError(last_err, self.mc.get_last_strerror())
def get(self, key):
try:
r = self.mc.get(key)
if r is None:
self._check_last_error()
return r
except ValueError:
self.mc.delete(key)
def get_raw(self, key):
r, flag = self.mc.get_raw(key)
if r is None:
self._check_last_error()
return r, flag
def get_multi(self, keys):
r = self.mc.get_multi(keys)
self._check_last_error()
return r
def delete(self, key):
return bool(self.mc.delete(key))
def delete_multi(self, keys, return_failure=False):
return self.mc.delete_multi(keys, return_failure=return_failure)
def exists(self, key):
return bool(self.mc.get('?' + key))
def incr(self, key, value):
return self.mc.incr(key, int(value))
class DBClient(MCStore):
def __init__(self, addr):
MCStore.__init__(self, addr)
self._is_old = None
def stats(self):
stats = self.mc.stats()
return stats.values()[0] if stats else None
def is_old(self):
if self._is_old is None:
ver = self.get_server_version()
self._is_old = (ver.strip().split(".")[0] == "0")
return self._is_old
def get_collision_summary(self, bucket):
check_bucket(bucket)
raw = self.get("@collision_%x" % bucket)
if raw is None:
return None
count, hcount, khash, data_size = raw.split()
return (int(count), int(hcount), int(khash, 16), int(data_size))
def get_collision(self, bucket):
check_bucket(bucket)
collisions = defaultdict(dict)
hint_data = self.get("@collision_all_%x" % bucket)
if hint_data is None:
return dict()
for key, meta, _ in parse_new_hint_body(hint_data):
khash_str, _, ver, vhash = meta
collisions[khash_str][key] = (vhash, ver)
return dict(collisions)
def get_records_by_khash_raw(self, khash):
if self.is_old():
return []
if not isinstance(khash, str):
khash = "%016x" % khash
return self.get("@@" + khash)
def get_records_by_khash(self, khash_str):
raw = self.get_records_by_khash_raw(khash_str)
if raw:
return parse_records(raw, False)
else:
return []
def start_gc(self, bucket='', start_fid=0, end_fid=None):
""" bucket must be in 0 or 00 string """
if bucket:
assert isinstance(bucket, basestring) and len(bucket) <= 2
t = telnetlib.Telnet(self.host, self.port)
tree = '@%s' % bucket
if end_fid is None:
gc_cmd = 'gc {} {}\n'.format(tree, start_fid)
else:
gc_cmd = 'gc {} {} {}\n'.format(tree, start_fid, end_fid)
t.write(gc_cmd)
out = t.read_until('\n').strip('\r\n')
assert out == 'OK'
t.write('quit\n')
t.close()
def start_gc_all_buckets(self, db_depth):
hex_digits = string.digits + 'abcdef'
buckets_iter = itertools.product(*[hex_digits for _ in range(db_depth)])
buckets = [''.join(i) for i in buckets_iter]
self.start_gc_buckets(buckets)
def start_gc_buckets(self, buckets):
for b in buckets:
self.start_gc(bucket=b)
while True:
status = self.get_gc_status()
if status.find('running') >= 0:
continue
elif status == 'success':
print "bucket %s gc done" % b
break
elif status == 'fail':
return self.fail("optimize_stat = fail")
else:
self.fail(status)
def get_gc_status(self):
return get_gc_status(self.host, self.port)
def get_version(self, key):
meta = self.get("?" + key)
if meta:
return int(meta.split()[0])
def item_count(self):
s = self.stats()
if s is None:
return None
return int(s['total_items'])
def get_key_info_mem(self, key, khash64=None):
''' return (vhash, ver) or None'''
if khash64 is None:
khash64 = get_khash64(key)
khash32_str = "@%08x" % (khash64 >> 32)
_dir = self.get_dir(khash32_str)
if self.is_old():
return _dir.get(key, None)
else:
return _dir.get("%016x" % khash64, None)
def get_khash_info_mem(self, khash):
''' return [(key, (vhash, ver))], key is "" for v2.'''
khash32 = "@%08x" % (khash >> 32)
_dir = self.get_dir(khash32)
ret = []
if self.is_old():
for k, (vhash, ver) in _dir.iteritems():
if get_khash64(k) == khash:
ret.append((k, (vhash, ver)))
else:
for k, (vhash, ver) in _dir.iteritems():
if int(k, 16) == khash:
return [("", (int(vhash), ver))]
return ret
def get_server_version(self):
try:
st = self.stats()
if st:
return st["version"]
except IOError:
logging.error("fail to get version %s", self)
except KeyError:
logging.error("fail to get version %s %s", self, st)
def get_dir(self, path):
''' return dict
case1: map dir(0-f) to (hash, count),
like {'0/': (1471, 27784005), ... },
case2: map key(or khash) to (vhash, version),
like {'3000000377e9c2ad': (22212, 1), ... }'''
try:
content = self.get(path)
except IOError:
content = ''
return dir_to_dict(content)
def list_dir(self, d): # FIXME: d should not need prefix @?
'''list all KEY in the dir!
not use it if dir is large!'''
for path, (vhash, ver) in sorted(self.get_dir(d).items()):
if path.endswith('/') and len(path) == 2:
for v in self.list_dir(d + path[:-1]):
yield v
else:
yield path, int(vhash), int(ver)
def get_bucket_keys_count(self, bucket, depth=1):
return get_bucket_keys_count(self, bucket, depth)
def get_key_info_disk(self, key):
'''return ver, vhash, flag, vsz, ts, fid, pos'''
return get_key_info_disk(self, key)
def prepare(self, data):
return libmc.encode_value(data, self.mc.comp_threshold)
def close(self):
pass
def test_new(addr, bucket):
b = bucket
c = DBClient(addr)
print "stats:", c.stats()
print 'version:', c.get_server_version()
print "isold:", c.is_old()
print "dir root:", c.get_dir("@")
print "bucket key count:", c.get_bucket_keys_count(int(b))
print "item_count:", c.item_count()
print "primary_buckets", get_primary_buckets(c)
leaf = c.get_dir("@" + b + "000000")
print "a dir leaf:", leaf
khash_str = list(leaf)[0]
print "a khash_str", khash_str
r = c.get_records_by_khash(khash_str)[0]
k = r[0]
print "key, len(value), (flag, tstamp, ver):", k, r[1], r[3:]
print "key info mem:", c.get_key_info_mem(k)
print "key info disk(ver, vhash, flag, vsz, ts, fid, pos):", \
c.get_key_info_disk(k)
print "key version:", c.get_version(k)
print "collision_summary", c.get_collision_summary(int(b))
print "gc status:", c.get_gc_status()
if __name__ == '__main__':
test_new("rosa3a:7900", '3')
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get_pos.py | zhuchong79/cok | 0 | 169136 | import cv2
import aircv as ac
import os
from cok_tool import click,snap,back
# print circle_center_pos
def draw_circle(img, pos, circle_radius, color, line_width):
cv2.circle(img, pos, circle_radius, color, line_width)
cv2.imshow('objDetect', imsrc)
cv2.waitKey(0)
cv2.destroyAllWindows()
def hero(pic='',devices=''):
if pic == '':
src_pic=snap(device,0)
else :
src_pic=pic
imsrc = ac.imread(src_pic)
imobj = ac.imread('base.jpg')
# find the match position
pos = ac.find_template(imsrc, imobj)
print pos['result']
click(pos['result'][0],pos['result'][1],0,devices)
click(530,1550,0,devices) #start fight
click(865,1810,8,devices) #fighting
back(devices)
#os.system("del %s"%src_pic)
def getbox(pic='',device=''):
if pic == '':
src_pic=snap(device,0)
else :
src_pic=pic
imsrc = ac.imread(src_pic)
imobj = ac.imread('box.jpg')
# find the match position
pos = ac.find_template(imsrc, imobj)
print pos['result']
click(pos['result'][0],pos['result'][1],2,device)
click(530,1515,2,device)
if __name__ == "__main__":
mi6='1f33ee18'
#getbox("127.0.0.1:62028")
pic=snap("127.0.0.1:62028",0)
hero(pic,"127.0.0.1:62028")
getbox(pic,"127.0.0.1:62028")
exit(0)
for i in xrange(3):
hero("127.0.0.1:62028")
#exit(0)
# circle_center_pos = pos['result']
# circle_radius = 50
# color = (0, 255, 0)
# line_width = 10
# draw circle
# draw_circle(imsrc, circle_center_pos, circle_radius, color, line_width) | [
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judge/submission/migrations/0001_initial.py | 22shubh22/online-judge | 0 | 159627 | # Generated by Django 3.1.1 on 2021-12-26 10:44
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
('question', '0005_auto_20211226_1036'),
]
operations = [
migrations.CreateModel(
name='Submission',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('code_file', models.FilePathField(path='code')),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('status', models.CharField(choices=[('TLE', 'TLE'), ('WA', 'WA'), ('AC', 'AC'), ('procesing', 'processing'), ('queue', 'queue')], max_length=20)),
('question', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='submission', to='question.question')),
],
options={
'verbose_name': 'Submission',
'verbose_name_plural': 'Submissions',
},
),
migrations.CreateModel(
name='SubmissionTest',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('output_file', models.FilePathField(path='submission_test', unique=True)),
('submission', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='submission_test', to='submission.submission')),
('test', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='submission_test', to='question.test')),
],
options={
'verbose_name': 'Submission Test',
'verbose_name_plural': 'Submission Tests',
},
),
]
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] |
bioplotlib/collections.py | darcyabjones/bioplotlib | 0 | 53782 | <reponame>darcyabjones/bioplotlib
""" Extension of matplotlib collections.
Classes for the efficient drawing of large collections of objects that
share most properties, e.g., a large number of line segments or
polygons.
The classes are not meant to be as flexible as their single element
counterparts (e.g., you may not be able to select all line styles) but
they are meant to be fast for common use cases (e.g., a large set of solid
line segemnts)
"""
############################ Import all modules ##############################
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from copy import copy
from collections import defaultdict
import numpy as np
import matplotlib.transforms as transforms
from matplotlib.path import Path
from matplotlib.patches import PathPatch
from matplotlib.patches import Patch
from matplotlib.collections import Collection
import bioplotlib.feature_shapes
from bioplotlib.feature_shapes import Triangle
from bioplotlib.feature_shapes import OpenTriangle
__contributors = [
"<NAME> <<EMAIL>>"
]
def new_shape(c, **kwargs):
""" . """
def callable(*a, **k):
kwargs.update(k)
return c(*a, **kwargs)
return callable
################################## Classes ###################################
class Feature(Collection):
""" Groups shapes into features so that they stay together
in stacked tracks. """
def __init__(
self,
blocks,
shape=new_shape(Triangle),
between_shape=None,
strand=None,
offset=0,
by_axis=None,
name=None,
**kwargs
):
if type(shape) in (tuple, list):
self._shape = shape
else:
self._shape = [shape]
if type(between_shape) in (tuple, list, type(None)):
self._between_shape = between_shape
else:
self._between_shape = [between_shape]
self._blocks = blocks
self._strand = strand
self._offset = offset
self._by_axis = by_axis
self._name = name
self._paths = None
self._patches = None
Collection.__init__(self, **kwargs)
self._draw_patches()
return
@property
def blocks(self):
return self._blocks
@blocks.setter
def blocks(self, blocks):
self._blocks = blocks
@property
def strand(self):
return self._strand
@strand.setter
def strand(self, strand):
self._strand = strand
for patch in self.patches:
if patch.strand is not None:
patch.strand = strand
@property
def offset(self):
return self._offset
@offset.setter
def offset(self, offset):
self._offset = offset
if offset != 0:
for patch in self.patches:
patch.offset += offset
@property
def by_axis(self):
return self._by_axis
@by_axis.setter
def by_axis(self, by_axis):
self._by_axis = by_axis
if by_axis is not None:
for patch in self.patches:
if patch.by_axis is not None:
patch.by_axis = by_axis
@property
def shape(self):
return self._shape
@shape.setter
def shape(self, shape):
self._shape = shape
self._draw_patches()
@property
def between_shape(self):
return self._between_shape
@between_shape.setter
def between_shape(self, shape):
self._between_shape = shape
self._draw_patches()
@property
def patches(self):
return self._patches
@patches.setter
def patches(self, patches):
self._patches = patches
self._set_paths()
self._set_props()
return
@property
def paths(self):
return self._paths
@paths.setter
def paths(self, paths):
self._paths = paths
return
def get_paths(self):
""" alias for paths property """
return self.paths
def set_paths(self, paths):
""" alias for paths.setter """
self.paths = paths
return
def _set_paths(self):
self.paths = [
p.get_transform().transform_path(p.get_path())
for p in self.patches
]
return
def _set_props(self):
def determine_facecolor(patch):
if patch.get_fill():
return patch.get_facecolor()
return [0, 0, 0, 0]
props = defaultdict(list)
valid = {
"facecolors": (self.set_facecolor, determine_facecolor),
"edgecolors": (self.set_edgecolor, Patch.get_edgecolor),
"linewidths": (self.set_linewidth, Patch.get_linewidth),
"linestyles": (self.set_linestyle, Patch.get_linestyle),
"antialiaseds": (self.set_antialiased, Patch.get_antialiased),
}
for p in self.patches:
for key, (set_, get) in valid.items():
props[key].append(get(p))
for key, (set_, get) in valid.items():
set_(props[key])
return
def _draw_patches(self):
start = 0
end = None
patches = list()
length_blocks = len(self.blocks)
# Draw the between shapes first
between_shape_pos = 0
between_blocks = []
if self.between_shape is not None:
between_blocks = list(zip(
range(0, length_blocks - 1),
range(1, length_blocks)
))
length_between_blocks = len(between_blocks)
# Note that if between shape is none there is nothing to iterate over.
for h, (i, j) in enumerate(between_blocks):
first = self.blocks[i]
second = self.blocks[j]
min_dist = min([(0, 0), (0, 1), (1, 0), (1, 1)],
key=lambda t: abs(second[t[0]] - first[t[1]])
)
start = first[min_dist[1]]
end = second[min_dist[0]]
strand_first = None
strand_second = None
try:
strand_first = first[2]
strand_second = second[2]
except:
pass
if strand_first == strand_second:
strand = strand_first
else:
strand = None
if len(self.between_shape) > 1 and h + 1 == length_between_blocks:
between_shape_pos = -1
patches.append(self.between_shape[between_shape_pos](
start=start,
end=end,
strand=None
))
if len(self.between_shape) > 2:
between_shape_pos = 1
# Now do the blocks
shape_pos = 0
for i, block in enumerate(self.blocks):
if len(self.shape) > 1 and i + 1 == length_blocks:
shape_pos = -1
start = block[0]
end = block[1]
strand = None
try:
strand = block[2]
except:
pass
patches.append(self.shape[shape_pos](
start=start,
end=end,
strand=strand
))
if len(self.shape) > 2:
shape_pos = 1
if self.offset != 0:
for patch in patches:
patch.offset += self.offset
self._patches = patches
self._set_paths()
self._set_props()
return
class FeatureGroup(Collection):
""" Generic collection for genomic tracks.
Methods
-------
stack
Determines how to stack features in a track
"""
def __init__(
self,
features,
width=1,
offset=0,
stack=None,
by_axis=None,
name=None,
**kwargs
):
""" . """
self._features = features
self._width = width
self._stack = stack
self._by_axis = by_axis
self._offset = offset
self.name = name
self._patches = None
self._paths = None
Collection.__init__(self, **kwargs)
self._draw_patches()
return
@property
def features(self):
return self._features
@features.setter
def features(self, features):
""" . """
self._features = features
self._draw_patches()
return
@property
def offset(self):
return self._offset
@offset.setter
def offset(self, offset):
self._offset = offset
self._draw_patches()
return
@property
def by_axis(self):
return self._by_axis
@by_axis.setter
def by_axis(self, by_axis):
self._by_axis = by_axis
if by_axis is not None:
for patch in self.patches:
if patch.by_axis is not None:
patch.by_axis = by_axis
return
@property
def paths(self):
return self._paths
@paths.setter
def paths(self, paths):
self._paths = paths
return
def get_paths(self):
""" alias for paths property """
return self.paths
def set_paths(self, paths):
""" alias for paths.setter """
self.paths = paths
return
def _set_paths(self):
self.paths = [
p.get_transform().transform_path(p.get_path())
for p in self._patches
]
return
def _set_props(self):
def determine_facecolor(patch):
if patch.get_fill():
return patch.get_facecolor()
return [0, 0, 0, 0]
props = defaultdict(list)
valid = {
"facecolors": (self.set_facecolor, determine_facecolor),
"edgecolors": (self.set_edgecolor, Patch.get_edgecolor),
"linewidths": (self.set_linewidth, Patch.get_linewidth),
"linestyles": (self.set_linestyle, Patch.get_linestyle),
"antialiaseds": (self.set_antialiased, Patch.get_antialiased),
}
for p in self._patches:
for key, (set_, get) in valid.items():
props[key].append(get(p))
for key, (set_, get) in valid.items():
set_(props[key])
return
def _draw_patches(self):
""" . """
patches = list()
for feature in self.features:
if self._offset != 0:
feature.offset = self._offset
if isinstance(feature, Patch):
patches.append(feature)
elif isinstance(feature, Feature):
patches.extend(feature.patches)
elif isinstance(feature, FeatureGroup):
patches.extend(feature.patches)
else:
pass
self._patches = patches
return
class LinkCollection(object):
""" . """
def __init__(
self,
obj,
links=list(),
add_to_fig=False,
by=None
):
""" . """
self.links = list()
self.links.extend(links)
self.obj = obj
self.add_to_fig = add_to_fig
self.by = by
lobj = obj()
self.figure = lobj.figure
return
def add(self, blocks, by=None, **kwargs):
"""
Keyword arguments:
blocks -- a 2, 3, or 4 dimensional array
2 dimensions: [[ax1_x1, ax1_x2], [ax2_x1, ax1_x2]] # single record
3 dimensions:
[
[[ax1_x1, ax1_x2], [ax2_x1, ax2_x2]],
[[ax1_x1, ax1_x2], [ax2_x1, ax2_x2]],
...
]
4 dimensions:
[
[
[[ax1_x1, ax1_x2], [ax1_y1, ax1_y2]],
[[ax2_x1, ax2_x2], [ax2_y1, ax2_y2]],
],
[
[[ax1_x1, ax1_x2], [ax1_y1, ax1_y2]],
[[ax2_x1, ax2_x2], [ax2_y1, ax2_y2]],
],
...
]
"""
by = self.by if by is None else by
obj = self.obj
if len(blocks) == 0:
return list()
blocks = np.array(blocks)
if len(blocks.shape) == 2:
if by == 'x' or self.by is None:
pblocks = np.array([
[[ax_xrange, None] for ax_xrange in blocks]
])
elif by == 'y':
pblocks = np.array([
[[None, ax_yrange] for ax_yrange in blocks]
])
elif len(blocks.shape) == 3:
if by == 'x' or self.by is None:
pblocks = np.array([
[[ax1_xrange, None],
[ax2_xrange, None]]
for ax1_xrange, ax2_xrange in blocks
])
elif by == 'y':
pblocks = np.array([
[[None, ax1_yrange],
[None, ax2_yrange]]
for ax1_yrange, ax2_yrange in blocks
])
else:
pblocks = blocks
new_links = list()
for block in pblocks:
((ax1_xrange, ax1_yrange), (ax2_xrange, ax2_yrange)) = block
params = dict() #copy(kwargs)
params['by'] = by
params['ax1_xrange'] = ax1_xrange
params['ax1_yrange'] = ax1_yrange
params['ax2_xrange'] = ax2_xrange
params['ax2_yrange'] = ax2_yrange
params = {k:v for k, v in params.items() if v is not None}
lobj = obj()
lobj.__dict__.update(params)
lobj.properties.update(kwargs)
self.links.append(lobj)
new_links.append(lobj)
return new_links
def __call__(self):
return self.draw()
def draw(self):
""" . """
patches = list()
for link in self.links:
if not link.in_limits():
continue
path = link.draw()
link_patch = PathPatch(
path,
transform=self.figure.transFigure,
**link.properties
)
rax = link.ax1
qax = link.ax2
patches.append(link_patch)
if self.add_to_fig:
self.figure.patches.extend(patches)
return patches
################################# Functions ##################################
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tests/functional_pyecore/test_processors_pyecore.py | aranega/textX | 4 | 162359 | """
Testing model and object processors.
"""
import pytest # noqa
import sys
pytestmark = pytest.mark.skipif(sys.version_info[0] < 3,
reason="pyecore is not Python 2 compatible") # noqa
pyecore = pytest.importorskip("pyecore") # noqa
import textx
from textx import metamodel_from_str
@pytest.fixture(scope="module")
def enable_pyecore_support():
textx.enable_pyecore_support()
yield
textx.enable_pyecore_support(enable=False)
pytestmark = pytest.mark.usefixtures("enable_pyecore_support")
grammar = """
First:
'first' seconds+=Second
('A' a+=INT)?
('B' b=BOOL)?
('C' c=STRING)?
;
Second:
sec = INT
;
"""
model_processor_called = False
def test_model_processor():
"""
Test that model processors are called after model parsing.
"""
global model_processor_called
model_str = 'first 34 45 7 A 45 65 B true C "dfdf"'
metamodel = metamodel_from_str(grammar)
metamodel.register_model_processor(model_processor)
metamodel.model_from_str(model_str)
assert model_processor_called
def model_processor(model, metamodel):
"""
Model processor is called when the model is successfully parsed.
"""
global model_processor_called
model_processor_called = True
assert model.__class__.__name__ == "First"
assert model.seconds[0].sec == 34
def test_object_processors():
"""
Test that object processors are called.
They should be called after each model object construction.
"""
call_order = []
def first_obj_processor(first):
first._first_called = True
call_order.append(1)
def second_obj_processor(second):
second._second_called = True
call_order.append(2)
# test that parent is fully initialised.
# b should be True
assert second.parent.b
obj_processors = {
'First': first_obj_processor,
'Second': second_obj_processor,
}
metamodel = metamodel_from_str(grammar)
metamodel.register_obj_processors(obj_processors)
model_str = 'first 34 45 7 A 45 65 B true C "dfdf"'
first = metamodel.model_from_str(model_str)
assert hasattr(first, '_first_called')
for s in first.seconds:
assert hasattr(s, '_second_called')
assert call_order == [2, 2, 2, 1]
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] |
leetcode/hard/145. Binary Tree Postorder Traversal.py | Jeongseo21/Algorithm-1 | 7 | 63047 | # problem : https://leetcode.com/problems/binary-tree-postorder-traversal/
# time complexity : O(N)
# data structure : stack
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
def postorderTraversal(self, root: TreeNode) -> List[int]:
ans = []
s = [(root, 0)]
while len(s) > 0:
node, appearCnt = s.pop()
if node is None:
continue
if appearCnt == 0:
s.append((node, 1))
s.append((node.right, 0))
s.append((node.left, 0))
else:
ans.append(node.val)
return ans
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plugins/modules/network_device.py | steinzi/ansible-ise | 0 | 71213 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright (c) 2021, Cisco Systems
# GNU General Public License v3.0+ (see LICENSE or https://www.gnu.org/licenses/gpl-3.0.txt)
DOCUMENTATION = r"""
---
module: network_device
short_description: Resource module for Network Device
description:
- Manage operations create, update and delete of the resource Network Device.
version_added: '1.0.0'
author: <NAME> (@racampos)
options:
NetworkDeviceGroupList:
description: List of Network Device Group names for this node.
elements: str
type: list
NetworkDeviceIPList:
description: List of IP Subnets for this node.
suboptions:
getIpaddressExclude:
description: It can be either single IP address or IP range address.
type: str
ipaddress:
description: Network Device's ipaddress.
type: str
mask:
description: Network Device's mask.
type: int
type: list
authenticationSettings:
description: Network Device's authenticationSettings.
suboptions:
dtlsRequired:
description: This value enforces use of dtls.
type: bool
enableKeyWrap:
description: EnableKeyWrap flag.
type: bool
enableMultiSecret:
description: EnableMultiSecret flag.
type: bool
enabled:
description: Enabled flag.
type: bool
keyEncryptionKey:
description: Network Device's keyEncryptionKey.
type: str
keyInputFormat:
description: Allowed values - ASCII, - HEXADECIMAL.
type: str
messageAuthenticatorCodeKey:
description: Network Device's messageAuthenticatorCodeKey.
type: str
networkProtocol:
description: Allowed values - RADIUS, - TACACS_PLUS.
type: str
radiusSharedSecret:
description: Network Device's radiusSharedSecret.
type: str
secondRadiusSharedSecret:
description: Network Device's secondRadiusSharedSecret.
type: str
type: dict
coaPort:
description: Network Device's coaPort.
type: int
description:
description: Network Device's description.
type: str
dtlsDnsName:
description: This value is used to verify the client identity contained in the X.509
RADIUS/DTLS client certificate.
type: str
id:
description: Network Device's id.
type: str
modelName:
description: Network Device's modelName.
type: str
name:
description: Network Device's name.
type: str
profileName:
description: Network Device's profileName.
type: str
snmpsettings:
description: Network Device's snmpsettings.
suboptions:
linkTrapQuery:
description: LinkTrapQuery flag.
type: bool
macTrapQuery:
description: MacTrapQuery flag.
type: bool
originatingPolicyServicesNode:
description: Network Device's originatingPolicyServicesNode.
type: str
pollingInterval:
description: Network Device's pollingInterval.
type: int
roCommunity:
description: Network Device's roCommunity.
type: str
version:
description: Network Device's version.
type: str
type: dict
softwareVersion:
description: Network Device's softwareVersion.
type: str
tacacsSettings:
description: Network Device's tacacsSettings.
suboptions:
connectModeOptions:
description: Allowed values - OFF, - ON_LEGACY, - ON_DRAFT_COMPLIANT.
type: str
sharedSecret:
description: Network Device's sharedSecret.
type: str
type: dict
trustsecsettings:
description: Network Device's trustsecsettings.
suboptions:
deviceAuthenticationSettings:
description: Network Device's deviceAuthenticationSettings.
suboptions:
sgaDeviceId:
description: Network Device's sgaDeviceId.
type: str
sgaDevicePassword:
description: Network Device's sgaDevicePassword.
type: str
type: dict
deviceConfigurationDeployment:
description: Network Device's deviceConfigurationDeployment.
suboptions:
enableModePassword:
description: Network Device's enableModePassword.
type: str
execModePassword:
description: Network Device's execModePassword.
type: str
execModeUsername:
description: Network Device's execModeUsername.
type: str
includeWhenDeployingSGTUpdates:
description: IncludeWhenDeployingSGTUpdates flag.
type: bool
type: dict
pushIdSupport:
description: PushIdSupport flag.
type: bool
sgaNotificationAndUpdates:
description: Network Device's sgaNotificationAndUpdates.
suboptions:
coaSourceHost:
description: Network Device's coaSourceHost.
type: str
downlaodEnvironmentDataEveryXSeconds:
description: Network Device's downlaodEnvironmentDataEveryXSeconds.
type: int
downlaodPeerAuthorizationPolicyEveryXSeconds:
description: Network Device's downlaodPeerAuthorizationPolicyEveryXSeconds.
type: int
downloadSGACLListsEveryXSeconds:
description: Network Device's downloadSGACLListsEveryXSeconds.
type: int
otherSGADevicesToTrustThisDevice:
description: OtherSGADevicesToTrustThisDevice flag.
type: bool
reAuthenticationEveryXSeconds:
description: Network Device's reAuthenticationEveryXSeconds.
type: int
sendConfigurationToDevice:
description: SendConfigurationToDevice flag.
type: bool
sendConfigurationToDeviceUsing:
description: Allowed values - ENABLE_USING_COA, - ENABLE_USING_CLI, - DISABLE_ALL.
type: str
type: dict
type: dict
requirements:
- ciscoisesdk
seealso:
# Reference by Internet resource
- name: Network Device reference
description: Complete reference of the Network Device object model.
link: https://ciscoisesdk.readthedocs.io/en/latest/api/api.html#v3-0-0-summary
"""
EXAMPLES = r"""
- name: Update by name
cisco.ise.network_device:
ise_hostname: "{{ise_hostname}}"
ise_username: "{{ise_username}}"
ise_password: "{{<PASSWORD>}}"
ise_verify: "{{ise_verify}}"
state: present
NetworkDeviceGroupList:
- string
NetworkDeviceIPList:
- getIpaddressExclude: string
ipaddress: string
mask: 0
authenticationSettings:
dtlsRequired: true
enableKeyWrap: true
enableMultiSecret: true
enabled: true
keyEncryptionKey: string
keyInputFormat: string
messageAuthenticatorCodeKey: string
networkProtocol: string
radiusSharedSecret: string
secondRadiusSharedSecret: string
coaPort: 0
description: string
dtlsDnsName: string
id: string
modelName: string
name: string
profileName: string
snmpsettings:
linkTrapQuery: true
macTrapQuery: true
originatingPolicyServicesNode: string
pollingInterval: 0
roCommunity: string
version: string
softwareVersion: string
tacacsSettings:
connectModeOptions: string
sharedSecret: string
trustsecsettings:
deviceAuthenticationSettings:
sgaDeviceId: string
sgaDevicePassword: string
deviceConfigurationDeployment:
enableModePassword: string
execModePassword: string
execModeUsername: string
includeWhenDeployingSGTUpdates: true
pushIdSupport: true
sgaNotificationAndUpdates:
coaSourceHost: string
downlaodEnvironmentDataEveryXSeconds: 0
downlaodPeerAuthorizationPolicyEveryXSeconds: 0
downloadSGACLListsEveryXSeconds: 0
otherSGADevicesToTrustThisDevice: true
reAuthenticationEveryXSeconds: 0
sendConfigurationToDevice: true
sendConfigurationToDeviceUsing: string
- name: Delete by name
cisco.ise.network_device:
ise_hostname: "{{ise_hostname}}"
ise_username: "{{ise_username}}"
ise_password: "{{<PASSWORD>}}"
ise_verify: "{{ise_verify}}"
state: absent
name: string
- name: Update by id
cisco.ise.network_device:
ise_hostname: "{{ise_hostname}}"
ise_username: "{{ise_username}}"
ise_password: "{{<PASSWORD>}}"
ise_verify: "{{ise_verify}}"
state: present
NetworkDeviceGroupList:
- string
NetworkDeviceIPList:
- getIpaddressExclude: string
ipaddress: string
mask: 0
authenticationSettings:
dtlsRequired: true
enableKeyWrap: true
enableMultiSecret: true
enabled: true
keyEncryptionKey: string
keyInputFormat: string
messageAuthenticatorCodeKey: string
networkProtocol: string
radiusSharedSecret: string
secondRadiusSharedSecret: string
coaPort: 0
description: string
dtlsDnsName: string
id: string
modelName: string
name: string
profileName: string
snmpsettings:
linkTrapQuery: true
macTrapQuery: true
originatingPolicyServicesNode: string
pollingInterval: 0
roCommunity: string
version: string
softwareVersion: string
tacacsSettings:
connectModeOptions: string
sharedSecret: string
trustsecsettings:
deviceAuthenticationSettings:
sgaDeviceId: string
sgaDevicePassword: string
deviceConfigurationDeployment:
enableModePassword: string
execModePassword: string
execModeUsername: string
includeWhenDeployingSGTUpdates: true
pushIdSupport: true
sgaNotificationAndUpdates:
coaSourceHost: string
downlaodEnvironmentDataEveryXSeconds: 0
downlaodPeerAuthorizationPolicyEveryXSeconds: 0
downloadSGACLListsEveryXSeconds: 0
otherSGADevicesToTrustThisDevice: true
reAuthenticationEveryXSeconds: 0
sendConfigurationToDevice: true
sendConfigurationToDeviceUsing: string
- name: Delete by id
cisco.ise.network_device:
ise_hostname: "{{ise_hostname}}"
ise_username: "{{ise_username}}"
ise_password: "{{<PASSWORD>}}"
ise_verify: "{{ise_verify}}"
state: absent
id: string
- name: Create
cisco.ise.network_device:
ise_hostname: "{{ise_hostname}}"
ise_username: "{{ise_username}}"
ise_password: "{{<PASSWORD>}}"
ise_verify: "{{ise_verify}}"
state: present
NetworkDeviceGroupList:
- string
NetworkDeviceIPList:
- getIpaddressExclude: string
ipaddress: string
mask: 0
authenticationSettings:
dtlsRequired: true
enableKeyWrap: true
enableMultiSecret: true
enabled: true
keyEncryptionKey: string
keyInputFormat: string
messageAuthenticatorCodeKey: string
networkProtocol: string
radiusSharedSecret: string
secondRadiusSharedSecret: string
coaPort: 0
description: string
dtlsDnsName: string
modelName: string
name: string
profileName: string
snmpsettings:
linkTrapQuery: true
macTrapQuery: true
originatingPolicyServicesNode: string
pollingInterval: 0
roCommunity: string
version: string
softwareVersion: string
tacacsSettings:
connectModeOptions: string
sharedSecret: string
trustsecsettings:
deviceAuthenticationSettings:
sgaDeviceId: string
sgaDevicePassword: string
deviceConfigurationDeployment:
enableModePassword: string
execModePassword: string
execModeUsername: string
includeWhenDeployingSGTUpdates: true
pushIdSupport: true
sgaNotificationAndUpdates:
coaSourceHost: string
downlaodEnvironmentDataEveryXSeconds: 0
downlaodPeerAuthorizationPolicyEveryXSeconds: 0
downloadSGACLListsEveryXSeconds: 0
otherSGADevicesToTrustThisDevice: true
reAuthenticationEveryXSeconds: 0
sendConfigurationToDevice: true
sendConfigurationToDeviceUsing: string
"""
RETURN = r"""
ise_response:
description: A dictionary or list with the response returned by the Cisco ISE Python SDK
returned: always
type: dict
sample: >
{
"UpdatedFieldsList": {
"updatedField": {
"field": "string",
"oldValue": "string",
"newValue": "string"
},
"field": "string",
"oldValue": "string",
"newValue": "string"
}
}
"""
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Tools/HTML/LIMEHTMLBuilder.py | bio-hpc/sibila | 1 | 122094 | <reponame>bio-hpc/sibila
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
LIMEHTMLBuilder.py:
Build a single HTML file with all the LIME plots.
"""
__author__ = "<NAME>"
__version__ = "1.0"
__maintainer__ = "Antonio"
__email__ = "<EMAIL>"
__status__ = "Production"
import bs4
import html
class LIMEHTMLBuilder():
def __init__(self):
self.html = '<html>\n<meta http-equiv="content-type" content="text/html; charset=utf-8">\n'
self.header_exists = False
self.body_exists = False
self.parser = None
def append(self, html, sample_id=None):
self.parser = bs4.BeautifulSoup(html, 'html.parser')
if not self.header_exists:
self.add_code('<head>' + self.get_content('head') + '</head>')
self.header_exists = True
if not self.body_exists:
self.html += '<body>'
self.body_exists = True
if sample_id is not None:
self.add_code('Sample #{}'.format(sample_id))
self.add_code(self.get_content('body'))
def add_code(self, html):
self.html += '\n' + html
def close(self):
if self.body_exists:
self.html += '\n</body>'
self.html += '\n</html>'
def get(self):
return self.html
def get_content(self, tag):
return '\n'.join(list(map(str, self.parser.find(tag).contents)))
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validated/migrations/0004_auto_20191118_1323.py | andrewbird2/validated | 0 | 1605045 | <reponame>andrewbird2/validated
# Generated by Django 2.2.7 on 2019-11-18 19:23
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('validated', '0003_auto_20191118_1245'),
]
operations = [
migrations.AlterField(
model_name='testresult',
name='message',
field=models.CharField(max_length=500),
),
migrations.AlterField(
model_name='testresult',
name='test_method',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='test_results', to='validated.TestMethod'),
),
]
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] |
utility_fun.py | Avijit20/Deep-Learning-Flower-Image-Classification-Using-PyTorch | 0 | 194200 | import numpy as np
import pandas as pd
import torch
import torchvision
import torch.nn.functional as F
from torchvision import datasets,transforms,models
import matplotlib.pyplot as plt
#from train import get_pretrained_model
from torch import nn,optim
from PIL import Image
#%matplotlib inline
def load_dataset(data_direc):
data_dir = data_direc
train_dir = data_dir + '/train'
valid_dir = data_dir + '/valid'
test_dir = data_dir + '/test'
train_transforms = transforms.Compose([transforms.RandomRotation(30),
transforms.RandomResizedCrop(224),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406],
[0.229, 0.224, 0.225])])
valid_transforms=transforms.Compose([transforms.Resize(255),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize([0.485,0.456,0.406],
[0.229,0.224,0.225])])
test_transforms = transforms.Compose([transforms.Resize(255),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406],
[0.229, 0.224, 0.225])])
train_data=datasets.ImageFolder(train_dir,transform=train_transforms)
valid_data=datasets.ImageFolder(valid_dir,transform=valid_transforms)
test_data=datasets.ImageFolder(test_dir,transform=test_transforms)
trainloader =torch.utils.data.DataLoader(train_data,batch_size=64,shuffle=True)
validloader =torch.utils.data.DataLoader(valid_data,batch_size=64)
testloader =torch.utils.data.DataLoader(test_data,batch_size=64)
return testloader,validloader,testloader,train_data
def load_checkpoint(filepath,device):
# Checkpoint for when using GPU
if torch.cuda.is_available():
map_location=lambda storage, loc: storage.cuda()
else:
map_location='cpu'
pretrained_model= 'vgg16' #get_pretrained_model()
checkpoint = torch.load(filepath, map_location=map_location)
model = getattr(models,pretrained_model)(pretrained=True)
model.classifier=checkpoint['classifier']
model.class_to_idx=checkpoint['class_to_idx']
model.load_state_dict(checkpoint['state_dict'])
#device=torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
return model
def process_image(image):
''' Scales, crops, and normalizes a PIL image for a PyTorch model,
returns an Numpy array
'''
# TODO: Process a PIL image for use in a PyTorch model
im=Image.open(image)
transform = transforms.Compose([transforms.Resize(256),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406],
[0.229, 0.224, 0.225])])
## Transforming image for use with network
trans_im = transform(im)
# Converting to Numpy array
array_im_tfd = np.array(trans_im)
return array_im_tfd
def imshow(image, ax=None, title=None):
"""Imshow for Tensor."""
if ax is None:
fig, ax = plt.subplots()
# PyTorch tensors assume the color channel is the first dimension
# but matplotlib assumes is the third dimension
#image = image.numpy().transpose((1, 2, 0))
image=image.transpose((1,2,0))
# Undo preprocessing
mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])
image = std * image + mean
# Image needs to be clipped between 0 and 1 or it looks like noise when displayed
image = np.clip(image, 0, 1)
ax.imshow(image)
return ax
def predict_im(image_path, model, topk):
''' Predict the class (or classes) of an image using a trained deep learning model.
