xszheng2020/the_stack_dedup_python_hits_0 · Datasets at Hugging Face

4fb78c149a41dbeab3a570874abce45140a86530

959

py

Python

python/peakAccelTest.py

crotwell/dragrace

2fdb009e9ca7e868e1435d3a38ac81a0b3698433

[ "MIT" ]

12

2018-11-27T16:18:16.000Z

2020-01-10T03:17:26.000Z

python/peakAccelTest.py

crotwell/dragrace

2fdb009e9ca7e868e1435d3a38ac81a0b3698433

[ "MIT" ]

null

python/peakAccelTest.py

crotwell/dragrace

2fdb009e9ca7e868e1435d3a38ac81a0b3698433

[ "MIT" ]

1

2019-04-12T18:34:22.000Z

from SeismogramTasks import VectorMagnitude, Rotate_2D_TimeSeries, Coordinate_Rotation_2D from peakACC import Magnitude_ThreeC_TimeSeries_jake import math x = [1.2, 1.5, 0.0, 0.4, -0.3, 1.5] y = [0.3, 0.2, 0.7, 0.3, 0.0, -0.5] z = [-0.1, 1.2, 1.4, 1.0, 1.1, 0.2] theta = [110.0, 45.0, -45.0, 20.0, -20.0, 30.0] # Rotate xyz array, find vector mag def maxaccel(x,y,z,theta): # Rotate r = Rotate_2D_TimeSeries(x, z, theta) x_prime = r[0] z_prime = r[1] # x_prime = [] # z_prime = [] # for i,j,k in x,z,theta: # r = Coordinate_Rotation_2D(i, j, k) # x_prime.append(r[0]) # z_prime.append(r[1]) # find vector mag vmag = Magnitude_ThreeC_TimeSeries_jake(x_prime,z_prime,y) ACCjson = { "x": x_prime, "y": y, "z": z_prime, "theta": theta, "VMAG": vmag } return ACCjson v = maxaccel(x,y,z,110.0) # # print(v) # magnitude = v["VMAG"] print(magnitude)

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959

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0.288235

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0.067542

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959

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null

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4fb7c5d2e861fa21e084d759a0950f43e6cd8a52

6,898

py

Python

or_suite/agents/rl/utils/tree_model_based.py

JasmineSamadi/ORSuite

e2b2b0a5b497ea6566e794dcef1f176081fca4ce

[ "MIT" ]

4

2021-12-01T10:56:17.000Z

2022-02-06T17:07:43.000Z

or_suite/agents/rl/utils/tree_model_based.py

JasmineSamadi/ORSuite

e2b2b0a5b497ea6566e794dcef1f176081fca4ce

[ "MIT" ]

2

2021-08-11T13:25:01.000Z

2022-03-20T19:23:23.000Z

or_suite/agents/rl/utils/tree_model_based.py

JasmineSamadi/ORSuite

e2b2b0a5b497ea6566e794dcef1f176081fca4ce

[ "MIT" ]

3

2021-04-02T20:24:25.000Z

2021-04-10T23:53:28.000Z

import numpy as np import matplotlib.pyplot as plt import matplotlib.patches as patches import matplotlib as mpl ''' Implementation of a tree structured used in the Adaptive Discretization Algorithm''' import numpy as np import matplotlib.pyplot as plt import matplotlib.patches as patches import matplotlib as mpl from or_suite.agents.rl.utils.bounds_utils import bounds_contains, split_bounds from or_suite.agents.rl.utils.tree import Node, Tree class MBNode(Node): """ Node representing an l-infinity ball in R^d, that points to sub-balls (defined via node children). Stores a value for the q_estimate, a number of visits, and **** rewards and transition probability to a list of other nodes. *** This class is used to represent (and store data about) a tuple (state, action, stage) = (x, a, h). Attributes: bounds : numpy.ndarray Bounds of each dimension [ [x0, y0], [x1, y1], ..., [xd, yd] ], representing the cartesian product in R^d: [x0, y0] X [x1, y1] X ... X [xd, yd] depth: int Node depth, root is at depth 0. qVal : double, default: 0 Initial node Q value num_visits : int, default = 0 Number of visits to the node. """ def __init__(self, bounds, depth, qVal, rEst, pEst, num_visits): self.dim = len(bounds) self.radius = (bounds[:, 1] - bounds[:, 0]).max() / 2.0 assert self.radius > 0.0 self.bounds = bounds self.depth = depth self.qVal = qVal self.rEst = rEst self.pEst = pEst self.num_visits = num_visits self.children = [] # Splits a node def split_node(self, inherit_flag = True, value = 1): child_bounds = split_bounds(self.bounds) for bounds in child_bounds: if inherit_flag: # updates estimates based on whether we are inheriting estimates or not self.children.append( MBNode(bounds, self.depth+1, self.qVal, self.rEst, self.pEst.copy(), self.num_visits) ) else: self.children.append( MBNode(bounds, self.depth+1, value, 0, [0 for _ in range(len(self.pEst))], 0) ) return self.children class MBTree(Tree): """ Tree representing a collection of l-infinity ball in R^d, that points to sub-balls (defined via node children). Stores a hierarchical collections of nodes with value for the q_estimate, a number of visits, and Attributes: dim : int Dimension of the space of R^d. head: (Node) Pointer to the first node in the hierarchical partition epLen: (int) Number of episodes (used for initializing estimates for Q Values) """ # Defines a tree by the number of steps for the initialization def __init__(self, epLen, state_dim, action_dim): self.dim = state_dim+action_dim # total dimension of state and action space self.epLen = epLen self.state_dim = state_dim # stores state space dimension separately # initializes head of the tree bounds = np.asarray([[0.0,1.0] for _ in range(self.dim)]) self.head = MBNode(bounds, 0, epLen, 0, [0.0], 0) # initializes state leaves of the tree and their value estimates used in the model based algorithm self.state_leaves = [[0.5 for _ in range(self.state_dim)]] self.leaves = [self.head] self.vEst = [self.epLen] def get_leaves(self): return self.leaves def tr_split_node(self, node, timestep = 0, inherit_flag = True, value = 1, previous_tree = None): """ Splits a node, while simultaneously updating the estimate of the transition kernels for all nodes if needed. Args: node: MBNode to split inherit_flag: (bool) boolean of whether to inherit estimates of not value: (float) default qVal estimate """ # Splits a node and updates the list of leaves self.leaves.remove(node) children = node.split_node(inherit_flag, value) self.leaves = self.leaves + children # Determines if we also need to adjust the state_leaves and carry those # estimates down as well # Gets one of their state value child_1_bounds = children[0].bounds child_1_radius = (child_1_bounds[:, 1] - child_1_bounds[:, 0]).max() / 2.0 child_1_state = child_1_bounds[:self.state_dim, 0] + child_1_radius if np.min(np.abs(np.asarray(self.state_leaves) - child_1_state)) >= child_1_radius: # determines if the children are at a finer granularity # gets state portion of the value of the current node node_radius = (node.bounds[:, 1] - node.bounds[:, 0]).max() / 2.0 node_state = node.bounds[:self.state_dim, 0] + node_radius # location of node in the larger state_leaves list parent_index = np.argmin(np.max(np.abs(np.asarray(self.state_leaves) - node_state), axis=1)) parent_vEst = self.vEst[parent_index] # pops their estimate self.state_leaves.pop(parent_index) self.vEst.pop(parent_index) # keeps track of the number added for redistributing the transition kernel estimate num_add = 0 for child in node.children: child_radius = (child.bounds[:,1] - child.bounds[:,0]).max() / 2.0 child_state = child.bounds[:self.state_dim, 0] + child_radius # gets the state portion of the node # determines if this child state has been added before if len(self.state_leaves) == 0 or np.min(np.max(np.abs(np.asarray(self.state_leaves) - child_state), axis=1)) > 0: num_add += 1 self.state_leaves.append(child_state) self.vEst.append(parent_vEst) # updates estimates based on the parent # updates the transition distribution for all leaves in the previous tree if timestep >= 1: previous_tree.update_transitions_after_split(parent_index, num_add) return children def update_transitions_after_split(self, parent_index, num_add): """ Helper function in order to update the transition estimates after a split. Args: parent_index: location in the list where the parent node was num_children: the numer of new nodes that were added for redistributing transition kernel estimate """ for node in self.leaves: pEst_parent = node.pEst[parent_index] node.pEst.pop(parent_index) for _ in range(num_add): node.pEst.append(pEst_parent / num_add)