'''
# TODO: Implement the code to predict the class from an image file
k=topk
test_img=process_image(image_path)
test_img=torch.from_numpy(test_img)
batch_img=torch.unsqueeze(test_img,0)
outputs=model(batch_img)
top_ps,top_indices = torch.topk(outputs,k)
top_ps=torch.exp(top_ps)
class_to_idx_inv={k:v for v,k in model.class_to_idx.items()}
top_ps=top_ps.view(k).tolist()
top_indices=top_indices.view(k).tolist()
final_indices=[class_to_idx_inv[x] for x in top_indices]
return top_ps,final_indices
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] |
src/linesegm.py | abhey1618/Text_Recognition | 0 | 173811 | import cv2
import os
import numpy as np
from sys import argv
from lib import sauvola, linelocalization, pathfinder
from WordSegmentation import wordSegmentation, prepareImg
from time import time as timer
from SamplePreprocessor import preprocess
from DataLoader import Batch
from Model import Model
def draw_line(im, path):
for p in path:
im[p[0], p[1]] = 0
def draw_box(im, path, prev):
curr=(path[0][1], path[0][0])
cv2.rectangle(im, prev, curr,0,3)
def draw_map(im, mapy):
for m in mapy:
im[m[0], m[1]] = 255
def print_path(path):
print('\t# path: ' + str(path[::-1]))
def save(filename, imbw, immap):
imbw_filename = str.replace(filename, '.', '_bw.')
#imbw_filename = str.replace(imbw_filename, 'data', 'data/bw')
print('Saving image "' + imbw_filename + '"..\n')
cv2.imwrite(imbw_filename, imbw)
immap_filename = str.replace(imbw_filename, '_bw', '_map')
cv2.imwrite(immap_filename, immap)
def infer(model, fnImg):
"recognize text in image provided by file path"
img = preprocess(cv2.imread(fnImg, cv2.IMREAD_GRAYSCALE), Model.imgSize)
batch = Batch(None, [img])
(recognized, probability) = model.inferBatch(batch, True)
#print('Recognized:', '"' + recognized[0] + '"')
#print('Probability:', probability[0])
return (recognized[0], probability[0])
######################
# ------ MAIN ------ #
######################
def identify_words(filepath, filenames, model):
begin = timer()
out_dict={}
out_path='../data/out/'
print('############################')
print('#Line and Word Segmentation#')
print('############################')
for filename in filenames:
fullpath=os.path.join(filepath,filename)
f=filename.split('.')[0]
ext=filename.split('.')[1]
if ext=='pdf':
continue
out_dict[f] = []
print('Reading image "' + filename + '"..')
im = cv2.imread(fullpath, 0)
print('- Thresholding image..')
#imbw = sauvola.binarize(im, [20, 20], 128, 0.3)
pxmin = np.min(im)
pxmax = np.max(im)
im = (im - pxmin) / (pxmax - pxmin) * 255
im = im.astype('uint8')
#binarize
_ , imbw = cv2.threshold(im, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
#cv2.imshow('tempb', imbw)
# increase line width
kernel = np.ones((3, 3), np.uint8)
imbw = cv2.erode(imbw, kernel, iterations = 1)
print('- Localizing lines..')
lines = linelocalization.localize(imbw)
lines.append(imbw.shape[0])
print(' => ' + str(len(lines)) + ' lines detected.')
print('- Path planning with ')
immap = np.zeros((imbw.shape), dtype=np.int32)
# for i in range(0, 1):
prev=(0,0)
n_line=1
for line in lines:
# line = lines[i]
rline = imbw[int(prev[1]):int(line),:]
img = prepareImg(rline, 50)
# execute segmentation with given parameters
# -kernelSize: size of filter kernel (odd integer)
# -sigma: standard deviation of Gaussian function used for filter kernel
# -theta: approximated width/height ratio of words, filter function is distorted by this factor
# - minArea: ignore word candidates smaller than specified area
res = wordSegmentation(img, kernelSize=25, sigma=11, theta=7, minArea=100, increase_dim=10)
# write output to 'out/inputFileName' directory
if not os.path.exists(out_path+'%s'%f):
os.mkdir(out_path+'%s'%f)
# iterate over all segmented words
#print('Segmented into %d words'%len(res))
for (j, w) in enumerate(res):
(wordBox, wordImg) = w
(x, y, w, h) = wordBox
imgloc=out_path+'%s/%d.png'%(f, j)
# increase contrast
cv2.imwrite(imgloc, wordImg) # save word
#FilePaths.fnInfer = 'out/%s/%d.png'%(f,j)
try:
result, prob = infer(model, imgloc)
except:
print("Couldn't infer: image%d"%j)
result=""
#updating output dictionary
out_dict[f].append(result)
#deleting intermediate file
##os.remove(imgloc)
cv2.rectangle(img,(x,y),(x+w,y+h),0,1) # draw bounding box in summary image
# output summary image with bounding boxes around words
cv2.imwrite(out_path+'%s/summary%d.png'%(f,n_line), img)
#path, mapy = pathfinder.search(imbw, 'A', line)
#path = [[int(line),0]]
path = [[int(line),rline.shape[1]]]
#print(rline.shape[1])
#print('path[0][0]: ',path[0][0], ' path[0][1]: ', path[0][1])
draw_box(im, path, prev)
#draw_map(immap, mapy)
prev=(0, path[0][0])
n_line+=1
# print_path(path)
#save(filename, imbw, immap)
cv2.imwrite(out_path+'%s/summary.png'%f, im)
return out_dict
print(' - Elapsed time: ' + str((timer() - begin)) + ' s') | [
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] |
beaverdet/tests/test_tube.py | SoftwareDevEngResearch/BeaverDet | 0 | 113006 | <reponame>SoftwareDevEngResearch/BeaverDet
# -*- coding: utf-8 -*-
"""
PURPOSE:
Unit tests for tools.py
CREATED BY:
<NAME>
Oregon State University
CIRE and Propulsion Lab
<EMAIL>
"""
from math import sqrt
import pytest
import pint
import os
import cantera as ct
import numpy as np
import pandas as pd
from mock import patch
from .. import tube
from .. import thermochem
ureg = pint.UnitRegistry()
quant = ureg.Quantity
def compare(manual, tested):
for key, value in manual.items():
try:
test_value = tested[key].to(value.units.format_babel()).magnitude
value = value.magnitude
except AttributeError:
test_value = tested[key]
assert abs(test_value - value) / value < 1e-4
# noinspection PyProtectedMember
class TestBolt:
thread_size = '1/4-28'
thread_class = '2'
plate_max_tensile = quant(30, 'ksi')
engagement_length = quant(0.5, 'in')
bolt_max_tensile = quant(80, 'ksi')
def test_calculate_stress_areas_over_100ksi(self):
# test bolt > 100ksi
bolt_max_tensile = quant(120, 'ksi')
hand_calc = {
'screw area': quant(0.034934049, 'in^2'),
'plate area': quant(0.308744082, 'in^2'),
'minimum engagement': quant(0.452595544, 'in')
}
test_areas = tube.Bolt.calculate_stress_areas(
self.thread_size,
self.thread_class,
bolt_max_tensile,
self.plate_max_tensile,
self.engagement_length,
ureg
)
compare(hand_calc, test_areas)
def test_calculate_stress_areas_under_100ksi(self):
# test bolt < 100ksi
bolt_max_tensile = quant(80, 'ksi')
hand_calc = {
'screw area': quant(0.036374073, 'in^2'),
'minimum engagement': quant(0.314168053, 'in')
}
test_areas = tube.Bolt.calculate_stress_areas(
self.thread_size,
self.thread_class,
bolt_max_tensile,
self.plate_max_tensile,
self.engagement_length,
ureg
)
compare(hand_calc, test_areas)
def test_calculate_stress_areas_length_too_short(self):
# ensure warning when engagement length < minimum
engagement_length = quant(0.05, 'in')
with pytest.warns(
Warning,
match='Screws fail in shear, not tension.' +
' Plate may be damaged.' +
' Consider increasing bolt engagement length'
):
tube.Bolt.calculate_stress_areas(
self.thread_size,
self.thread_class,
self.bolt_max_tensile,
self.plate_max_tensile,
engagement_length,
ureg
)
@staticmethod
def test_import_thread_specs():
# good input
test_size = '0-80'
test_type = ['external', 'internal']
test_property = 'pitch diameter max'
test_classes = [['2A', '3A'], ['2B', '3B']]
good_result = [[0.0514, 0.0519], [0.0542, 0.0536]]
specifications = tube.Bolt._import_thread_specs()
for thread, classes, expected in zip(test_type, test_classes,
good_result):
# check for correct output
current_frame = specifications[thread]
for thread_class, result in zip(classes, expected):
test_result = current_frame[test_property][test_size][
thread_class]
assert abs(test_result - result) < 1e-7
@staticmethod
def test_get_thread_property():
# good input
good_args = [
[
'pitch diameter max',
'1/4-20',
'2B',
ureg
],
[
'pitch diameter max',
'1/4-20',
'2A',
ureg
]
]
good_results = [
0.2248,
0.2164
]
for args, result in zip(good_args, good_results):
test_result = tube.Bolt.get_thread_property(*args)
assert abs(test_result.magnitude - result) < 1e-7
@staticmethod
def test_get_thread_property_not_in_dataframe():
dataframes = tube.Bolt._import_thread_specs()
# property not in dataframe
bad_property = 'jello'
bad_message = (
'Thread property \'' +
bad_property +
'\' not found. Available specs: ' +
"'" + "', '".join(dataframes['internal'].keys()) + "'"
)
with pytest.raises(
KeyError,
match=bad_message
):
tube.Bolt.get_thread_property(
bad_property,
'1/4-20',
'2B',
ureg
)
@staticmethod
def test_get_thread_property_invalid_class():
bad_args = [
[
'pitch diameter max',
'1/4-20',
'2F',
ureg
],
[
'pitch diameter max',
'1/4-20',
'6A',
ureg
]
]
for args in bad_args:
with pytest.raises(
ValueError,
match='bad thread class'
):
tube.Bolt.get_thread_property(*args)
@staticmethod
def test_get_thread_property_invalid_size():
bad_size = '1290-33'
bad_message = (
'Thread size \'' +
bad_size +
'\' not found'
)
with pytest.raises(
KeyError,
match=bad_message
):
tube.Bolt.get_thread_property(
'pitch diameter max',
bad_size,
'2B',
ureg
)
class TestDDT:
diameter = quant(5.76, ureg.inch)
# use a unit diameter to match diameter-specific values from plot
tube_diameter = quant(1, 'meter')
# define gas mixture and relevant pint quantities
mechanism = 'gri30.cti'
gas = ct.Solution(mechanism)
gas.TP = 300, 101325
initial_temperature = quant(gas.T, 'K')
initial_pressure = quant(gas.P, 'Pa')
gas.set_equivalence_ratio(1, 'CH4', {'O2': 1, 'N2': 3.76})
species_dict = gas.mole_fraction_dict()
def test_calculate_spiral_diameter(self):
# define a blockage ratio
test_blockage_ratio = 0.44
# define expected result and actual result
expected_spiral_diameter = (
self.diameter / 2 * (1 - sqrt(1 - test_blockage_ratio))
)
result = tube.DDT.calculate_spiral_diameter(
self.diameter,
test_blockage_ratio
)
# ensure good output
assert expected_spiral_diameter == result.to(ureg.inch)
def test_calculate_spiral_diameter_non_numeric_br(self):
# ensure proper handling with non-numeric blockage ratio
with pytest.raises(
ValueError,
match='Non-numeric blockage ratio.'
):
# noinspection PyTypeChecker
tube.DDT.calculate_spiral_diameter(
self.diameter,
'doompity doo'
)
def test_calculate_spiral_diameter_bad_br(self):
# ensure proper handling with blockage ratio outside allowable limits
bad_blockage_ratios = [-35.124, 0, 1, 120.34]
for ratio in bad_blockage_ratios:
with pytest.raises(
ValueError,
match='Blockage ratio outside of 0<BR<1'
):
tube.DDT.calculate_spiral_diameter(
self.diameter,
ratio
)
@staticmethod
def test_calculate_blockage_ratio():
hand_calc_blockage_ratio = 0.444242326717679
# check for expected result with good input
test_result = tube.DDT.calculate_blockage_ratio(
quant(3.438, ureg.inch),
quant(7. / 16., ureg.inch)
)
assert (test_result - hand_calc_blockage_ratio) < 1e-8
@staticmethod
def test_calculate_blockage_ratio_0_tube_diameter():
with pytest.raises(
ValueError,
match='tube ID cannot be 0'
):
tube.DDT.calculate_blockage_ratio(
quant(0, ureg.inch),
quant(7. / 16., ureg.inch)
)
def test_calculate_blockage_ratio_blockage_gt_tube(self):
# check for correct handling when blockage diameter >= tube diameter
with pytest.raises(
ValueError,
match='blockage diameter >= tube diameter'
):
tube.DDT.calculate_blockage_ratio(
quant(1, ureg.inch),
quant(3, ureg.inch)
)
def test_calculate_ddt_run_up_bad_blockage_ratio(self):
bad_blockages = [-4., 0, 1]
for blockage_ratio in bad_blockages:
with pytest.raises(
ValueError,
match='Blockage ratio outside of correlation range'
):
tube.DDT.calculate_run_up(
blockage_ratio,
self.tube_diameter,
self.initial_temperature,
self.initial_pressure,
self.species_dict,
self.mechanism,
ureg
)
def test_calculate_ddt_run_up(self):
# define good blockage ratios and expected result from each
good_blockages = [0.1, 0.2, 0.3, 0.75]
good_results = [
48.51385390428211,
29.24433249370277,
18.136020151133494,
4.76070528967254
]
# test with good inputs
for blockage_ratio, result in zip(good_blockages, good_results):
test_runup = tube.DDT.calculate_run_up(
blockage_ratio,
self.tube_diameter,
self.initial_temperature,
self.initial_pressure,
self.species_dict,
self.mechanism,
ureg,
phase_specification='gri30_mix'
)
assert 0.5 * result <= test_runup.magnitude <= 1.5 * result
class TestWindow:
width = quant(50, ureg.mm).to(ureg.inch)
length = quant(20, ureg.mm).to(ureg.mile)
pressure = quant(1, ureg.atm).to(ureg.torr)
thickness = quant(1.2, ureg.mm).to(ureg.furlong)
rupture_modulus = quant(5300, ureg.psi).to(ureg.mmHg)
def test_safety_factor(self):
desired_safety_factor = 4
test_sf = tube.Window.safety_factor(
self.length,
self.width,
self.thickness,
self.pressure,
self.rupture_modulus
)
assert abs(test_sf - desired_safety_factor) / test_sf < 0.01
def test_minimum_thickness_sf_less_than_1(self):
# safety factor < 1
safety_factor = [0.25, -7]
for factor in safety_factor:
with pytest.raises(
ValueError,
match='Window safety factor < 1'
):
tube.Window.minimum_thickness(
self.length,
self.width,
factor,
self.pressure,
self.rupture_modulus,
ureg
)
def test_minimum_thickness_sf_non_numeric(self):
safety_factor = 'BruceCampbell'
with pytest.raises(
TypeError,
match='Non-numeric window safety factor'
):
# noinspection PyTypeChecker
tube.Window.minimum_thickness(
self.length,
self.width,
safety_factor,
self.pressure,
self.rupture_modulus,
ureg
)
def test_minimum_thickness(self):
safety_factor = 4
test_thickness = tube.Window.minimum_thickness(
self.length,
self.width,
safety_factor,
self.pressure,
self.rupture_modulus,
ureg
)
test_thickness = test_thickness.to(self.thickness.units).magnitude
desired_thickness = self.thickness.magnitude
assert abs(test_thickness - desired_thickness) / test_thickness < 0.01
@staticmethod
def test_solver_wrong_number_args():
args = [
{
'length': 5,
'width': 4,
'thickness': 2,
'pressure': 2
},
{
'length': 5,
'width': 4,
'thickness': 2,
'pressure': 2,
'rupture_modulus': 10,
'safety_factor': 4
}
]
for argument_dict in args:
with pytest.raises(
ValueError,
match='Incorrect number of arguments sent to solver'
):
tube.Window.solver(**argument_dict)
@staticmethod
def test_solver_bad_kwarg():
kwargs = {
'length': 5,
'width': 4,
'thickness': 2,
'pressure': 2,
'pulled_pork': 9
}
with pytest.raises(
ValueError,
match='Bad keyword argument:\npulled_pork'
):
tube.Window.solver(**kwargs)
@staticmethod
def test_solver_imaginary_result():
kwargs = {
'length': 20,
'width': 50,
'safety_factor': 4,
'pressure': -139,
'rupture_modulus': 5300
}
with pytest.warns(
Warning,
match='Window inputs resulted in imaginary solution.'
):
test_nan = tube.Window.solver(**kwargs)
assert test_nan is np.nan
@staticmethod
def test_solver():
args = [
{
'length': 20,
'width': 50,
'safety_factor': 4,
'pressure': 14.7,
'rupture_modulus': 5300
},
{
'length': 20,
'width': 50,
'thickness': 1.2,
'pressure': 14.7,
'rupture_modulus': 5300
}
]
good_solutions = [1.2, 4.]
for index in range(len(args)):
test_output = tube.Window.solver(**args[index])
assert abs(test_output - good_solutions[index]) < 0.1
@staticmethod
def test_calculate_window_bolt_sf():
max_pressure = quant(1631.7, 'psi')
window_area = quant(5.75 * 2.5, 'in^2')
num_bolts = 20
thread_size = '1/4-28'
thread_class = '2'
bolt_max_tensile = quant(120, 'ksi')
plate_max_tensile = quant(30, 'ksi')
engagement_length = quant(0.5, 'in')
hand_calc = {
'bolt': 3.606968028,
'plate': 7.969517321,
}
test_values = tube.Window.calculate_bolt_sfs(
max_pressure,
window_area,
num_bolts,
thread_size,
thread_class,
bolt_max_tensile,
plate_max_tensile,
engagement_length,
ureg
)
compare(hand_calc, test_values)
# noinspection PyProtectedMember
@pytest.mark.tube
class TestTube:
material = '316L'
schedule = '80'
nominal_size = '6'
welded = False
safety_factor = 4
fake_material_groups = {'thing0': 'group0', 'thing1': 'group1'}
fake_materials = pd.DataFrame(columns=['Group', 'Grade'])
class FakeOpen:
"""
fake open()
"""
def __init__(self, *_):
"""
dummy init statement
"""
def __enter__(self, *_):
"""
enter statement that returns a FakeFile
"""
return self.FakeFile()
def __exit__(self, *_):
"""
dummy exit statement
"""
return None
class FakeFile:
"""
fake file used for FakeOpen
"""
@staticmethod
def readline(*_):
"""
fake file for use with FakeOpen()
"""
return 'ASDF,thing0,thing1\n'
def test__dimensions_lookup_bad_schedule(self):
test_tube = tube.Tube()
test_tube._set_property('schedule', 'garbage')
with pytest.raises(
ValueError,
match='\nPipe schedule not found'
):
test_tube._dimensions_lookup()
def test__dimensions_lookup_bad_size(self):
test_tube = tube.Tube()
test_tube._set_property('nominal_size', '2.222')
with pytest.raises(
ValueError,
match='\nNominal size not found for given pipe schedule'
):
test_tube._dimensions_lookup()
def test_prop_autocalc_initial_set_get(self):
inputs = [True, False, 0, 1]
expected = [bool(item) for item in inputs]
test_tube = tube.Tube()
results = []
for value, correct in zip(inputs, expected):
test_tube.autocalc_initial = value
results.append(value == correct)
assert all(results)
def test_prop_show_warnings_set_get(self):
inputs = [True, False, 0, 1]
expected = [bool(item) for item in inputs]
test_tube = tube.Tube()
results = []
for value, correct in zip(inputs, expected):
test_tube.show_warnings = value
results.append(value == correct)
assert all(results)
def test_prop_available_pipe_sizes_set(self):
test_tube = tube.Tube()
with pytest.raises(
PermissionError,
match='\nPipe sizes can not be set manually.'
):
test_tube.available_pipe_sizes = 7
def test_prop_available_pipe_sizes_get(self):
test_tube = tube.Tube()
assert isinstance(test_tube.available_pipe_sizes, list)
def test_prop_available_pipe_schedules_set(self):
test_tube = tube.Tube()
with pytest.raises(
PermissionError,
match='\nPipe schedules can not be set manually.'
):
test_tube.available_pipe_schedules = 'big as hell'
def test_prop_available_pipe_schedules_get(self):
test_tube = tube.Tube()
assert isinstance(test_tube.available_pipe_schedules, list)
def test_prop_available_tube_materials_set(self):
test_tube = tube.Tube()
with pytest.raises(
PermissionError,
match='\nAvailable tube materials can not be set manually.'
):
test_tube.available_tube_materials = 'Aluminum Foil'
def test_prop_available_tube_materials_get(self):
test_tube = tube.Tube()
assert isinstance(test_tube.available_tube_materials, list)
def test_prop_nominal_size_set_get(self):
test_tube = tube.Tube()
inputs = [(1), 6, '1 1/2']
expected = [str(item) for item in inputs]
results = []
for value, correct in zip(inputs, expected):
test_tube.nominal_size = value
result = test_tube.nominal_size
results.append(result == correct)
assert all(results)
def test_prop_nominal_size_set_bad_size(self):
bad_size = 'really big'
match_string = '\n{0} is not a valid pipe size. '.format(bad_size) + \
'For a list of available sizes, try \n' + \
'`mytube.available_pipe_sizes`'
with pytest.raises(
ValueError,
match=match_string
):
test_tube = tube.Tube()
test_tube.nominal_size = bad_size
def test_prop_schedule_set_get(self):
test_tube = tube.Tube()
inputs = [40, 'XXH']
expected = [str(item) for item in inputs]
results = []
for value, correct in zip(inputs, expected):
test_tube.schedule = value
result = test_tube.schedule
results.append(result == correct)
assert all(results)
def test_prop_schedule_set_bad_schedule(self):
bad_schedule = 'Kropotkin'
match_string = '\n{0} is not a valid pipe schedule for this nominal' \
' size. '.format(bad_schedule) + \
'For a list of available schedules, try \n' + \
'`mytube.available_pipe_schedules`'
with pytest.raises(
ValueError,
match=match_string
):
test_tube = tube.Tube()
test_tube.schedule = bad_schedule
def test_prop_dimensions_set(self):
test_tube = tube.Tube()
match_string = '\nTube dimensions are looked up based on nominal' \
' pipe size and schedule, not set. Try ' \
'`mytube.schedule()` or `mytube.nominal_size()` instead.'
with pytest.raises(PermissionError) as err:
test_tube.dimensions = [0, 2, 3]
assert str(err.value) == match_string
def test_prop_dimensions_get(self):
test_tube = tube.Tube(
nominal_size=self.nominal_size,
schedule=self.schedule
)
# Note: _get_dimensions is called during __init__
outer_diameter = test_tube.dimensions.outer_diameter
inner_diameter = test_tube.dimensions.inner_diameter
wall_thickness = test_tube.dimensions.wall_thickness
assert outer_diameter.units.format_babel() == 'inch'
assert inner_diameter.units.format_babel() == 'inch'
assert wall_thickness.units.format_babel() == 'inch'
assert outer_diameter.magnitude - 6.625 < 1e-7
assert inner_diameter.magnitude - 5.761 < 1e-7
assert wall_thickness.magnitude - 0.432 < 1e-7
def test_prop_material_set_bad_material(self):
test_tube = tube.Tube()
match_string = '\nPipe material not found. For a list of ' + \
'available materials try:\n' + \
'`mytube.available_tube_materials`'
with pytest.raises(
ValueError,
match=match_string
):
test_tube.material = 'unobtainium'
def test_prop_welded(self):
welded_args = [0, 1, True, False]
welded_results = [False, True, True, False]
test_tube = tube.Tube()
tests = []
for welded_in, good_result in zip(welded_args, welded_results):
test_tube.welded = welded_in
tests.append(test_tube.welded == good_result)
assert all(tests)
def test_check_materials_list(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
assert test_tube._check_materials_list()
def test_check_materials_list_no_files_found(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
def fake_listdir(*_):
# returns an empty list to test for files-not-found condition
return []
with pytest.raises(
FileNotFoundError,
match='no files containing "flange" or "stress" found'
):
with patch('os.listdir', new=fake_listdir):
test_tube._check_materials_list()
def test_check_materials_list_group_lookup_fails(self):
test_tube = tube.Tube()
# there is no group0 in any of the flange rating groups, and trying to
# look it up should generate a material group not found portion of the
# error string. This test sets the materials dataframe to an empty one
# with only Group and Grade columns, then adds a material group
# 'group0' to generate the desired error. Grade is set to 316L to
# avoid a grade-related error.
try:
test_tube._materials = self.fake_materials.copy()
test_tube._materials['Group'] = ['group0']
test_tube._materials['Grade'] = ['316L']
test_tube._check_materials_list()
except ValueError as err:
message = '\nmaterial group group0 not found\n'
assert message == str(err)
def test_check_materials_list_no_welded_or_seamless(self):
test_tube = tube.Tube()
def fake_listdir(*_):
# causes welded/seamless warning
return ['asdfflangegroup0sfh',
'asdfflangegroup1asd',
'asdfstresswdasdg']
test_tube._material_groups = self.fake_material_groups
test_tube._materials = self.fake_materials
with patch('builtins.open', new=self.FakeOpen):
with patch('os.listdir', new=fake_listdir):
error_string = 'asdfstresswdasdg' + \
'does not indicate whether it is welded' + \
' or seamless'
with pytest.warns(UserWarning, match=error_string):
test_tube._check_materials_list()
def test_check_materials_list_missing_material(self):
test_tube = tube.Tube()
file_directory = os.path.join(
'beaverdet',
'lookup_data'
)
def fake_listdir(*_):
"""
listdir function that should work 100%
"""
return ['asdfflangegroup0sfh',
'asdfflangegroup1asd',
'asdfstressweldedasdg']
test_tube._material_groups = self.fake_material_groups
test_tube._materials = pd.DataFrame(
columns=['Grade', 'Group'],
data=list(map(list, zip(
self.fake_material_groups.keys(),
self.fake_material_groups.values()
)))
)
with patch('builtins.open', new=self.FakeOpen):
with patch('os.listdir', new=fake_listdir):
class NewFakeFile:
"""
FakeFile class that should fail material lookup
"""
@staticmethod
def readline(*_):
"""
readline function that should fail material
lookup for thing1
"""
return 'ASDF,thing0\n'
setattr(self.FakeOpen, 'FakeFile', NewFakeFile)
error_string = '\nMaterial thing1 not found in ' + \
os.path.join(
file_directory,
'asdfstressweldedasdg'
) + '\n'
try:
test_tube._check_materials_list()
except ValueError as err:
assert str(err) == error_string
def test_get_material_groups(self):
# ensure correctness by comparing to a pandas dataframe reading the
# same file
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
# file information
file_directory = os.path.join(
os.path.dirname(
os.path.relpath(__file__)
),
'..',
'lookup_data'
)
file_name = 'materials_list.csv'
file_location = os.path.join(file_directory, file_name)
# load data into a test dataframe
test_dataframe = pd.read_csv(file_location)
# load data into a dictionary using get_material_groups()
test_output = test_tube._material_groups
# collect keys and values from dataframe that should correspond to
# those of the dictionary
keys_from_dataframe = test_dataframe.Grade.values.astype(str)
values_from_dataframe = test_dataframe.Group.values.astype(str)
for index, key in enumerate(keys_from_dataframe):
# make sure each set of values are approximately equal
dict_value = test_output[key]
dataframe_value = values_from_dataframe[index]
assert dict_value == dataframe_value
def test_collect_tube_materials(self):
test_tube = tube.Tube()
columns = ['Grade', 'Group', 'ElasticModulus', 'Density', 'Poisson']
data = [
['304', 2.1, 200, 7.8, 0.28],
['304H', 2.1, 200, 7.8, 0.28],
['316', 2.2, 200, 7.9, 0.28],
['316H', 2.2, 200, 7.9, 0.28],
['317', 2.2, 200, 7.9, 0.28],
['304L', 2.3, 200, 7.8, 0.28],
['316L', 2.3, 200, 7.9, 0.28]
]
good_dataframe = pd.DataFrame(
data=data,
index=None,
columns=columns
)
good_dataframe['ElasticModulus'] = [
test_tube._units.quant(item, 'GPa') for item in
good_dataframe['ElasticModulus']
]
good_dataframe['Density'] = [
test_tube._units.quant(item, 'g/cm^3') for item in
good_dataframe['Density']
]
assert test_tube._materials.equals(good_dataframe)
def test_collect_tube_materials_nonexistent_file(self):
def fake_exists(*_):
return False
with patch(
'os.path.exists',
new=fake_exists
):
with pytest.raises(
ValueError,
match='materials_list.csv does not exist'
):
tube.Tube()
def test_collect_tube_materials_empty_file(self):
# noinspection PyUnresolvedReferences
def fake_csv_import(*_):
raise pd.errors.EmptyDataError
with patch(
'pandas.read_csv',
new=fake_csv_import
):
# check for proper error handling when file is blank
with pytest.raises(
ValueError,
match='materials_list.csv is empty'
):
tube.Tube()
def test_get_flange_limits_from_csv(self):
test_tube = tube.Tube()
flange_class = '900'
temperature = test_tube._units.quant(400, 'degC')
# good pressures manually entered based on values from .csv files
good_pressures = {
'2.1': 85.3,
'2.2': 88.3,
'2.3': 72.9
}
tests = []
for group, pressure in good_pressures.items():
# read the imported pressure and compare it to the correct pressure
test_pressure = test_tube._flange_limits[group] \
.loc[test_tube._flange_limits[group]['Temperature'] ==
temperature][flange_class].values[0]
good_pressure = test_tube._units.quant(pressure, 'bar')
tests.append(test_pressure == good_pressure)
assert all(tests)
def test_get_flange_limits_from_csv_bad_group(self):
test_tube = tube.Tube()
file_name = 'ASME_B16_5_flange_ratings_group_2_1.csv'
file_directory = os.path.join(
os.path.dirname(os.path.relpath(tube.__file__)),
'lookup_data')
file_location = os.path.join(
file_directory,
file_name
)
match_string = '\n' + file_location + 'not found'
# bad group is identified by checking the existence of a .csv fil
def fake_os_path_exists(*_):
return False
with patch(
'os.path.exists',
new=fake_os_path_exists
):
try:
test_tube._get_flange_limits_from_csv()
except FileNotFoundError as err:
err = str(err)
assert match_string == err
def test_get_flange_limits_from_csv_bad_pressure(self):
test_tube = tube.Tube()
match_string = '\nPressure less than zero.'
# an error should be thrown when a non-temperature column has a
# negative value
def fake_read_csv(*_):
return pd.DataFrame(columns=['Temperature', '900'],
data=[[10, -10]])
with patch(
'pandas.read_csv',
new=fake_read_csv
):
with pytest.raises(
ValueError,
match=match_string
):
test_tube._get_flange_limits_from_csv()
def test_get_flange_limits_from_csv_zeroed_non_numeric(self):
test_tube = tube.Tube()
# create test dataframe and a dataframe of what the output should
# look like after the test dataframe is imported
test_temperatures = [9, 's', 'd']
good_temperatures = [9., 0., 0.]
test_pressures = ['a', 3, 'f']
good_pressures = [0., 3., 0.]
test_dataframe = pd.DataFrame({'Temperature': test_temperatures,
'Pressure': test_pressures})
good_dataframe = pd.DataFrame({'Temperature': good_temperatures,
'Pressure': good_pressures})
# convince the tube to load the test dataframe without having to
# write a .csv to disk
def fake_read_csv(*_):
return test_dataframe
with patch(
'pandas.read_csv',
new=fake_read_csv
):
test_tube._get_flange_limits_from_csv()
tests = []
for group in set(test_tube._material_groups.values()):
# pull the dataframe of flange limits for each material group
# and use applymap to remove units from all pint quantities.
# This is done to circumvent an error caused by using
# np.allclose for an array of pint quantities. Comparison to
# good_dataframe.values is done to avoid having to care about
# how the values are distributed by pandas.
df = test_tube._flange_limits[group]
test_values = df.applymap(lambda x: x.magnitude)
test = np.allclose(test_values,
good_dataframe.values)
tests.append(test)
assert all(tests)
def test_get_pipe_stress_limits_welded(self):
test_tube = tube.Tube(
material='304',
welded=True
)
# known values for 304
welded_values = np.array(
[16, 16, 13.3, 12, 11, 10.5, 9.7, 9.5, 9.4, 9.2, 9,
8.8, 8.7, 8.5, 8.3, 8.1, 7.6, 6.5, 5.4])
test_limits = test_tube._get_pipe_stress_limits()
test_limits = np.array(test_limits['stress'][1])
assert np.allclose(welded_values, test_limits)
def test_get_pipe_stress_limits_seamless(self):
test_tube = tube.Tube(
material='304',
welded=False
)
# known values for 304
seamless_values = np.array(
[18.8, 18.8, 15.7, 14.1, 13, 12.2, 11.4, 11.3,
11.1, 10.8, 10.6, 10.4, 10.2, 10, 9.8, 9.5, 8.9,
7.7, 6.1])
test_limits = test_tube._get_pipe_stress_limits()
test_limits = np.array(test_limits['stress'][1])
assert np.allclose(seamless_values, test_limits)
def test_get_pipe_dlf(self):
"""
Tests get_pipe_dlf
Conditions tested:
- good input
* load factor is 1
* load factor is 2
* load factor is 4
- plus_or_minus outside of (0, 1)
- pipe material not in materials list
"""
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
# from hand calcs, critical velocity is 1457.44 m/s, giving upper and
# lower bounds of 1603.188 and 1311.700 m/s
cj_speeds = [
test_tube._units.quant(1200, 'm/s'), # DLF 1
test_tube._units.quant(1311, 'm/s'), # DLF 1
test_tube._units.quant(1312, 'm/s'), # DLF 4
test_tube._units.quant(1400, 'm/s'), # DLF 4
test_tube._units.quant(1603, 'm/s'), # DLF 4
test_tube._units.quant(1604, 'm/s'), # DLF 2
test_tube._units.quant(2000, 'm/s') # DLF 2
]
expected_dlf = [1, 1, 4, 4, 4, 2, 2]
test_dlf = []
for cj_speed in cj_speeds:
test_dlf.append(
test_tube._get_pipe_dlf(plus_or_minus=0.1, cj_vel=cj_speed)
)
assert all(
dlf == good_dlf for dlf, good_dlf in zip(test_dlf, expected_dlf)
)
def test_get_pipe_dlf_bad_plus_minus_value(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
# plus_or_minus outside of (0, 1)
bad_plus_minus = [-1, 0, 1, 2]
for plus_minus in bad_plus_minus:
with pytest.raises(
ValueError,
match='plus_or_minus factor not between 0 and 1'
):
test_tube._get_pipe_dlf(
plus_or_minus=plus_minus,
cj_vel=test_tube._units.quant(2, 'm/s')
)
def test_calculate_max_stress_seamless(self):
test_tube = tube.Tube(
material='316L',
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=False,
safety_factor=self.safety_factor
)
initial_temperatures = [
test_tube._units.quant(100, 'degF'),
test_tube._units.quant(200, 'degF'),
test_tube._units.quant(150, 'degF')
]
# in ksi
good_stresses = [
15.7,
13.3,
14.5
]
for temperature, stress in zip(initial_temperatures, good_stresses):
test_tube.initial_temperature = temperature
assert np.allclose(
test_tube.calculate_max_stress().to('ksi').magnitude,
stress
)
def test_calculate_max_stress_welded(self):
test_tube = tube.Tube(
material='304',
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=True,
safety_factor=self.safety_factor
)
initial_temperatures = [
test_tube._units.quant(650, 'degF'),
test_tube._units.quant(700, 'degF'),
test_tube._units.quant(675, 'degF')
]
# in ksi
good_stresses = [
9.5,
9.4,
9.45
]
for temperature, stress in zip(initial_temperatures, good_stresses):
test_tube.initial_temperature = temperature
assert np.allclose(
test_tube.calculate_max_stress().to('ksi').magnitude,
stress
)
def test_calculate_max_stress_non_monotonic(self):
test_tube = tube.Tube()
temp = test_tube._units.quant(100, 'degF')
def make_non_monotonic(*_):
return {
'temperature': ('degF', [0, 1, -1]),
'stress': ('ksi', [0, 0, 0])
}
with patch(
'beaverdet.tube.Tube._get_pipe_stress_limits',
new=make_non_monotonic
):
with pytest.raises(
ValueError,
match='Stress limits require temperatures to be ' +
'monotonically increasing'
):
test_tube.initial_temperature = temp
@staticmethod
def test_calculate_max_pressure():
safety_factor = 4
test_tube = tube.Tube(
material='304',
schedule='80',
nominal_size='6',
welded=False,
safety_factor=safety_factor
)
max_stress = test_tube._units.quant(18.8, 'ksi')
wall_thickness = test_tube._units.quant(0.432, 'in')
outer_diameter = test_tube._units.quant(6.625, 'in')
inner_diameter = outer_diameter - 2 * wall_thickness
mean_diameter = (inner_diameter + outer_diameter) / 2
asme_fs = 4
good_max_pressure = (
max_stress * (2 * wall_thickness) * asme_fs /
(mean_diameter * safety_factor)
).to('Pa').magnitude
test_tube.max_stress = max_stress
test_max_pressure = test_tube.calculate_max_pressure()\
.to('Pa').magnitude
assert np.allclose(test_max_pressure, good_max_pressure)
def test_calculate_initial_pressure_no_mp(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor,
mechanism='gri30.cti',
fuel='H2',
oxidizer='O2',
equivalence_ratio=1,
show_warnings=False,
initial_temperature=(300, 'K'),
autocalc_initial=True,
use_multiprocessing=False
)
# the initial pressure should cause the reflected detonation pressure
# to be equal to the tube's max pressure, accounting for dynamic load
# factor
correct_max = test_tube.max_pressure.to('Pa').magnitude
test_state = thermochem.calculate_reflected_shock_state(
test_tube.initial_temperature,
test_tube.initial_pressure,
test_tube.reactant_mixture,
test_tube.mechanism,
test_tube._units.ureg
)
error = abs(
correct_max -
test_state['reflected']['state'].P * test_tube.dynamic_load_factor
) / correct_max
assert error <= 0.0005
def test_calculate_initial_pressure_with_mp(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor,
mechanism='gri30.cti',
fuel='H2',
oxidizer='O2',
equivalence_ratio=1,
show_warnings=False,
initial_temperature=(300, 'K'),
autocalc_initial=True,
use_multiprocessing=True,
verbose=True
)
# the initial pressure should cause the reflected detonation pressure
# to be equal to the tube's max pressure, accounting for dynamic load
# factor
correct_max = test_tube.max_pressure.to('Pa').magnitude
test_state = thermochem.calculate_reflected_shock_state(
test_tube.initial_temperature,
test_tube.initial_pressure,
test_tube.reactant_mixture,
test_tube.mechanism,
test_tube._units.ureg
)
error = abs(
correct_max -
test_state['reflected']['state'].P * test_tube.dynamic_load_factor
) / correct_max
assert error <= 0.0005
def test_lookup_flange_class(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
test_tube.max_pressure = test_tube._units.quant(125, 'bar')
test_tube.initial_temperature = test_tube._units.quant(350, 'degC')
assert test_tube.lookup_flange_class() == 1500
def test_lookup_flange_class_bad_material(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
test_tube.max_pressure = test_tube._units.quant(125, 'bar')
test_tube.initial_temperature = test_tube._units.quant(350, 'degC')
assert test_tube.lookup_flange_class() == 1500
def test_lookup_flange_class_bad_temperature(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
test_temperatures = [
test_tube._units.quant(-100, 'degC'),
test_tube._units.quant(500, 'degC')
]
test_tube.max_pressure = test_tube._units.quant(125, 'bar')
for temperature in test_temperatures:
# fake out the initial temperature set, because using the property
# directly causes flange class to be calculated. Direct calculation
# isn't desirable for this test because it is less direct.
test_tube._properties['initial_temperature'] = temperature
with pytest.raises(
ValueError,
match='Temperature out of range.'
):
test_tube.lookup_flange_class()
def test_lookup_flange_class_bad_pressure(self):
test_tube = tube.Tube(
material=self.material,
schedule=self.schedule,
nominal_size=self.nominal_size,
welded=self.welded,
safety_factor=self.safety_factor
)
test_tube.initial_temperature = test_tube._units.quant(350, 'degC')
test_pressure = test_tube._units.quant(350, ureg.bar)
# fake out the initial pressure set, because using the property
# directly causes flange class to be calculated. Direct calculation
# isn't desirable for this test because it is less direct.
test_tube._properties['max_pressure'] = test_pressure
with pytest.raises(
ValueError,
match='Pressure out of range.'
):
test_tube.lookup_flange_class()
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15945,
29908,
13,
29925,
4574,
13152,
1660,
29901,
13,
1678,
13223,
6987,
363,
8492,
29889,
2272,
13,
13,
27045,
29928,
6770,
29901,
13,
1678,
529,
5813,
29958,
13,
1678,
25203,
4306,
3014,
13,
1678,
25781,
1525,
322,
18264,
25381,
12016,
13,
1678,
529,
26862,
6227,
29958,
13,
15945,
29908,
13,
13,
13,
3166,
5844,
1053,
18074,
2273,
13,
5215,
11451,
1688,
13,
5215,
16483,
13,
5215,
2897,
13,
5215,
508,
10120,
408,
274,
29873,
13,
5215,
12655,
408,
7442,
13,
5215,
11701,
408,
10518,
13,
3166,
11187,
1053,
13261,
13,
3166,
6317,
1053,
260,
4003,
13,
3166,
6317,
1053,
14563,
2878,
331,
13,
13,
545,
29887,
353,
16483,
29889,
8325,
22579,
580,
13,
12150,
353,
318,
1727,
29889,
22930,
537,
13,
13,
13,
1753,
7252,
29898,
11288,
29892,
9528,
1125,
13,
1678,
363,
1820,
29892,
995,
297,
12219,
29889,
7076,
7295,
13,
4706,
1018,
29901,
13,
9651,
1243,
29918,
1767,
353,
9528,
29961,
1989,
1822,
517,
29898,
1767,
29889,
348,
1169,
29889,
4830,
29918,
28727,
16655,
29885,
4211,
4279,
13,
9651,
995,
353,
995,
29889,
29885,
4211,
4279,
13,
4706,
5174,
23833,
2392,
29901,
13,
9651,
1243,
29918,
1767,
353,
9528,
29961,
1989,
29962,
13,
13,
4706,
4974,
6425,
29898,
1688,
29918,
1767,
448,
995,
29897,
847,
995,
529,
29871,
29896,
29872,
29899,
29946,
13,
13,
13,
29937,
694,
1144,
27988,
10772,
1184,
371,
2954,
13404,
13,
1990,
4321,
29933,
14339,
29901,
13,
1678,
3244,
29918,
2311,
353,
525,
29896,
29914,
29946,
29899,
29906,
29947,
29915,
13,
1678,
3244,
29918,
1990,
353,
525,
29906,
29915,
13,
1678,
15284,
29918,
3317,
29918,
29873,
575,
488,
353,
4323,
29898,
29941,
29900,
29892,
525,
29895,
1039,
1495,
13,
1678,
3033,
5049,
29918,
2848,
353,
4323,
29898,
29900,
29889,
29945,
29892,
525,
262,
1495,
13,
1678,
289,
14339,
29918,
3317,
29918,
29873,
575,
488,
353,
4323,
29898,
29947,
29900,
29892,
525,
29895,
1039,
1495,
13,
13,
1678,
822,
1243,
29918,
15807,
403,
29918,
710,
404,
29918,
598,
294,
29918,
957,
29918,
29896,
29900,
29900,
29895,
1039,
29898,
1311,
1125,
13,
4706,
396,
1243,
289,
14339,
1405,
29871,
29896,
29900,
29900,
29895,
1039,
13,
4706,
289,
14339,
29918,
3317,
29918,
29873,
575,
488,
353,
4323,
29898,
29896,
29906,
29900,
29892,
525,
29895,
1039,
1495,
13,
4706,
1361,
29918,
28667,
353,
426,
13,
9651,
525,
29879,
1037,
29893,
4038,
2396,
4323,
29898,
29900,
29889,
29900,
29941,
29946,
29929,
29941,
29946,
29900,
29946,
29929,
29892,
525,
262,
29985,
29906,
5477,
13,
9651,
525,
2341,
4038,
2396,
4323,
29898,
29900,
29889,
29941,
29900,
29947,
29955,
29946,
29946,
29900,
29947,
29906,
29892,
525,
262,
29985,
29906,
5477,
13,
9651,
525,
1195,
12539,
3033,
5049,
2396,
4323,
29898,
29900,
29889,
29946,
29945,
29906,
29945,
29929,
29945,
29945,
29946,
29946,
29892,
525,
262,
1495,
13,
4706,
500,
13,
4706,
1243,
29918,
598,
294,
353,
260,
4003,
29889,
29933,
14339,
29889,
15807,
403,
29918,
710,
404,
29918,
598,
294,
29898,
13,
9651,
1583,
29889,
7097,
29918,
2311,
29892,
13,
9651,
1583,
29889,
7097,
29918,
1990,
29892,
13,
9651,
289,
14339,
29918,
3317,
29918,
29873,
575,
488,
29892,
13,
9651,
1583,
29889,
2341,
29918,
3317,
29918,
29873,
575,
488,
29892,
13,
9651,
1583,
29889,
996,
5049,
29918,
2848,
29892,
13,
9651,
318,
1727,
13,
4706,
1723,
13,
4706,
7252,
29898,
3179,
29918,
28667,
29892,
1243,
29918,
598,
294,
29897,
13,
13,
1678,
822,
1243,
29918,
15807,
403,
29918,
710,
404,
29918,
598,
294,
29918,
5062,
29918,
29896,
29900,
29900,
29895,
1039,
29898,
1311,
1125,
13,
4706,
396,
1243,
289,
14339,
529,
29871,
29896,
29900,
29900,
29895,
1039,
13,
4706,
289,
14339,
29918,
3317,
29918,
29873,
575,
488,
353,
4323,
29898,
29947,
29900,
29892,
525,
29895,
1039,
1495,
13,
4706,
1361,
29918,
28667,
353,
426,
13,
9651,
525,
29879,
1037,
29893,
4038,
2396,
4323,
29898,
29900,
29889,
29900,
29941,
29953,
29941,
29955,
29946,
29900,
29955,
29941,
29892,
525,
262,
29985,
29906,
5477,
13,
9651,
525,
1195,
12539,
3033,
5049,
2396,
4323,
29898,
29900,
29889,
29941,
29896,
29946,
29896,
29953,
29947,
29900,
29945,
29941,
29892,
525,
262,
1495,
13,
4706,
500,
13,
4706,
1243,
29918,
598,
294,
353,
260,
4003,
29889,
29933,
14339,
29889,
15807,
403,
29918,
710,
404,
29918,
598,
294,
29898,
13,
9651,
1583,
29889,
7097,
29918,
2311,
29892,
13,
9651,
1583,
29889,
7097,
29918,
1990,
29892,
13,
9651,
289,
14339,
29918,
3317,
29918,
29873,
575,
488,
29892,
13,
9651,
1583,
29889,
2341,
29918,
3317,
29918,
29873,
575,
488,
29892,
13,
9651,
1583,
29889,
996,
5049,
29918,
2848,
29892,
13,
9651,
318,
1727,
13,
4706,
1723,
13,
4706,
7252,
29898,
3179,
29918,
28667,
29892,
1243,
29918,
598,
294,
29897,
13,
13,
1678,
822,
1243,
29918,
15807,
403,
29918,
710,
404,
29918,
598,
294,
29918,
2848,
29918,
517,
29877,
29918,
12759,
29898,
1311,
1125,
13,
4706,
396,
9801,
9177,
746,
3033,
5049,
3309,
529,
9212,
13,
4706,
3033,
5049,
29918,
2848,
353,
4323,
29898,
29900,
29889,
29900,
29945,
29892,
525,
262,
1495,
13,
4706,
411,
11451,
1688,
29889,
4495,
1983,
29898,
13,
18884,
24412,
29892,
13,
18884,
1993,
2433,
29903,
1037,
5652,
4418,
297,
1183,
279,
29892,
451,
260,
2673,
6169,
718,
13,
462,
418,
525,
1858,
403,
1122,
367,
5625,
4063,
6169,
718,
13,
462,
418,
525,
10056,
10231,
289,
14339,
3033,
5049,
3309,
29915,
13,
308,
1125,
13,
9651,
260,
4003,
29889,
29933,
14339,
29889,
15807,
403,
29918,
710,
404,
29918,
598,
294,
29898,
13,
18884,
1583,
29889,
7097,
29918,
2311,
29892,
13,
18884,
1583,
29889,
7097,
29918,
1990,
29892,
13,
18884,
1583,
29889,
2095,
29873,
29918,
3317,
29918,
29873,
575,
488,
29892,
13,
18884,
1583,
29889,
2341,
29918,
3317,
29918,
29873,
575,
488,
29892,
13,
18884,
3033,
5049,
29918,
2848,
29892,
13,
18884,
318,
1727,
13,
9651,
1723,
13,
13,
1678,
732,
7959,
5696,
13,
1678,
822,
1243,
29918,
5215,
29918,
7097,
29918,
5965,
2395,
7295,
13,
4706,
396,
1781,
1881,
13,
4706,
1243,
29918,
2311,
353,
525,
29900,
29899,
29947,
29900,
29915,
13,
4706,
1243,
29918,
1853,
353,
6024,
23176,
742,
525,
7564,
2033,
13,
4706,
1243,
29918,
6799,
353,
525,
29886,
2335,
24235,
4236,
29915,
13,
4706,
1243,
29918,
13203,
353,
518,
1839,
29906,
29909,
742,
525,
29941,
29909,
7464,
6024,
29906,
29933,
742,
525,
29941,
29933,
2033,
29962,
13,
4706,
1781,
29918,
2914,
353,
5519,
29900,
29889,
29900,
29945,
29896,
29946,
29892,
29871,
29900,
29889,
29900,
29945,
29896,
29929,
1402,
518,
29900,
29889,
29900,
29945,
29946,
29906,
29892,
29871,
29900,
29889,
29900,
29945,
29941,
29953,
5262,
13,
4706,
2702,
800,
353,
260,
4003,
29889,
29933,
14339,
3032,
5215,
29918,
7097,
29918,
5965,
2395,
580,
13,
4706,
363,
3244,
29892,
4413,
29892,
3806,
297,
14319,
29898,
1688,
29918,
1853,
29892,
1243,
29918,
13203,
29892,
13,
462,
462,
632,
1781,
29918,
2914,
1125,
13,
9651,
396,
1423,
363,
1959,
1962,
13,
9651,
1857,
29918,
2557,
353,
2702,
800,
29961,
7097,
29962,
13,
9651,
363,
3244,
29918,
1990,
29892,
1121,
297,
14319,
29898,
13203,
29892,
3806,
1125,
13,
18884,
1243,
29918,
2914,
353,
1857,
29918,
2557,
29961,
1688,
29918,
6799,
3816,
1688,
29918,
2311,
3816,
13,
462,
1678,
3244,
29918,
1990,
29962,
13,
18884,
4974,
6425,
29898,
1688,
29918,
2914,
448,
1121,
29897,
529,
29871,
29896,
29872,
29899,
29955,
13,
13,
1678,
732,
7959,
5696,
13,
1678,
822,
1243,
29918,
657,
29918,
7097,
29918,
6799,
7295,
13,
4706,
396,
1781,
1881,
13,
4706,
1781,
29918,
5085,
353,
518,
13,
9651,
518,
13,
18884,
525,
29886,
2335,
24235,
4236,
742,
13,
18884,
525,
29896,
29914,
29946,
29899,
29906,
29900,
742,
13,
18884,
525,
29906,
29933,
742,
13,
18884,
318,
1727,
13,
9651,
21251,
13,
9651,
518,
13,
18884,
525,
29886,
2335,
24235,
4236,
742,
13,
18884,
525,
29896,
29914,
29946,
29899,
29906,
29900,
742,
13,
18884,
525,
29906,
29909,
742,
13,
18884,
318,
1727,
13,
9651,
4514,
13,
4706,
4514,
13,
4706,
1781,
29918,
9902,
353,
518,
13,
632,
29900,
29889,
29906,
29906,
29946,
29947,
29892,
13,
632,
29900,
29889,
29906,
29896,
29953,
29946,
13,
4706,
4514,
13,
4706,
363,
6389,
29892,
1121,
297,
14319,
29898,
16773,
29918,
5085,
29892,
1781,
29918,
9902,
1125,
13,
9651,
1243,
29918,
2914,
353,
260,
4003,
29889,
29933,
14339,
29889,
657,
29918,
7097,
29918,
6799,
10456,
5085,
29897,
13,
13,
9651,
4974,
6425,
29898,
1688,
29918,
2914,
29889,
29885,
4211,
4279,
448,
1121,
29897,
529,
29871,
29896,
29872,
29899,
29955,
13,
13,
1678,
732,
7959,
5696,
13,
1678,
822,
1243,
29918,
657,
29918,
7097,
29918,
6799,
29918,
1333,
29918,
262,
29918,
1272,
2557,
7295,
13,
4706,
848,
19935,
353,
260,
4003,
29889,
29933,
14339,
3032,
5215,
29918,
7097,
29918,
5965,
2395,
580,
13,
4706,
396,
2875,
451,
297,
12205,
13,
4706,
4319,
29918,
6799,
353,
525,
29926,
3156,
29915,
13,
4706,
4319,
29918,
4906,
353,
313,
13,
18884,
525,
4899,
2875,
320,
4907,
718,
13,
18884,
4319,
29918,
6799,
718,
13,
18884,
11297,
29915,
451,
1476,
29889,
7740,
3106,
1580,
29879,
29901,
525,
718,
13,
18884,
376,
11838,
718,
376,
742,
525,
1642,
7122,
29898,
1272,
19935,
1839,
7564,
13359,
8149,
3101,
718,
376,
11838,
13,
4706,
1723,
13,
4706,
411,
11451,
1688,
29889,
336,
4637,
29898,
13,
18884,
7670,
2392,
29892,
13,
18884,
1993,
29922,
12313,
29918,
4906,
13,
308,
1125,
13,
9651,
260,
4003,
29889,
29933,
14339,
29889,
657,
29918,
7097,
29918,
6799,
29898,
13,
18884,
4319,
29918,
6799,
29892,
13,
18884,
525,
29896,
29914,
29946,
29899,
29906,
29900,
742,
13,
18884,
525,
29906,
29933,
742,
13,
18884,
318,
1727,
13,
9651,
1723,
13,
13,
1678,
732,
7959,
5696,
13,
1678,
822,
1243,
29918,
657,
29918,
7097,
29918,
6799,
29918,
20965,
29918,
1990,
7295,
13,
4706,
4319,
29918,
5085,
353,
518,
13,
9651,
518,
13,
18884,
525,
29886,
2335,
24235,
4236,
742,
13,
18884,
525,
29896,
29914,
29946,
29899,
29906,
29900,
742,
13,
18884,
525,
29906,
29943,
742,
13,
18884,
318,
1727,
13,
9651,
21251,
13,
9651,
518,
13,
18884,
525,
29886,
2335,
24235,
4236,
742,
13,
18884,
525,
29896,
29914,
29946,
29899,
29906,
29900,
742,
13,
18884,
525,
29953,
29909,
742,
13,
18884,
318,
1727,
13,
9651,
4514,
13,
4706,
4514,
13,
4706,
363,
6389,
297,
4319,
29918,
5085,
29901,
13,
9651,
411,
11451,
1688,
29889,
336,
4637,
29898,
13,
18884,
7865,
2392,
29892,
13,
18884,
1993,
2433,
12313,
3244,
770,
29915,
13,
632,
1125,
13,
18884,
260,
4003,
29889,
29933,
14339,
29889,
657,
29918,
7097,
29918,
6799,
10456,
5085,
29897,
13,
13,
1678,
732,
7959,
5696,
13,
1678,
822,
1243,
29918,
657,
29918,
7097,
29918,
6799,
29918,
20965,
29918,
2311,
7295,
13,
4706,
4319,
29918,
2311,
353,
525,
29896,
29906,
29929,
29900,
29899,
29941,
29941,
29915,
13,
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src/TestDice.py | Yamanama/CodeMonkeyApplication | 0 | 14519 | import unittest
from Dice import Dice
class TestDice(unittest.TestCase):
def setUp(self):
self.sides = 8
self.dice = Dice(self.sides)
def test_roll(self):
for i in range(1000):
self.assertLessEqual(self.dice.roll(), self.sides)
def test_error(self):
self.assertRaises(ValueError, Dice, 0)
if __name__ == '__main__': # pragma no cover
unittest.main()
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Interfas Grafica VIII (GUI)/InterfasGraficaVIII.py | BrianMarquez3/Python-Course | 20 | 45487 | # Interfas Grafica VIII
# Operacion Matematicas
from tkinter import *
raiz = Tk()
miFrame=Frame(raiz)
miFrame.pack()
operacion =""
resultado=0
#Entry
#------------------------------Pantalla---------------------------------
numeroPantalla=StringVar()
pantalla=Entry(miFrame, textvariable=numeroPantalla)
pantalla.grid(row=1, column=1, padx=10, pady=10, columnspan=4) #Espaciador
pantalla.config(background="black",fg="#2EF907", justify="right", width=30)
#--------------------------Pulsaciones teclado---------------------------
def numeroPulsado(num):
global operacion
if operacion!="":
numeroPantalla.set(num)
operacion=""
else:
numeroPantalla.set(numeroPantalla.get() + num)
#------------------------------Funcion Suma------------------------------
def suma(num):
global operacion
global resultado
resultado=resultado+int(num)
operacion="suma"
numeroPantalla.set(resultado)
#------------------------------Funcion Resultado------------------------------
def el_resultado():
global resultado
numeroPantalla.set(resultado+int(numeroPantalla.get()))
resultado=0
#-------------------------------1 Fila-----------------------------------
buton7=Button(miFrame, text="7", width=7, height=3, command=lambda:numeroPulsado("7"))
buton7.grid(row=2, column=1)
buton8=Button(miFrame, text="8", width=7, height=3, command=lambda:numeroPulsado("8"))
buton8.grid(row=2, column=2)
buton9=Button(miFrame, text="9", width=7, height=3, command=lambda:numeroPulsado("9"))
buton9.grid(row=2, column=3)
botonDiv=Button(miFrame, text="/", width=7, height=3)
botonDiv.grid(row=2, column=4)
#-------------------------------2 Fila-----------------------------------
buton4=Button(miFrame, text="4", width=7, height=3, command=lambda:numeroPulsado("4"))
buton4.grid(row=3, column=1)
buton5=Button(miFrame, text="5", width=7, height=3, command=lambda:numeroPulsado("5"))
buton5.grid(row=3, column=2)
buton6=Button(miFrame, text="6", width=7, height=3, command=lambda:numeroPulsado("6"))
buton6.grid(row=3, column=3)
botonMul=Button(miFrame, text="*", width=7, height=3)
botonMul.grid(row=3, column=4)
#-------------------------------3 Fila-----------------------------------
buton1=Button(miFrame, text="1", width=7, height=3, command=lambda:numeroPulsado("1"))
buton1.grid(row=4, column=1)
buton2=Button(miFrame, text="2", width=7, height=3, command=lambda:numeroPulsado("2"))
buton2.grid(row=4, column=2)
buton3=Button(miFrame, text="3", width=7, height=3 , command=lambda:numeroPulsado("3"))
buton3.grid(row=4, column=3)
botonRes=Button(miFrame, text="-",width=7, height=3)
botonRes.grid(row=4, column=4)
#-------------------------------4 Fila-----------------------------------
buton0=Button(miFrame, text="0", width=7, height=3, command=lambda:numeroPulsado("0"))
buton0.grid(row=5, column=1)
butonComa=Button(miFrame, text=".", width=7, height=3)
butonComa.grid(row=5, column=2)
butonIgual=Button(miFrame, text="=", width=7, height=3, command=lambda:el_resultado())
butonIgual.grid(row=5, column=3)
botonSuma=Button(miFrame, text="+", width=7, height=3, command=lambda:suma(numeroPantalla.get()))
botonSuma.grid(row=5, column=4)
raiz.mainloop()
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data/objects/sample.py | predictive-analytics-lab/tiny-comparison-framework | 0 | 11491 | <filename>data/objects/sample.py
from data.objects.data import Data
class Sample(Data):
"""
A way to sample from a dataset for testing purposes.
"""
def __init__(self, data, num = 100):
self.data = data
self.dataset_name = data.get_dataset_name()
self.class_attr = data.get_class_attribute()
self.positive_class_val = data.get_positive_class_val("") # sigh
self.sensitive_attrs = data.get_sensitive_attributes()
self.privileged_class_names = data.get_privileged_class_names("") # sigh
self.categorical_features = data.get_categorical_features()
self.features_to_keep = data.get_features_to_keep()
self.missing_val_indicators = data.get_missing_val_indicators()
self.num_to_sample = num
def data_specific_processing(self, dataframe):
dataframe = self.data.data_specific_processing(dataframe)
return dataframe.sample(n = self.num_to_sample, replace=True)
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Numpy/Numpy Basics.py | Akshat-MS/DataScience-Learning | 0 | 180530 | #!/usr/bin/env python
# coding: utf-8
# # NumPy
#
#
# In[32]:
# NumPy is a library for scientific computations in Python.
# Numpy is one of the packages you have to know if you're going to do data science with Python.
# It is a Python library that provides support for large, multidimensional arrays along with masked
# arrays and matrices, and provides extensive functions for performing array manipulation, including
# mathematical, logical, and shape calculations, sorting, selecting, I/O, discrete Fourier transforms,
# linear algebra, basic statistical operations, random simulations, and so on.
# In[3]:
# Importing the Numpy library
import numpy as np
# In[5]:
# Numpy version
np.__version__
# # Function - numpy.array()
# In[6]:
# Function - numpy.array() (Note only most frequently parameters are explain below)
# numpy.array(object, dtype=None, *, copy=True, order='K', subok=False, ndmin=0, like=None)
# Parameters :
# object : array_like
# An array, any object exposing the array interface, an object whose __array__ method returns an array,
# or any (nested) sequence. If object is a scalar, a 0-dimensional array containing object is returned.
# Example - list object [1,2,3] or list of tuple [(1,2,3),(4,5,6)]
# dtype : data-type (optional)
# The desired data-type for the array. If not given, then the type will be determined as the minimum
# type required to hold the objects in the sequence.
# Example - dtype - float or str
# In[7]:
a = np.array([1,2,3])
b = np.array([(1,2,3),(6,7,8)],dtype = float)
c = np.array([[(1,2,3),(4,5,6)],[(7,8,9),(10,11,12)]], dtype= str)
# In[8]:
print(a, " \t" , type(a))
print("\n",b, " \t" , type(b))
print("\n",c, " \t" , type(c))
# # Numpy supports - element-wise operations
# In[9]:
# When a*2 is used, it performs element-wise operations rather than duplicating the content as with lists.
print(a*2)
print(b*2)
# # Function required for inspecting the Numpy Array
# - a.shape
# - a.ndim
# - a.size
# - a.dtype
# - a.dtype.name
# - a.astype(float)
# In[10]:
# a.shape - Tuple of array dimensions.
## The shape property is usually used to get the current shape of an array
## Example - (3,) - What is the magnitude of each dimension.
c.shape
# In[11]:
# a.ndim - Dimension of the array (1d,2d or nth array)
## Example - a.ndim - Array of dimension 1 (1d).
c.ndim
# In[12]:
# a.size - Number of elements in the array.
## Equal to np.prod(a.shape), i.e., the product of the array’s dimensions.
## Example c.size - shape of c is (2,2,3) = 2*2*3 = 12
c.size
# In[13]:
# a.dtype - Data-type of the array’s elements.
## Example a.dtype - dtype('int32') and b.dtype - dtype('float64')
b.dtype
# In[14]:
# a.dtype.name - A bit-width name for this data-type.
## Un-sized flexible data-type objects do not have this attribute.
## Example x = np.dtype(float) x.name is float64
x = np.dtype(float)
y = np.dtype([('a', np.int32, 8), ('b', np.float64, 6)])
print(x.name,y.name)
# In[15]:
# a.astype(float)
## Convert the array's datatype according to the parameter given
## b.astype - When creating the array b, we used float, and then used astype to convert to integer.
b.astype(int)
# # Different methods to Initialize the numpy array
# ## numpy.arange
# In[16]:
# numpy.arange([start, ]stop, [step, ]dtype=None, *, like=None)
## Return evenly spaced values within a given interval.
## Values are generated within the half-open interval [start, stop)
## (In other words, the interval including start but excluding stop).
## For integer arguments the function is equivalent to the Python built-in range function,
## but returns an ndarray rather than a list.
print(np.arange(0,10,2,dtype = int))
print(np.arange(0,10,0.5,dtype=float))
# ## numpy.linspace
# In[17]:
# numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)[source]
## Return evenly spaced numbers over a specified interval.
## Returns num evenly spaced samples, calculated over the interval [start, stop].
## The endpoint of the interval can optionally be excluded.
print(np.linspace(2.0, 3.0, num=5))
print(np.linspace(2.0, 3.0, num=5, endpoint=False))
print(np.linspace(2.0, 3.0, num=5, retstep=True))
# ## Difference between the linspace and arange.
# In[18]:
# Difference between the linspace and arange.
## arange allow you to define the size of the step. linspace allow you to define the number of steps.
## Example where arange might fail are -
print(" Using arange ",np.arange(0, 5, 0.5, dtype=int))
print(" Using arange ",np.arange(-3, 3, 0.5, dtype=int))
print(" Using Linspace ", np.linspace(0, 5, num = 5))
print(" Using Linspace ",np.linspace(-3, 3,num = 5))
# ## Difference between numpy Array and Lists
# |Numpy Array|List|
# |-----|-------|
# |Numpy data structures consume less memory|List take more memory than numpy array|
# |Numpy are faster |Lists are slower as compared to numpy array|
# |NumPy have optimized functions such as linear algebra operations built in||
# |Element wise operation is possible||
# |Array are by default Homogeneous, which means data inside an array must be of the same Datatype.|A list can store different data types|
# ||A list can consist of different nested data size|
# |We can create a N-dimensional array in python using numpy.array().||
# ||A list is easier to modify|
# |Array can handle mathematical operations|A list cannot directly handle a mathematical operations|
# ## numpy.zeros
# In[25]:
# numpy.zeros(shape, dtype=float, order='C', *, like=None)
## Return (ndarray) a new array of given shape and type, filled with zeros.
arr_1d_zeros = np.zeros(5)
arr_2d_zeros = np.zeros((2,5),dtype="int64")
arr_3d_zeros = np.zeros((2,3,4),dtype = int)
# In[31]:
print("\n 1D Array\n",arr_1d_zeros)
print("\n 2D Array\n", arr_2d_zeros)
print("\n 3D Array\n",arr_3d_zeros)
# ## numpy.ones
# In[32]:
# numpy.ones(shape, dtype=None, order='C', *, like=None)
## Return a new array of given shape and type, filled with ones.
arr_1d_ones = np.ones(5)
arr_2d_ones = np.ones((2,5),dtype="int64")
arr_3d_ones = np.ones((2,3,4),dtype = int)
# In[33]:
print("\n 1D Array\n",arr_1d_ones)
print("\n 2D Array\n", arr_2d_ones)
print("\n 3D Array\n",arr_3d_ones)
# ## numpy.full
# In[35]:
# numpy.full(shape, fill_value, dtype=None, order='C', *, like=None)
## Return a new array of given shape and type, filled with fill_value.
arr_1d_full = np.full(2, np.inf)
arr_2d_full = np.full((2, 2), 5)
arr_3d_full = np.full((2, 2,2), [1, 2])
# In[36]:
print("\n 1D Array\n",arr_1d_full)
print("\n 2D Array\n", arr_2d_full)
print("\n 3D Array\n",arr_3d_full)
# ## numpy.eye
# In[37]:
# numpy.eye(N, M=None, k=0, dtype=<class 'float'>, order='C', *, like=None)
## Return a 2-D array with ones on the diagonal and zeros elsewhere
arr_2d_diag0 = np.eye(2, dtype=int)
arr_2d_diag1 = np.eye(3, k=1)
# In[39]:
print("\n 2D Array\n", arr_2d_diag0)
print("\n 2D Array\n", arr_2d_diag1)
# ## random.random
# In[40]:
# random.random(size=None)
## Return random floats in the half-open interval [0.0, 1.0).
## Alias for random_sample to ease forward-porting to the new random API.
np.random.random()
# # Array Manipulation
#
# ## numpy.transpose
# In[55]:
# numpy.transpose(a, axes=None)
# Reverse or permute the axes of an array; returns the modified array.
# Parameters | aarray_like | Input array.
# axes | tuple or list of ints, optional
# If specified, it must be a tuple or list which contains a permutation of [0,1,..,N-1] where N is the
# number of axes of a. The i’th axis of the returned array will correspond to the axis numbered
# axes[i] of the input. If not specified, defaults to range(a.ndim)[::-1], which reverses the order
# of the axes.
x = np.arange(4).reshape((2,2))
print(x)
np.transpose(x)
# In[59]:
x = np.ones((1, 2, 3))
print("Original Array\n",x)
print("\n After Transpose \n",np.transpose(x, (1, 0, 2)))
# ## numpy.vstack
# In[44]:
# numpy.vstack(tup)
# Stack arrays in sequence vertically (row wise).
# Parameters | tup | sequence of ndarrays
# The arrays must have the same shape along all but the first axis.
# 1-D arrays must have the same length.
# Returns | stacked | ndarray
# The array formed by stacking the given arrays, will be at least 2-D.
top_stack = np.linspace(0, 3, 4).reshape(2,2)
bottom_stack = np.linspace(5, 8, 4).reshape(2,2)
vstack = np.vstack((top_stack,bottom_right))
# In[47]:
print("Array \n",top_stack)
print("\nArray \n",bottom_right)
print("\nMerged Array \n",vstack)
# ## numpy.hstack
# In[48]:
# numpy.hstack(tup)
# Stack arrays in sequence horizontally (column wise).
# Parameters | tup | sequence of ndarrays
# The arrays must have the same shape along all but the second axis,
#except 1-D arrays which can be any length.
# Returns | stacked | ndarray
# The array formed by stacking the given arrays.
left_stack = np.linspace(0, 3, 4).reshape(2,2)
right_stack = np.linspace(5, 8, 4).reshape(2,2)
hstack = np.hstack((left_stack,right_stack))
# In[49]:
print("Array \n",left_stack)
print("\nArray \n",right_stack)
print("\nMerged Array \n",hstack)
# ## numpy.concatenate
# In[51]:
# numpy.concatenate((a1, a2, ...), axis=0, out=None, dtype=None, casting="same_kind")
# Join a sequence of arrays along an existing axis
# Parameters | a1, a2, …sequence of array_like
# The arrays must have the same shape, except in the dimension corresponding to axis
# (the first, by default).
# axis | int, optional
# The axis along which the arrays will be joined. If axis is None, arrays are flattened before use.
# Default is 0.
# Returns | res | ndarray | he concatenated array.
a = np.array([[1, 2], [3, 4]])
b = np.array([[5, 6]])
np.concatenate((a, b), axis=0)
# In[52]:
np.concatenate((a, b.T), axis=1)
# In[53]:
np.concatenate((a, b), axis=None)
# In[ ]:
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src/matchingframework/scores/clusters.py | quoctoanpk2511/matching-framework | 0 | 118801 | import abc
class Clustering:
def add_matcher(self, matcher):
"""
Add the match object on the Clustering.
Args:
matcher: matchingframework.match.matchers.Matcher
Returns: None
"""
self.matcher = matcher
"""The matcher object"""
@abc.abstractmethod
def analyze(self):
"""
Analyze data using Cluster Analysis.
"""
def add_cluster(self):
"""
Adding cluster results to two matcher's dataset
"""
cluster_left, cluster_right = self.split_list_records()
self.matcher.left_data.df['match_cluster_id'] = cluster_left
self.matcher.right_data.df['match_cluster_id'] = cluster_right
def split_list_records(self):
"""
Get the split point.