34.49

147

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6,898

4.440085

0.227996

0.025794

0.025078

0.010509

0.197277

0.17411

0.139718

0.111297

0.095056

0

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0.295303

6,898

200

148

34.49

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0

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false

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0.272727

0

null

0

null

0

1

0

4fb817161338ef80c25e699b2bc29de57a33bf5a

1,219

py

Python

netpyne/tutorials/saving_loading_tut/saving_netParams.py

adamjhn/netpyne

b9e104645f11fe6688496b22cd4183f463e11adc

[ "MIT" ]

120

2015-12-29T08:30:08.000Z

2021-11-16T11:49:58.000Z

netpyne/tutorials/saving_loading_tut/saving_netParams.py

ericaygriffith/netpyne

d5745015755855a1214e25d6033d3685cccace0d

[ "MIT" ]

1,178

2020-06-21T16:52:57.000Z

2021-03-11T15:47:54.000Z

netpyne/tutorials/saving_loading_tut/saving_netParams.py

ericaygriffith/netpyne

d5745015755855a1214e25d6033d3685cccace0d

[ "MIT" ]

143

2016-01-09T17:51:43.000Z

2022-01-02T06:37:12.000Z

from netpyne import specs, sim from __main__ import cfg # Network parameters netParams = specs.NetParams() # object of class NetParams to store the network parameters ## Cell parameters PYRcell = {'secs': {}} PYRcell['secs']['soma'] = {'geom': {}, 'mechs': {}} PYRcell['secs']['soma']['geom'] = {'diam': 18.8, 'L': 18.8, 'Ra': 123.0} PYRcell['secs']['soma']['mechs']['hh'] = {'gnabar': 0.12, 'gkbar': 0.036, 'gl': 0.003, 'el': -70} netParams.cellParams['PYR'] = PYRcell ## Population parameters netParams.popParams['S'] = {'cellType': 'PYR', 'numCells': 20} netParams.popParams['M'] = {'cellType': 'PYR', 'numCells': 20} ## Synaptic mechanism parameters netParams.synMechParams['exc'] = {'mod': 'Exp2Syn', 'tau1': 0.1, 'tau2': cfg.synMechTau2, 'e': 0} # Stimulation parameters netParams.stimSourceParams['bkg'] = {'type': 'NetStim', 'rate': 10, 'noise': 0.5} netParams.stimTargetParams['bkg->PYR'] = {'source': 'bkg', 'conds': {'cellType': 'PYR'}, 'weight': 0.01, 'delay': 5, 'synMech': 'exc'} ## Cell connectivity rules netParams.connParams['S->M'] = { 'preConds': {'pop': 'S'}, 'postConds': {'pop': 'M'}, 'probability': 0.5, 'weight': cfg.connWeight, 'delay': 5, 'synMech': 'exc'}

35.852941

134

0.62018

148

1,219

5.081081

0.554054

0.101064

0.05984

0.050532

0

0.042857

0.138638

1,219

33

135

36.939394

0.673333

0.156686

0

0.268701

0

1

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false

0

0.1

0

0.1

0

null

0

null

0

1

0

4fc21df0fc15f305205a0557ed15aa9949db40c0

60,989

py

Python

moral_kombat_backend/lead/tables/views.py

david-fisher/320-S21-Track2

abd78fa150c07cc375cff4bd1a5595f3267a1884

[ "BSD-3-Clause" ]

8

2021-02-12T16:13:55.000Z

2021-03-12T00:24:46.000Z

moral_kombat_backend/lead/tables/views.py

david-fisher/320-S21-Track2

abd78fa150c07cc375cff4bd1a5595f3267a1884

[ "BSD-3-Clause" ]

225

2021-02-17T19:24:25.000Z

2021-10-02T19:10:28.000Z

moral_kombat_backend/lead/tables/views.py

david-fisher/320-S21-Track2

abd78fa150c07cc375cff4bd1a5595f3267a1884

[ "BSD-3-Clause" ]