"""
part = len(self.matcher.left_data.df['id_left'])
return self.matcher.clusters[:part], self.matcher.clusters[part:]
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packages/augur-core/tests/trading/test_affiliates.py | joeykrug/augur | 0 | 72876 | <filename>packages/augur-core/tests/trading/test_affiliates.py<gh_stars>0
#!/usr/bin/env python
from eth_tester.exceptions import TransactionFailed
from pytest import raises, fixture, mark
from utils import fix, AssertLog, EtherDelta, TokenDelta, BuyWithCash, nullAddress, longTo32Bytes
from constants import YES, NO
from old_eth_utils import ecsign, sha3, normalize_key, int_to_32bytearray, bytearray_to_bytestr, zpad
def test_fingerprint(kitchenSinkFixture, universe, cash, market):
affiliates = kitchenSinkFixture.contracts['Affiliates']
affiliateValidator = kitchenSinkFixture.contracts['AffiliateValidator']
shareToken = kitchenSinkFixture.contracts['ShareToken']
accountFingerprint = longTo32Bytes(11)
affiliateFingerprint = longTo32Bytes(12)
account = kitchenSinkFixture.accounts[0]
affiliate = kitchenSinkFixture.accounts[1]
affiliates.setFingerprint(accountFingerprint, sender=account)
affiliates.setFingerprint(affiliateFingerprint, sender=affiliate)
affiliates.setReferrer(affiliate)
# Confirm affiliate fees begin at 0 for the referrer
assert market.affiliateFeesAttoCash(affiliate) == 0
numSets = 10
cost = numSets * market.getNumTicks()
cash.faucet(cost)
shareToken.buyCompleteSets(market.address, account, numSets)
shareToken.sellCompleteSets(market.address, account, account, numSets, accountFingerprint)
expectedAffiliateFees = cost * .0025
expectedAffiliateFees *= .8
assert market.affiliateFeesAttoCash(affiliate) == expectedAffiliateFees
# If we pass the affiliate fingerprint we will see that the affiliate fees do not apply and will remain what they were before complete set sale
cash.faucet(cost)
shareToken.buyCompleteSets(market.address, account, numSets)
shareToken.sellCompleteSets(market.address, account, account, numSets, affiliateFingerprint)
assert market.affiliateFeesAttoCash(affiliate) == expectedAffiliateFees
def test_affiliate_validator(kitchenSinkFixture, universe, cash):
affiliates = kitchenSinkFixture.contracts['Affiliates']
affiliateValidator = kitchenSinkFixture.contracts['AffiliateValidator']
shareToken = kitchenSinkFixture.contracts['ShareToken']
market = kitchenSinkFixture.createReasonableYesNoMarket(universe, affiliateValidator = affiliateValidator.address)
accountFingerprint = longTo32Bytes(11)
affiliateFingerprint = longTo32Bytes(12)
account = kitchenSinkFixture.accounts[0]
affiliate = kitchenSinkFixture.accounts[1]
affiliateValidatorOperator = kitchenSinkFixture.accounts[5]
affiliateValidatorOperatorPrivKey = kitchenSinkFixture.privateKeys[5]
affiliates.setFingerprint(accountFingerprint, sender=account)
affiliates.setFingerprint(affiliateFingerprint, sender=affiliate)
affiliates.setReferrer(affiliate)
accountKey = longTo32Bytes(21)
salt = 0
accountHash = affiliateValidator.getKeyHash(accountKey, salt)
# A bad signature will be rejected
with raises(TransactionFailed):
affiliateValidator.addKey(accountKey, salt, longTo32Bytes(0), longTo32Bytes(0), 8, sender=account)
# This includes being signed by a non operator. So the same sig will fail initially but work once the signer is approved as an operator
r, s, v = signHash(accountHash, affiliateValidatorOperatorPrivKey)
with raises(TransactionFailed):
affiliateValidator.addKey(accountKey, salt, r, s, v, sender=account)
# Succesfully add the key for the trader account
affiliateValidator.addOperator(affiliateValidatorOperator)
affiliateValidator.addKey(accountKey, salt, r, s, v, sender=account)
# Re-using a salt will not work
with raises(TransactionFailed):
affiliateValidator.addKey(accountKey, salt, r, s, v, sender=account)
affiliateKey = longTo32Bytes(22)
salt += 1
affiliateHash = affiliateValidator.getKeyHash(affiliateKey, salt)
r, s, v = signHash(affiliateHash, affiliateValidatorOperatorPrivKey)
affiliateValidator.addKey(affiliateKey, salt, r, s, v, sender=affiliate)
# Confirm affiliate fees begin at 0 for the referrer
assert market.affiliateFeesAttoCash(affiliate) == 0
numSets = 10
cost = numSets * market.getNumTicks()
cash.faucet(cost)
shareToken.buyCompleteSets(market.address, account, numSets)
shareToken.sellCompleteSets(market.address, account, account, numSets, accountFingerprint)
expectedAffiliateFees = cost * .0025
expectedAffiliateFees *= .8
assert market.affiliateFeesAttoCash(affiliate) == expectedAffiliateFees
# If we try to use an account that has registered an affiliate key which is the same as the referrer the affiliate fees do not apply and will remain what they were before complete set sale
dupeAccount = kitchenSinkFixture.accounts[2]
affiliates.setReferrer(affiliate, sender=dupeAccount)
salt += 1
affiliateHash = affiliateValidator.getKeyHash(affiliateKey, salt)
r, s, v = signHash(affiliateHash, affiliateValidatorOperatorPrivKey)
affiliateValidator.addKey(affiliateKey, salt, r, s, v, sender=dupeAccount)
cash.faucet(cost, sender=dupeAccount)
shareToken.buyCompleteSets(market.address, dupeAccount, numSets, sender=dupeAccount)
shareToken.sellCompleteSets(market.address, dupeAccount, dupeAccount, numSets, accountFingerprint, sender=dupeAccount)
assert market.affiliateFeesAttoCash(affiliate) == expectedAffiliateFees
# It will also not work if the account or the referrer does not have a key registered with the validator
noKeyAccount = kitchenSinkFixture.accounts[3]
affiliates.setReferrer(affiliate, sender=noKeyAccount)
cash.faucet(cost, sender=noKeyAccount)
shareToken.buyCompleteSets(market.address, noKeyAccount, numSets, sender=noKeyAccount)
shareToken.sellCompleteSets(market.address, noKeyAccount, noKeyAccount, numSets, accountFingerprint, sender=noKeyAccount)
assert market.affiliateFeesAttoCash(affiliate) == expectedAffiliateFees
def signHash(hash, private_key):
key = normalize_key(private_key.to_hex())
v, r, s = ecsign(sha3("\x19Ethereum Signed Message:\n32".encode('utf-8') + hash), key)
return zpad(bytearray_to_bytestr(int_to_32bytearray(r)), 32), zpad(bytearray_to_bytestr(int_to_32bytearray(s)), 32), v | [
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mainnotes/migrations/0001_initial.py | gokulvibe/NoteIt-NoteMaker-Django | 1 | 71073 | <filename>mainnotes/migrations/0001_initial.py<gh_stars>1-10
# Generated by Django 3.1.7 on 2021-03-30 08:22
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import encrypted_fields.fields
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='Notes',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=300)),
('description', models.TextField()),
('created_date', models.DateTimeField(auto_now_add=True)),
('recently_modified_date', models.DateTimeField(auto_now=True)),
('hidden_note', models.BooleanField(default=False)),
('trashed_note', models.BooleanField(default=False)),
('owner', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
migrations.CreateModel(
name='Image',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('image', models.ImageField(upload_to='notesImages/')),
('note', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='mainnotes.notes')),
],
),
migrations.CreateModel(
name='HiddenNotePassword',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('hidden_note_password', encrypted_fields.fields.EncryptedCharField(max_length=50)),
('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
]
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] |
elyra/pipeline/component_parser_kfp.py | rachaelhouse/elyra | 0 | 20440 | #
# Copyright 2018-2021 Elyra Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from types import SimpleNamespace
from typing import Any
from typing import Dict
from typing import List
from typing import Optional
import yaml
from elyra.pipeline.component import Component
from elyra.pipeline.component import ComponentParameter
from elyra.pipeline.component import ComponentParser
class KfpComponentParser(ComponentParser):
_component_platform = "kfp"
_file_types = [".yaml"]
def parse(self, registry_entry: SimpleNamespace) -> Optional[List[Component]]:
# Get YAML object from component definition
component_yaml = self._read_component_yaml(registry_entry)
if not component_yaml:
return None
# Assign component_id and description
component_id = self.get_component_id(registry_entry.location, component_yaml.get('name', ''))
description = ""
if component_yaml.get('description'):
# Remove whitespace characters and replace with spaces
description = ' '.join(component_yaml.get('description').split())
component_properties = self._parse_properties(component_yaml)
component = Component(id=component_id,
name=component_yaml.get('name'),
description=description,
runtime=self.component_platform,
location_type=registry_entry.location_type,
location=registry_entry.location,
properties=component_properties,
categories=registry_entry.categories)
return [component]
def _parse_properties(self, component_yaml: Dict[str, Any]) -> List[ComponentParameter]:
properties: List[ComponentParameter] = list()
# NOTE: Currently no runtime-specific properties are needed
# properties.extend(self.get_runtime_specific_properties())
# Then loop through and create custom properties
input_params = component_yaml.get('inputs', [])
for param in input_params:
# KFP components default to being required unless otherwise stated.
# Reference: https://www.kubeflow.org/docs/components/pipelines/reference/component-spec/#interface
required = True
if "optional" in param and param.get('optional') is True:
required = False
# Assign type, default to string
data_type = param.get('type', 'string')
# Set description and include parsed type information
description = self._format_description(description=param.get('description', ''),
data_type=data_type)
# Change type to reflect the type of input (inputValue vs inputPath)
data_type = self._get_adjusted_parameter_fields(component_body=component_yaml,
io_object_name=param.get('name'),
io_object_type="input",
parameter_type=data_type)
data_type, control_id, default_value = self.determine_type_information(data_type)
# Get value if provided
value = param.get('default', '')
ref = param.get('name').lower().replace(' ', '_')
properties.append(ComponentParameter(id=ref,
name=param.get('name'),
data_type=data_type,
value=(value or default_value),
description=description,
control_id=control_id,
required=required))
return properties
def get_runtime_specific_properties(self) -> List[ComponentParameter]:
"""
Define properties that are common to the KFP runtime.
"""
return [
ComponentParameter(
id="runtime_image",
name="Runtime Image",
data_type="string",
value="",
description="Docker image used as execution environment.",
control="readonly",
required=True,
)
]
def _read_component_yaml(self, registry_entry: SimpleNamespace) -> Optional[Dict[str, Any]]:
"""
Convert component_definition string to YAML object
"""
try:
return yaml.safe_load(registry_entry.component_definition)
except Exception as e:
self.log.debug(f"Could not read definition for component at "
f"location: '{registry_entry.location}' -> {str(e)}")
return None
def _get_adjusted_parameter_fields(self,
component_body: Dict[str, Any],
io_object_name: str,
io_object_type: str,
parameter_type: str) -> str:
"""
Change the parameter ref according if it is a KFP path parameter (as opposed to a value parameter)
"""
adjusted_type = parameter_type
if "implementation" in component_body and "container" in component_body['implementation']:
if "command" in component_body['implementation']['container']:
for command in component_body['implementation']['container']['command']:
if isinstance(command, dict) and list(command.values())[0] == io_object_name and \
list(command.keys())[0] == f"{io_object_type}Path":
adjusted_type = "file"
if "args" in component_body['implementation']['container']:
for arg in component_body['implementation']['container']['args']:
if isinstance(arg, dict) and list(arg.values())[0] == io_object_name and \
list(arg.keys())[0] == f"{io_object_type}Path":
adjusted_type = "file"
return adjusted_type
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] |
setup.py | akrito/cursors | 1 | 160573 | <filename>setup.py
from setuptools import setup
import os
try:
long_desc = open(os.path.join(os.path.dirname(__file__), 'README.md')).read()
except (IOError, OSError):
long_desc = ''
setup(
name = "cursors",
version = '0.1',
url = 'http://github.com/akrito/cursors',
author = '<NAME>',
author_email = '<EMAIL>',
description = 'Cursors takes SQL and gives you a sequence of named tuples.',
long_description = long_desc,
install_requires = ['psycopg2'],
py_modules = ['cursors'],
)
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source/ui/button.py | HugoPFe/Project-Asteroids | 0 | 171736 | import pygame
from media.paths import button_font
class Button:
def __init__(self, **kwargs):
"""
Creates a new Button istance for UI.
Accepted Parameters: screen, x, y, width, height, text, padding, command.
"""
self.screen = kwargs.get('screen')
self.x = kwargs.get('x')
self.y = kwargs.get('y')
self.width = kwargs.get('width')
self.height = kwargs.get('height')
self.text = kwargs.get('text')
self.padding = kwargs.get('padding')
self.command = kwargs.get('command')
for k, v in kwargs.items():
if v is not None:
self.__dict__[k] = v
else:
self.__dict__['text'] = 'Text'
self.__dict__['padding'] = 1
self.split_text = False
if '\n' in self.text:
self.split_text = True
splitted_text = self.text.split('\n')
self.text1 = splitted_text[0]
self.text2 = splitted_text[1]
self.current_color = pygame.Color('#4948D9')
self.clicked = set()
# Button Border
self.border = pygame.Surface((self.width, self.height))
self.border.fill(self.current_color)
self.bd_rect = self.border.get_rect(center=(self.x, self.y))
# Button Background
self.background = pygame.Surface((self.width*0.95, self.height*0.9))
self.background.fill((0, 0, 0))
self.rect = self.background.get_rect()
# Text
self.txt_size = int((self.width+self.height)*0.2)-self.padding
self.font = pygame.font.Font(button_font, self.txt_size, bold=True)
if self.split_text:
text_space = 10
self.screen_text1 = self.font.render(self.text1, True, (255, 255, 255), (0, 0, 0))
self.screen_text2 = self.font.render(self.text2, True, (255, 255, 255), (0, 0, 0))
self.txt_rect1 = self.screen_text1.get_rect(center=(self.rect.centerx, self.rect.centery-10))
self.txt_rect2 = self.screen_text2.get_rect(center=(self.rect.centerx, self.rect.centery+text_space))
else:
self.screen_text = self.font.render(self.text, True, (255, 255, 255), (0, 0, 0))
self.txt_rect = self.screen_text.get_rect(center=(self.rect.centerx, self.rect.centery))
def render(self):
self.mouse_above()
if self.split_text:
self.background.blit(self.screen_text1, self.txt_rect1)
self.background.blit(self.screen_text2, self.txt_rect2)
else:
self.background.blit(self.screen_text, self.txt_rect)
self.border.blit(self.background, self.rect)
self.screen.blit(self.border, self.bd_rect)
def mouse_above(self):
is_above = self.bd_rect.collidepoint(pygame.mouse.get_pos())
if is_above:
self.mouse_click()
self.current_color = self.current_color.lerp('#9848D9', 0.5)
else:
self.clicked.clear()
self.current_color = self.current_color.lerp('#4948D9', 0.5)
self.border.fill(self.current_color)
def mouse_click(self):
bt_pressed = pygame.mouse.get_pressed(3)
if bt_pressed[0]:
self.clicked.add(True)
self.background.fill('white')
if self.split_text:
self.screen_text1 = self.font.render(self.text1, True, (0, 0, 0), (255, 255, 255))
self.screen_text2 = self.font.render(self.text2, True, (0, 0, 0), (255, 255, 255))
else:
self.screen_text = self.font.render(self.text, True, (0, 0, 0), (255, 255, 255))
else:
self.background.fill('black')
if self.split_text:
self.screen_text1 = self.font.render(self.text1, True, (255, 255, 255), (0, 0, 0))
self.screen_text2 = self.font.render(self.text2, True, (255, 255, 255), (0, 0, 0))
else:
self.screen_text = self.font.render(self.text, True, (255, 255, 255), (0, 0, 0))
if self.clicked == {True}:
self.clicked.clear()
try:
self.command()
except TypeError:
pass
__all__ = ['Button']
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] |
tests/retrieval/helpers.py | sameetsinghsidhu/metrics | 0 | 1613173 | <gh_stars>0
# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from functools import partial
from typing import Callable, Dict, List, Tuple, Type, Union
import numpy as np
import pytest
import torch
from numpy import array
from torch import Tensor, tensor
from tests.helpers import seed_all
from tests.helpers.testers import Metric, MetricTester
from tests.retrieval.inputs import _input_retrieval_scores as _irs
from tests.retrieval.inputs import _input_retrieval_scores_all_target as _irs_all
from tests.retrieval.inputs import _input_retrieval_scores_empty as _irs_empty
from tests.retrieval.inputs import _input_retrieval_scores_extra as _irs_extra
from tests.retrieval.inputs import _input_retrieval_scores_mismatching_sizes as _irs_mis_sz
from tests.retrieval.inputs import _input_retrieval_scores_mismatching_sizes_func as _irs_mis_sz_fn
from tests.retrieval.inputs import _input_retrieval_scores_no_target as _irs_no_tgt
from tests.retrieval.inputs import _input_retrieval_scores_non_binary_target as _irs_non_binary
from tests.retrieval.inputs import _input_retrieval_scores_wrong_targets as _irs_bad_tgt
seed_all(42)
# a version of get_group_indexes that depends on NumPy is here to avoid this dependency for the full library
def get_group_indexes(indexes: Union[Tensor, np.ndarray]) -> List[Union[Tensor, np.ndarray]]:
"""
Given an integer `torch.Tensor` or `np.ndarray` `indexes`, return a `torch.Tensor` or `np.ndarray` of indexes for
each different value in `indexes`.
Args:
indexes: a `torch.Tensor` or `np.ndarray` of integers
Return:
A list of integer `torch.Tensor`s or `np.ndarray`s
Example:
>>> indexes = torch.tensor([0, 0, 0, 1, 1, 1, 1])
>>> get_group_indexes(indexes)
[tensor([0, 1, 2]), tensor([3, 4, 5, 6])]
"""
structure, dtype = (tensor, torch.long) if isinstance(indexes, Tensor) else (np.array, np.int64)
res = {}
for i, _id in enumerate(indexes):
_id = _id.item()
if _id in res:
res[_id] += [i]
else:
res[_id] = [i]
return [structure(x, dtype=dtype) for x in res.values()]
def _compute_sklearn_metric(
preds: Union[Tensor, array],
target: Union[Tensor, array],
indexes: np.ndarray = None,
metric: Callable = None,
empty_target_action: str = "skip",
reverse: bool = False,
**kwargs
) -> Tensor:
""" Compute metric with multiple iterations over every query predictions set. """
if indexes is None:
indexes = np.full_like(preds, fill_value=0, dtype=np.int64)
if isinstance(indexes, Tensor):
indexes = indexes.cpu().numpy()
if isinstance(preds, Tensor):
preds = preds.cpu().numpy()
if isinstance(target, Tensor):
target = target.cpu().numpy()
assert isinstance(indexes, np.ndarray)
assert isinstance(preds, np.ndarray)
assert isinstance(target, np.ndarray)
indexes = indexes.flatten()
preds = preds.flatten()
target = target.flatten()
groups = get_group_indexes(indexes)
sk_results = []
for group in groups:
trg, pds = target[group], preds[group]
if ((1 - trg) if reverse else trg).sum() == 0:
if empty_target_action == 'skip':
pass
elif empty_target_action == 'pos':
sk_results.append(1.0)
else:
sk_results.append(0.0)
else:
res = metric(trg, pds, **kwargs)
sk_results.append(res)
if len(sk_results) > 0:
return np.mean(sk_results)
return np.array(0.0)
def _concat_tests(*tests: Tuple[Dict]) -> Dict:
"""Concat tests composed by a string and a list of arguments."""
assert len(tests), "`_concat_tests` expects at least an argument"
assert all(tests[0]['argnames'] == x['argnames'] for x in tests[1:]), "the header must be the same for all tests"
return dict(argnames=tests[0]['argnames'], argvalues=sum((x['argvalues'] for x in tests), []))
_errors_test_functional_metric_parameters_default = dict(
argnames="preds,target,message,metric_args",
argvalues=[
# check input shapes are consistent (func)
(_irs_mis_sz_fn.preds, _irs_mis_sz_fn.target, "`preds` and `target` must be of the same shape", {}),
# check input tensors are not empty
(_irs_empty.preds, _irs_empty.target, "`preds` and `target` must be non-empty and non-scalar tensors", {}),
# check on input dtypes
(_irs.preds.bool(), _irs.target, "`preds` must be a tensor of floats", {}),
(_irs.preds, _irs.target.float(), "`target` must be a tensor of booleans or integers", {}),
# check targets are between 0 and 1
(_irs_bad_tgt.preds, _irs_bad_tgt.target, "`target` must contain `binary` values", {}),
]
)
_errors_test_functional_metric_parameters_k = dict(
argnames="preds,target,message,metric_args",
argvalues=[
(_irs.preds, _irs.target, "`k` has to be a positive integer or None", dict(k=-10)),
(_irs.preds, _irs.target, "`k` has to be a positive integer or None", dict(k=4.0)),
]
)
_errors_test_class_metric_parameters_no_pos_target = dict(
argnames="indexes,preds,target,message,metric_args",
argvalues=[
# check when error when there are no positive targets
(
_irs_no_tgt.indexes, _irs_no_tgt.preds, _irs_no_tgt.target,
"`compute` method was provided with a query with no positive target.", dict(empty_target_action="error")
),
]
)
_errors_test_class_metric_parameters_no_neg_target = dict(
argnames="indexes,preds,target,message,metric_args",
argvalues=[
# check when error when there are no negative targets
(
_irs_all.indexes, _irs_all.preds, _irs_all.target,
"`compute` method was provided with a query with no negative target.", dict(empty_target_action="error")
),
]
)
_errors_test_class_metric_parameters_default = dict(
argnames="indexes,preds,target,message,metric_args",
argvalues=[
(None, _irs.preds, _irs.target, "`indexes` cannot be None", dict(empty_target_action="error")),
# check when input arguments are invalid
(
_irs.indexes, _irs.preds, _irs.target, "`empty_target_action` received a wrong value `casual_argument`.",
dict(empty_target_action="casual_argument")
),
# check input shapes are consistent
(
_irs_mis_sz.indexes, _irs_mis_sz.preds, _irs_mis_sz.target,
"`indexes`, `preds` and `target` must be of the same shape", dict(empty_target_action="skip")
),
# check input tensors are not empty
(
_irs_empty.indexes, _irs_empty.preds,
_irs_empty.target, "`indexes`, `preds` and `target` must be non-empty and non-scalar tensors",
dict(empty_target_action="skip")
),
# check on input dtypes
(
_irs.indexes.bool(), _irs.preds, _irs.target, "`indexes` must be a tensor of long integers",
dict(empty_target_action="skip")
),
(
_irs.indexes, _irs.preds.bool(), _irs.target, "`preds` must be a tensor of floats",
dict(empty_target_action="skip")
),
(
_irs.indexes, _irs.preds, _irs.target.float(), "`target` must be a tensor of booleans or integers",
dict(empty_target_action="skip")
),
# check targets are between 0 and 1
(
_irs_bad_tgt.indexes, _irs_bad_tgt.preds, _irs_bad_tgt.target, "`target` must contain `binary` values",
dict(empty_target_action="skip")
),
]
)
_errors_test_class_metric_parameters_k = dict(
argnames="indexes,preds,target,message,metric_args",
argvalues=[
(_irs.index, _irs.preds, _irs.target, "`k` has to be a positive integer or None", dict(k=-10)),
]
)
_default_metric_class_input_arguments = dict(
argnames="indexes,preds,target",
argvalues=[
(_irs.indexes, _irs.preds, _irs.target),
(_irs_extra.indexes, _irs_extra.preds, _irs_extra.target),
(_irs_no_tgt.indexes, _irs_no_tgt.preds, _irs_no_tgt.target),
]
)
_default_metric_class_input_arguments_with_non_binary_target = dict(
argnames="indexes,preds,target",
argvalues=[
(_irs.indexes, _irs.preds, _irs.target),
(_irs_extra.indexes, _irs_extra.preds, _irs_extra.target),
(_irs_no_tgt.indexes, _irs_no_tgt.preds, _irs_no_tgt.target),
(_irs_non_binary.indexes, _irs_non_binary.preds, _irs_non_binary.target),
]
)
_default_metric_functional_input_arguments = dict(
argnames="preds,target",
argvalues=[
(_irs.preds, _irs.target),
(_irs_extra.preds, _irs_extra.target),
(_irs_no_tgt.preds, _irs_no_tgt.target),
]
)
_default_metric_functional_input_arguments_with_non_binary_target = dict(
argnames="preds,target",
argvalues=[
(_irs.preds, _irs.target),
(_irs_extra.preds, _irs_extra.target),
(_irs_no_tgt.preds, _irs_no_tgt.target),
(_irs_non_binary.preds, _irs_non_binary.target),
]
)
def _errors_test_class_metric(
indexes: Tensor,
preds: Tensor,
target: Tensor,
metric_class: Metric,
message: str = "",
metric_args: dict = None,
exception_type: Type[Exception] = ValueError,
kwargs_update: dict = None,
):
"""Utility function doing checks about types, parameters and errors.
Args:
indexes: torch tensor with indexes
preds: torch tensor with predictions
target: torch tensor with targets
metric_class: lightning metric class that should be tested
message: message that exception should return
metric_args: arguments for class initialization
exception_type: callable function that is used for comparison
kwargs_update: Additional keyword arguments that will be passed with indexes, preds and
target when running update on the metric.
"""
metric_args = metric_args or {}
kwargs_update = kwargs_update or {}
with pytest.raises(exception_type, match=message):
metric = metric_class(**metric_args)
metric(preds, target, indexes=indexes, **kwargs_update)
def _errors_test_functional_metric(
preds: Tensor,
target: Tensor,
metric_functional: Metric,
message: str = "",
exception_type: Type[Exception] = ValueError,
kwargs_update: dict = None,
):
"""Utility function doing checks about types, parameters and errors.
Args:
preds: torch tensor with predictions
target: torch tensor with targets
metric_functional: lightning functional metric that should be tested
message: message that exception should return
exception_type: callable function that is used for comparison
kwargs_update: Additional keyword arguments that will be passed with indexes, preds and
target when running update on the metric.
"""
kwargs_update = kwargs_update or {}
with pytest.raises(exception_type, match=message):
metric_functional(preds, target, **kwargs_update)
class RetrievalMetricTester(MetricTester):
def run_class_metric_test(
self,
ddp: bool,
indexes: Tensor,
preds: Tensor,
target: Tensor,
metric_class: Metric,
sk_metric: Callable,
dist_sync_on_step: bool,
metric_args: dict,
reverse: bool = False,
):
_sk_metric_adapted = partial(_compute_sklearn_metric, metric=sk_metric, reverse=reverse, **metric_args)
super().run_class_metric_test(
ddp=ddp,
preds=preds,
target=target,
metric_class=metric_class,
sk_metric=_sk_metric_adapted,
dist_sync_on_step=dist_sync_on_step,
metric_args=metric_args,
fragment_kwargs=True,
indexes=indexes, # every additional argument will be passed to metric_class and _sk_metric_adapted
)
def run_functional_metric_test(
self,
preds: Tensor,
target: Tensor,
metric_functional: Callable,
sk_metric: Callable,
metric_args: dict,
reverse: bool = False,
**kwargs,
):
_sk_metric_adapted = partial(_compute_sklearn_metric, metric=sk_metric, reverse=reverse, **metric_args)
super().run_functional_metric_test(
preds=preds,
target=target,
metric_functional=metric_functional,
sk_metric=_sk_metric_adapted,
metric_args=metric_args,
fragment_kwargs=True,
**kwargs,
)
def run_precision_test_cpu(
self,
indexes: Tensor,
preds: Tensor,
target: Tensor,
metric_module: Metric,
metric_functional: Callable,
):
def metric_functional_ignore_indexes(preds, target, indexes):
return metric_functional(preds, target)
super().run_precision_test_cpu(
preds=preds,
target=target,
metric_module=metric_module,
metric_functional=metric_functional_ignore_indexes,
metric_args={'empty_target_action': 'neg'},
indexes=indexes, # every additional argument will be passed to RetrievalMAP and _sk_metric_adapted
)
def run_precision_test_gpu(
self,
indexes: Tensor,
preds: Tensor,
target: Tensor,
metric_module: Metric,
metric_functional: Callable,
):
if not torch.cuda.is_available():
pytest.skip()
def metric_functional_ignore_indexes(preds, target, indexes):
return metric_functional(preds, target)
super().run_precision_test_gpu(
preds=preds,
target=target,
metric_module=metric_module,
metric_functional=metric_functional_ignore_indexes,
metric_args={'empty_target_action': 'neg'},
indexes=indexes, # every additional argument will be passed to RetrievalMAP and _sk_metric_adapted
)
@staticmethod
def run_metric_class_arguments_test(
indexes: Tensor,
preds: Tensor,
target: Tensor,
metric_class: Metric,
message: str = "",
metric_args: dict = None,
exception_type: Type[Exception] = ValueError,
kwargs_update: dict = None,
):
_errors_test_class_metric(
indexes=indexes,
preds=preds,
target=target,
metric_class=metric_class,
message=message,
metric_args=metric_args,
exception_type=exception_type,
**kwargs_update,
)
@staticmethod
def run_functional_metric_arguments_test(
preds: Tensor,
target: Tensor,
metric_functional: Callable,
message: str = "",
exception_type: Type[Exception] = ValueError,
kwargs_update: dict = None,
):
_errors_test_functional_metric(
preds=preds,
target=target,
metric_functional=metric_functional,
message=message,
exception_type=exception_type,
kwargs_update=kwargs_update,
)
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12714,
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2220,
284,
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11965,
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3646,
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3579,
19290,
29918,
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13,
13,
13,
1990,
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791,
10095,
2200,
3057,
261,
29898,
10095,
2200,
3057,
261,
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13,
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1688,
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13,
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1583,
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13,
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270,
6099,
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13,
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323,
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13,
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12714,
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1990,
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4737,
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13,
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2071,
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16414,
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519,
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1320,
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265,
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268,
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19668,
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11837,
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24244,
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3579,
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5085,
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2428,
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1990,
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270,
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1990,
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2248,
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13,
13,
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2428,
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2459,
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21970,
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284,
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284,
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17281,
29918,
2248,
267,
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13,
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12714,
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5085,
3790,
29915,
6310,
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5182,
29918,
2467,
2396,
525,
10052,
16675,
13,
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2248,
267,
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396,
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322,
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13,
13,
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323,
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13,
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323,
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13,
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12714,
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4737,
2200,
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13,
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12714,
29918,
2220,
284,
29901,
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519,
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13,
268,
1125,
13,
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565,
451,
4842,
305,
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29883,
6191,
29889,
275,
29918,
16515,
7295,
13,
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11451,
1688,
29889,
11014,
580,
13,
13,
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822,
12714,
29918,
2220,
284,
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17281,
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2248,
267,
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11965,
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3646,
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13,
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736,
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2220,
284,
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11965,
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3646,
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13,
13,
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2428,
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3389,
29918,
17990,
2459,
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1688,
29918,
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3746,
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13,
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4450,
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29922,
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13,
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13,
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12714,
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13,
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12714,
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284,
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284,
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17281,
29918,
2248,
267,
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13,
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12714,
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5085,
3790,
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6310,
29918,
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29918,
2467,
2396,
525,
10052,
16675,
13,
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2248,
267,
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396,
1432,
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674,
367,
4502,
304,
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791,
23827,
322,
903,
808,
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415,
287,
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13,
13,
1678,
732,
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5696,
13,
1678,
822,
1065,
29918,
16414,
29918,
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29918,
25699,
29918,
1688,
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13,
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18111,
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323,
6073,
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13,
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4450,
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323,
6073,
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13,
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3646,
29901,
323,
6073,
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13,
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12714,
29918,
1990,
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4737,
2200,
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13,
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2643,
29901,
851,
353,
12633,
13,
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12714,
29918,
5085,
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353,
6213,
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13,
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3682,
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1853,
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5167,
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2451,
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353,
7865,
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13,
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6213,
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13,
268,
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13,
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903,
12523,
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1990,
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13,
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2248,
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11965,
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13,
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13,
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12714,
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1990,
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16414,
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1990,
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13,
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2643,
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4906,
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13,
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13,
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323,
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12714,
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2220,
284,
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519,
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13,
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2643,
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851,
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12633,
13,
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3682,
29918,
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353,
7865,
2392,
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13,
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353,
6213,
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13,
268,
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13,
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903,
12523,
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1688,
29918,
2220,
284,
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16414,
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13,
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4450,
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29922,
11965,
29879,
29892,
13,
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3646,
29922,
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] |
mmdet-v2/tools/__tmp__/3.py | li-phone/DetectionCompetition | 0 | 113963 | <filename>mmdet-v2/tools/__tmp__/3.py<gh_stars>0
import collections
def equ(C1, C2):
for k1, v1 in C1.items():
if k1 not in C2 or C1[k1] != C2[k1]:
return False
return True
while True:
try:
n, m = list(map(int, input().split()))
Ai = list(map(int, input().split()))
Bi = list(map(int, input().split()))
res = []
for a in set(Ai):
for b in set(Bi):
x = b + m - a
Ci = [(_ + x) % m for _ in Ai]
C1 = dict(collections.Counter(Ci))
C2 = dict(collections.Counter(Bi))
if equ(C1, C2):
res.append(x)
print(min(res))
except EOFError:
break
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gnuradio-3.7.13.4/gr-wxgui/python/wxgui/stdgui2.py | v1259397/cosmic-gnuradio | 1 | 1614416 | #
# Copyright 2004 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your option)
# any later version.
#
# GNU Radio is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GNU Radio; see the file COPYING. If not, write to
# the Free Software Foundation, Inc., 51 Franklin Street,
# Boston, MA 02110-1301, USA.
#
'''A simple wx gui for GNU Radio applications'''
import ctypes
import wx
import sys
from gnuradio import gr
class stdapp (wx.App):
def __init__ (self, top_block_maker, title="GNU Radio", nstatus=2,
max_noutput_items=None):
self.top_block_maker = top_block_maker
self.title = title
self._nstatus = nstatus
self._max_noutput_items = max_noutput_items
# If we're on Linux, also enable multi-threading Xlib access
if sys.platform.startswith('linux'):
try:
x11 = ctypes.cdll.LoadLibrary('libX11.so')
x11.XInitThreads()
except:
print "Warning: failed to XInitThreads()"
# All our initialization must come before calling wx.App.__init__.
# OnInit is called from somewhere in the guts of __init__.
wx.App.__init__ (self, redirect=False)
def OnInit (self):
frame = stdframe (self.top_block_maker, self.title, self._nstatus)
frame.Show (True)
self.SetTopWindow (frame)
if(self._max_noutput_items is not None):
frame.top_block().start (self._max_noutput_items)
else:
frame.top_block().start ()
return True
class stdframe (wx.Frame):
def __init__ (self, top_block_maker, title="GNU Radio", nstatus=2):
# print "stdframe.__init__"
wx.Frame.__init__(self, None, -1, title)
self.CreateStatusBar (nstatus)
mainmenu = wx.MenuBar ()
menu = wx.Menu ()
item = menu.Append (200, 'E&xit', 'Exit')
self.Bind (wx.EVT_MENU, self.OnCloseWindow, item)
mainmenu.Append (menu, "&File")
self.SetMenuBar (mainmenu)
self.Bind (wx.EVT_CLOSE, self.OnCloseWindow)
self.panel = stdpanel (self, self, top_block_maker)
vbox = wx.BoxSizer(wx.VERTICAL)
vbox.Add(self.panel, 1, wx.EXPAND)
self.SetSizer(vbox)
self.SetAutoLayout(True)
vbox.Fit(self)
def OnCloseWindow (self, event):
self.top_block().stop()
self.top_block().wait()
self.Destroy ()
def top_block (self):
return self.panel.top_block
class stdpanel (wx.Panel):
def __init__ (self, parent, frame, top_block_maker):
# print "stdpanel.__init__"
wx.Panel.__init__ (self, parent, -1)
self.frame = frame
vbox = wx.BoxSizer (wx.VERTICAL)
self.top_block = top_block_maker (frame, self, vbox, sys.argv)
self.SetSizer (vbox)
self.SetAutoLayout (True)
vbox.Fit (self)
class std_top_block (gr.top_block):
def __init__ (self, parent, panel, vbox, argv):
# Call the hier_block2 constructor
# Top blocks have no inputs and outputs
gr.top_block.__init__(self, "std_top_block")
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ansys/dpf/core/operators/logic/identical_fc.py | TheGoldfish01/pydpf-core | 11 | 40214 | <reponame>TheGoldfish01/pydpf-core
"""
identical_fc
============
"""
from ansys.dpf.core.dpf_operator import Operator
from ansys.dpf.core.inputs import Input, _Inputs
from ansys.dpf.core.outputs import Output, _Outputs, _modify_output_spec_with_one_type
from ansys.dpf.core.operators.specification import PinSpecification, Specification
"""Operators from Ans.Dpf.Native plugin, from "logic" category
"""
class identical_fc(Operator):
"""Check if two fields container are identical.
available inputs:
- fields_containerA (FieldsContainer)
- fields_containerB (FieldsContainer)
- tolerance (float)
- small_value (float)
available outputs:
- boolean (bool)
- message (str)
Examples
--------
>>> from ansys.dpf import core as dpf
>>> # Instantiate operator
>>> op = dpf.operators.logic.identical_fc()
>>> # Make input connections
>>> my_fields_containerA = dpf.FieldsContainer()
>>> op.inputs.fields_containerA.connect(my_fields_containerA)
>>> my_fields_containerB = dpf.FieldsContainer()
>>> op.inputs.fields_containerB.connect(my_fields_containerB)
>>> my_tolerance = float()
>>> op.inputs.tolerance.connect(my_tolerance)
>>> my_small_value = float()
>>> op.inputs.small_value.connect(my_small_value)
>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.logic.identical_fc(fields_containerA=my_fields_containerA,fields_containerB=my_fields_containerB,tolerance=my_tolerance,small_value=my_small_value)
>>> # Get output data
>>> result_boolean = op.outputs.boolean()
>>> result_message = op.outputs.message()"""
def __init__(self, fields_containerA=None, fields_containerB=None, tolerance=None, small_value=None, config=None, server=None):
super().__init__(name="AreFieldsIdentical_fc", config = config, server = server)
self._inputs = InputsIdenticalFc(self)
self._outputs = OutputsIdenticalFc(self)
if fields_containerA !=None:
self.inputs.fields_containerA.connect(fields_containerA)
if fields_containerB !=None:
self.inputs.fields_containerB.connect(fields_containerB)
if tolerance !=None:
self.inputs.tolerance.connect(tolerance)
if small_value !=None:
self.inputs.small_value.connect(small_value)
@staticmethod
def _spec():
spec = Specification(description="""Check if two fields container are identical.""",
map_input_pin_spec={
0 : PinSpecification(name = "fields_containerA", type_names=["fields_container"], optional=False, document=""""""),
1 : PinSpecification(name = "fields_containerB", type_names=["fields_container"], optional=False, document=""""""),
2 : PinSpecification(name = "tolerance", type_names=["double"], optional=False, document="""Double relative tolerance. Maximum tolerance gap between to compared values: values within relative tolerance are considered identical (v1-v2)/v2 < relativeTol (default is 0.001)."""),
3 : PinSpecification(name = "small_value", type_names=["double"], optional=False, document="""Double positive small value.Smallest value which will be considered during the comparison step : all the abs(values) in field less than this value is considered as null, (default value:1.0e-14).""")},
map_output_pin_spec={
0 : PinSpecification(name = "boolean", type_names=["bool"], optional=False, document="""bool (true if identical...)"""),
1 : PinSpecification(name = "message", type_names=["string"], optional=False, document="""""")})
return spec
@staticmethod
def default_config():
return Operator.default_config(name = "AreFieldsIdentical_fc")
@property
def inputs(self):
"""Enables to connect inputs to the operator
Returns
--------
inputs : InputsIdenticalFc
"""
return super().inputs
@property
def outputs(self):
"""Enables to get outputs of the operator by evaluationg it
Returns
--------
outputs : OutputsIdenticalFc
"""
return super().outputs
#internal name: AreFieldsIdentical_fc
#scripting name: identical_fc
class InputsIdenticalFc(_Inputs):
"""Intermediate class used to connect user inputs to identical_fc operator
Examples
--------
>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.logic.identical_fc()
>>> my_fields_containerA = dpf.FieldsContainer()
>>> op.inputs.fields_containerA.connect(my_fields_containerA)
>>> my_fields_containerB = dpf.FieldsContainer()
>>> op.inputs.fields_containerB.connect(my_fields_containerB)
>>> my_tolerance = float()
>>> op.inputs.tolerance.connect(my_tolerance)
>>> my_small_value = float()
>>> op.inputs.small_value.connect(my_small_value)
"""
def __init__(self, op: Operator):
super().__init__(identical_fc._spec().inputs, op)
self._fields_containerA = Input(identical_fc._spec().input_pin(0), 0, op, -1)
self._inputs.append(self._fields_containerA)
self._fields_containerB = Input(identical_fc._spec().input_pin(1), 1, op, -1)
self._inputs.append(self._fields_containerB)
self._tolerance = Input(identical_fc._spec().input_pin(2), 2, op, -1)
self._inputs.append(self._tolerance)
self._small_value = Input(identical_fc._spec().input_pin(3), 3, op, -1)
self._inputs.append(self._small_value)
@property
def fields_containerA(self):
"""Allows to connect fields_containerA input to the operator
Parameters
----------
my_fields_containerA : FieldsContainer,
Examples
--------
>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.logic.identical_fc()
>>> op.inputs.fields_containerA.connect(my_fields_containerA)
>>> #or
>>> op.inputs.fields_containerA(my_fields_containerA)
"""
return self._fields_containerA
@property
def fields_containerB(self):
"""Allows to connect fields_containerB input to the operator
Parameters
----------
my_fields_containerB : FieldsContainer,
Examples
--------
>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.logic.identical_fc()
>>> op.inputs.fields_containerB.connect(my_fields_containerB)
>>> #or
>>> op.inputs.fields_containerB(my_fields_containerB)
"""
return self._fields_containerB
@property
def tolerance(self):
"""Allows to connect tolerance input to the operator
- pindoc: Double relative tolerance. Maximum tolerance gap between to compared values: values within relative tolerance are considered identical (v1-v2)/v2 < relativeTol (default is 0.001).
Parameters
----------
my_tolerance : float,
Examples
--------
>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.logic.identical_fc()
>>> op.inputs.tolerance.connect(my_tolerance)
>>> #or
>>> op.inputs.tolerance(my_tolerance)
"""
return self._tolerance
@property
def small_value(self):
"""Allows to connect small_value input to the operator
- pindoc: Double positive small value.Smallest value which will be considered during the comparison step : all the abs(values) in field less than this value is considered as null, (default value:1.0e-14).
Parameters
----------
my_small_value : float,
Examples
--------
>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.logic.identical_fc()
>>> op.inputs.small_value.connect(my_small_value)
>>> #or
>>> op.inputs.small_value(my_small_value)
"""
return self._small_value
class OutputsIdenticalFc(_Outputs):
"""Intermediate class used to get outputs from identical_fc operator
Examples
--------
>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.logic.identical_fc()
>>> # Connect inputs : op.inputs. ...
>>> result_boolean = op.outputs.boolean()
>>> result_message = op.outputs.message()
"""
def __init__(self, op: Operator):
super().__init__(identical_fc._spec().outputs, op)
self._boolean = Output(identical_fc._spec().output_pin(0), 0, op)
self._outputs.append(self._boolean)
self._message = Output(identical_fc._spec().output_pin(1), 1, op)
self._outputs.append(self._message)
@property
def boolean(self):
"""Allows to get boolean output of the operator
- pindoc: bool (true if identical...)
Returns
----------
my_boolean : bool,
Examples
--------
>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.logic.identical_fc()
>>> # Connect inputs : op.inputs. ...
>>> result_boolean = op.outputs.boolean()
"""
return self._boolean
@property
def message(self):
"""Allows to get message output of the operator
Returns
----------
my_message : str,
Examples
--------
>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.logic.identical_fc()
>>> # Connect inputs : op.inputs. ...
>>> result_message = op.outputs.message()
"""
return self._message
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] |
maps/urls.py | lueho/BRIT | 0 | 1612756 | <reponame>lueho/BRIT
from django.urls import include, path
from .views import (
AttributeListView,
AttributeCreateView,
AttributeModalCreateView,
AttributeDetailView,
AttributeModalDetailView,
AttributeUpdateView,
AttributeModalUpdateView,
AttributeModalDeleteView,
RegionAttributeValueListView,
RegionAttributeValueCreateView,
RegionAttributeValueModalCreateView,
RegionAttributeValueDetailView,
RegionAttributeValueModalDetailView,
RegionAttributeValueUpdateView,
RegionAttributeValueModalUpdateView,
RegionAttributeValueModalDeleteView,
CatchmentAutocompleteView,
CatchmentBrowseView,
CatchmentCreateView,
CatchmentGeometryAPI,
CatchmentOptionGeometryAPI,
CatchmentUpdateView,
CatchmentDeleteView,
CatchmentRegionGeometryAPI,
CatchmentRegionSummaryAPIView,
MapsListView,
RegionGeometryAPI,
NutsRegionMapView,
NutsRegionAPIView,
NutsRegionSummaryAPIView,
NutsRegionPedigreeAPI,
LauRegionOptionsAPI,
NutsAndLauCatchmentPedigreeAPI
)
urlpatterns = [
path('list/', MapsListView.as_view(), name='maps_list'),
path('attributes/', AttributeListView.as_view(), name='attribute-list'),
path('attributes/create/', AttributeCreateView.as_view(), name='attribute-create'),
path('attributes/create/modal/', AttributeModalCreateView.as_view(), name='attribute-create-modal'),
path('attributes/<int:pk>/', AttributeDetailView.as_view(), name='attribute-detail'),
path('attributes/<int:pk>/modal/', AttributeModalDetailView.as_view(), name='attribute-detail-modal'),
path('attributes/<int:pk>/update/', AttributeUpdateView.as_view(), name='attribute-update'),
path('attributes/<int:pk>/update/modal/', AttributeModalUpdateView.as_view(), name='attribute-update-modal'),
path('attributes/<int:pk>/delete/modal', AttributeModalDeleteView.as_view(), name='attribute-delete-modal'),
path('attribute_values/', RegionAttributeValueListView.as_view(), name='regionattributevalue-list'),
path('attribute_values/create/', RegionAttributeValueCreateView.as_view(), name='regionattributevalue-create'),
path('attribute_values/create/modal/', RegionAttributeValueModalCreateView.as_view(), name='regionattributevalue-create-modal'),
path('attribute_values/<int:pk>/', RegionAttributeValueDetailView.as_view(), name='regionattributevalue-detail'),
path('attribute_values/<int:pk>/modal/', RegionAttributeValueModalDetailView.as_view(), name='regionattributevalue-detail-modal'),
path('attribute_values/<int:pk>/update/', RegionAttributeValueUpdateView.as_view(), name='regionattributevalue-update'),
path('attribute_values/<int:pk>/update/modal/', RegionAttributeValueModalUpdateView.as_view(), name='regionattributevalue-update-modal'),
path('attribute_values/<int:pk>/delete/modal', RegionAttributeValueModalDeleteView.as_view(), name='regionattributevalue-delete-modal'),
path('catchments/', CatchmentBrowseView.as_view(), name='catchment_list'),
path('catchment/create/', CatchmentCreateView.as_view(), name='catchment_definition'),
path('catchment/create/modal/', CatchmentCreateView.as_view(), name='catchment-create-modal'),
path('catchments/<int:pk>/update/', CatchmentUpdateView.as_view(), name='catchment_update'),
path('catchments/<int:pk>/delete/', CatchmentDeleteView.as_view(), name='catchment_delete'),
path('catchments/data/', RegionGeometryAPI.as_view(), name='data.catchments'),
path('catchments/autocomplete/', CatchmentAutocompleteView.as_view(), name='catchment-autocomplete'),
path('catchment_options/data/', CatchmentOptionGeometryAPI.as_view(), name='data.catchment-options'),
path('nutsregions/map/', NutsRegionMapView.as_view(), name='NutsRegion'),
path('nutsregions/data/', NutsRegionAPIView.as_view(), name='data.nutsregion'),
path('nutsregions/summary/', NutsRegionSummaryAPIView.as_view(), name='data.nutsregion-summary'),
path('nutsregions/options/data/', NutsRegionPedigreeAPI.as_view(), name='data.nuts_region_options'),
path('lau_options/data/', LauRegionOptionsAPI.as_view(), name='data.lau_region_options'),
path('nuts_lau_catchment_options/data/', NutsAndLauCatchmentPedigreeAPI.as_view(),
name='data.nuts_lau_catchment_options'),
path('region_geometries/', RegionGeometryAPI.as_view(), name='ajax_region_geometries'),
path('catchment_region_geometries/', CatchmentRegionGeometryAPI.as_view(), name='data.catchment_region_geometries'),
path('catchment_regions_summaries/', CatchmentRegionSummaryAPIView.as_view(), name='data.catchment_region_summaries'),
path('catchment_geometries/', CatchmentGeometryAPI.as_view(), name='ajax_catchment_geometries'),
# TODO: Can case study urls be detected and added automatically?
path('nantes/', include('case_studies.flexibi_nantes.urls')),
path('hamburg/', include('case_studies.flexibi_hamburg.urls')),
]
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tahoe_scorm/exceptions.py | appsembler/tahoe-scorm | 0 | 119394 | <filename>tahoe_scorm/exceptions.py<gh_stars>0
class ScormException(Exception):
pass
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src/baselines/a2c/a2c.py | Officium/RL-Experiments | 54 | 190393 | import os
import time
from collections import deque
import torch
import torch.distributions
import torch.nn as nn
from torch.optim.lr_scheduler import LambdaLR
from common.util import scale_ob, Trajectories
def learn(logger,
device,
env, nenv,
number_timesteps,
network, optimizer,
save_path, save_interval, ob_scale,
gamma, grad_norm, timesteps_per_batch, ent_coef, vf_coef):
"""
Paper:
<NAME>, <NAME>, <NAME>, et al. Asynchronous methods for deep
reinforcement learning[C]// International Conference on Machine Learning.
2016: 1928-1937.
Parameters:
----------
gram_norm (float | None): grad norm
timesteps_per_batch (int): number of steps per update
ent_coef (float): policy entropy coefficient in the objective
vf_coef (float): value function loss coefficient in the objective
"""
policy = network.to(device)
number_timesteps = number_timesteps // nenv
generator = _generate(
device, env, policy, ob_scale,
number_timesteps, gamma, timesteps_per_batch
)
max_iter = number_timesteps // timesteps_per_batch
scheduler = LambdaLR(optimizer, lambda i_iter: 1 - i_iter / max_iter)
total_timesteps = 0
infos = {k: deque(maxlen=100)
for k in ['eplenmean', 'eprewmean', 'pgloss', 'v', 'entropy']}
start_ts = time.time()
for n_iter in range(1, max_iter + 1):
scheduler.step()
batch = generator.__next__()
b_o, b_a, b_r, b_v_old, info = batch
for d in info:
infos['eplenmean'].append(d['l'])
infos['eprewmean'].append(d['r'])
total_timesteps += b_o.size(0)
# calculate advantange
b_logits, b_v = policy(b_o)
b_v = b_v[:, 0]
dist = torch.distributions.Categorical(logits=b_logits)
entropy = dist.entropy().mean()
b_logp = dist.log_prob(b_a)
adv = b_r - b_v_old
# update policy
vloss = (b_v - b_r).pow(2).mean()
pgloss = -(adv * b_logp).mean()
loss = pgloss + vf_coef * vloss - ent_coef * entropy
optimizer.zero_grad()
loss.backward()
if grad_norm is not None:
nn.utils.clip_grad_norm_(policy.parameters(), grad_norm)
optimizer.step()
# record logs
infos['pgloss'].append(pgloss.item())
infos['v'].append(vloss.item())
infos['entropy'].append(entropy.item())
logger.info('{} Iter {} {}'.format('=' * 10, n_iter, '=' * 10))
fps = int(total_timesteps / (time.time() - start_ts))
logger.info('Total timesteps {} FPS {}'.format(total_timesteps, fps))
for k, v in infos.items():
v = (sum(v) / len(v)) if v else float('nan')
logger.info('{}: {:.6f}'.format(k, v))
if save_interval and n_iter % save_interval == 0:
torch.save([policy.state_dict(), optimizer.state_dict()],
os.path.join(save_path, '{}.checkpoint'.format(n_iter)))
def _generate(device, env, policy, ob_scale,
number_timesteps, gamma, timesteps_per_batch):
""" Generate trajectories """
record = ['o', 'a', 'r', 'done', 'vpred']
export = ['o', 'a', 'r', 'vpred']
trajectories = Trajectories(record, export, device, gamma, ob_scale)
o = env.reset()
infos = []
for n in range(1, number_timesteps + 1):
# sample action
with torch.no_grad():
logits, v = policy(scale_ob(o, device, ob_scale))
dist = torch.distributions.Categorical(logits=logits)
a = dist.sample().cpu().numpy()
v = v.cpu().numpy()[:, 0]
# take action in env
o_, r, done, info = env.step(a)
for d in info:
if d.get('episode'):
infos.append(d['episode'])
# store batch data and update observation
trajectories.append(o, a, r, done, v)
if n % timesteps_per_batch == 0:
with torch.no_grad():
ob = scale_ob(o_, device, ob_scale)
v_ = policy(ob)[1].cpu().numpy()[:, 0] * (1 - done)
yield trajectories.export(v_) + (infos, )
infos.clear()
o = o_
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src/test/marker_array_test.py | fftn/rviz | 0 | 139469 | #!/usr/bin/env python
from visualization_msgs.msg import Marker
from visualization_msgs.msg import MarkerArray
import rospy
import math
topic = "visualization_marker_array"
publisher = rospy.Publisher(topic, MarkerArray)
rospy.init_node("register")
markerArray = MarkerArray()
count = 0
MARKERS_MAX = 100
while not rospy.is_shutdown():
marker = Marker()
marker.header.frame_id = "base_link"
marker.type = marker.SPHERE
marker.action = marker.ADD
marker.scale.x = 0.2
marker.scale.y = 0.2
marker.scale.z = 0.2
marker.color.a = 1.0
marker.color.r = 1.0
marker.color.g = 1.0
marker.color.b = 0.0
marker.pose.orientation.w = 1.0
marker.pose.position.x = math.cos(count / 50.0)
marker.pose.position.y = math.cos(count / 40.0)
marker.pose.position.z = math.cos(count / 30.0)
# We add the new marker to the MarkerArray, removing the oldest marker from it when necessary
if count > MARKERS_MAX:
markerArray.markers.pop(0)
markerArray.markers.append(marker)
# Renumber the marker IDs
id = 0
for m in markerArray.markers:
m.id = id
id += 1
# Publish the MarkerArray
publisher.publish(markerArray)
count += 1
rospy.sleep(0.01)
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qa/rpc-tests/cryptoconditions_faucet.py | wallnutkraken/komodo | 1 | 72566 | <gh_stars>1-10
#!/usr/bin/env python2
# Copyright (c) 2018 SuperNET developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
from test_framework.test_framework import CryptoconditionsTestFramework
from test_framework.authproxy import JSONRPCException
from test_framework.util import assert_equal, assert_greater_than, \
initialize_chain_clean, initialize_chain, start_nodes, start_node, connect_nodes_bi, \
stop_nodes, sync_blocks, sync_mempools, wait_bitcoinds, rpc_port, assert_raises
from cryptoconditions import assert_success, assert_error, generate_random_string
class CryptoconditionsFaucetTest(CryptoconditionsTestFramework):
def run_faucet_tests(self):
rpc = self.rpc
rpc1 = self.rpc1
# basic sanity tests
result = rpc.getwalletinfo()
assert_greater_than(result['txcount'], 100)
assert_greater_than(result['balance'], 0.0)
balance = result['balance']
faucet = rpc.faucetaddress()
assert_equal(faucet['result'], 'success')
# verify all keys look like valid AC addrs, could be better
for x in ['myCCaddress', 'FaucetCCaddress', 'Faucetmarker', 'myaddress']:
assert_equal(faucet[x][0], 'R')
result = rpc.faucetaddress(self.pubkey)
assert_success(result)
# test that additional CCaddress key is returned
for x in ['myCCaddress', 'FaucetCCaddress', 'Faucetmarker', 'myaddress', 'CCaddress']:
assert_equal(result[x][0], 'R')
# no funds in the faucet yet
result = rpc.faucetget()
assert_error(result)
result = rpc.faucetinfo()
assert_success(result)
result = rpc.faucetfund("0")
assert_error(result)
result = rpc.faucetfund("-1")
assert_error(result)
# we need at least 1 + txfee to get
result = rpc.faucetfund("2")
assert_success(result)
assert result['hex'], "hex key found"
# broadcast the xtn
result = rpc.sendrawtransaction(result['hex'])
txid = result[0]
assert txid, "found txid"
# we need the tx above to be confirmed in the next block
rpc.generate(1)
self.sync_all()
result = rpc.getwalletinfo()
# minus one block reward
balance2 = result['balance'] - 100000
# make sure our balance is less now
assert_greater_than(balance, balance2)
result = rpc.faucetinfo()
assert_success(result)
assert_greater_than( result['funding'], 0 )
# claiming faucet on second node
faucetgethex = rpc1.faucetget()
assert_success(faucetgethex)
assert faucetgethex['hex'], "hex key found"
balance1 = rpc1.getwalletinfo()['balance']
# try to broadcast the faucetget transaction
result = self.send_and_mine(faucetgethex['hex'], rpc1)
assert txid, "transaction broadcasted"
balance2 = rpc1.getwalletinfo()['balance']
assert_greater_than(balance2, balance1)
self.sync_all()
def run_test(self):
print("Mining blocks...")
rpc = self.nodes[0]
rpc1 = self.nodes[1]
# utxos from block 1 become mature in block 101
rpc.generate(101)
self.sync_all()
rpc.getinfo()
rpc1.getinfo()
# this corresponds to -pubkey above
print("Importing privkeys")
rpc.importprivkey(self.privkey)
rpc1.importprivkey(self.privkey1)
self.run_faucet_tests()
if __name__ == '__main__':
CryptoconditionsFaucetTest ().main()
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models/points_rcnn/__init__.py | periakiva/finding_berries | 11 | 97351 | <reponame>periakiva/finding_berries
from .faster_rcnn import *
from .mask_rcnn import *
from .keypoint_rcnn import * | [
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skins.py | shycoldii/agario | 0 | 101524 | <reponame>shycoldii/agario
import pygame
import pygame.gfxdraw
import os
import random
from vector import vector
default_skin = "skin1"
class Skins:
all_skins = None
PATH = "./data"
@classmethod
def init(cls):
cls.all_skins = {}
all_skins = cls.loadskins() #грузим все скины из папки
for name in all_skins.keys():
img = all_skins[name]
circle = cls.Image_to_circle(img)
cls.all_skins[name] = (circle)
@classmethod
def loadskins(cls):
"""Загрузка скинов из папки"""
all_img = {}
flag = 0
full_names = os.listdir(cls.PATH + "/skins")
if "pi19" in full_names:
full_names = os.listdir(cls.PATH + "/skins/pi19")
flag = 1
for file in full_names:
file_name = file.split('.')
if True:
extension = file_name[-1] #расширение
del file_name[-1]
file_name = ''.join(file_name)
if extension in ("png", "jpg"):
if flag:
img = pygame.image.load(cls.PATH + "/skins/pi19/" + file_name + '.' + extension).convert()
else:
img = pygame.image.load(cls.PATH + "/skins/" + file_name + '.' +extension).convert()
all_img[file_name] = (img)
return all_img
@classmethod
def get_player_skin(cls):
#player_skin = pygame.image.load(cls.PATH + "/skins/skin1.png").convert()
#circle = cls.Image_to_circle(player_skin)
player_skin = []
if "pi19" in os.listdir(cls.PATH + "/skins"):
player_skin.append("g5")
player_skin.append("g7")
return cls.all_skins[random.choice(player_skin)]
else:
return cls.all_skins[list(cls.all_skins.keys())[random.randrange(len(list(cls.all_skins.keys())))]]
@classmethod
def get_rand_skin(cls):
skin = list(cls.all_skins.keys())[random.randrange(len(list(cls.all_skins.keys())))]
return cls.all_skins[skin]
@classmethod
def Image_to_circle(cls, img):
"""Конвертирует картинку в круг"""
width = img.get_width()
height = img.get_height()
if width == height:
size = width
else:
raise ValueError("Одна из картинок имеет неквадратный формат")
surface = pygame.Surface((size+1, size+1), pygame.SRCALPHA)
center = vector(size / 2, size / 2)
radius = int(size/2)
for x in range(size):
for y in range(size):
pos = vector(x, y)
if vector.distant(pos, center) < radius**2:
color = img.get_at((x, y))
if color[3] != 255:
color[3] = 255
#если есть прозрачность
if color == (99, 28, 11):
color[0] += 1
else:
color = (255, 255, 255, 0)
# Вне круга будет прозрачный цвет
pygame.gfxdraw.pixel(surface, x, y, color)
pygame.gfxdraw.aacircle(surface, int(size/2), int(size/2), radius, (0, 0, 0))
surface.set_colorkey((99, 28, 11))
surface = surface.convert_alpha()
return surface
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treadmill_pipeline/treadmill.py | ttngu207/project-treadmill | 0 | 22134 | import numpy as np
import datajoint as dj
from treadmill_pipeline import project_database_prefix
from ephys.utilities import ingestion, time_sync
from ephys import get_schema_name
schema = dj.schema(project_database_prefix + 'treadmill_pipeline')
reference = dj.create_virtual_module('reference', get_schema_name('reference'))
acquisition = dj.create_virtual_module('acquisition', get_schema_name('acquisition'))
behavior = dj.create_virtual_module('behavior', get_schema_name('behavior'))
@schema
class TreadmillTracking(dj.Imported):
definition = """ # session-level tracking data from the treadmill_pipeline(s) employed in the experiment
-> acquisition.Session
treadmill_tracking_time: datetime # start time of this treadmill_pipeline speed recording
---
treadmill_tracking_name: varchar(40) # user-assign name of this treadmill_pipeline tracking (e.g. 27032019laserSess1)
treadmill_timestamps: blob@ephys_store # (s) timestamps of the treadmill_pipeline speed samples
"""
class TreadmillSync(dj.Part):
definition = """
-> master
---
sync_master_clock: varchar(128) # name of the sync-master
track_sync_data=null: blob@ephys_store # sync data (binary)
track_time_zero=null: float # (s) the first time point of this tracking
track_sync_timestamps=null: blob@ephys_store # (s) timestamps of sync data in tracking clock
track_sync_master_timestamps=null: blob@ephys_store # (s) timestamps of sync data in master clock
"""
class Speed(dj.Part):
definition = """
-> master
treadmill_name: varchar(32)
---
treadmill_speed: blob@ephys_store # (s) treadmill_pipeline speed at each timestamp
"""
key_source = acquisition.Session & acquisition.Recording # wait for recording to be ingested first before tracking
def make(self, key):
input_dir = ingestion.find_input_directory(key)
if not input_dir:
print(f'{input_dir} not found in this machine, skipping...')
return
rec_type, recordings = ingestion.get_recordings(input_dir)
if rec_type in ('neuropixels', 'neurologger'): # if 'neuropixels' recording, check for OptiTrack's `motive` or `.csv`
opti_list = ingestion.get_optitrack(input_dir)
if not opti_list:
raise FileNotFoundError('No OptiTrack "matmot.mtv" or ".csv" found')
for opti in opti_list:
if 'Format Version' not in opti.meta:
raise NotImplementedError('Treadmill data ingest from type other than "optitrack.csv" not implemented')
secondary_data = opti.secondary_data
if 'Treadmill' not in secondary_data:
raise KeyError('No "Treadmill" found in the secondary data of optitrack.csv')
treadmill_key = dict(key, treadmill_tracking_time=opti.recording_time)
self.insert1(dict(treadmill_key,
treadmill_tracking_name=opti.tracking_name, # name of the session folder
treadmill_timestamps=secondary_data['t']))
if hasattr(opti, 'sync_data'):
self.TreadmillSync.insert1(dict(treadmill_key,
sync_master_clock=opti.sync_data['master_name'],
track_time_zero=secondary_data['t'][0],
track_sync_timestamps=opti.sync_data['slave'],
track_sync_master_timestamps=opti.sync_data['master']))
else: # data presynced with tracking-recording pair,
# still need for a linear shift from session start to the recording this tracking is synced to
self.TrackingSync.insert1(time_sync.create_tracking_sync_data(
treadmill_key, np.array([secondary_data['t'][0], secondary_data['t'][-1]])))
self.Speed.insert1([dict(treadmill_key, treadmill_name=k, treadmill_speed=v['speed'])
for k, v in secondary_data['Treadmill'].items()])
print(f'Insert {len(opti_list)} treadmill_pipeline tracking(s): {input_dir.stem}')
else:
raise NotImplementedError(f'Treadmill Tracking ingestion for recording type {rec_type} not implemented')
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2
] |
bookapp/views.py | RafaCucurull/Bookiernes | 0 | 139445 | from django.http import HttpResponseRedirect, HttpResponse
from django.shortcuts import render, redirect
from bookapp import models
from bookapp.forms import AfegirLlibreForm, SolicitarImatgesForm, SolicitarMaquetacioForm, PujarMaquetacio, pujarImatge, \
SolicitarPublicacioForm, EnviarMissatgeForm, SolicitarTraduccioForm
from bookapp.models import Llibre, TematiquesLlibre, Comentari, Notificacio, Tematica, Imatge, Missatge
from users.forms import ConfiguracioForm
from users.models import CustomUser
from django.core.files.storage import FileSystemStorage
from datetime import datetime
import PyPDF2
from translate import Translator
from fpdf import FPDF
from django.urls import reverse
from django.core.files.base import File
def homePage(request):
return render(request, "home.html")
def Escriptori(request):
global llibres
usuari = CustomUser.objects.get(email=request.user)
if not usuari.is_Treballador:
return render(request, "home.html")
if usuari.is_Editor:
llibres = Llibre.objects.filter(editor=usuari)
if usuari.is_Escriptor:
llibres = Llibre.objects.filter(escriptor=usuari)
if usuari.is_Dissenyador:
llibres = Llibre.objects.filter(dissenyador=usuari)
if usuari.is_Maquetacio:
llibres = Llibre.objects.filter(maquetador=usuari)
if usuari.is_IT:
llibres = Llibre.objects.filter(it=usuari)
tematiques = list()
for llibre in llibres:
tematiques.append(TematiquesLlibre.objects.filter(llibre=llibre))
mylist = zip(llibres, tematiques)
llibreshtml = {
"object_list": llibres,
"mylist": mylist
}
if usuari.is_Escriptor:
return render(request, "escriptori_escriptor.html", llibreshtml)
if usuari.is_Editor:
return render(request, "escriptori_editor.html", llibreshtml)
if usuari.is_Dissenyador:
return render(request, "escriptori_maquetador_dissenyador.html", llibreshtml)
if usuari.is_Maquetacio:
return render(request, "escriptori_maquetador_dissenyador.html", llibreshtml)
if usuari.is_IT:
return render(request, "escriptori_it.html", llibreshtml)
def afegirLlibre(request):
if request.method == 'POST':
form = AfegirLlibreForm(request.POST, request.FILES)
if form.is_valid():
obj = form.save()
afegirDocuments(obj)
seleccionar_editor(obj)
obj.escriptor = request.user
obj.save()
return redirect('/escriptori')
else:
form = AfegirLlibreForm()
return render(request, "afegirllibre.html", {'form': form})
def afegirDocuments(llibre):
with open('text.txt') as f:
llibre.textPla.save('text', File(f))
with open('text.txt') as f:
llibre.pdf_retall.save('retall', File(f))
with open('text.txt') as esdoc:
llibre.es.save('es', File(esdoc))
with open('text.txt') as g:
llibre.es_retall.save('esRetall', File(g))
with open('text.txt') as g:
llibre.en.save('en', File(g))
with open('text.txt') as h:
llibre.en_retall.save('enRetall', File(h))
with open('text.txt') as g:
llibre.pt.save('pt', File(g))
with open('text.txt') as h:
llibre.pt_retall.save('ptRetall', File(h))
with open('text.txt') as g:
llibre.zh.save('zh', File(g))
with open('text.txt') as h:
llibre.zh_retall.save('zhRetall', File(h))
def seleccionar_editor(llibre):
editors_lliures = CustomUser.objects.filter(is_Editor=True, lliure=True)
editoraux = editors_lliures[0]
llibre.editor = editoraux
editor = CustomUser.objects.get(email=editoraux)
# editor.lliure = False
editor.save()
notificacio = Notificacio()
notificacio.missatge = "Tens un nou llibre assignat"
notificacio.usuari = editoraux
data = datetime.now()
notificacio.data = data
notificacio.llibre = llibre
notificacio.save()
def areaedicio(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibre": llibre
}
return render(request, 'area_edicio.html', context)
def enviarmissatge(request):
if request.method == 'POST':
form = EnviarMissatgeForm(request.POST)
if form.is_valid():
obj = form.save()
obj.autor = request.user
obj.save()
return redirect(request.path_info)
else:
form = EnviarMissatgeForm()
context = {
'form': form
}
return render(request, "missatge.html", context)
def areaescriptor(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibre": llibre
}
return render(request, 'area_escriptor.html', context)
def areait(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibre": llibre
}
return render(request, 'area_escriptor.html', context)
def enviarnovaversio(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibrehtml": llibre
}
if request.method == "POST" and request.FILES['pdf']:
pdf = request.FILES['pdf']
print(pdf)
fs = FileSystemStorage()
filename = fs.save(pdf.name, pdf)
llibre.pdf = fs.url(filename)
print(llibre.pdf)
llibre.save()
return redirect(reverse('areaescriptor', kwargs={'pk': pk}))
return render(request, 'enviar_nova_versio.html', context)
def commentseditor(request, pk):
llibre = Llibre.objects.get(pk=pk)
usuari = CustomUser.objects.get(email=request.user)
comentaris = Comentari.objects.filter(usuari=usuari, llibre=llibre)
context = {
"llibre": llibre,
"usuari": usuari,
"comentaris": comentaris
}
if request.method == "POST":
titol = request.POST.get('titol')
descripcio = request.POST.get('descripcio')
nou_comentari = Comentari()
nou_comentari.usuari = request.user
nou_comentari.titol = titol
nou_comentari.descripcio = descripcio
nou_comentari.llibre = Llibre.objects.get(pk=pk)
nou_comentari.save()
notificarEscriptorComentari(Llibre.objects.get(pk=pk))
return render(request, 'comments_editor.html', context)
def dirbateriaimatges(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibre": llibre,
}
return render(request, 'directori_imatges.html', context)
def dirmaquetacions(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibre": llibre,
}
return render(request, 'directori_maquetacions.html', context)
def notificarEscriptorComentari(llibre):
notificacio = Notificacio()
notificacio.missatge = "Tens un comentari pendent de revisar"
notificacio.usuari = llibre.escriptor
notificacio.llibre = llibre
data = datetime.now()
notificacio.data = data
notificacio.save()
def canviardocument(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibre": llibre
}
if request.method == "POST" and request.FILES['pdf']:
pdf = request.FILES['pdf']
print(pdf)
fs = FileSystemStorage()
filename = fs.save(pdf.name, pdf)
llibre.pdf = fs.url(filename)
print(llibre.pdf)
llibre.save()
return redirect(reverse('areaedicio', kwargs={'pk': pk}))
return render(request, 'canviar_document.html', context)
def notificacions(request):
notificacions = Notificacio.objects.filter(usuari=request.user)
context = {
"object_list": notificacions
}
return render(request, "notificacions.html", context)
def veuremissatge(request):
missatges = Missatge.objects.filter(destinatari=request.user)
context = {
"object_list": missatges
}
return render(request, "veuremissatge.html", context)
def comments(request, pk):
llibre = Llibre.objects.get(pk=pk)
comentaris = Comentari.objects.filter(llibre=llibre)
context = {
"llibre": llibre,
"comentaris": comentaris
}
return render(request, 'comments.html', context)
def cataleg(request):
qs = filtrar(request)
print(qs)
for llibre in qs:
print(llibre.nom_llibre)
context = {
'queryset': qs,
'tematiques': Tematica.objects.all()
}
return render(request, "cataleg.html", context)
def filtrar(request):
queryset = Llibre.objects.all()
tematiques = Tematica.objects.all()
escriptor = CustomUser.objects.filter(is_Escriptor=True)
titol = request.GET.get('titol')
autor = request.GET.get('autor')
colleccio = request.GET.get('collecio')
min_pagines = request.GET.get('pagines_min')
max_pagines = request.GET.get('pagines_max')
tematica = request.GET.get('tematica')
if is_valid(titol):
queryset = queryset.filter(nom_llibre__icontains=titol)
if is_valid(autor):
queryset = queryset.filter(escriptor__nom__icontains=autor)
if is_valid(colleccio):
queryset = queryset.filter(coleccio__icontains=colleccio)
if is_valid(min_pagines):
queryset = queryset.filter(num_pagines__gte=min_pagines)
if is_valid(max_pagines):
queryset = queryset.filter(num_pagines__lt=max_pagines)
if is_valid(tematica) and tematica != 'Tria...':
queryset = queryset.filter(tematiques__nom_tematica=tematica)
return queryset
def is_valid(param):
return param != '' and param is not None
def publicarllibre(request, pk):
llibre = Llibre.objects.get(pk=pk)
llibreshtml = {
"llibre": llibre,
}
if request.method == "POST":
llibre.publicat = True
llibre.save()
notificarEditorPublicat(llibre)
notificarITPublicat(llibre)
return redirect('/escriptori')
return render(request, "publicarllibre.html", llibreshtml)
def notificarEditorPublicat(llibre):
editor = llibre.editor
notificacio = Notificacio()
notificacio.missatge = "El llibre que has estat editant ja ha estat publicat a la Web"
notificacio.usuari = editor
data = datetime.now()
notificacio.data = data
notificacio.llibre = llibre
notificacio.save()
def notificarITPublicat(llibre):
it = llibre.it
notificacio = Notificacio()
notificacio.missatge = "El llibre que tenies assignat ja ha estat publicat a la Web"
notificacio.usuari = it
data = datetime.now()
notificacio.data = data
notificacio.llibre = llibre
notificacio.save()
def galeriaImatges(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
'imatges': llibre.imatges.all(),
'llibre': llibre,
}
return render(request, "galeria_imatges.html", context)
def solicitudImatges(request, pk):
llibre = Llibre.objects.get(pk=pk)
if request.method == 'POST':
form = SolicitarImatgesForm(request.POST)
if form.is_valid():
obj = form.save()
obj.llibre = llibre
obj.editor = request.user
seleccionar_dissenyador(obj, llibre)
obj.save()
return redirect(reverse('areaedicio', kwargs={'pk': pk}))
else:
form = SolicitarImatgesForm()
context = {
'llibre': llibre,
'form': form
}
return render(request, "solicitud_imatges.html", context)
def seleccionar_dissenyador(solicitud, llibre):
dissenyadors_lliures = CustomUser.objects.filter(is_Dissenyador=True, lliure=True)
dissenyadoraux = dissenyadors_lliures[0]
llibre.dissenyador = dissenyadoraux
llibre.save()
solicitud.dissenyador = dissenyadoraux
dissenyador = CustomUser.objects.get(email=dissenyadoraux)
# dissenyador.lliure = False
dissenyador.save()
notificacio = Notificacio()
notificacio.missatge = "Tens un nova sol·licitud d'imatges assignada"
notificacio.usuari = dissenyadoraux
data = datetime.now()
notificacio.data = data
notificacio.llibre = llibre
notificacio.save()
def galeriaMaquetacions(request, pk):
llibre = Llibre.objects.get(pk=pk)
maquetacio = llibre.maquetacio
context = {
"llibre": llibre,
"maquetacio": maquetacio
}
return render(request, "galeria_maquetacions.html", context)
def solicitudmaquetacio(request, pk):
llibre = Llibre.objects.get(pk=pk)
if request.method == 'POST':
form = SolicitarMaquetacioForm(request.POST)
if form.is_valid():
obj = form.save()
obj.llibre = llibre
obj.editor = request.user
seleccionar_maquetador(obj, llibre)
obj.save()
return redirect(reverse('areaedicio', kwargs={'pk': pk}))
else:
form = SolicitarMaquetacioForm()
return render(request, "enviar_llibre_maquetar.html", {'form': form})
def seleccionar_maquetador(solicitud, llibre):
maquetador_lliures = CustomUser.objects.filter(is_Maquetacio=True, lliure=True)
maquetadoraux = maquetador_lliures[0]
llibre.maquetador = maquetadoraux
llibre.save()
solicitud.maquetador = maquetadoraux
maquetador = CustomUser.objects.get(email=maquetadoraux)
# maquetador.lliure = False
maquetador.save()
notificacio = Notificacio()
notificacio.missatge = "Tens un nova sol·licitud de maquetació assignada"
notificacio.usuari = maquetadoraux
data = datetime.now()
notificacio.data = data
notificacio.llibre = llibre
notificacio.save()
def areaDisssenyiMaquetacio(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibre": llibre
}
return render(request, 'area_disseny_i_maquetacio.html', context)
def veuresolicitudsImatge(request, pk):
llibre = Llibre.objects.get(pk=pk)
solicituds_disseny = models.solicitudImatges.objects.filter(llibre=llibre)
context = {
'llista_solicituds': solicituds_disseny,
'llibre': llibre
}
return render(request, 'solicituds_imatges_disseny.html', context)
def enviarbat(request, pk, pksol):
llibre = Llibre.objects.get(pk=pk)
solicitud = models.solicitudImatges.objects.filter(pk=pksol)
if request.method == 'POST':
form = pujarImatge(request.POST, request.FILES)
if form.is_valid():
obj = form.save()
obj.save()
llibre.imatges.add(obj)
llibre.save()
solicitud.delete()
notificarEditorImatges(llibre)
return redirect(reverse('areadismaq', kwargs={'pk': pk}))
else:
form = pujarImatge()
return render(request, 'enviar_imatges.html', {'form': form, 'llibre': llibre})
def notificarEditorImatges(llibre):
editor = llibre.editor
notificacio = Notificacio()
notificacio.missatge = "Tens disponible la bateria d'imatges que vas sol·licitar per l'obra"
notificacio.usuari = editor
data = datetime.now()
notificacio.data = data
notificacio.llibre = llibre
notificacio.save()
def notificarEditorMaquetacio(llibre):
editor = llibre.editor
notificacio = Notificacio()
notificacio.missatge = "Tens disponible el llibre maquetat que vas sol·licitar"
notificacio.usuari = editor
data = datetime.now()
notificacio.data = data
notificacio.llibre = llibre
notificacio.save()
def veuresolicitudsMaquetacio(request, pk):
llibre = Llibre.objects.get(pk=pk)
solicituds_maquetacio = models.solicitudMaquetacio.objects.filter(llibre=llibre)
context = {
'llista_solicituds': solicituds_maquetacio,
'llibre': llibre
}
return render(request, 'solicituds_maquetacio_disseny.html', context)
def enviarMaquetacio(request, pk, pksol):
llibre = Llibre.objects.get(pk=pk)
solicitud = models.solicitudMaquetacio.objects.filter(pk=pksol)
if request.method == 'POST':
form = PujarMaquetacio(request.POST, request.FILES)
if form.is_valid():
obj = form.save()
obj.save()
llibre.maquetacio = obj
llibre.save()
solicitud.delete()
notificarEditorMaquetacio(llibre)
return redirect(reverse('areadismaq', kwargs={'pk': pk}))
else:
form = PujarMaquetacio()
return render(request, 'enviar_maquetat.html', {'form': form, 'llibre': llibre})
def eliminarimatge(request, pk, pkimatge):
llibre = Llibre.objects.get(pk=pk)
imatge = Imatge.objects.get(pk=pkimatge)
llibre.imatges.remove(imatge)
llibre.save()
return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))
def download_image(request, pk, pkimatge):
image = Imatge.objects.get(pk=pkimatge)
filename = image.image.file.name.split('/')[-1]
response = HttpResponse(image.image.file, content_type='text/plain')
response['Content-Disposition'] = 'attachment; filename=%s' % filename
return response
def eliminarnotificacio(request, pknotificacio):
Notificacio.objects.filter(pk=pknotificacio).delete()
return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))
def eliminarmissatge(request, pkmissatge):
Missatge.objects.filter(pk=pkmissatge).delete()
return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))
def solicitudpublicacio(request, pk):
llibre = Llibre.objects.get(pk=pk)
if request.method == 'POST':
form = SolicitarPublicacioForm(request.POST)
if form.is_valid():
anotacions = request.POST.get('anotacions')
obj = form.save()
obj.llibre = llibre
obj.editor = request.user
llibre.comentari_it = anotacions
seleccionar_it(obj, llibre)
llibre.save()
obj.save()
return redirect(reverse('areaedicio', kwargs={'pk': pk}))
else:
form = SolicitarMaquetacioForm()
retallarobra(llibre)