1

2022-03-24T15:38:01.000Z

from django.shortcuts import render from rest_framework import viewsets, permissions, generics from rest_framework.views import APIView from rest_framework.response import Response from django_filters.rest_framework import DjangoFilterBackend from .models import * from .serializer import * from django.core import serializers from rest_framework import status import json from django.db import connection from rest_framework.parsers import JSONParser from rest_framework.viewsets import ModelViewSet from django.http.response import JsonResponse from rest_framework.decorators import action from rest_framework.decorators import api_view from rest_framework import mixins # DemographicsSerializer, StudentSerializer, ProfessorSerializer, ScenariosSerializer, allScenariosSerializer, Stakeholder_pageSerializer, StakeholdersSerializer, ConversationsSerializer def getcredentials(request): credentials = { "uid": request.META['uid'], "name": request.META['displayname'], "affiliation": request.META['edupersonprimaryaffiliation'], "email": request.META['mail'], #"title": request.META['title'], "intid": request.META['fcidnumber'] } credentials.update({"intid": credentials.get("intid").split("@")[0]}) return credentials class ReturnIdentifierView(APIView): def get(self, request, *args, **kwargs): # if ('title' in request.META): # return Response({"id":"professor"}) # else: # # if(len(scenarios.objects.filter(professors_to_scenario = request.META['displayname']).values()) != 0): # # return Response({"id":"editor"}) # # else: # return Response({"id":"student"}) #return(Response({"id": request.META['uid']})) if(len(professors.objects.filter(professor = request.META['uid']).values()) != 0): #data = "You are prof " + request.META['uid'] return(Response({"id": "You are prof "})) else: #data = "You are student " + request.META['uid'] return(Response({"id": "You are student "})) # if (credentials.get("title") == "lecturer"): # return Response({"id":"professor"}) # else: # return Response({"id":"student"}) #return Response({"id":"student"}) # stakeholders viewset - chirag - 4/14 class StakeholdersViewSet(viewsets.ModelViewSet): def get_queryset(self): queryset = stakeholders.objects.all() return queryset queryset = stakeholders.objects.all() permissions_classes = [ permissions.AllowAny ] serializer_class = StakeholdersSerializer filter_backends = [DjangoFilterBackend] filterset_fields = ['scenario'] lookup_field = 'stakeholder' # class stakeholdersviewset(viewsets.ModelViewSet): # queryset = stakeholders.objects.all() # permissions_classes = [ # permissions.AllowAny # ] # serializer_class = stakeholdersserializer class QuestionsViewset(viewsets.ModelViewSet): queryset = questions.objects.all() permissions_classes = [ permissions.AllowAny ] serializer_class = QuestionsSerializer # conversations viewset # checked - chirag - 04/15/2021 class ConversationsViewSet(viewsets.ModelViewSet): queryset = conversations.objects.all() permissions_classes = [ permissions.AllowAny ] serializer_class = ConversationsSerializer filter_backends = [DjangoFilterBackend] filterset_fields = ['stakeholder', 'question'] class Responses_to_ConversationsViewSet(viewsets.ModelViewSet): queryset = responses_to_conversations.objects.all() permissions_classes = [ permissions.AllowAny ] serializer_class = Responses_to_ConversationsSerializer # checked - chirag - 04/15/2021 class multi_conv(APIView): def put(self, request, *args, **kwargs): stakeholder = self.request.query_params.get('stakeholder') if stakeholder == None: return Response({'status': 'details'}, status=status.HTTP_404_NOT_FOUND) for updated_conv in request.data: extant_conv = conversations.objects.get(stakeholder = stakeholder, conversation = updated_conv['conversation']) serializer = ConversationsSerializer(extant_conv, data=updated_conv) if serializer.is_valid(): serializer.save() conv_query = conversations.objects.filter(stakeholder = stakeholder).values() return Response(conv_query) # no change - checked - chirag - 04/15/2021 class multi_stake(APIView): def put(self, request, *args, **kwargs): scenario = self.request.query_params.get('scenario') if scenario == None: return Response({'status': 'details'}, status=status.HTTP_404_NOT_FOUND) for updated_stake in request.data: extant_stake = stakeholders.objects.get(scenario_id = scenario, stakeholder = updated_stake['stakeholder']) serializer = StakeholdersSerializer(extant_stake, data=updated_stake) if serializer.is_valid(): serializer.save() stake_query = stakeholders.objects.filter(scenario = scenario).values() return Response(stake_query) # checked - ed - 4/15/2021 class multi_coverage(APIView): def put(self, request, *args, **kwargs): stakeholder = self.request.query_params.get('stakeholder') if stakeholder == None: return Response({'status': 'details'}, status=status.HTTP_404_NOT_FOUND) for updated_coverage in request.data: extant_coverage = coverage.objects.get(stakeholder = stakeholder, issue = updated_coverage['issue']) serializer = coverageSerializer(extant_coverage, data=updated_coverage) if serializer.is_valid(): serializer.save() coverage_query = coverage.objects.filter(stakeholder = stakeholder).values() return Response(coverage_query) # done - chirag - 04/15/2021 class CoverageViewSet(viewsets.ModelViewSet): queryset = coverage.objects.all() permission_classe = [permissions.AllowAny] serializer_class = coverageSerializer filter_backends = [DjangoFilterBackend] filterset_fields = ['stakeholder'] class DemographicsViewSet(viewsets.ModelViewSet): # print(demographics.objects.all()) serializer_class = DemographicsSerializer queryset = demographics.objects.only('student', 'age', 'gender', 'race', 'major') # print(queryset) permission_classes = [ permissions.AllowAny ] class StudentsViewSet(viewsets.ModelViewSet): queryset = students.objects.all() permission_classes = [ permissions.AllowAny ] serializer_class = StudentSerializer class PagesToScenarioViewSet(viewsets.ModelViewSet): queryset = pages_to_scenario.objects.all() permission_classes = [ permissions.AllowAny ] serializer_class = PagesToScenarioSerializer class ProfessorsViewSet(viewsets.ModelViewSet): queryset = professors.objects.all() permission_classes = [ permissions.AllowAny ] serializer_class = ProfessorSerializer class StudentTimesViewSet(viewsets.ModelViewSet): queryset = student_times.objects.all() permission_classes = [ permissions.AllowAny ] serializer_class = StudentTimesSerializer class ScenariosViewSet(viewsets.ModelViewSet): queryset = scenarios.objects.all() permissions_classes = [ permissions.AllowAny ] serializer_class = ScenariosSerializer # uncommeented cuz main - chirag - 04/15/2021 def delete(self, request, pk, format=None): snippet = self.get_object(pk) snippet.delete() return Response(status=status.HTTP_204_NO_CONTENT) class SingleScenarioViewSet(viewsets.ModelViewSet): def get(self, request): scenario = scenarios.objects.all() serializer = ScenariosSerializer(scenarios) return Response(serializer.data) # class professors_to_scenarioviewset(viewsets.ModelViewSet): # def get(self, request): # scenario = scenarios.objects.all() # serializer = scenariosserializer(scenarios) # return Response(serializer.data) # def delete(self, request, pk, format=None): # snippet = self.get_object(pk) # snippet.delete() # return Response(status=status.HTTP_204_NO_CONTENT) class professors_to_scenarioViewSet(viewsets.ModelViewSet): queryset = professors_to_scenario.objects.all() permission_classes = [ permissions.AllowAny ] serializer_class = Professors_to_scenarioSerializer class PagesViewSet(viewsets.ModelViewSet): queryset = pages.objects.all() serializer_class = PagesSerializer # stakeholder_page viewset class Stakeholder_pageViewSet(viewsets.ModelViewSet): queryset = stakeholder_to_page.objects.all() permissions_classes = [ permissions.AllowAny ] serializer_class = Stakeholder_to_pageSerializer class Reflection_QuestionsViewSet(viewsets.ModelViewSet): queryset = reflection_questions.objects.all() permissions_classes = [ permissions.AllowAny ] serializer_class = Reflection_questionsSerializer class Reflection_Question_to_pageViewSet(viewsets.ModelViewSet): queryset = reflection_question_to_page.objects.all() permissions_classes = [ permissions.AllowAny ] serializer_class = Reflection_questions_to_pageSerializer class ReflectionsTakenViewSet(viewsets.ModelViewSet): queryset = reflections_taken.objects.all() permission_class = [ permissions.AllowAny ] serializer_class = ReflectionsTakenSerializer # class actionstakenviewset(viewsets.ModelViewSet): # queryset = actions_taken.objects.all() # permission_class = [ # permissions.AllowAny # ] # serializer_class = actions_takenserializer # class conversationshadviewset(viewsets.ModelViewSet): # queryset = conversations_had.objects.all() # permission_class = [ # permissions.AllowAny # ] # serializer_class = conversationshadserializer # class studentsinviewset(viewsets.ModelViewSet): # queryset = students_in.objects.all() # permission_class = [permissions.AllowAny] # serializer_class = studentsinserializer class CoursesViewSet(viewsets.ModelViewSet): queryset = courses.objects.all() permission_classes = [permissions.AllowAny] serializer_class = CoursesSerializer class ResponsesViewSet(viewsets.ModelViewSet): queryset = responses.objects.all() permission_classe = [permissions.AllowAny] serializer_class = ResponsesSerializer #this allows for filerting scenarios by professor_id class allScenariosViewSet(generics.ListAPIView): serializer_class = allScenariosSerializer queryset = scenarios.objects.all() filter_backends = [DjangoFilterBackend] filterset_fields = ['professor', 'is_finished'] # scenarios_for viewset class Scenarios_forViewSet(viewsets.ModelViewSet): queryset = scenarios_for.objects.all() permissions_class = [ permissions.AllowAny ] serializer_class = Scenarios_forSerializer class courses_to_scenarioViewset(viewsets.ModelViewSet): queryset = courses_to_scenario.objects.all() permissions_class = [ permissions.AllowAny ] serializer_class = Courses_to_ScenarioSerializer # generic_page viewset class generic_pageViewSet(viewsets.ModelViewSet): queryset = generic_page.objects.all() permissions_class = [ permissions.AllowAny ] serializer_class = Generic_pageSerializer # professors_teach viewset # class professors_teachviewset(viewsets.ModelViewSet): # queryset = professors_teach.objects.all() # permissions_class = [ # permissions.AllowAny # ] # serializer_class = professors_teachserializer # changed - chirag - 04/15/2021 class IssuesViewSet(viewsets.ModelViewSet): queryset = issues.objects.all() serializer_class = IssuesSerializer # queryset = issues.objects.all() # permission_classes = [ # permissions.AllowAny # ] # serializer_class = IssuesSerializer # filter_backends = [DjangoFilterBackend] # filterset_fields = ['scenario_id', "name"] # def create(self, request, *args, **kwargs): # serializer = IssuesSerializer(data=request.data) # if serializer.is_valid(): # serializer.save() # scenarioID = serializer.data['scenario_id'] # issueID = serializer.data['issue'] # stakeholders = stakeholders.objects.filter(scenario=scenarioID).values() # for stakeholder in stakeholders: # newCoverage = {} # newCoverage['stakeholder'] = stakeholder['stakeholder'] # newCoverage['issue'] = issueID # newCoverage['coverage_score'] = 0 # coverageSerial = coverageSerializer(data=newCoverage) # if coverageSerial.is_valid(): # coverageSerial.save() # else: # return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) # return Response(serializer.data, status=status.HTTP_201_CREATED) # return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) class Action_pageViewSet(viewsets.ModelViewSet): queryset = action_page.objects.all() permission_classes = [ permissions.AllowAny ] serializer_class = Action_pageSerializer class response_to_action_pageViewSet(viewsets.ModelViewSet): queryset = response_to_action_page.objects.all() permission_classes = [ permissions.AllowAny ] serializer_class = Response_to_action_pageSerializer # checked - ed - 4/15/21 #for getting/editing scenarios in dashboard class logistics_page(APIView): #http_method_names = [ 'post,' 'put', 'delete'] def get(self, request, *args, **kwargs): #take professor_id as input from url by adding ?professor_id=<the id #> to the end of the url. scenario_id = self.request.query_params.get('scenario') #todo check that id != None #get all scenarios belonging to this professor # scenario_query = professors_to_scenario.objects.filter(professor = professor_id).values() scenario = scenarios.objects.get(scenario_id = scenario_id) scenario_dict = ScenariosSerializer(scenario).data #loop through scenarios and append required information (course, page info) # print(scenario_dict) scenarios_for_query = scenarios_for.objects.filter(scenario_id=scenario_dict['scenario_id']).values() course_id_array = [] for x in scenarios_for_query: # print(x) course_id_array.append(x['course_id']) course_dict_array = [] for x in course_id_array: course = courses.objects.get(course = x) course_dict_array.append({"course":course.course, "name": course.name}) pages_query = pages.objects.filter(scenario=scenario_id).values() # print("pages: ", pages_query) page_array = [] for page in pages_query: cropped_page = {} cropped_page['page'] = page['page'] cropped_page['page_title'] = page['page_title'] cropped_page['page_type'] = page['page_type'] page_array.append(cropped_page) scenario_dict.update({ "courses": course_dict_array, "pages": page_array }) logistics = scenario_dict # print(logistics) return Response(logistics) """format: { "scenario": 1, "version": 0, "name": "pizza is good!", "is_finished": False, "public": False, "num_conversation": 5, "professor": 12345678, "courses": [ { "course": 2, "name": "590g" }, { "course": 1, "name": "320" } ] } """ #a put request for editing scenarios. must provide scenario in url thusly: /logistics?scenario=<insert id number here> def put(self, request, *args, **kwargs): #save the scenario extant_scenario = scenarios.objects.get(scenario_id = request.data['scenario_id']) scenario_serializer = ScenariosSerializer(extant_scenario, data = request.data) if scenario_serializer.is_valid(): scenario_serializer.save() #delete currently assocated classes scenarios_for.objects.filter(scenario_id = request.data['scenario_id']).delete() #get array of courses from frontend courses = request.data['courses'] for course in courses: scenarios_for_dict = { "course" : course['course'], "scenario" : request.data['scenario'], "version" : request.data['version'] } print(scenarios_for_dict) #save the classes associated with it in scenarios_for for_serializer = Scenarios_forSerializer(data=scenarios_for_dict) if for_serializer.is_valid(): for_serializer.save() print('saved!') print(for_serializer.errors) scenario_dict = ScenariosSerializer(scenarios.objects.get(scenario_id = request.data['scenario_id'])).data scenario_dict['courses'] = request.data['courses'] return Response(scenario_dict) # checked - ed - 4/15/2021 #returns list of scenarios for given professor along with list of associated courses class dashboard_page(APIView): def get(self, request, *args, **kwargs): #take professor_id as input from url by adding ?professor=<the id #> to the end of the url. #--old schema #professor_id = self.request.query_params.get('professor') #new, changed the endpoint request #professor_id = request.META['uid'] #todo check that id != None #scenario_query = scenarios_for.objects.filter(scenario_id=scenario_dict['scenario_id']).values() #get all scenarios belonging to this professor #scenario_query = professors_to_scenario.objects.filter(professor = professor_id).values() scenario_query = scenarios.objects.values() # if(len(scenario_query) == 0): # return Response({"error": "you are not associated with any scenarios"}) #loop through scenarios and append required information (course, page info) logistics = [] #print(scenario_query) for scenario in scenario_query: scenarios_for_query = scenarios_for.objects.filter(scenario_id = scenario['scenario_id']).values() course_id_array = [] for x in scenarios_for_query: course_id_array.append(x['course_id']) course_dict_array = [] for x in course_id_array: course = courses.objects.get(course= x) course_dict = {"course":course.course, "name": course.name} course_dict_array.append(course_dict) scenario["courses"] = course_dict_array logistics.append(scenario) return Response(logistics) """format: { "name": "best test", "is_finished": False, "public": False, "num_conversation": 5, "professor": 12345678, "courses":[ {"course": 1}, {"course": 2}, {"course": 3} ] } """ def post(self, request, *args, **kwargs): #save the scenario scenario_serializer = ScenariosSerializer(data = request.data) if not (scenario_serializer.is_valid()): print("scenario saved incorrectly") return Response(scenario_serializer.errors) scenario_serializer.save() scenario_dict = scenario_serializer.data #get array of courses from frontend courses = request.data['courses'] for course in courses: scenarios_for_dict = { "scenario" : scenario_dict['scenario'], "course" : course['course'], "version" : scenario_dict['version'] } print(scenarios_for_dict) print(scenario_dict) for_serializer = Scenarios_forSerializer(data=scenarios_for_dict) if not for_serializer.is_valid(): print("scenarios_for saved incorrectly") return Response(for_serializer.errors) for_serializer.save() #create a new intro page intro_page = { "page_type": "i", "page_title": "introduction", "page_body": "page body", "scenario": scenario_dict['scenario'], "next_page": None, "x_coordinate": 0, "y_coordinate": 0, "next_page_version": None } intro_page_serializer = PagesSerializer(data=intro_page) if intro_page_serializer.is_valid(): intro_page_serializer.save() print("intro page saved") else: print("intro page saved incorrectly") return Response(intro_page_serializer.errors) #todo create blank stakeholder page and return it #page must be called stakeholder_page and serialier must be called stakeholder_page_serializer stakeholder_page = { "page_type": "s", "page_title": "stakeholders", "page_body": "page of stakeholders", "scenario": scenario_dict['scenario'], "next_page": None, "x_coordinate": 0, "y_coordinate": 0, "next_page_version": None } stakeholder_page_serializer = PagesSerializer(data=stakeholder_page) if stakeholder_page_serializer.is_valid(): stakeholder_page_serializer.save() else: print("stakeholders page saved incorrectly") return Response(stakeholder_page_serializer.errors) scenario_dict = ScenariosSerializer(scenarios.objects.get(scenario = scenario_dict['scenario'])).data scenario_dict['courses'] = request.data['courses'] scenario_dict['intro_page'] = intro_page_serializer.data scenario_dict['stakeholder_page'] = stakeholder_page_serializer.data return Response(scenario_dict) # checked - ed - 4/15/2021 #change a list of issue objects at url /multi_issue?scenario=<insert id number here> class multi_issue(APIView): def put(self, request, *args, **kwargs): scenario = self.request.query_params.get('scenario') if scenario == None: return Response({'status': 'details'}, status=status.HTTP_404_NOT_FOUND) for updated_issue in request.data: extant_issue = issues.objects.get(scenario_id = scenario, issue = updated_issue['issue']) serializer = IssuesSerializer(extant_issue, data=updated_issue) if not serializer.is_valid(): return Response(serializer.errors) try: serializer.save() except: print('something went wrong with the put') issues_query = issues.objects.filter(scenario_id = scenario).values() return Response(issues_query) # checked - ed - 4/15/2021 #for use in the pages flowchart, input is an array of page objects class flowchart(APIView): #get all page objects given a scenario id def get(self, request, *args, **kwargs): scenario_id = self.request.query_params.get('scenario') print(scenario_id) pages_query = pages.objects.filter(scenario=scenario_id).values() print(pages_query) for page in pages_query: if page['page_type'] == 'a': page['action'] = action_page.objects.filter(page=page['page']).values() return Response(pages_query) #update the next_page field of all page objects def put(self, request, *args, **kwargs): scenario_id = self.request.query_params.get('scenario') if scenario_id == None: return Response({'status': 'details'}, status=status.HTTP_404_NOT_FOUND) for updated_page in request.data: #save updated choices within action pages if updated_page['page_type'] == 'a': print('action page') print(update) for updated_choice in updated_page['action']: print(updated_choice) extant_choice = action_page.objects.get(id=updated_choice['id']) action_serializer = action_pageserializer(extant_choice, updated_choice) if not action_serializer.is_valid(): print("error with puting choices") return Response(action_serializer.errors) action_serializer.save() #save the page itself extant_page = pages.objects.get(scenario = scenario_id, page = updated_page['page']) serializer = PagesSerializer(extant_page, data=updated_page) if not serializer.is_valid(): print("error with puting pages") return Response(serializer.errors) serializer.save() #return query with newly saved pages pages_query = pages.objects.filter(scenario=scenario_id).values() for page in pages_query: if page['page_type'] == 'a': page['action'] = action_page.objects.filter(page=page['page']).values() return Response(pages_query) #pages viewset #Cooper 05/05/2021 class Page_reflectionViewSet(generics.CreateAPIView): model = pages serializer_class = Pages_reflectionSerializer #Cooper 05/05/2021 class Page_actionViewSet(generics.CreateAPIView): model = pages serializer_class = Pages_actionSerializer #Cooper 05/05/2021 class Page_genericViewSet(generics.CreateAPIView): model = pages serializer_class = Pages_genericSerializer #Cooper 05/05/2021 class Page_StakeholderViewSet(generics.CreateAPIView): model = pages serializer_class = Pages_stakeholderSerializer class pages_page(APIView): # define get method for pages # @api_view(['get']) def get(self, request, *args, **kwargs): # takes the page_id from the url if the url has ?page_id=<id> at the end, no parameter passed return error 400 page_id = self.request.query_params.get('page_id') # get all fields from this page_id if ti doesn't exist return error 404 try: page = pages.objects.get(page = page_id) except pages.DoesNotExist: return Response(status=status.HTTP_404_NOT_FOUND) # print(page) # convers django model object into a dictionary page_data = PagesSerializer(page).data # print(page_data) page_type = page_data['page_type'] # print("page type: ", page_type) # check page.page_type = 'reflection' if (page_type == 'r'): reflection_query = reflection_questions.objects.filter(reflection_questions_to_page1 = page_id).values() page_data.update( { "reflection_questions": reflection_query } ) return Response(page_data, status=status.HTTP_200_OK) # check page.page_type = 'action' if (page_type == 'a'): action_query = action_page.objects.filter(page = page_id).values() page_data.update( { "choices": action_query } ) return Response(page_data, status=status.HTTP_200_OK) # check page.page_type = 'generic' if (page_type == 'g' or page_type == 'i'): generic_query = generic_page.objects.filter(page = page_id).values() page_data.update( { "bodies":generic_query } ) return Response(page_data, status=status.HTTP_200_OK) # check page.page_type = 'stakeholder' if (page_type == 's'): stakeholder_query = stakeholder_to_page.objects.filter(page = page_id).values() page_data.update( { "stakeholders": stakeholder_query } ) return Response(page_data, status=status.HTTP_200_OK) # neither of these pages, something went wrong or missing implementation else: return Response(status=status.HTTP_400_BAD_REQUEST) # # define post function for pages # # @api_view(['post']) def post(self, request): # takes the scenario_id from the url if the url has ?scenario_id=<id> at the end, no parameter passed return error 400 page_type = request.data["page_type"] # if the request is a reflection page if (page_type == 'r'): pages_serializer = PagesSerializer(data=request.data) if pages_serializer.is_valid(): pages_serializer.save() page_id = pages_serializer.data["page"] for question in request.data['reflection_questions']: question['page'] = page_id nested_serializer = Reflection_questionsSerializer(data=question) if nested_serializer.is_valid(): nested_serializer.save() # if the nested page is not valid it deletes the wrapper page created above else: page = pages.objects.get(page=page_id) page.delete() return Response(nested_serializer.data, status=status.HTTP_400_BAD_REQUEST) #nested_serializer.save() return Response(pages_serializer.data, status=status.HTTP_201_CREATED) # if the request was badly made or could not be created return Response(pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) # if the request is an action page if (page_type == 'a'): pages_serializer = PagesSerializer(data=request.data) if pages_serializer.is_valid(): pages_serializer.save() page_id = pages_serializer.data["page"] for choice in request.data['page_choices']: choice['page'] = page_id nested_serializer = Action_pageSerializer(data=choice) if nested_serializer.is_valid(): nested_serializer.save() # if the nested page is not valid it deletes the wrapper page created above else: page = pages.objects.get(page=page_id) page.delete() return Response(nested_serializer.data, status=status.HTTP_400_BAD_REQUEST) #nested_serializer.save() return Response(pages_serializer.data, status=status.HTTP_201_CREATED) # if the request was badly made or could not be created return Response(pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) # if the request is a generic page if (page_type == 'g' or page_type == 'i'): pages_serializer = PagesSerializer(data=request.data) if pages_serializer.is_valid(): pages_serializer.save() page_id = pages_serializer.data["page"] for body in request.data['body']: body['page'] = page_id nested_serializer = Generic_pageSerializer(data=body) if nested_serializer.is_valid(): nested_serializer.save() # if the nested page is not valid it deletes the wrapper page created above else: page = pages.objects.get(page=page_id) page.delete() return Response(nested_serializer.data, status=status.HTTP_400_BAD_REQUEST) #nested_serializer.save() return Response(pages_serializer.data, status=status.HTTP_201_CREATED) # if the request was badly made or could not be created return Response(pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) # if the request is a stakeholder page if (page_type == 's'): pages_serializer = PagesSerializer(data=request.data) if pages_serializer.is_valid(): pages_serializer.save() page_id = pages_serializer.data["page"] for stakeholder in request.data['stakeholders']: stakeholder['page'] = page_id nested_serializer = Stakeholder_pageSerializer(data=stakeholder) if nested_serializer.is_valid(): nested_serializer.save() # if the nested page is not valid it deletes the wrapper page created above else: page = pages.objects.get(page=page_id) page.delete() return Response(nested_serializer.data, status=status.HTTP_400_BAD_REQUEST) #nested_serializer.save() #delete return Response(pages_serializer.data, status=status.HTTP_201_CREATED) # if the request was badly made or could not be created return Response(pages_serializer.data, status=status.HTTP_400_BAD_REQUEST) else: return Response(status=status.HTTP_400_BAD_REQUEST) # @api_view(['put']) def put(self, request): # takes the page_id from the url if the url has ?page_id=<id> at the end, no parameter passed return error 400 page_id = self.request.query_params.get('page_id') # get all fields from this page_id if it doesn't exist return error 404 try: page = pages.objects.get(page = page_id) except pages.DoesNotExist: return Response(status=status.HTTP_404_NOT_FOUND) # please don't modify the scenario print(request.data) request.data["scenario_id"] = PagesSerializer(page).data['scenario'] if request.method == "put": page_type = request.data["page_type"] # check page.page_type = 'reflection' if (page_type == 'r'): pages_serializer = PagesSerializer(page, data=request.data) if pages_serializer.is_valid(): pages_serializer.save() # check that each reflectuon question already exists for question in request.data['reflection_questions']: try: reflection_page = reflection_questions.objects.get(id = question.get('id')) except: # if the subpage does not exist, then you create that new page and post it and continue to the next component question['page'] = page_id nested_serializer = Reflection_questionsSerializer(data=question) if nested_serializer.is_valid(): nested_serializer.save() else: return Response(nested_serializer.errors, status=status.HTTP_400_BAD_REQUEST) continue question['page'] = page_id nested_serializer = Reflection_questionsSerializer(reflection_page, data=question) if nested_serializer.is_valid(): nested_serializer.save() else: return Response(nested_serializer.errors, status=status.HTTP_400_BAD_REQUEST) return Response(pages_serializer.data, status=status.HTTP_200_OK) # else the request was badly made return Response(pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) # check page.page_type = 'action' if (page_type == 'a'): pages_serializer = PagesSerializer(page, data=request.data) if pages_serializer.is_valid(): pages_serializer.save() # check that each action_page already exists for action in request.data['choices']: try: choices_page = action_page.objects.get(id = action.get('id')) except: # if the subpage does not exist, then you create that new page and post it and continue to the next component action['page'] = page_id nested_serializer = Action_pageSerializer(data=action) if nested_serializer.is_valid(): nested_serializer.save() else: return Response(nested_serializer.errors, status=status.HTTP_400_BAD_REQUEST) continue action['page'] = page_id nested_serializer = Action_pageSerializer(choices_page, data=action) if nested_serializer.is_valid(): nested_serializer.save() else: return Response(nested_serializer.errors, status=status.HTTP_400_BAD_REQUEST) return Response(pages_serializer.data, status=status.HTTP_200_OK) # else the request was badly made return Response(pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) # check page.page_type = 'generic' if (page_type == 'g' or page_type == 'i'): pages_serializer = PagesSerializer(page, data=request.data) if pages_serializer.is_valid(): pages_serializer.save() # check that each generic page already exists for body in request.data['bodies']: try: body_page = generic_page.objects.get(id = body.get('id')) except: # if the subpage does not exist, then you create that new page and post it and continue to the next component body['page'] = page_id nested_serializer = Generic_pageSerializer(data=body) if nested_serializer.is_valid(): nested_serializer.save() else: return Response(nested_serializer.errors, status=status.HTTP_400_BAD_REQUEST) continue body['page'] = page_id nested_serializer = Generic_pageSerializer(body_page, data=body) if nested_serializer.is_valid(): nested_serializer.save() else: return Response(nested_serializer.errors, status=status.HTTP_400_BAD_REQUEST) return Response(pages_serializer.data, status=status.HTTP_200_OK) # else the request was badly made return Response(pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) # check page.page_type = 'stakeholders' if (page_type == 's'): pages_serializer = PagesSerializer(page, data=request.data) if pages_serializer.is_valid(): pages_serializer.save() # check that each stakeholder page already exists for stakeholder in request.data['stakeholders']: try: page_stakeholder = stakeholder_to_page.objects.get(stakeholder = stakeholder.get('id')) except: # if the subpage does not exist, then you create that new page and post it and continue to the next component stakeholder['page'] = page_id nested_serializer = Stakeholder_pageSerializer(data=stakeholder) if nested_serializer.is_valid(): nested_serializer.save() else: return Response(nested_serializer.errors, status=status.HTTP_400_BAD_REQUEST) continue stakeholder['page'] = page_id nested_serializer = Stakeholder_pageSerializer(page_stakeholder, data=stakeholder) if nested_serializer.is_valid(): nested_serializer.save() else: return Response(nested_serializer.errors, status=status.HTTP_400_BAD_REQUEST) return Response(pages_serializer.data, status=status.HTTP_200_OK) # else the request was badly made return Response(pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) # not a valid type of page else: return Response(status=status.HTTP_400_BAD_REQUEST) # @api_view(['delete']) def delete(self, request): # takes the page_id from the url if the url has ?page_id=<id> at the end, no parameter passed return error 400 page_id = self.request.query_params.get('page_id') # check if the page exists. try: page = pages.objects.get(page=page_id) except pages.DoesNotExist: return Response(status=status.HTTP_404_NOT_FOUND) # delete the page if (request.method == "delete"): #set next page field of pages pointing to the deleted page to be None/null next_pages = pages.objects.filter(next_page = page_id) for updated_page in next_pages: extant_page = updated_page