return render(request, "enviar_llibre_publicar.html", {'form': form})
def seleccionar_it(solicitud, llibre):
it_lliures = CustomUser.objects.filter(is_IT=True, lliure=True)
it_aux = it_lliures[0]
llibre.it = it_aux
llibre.save()
solicitud.it = it_aux
it = CustomUser.objects.get(email=it_aux)
# it.lliure = False
it.save()
notificacio = Notificacio()
notificacio.missatge = "Tens un nova sol·licitud de publicació assignada"
notificacio.usuari = it_aux
data = datetime.now()
notificacio.data = data
notificacio.llibre = llibre
notificacio.save()
def solicitudTraduccio(request, pk):
llibre = Llibre.objects.get(pk=pk)
if request.method == 'POST':
form = SolicitarTraduccioForm(request.POST)
if form.is_valid():
obj = form.save()
obj.llibre = llibre
obj.editor = request.user
idioma = obj.idioma
obj.save()
traduirLlibre(llibre, idioma)
# notificarEditorTraduccio(llibre)
return redirect(request.path_info)
else:
form = SolicitarTraduccioForm()
return render(request, 'solicitud_traduccio.html', {'form': form, 'llibre': llibre})
def galeriaTraduccions(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
'llibre': llibre,
}
return render(request, "galeria_traduccions.html", context)
def traduirLlibre(llibre, idioma):
pdf = llibre.pdf.path
txt = llibre.textPla.path
if (idioma == 'es'):
traduccio = llibre.es.path
if (idioma == 'en'):
traduccio = llibre.en.path
elif (idioma == 'pt'):
traduccio = llibre.pt.path
elif (idioma == 'zh'):
traduccio = llibre.zh.path
with open(pdf, 'rb') as pdf_file, open(txt, 'w') as txt_file:
read_pdf = PyPDF2.PdfFileReader(pdf_file)
number_of_pages = read_pdf.getNumPages()
for page_number in range(number_of_pages):
page = read_pdf.getPage(page_number)
page_content = page.extractText()
txt_file.write(page_content)
translator = Translator(to_lang=idioma)
with open(txt, 'r') as textOriginal:
data = textOriginal.read()
to_translate = data[:500]
translation = translator.translate(to_translate)
pdf = FPDF()
pdf.add_page()
pdf.set_font('arial', size=12)
pdf.multi_cell(190, 12, txt=translation)
pdf.output(traduccio + ".pdf")
# with open(llibre.traduccio, "wb") as llibreTraduccioStream:
# translation.write(llibreTraduccioStream)
def dirtraduccions(request, pk):
llibre = Llibre.objects.get(pk=pk)
context = {
"llibre": llibre,
}
return render(request, 'directori_traduccions.html', context)
def retallarobra(llibre):
# PDF
retallPDF = FPDF()
retallPDF.add_page()
retallPDF.set_font("Arial", size=15)
f = open(llibre.textPla.path, "r")
for x in f:
retallPDF.multi_cell(190, 10, txt=x, border=0, align='J', fill=False)
retallPDF.cell(190, 10, txt="HEU ARRIBAT AL FINAL DEL FRAGMENT DE MOSTRA",
ln=1, align='C')
retallPDF.cell(190, 10, txt="Per continuar gaudint del contigut del llibre, subscriviu-vos a Bookiernes",
ln=2, align='C')
retallPDF.output(llibre.pdf_retall.path + ".pdf")
# ES
retallES = FPDF()
retallES.add_page()
retallES.set_font("Arial", size=15)
es = open(llibre.es.path, "r")
for x in es:
retallES.multi_cell(200, 10, txt=x, border=0, align='J', fill=False)
retallES.cell(200, 10,
txt="HEU ARRIBAT AL FINAL DEL FRAGMENT DE MOSTRA\nHAS LLEGADO AL FINAL DEL FRAGMENTO DE MUESTRA ",
ln=1, align='C')
retallES.cell(200, 10,
txt="Per continuar gaudint del contingut del llibre, subscriviu-vos a Bookiernes\nPara continuar disfrutando del contenido del libro, suscríbase a Bookiernes ",
ln=2, align='C')
retallES.output(llibre.es_retall.path + ".pdf")
print(llibre.es_retall.path)
# EN
retallEN = FPDF()
retallEN.add_page()
retallEN.set_font("Arial", size=15)
en = open(llibre.en.path, "r")
for x in en:
retallEN.multi_cell(200, 10, txt=x, border=0, align='J', fill=False)
retallEN.cell(200, 10, txt="HEU ARRIBAT AL FINAL DEL FRAGMENT DE MOSTRA ",
ln=1, align='C')
retallEN.cell(200, 10, txt="YOU HAVE REACHED THE END OF THE SAMPLE FRAGMENT ",
ln=1, align='C')
retallEN.cell(200, 10, txt="Per continuar gaudint del contingut del llibre, subscriviu-vos a Bookiernes ",
ln=2, align='C')
retallEN.cell(200, 10, txt="To continue enjoying the contents of the book, subscribe to Bookiernes ",
ln=2, align='C')
retallEN.output(llibre.en_retall.path + ".pdf")
# PT
retallPT = FPDF()
retallPT.add_page()
retallPT.set_font("Arial", size=15)
pt = open(llibre.pt.path, "r")
for x in pt:
retallPT.multi_cell(200, 10, txt=x, border=0, align='J', fill=False)
retallPT.cell(200, 10, txt="HEU ARRIBAT AL FINAL DEL FRAGMENT DE MOSTRA ",
ln=1, align='C')
retallPT.cell(200, 10, txt="VOCÊ ALCANÇOU O FIM DO FRAGMENTO DE AMOSTRA ",
ln=1, align='C')
retallPT.cell(200, 10, txt="Per continuar gaudint del contingut del llibre, subscriviu-vos a Bookiernes",
ln=2, align='C')
retallPT.cell(200, 10, txt="Para continuar aproveitando o conteúdo do livro, assine Bookiernes",
ln=2, align='C')
retallPT.output(llibre.pt_retall.path + ".pdf")
# ZH
retallZH = FPDF()
retallZH.add_page()
retallZH.set_font("Arial", size=15)
zh = open(llibre.zh.path, "r")
for x in zh:
retallZH.multi_cell(200, 10, txt=x, border=0, align='J', fill=False)
retallZH.cell(200, 10, txt="HEU ARRIBAT AL FINAL DEL FRAGMENT DE MOSTRA",
ln=1, align='C')
retallZH.cell(200, 10, txt="Per continuar gaudint del contingut del llibre, subscriviu-vos a Bookiernes",
ln=2, align='C')
retallZH.output(llibre.zh_retall.path + ".pdf")
llibre.save()
def perfil(request, pkperfil):
usuari = CustomUser.objects.get(email=request.user)
llistallibres = list()
if usuari.is_Editor:
llistallibres = Llibre.objects.filter(editor=usuari)
if usuari.is_Escriptor:
llistallibres = Llibre.objects.filter(escriptor=usuari)
if usuari.is_Dissenyador:
llistallibres = Llibre.objects.filter(dissenyador=usuari)
if usuari.is_Maquetacio:
llistallibres = Llibre.objects.filter(maquetador=usuari)
if usuari.is_IT:
llistallibres = Llibre.objects.filter(it=usuari)
context = {
'llibres': llistallibres
}
return render(request, 'profile.html', context)
def configuracio(request, pkperfil):
usuari = CustomUser.objects.get(pk=pkperfil)
if request.method == 'POST':
form = ConfiguracioForm(request.POST)
if form.is_valid():
usuari.nom = form.cleaned_data.get('nom')
usuari.edat = form.cleaned_data.get('edat')
usuari.sexe = form.cleaned_data.get('sexe')
usuari.save()
return redirect(reverse('perfil', kwargs={'pkperfil': pkperfil}))
else:
form = ConfiguracioForm()
return render(request, 'configuracio_perfil.html', {'form': form})
def idiomes(request, pk):
llibre = Llibre.objects.get(pk=pk)
comentaris = Comentari.objects.filter(llibre=llibre)
context = {
"llibre": llibre,
"comentaris": comentaris
}
return render(request, 'idioma.html', context)
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test/pyroapi/test_pyroapi.py | MarcoGorelli/numpyro | 1 | 91191 | <reponame>MarcoGorelli/numpyro<filename>test/pyroapi/test_pyroapi.py
# Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
from pyroapi import pyro_backend
from pyroapi.tests import * # noqa F401
import pytest
pytestmark = pytest.mark.filterwarnings(
"ignore::numpyro.compat.util.UnsupportedAPIWarning",
"ignore:Currently, SVI does not support models with discrete",
)
@pytest.fixture
def backend():
with pyro_backend("numpy"):
yield
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knox/settings.py | liradb2000/django-rest-knox | 0 | 77872 | <filename>knox/settings.py
from datetime import timedelta
from django.conf import settings
from django.test.signals import setting_changed
from rest_framework.settings import APISettings, api_settings, import_from_string, perform_import, REMOVED_SETTINGS
USER_SETTINGS = getattr(settings, 'REST_KNOX', None)
DEFAULTS = {
'SECURE_HASH_ALGORITHM': 'cryptography.hazmat.primitives.hashes.SHA512',
'AUTH_TOKEN_CHARACTER_LENGTH': 64,
'TOKEN_TTL': timedelta(hours=10),
'USER_SERIALIZER': None,
'TOKEN_LIMIT_PER_USER': None,
'AUTO_REFRESH': False,
'MIN_REFRESH_INTERVAL': 60,
'AUTH_HEADER_PREFIX': 'Token',
'EXPIRY_DATETIME_FORMAT': api_settings.DATETIME_FORMAT,
'USE_COOKIE': False,
'COOKIE_SETTINGS': {
'NAME': 'partial_token',
'PATH': '/',
'DOMAIN': None,
'SECURE': False,
'HTTP_ONLY': True,
'SAMESITE': None
}
}
IMPORT_STRINGS = {
'SECURE_HASH_ALGORITHM',
'USER_SERIALIZER',
}
class knox_APISettings(APISettings):
def __init__(self, user_settings=None, defaults=None, import_strings=None):
self.defaults = defaults or DEFAULTS
if user_settings:
self._user_settings = self.__check_user_settings(user_settings)
self.import_strings = import_strings or IMPORT_STRINGS
self._cached_attrs = set()
def __getattr__(self, attr):
if attr not in self.defaults:
raise AttributeError("Invalid API setting: '%s'" % attr)
try:
# Check if present in user settings
val = self.user_settings[attr]
except KeyError:
# Fall back to defaults
val = self.defaults[attr]
# Coerce import strings into classes
if attr in self.import_strings:
val = perform_import(val, attr)
# Cache the result
self._cached_attrs.add(attr)
setattr(self, attr, val)
return val
def __check_user_settings(self, user_settings):
SETTINGS_DOC = "https://www.django-rest-framework.org/api-guide/settings/"
for attr, val in user_settings.items():
if isinstance(val, dict):
user_settings[attr]=dict(self.defaults.get(attr,{}), **val)
for setting in REMOVED_SETTINGS:
if setting in user_settings:
raise RuntimeError("The '%s' setting has been removed. Please refer to '%s' for available settings." % (setting, SETTINGS_DOC))
return user_settings
knox_settings = knox_APISettings(USER_SETTINGS, DEFAULTS, IMPORT_STRINGS)
def reload_api_settings(*args, **kwargs):
global knox_settings
setting, value = kwargs['setting'], kwargs['value']
if setting == 'REST_KNOX':
knox_settings = knox_APISettings(value, DEFAULTS, IMPORT_STRINGS)
setting_changed.connect(reload_api_settings)
class CONSTANTS:
'''
Constants cannot be changed at runtime
'''
TOKEN_KEY_LENGTH = 8
DIGEST_LENGTH = 128
def __setattr__(self, *args, **kwargs):
raise Exception('''
Constant values must NEVER be changed at runtime, as they are
integral to the structure of database tables
''')
CONSTANTS = CONSTANTS()
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misc/utils.py | citharus/AzuryModerator | 2 | 1605456 | from typing import Type
import motor.motor_asyncio as motor
from discord.ext import commands
__all__: list[str] = ["add_cogs", "replace_placeholders"]
def add_cogs(db: motor.AsyncIOMotorDatabase, bot: commands.Bot, cogs: list[Type[commands.Cog]]) -> None:
for cog in cogs:
bot.add_cog(cog(bot, db))
def replace_placeholders(string: str, replacements: dict) -> str:
for original, replacement in replacements.items():
string = string.replace(original, replacement)
return string
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src/scripts/flann.py | PenTesting/mlsvm | 0 | 84112 | <gh_stars>0
'''
Created on Feb 3, 2016
Version 1: March 8, 2016
The script reads 2 parameters from command line which are path and filename
It calculates the Flann and save the result, in the same path with similar file names
Drawback: convert from csr to ndarray and vise versa
@author: <NAME>
@note: read the data and calculate the flann
@input: PetscBinary format
@output: PetscBinary format
'''
import timeit
# import pickle
# import numpy as np
from sys import argv,exit,path
from os import environ
import scipy.sparse
from pyflann import *
from numpy import *
from numpy.random import *
dirs = environ['PETSC_DIR']
sys.path.insert(0, dirs+'/bin/')
#sys.path.insert(0, '/home/esfp/tools/libraries/petsc/bin/')
import PetscBinaryIO
def run_flann(file_path, file_name, num_NN, dist_type):
# read input in PetscBinary format
try:
start = timeit.default_timer()
print('Start reading input: '+file_path + file_name)
# mfile = open(outputfile,'r')
io = PetscBinaryIO.PetscBinaryIO()
#"scipy.sparse" is tested and works fine except, I need to convert it to numpy.ndarray and vise verse for flann and writing to petsc binary in the end
sparse_data= io.readBinaryFile(file_path + file_name, mattype='scipy.sparse')
# sparse_data= io.readBinaryFile(file_path + file_name, mattype='sparse') # not useful
#convert the "scipy.sparse.csr.csr_matrix" to "numpy.ndarray"
data = sparse_data[0].toarray()
print("data shape before transpose:"+ str(data.shape))
#data_T = transpose(data)
#print("data_T shape after transpose:"+ str(data_T.shape))
stop = timeit.default_timer()
print("Data is read from PETSc binary format: %.1f seconds" % (stop - start))
except e:
print("\n\nException in reading the input file:%s"% (file_path + file_name))
exit(1)
# print("data is:")
# print(data)
# print("data[0] is:")
# print(data[0])
try:
start = timeit.default_timer()
flann = FLANN()
if(dist_type == 3):
set_distance_type(3,100) #this is for flann Minkowski
else:
set_distance_type(int(dist_type))
m_result,m_dists = flann.nn(data, data, int(num_NN),algorithm="kdtree",branching=32, iterations=3, trees=1, checks=64);
stop = timeit.default_timer()
print("Flann calculation takes: %.1f seconds" % (stop - start))
except:
print("\n\nException in running Flann, error: %s" % sys.exc_info()[0])
exit(1)
#convert the "numpy.ndarray" to "scipy.sparse.csr.csr_matrix"
start = timeit.default_timer()
m_result_sparse= scipy.sparse.csr.csr_matrix(m_result);
m_dists_sparse= scipy.sparse.csr.csr_matrix(m_dists);
stop = timeit.default_timer()
print("Convert the ndarray to sparse takes: %.1f seconds" % (stop - start))
# save the result
try:
#no_suffix_name = file_name.split(".")[0]
start = timeit.default_timer()
#result_outputfile = file_path+''+ no_suffix_name+'_indices.dat'
result_outputfile = file_path+''+ file_name.split('.')[0]+'_indices.dat'
print('Outputing Data: '+result_outputfile)
result_file = open(result_outputfile,'w')
PetscBinaryIO.PetscBinaryIO().writeMatSciPy(result_file, m_result_sparse)
stop = timeit.default_timer()
print("result saved in PETSc format: %.1f seconds" % (stop - start))
except:
print("\n\nException in saving the result, error: %s"% sys.exc_info()[0])
exit(1)
try:
start = timeit.default_timer()
#dists_outputfile = file_path+''+ no_suffix_name+'_dists.dat'
dists_outputfile = file_path+''+ file_name.split('.')[0] +'_dists.dat'
print('Outputing Data: '+dists_outputfile)
dists_file = open(dists_outputfile,'w')
PetscBinaryIO.PetscBinaryIO().writeMatSciPy(dists_file, m_dists_sparse)
stop = timeit.default_timer()
print("dists saved in PETSc format: %.1f seconds" % (stop - start))
except:
print("\n\nException in saving the dists, error: %s" % sys.exc_info()[0])
exit(1)
if __name__ == '__main__':
debug = 0
file_path=""
file_name=""
if debug: # ----------------------- get parameters for debug -------------------------------
file_path = './'
file_name = 'kfold_min_train.dat'
else: # ----------------------- get parameters for production -------------------------------
if (len(argv)) < 4:
print ("please enter path and file_name")
print("Example: /data/ twonorm_min_data.dat int_num_NN int_dist_type \nExit due to lack of parameters!")
exit(1)
else:
try:
last_slash = argv[1].rfind('/')
file_path = argv[1][0:last_slash+1]
file_name = argv[1][last_slash+1:]
num_NN = argv[2]
dist_type = argv[3] # 1: squared euclidean distance
except:
print("\n\nException on input path and file name, try again!")
exit(1)
# --------------------- After reading parameters, run the script ------------------------
print("Input filename is: "+file_path+ file_name)
run_flann(file_path, file_name, num_NN, dist_type)
#serial 3
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] |
infapy/v3/agentService.py | infapy/infapy | 0 | 8345 | # Copyright (c) 2021-Present (<NAME>)
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import requests as re
import infapy
from infapy.exceptions import InvalidDetailsProvided
class AgentService():
def __init__(self,v3,v3BaseURL,v3SessionID):
self._v3 = v3
self._v3BaseURL = v3BaseURL
self._v3SessionID = v3SessionID
def updateAgentService(self,serviceName, serviceAction, agentId):
url=self._v3BaseURL + "/public/core/v3/agent/service"
headers = {'Content-Type': "application/json", 'Accept': "application/json","INFA-SESSION-ID":self._v3SessionID}
body = {
'serviceName':serviceName,
'serviceAction':serviceAction,
'agentId':agentId}
infapy.log.info("agentService API URL - " + url)
infapy.log.info("API Headers: " + str(headers))
infapy.log.info("Body: " + str(body))
try:
response = re.post(url=url, json=body, headers=headers)
data = response.json()
infapy.log.debug(str(data))
try:
if ("error" in data):
infapy.log.error("Please validate the details passed")
infapy.log.error(str(data))
raise InvalidDetailsProvided
except Exception as e:
infapy.log.exception(e)
raise
except Exception as e:
infapy.log.exception(e)
raise
infapy.log.info(data["message"])
return data | [
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src/components/examples/python-sample/pysample.py | ghsecuritylab/comanche | 19 | 100786 | <reponame>ghsecuritylab/comanche<filename>src/components/examples/python-sample/pysample.py
# python class
import sys
class Sample:
def __init__(self):
print("Python Sample component instantiated.")
def say_hello(self):
print("Say hello from Python my friend! :" + str(sys.version))
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tests/parallel/conftest.py | dtpryce/MLServer | 0 | 164959 | <reponame>dtpryce/MLServer
import asyncio
import pytest
from multiprocessing import Queue
from mlserver.settings import ModelSettings
from mlserver.types import InferenceRequest
from mlserver.utils import generate_uuid
from mlserver.model import MLModel
from mlserver.parallel.pool import InferencePool
from mlserver.parallel.worker import Worker
from mlserver.parallel.utils import cancel_task
from mlserver.parallel.messages import (
ModelUpdateMessage,
ModelUpdateType,
InferenceRequestMessage,
)
@pytest.fixture
async def inference_pool(
inference_pool: InferencePool, sum_model: MLModel
) -> InferencePool:
await inference_pool.load_model(sum_model)
yield inference_pool
await inference_pool.unload_model(sum_model)
@pytest.fixture
async def requests() -> Queue:
q = Queue()
yield q
q.close()
@pytest.fixture
async def responses() -> Queue:
q = Queue()
yield q
q.close()
@pytest.fixture
async def worker(
event_loop,
requests: Queue,
responses: Queue,
load_message: ModelUpdateMessage,
) -> Worker:
worker = Worker(requests, responses)
# Simulate the worker running on a different process, but keep it to a
# thread to simplify debugging.
# Note that we call `worker.coro_run` instead of `worker.run` to avoid also
# triggering the other set up methods of `worker.run`.
worker_task = event_loop.run_in_executor(
None, lambda: asyncio.run(worker.coro_run())
)
await worker.send_update(load_message)
yield worker
await worker.stop()
await cancel_task(worker_task)
@pytest.fixture
def load_message(sum_model_settings: ModelSettings) -> ModelUpdateMessage:
return ModelUpdateMessage(
update_type=ModelUpdateType.Load, model_settings=sum_model_settings
)
@pytest.fixture
def unload_message(sum_model_settings: ModelSettings) -> ModelUpdateMessage:
return ModelUpdateMessage(
update_type=ModelUpdateType.Unload, model_settings=sum_model_settings
)
@pytest.fixture
def inference_request_message(
sum_model_settings: ModelSettings, inference_request: InferenceRequest
) -> InferenceRequestMessage:
return InferenceRequestMessage(
id=generate_uuid(),
model_name=sum_model_settings.name,
model_version=sum_model_settings.parameters.version,
inference_request=inference_request,
)
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src/seak/cct.py | HealthML/seak | 2 | 72824 |
"""
Functions related to STAAR
"""
import numpy as np
from scipy.stats import cauchy
c = cauchy()
def cct(pvals, weights=None):
"""
Python port of the CCT function as defined in the STAAR R-package (https://github.com/xihaoli/STAAR/blob/2f67fafec591a45e81a54eca24564b09ce90e252/R/CCT.R)
An analytical p-value combination method using the Cauchy distribution.
takes in a numeric vector of p-values, a numeric vector of non-negative weights, and return the aggregated p-value using Cauchy method.
:param np.ndarray pval: Numpy array containing the p-values
:param np.ndarray weights: Numpy array containing the weights
:return: The aggregated p-value
:rtype: float
<NAME>., & <NAME>. (2020). Cauchy combination test: a powerful test with analytic p-value calculation under arbitrary dependency structures.
<NAME>., et al. (2019). Acat: A fast and powerful p value combination method for rare-variant analysis in sequencing studies.
"""
# check for NA
assert not np.isnan(pvals).any(), 'Error: Cannot have nan in the p-values!'
# check range
assert not (((pvals < 0).sum() + (pvals > 1).sum()) > 0), "Error: All p-values must be between 0 and 1"
# check for p-values that are either exactly 0 or 1
is_zero = (pvals == 0.).any()
is_one = (pvals == 1.).any()
assert not (is_zero & is_one), 'Error: Cannot have both 0 and 1 p-values'
if is_zero:
return 0
if is_one:
print('Warning: there are p-values that are exactly 1!')
return 1.
# check the validity of weights
if weights is None:
weights = np.ones_like(pvals) / len(pvals)
else:
assert len(weights) == len(pvals), 'Error: length of weights should be the same as that of the p-values!'
assert not ((weights < 0).any()), 'Error: all weights must be positive!'
weights /= weights.sum()
# check if there are very small non-zero p-values
is_small = pvals < 1e-16
if not is_small.any():
cct_stat = (weights * np.tan((0.5 - pvals) * np.pi)).sum()
else:
cct_stat = (weights[is_small] / pvals[is_small] / np.pi).sum()
cct_stat += (weights[~is_small] * np.tan((0.5 - pvals[~is_small]) * np.pi)).sum()
# check if the test statistic is very large
if (cct_stat > 1e15):
pval = (1. / cct_stat) / np.pi
else:
pval = c.sf(cct_stat)
return pval
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mease_elabftw/tests/test_metadata.py | ssciwr/mease-elabftw | 0 | 78273 | import pytest
import mease_elabftw
import test_ids
def test_get_metadata():
data = mease_elabftw.get_metadata(test_ids.valid_experiment)
assert len(data.keys()) == 9
start_time = data.get("ElectrodeGroup name")
assert start_time["value"] == "ElectrodeGroup"
description = data.get("Ecephys Device name")
assert description["value"] == "Device_ecephys"
def test_get_metadata_no_token(monkeypatch):
monkeypatch.delenv("ELABFTW_TOKEN")
with pytest.raises(Exception) as exception_info:
data = mease_elabftw.get_metadata(test_ids.valid_experiment)
assert exception_info.type == RuntimeError
assert (
str(exception_info.value)
== "The ELABFTW_TOKEN environment variable needs to be set to your eLabFTW access token."
)
def test_get_metadata_invalid_token(monkeypatch):
monkeypatch.setenv("ELABFTW_TOKEN", "<PASSWORD>")
with pytest.raises(Exception) as exception_info:
data = mease_elabftw.get_metadata(test_ids.valid_experiment)
assert exception_info.type == RuntimeError
assert (
str(exception_info.value)
== "Could not connect to https://elabftw.uni-heidelberg.de - do you have a valid token?"
)
def test_get_metadata_invalid_id(monkeypatch):
with pytest.raises(Exception) as exception_info:
data = mease_elabftw.get_metadata(test_ids.invalid_experiment)
assert exception_info.type == RuntimeError
assert (
str(exception_info.value)
== f"Experiment with id {test_ids.invalid_experiment} not found - do you have the correct id?"
)
def test_get_metadata_no_metadata():
with pytest.raises(Exception) as exception_info:
data = mease_elabftw.get_metadata(test_ids.valid_experiment_no_metadata)
assert exception_info.type == RuntimeError
assert (
str(exception_info.value)
== f"Experiment with id {test_ids.valid_experiment_no_metadata} doesn't contain any metadata."
)
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] |
src/oracle/handlers/handlers.py | orisi/orisi | 70 | 57721 | <filename>src/oracle/handlers/handlers.py
from timelock_contract.timelock_create_handler import TimelockCreateHandler
from bounty_contract.bounty_create_handler import BountyCreateHandler
from bounty_contract.bounty_redeem_handler import GuessPasswordHandler
from transactionsigner import TransactionSigner
from safe_timelock_contract.timelock_mark_release_handler import TimelockMarkReleaseHandler
from safe_timelock_contract.safe_timelock_create_handler import SafeTimelockCreateHandler
op_handlers = {
'sign': TransactionSigner,
'timelock_create': TimelockCreateHandler,
'bounty_create': BountyCreateHandler,
'bounty_redeem': GuessPasswordHandler,
'safe_timelock_create': SafeTimelockCreateHandler,
'timelock_mark_release': TimelockMarkReleaseHandler,
}
OPERATION_REQUIRED_FIELDS = {
'timelock_create': ['message_id', 'sum_satoshi', 'prevtxs', 'outputs', 'miners_fee_satoshi', 'return_address', 'locktime', 'pubkey_list', 'req_sigs'],
'bounty_create': ['prevtx', 'locktime', 'message_id', 'sum_amount', 'miners_fee', 'oracle_fees', 'pubkey_list', 'req_sigs', 'password_hash', 'return_address'],
'bounty_redeem': ['pwtxid', 'passwords'],
'timelock_mark_release': [],
'safe_timelock_create': ['message_id', 'oracle_fees', 'miners_fee_satoshi','return_address', 'locktime', 'pubkey_list', 'req_sigs'],
}
PROTOCOL_VERSION = '0.12'
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2
] |
plot_robeson.py | jsunn-y/gasseparationML | 0 | 104839 | <gh_stars>0
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
'''
Script to visualize permeability data in the O2/N2, CO2/CH4, CO2/N2, and H2/CO2 Robeson spaces.
Data must be a csv file with 6 columns in the order of ['He','H2','O2','N2','CO2','CH4'] permeabilities.
Update the filelist list with paths to each of the .csv files that are desired.
Works with the .csv outputs of screen.py and train.py.
'''
#change the paths to the files that are desired to be plotted
filelist= ['models/DNN_BLR_fing/Y_pred_datasetBX_fing.csv', 'models/DNN_BLR_fing/Y_pred_datasetCX_fing_0.csv', 'models/DNN_BLR_fing2/Y_pred_datasetDX_fing.csv', 'models/RF_BLR_fing/Y_train.csv']
sns.set_palette("colorblind")
#plot permeability values on a Robeson plot
fig = plt.figure(figsize=(12,8))
for i, dataset in enumerate(filelist[:-1]):
#read in the permeability data for each dataset
Y_pred = pd.read_csv(dataset, header=None)
Y_pred = np.array(Y_pred)
#O2/N2 separations
plt.subplot(2,2,1)
permeability = Y_pred[:,-4]
selectivity = Y_pred[:,-4] - Y_pred[:,-3]
plt.plot(permeability, selectivity, '.', alpha = 0.2)
#CO2/CH4 separations
plt.subplot(2,2,2)
permeability = Y_pred[:,-2]
selectivity = Y_pred[:,-2] - Y_pred[:,-1]
plt.plot(permeability, selectivity, '.', alpha=0.2)
#CO2/N2 separations
plt.subplot(2,2,3)
permeability = Y_pred[:,-2]
selectivity = Y_pred[:,-2] - Y_pred[:,-3]
plt.plot(permeability, selectivity, '.', alpha=0.2)
#H2/CO2 separations
plt.subplot(2,2,4)
permeability = Y_pred[:,-5]
selectivity = Y_pred[:,-5] - Y_pred[:,-2]
plt.plot(permeability, selectivity, '.', alpha=0.2)
#read in the permeability data for each dataset
Y_pred = pd.read_csv(filelist[-1], header=None)
Y_pred = np.array(Y_pred)
#O2/N2 separations
plt.subplot(2,2,1)
permeability = Y_pred[:,-4]
selectivity = Y_pred[:,-4] - Y_pred[:,-3]
plt.plot(permeability, selectivity, '.', markersize=3, color='k')
#CO2/CH4 separations
plt.subplot(2,2,2)
permeability = Y_pred[:,-2]
selectivity = Y_pred[:,-2] - Y_pred[:,-1]
plt.plot(permeability, selectivity, '.', markersize=3, color='k')
#CO2/N2 separations
plt.subplot(2,2,3)
permeability = Y_pred[:,-2]
selectivity = Y_pred[:,-2] - Y_pred[:,-3]
plt.plot(permeability, selectivity, '.', markersize=3, color='k')
#H2/CO2 separations
plt.subplot(2,2,4)
permeability = Y_pred[:,-5]
selectivity = Y_pred[:,-5] - Y_pred[:,-2]
plt.plot(permeability, selectivity, '.', markersize=3, color='k')
#format the plot and add Robeson upper bounds
plt.subplot(2,2,1)
xmin = -4
xmax = 7
plt.xlim([xmin, xmax])
plt.ylim([-1, 2])
plt.plot([xmin, xmax], [np.log10(9.2008)-0.1724*xmin, np.log10(9.2008)-0.1724*xmax], '-k') #1991 upper bound
plt.plot([xmin, xmax], [np.log10(12.148)-0.1765*xmin, np.log10(12.148)-0.1765*xmax], '--k') #2008 upper bound
plt.plot([xmin, xmax], [np.log10(18.50)-0.1754*xmin, np.log10(18.50)-0.1754*xmax], ':k') #2015 upper bound
plt.title("O2/N2 Separations")
#plt.legend(filelist)
plt.subplot(2,2,2)
xmin = -2
xmax =7
plt.xlim([xmin, xmax])
plt.ylim([-2, 4])
plt.plot([xmin, xmax], [np.log10(197.81)-0.3807*xmin, np.log10(197.81)-0.3807*xmax], '-k') #1991 upper bound
plt.plot([xmin, xmax], [np.log10(357.33)-0.3794*xmin, np.log10(357.33)-0.3794*xmax], '--k') #2008 upper bound
plt.plot([xmin, xmax], [np.log10(1155.60)-0.4165*xmin, np.log10(1155.60)-0.4165*xmax], ':k') #2019 upper bound
plt.title('CO2/CH4 Separations')
plt.subplot(2,2,3)
xmin = -2
xmax =7
plt.xlim([xmin, xmax])
plt.ylim([-1, 3])
plt.plot([xmin, xmax], -1/2.888*np.array([-np.log10(30967000)+xmin, -np.log10(30967000)+xmax]), '--k') #2008 upper bound
plt.plot([xmin, xmax], -1/3.409*np.array([-np.log10(755.58e6)+xmin, -np.log10(755.58e6)+xmax]), ':k') #2019 upper bound
plt.title('CO2/N2 Separations')
plt.subplot(2,2,4)
xmin = -2
xmax =7
plt.xlim([xmin, xmax])
plt.ylim([-1.5, 2])
plt.plot([xmin, xmax], -1/1.9363*np.array([-np.log10(1200)+xmin, -np.log10(1200)+xmax]), '-k') #1991 upper bound
plt.plot([xmin, xmax], -1/2.302*np.array([-np.log10(4515)+xmin, -np.log10(4515)+xmax]), '--k') #2008 upper bound
plt.title('H2/CO2 Separations')
plt.show()
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Generalisation/utils.py | act65/Experiments | 0 | 100141 | from __future__ import print_function
import tensorflow as tf
import tensorflow.contrib.slim as slim
from sklearn.utils import shuffle
def wide_net(x):
with slim.arg_scope([slim.fully_connected],
activation_fn=tf.nn.relu,
weights_initializer=tf.orthogonal_initializer(),
biases_initializer=tf.constant_initializer(0.0)):
h = slim.fully_connected(x, 1000)
return slim.fully_connected(h, 10, activation_fn=None)
def deep_net(x):
with slim.arg_scope([slim.fully_connected],
activation_fn=tf.nn.relu,
weights_initializer=tf.orthogonal_initializer(),
biases_initializer=tf.constant_initializer(0.0)):
h = slim.stack(x, slim.fully_connected, [200] * 17)
return slim.fully_connected(h, 10, activation_fn=None)
################################################################################
def batch(ims, labels, batchsize):
ims, labels = shuffle(ims, labels)
shape = ims.shape
for i in range(len(labels)//batchsize):
yield (i, ims[i*batchsize:(i+1)*batchsize, ...],
labels[i*batchsize:(i+1)*batchsize, ...])
def validate(sess, writer, step, x, T, valid_ims, valid_labels, batchsize, name=''):
### Validate classifier
metrics = tf.get_collection('METRICS')
updates = tf.get_collection('METRIC_UPDATES')
variables = tf.get_collection('LOCAL_VARIABLES', scope='metrics')
sess.run(tf.variables_initializer(variables))
# eval and aggregate
for _, batch_ims, batch_labels in batch(valid_ims, valid_labels, batchsize):
sess.run(updates, {x: batch_ims, T: batch_labels})
values = sess.run(metrics, {x: batch_ims, T: batch_labels})
# write summary
for k, v in zip(metrics, values):
add_summary(writer, step, 'valid/'+name, float(v))
def add_summary(writer, step, name, val):
summ = tf.Summary(value=[tf.Summary.Value(tag=name, simple_value=val)])
writer.add_summary(summ, step)
def get_loss_fn(name, logits):
return
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cbackup.py | andytaylor823/discord-draft-assist | 0 | 197905 | import functions as f
import defs as d
import discord
import error_messages as em
import numpy as np
# look for bad input with the error functions defined here
def check_bad_input(ctx, rd, pokemon, tier):
testfns = [check_no_primary_yet, check_backup_equals_primary]
e = ''
i = 0
while e == '' and i < len(testfns):
e = testfns[i](ctx, rd, pokemon, tier)
i += 1
return(e)
# check if the user has not already selected a primary
# if they have, they can't select a backup
def check_no_primary_yet(ctx, rd, pokemon, tier):
rd = int(rd)
user = ctx.author
if d.lists[user][rd-1] == 'None':
return(em.no_primary_yet)
return('')
# the user can't select the same backup as their primary
def check_backup_equals_primary(ctx, rd, pokemon, tier):
user = ctx.author
rd = int(rd)
user_primary = d.lists[user][rd-1]
if user_primary == pokemon:
return(em.backup_equals_primary)
return('')
# if the command has been entered correctly, apply the backup
def apply_backup(ctx, rd, pokemon, tier):
author = ctx.author
msg = 'Done! I have registered your Round {} backup as {} (Tier {})!\n'
msg = msg.format(str(rd), pokemon, str(tier))
msg += 'Remember, you can use the command "!list" at any time to see the list of the picks you have made and the ones you have planned!'
d.backups[author][int(rd)-1] = pokemon
return(msg)
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build_vocab/build_vocab.py | zaidalyafeai/pytorch-G2P | 22 | 197361 | """Standalone script to generate word vocabularies from monolingual corpus."""
import argparse
import data_utils
def main():
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument(
"--model_dir", default="../prepared_data/", help="Data for training")
parser.add_argument(
"--train_file", default="../naive_data/train", help="Data for training")
parser.add_argument(
"--valid_file", default="", help="Data for validation")
parser.add_argument(
"--test_file", default="", help="Data for test")
args = parser.parse_args()
data_utils.prepare_g2p_from_naive_data(args.model_dir,args.train_file, args.valid_file,args.test_file)
if __name__ == "__main__":
main()
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irlb/irlb.py | WeazelDev/ML_Project | 0 | 124002 | import numpy as np
import scipy.sparse as sp
import warnings
#import pdb
# Matrix-vector product wrapper
# A is a numpy 2d array or matrix, or a scipy matrix or sparse matrix.
# x is a numpy vector only.
# Compute A.dot(x) if t is False,
# A.transpose().dot(x) otherwise.
def mult(A, x, t=False):
if sp.issparse(A):
m = A.shape[0]
n = A.shape[1]
if(t):
return sp.csr_matrix(x).dot(A).transpose().todense().A[:,0]
return A.dot(sp.csr_matrix(x).transpose()).todense().A[:,0]
if t:
return x.dot(A)
return A.dot(x)
def orthog(Y,X):
"""Orthogonalize a vector or matrix Y against the columns of the matrix X.
This function requires that the column dimension of Y is less than X and
that Y and X have the same number of rows.
"""
dotY = mult(X,Y,t=True)
return Y - mult(X,dotY)
# Simple utility function used to check linear dependencies during computation:
def invcheck(x):
eps2 = 2*np.finfo(np.float).eps
if(x>eps2):
x = 1/x
else:
x = 0
warnings.warn("Ill-conditioning encountered, result accuracy may be poor")
return(x)
def tsvd(A,n,tol=0.0001,maxit=50):
"""Estimate a few of the largest singular values and corresponding singular
vectors of matrix using the implicitly restarted Lanczos bidiagonalization
method of Baglama and Reichel, see:
Augmented Implicitly Restarted Lanczos Bidiagonalization Methods,
<NAME> and <NAME>, SIAM J. Sci. Comput. 2005
Keyword arguments:
tol -- An estimation tolerance. Smaller means more accurate estimates.
maxit -- Maximum number of Lanczos iterations allowed.
Given an input matrix A of dimension j * k, and an input desired number
of singular values n, the function returns a tuple X with five entries:
X[0] A j * nu matrix of estimated left singular vectors.
X[1] A vector of length nu of estimated singular values.
X[2] A k * nu matrix of estimated right singular vectors.
X[3] The number of Lanczos iterations run.
X[4] The number of matrix-vector products run.
The algorithm estimates the truncated singular value decomposition:
A.dot(X[2]) = X[0]*X[1].
"""
nu = n
m = A.shape[0]
n = A.shape[1]
if(min(m,n)<2):
raise Exception("The input matrix must be at least 2x2.")
m_b = min((nu+20, 3*nu, n)) # Working dimension size
mprod = 0
it = 0
j = 0
k = nu
smax = 1
sparse = sp.issparse(A)
V = np.zeros((n,m_b))
W = np.zeros((m,m_b))
F = np.zeros((n,1))
B = np.zeros((m_b,m_b))
V[:,0] = np.random.randn(n) # Initial vector
V[:,0] = V[:,0]/np.linalg.norm(V)
while(it < maxit):
print("Iteration:", it)
if(it>0): j=k
W[:,j] = mult(A,V[:,j])
mprod+=1
if(it>0):
W[:,j] = orthog(W[:,j],W[:,0:j]) # NB W[:,0:j] selects columns 0,1,...,j-1
s = np.linalg.norm(W[:,j])
sinv = invcheck(s)
W[:,j] = sinv*W[:,j]
# Lanczos process
while(j<m_b):
F = mult(A,W[:,j],t=True)
mprod+=1
F = F - s*V[:,j]
F = orthog(F,V[:,0:j+1])
fn = np.linalg.norm(F)
fninv= invcheck(fn)
F = fninv * F
if(j<m_b-1):
V[:,j+1] = F
B[j,j] = s
B[j,j+1] = fn
W[:,j+1] = mult(A,V[:,j+1])
mprod+=1
# One step of classical Gram-Schmidt...
W[:,j+1] = W[:,j+1] - fn*W[:,j]
# ...with full reorthogonalization
W[:,j+1] = orthog(W[:,j+1],W[:,0:(j+1)])
s = np.linalg.norm(W[:,j+1])
sinv = invcheck(s)
W[:,j+1] = sinv * W[:,j+1]
else:
B[j,j] = s
j+=1
# End of Lanczos process
S = np.linalg.svd(B)
R = fn * S[0][m_b-1,:] # Residuals
if it<1:
smax = S[1][0] # Largest Ritz value
else:
smax = max((S[1][0],smax))
conv = sum(np.abs(R[0:nu]) < tol*smax)
if(conv < nu): # Not coverged yet
k = max(conv+nu,k)
k = min(k,m_b-3)
else:
break
# Update the Ritz vectors
V[:,0:k] = V[:,0:m_b].dot(S[2].transpose()[:,0:k])
V[:,k] = F
B = np.diag(S[1])
B[0:k,k] = R[0:k]
# Update the left approximate singular vectors
W[:,0:k] = W[:,0:m_b].dot(S[0][:,0:k])
it+=1
U = W[:,0:m_b].dot(S[0][:,0:nu])
V = V[:,0:m_b].dot(S[2].transpose()[:,0:nu])
return (U,S[1][0:nu],V,it,mprod) | [
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messaging/kombu_brighter/kombu_messaging.py | iancooper/RpcIsEvil | 0 | 24270 | """"
File : kombu_messaging.py
Author : ian
Created : 09-28-2016
Last Modified By : ian
Last Modified On : 09-28-2016
***********************************************************************
The MIT License (MIT)
Copyright © 2016 <NAME> <<EMAIL>>
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.
**********************************************************************i*
"""
from kombu.message import Message as Message
from core.messaging import BrightsideMessage, BrightsideMessageHeader, BrightsideMessageBody, BrightsideMessageType
from core.exceptions import MessagingException
from uuid import UUID, uuid4
from typing import Dict
import re
import codecs
message_type_header = "MessageType"
message_id_header = "MessageId"
message_correlation_id_header = "CorrelationId"
message_topic_name_header = "Topic"
message_handled_count_header = "HandledCount"
message_delay_milliseconds_header = "x-delay"
message_delayed_milliseconds_header = "x-delay"
message_original_message_id_header = "x-original-message-id"
message_delivery_tag_header = "DeliveryTag"
# See http://stackoverflow.com/questions/4020539/process-escape-sequences-in-a-string-in-python
ESCAPE_SEQUENCE_RE = re.compile(r'''
( \\U........ # 8-digit hex escapes
| \\u.... # 4-digit hex escapes
| \\x.. # 2-digit hex escapes
| \\[0-7]{1,3} # Octal escapes
| \\N\{[^}]+\} # Unicode characters by name
| \\[\\'"abfnrtv] # Single-character escapes
)''', re.UNICODE | re.VERBOSE)
def decode_escapes(s):
def decode_match(match):
return codecs.decode(match.group(0), 'unicode-escape')
return ESCAPE_SEQUENCE_RE.sub(decode_match, s)
class ReadError:
def __init__(self, error_message: str) -> None:
self.error_message = error_message
def __str__(self) -> str:
return self.error_message
class BrightsideMessageFactory:
"""
The message factory turn an 'on-the-wire' message into our internal representation. We try to be as
tolerant as possible (following Postel's Law: https://en.wikipedia.org/wiki/Robustness_principle) Be conservative
in what you do, be liberal in what you accept
"""
def __init__(self):
self._has_read_errors = False
def create_message(self, message: Message) -> BrightsideMessage:
self._has_read_errors = False
def _get_correlation_id() -> UUID:
header, err = self._read_header(message_correlation_id_header, message)
if err is None:
return UUID(header)
else:
self._has_read_errors = True
return ""
def _get_message_id() -> UUID:
header, err = self._read_header(message_id_header, message)
if err is None:
return UUID(header)
else:
self._has_read_errors = True
return uuid4()
def _get_message_type() -> BrightsideMessageType:
header, err = self._read_header(message_type_header, message)
if err is None:
return BrightsideMessageType(header)
else:
self._has_read_errors = True
return BrightsideMessageType.unacceptable
def _get_payload() -> str:
body, err = self._read_payload(message)
if err is None:
return body
else:
self._has_read_errors = True
return ""
def _get_payload_type() -> str:
payload_type, err = self._read_payload_type(message)
if err is None:
return payload_type
else:
self._has_read_errors = True
return ""
def _get_topic() -> str:
header, err = self._read_header(message_topic_name_header, message)
if err is None:
return header
else:
self._has_read_errors = True
return ""
message_id = _get_message_id()
topic = _get_topic()
message_type = _get_message_type() if not message.errors or self._has_read_errors else BrightsideMessageType.unacceptable
correlation_id = _get_correlation_id()
payload = _get_payload()
payload_type = _get_payload_type()
message_header = BrightsideMessageHeader(identity=message_id, topic=topic, message_type=message_type,
correlation_id=correlation_id, content_type="json")
message_body = BrightsideMessageBody(body=payload, body_type=payload_type)
return BrightsideMessage(message_header, message_body)
# All of these methods are warned as static, implies they should be helper classes that take state in constructor
def _read_header(self, header_key: str, message: Message) -> (str, ReadError):
if header_key not in message.headers.keys():
return "", ReadError("Could not read header with key: {}".format(header_key))
else:
return message.headers.get(header_key), None
def _read_payload(self, message: Message) -> (str, ReadError):
if not message.errors:
body_text = decode_escapes(message.body)
return body_text[1:-1], None
else:
errors = ", ".join(message.errors)
return "", ReadError("Could not parse message. Errors: {}".format(errors))
def _read_payload_type(self, message: Message) -> (str, ReadError):
if not message.errors:
return message.content_type, None
else:
errors = ", ".join(message.errors)
return "", ReadError("Could not read payload type. Errors: {}".format(errors))
class KombuMessageFactory():
def __init__(self, message: BrightsideMessage) -> None:
self._message = message
def create_message_header(self) -> Dict:
def _add_correlation_id(brightstide_message_header: Dict, correlation_id: UUID) -> None:
if correlation_id is not None:
brightstide_message_header[message_correlation_id_header] = correlation_id
def _add_message_id(brightside_message_header: Dict, identity: UUID) -> None:
if identity is None:
raise MessagingException("Missing id on message, this is a required field")
brightside_message_header[message_id_header] = identity
def _add_message_type(brightside_message_header: Dict, brightside_message_type: BrightsideMessageType) -> None:
if brightside_message_type is None:
raise MessagingException("Missing type on message, this is a required field")
brightside_message_header[message_type_header] = brightside_message_type
header = {}
_add_message_id(header, str(self._message.header.id))
_add_message_type(header, self._message.header.message_type.value)
_add_correlation_id(header, str(self._message.header.correlation_id))
return header
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] |
apps/materialPlanning/models.py | yhkl-dev/JAutoOps | 0 | 76466 | from django.db import models
from django.contrib.auth import get_user_model
from material.models import MaterialModel, MaterialGroup, Plant, ImportanceLevelModel, TechnologyCode, PurchaseTypeModel, ImportanceLevelModel, GICategoryModel
from workflow.models import WorkFlowEntityModel, WorkFlowModel
User = get_user_model()
class PlanningStatusRuleModel(models.Model):
status_name = models.CharField('status name', max_length=100, null=True, default=None, help_text='status name')
next_status_name = models.CharField('next status name', max_length=100, null=True, default=None, help_text='next status name')
comment = models.DateTimeField('comment', auto_now_add=True, help_text='create time')
def __str__(self):
return f"Rule: {self.status_name}:{self.next_status_name}"
class Meta:
ordering = ['id']
db_table = 't_material_planning_status'
class MaterialPlanningModel(models.Model):
STATUS_CHOICE = (
(1, 'Start'),
(2, 'Waiting'),
(3, 'MRHConfirming'),
(4, 'Pending'),
(5, 'MRHConfirmed'),
(6, 'STRConfirming'),
(7, 'STRConfirmed'),
(8, 'STRBalanced'), # pass -> STRFinished / reject STRConfirmed
(9, 'STRFinished'),
(10, 'OTBCollection'),
(11, 'PRProcessing'),
(12, 'OrderCreating'),
(13, 'OrderConfirming'),
(14, 'OrderConfirmed'),
(15, 'Producing'),
(16, 'Delivery'),
(17, 'GoodsReady'),
(18, 'GoodsReceived'),
(19, 'Invoice'),
(20, "Cancel")
)
material_number = models.ForeignKey(MaterialModel, on_delete=models.CASCADE, null=False,
verbose_name='material_basic_info',
related_name='material_basic_info', help_text='零件号')
plant = models.ForeignKey(Plant, on_delete=models.CASCADE, null=False,
verbose_name='plant_info',
related_name='plant_info', help_text='工厂代码')
material_group_name = models.ForeignKey(MaterialGroup, on_delete=models.CASCADE, null=False, verbose_name='material_group_name',
related_name='material_group_name', help_text='Material Group')
engineer_user = models.ForeignKey(User, on_delete=models.CASCADE, null=False, verbose_name='EngineerUser',
related_name='EngineerUser', help_text='维修计划负责人')
plant_tech_code = models.ForeignKey(TechnologyCode, on_delete=models.CASCADE, null=False, verbose_name='plant_tech_code_info',
related_name='plant_tech_code_info', help_text='Technology Code')
purchase_type = models.ForeignKey(PurchaseTypeModel, on_delete=models.CASCADE, null=False, verbose_name='purchase_type_info',
related_name='purchase_type_info', help_text='采购类型')
importance_level = models.ForeignKey(ImportanceLevelModel, on_delete=models.CASCADE, null=False, verbose_name='importance_level',
related_name='importance_level', help_text='采购类型')
gi_category = models.ForeignKey(GICategoryModel, on_delete=models.CASCADE, null=False, verbose_name='gi_category',
related_name='gi_category', help_text='GI类别')
workflow_template = models.ForeignKey(WorkFlowModel, on_delete=models.CASCADE, null=False, verbose_name='workflow template',
related_name='workflow_template', help_text='workflow template')
workflow_entity = models.ForeignKey(WorkFlowEntityModel, on_delete=models.CASCADE, null=False, verbose_name='workflow entity',
related_name='workflow_entity', help_text='workflow entity')
planning_status = models.CharField("current status",choices=STATUS_CHOICE, max_length=100, null=False, default="Start", help_text="Planning status")
storage_location = models.CharField('存储库位', max_length=100, null=True, default=None, help_text='Storage Location')
part_description_zh = models.CharField('零件描述(中文)', max_length=100, null=True, default=None, help_text='Part Description Zh')
part_description_en = models.CharField('零件描述(英文)', max_length=100, null=True, default=None, help_text='Part Description EN')
dimension = models.CharField('技术数据', max_length=100, null=True, default=None, help_text='Dimension')
min_stock = models.CharField('安全库存', max_length=100, null=True, default=None, help_text='Min Stock')
max_stock = models.CharField('最大库存量', max_length=100, null=True, default=None, help_text='Max Stock')
handover_stock = models.CharField('初始移交库存', max_length=100, null=True, default=None, help_text='Handover Stock')
unit = models.CharField('计量单位', max_length=100, null=True, default=None, help_text='Unit')
manufacturer_name = models.CharField('制造商名称', max_length=100, null=True, default=None, help_text='Manufacturer Name')
manufacturer_model = models.CharField('制造商的规格型号', max_length=100, null=True, default=None, help_text='Manufacturer Model')
manufacturer_part_number = models.CharField('制造商的订货号', max_length=100, null=True, default=None, help_text='Manufacturer Part Number')
supplier_code = models.CharField('供应商编码', max_length=100, null=True, default=None, help_text='Supplier Code')
supplier_name = models.CharField('供应商名称', max_length=100, null=True, default=None, help_text='Supplier Name')
supplier_model = models.CharField('供应商的规格型号', max_length=100, null=True, default=None, help_text='Supplier Model')
supplier_part_number = models.CharField('供应商的订货号', max_length=100, null=True, default=None, help_text='Supplier Part Number')
supplier_contact_person = models.CharField('供应商联系人', max_length=100, null=True, default=None, help_text='Supplier Contact Person')
supplier_contact_phone = models.CharField('供应商联系电话', max_length=100, null=True, default=None, help_text='Supplier Contact Phone')
supplier_email = models.CharField('供应商邮箱', max_length=100, null=True, default=None, help_text='Supplier Email')
fc_no = models.CharField('框架协议号码', max_length=100, null=True, default=None, help_text='FCNo')
unit_price = models.CharField('单价', max_length=100, null=True, default=None, help_text='Unit Price')
currency = models.CharField('货币', max_length=100, null=True, default=None, help_text='Currency')
equipment_name = models.CharField('设备名称', max_length=100, null=True, default=None, help_text='Equipment Name')
repairable = models.CharField('可修理的零件', max_length=100, null=True, default=None, help_text='Repairable')
calibration = models.CharField('校准件', max_length=100, null=True, default=None, help_text='Calibration')
drawing = models.CharField('图纸号', max_length=100, null=True, default=None, help_text='Drawing')
installation_quantity = models.CharField('安装数量', max_length=100, null=True, default=None, help_text='Installation Quantity')
part_special_treatment = models.CharField('零件特殊处理', max_length=100, null=True, default=None, help_text='PartSpecial Treatment')
surplus_stock = models.CharField('剩余库存', max_length=100, null=True, default=None, help_text='Surplus Stock')
create_at = models.DateTimeField('create time', auto_now_add=True, null=True, help_text='create time')
update_at = models.DateTimeField('update time', auto_now=True, help_text='update time')
def __str__(self):
return self.part_description_zh
class Meta:
ordering = ['id']
db_table = 't_material_planning'
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week07/code09.py | byeongal/KMUCP | 0 | 110671 | <filename>week07/code09.py
import turtle
t = turtle.Turtle()
color_list = ["black", "red", "green", "blue", "cyan", "yellow", "magenta"]
for i in range(7):
radius = (i + 1) * 10
t.color(color_list[i])
t.circle(radius)
turtle.mainloop() | [
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pyPLANES/pw/pw_classes.py | matael/pyPLANES | 0 | 11129 | #! /usr/bin/env python
# -*- coding:utf8 -*-
#
# pw_classes.py
#
# This file is part of pyplanes, a software distributed under the MIT license.
# For any question, please contact one of the authors cited below.
#
# Copyright (c) 2020
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
#
# 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.
#
import numpy as np
import numpy.linalg as LA
import matplotlib.pyplot as plt
from mediapack import from_yaml
from mediapack import Air, PEM, EqFluidJCA
from pyPLANES.utils.io import initialisation_out_files_plain
from pyPLANES.core.calculus import PwCalculus
from pyPLANES.core.multilayer import MultiLayer
from pyPLANES.pw.pw_layers import FluidLayer
from pyPLANES.pw.pw_interfaces import FluidFluidInterface, RigidBacking
Air = Air()
# def initialise_PW_solver(L, b):
# nb_PW = 0
# dofs = []
# for _layer in L:
# if _layer.medium.MODEL == "fluid":
# dofs.append(nb_PW+np.arange(2))
# nb_PW += 2
# elif _layer.medium.MODEL == "pem":
# dofs.append(nb_PW+np.arange(6))
# nb_PW += 6
# elif _layer.medium.MODEL == "elastic":
# dofs.append(nb_PW+np.arange(4))
# nb_PW += 4
# interface = []
# for i_l, _layer in enumerate(L[:-1]):
# interface.append((L[i_l].medium.MODEL, L[i_l+1].medium.MODEL))
# return nb_PW, interface, dofs
class PwProblem(PwCalculus, MultiLayer):
"""
Plane Wave Problem
"""
def __init__(self, **kwargs):
PwCalculus.__init__(self, **kwargs)
termination = kwargs.get("termination","rigid")
self.method = kwargs.get("termination","global")
MultiLayer.__init__(self, **kwargs)
self.kx, self.ky, self.k = None, None, None
self.shift_plot = kwargs.get("shift_pw", 0.)
self.plot = kwargs.get("plot_results", [False]*6)
self.result = {}
self.outfiles_directory = False
if self.method == "global":
self.layers.insert(0,FluidLayer(Air,1.e-2))
if self.layers[1].medium.MEDIUM_TYPE == "fluid":
self.interfaces.append(FluidFluidInterface(self.layers[0],self.layers[1]))
self.nb_PW = 0
for _layer in self.layers:
if _layer.medium.MODEL == "fluid":
_layer.dofs = self.nb_PW+np.arange(2)
self.nb_PW += 2
elif _layer.medium.MODEL == "pem":
_layer.dofs = self.nb_PW+np.arange(6)
self.nb_PW += 6
elif _layer.medium.MODEL == "elastic":
_layer.dofs = self.nb_PW+np.arange(4)
self.nb_PW += 4
def update_frequency(self, f):
PwCalculus.update_frequency(self, f)
MultiLayer.update_frequency(self, f, self.k, self.kx)
def create_linear_system(self, f):
self.A = np.zeros((self.nb_PW-1, self.nb_PW), dtype=complex)
i_eq = 0
# Loop on the interfaces
for _int in self.interfaces:
if self.method == "global":
i_eq = _int.update_M_global(self.A, i_eq)
# for i_inter, _inter in enumerate(self.interfaces):
# if _inter[0] == "fluid":
# if _inter[1] == "fluid":
# i_eq = self.interface_fluid_fluid(i_eq, i_inter, Layers, dofs, M)
# if _inter[1] == "pem":
# i_eq = self.interface_fluid_pem(i_eq, i_inter, Layers, dofs, M)
# if _inter[1] == "elastic":
# i_eq = self.interface_fluid_elastic(i_eq, i_inter, Layers, dofs, M)
# elif _inter[0] == "pem":
# if _inter[1] == "fluid":
# i_eq = self.interface_pem_fluid(i_eq, i_inter, Layers, dofs, M)
# if _inter[1] == "pem":
# i_eq = self.interface_pem_pem(i_eq, i_inter, Layers, dofs, M)
# if _inter[1] == "elastic":
# i_eq = self.interface_pem_elastic(i_eq, i_inter, Layers, dofs, M)
# elif _inter[0] == "elastic":
# if _inter[1] == "fluid":
# i_eq = self.interface_elastic_fluid(i_eq, i_inter, Layers, dofs, M)
# if _inter[1] == "pem":
# i_eq = self.interface_elastic_pem(i_eq, i_inter, Layers, dofs, M)
# if _inter[1] == "elastic":
# i_eq = self.interface_elastic_elastic(i_eq, i_inter, Layers, dofs, M)
# if self.backing == backing.rigid:
# if Layers[-1].medium.MODEL == "fluid":
# i_eq = self.interface_fluid_rigid(M, i_eq, Layers[-1], dofs[-1] )
# elif Layers[-1].medium.MODEL == "pem":
# i_eq = self.interface_pem_rigid(M, i_eq, Layers[-1], dofs[-1])
# elif Layers[-1].medium.MODEL == "elastic":
# i_eq = self.interface_elastic_rigid(M, i_eq, Layers[-1], dofs[-1])
# elif self.backing == "transmission":
# i_eq = self.semi_infinite_medium(M, i_eq, Layers[-1], dofs[-1] )
self.F = -self.A[:, 0]*np.exp(1j*self.ky*self.layers[0].d) # - is for transposition, exponential term is for the phase shift
self.A = np.delete(self.A, 0, axis=1)
# print(self.A)
X = LA.solve(self.A, self.F)
# print(X)
# R_pyPLANES_PW = X[0]
# if self.backing == "transmission":
# T_pyPLANES_PW = X[-2]
# else:
# T_pyPLANES_PW = 0.
# X = np.delete(X, 0)
# del(dofs[0])
# for i, _ld in enumerate(dofs):
# dofs[i] -= 2
# if self.plot:
# self.plot_sol_PW(X, dofs)
# out["R"] = R_pyPLANES_PW
# out["T"] = T_pyPLANES_PW
# return out
# class Solver_PW(PwCalculus):
# def __init__(self, **kwargs):
# PwCalculus.__init__(self, **kwargs)
# ml = kwargs.get("ml")
# termination = kwargs.get("termination")
# self.layers = []
# for _l in ml:
# if _l[0] == "Air":
# mat = Air
# else:
# mat = from_yaml(_l[0]+".yaml")
# d = _l[1]
# self.layers.append(Layer(mat,d))
# if termination in ["trans", "transmission","Transmission"]:
# self.backing = "Transmission"
# else:
# self.backing = backing.rigid
# self.kx, self.ky, self.k = None, None, None
# self.shift_plot = kwargs.get("shift_pw", 0.)
# self.plot = kwargs.get("plot_results", [False]*6)
# self.result = {}
# self.outfiles_directory = False
# initialisation_out_files_plain(self)
# def write_out_files(self, out):
# self.out_file.write("{:.12e}\t".format(self.current_frequency))
# abs = 1-np.abs(out["R"])**2
# self.out_file.write("{:.12e}\t".format(abs))
# self.out_file.write("\n")
# def interface_fluid_fluid(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = fluid_SV(self.kx, self.k, L[iinter].medium.K)
# SV_2, k_y_2 = fluid_SV(self.kx, self.k, L[iinter+1].medium.K)
# M[ieq, d[iinter+0][0]] = SV_1[0, 0]*np.exp(-1j*k_y_1*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[0, 1]
# M[ieq, d[iinter+1][0]] = -SV_2[0, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[0, 1]*np.exp(-1j*k_y_2*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = SV_1[1, 0]*np.exp(-1j*k_y_1*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[1, 1]
# M[ieq, d[iinter+1][0]] = -SV_2[1, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[1, 1]*np.exp(-1j*k_y_2*L[iinter+1].thickness)
# ieq += 1
# return ieq
# def interface_fluid_rigid(self, M, ieq, L, d):
# SV, k_y = fluid_SV(self.kx, self.k, L.medium.K)
# M[ieq, d[0]] = SV[0, 0]*np.exp(-1j*k_y*L.thickness)
# M[ieq, d[1]] = SV[0, 1]
# ieq += 1
# return ieq
# def semi_infinite_medium(self, M, ieq, L, d):
# M[ieq, d[1]] = 1.
# ieq += 1
# return ieq
# def interface_pem_pem(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = PEM_SV(L[iinter].medium, self.kx)
# SV_2, k_y_2 = PEM_SV(L[iinter+1].medium, self.kx)
# for _i in range(6):
# M[ieq, d[iinter+0][0]] = SV_1[_i, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[_i, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[_i, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = SV_1[_i, 3]
# M[ieq, d[iinter+0][4]] = SV_1[_i, 4]
# M[ieq, d[iinter+0][5]] = SV_1[_i, 5]
# M[ieq, d[iinter+1][0]] = -SV_2[_i, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[_i, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[_i, 2]
# M[ieq, d[iinter+1][3]] = -SV_2[_i, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = -SV_2[_i, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = -SV_2[_i, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# return ieq
# def interface_fluid_pem(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = fluid_SV(self.kx, self.k, L[iinter].medium.K)
# SV_2, k_y_2 = PEM_SV(L[iinter+1].medium,self.kx)
# # print(k_y_2)
# M[ieq, d[iinter+0][0]] = SV_1[0, 0]*np.exp(-1j*k_y_1*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[0, 1]
# M[ieq, d[iinter+1][0]] = -SV_2[2, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[2, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[2, 2]
# M[ieq, d[iinter+1][3]] = -SV_2[2, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = -SV_2[2, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = -SV_2[2, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = SV_1[1, 0]*np.exp(-1j*k_y_1*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[1, 1]
# M[ieq, d[iinter+1][0]] = -SV_2[4, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[4, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[4, 2]
# M[ieq, d[iinter+1][3]] = -SV_2[4, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = -SV_2[4, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = -SV_2[4, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+1][0]] = SV_2[0, 0]
# M[ieq, d[iinter+1][1]] = SV_2[0, 1]
# M[ieq, d[iinter+1][2]] = SV_2[0, 2]
# M[ieq, d[iinter+1][3]] = SV_2[0, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = SV_2[0, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = SV_2[0, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+1][0]] = SV_2[3, 0]
# M[ieq, d[iinter+1][1]] = SV_2[3, 1]
# M[ieq, d[iinter+1][2]] = SV_2[3, 2]
# M[ieq, d[iinter+1][3]] = SV_2[3, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = SV_2[3, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = SV_2[3, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# return ieq
# def interface_elastic_pem(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = elastic_SV(L[iinter].medium,self.kx, self.omega)
# SV_2, k_y_2 = PEM_SV(L[iinter+1].medium,self.kx)
# # print(k_y_2)
# M[ieq, d[iinter+0][0]] = -SV_1[0, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = -SV_1[0, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = -SV_1[0, 2]
# M[ieq, d[iinter+0][3]] = -SV_1[0, 3]
# M[ieq, d[iinter+1][0]] = SV_2[0, 0]
# M[ieq, d[iinter+1][1]] = SV_2[0, 1]
# M[ieq, d[iinter+1][2]] = SV_2[0, 2]
# M[ieq, d[iinter+1][3]] = SV_2[0, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = SV_2[0, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = SV_2[0, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = -SV_1[1, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = -SV_1[1, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = -SV_1[1, 2]
# M[ieq, d[iinter+0][3]] = -SV_1[1, 3]
# M[ieq, d[iinter+1][0]] = SV_2[1, 0]
# M[ieq, d[iinter+1][1]] = SV_2[1, 1]
# M[ieq, d[iinter+1][2]] = SV_2[1, 2]
# M[ieq, d[iinter+1][3]] = SV_2[1, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = SV_2[1, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = SV_2[1, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = -SV_1[1, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = -SV_1[1, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = -SV_1[1, 2]
# M[ieq, d[iinter+0][3]] = -SV_1[1, 3]
# M[ieq, d[iinter+1][0]] = SV_2[2, 0]
# M[ieq, d[iinter+1][1]] = SV_2[2, 1]
# M[ieq, d[iinter+1][2]] = SV_2[2, 2]
# M[ieq, d[iinter+1][3]] = SV_2[2, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = SV_2[2, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = SV_2[2, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = -SV_1[2, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = -SV_1[2, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = -SV_1[2, 2]
# M[ieq, d[iinter+0][3]] = -SV_1[2, 3]
# M[ieq, d[iinter+1][0]] = (SV_2[3, 0]-SV_2[4, 0])
# M[ieq, d[iinter+1][1]] = (SV_2[3, 1]-SV_2[4, 1])
# M[ieq, d[iinter+1][2]] = (SV_2[3, 2]-SV_2[4, 2])
# M[ieq, d[iinter+1][3]] = (SV_2[3, 3]-SV_2[4, 3])*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = (SV_2[3, 4]-SV_2[4, 4])*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = (SV_2[3, 5]-SV_2[4, 5])*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = -SV_1[3, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = -SV_1[3, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = -SV_1[3, 2]
# M[ieq, d[iinter+0][3]] = -SV_1[3, 3]
# M[ieq, d[iinter+1][0]] = SV_2[5, 0]
# M[ieq, d[iinter+1][1]] = SV_2[5, 1]
# M[ieq, d[iinter+1][2]] = SV_2[5, 2]
# M[ieq, d[iinter+1][3]] = SV_2[5, 3]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][4]] = SV_2[5, 4]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][5]] = SV_2[5, 5]*np.exp(-1j*k_y_2[2]*L[iinter+1].thickness)
# ieq += 1
# return ieq
# def interface_pem_elastic(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = PEM_SV(L[iinter].medium,self.kx)
# SV_2, k_y_2 = elastic_SV(L[iinter+1].medium,self.kx, self.omega)
# # print(k_y_2)
# M[ieq, d[iinter+0][0]] = SV_1[0, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[0, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[0, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = SV_1[0, 3]
# M[ieq, d[iinter+0][4]] = SV_1[0, 4]
# M[ieq, d[iinter+0][5]] = SV_1[0, 5]
# M[ieq, d[iinter+1][0]] = -SV_2[0, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[0, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[0, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = -SV_2[0, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = SV_1[1, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[1, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[1, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = SV_1[1, 3]
# M[ieq, d[iinter+0][4]] = SV_1[1, 4]
# M[ieq, d[iinter+0][5]] = SV_1[1, 5]
# M[ieq, d[iinter+1][0]] = -SV_2[1, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[1, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[1, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = -SV_2[1, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = SV_1[2, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[2, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[2, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = SV_1[2, 3]
# M[ieq, d[iinter+0][4]] = SV_1[2, 4]
# M[ieq, d[iinter+0][5]] = SV_1[2, 5]
# M[ieq, d[iinter+1][0]] = -SV_2[1, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[1, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[1, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = -SV_2[1, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = (SV_1[3, 0]-SV_1[4, 0])*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = (SV_1[3, 1]-SV_1[4, 1])*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = (SV_1[3, 2]-SV_1[4, 2])*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = (SV_1[3, 3]-SV_1[4, 3])
# M[ieq, d[iinter+0][4]] = (SV_1[3, 4]-SV_1[4, 4])
# M[ieq, d[iinter+0][5]] = (SV_1[3, 5]-SV_1[4, 5])
# M[ieq, d[iinter+1][0]] = -SV_2[2, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[2, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[2, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = -SV_2[2, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = SV_1[5, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[5, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[5, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = SV_1[5, 3]
# M[ieq, d[iinter+0][4]] = SV_1[5, 4]
# M[ieq, d[iinter+0][5]] = SV_1[5, 5]
# M[ieq, d[iinter+1][0]] = -SV_2[3, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[3, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[3, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = -SV_2[3, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# return ieq
# def interface_elastic_elastic(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = elastic_SV(L[iinter].medium,self.kx, self.omega)
# SV_2, k_y_2 = elastic_SV(L[iinter+1].medium,self.kx, self.omega)
# for _i in range(4):
# M[ieq, d[iinter+0][0]] = SV_1[_i, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[_i, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[_i, 2]
# M[ieq, d[iinter+0][3]] = SV_1[_i, 3]
# M[ieq, d[iinter+1][0]] = -SV_2[_i, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[_i, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[_i, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = -SV_2[_i, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# return ieq
# def interface_fluid_elastic(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = fluid_SV(self.kx, self.k, L[iinter].medium.K)
# SV_2, k_y_2 = elastic_SV(L[iinter+1].medium, self.kx, self.omega)
# # Continuity of u_y
# M[ieq, d[iinter+0][0]] = SV_1[0, 0]*np.exp(-1j*k_y_1*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[0, 1]
# M[ieq, d[iinter+1][0]] = -SV_2[1, 0]
# M[ieq, d[iinter+1][1]] = -SV_2[1, 1]
# M[ieq, d[iinter+1][2]] = -SV_2[1, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = -SV_2[1, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# # sigma_yy = -p
# M[ieq, d[iinter+0][0]] = SV_1[1, 0]*np.exp(-1j*k_y_1*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[1, 1]
# M[ieq, d[iinter+1][0]] = SV_2[2, 0]
# M[ieq, d[iinter+1][1]] = SV_2[2, 1]
# M[ieq, d[iinter+1][2]] = SV_2[2, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = SV_2[2, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# # sigma_xy = 0
# M[ieq, d[iinter+1][0]] = SV_2[0, 0]
# M[ieq, d[iinter+1][1]] = SV_2[0, 1]
# M[ieq, d[iinter+1][2]] = SV_2[0, 2]*np.exp(-1j*k_y_2[0]*L[iinter+1].thickness)
# M[ieq, d[iinter+1][3]] = SV_2[0, 3]*np.exp(-1j*k_y_2[1]*L[iinter+1].thickness)
# ieq += 1
# return ieq
# def interface_pem_fluid(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = PEM_SV(L[iinter].medium, self.kx)
# SV_2, k_y_2 = fluid_SV(self.kx, self.k, L[iinter+1].medium.K)
# # print(k_y_2)
# M[ieq, d[iinter+0][0]] = -SV_1[2, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = -SV_1[2, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = -SV_1[2, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = -SV_1[2, 3]
# M[ieq, d[iinter+0][4]] = -SV_1[2, 4]
# M[ieq, d[iinter+0][5]] = -SV_1[2, 5]
# M[ieq, d[iinter+1][0]] = SV_2[0, 0]
# M[ieq, d[iinter+1][1]] = SV_2[0, 1]*np.exp(-1j*k_y_2*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = -SV_1[4, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = -SV_1[4, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = -SV_1[4, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = -SV_1[4, 3]
# M[ieq, d[iinter+0][4]] = -SV_1[4, 4]
# M[ieq, d[iinter+0][5]] = -SV_1[4, 5]
# M[ieq, d[iinter+1][0]] = SV_2[1, 0]
# M[ieq, d[iinter+1][1]] = SV_2[1, 1]*np.exp(-1j*k_y_2*L[iinter+1].thickness)
# ieq += 1
# M[ieq, d[iinter+0][0]] = SV_1[0, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[0, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[0, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = SV_1[0, 3]
# M[ieq, d[iinter+0][4]] = SV_1[0, 4]
# M[ieq, d[iinter+0][5]] = SV_1[0, 5]
# ieq += 1
# M[ieq, d[iinter+0][0]] = SV_1[3, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[3, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[3, 2]*np.exp(-1j*k_y_1[2]*L[iinter].thickness)
# M[ieq, d[iinter+0][3]] = SV_1[3, 3]
# M[ieq, d[iinter+0][4]] = SV_1[3, 4]
# M[ieq, d[iinter+0][5]] = SV_1[3, 5]
# ieq += 1
# return ieq
# def interface_elastic_fluid(self, ieq, iinter, L, d, M):
# SV_1, k_y_1 = elastic_SV(L[iinter].medium, self.kx, self.omega)
# SV_2, k_y_2 = fluid_SV(self.kx, self.k, L[iinter+1].medium.K)
# # Continuity of u_y
# M[ieq, d[iinter+0][0]] = -SV_1[1, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = -SV_1[1, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = -SV_1[1, 2]
# M[ieq, d[iinter+0][3]] = -SV_1[1, 3]
# M[ieq, d[iinter+1][0]] = SV_2[0, 0]
# M[ieq, d[iinter+1][1]] = SV_2[0, 1]*np.exp(-1j*k_y_2*L[iinter+1].thickness)
# ieq += 1
# # sigma_yy = -p
# M[ieq, d[iinter+0][0]] = SV_1[2, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[2, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[2, 2]
# M[ieq, d[iinter+0][3]] = SV_1[2, 3]
# M[ieq, d[iinter+1][0]] = SV_2[1, 0]
# M[ieq, d[iinter+1][1]] = SV_2[1, 1]*np.exp(-1j*k_y_2*L[iinter+1].thickness)
# ieq += 1
# # sigma_xy = 0
# M[ieq, d[iinter+0][0]] = SV_1[0, 0]*np.exp(-1j*k_y_1[0]*L[iinter].thickness)
# M[ieq, d[iinter+0][1]] = SV_1[0, 1]*np.exp(-1j*k_y_1[1]*L[iinter].thickness)
# M[ieq, d[iinter+0][2]] = SV_1[0, 2]
# M[ieq, d[iinter+0][3]] = SV_1[0, 3]
# ieq += 1
# return ieq
# def interface_elastic_rigid(self, M, ieq, L, d):
# SV, k_y = elastic_SV(L.medium,self.kx, self.omega)
# M[ieq, d[0]] = SV[1, 0]*np.exp(-1j*k_y[0]*L.thickness)
# M[ieq, d[1]] = SV[1, 1]*np.exp(-1j*k_y[1]*L.thickness)
# M[ieq, d[2]] = SV[1, 2]
# M[ieq, d[3]] = SV[1, 3]
# ieq += 1
# M[ieq, d[0]] = SV[3, 0]*np.exp(-1j*k_y[0]*L.thickness)
# M[ieq, d[1]] = SV[3, 1]*np.exp(-1j*k_y[1]*L.thickness)
# M[ieq, d[2]] = SV[3, 2]
# M[ieq, d[3]] = SV[3, 3]
# ieq += 1
# return ieq
# def interface_pem_rigid(self, M, ieq, L, d):
# SV, k_y = PEM_SV(L.medium, self.kx)
# M[ieq, d[0]] = SV[1, 0]*np.exp(-1j*k_y[0]*L.thickness)
# M[ieq, d[1]] = SV[1, 1]*np.exp(-1j*k_y[1]*L.thickness)
# M[ieq, d[2]] = SV[1, 2]*np.exp(-1j*k_y[2]*L.thickness)
# M[ieq, d[3]] = SV[1, 3]
# M[ieq, d[4]] = SV[1, 4]
# M[ieq, d[5]] = SV[1, 5]
# ieq += 1
# M[ieq, d[0]] = SV[2, 0]*np.exp(-1j*k_y[0]*L.thickness)
# M[ieq, d[1]] = SV[2, 1]*np.exp(-1j*k_y[1]*L.thickness)
# M[ieq, d[2]] = SV[2, 2]*np.exp(-1j*k_y[2]*L.thickness)
# M[ieq, d[3]] = SV[2, 3]
# M[ieq, d[4]] = SV[2, 4]
# M[ieq, d[5]] = SV[2, 5]
# ieq += 1
# M[ieq, d[0]] = SV[5, 0]*np.exp(-1j*k_y[0]*L.thickness)
# M[ieq, d[1]] = SV[5, 1]*np.exp(-1j*k_y[1]*L.thickness)
# M[ieq, d[2]] = SV[5, 2]*np.exp(-1j*k_y[2]*L.thickness)
# M[ieq, d[3]] = SV[5, 3]
# M[ieq, d[4]] = SV[5, 4]
# M[ieq, d[5]] = SV[5, 5]
# ieq += 1
# return ieq
# def plot_sol_PW(self, X, dofs):
# x_start = self.shift_plot
# for _l, _layer in enumerate(self.layers):
# x_f = np.linspace(0, _layer.thickness,200)
# x_b = x_f-_layer.thickness
# if _layer.medium.MODEL == "fluid":
# SV, k_y = fluid_SV(self.kx, self.k, _layer.medium.K)
# pr = SV[1, 0]*np.exp(-1j*k_y*x_f)*X[dofs[_l][0]]
# pr += SV[1, 1]*np.exp( 1j*k_y*x_b)*X[dofs[_l][1]]
# ut = SV[0, 0]*np.exp(-1j*k_y*x_f)*X[dofs[_l][0]]
# ut += SV[0, 1]*np.exp( 1j*k_y*x_b)*X[dofs[_l][1]]
# if self.plot[2]:
# plt.figure(2)
# plt.plot(x_start+x_f, np.abs(pr), 'r')
# plt.plot(x_start+x_f, np.imag(pr), 'm')
# plt.title("Pressure")
# # plt.figure(5)
# # plt.plot(x_start+x_f,np.abs(ut),'b')
# # plt.plot(x_start+x_f,np.imag(ut),'k')
# if _layer.medium.MODEL == "pem":
# SV, k_y = PEM_SV(_layer.medium, self.kx)
# ux, uy, pr, ut = 0*1j*x_f, 0*1j*x_f, 0*1j*x_f, 0*1j*x_f
# for i_dim in range(3):
# ux += SV[1, i_dim ]*np.exp(-1j*k_y[i_dim]*x_f)*X[dofs[_l][i_dim]]
# ux += SV[1, i_dim+3]*np.exp( 1j*k_y[i_dim]*x_b)*X[dofs[_l][i_dim+3]]
# uy += SV[5, i_dim ]*np.exp(-1j*k_y[i_dim]*x_f)*X[dofs[_l][i_dim]]
# uy += SV[5, i_dim+3]*np.exp( 1j*k_y[i_dim]*x_b)*X[dofs[_l][i_dim+3]]
# pr += SV[4, i_dim ]*np.exp(-1j*k_y[i_dim]*x_f)*X[dofs[_l][i_dim]]
# pr += SV[4, i_dim+3]*np.exp( 1j*k_y[i_dim]*x_b)*X[dofs[_l][i_dim+3]]
# ut += SV[2, i_dim ]*np.exp(-1j*k_y[i_dim]*x_f)*X[dofs[_l][i_dim]]
# ut += SV[2, i_dim+3]*np.exp( 1j*k_y[i_dim]*x_b)*X[dofs[_l][i_dim+3]]
# if self.plot[0]:
# plt.figure(0)
# plt.plot(x_start+x_f, np.abs(uy), 'r')
# plt.plot(x_start+x_f, np.imag(uy), 'm')
# plt.title("Solid displacement along x")
# if self.plot[1]:
# plt.figure(1)
# plt.plot(x_start+x_f, np.abs(ux), 'r')
# plt.plot(x_start+x_f, np.imag(ux), 'm')
# plt.title("Solid displacement along y")
# if self.plot[2]:
# plt.figure(2)
# plt.plot(x_start+x_f, np.abs(pr), 'r')
# plt.plot(x_start+x_f, np.imag(pr), 'm')
# plt.title("Pressure")
# if _layer.medium.MODEL == "elastic":
# SV, k_y = elastic_SV(_layer.medium, self.kx, self.omega)
# ux, uy, pr, sig = 0*1j*x_f, 0*1j*x_f, 0*1j*x_f, 0*1j*x_f
# for i_dim in range(2):
# ux += SV[1, i_dim ]*np.exp(-1j*k_y[i_dim]*x_f)*X[dofs[_l][i_dim]]
# ux += SV[1, i_dim+2]*np.exp( 1j*k_y[i_dim]*x_b)*X[dofs[_l][i_dim+2]]
# uy += SV[3, i_dim ]*np.exp(-1j*k_y[i_dim]*x_f)*X[dofs[_l][i_dim]]
# uy += SV[3, i_dim+2]*np.exp( 1j*k_y[i_dim]*x_b)*X[dofs[_l][i_dim+2]]
# pr -= SV[2, i_dim ]*np.exp(-1j*k_y[i_dim]*x_f)*X[dofs[_l][i_dim]]
# pr -= SV[2, i_dim+2]*np.exp( 1j*k_y[i_dim]*x_b)*X[dofs[_l][i_dim+2]]
# sig -= SV[0, i_dim ]*np.exp(-1j*k_y[i_dim]*x_f)*X[dofs[_l][i_dim]]
# sig -= SV[0, i_dim+2]*np.exp( 1j*k_y[i_dim]*x_b)*X[dofs[_l][i_dim+2]]
# if self.plot[0]:
# plt.figure(0)
# plt.plot(x_start+x_f, np.abs(uy), 'r')
# plt.plot(x_start+x_f, np.imag(uy), 'm')
# plt.title("Solid displacement along x")
# if self.plot[1]:
# plt.figure(1)
# plt.plot(x_start+x_f, np.abs(ux), 'r')
# plt.plot(x_start+x_f, np.imag(ux), 'm')
# plt.title("Solid displacement along y")
# # if self.plot[2]:
# # plt.figure(2)
# # plt.plot(x_start+x_f, np.abs(pr), 'r')
# # plt.plot(x_start+x_f, np.imag(pr), 'm')
# # plt.title("Sigma_yy")
# # if self.plot[2]:
# # plt.figure(3)
# # plt.plot(x_start+x_f, np.abs(sig), 'r')
# # plt.plot(x_start+x_f, np.imag(sig), 'm')
# # plt.title("Sigma_xy")
# x_start += _layer.thickness
# def PEM_SV(mat,ky):
# ''' S={0:\hat{\sigma}_{xy}, 1:u_y^s, 2:u_y^t, 3:\hat{\sigma}_{yy}, 4:p, 5:u_x^s}'''
# kx_1 = np.sqrt(mat.delta_1**2-ky**2)
# kx_2 = np.sqrt(mat.delta_2**2-ky**2)
# kx_3 = np.sqrt(mat.delta_3**2-ky**2)
# kx = np.array([kx_1, kx_2, kx_3])
# delta = np.array([mat.delta_1, mat.delta_2, mat.delta_3])
# alpha_1 = -1j*mat.A_hat*mat.delta_1**2-1j*2*mat.N*kx[0]**2
# alpha_2 = -1j*mat.A_hat*mat.delta_2**2-1j*2*mat.N*kx[1]**2
# alpha_3 = -2*1j*mat.N*kx[2]*ky
# SV = np.zeros((6,6), dtype=complex)
# SV[0:6, 0] = np.array([-2*1j*mat.N*kx[0]*ky, kx[0], mat.mu_1*kx[0], alpha_1, 1j*delta[0]**2*mat.K_eq_til*mat.mu_1, ky])
# SV[0:6, 3] = np.array([ 2*1j*mat.N*kx[0]*ky,-kx[0],-mat.mu_1*kx[0], alpha_1, 1j*delta[0]**2*mat.K_eq_til*mat.mu_1, ky])
# SV[0:6, 1] = np.array([-2*1j*mat.N*kx[1]*ky, kx[1], mat.mu_2*kx[1],alpha_2, 1j*delta[1]**2*mat.K_eq_til*mat.mu_2, ky])
# SV[0:6, 4] = np.array([ 2*1j*mat.N*kx[1]*ky,-kx[1],-mat.mu_2*kx[1],alpha_2, 1j*delta[1]**2*mat.K_eq_til*mat.mu_2, ky])
# SV[0:6, 2] = np.array([1j*mat.N*(kx[2]**2-ky**2), ky, mat.mu_3*ky, alpha_3, 0., -kx[2]])
# SV[0:6, 5] = np.array([1j*mat.N*(kx[2]**2-ky**2), ky, mat.mu_3*ky, -alpha_3, 0., kx[2]])
# return SV, kx
# def elastic_SV(mat,ky, omega):
# ''' S={0:\sigma_{xy}, 1: u_y, 2 \sigma_{yy}, 3 u_x}'''
# P_mat = mat.lambda_ + 2.*mat.mu
# delta_p = omega*np.sqrt(mat.rho/P_mat)
# delta_s = omega*np.sqrt(mat.rho/mat.mu)
# kx_p = np.sqrt(delta_p**2-ky**2)
# kx_s = np.sqrt(delta_s**2-ky**2)
# kx = np.array([kx_p, kx_s])
# alpha_p = -1j*mat.lambda_*delta_p**2 - 2j*mat.mu*kx[0]**2
# alpha_s = 2j*mat.mu*kx[1]*ky
# SV = np.zeros((4, 4), dtype=np.complex)
# SV[0:4, 0] = np.array([-2.*1j*mat.mu*kx[0]*ky, kx[0], alpha_p, ky])
# SV[0:4, 2] = np.array([ 2.*1j*mat.mu*kx[0]*ky, -kx[0], alpha_p, ky])
# SV[0:4, 1] = np.array([1j*mat.mu*(kx[1]**2-ky**2), ky,-alpha_s, -kx[1]])
# SV[0:4, 3] = np.array([1j*mat.mu*(kx[1]**2-ky**2), ky, alpha_s, kx[1]])
# return SV, kx
# def fluid_SV(kx, k, K):
# ''' S={0:u_y , 1:p}'''
# ky = np.sqrt(k**2-kx**2)
# SV = np.zeros((2, 2), dtype=complex)
# SV[0, 0:2] = np.array([ky/(1j*K*k**2), -ky/(1j*K*k**2)])
# SV[1, 0:2] = np.array([1, 1])
# return SV, ky
# def resolution_PW_imposed_displacement(S, p):
# # print("k={}".format(p.k))
# Layers = S.layers.copy()
# n, interfaces, dofs = initialise_PW_solver(Layers, S.backing)
# M = np.zeros((n, n), dtype=complex)
# i_eq = 0
# # Loop on the layers
# for i_inter, _inter in enumerate(interfaces):
# if _inter[0] == "fluid":
# if _inter[1] == "fluid":
# i_eq = interface_fluid_fluid(i_eq, i_inter, Layers, dofs, M, p)
# if _inter[1] == "pem":
# i_eq = interface_fluid_pem(i_eq, i_inter, Layers, dofs, M, p)
# elif _inter[0] == "pem":
# if _inter[1] == "fluid":
# i_eq = interface_pem_fluid(i_eq, i_inter, Layers, dofs, M, p)
# if _inter[1] == "pem":
# i_eq = interface_pem_pem(i_eq, i_inter, Layers, dofs, M, p)
# if S.backing == backing.rigid:
# if Layers[-1].medium.MODEL == "fluid":
# i_eq = interface_fluid_rigid(M, i_eq, Layers[-1], dofs[-1], p)
# elif Layers[-1].medium.MODEL == "pem":
# i_eq = interface_pem_rigid(M, i_eq, Layers[-1], dofs[-1], p)
# if Layers[0].medium.MODEL == "fluid":
# F = np.zeros(n, dtype=complex)
# SV, k_y = fluid_SV(p.kx, p.k, Layers[0].medium.K)
# M[i_eq, dofs[0][0]] = SV[0, 0]
# M[i_eq, dofs[0][1]] = SV[0, 1]*np.exp(-1j*k_y*Layers[0].thickness)
# F[i_eq] = 1.
# elif Layers[0].medium.MODEL == "pem":
# SV, k_y = PEM_SV(Layers[0].medium, p.kx)
# M[i_eq, dofs[0][0]] = SV[2, 0]
# M[i_eq, dofs[0][1]] = SV[2, 1]
# M[i_eq, dofs[0][2]] = SV[2, 2]
# M[i_eq, dofs[0][3]] = SV[2, 3]*np.exp(-1j*k_y[0]*Layers[0].thickness)
# M[i_eq, dofs[0][4]] = SV[2, 4]*np.exp(-1j*k_y[1]*Layers[0].thickness)
# M[i_eq, dofs[0][5]] = SV[2, 5]*np.exp(-1j*k_y[2]*Layers[0].thickness)
# F = np.zeros(n, dtype=complex)
# F[i_eq] = 1.
# i_eq +=1
# M[i_eq, dofs[0][0]] = SV[0, 0]
# M[i_eq, dofs[0][1]] = SV[0, 1]
# M[i_eq, dofs[0][2]] = SV[0, 2]
# M[i_eq, dofs[0][3]] = SV[0, 3]*np.exp(-1j*k_y[0]*Layers[0].thickness)
# M[i_eq, dofs[0][4]] = SV[0, 4]*np.exp(-1j*k_y[1]*Layers[0].thickness)
# M[i_eq, dofs[0][5]] = SV[0, 5]*np.exp(-1j*k_y[2]*Layers[0].thickness)
# i_eq += 1
# M[i_eq, dofs[0][0]] = SV[3, 0]
# M[i_eq, dofs[0][1]] = SV[3, 1]
# M[i_eq, dofs[0][2]] = SV[3, 2]
# M[i_eq, dofs[0][3]] = SV[3, 3]*np.exp(-1j*k_y[0]*Layers[0].thickness)
# M[i_eq, dofs[0][4]] = SV[3, 4]*np.exp(-1j*k_y[1]*Layers[0].thickness)
# M[i_eq, dofs[0][5]] = SV[3, 5]*np.exp(-1j*k_y[2]*Layers[0].thickness)
# X = LA.solve(M, F)
# # print("|R pyPLANES_PW| = {}".format(np.abs(X[0])))
# print("R pyPLANES_PW = {}".format(X[0]))
# plot_sol_PW(S, X, dofs, p)
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] |
losses.py | EIHW/Logit_Separation | 4 | 1604638 | """
Computes the Batch Cross-Entropy loss, as appears in:
"Fast Single-Class Classification and the Principle of Logit Separation",
<NAME>, <NAME> and <NAME>.
(https://arxiv.org/abs/1705.10246)
Args:
logits: The logits for the batch, of shape `[batch_size, num_classes]`
labels: The labels for the batch, of shape `[batch_size]` containing class indices,
or `[batch_size, num_classes]` for one hot encoding.
Returns:
The batch cross-entropy loss
"""
def batch_ce(logits, labels):
epsilon = 1e-6
batch_size = tf.shape(logits)[0]
n_classes = logits.shape[1].value
# Convert labels to one hot encoding
if len(labels.shape) == 1:
labels = tf.one_hot(labels, n_classes)
# The model output distribution Q
Q = tf.nn.softmax(tf.reshape(logits, [-1]))
# Mask for true logits
true_mask = tf.cast(labels,
tf.bool)
# The target distribution P
P = tf.where(true_mask,
tf.ones_like(logits, tf.float32) / tf.to_float(batch_size),
tf.zeros_like(logits, tf.float32))
P = tf.reshape(P, [-1])
# The batch cross-entropy loss is the KL divergence between P and Q
# Epsilon is added for numerical stability
KL = tf.reduce_sum(tf.log(P / (Q + epsilon) + epsilon) * P)
return KL
"""
Computes the Batch Cross-Entropy loss, as appears in:
"Fast Single-Class Classification and the Principle of Logit Separation",
<NAME>, <NAME> and <NAME>.
(https://arxiv.org/abs/1705.10246)
Args:
logits: The logits for the batch, of shape `[batch_size, num_classes]`
labels: The labels for the batch, of shape `[batch_size]` containing class indices,
or `[batch_size, num_classes]` for one hot encoding.
Returns:
The batch max-margin loss
"""
def batch_max_margin_final(logits, labels):
batch_size = tf.shape(logits)[0]
n_classes = logits.shape[1].value
# Convert labels to one hot encoding
if len(labels.shape) == 1:
labels = tf.one_hot(labels, n_classes)
# Mask for true logits
true_mask = tf.cast(labels,
tf.bool)
# True and false logits
true_logits = tf.boolean_mask(logits, true_mask)
false_logits = tf.boolean_mask(logits, tf.logical_not(true_mask))
false_logits = tf.reshape(false_logits, [batch_size, n_classes-1])
# Max false logit per example
false_logits_example_max = tf.reduce_max(false_logits, axis=1)
# Max of false logits and Min of correct logits
true_logits_min = tf.reduce_min(true_logits)
false_logits_max = tf.reduce_max(false_logits)
# True to false logits difference, per example and per batch
example_diff = true_logits - false_logits_example_max
batch_diff = true_logits_min - false_logits_max
# The batch max-margin loss
return tf.reduce_mean(tf.maximum(0.0, FLAGS.gamma - example_diff)) + \
tf.maximum(0.0, FLAGS.gamma - batch_diff) * (1.0 / tf.to_float(batch_size))
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] |
CrazyFliePythonServer/lib/cflib/crazyflie/log.py | shreks7/crazyflie-android-no-otg | 1 | 141309 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# || ____ _ __
# +------+ / __ )(_) /_______________ _____ ___
# | 0xBC | / __ / / __/ ___/ ___/ __ `/_ / / _ \
# +------+ / /_/ / / /_/ /__/ / / /_/ / / /_/ __/
# || || /_____/_/\__/\___/_/ \__,_/ /___/\___/
#
# Copyright (C) 2011-2013 Bitcraze AB
#
# Crazyflie Nano Quadcopter Client
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston,
# MA 02110-1301, USA.
"""
Enableds logging of variables from the Crazyflie.
When a Crazyflie is connected it's possible to download a TableOfContent of all
the variables that can be logged. Using this it's possible to add logging
configurations where selected variables are sent to the client at a
specified period.
"""
__author__ = 'Bitcraze AB'
__all__ = ['Log', 'LogTocElement']
import struct
from cflib.crtp.crtpstack import CRTPPacket, CRTPPort
from cflib.utils.callbacks import Caller
from .toc import Toc, TocFetcher
# Channels used for the logging port
CHAN_TOC = 0
CHAN_SETTINGS = 1
CHAN_LOGDATA = 2
# Commands used when accessing the Table of Contents
CMD_TOC_ELEMENT = 0
CMD_TOC_INFO = 1
# Commands used when accessing the Log configurations
CMD_CREATE_BLOCK = 0
CMD_APPEND_BLOCK = 1
CMD_DELETE_BLOCK = 2
CMD_START_LOGGING = 3
CMD_STOP_LOGGING = 4
CMD_RESET_LOGGING = 5
# Possible states when receiving TOC
IDLE = "IDLE"
GET_TOC_INF = "GET_TOC_INFO"
GET_TOC_ELEMENT = "GET_TOC_ELEMENT"
# The max size of a CRTP packet payload
MAX_LOG_DATA_PACKET_SIZE = 30
import logging
logger = logging.getLogger(__name__)
class LogEntry:
"""Representation of one log configuration that enables logging
from the Crazyflie"""
block_idCounter = 1
def __init__(self, crazyflie, logconf):
"""Initialize the entry"""
self.data_received = Caller()
self.error = Caller()
self.logconf = logconf
self.block_id = LogEntry.block_idCounter
LogEntry.block_idCounter += 1
self.cf = crazyflie
self.period = logconf.getPeriod() / 10
self.block_created = False
def start(self):
"""Start the logging for this entry"""
if (self.cf.link is not None):
if (self.block_created is False):
logger.debug("First time block is started, add block")
self.block_created = True
pk = CRTPPacket()
pk.set_header(5, CHAN_SETTINGS)
pk.data = (CMD_CREATE_BLOCK, self.block_id)
for var in self.logconf.getVariables():
if (var.isTocVariable() is False): # Memory location
logger.debug("Logging to raw memory %d, 0x%04X",
var.getStoredFetchAs(), var.getAddress())
pk.data += struct.pack('<B', var.getStoredFetchAs())
pk.data += struct.pack('<I', var.getAddress())
else: # Item in TOC
logger.debug("Adding %s with id=%d and type=0x%02X",
var.getName(),
self.cf.log.toc.get_element_id(
var.getName()), var.getStoredFetchAs())
pk.data += struct.pack('<B', var.getStoredFetchAs())
pk.data += struct.pack('<B', self.cf.log.toc.
get_element_id(var.getName()))
logger.debug("Adding log block id {}".format(self.block_id))
self.cf.send_packet(pk)
else:
logger.debug("Block already registered, starting logging"
" for %d", self.block_id)
pk = CRTPPacket()
pk.set_header(5, CHAN_SETTINGS)
pk.data = (CMD_START_LOGGING, self.block_id, self.period)
self.cf.send_packet(pk)
def stop(self):
"""Stop the logging for this entry"""
if (self.cf.link is not None):
if (self.block_id is None):
logger.warning("Stopping block, but no block registered")
else:
logger.debug("Sending stop logging for block %d", self.block_id)
pk = CRTPPacket()
pk.set_header(5, CHAN_SETTINGS)
pk.data = (CMD_STOP_LOGGING, self.block_id)
self.cf.send_packet(pk)
def close(self):
"""Delete this entry in the Crazyflie"""
if (self.cf.link is not None):
if (self.block_id is None):
logger.warning("Delete block, but no block registered")
else:
logger.debug("LogEntry: Sending delete logging for block %d"
% self.block_id)
pk = CRTPPacket()
pk.set_header(5, CHAN_SETTINGS)
pk.data = (CMD_DELETE_BLOCK, self.block_id)
self.cf.send_packet(pk)
self.block_id = None # Wait until we get confirmation of delete
def unpack_log_data(self, log_data):
"""Unpack received logging data so it represent real values according
to the configuration in the entry"""
ret_data = {}
data_index = 0
for var in self.logconf.getVariables():
size = LogTocElement.get_size_from_id(var.getFetchAs())
name = var.getName()
unpackstring = LogTocElement.get_unpack_string_from_id(
var.getFetchAs())
value = struct.unpack(unpackstring,
log_data[data_index:data_index + size])[0]
data_index += size
ret_data[name] = value
self.data_received.call(ret_data)
class LogTocElement:
"""An element in the Log TOC."""
types = {0x01: ("uint8_t", '<B', 1),
0x02: ("uint16_t", '<H', 2),
0x03: ("uint32_t", '<L', 4),
0x04: ("int8_t", '<b', 1),
0x05: ("int16_t", '<h', 2),
0x06: ("int32_t", '<i', 4),
0x08: ("FP16", '<h', 2),
0x07: ("float", '<f', 4)}
@staticmethod
def get_id_from_cstring(name):
"""Return variable type id given the C-storage name"""
for key in LogTocElement.types.keys():
if (LogTocElement.types[key][0] == name):
return key
raise KeyError("Type [%s] not found in LogTocElement.types!" % name)
@staticmethod
def get_cstring_from_id(ident):
"""Return the C-storage name given the variable type id"""
try:
return LogTocElement.types[ident][0]
except KeyError:
raise KeyError("Type [%d] not found in LogTocElement.types"
"!" % ident)
@staticmethod
def get_size_from_id(ident):
"""Return the size in bytes given the variable type id"""
try:
return LogTocElement.types[ident][2]
except KeyError:
raise KeyError("Type [%d] not found in LogTocElement.types"
"!" % ident)
@staticmethod
def get_unpack_string_from_id(ident):
"""Return the Python unpack string given the variable type id"""
try:
return LogTocElement.types[ident][1]
except KeyError:
raise KeyError("Type [%d] not found in LogTocElement.types"
"!" % ident)
def __init__(self, data=None):
"""TocElement creator. Data is the binary payload of the element."""
if (data):
strs = struct.unpack("s" * len(data[2:]), data[2:])
strs = ("{}" * len(strs)).format(*strs).split("\0")
self.group = strs[0]
self.name = strs[1]
self.ident = ord(data[0])
self.ctype = LogTocElement.get_cstring_from_id(ord(data[1]))
self.pytype = LogTocElement.get_unpack_string_from_id(ord(data[1]))
self.access = ord(data[1]) & 0x10
class Log():
"""Create log configuration"""
def __init__(self, crazyflie=None):
self.log_blocks = []
self.cf = crazyflie
self.toc = None
self.cf.add_port_callback(CRTPPort.LOGGING, self._new_packet_cb)
self.toc_updatedd = Caller()
self.state = IDLE
self.fake_toc_crc = 0xDEADBEEF
def create_log_packet(self, logconf):
"""Create a new log configuration"""
size = 0
period = logconf.getPeriod() / 10
for var in logconf.getVariables():
size += LogTocElement.get_size_from_id(var.getFetchAs())
# Check that we are able to find the variable in the TOC so
# we can return error already now and not when the config is sent
if (var.isTocVariable()):
if (self.toc.get_element_by_complete_name(
var.getName()) is None):
logger.warning("Log: %s not in TOC, this block cannot be"
" used!", var.getName())
return None
if (size <= MAX_LOG_DATA_PACKET_SIZE and period > 0 and period < 0xFF):
block = LogEntry(self.cf, logconf)
self.log_blocks.append(block)
return block
else:
return None
def refresh_toc(self, refresh_done_callback, toc_cache):
"""Start refreshing the table of loggale variables"""
self.toc = Toc()
toc_fetcher = TocFetcher(self.cf, LogTocElement, CRTPPort.LOGGING,
self.toc, refresh_done_callback, toc_cache)
toc_fetcher.start()
def _new_packet_cb(self, packet):
"""Callback for newly arrived packets with TOC information"""
chan = packet.channel
cmd = packet.datal[0]
payload = struct.pack("B" * (len(packet.datal) - 1), *packet.datal[1:])
if (chan == CHAN_SETTINGS):
new_block_id = ord(payload[0])
error_status = ord(payload[1])
if (cmd == CMD_CREATE_BLOCK):
block = None
for blocks in self.log_blocks:
if (blocks.block_id == new_block_id):
block = blocks
if (block is not None):
if (error_status == 0): # No error
logger.debug("Have successfully added block_id=%d",
new_block_id)
pk = CRTPPacket()
pk.set_header(5, CHAN_SETTINGS)
pk.data = (CMD_START_LOGGING, new_block_id,
block.period)
self.cf.send_packet(pk)
else:
logger.warning("Error when adding block_id=%d, should"
" tell listenders...", new_block_id)
else:
logger.warning("No LogEntry to assign block to !!!")
if (cmd == CMD_START_LOGGING):
if (error_status == 0x00):
logger.info("Have successfully logging for block=%d",
new_block_id)
else:
logger.warning("Error=%d when starting logging for "
"block=%d", error_status, new_block_id)
if (chan == CHAN_LOGDATA):
chan = packet.channel
block_id = ord(packet.data[0])
# timestamp = packet.data[0:4] # Not currently used
logdata = packet.data[4:]
block = None
for blocks in self.log_blocks:
if (blocks.block_id == block_id):
block = blocks
if (block is not None):
block.unpack_log_data(logdata)
else:
logger.warning("Error no LogEntry to handle block=%d", block_id)
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day_1/if_2.py | YugoNishio/python_study | 0 | 183763 | <reponame>YugoNishio/python_study
#条件について
if int(input("整数を入力してください")): #整数が入力されれば条件がTrue
print("整数が入力されました")
else: #整数が入力されなかったら?
print("整数が入力されませんでした")
#残念ながら整数以外を入力するとエラーが起きてしまいました。
#どうすれば良かったのでしょうか...(error_1.pyに続く…)
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scripts/call_logs.py | asad-saleem-confiz/general-congress-hotline | 44 | 175274 | import csv
import operator
import os
from collections import defaultdict
from datetime import datetime
from twilio.rest import TwilioRestClient
FAILED_STATUSES = set(['busy', 'no-answer', 'ringing', 'failed', 'canceled'])
account_sid = os.environ['TWILIO_ACCOUNT_SID']
auth_token = os.environ['TWILIO_AUTH_TOKEN']
client = TwilioRestClient(account_sid, auth_token)
inbound_calls = []
outbound_calls = []
durations = []
nonzero_durations = []
failed_calls = []
to = []
total = 0
c = 0
calls = client.calls.iter()
with open('logs_844usa.csv', 'w') as csvfile:
fieldnames = ['from', 'to', 'status', 'duration', 'direction', 'time']
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
for call in calls:
duration = 0 if call.duration is None else int(call.duration)
if call.direction == 'inbound':
inbound_calls.append(call)
if call.direction == 'outbound-dial':
outbound_calls.append(call)
durations.append(duration)
if duration > 0:
nonzero_durations.append(duration)
to.append(call.to_formatted)
if call.status in FAILED_STATUSES:
failed_calls.append(call)
writer.writerow({
'from': call.from_formatted,
'to': call.to_formatted,
'status': call.status,
'duration': duration,
'direction': call.direction,
'time': call.date_created.isoformat(),
})
total += 1
c += 1
if c > 100:
print total, '...'
c = 0
print('busy/failed', len(failed_calls))
print('inbound', len(inbound_calls))
print('outbound', len(outbound_calls))
print('in/out ratio', round(float(len(outbound_calls))/(float(len(inbound_calls)))),3)[0]
print('total duration', sum(durations))
print('average duration', float(sum(durations))/max(1, len(durations)))
print('total nonzero duration', sum(nonzero_durations))
print('average nonzero duration', float(sum(nonzero_durations))/max(1, len(nonzero_durations)))
print('num reps', len(set(to)))
freq = defaultdict(int)
for phone in to:
freq[phone] += 1
print('frequencies')
print(sorted(freq.items(), key=operator.itemgetter(1)))
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tests/description/match_counter_test.py | centre-for-humanities-computing/danish-foundation-models | 8 | 98261 | import pytest
import spacy
from dfm.description import MatchCounter
class TestMatchCounter:
@pytest.fixture(scope="class")
def texts(self):
texts = [
"Der kom en soldat marcherende hen ad landevejen: én, to! én, to! Han havde sit tornyster på ryggen og en sabel ved siden, for han havde været i krigen, og nu skulle han hjem.",
"Så mødte han en gammel heks på landevejen; hun var så ækel, hendes underlæbe hang hende lige ned på brystet.",
"Hun sagde: God aften, soldat! Hvor du har en pæn sabel og et stort tornyster, du er en rigtig soldat! Nu skal du få så mange penge, du vil eje!",
]
return texts
@pytest.fixture(scope="class")
def regex_patterns(self):
return [
{"soldat": [{"LOWER": {"REGEX": "soldat.+"}}]},
{"tokens": [{"LOWER": {"REGEX": ".+"}}]},
]
@pytest.fixture(scope="class")
def term_pattern_list(self):
return MatchCounter.term_list_to_spacy_match_patterns(
term_list=["heks", "soldat"]
)
@pytest.fixture(scope="class")
def nlp(self):
return spacy.blank("da")
@pytest.fixture(scope="class")
def mc_basic(self, nlp, term_pattern_list):
return MatchCounter(match_patterns=term_pattern_list, nlp=nlp)
@pytest.fixture(scope="class")
def pæn_matcher(self, nlp):
pæn_match_patterns = MatchCounter.term_list_to_spacy_match_patterns(
term_list=["pæn"]
)
return MatchCounter(match_patterns=pæn_match_patterns, nlp=nlp)
def test_term_list_pattern_generation(self, term_pattern_list):
assert term_pattern_list == [
{"heks": [{"LOWER": "heks"}]},
{"soldat": [{"LOWER": "soldat"}]},
]
def test_matcher_object_generation(self, regex_patterns, mc_basic):
matcher_objects = mc_basic.create_matcher_object_from_pattern_list(
pattern_container_list=regex_patterns
)
assert len(matcher_objects) == 2
def test_token_counts(self, regex_patterns, nlp):
mc = MatchCounter(match_patterns=regex_patterns, nlp=nlp)
texts = ["Været på Altevatnet kl. "]
assert mc.count(texts)["tokens"] == [4]
def test_get_counts_from_each_doc(self, texts, mc_basic):
"""
Gets counts from all docs in texts. For e.g. "heks", the list means that the token occurs:
0 times in doc 1,
1 time on doc 2,
0 times in doc 3
"""
counts = mc_basic.count(texts)
assert counts == {"heks": [0, 1, 0], "soldat": [1, 0, 2]}
def test_multiple_matches_under_same_label(self, nlp):
from dfm.description.description_patterns import get_religion_patterns
mc = MatchCounter(match_patterns=get_religion_patterns(), nlp=nlp)
texts = ["En kristen er en del af de kristne, og kristne tror på kristendommen"]
assert mc.count(texts)["rel_christian"] == [4]
def test_genders_not_matching_on_prefix(self, nlp):
gender_pronoun_patterns = [
{"male_pronoun": [{"LOWER": "han"}]},
{"female_pronoun": [{"LOWER": "hun"}]},
]
mc = MatchCounter(match_patterns=gender_pronoun_patterns, nlp=nlp)
texts = ["Handlekraftig, handlekraft, handlekraften"]
assert mc.count(texts)["male_pronoun"] == [0]
def test_labelled_term_list_generation(self):
labelled_term_list = [{"christian": ["christian", "christianity"]}]
output = MatchCounter.list_of_labelled_term_lists_to_spacy_match_patterns(
list_of_labelled_term_lists=labelled_term_list, lowercase=True
)
assert output == [
{"christian": [{"LOWER": "christian"}]},
{"christian": [{"LOWER": "christianity"}]},
]
def test_count_token_multipel_times(self, mc_basic):
texts = ["En soldat er en soldat som en soldat er"]
counts = mc_basic.count(texts)
assert counts == {"heks": [0], "soldat": [3]}
def test_lowercasing(self, mc_basic):
texts = ["Soldat"]
counts = mc_basic.count(texts)
assert counts == {"heks": [0], "soldat": [1]}
def test_normalisation(self, pæn_matcher):
texts = ["pæn", "paen", "pœn"]
assert pæn_matcher.count(texts) == {"pæn": [1, 0, 0]}
def test_symbols(self, pæn_matcher):
texts = ["pæn", "pæn,", "pæn?"]
assert pæn_matcher.count(texts) == {"pæn": [1, 1, 1]}
def test_newlines(self, pæn_matcher):
texts = ["pæn", "p\næn,"]
assert pæn_matcher.count(texts) == {"pæn": [1, 0]}
def test_lemmatization(self, pæn_matcher):
texts = ["pæn", "pænere", "pænest"]
assert pæn_matcher.count(texts) == {"pæn": [1, 0, 0]}
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] |
understand_morris.py | bhmueller/thesis | 0 | 195117 | <reponame>bhmueller/thesis
from multiprocessing import Pool
from multiprocessing import cpu_count
from joblib import Parallel, delayed
import numpy as np
import pandas as pd
from python.auxiliary import rust_model_morris
from econsa.morris import elementary_effects
from econsa.morris import _get_uniform_base_draws
from econsa.morris import _uniform_to_standard_normal
from econsa.morris import _dependent_draws
from econsa.morris import _shift_sample
from econsa.morris import _shift_cov
from econsa.morris import _calculate_indices
from econsa.morris import _calculate_cumulative_indices
use_eoq = True
def eoq_model_morris(x, r=0.1):
"""EOQ Model that handles data as presented by elementary_effects."""
m = x["value"][0]
c = x["value"][1]
s = x["value"][2]
# m_below_zero = 0
if m < 0:
m = 0
# print('m < 0')
elif c < 0:
raise ValueError
elif s < 0:
s = 0
# print('s < 0')
else:
pass
return np.sqrt((24 * m * s) / (r * c))
# if (24 * m * s) / (r * c) <= 0:
# return 0
# elif (24 * m * s) / (r * c) > 0:
# return np.sqrt((24 * m * s) / (r * c))
# else:
# raise ValueError
def model_func(params):
return 5
# Choose model.
if use_eoq is True:
func = eoq_model_morris
elif use_eoq is False:
func = model_func
else:
raise ValueError
params = pd.DataFrame(data=[5.345, 0.0135, 2.15], columns=["value"])
cov = pd.DataFrame(data=np.diag([1, 0.000001, 0.01]))
n_draws = 100
n_cores = cpu_count()
sampling_scheme = "sobol"
u_a, u_b = _get_uniform_base_draws(n_draws, len(params), sampling_scheme)
z_a = _uniform_to_standard_normal(u_a)
z_b = _uniform_to_standard_normal(u_b)
mean_np = params["value"].to_numpy()
cov_np = cov.to_numpy()
dep_samples_ind_x, a_sample_ind_x = _dependent_draws(
z_a,
z_b,
mean_np,
cov_np,
"ind",
)
dep_samples_corr_x, _ = _dependent_draws(z_a, z_b, mean_np, cov_np, "corr")
# Dive into _evaluate_model
sample = dep_samples_ind_x
# def _evaluate_model(func, params, sample, n_cores):
# n_draws, n_params, _ = sample.shape
# evals = np.zeros((n_draws, n_params))
# inputs = []
# for d in range(n_draws):
# for p in range(n_params):
# par = params.copy()
# par["value"] = sample[d, p]
# inputs.append(par)
# # TypeError joblib; cannot unpack non-it fct. object.
# inputs = np.asarray(inputs)
# p = Pool(processes=n_cores)
# # The below line causes malfunction.
# # evals_flat = p.map(func, inputs)
# # Alternative: use map only. No multiprocessing.
# # evals_flat = map(func, inputs)
# # evals_flat = np.asarray(list(evals_flat))
# # This was in the original script as well, but commented out.
# evals_flat = Parallel(n_jobs=n_cores)(delayed(func)(inp) for inp in inputs)
# evals = np.array(evals_flat).reshape(n_draws, n_params)
# return evals
def _evaluate_model(func, params, sample, n_cores):
"""Do all model evaluations needed for the EE indices.
Args:
func (function): Maps params to quantity of interest.
params (pd.DataFrame): Model parameters. The "value" column will be replaced
with values from the morris samples.
sample (np.ndarray): Array of shape (n_draws, n_params, n_params).
Morris samples in the multivariate normal space.
Returns:
evals (np.ndarray): Array of shape (n_draws, n_params) with model evaluations
"""
n_draws, n_params, _ = sample.shape
evals = np.zeros((n_draws, n_params))
inputs = []
for d in range(n_draws):
for p in range(n_params):
par = params.copy()
par["value"] = sample[d, p]
inputs.append(par)
p = Pool(processes=n_cores)
# evals_flat = p.map(func, inputs)
evals_flat = Parallel(n_jobs=n_cores)(delayed(func)(inp) for inp in inputs)
evals = np.array(evals_flat).reshape(n_draws, n_params)
return evals
evals_ind = _evaluate_model(func, params, dep_samples_ind_x, n_cores)
evals_base_ind = _evaluate_model(func, params, a_sample_ind_x, n_cores)
evals_corr = _evaluate_model(func, params, dep_samples_corr_x, n_cores)
evals_base_corr = _shift_sample(evals_base_ind, -1)
deltas = u_b - u_a
mu_ind, sigma_ind = _calculate_indices(
evals_ind,
evals_base_ind,
deltas,
params.index,
)
mu_corr, sigma_corr = _calculate_indices(
evals_corr,
evals_base_corr,
deltas,
params.index,
)
mu_ind_cum, sigma_ind_cum = _calculate_cumulative_indices(
evals_ind,
evals_base_ind,
deltas,
params.index,
)
mu_corr_cum, sigma_corr_cum = _calculate_cumulative_indices(
evals_corr,
evals_base_corr,
deltas,
params.index,
)
res = {
"mu_ind": mu_ind,
"mu_corr": mu_corr,
"sigma_ind": sigma_ind,
"sigma_corr": sigma_corr,
"mu_ind_cum": mu_ind_cum,
"mu_corr_cum": mu_corr_cum,
"sigma_ind_cum": sigma_ind_cum,
"sigma_corr_cum": sigma_corr_cum,
}
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] |
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