updated_page.next_page = None updated_page_dict = PagesSerializer(updated_page).data pages_serializer = PagesSerializer(extant_page, data=updated_page_dict) if pages_serializer.is_valid(): pages_serializer.save() else: print("error in making next_page = null during delete!") return Response(pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) #also set and result_page fields pointing to the deleted page to be null as well. action_pages = action_page.objects.filter(result_page = page_id) for updated_page in action_pages: extant_page = updated_page updated_page.result_page = None updated_page_dict = Action_pageSerializer(updated_page).data action_pages_serializer = Action_pageSerializer(extant_page, data=updated_page_dict) if action_pages_serializer.is_valid(): action_pages_serializer.save() else: print("error in making next_page = null during delete!") return Response(action_pages_serializer.errors, status=status.HTTP_400_BAD_REQUEST) # finally delete the page operation = page.delete() page_data = {} if (operation): page_data["success"] = "delete successful" else: page_data["failure"] = "delete failed" return Response(data=page_data) # checked - ed - 4/15/2021 class student_info(APIView): def get(self,request,*args,**kwargs): scenario_id = self.request.query_params.get('scenario') responses_query = responses.objects.filter(scenario=scenario_id).values() student_ids = [] data = [] for response in responses_query: student = response['student'] if student not in student_ids: date_taken = response['date_taken'] student_ids.append(student) for student in student_ids: demographics_query = demographics.objects.filter(student = student).values() for dem in demographics_query: student_query = students.objects.filter(student = dem['student']).values() for x in student_query: name = x['name'] dem['name'] = name dem['date_taken'] = date_taken data.append(dem) return Response(data) # seems like no change required - chirag - 4/15 class coverages_page(APIView): def get(self, request, *args, **kwargs): stakeholder_id = self.request.query_params.get('stakeholder') stkholder = {} # print(stakeholder_id) try: coverage_list = coverage.objects.filter(stakeholder=stakeholder_id).values() # print("coverage list:", coverage_list) except coverage.DoesNotExist: return Response(status=status.HTTP_404_NOT_FOUND) issue_list = [] # check for every single coverage object that belongs to the staheholder id 'id' for coverages in coverage_list: issues_dict = {} # issuelist = coverageserializer(coverage.objects.get(issue=issueid)).data # issuelist.update({"name": issuesserializer(issues.objects.get(issue=issueid)).data['name']}) # getting the issue for the coverage dictionary associated with the stakeholder_id try: issue = issues.objects.get(issue=coverages.get('issue_id')) except: continue issues_dict.update(coverages) # del issues_dict['id'] # issues_dict['issue'] = issues_dict['issue_id'] # del issues_dict['issue_id'] # issues_dict['stakeholder'] = issues_dict['stakeholder_id'] # del issues_dict['stakeholder'] issues_dict.update( { "name": issue.name }) issue_list.append(issues_dict) stkholder.update( { "issues": issue_list } ) return Response(stkholder, status=status.HTTP_200_OK) def put(self, request, *args, **kwargs): # """ # docstring # """ data = JSONParser().parse(request) if type(data) == list: response = [] for item in data: stkholderid = item['stakeholder'] issueid = item['issue'] updatingitem = coverage.objects.get( stakeholder=stkholderid, issue=issueid) serializer = coverageSerializer( updatingitem, data=item) if serializer.is_valid(): serializer.save() response.append(serializer.data) else: return Response(response, status=status.HTTP_400_BAD_REQUEST) return Response(response, status=status.HTTP_200_OK) else: stkholderid = data['stakeholder'] issueid = data['issue'] updatingitem = coverage.objects.get( stakeholder=stkholderid, issue=issueid) serializer = coverageSerializer( updatingitem, data=data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=status.HTTP_200_OK) else: return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) class stakeholders_page(APIView): def add_detail(self, stkholders): for stkholder in stkholders: stakeholder_id = stkholder['stakeholder'] queryset = conversations.objects.filter(stakeholder=stakeholder_id) conlist = ConversationsSerializer(queryset, many=True).data stkholder['conversations'] = conlist try: coverage_list = coverage.objects.filter(stakeholder=stakeholder_id).values() except coverage.DoesNotExist: return Response(status=status.HTTP_404_NOT_FOUND) issue_list = [] # check for every single coverage object that belongs to the staheholder id 'id' for coverages in coverage_list: issues_dict = {} # issuelist = coverageserializer(coverage.objects.get(issue=issueid)).data # issuelist.update({"name": issuesserializer(issues.objects.get(issue=issueid)).data['name']}) # getting the issue for the coverage dictionary associated with the stakeholder_id try: issue = issues.objects.get(issue=coverages.get('issue')) except: continue issues_dict.update(coverages) # del issues_dict['id'] # issues_dict['issue'] = issues_dict['issue_id'] # del issues_dict['issue_id'] # issues_dict['stakeholder'] = issues_dict['stakeholder_id'] # del issues_dict['stakeholder_id'] issues_dict.update( { "name": issue.name }) issue_list.append(issues_dict) stkholder.update( { "issues": issue_list } ) return stkholders # ''' # page_data = pagesserializer(page).datapage_data.update( # { # "reflection_questions": reflection_query # } # ) # reflection_query = reflection_questions.objects.filter(page = page_id).values() # page_data.update( # { # "reflection_questions": reflection_query # } # ) # ''' def get(self, request, *args, **kwargs): ''' return format [ { "stakeholder": 3, "name": "mon", "description": "this is mon", "job": "driver", "introduction": "mon is a driver", "scenario": 1, "version": 1, "conversations": [ { "conversation": 4, "question": "question 1", "response": "answer 1", "stakeholder": 3 } ], "issues": [ { "issue": 4, "name": "issue 3", "importance_score": 10.0, "scenario": 1, "version": 1 } ] }, ] parse scenario_id and stakeholder_id from the request url example http://127.0.0.1:8000/stakeholders?scenario_id=3 http://127.0.0.1:8000/stakeholders?stakeholder_id=0 ''' # scenario not id scenario_id = self.request.query_params.get('scenario_id') stakeholder_id = self.request.query_params.get('stakeholder_id') # stakeholder_id = self.request.get.get('stakeholder_id') # handle request for scenario_id # get all stakeholder in scenario with id = scenario_id if scenario_id != None: # checking valid scenario id try: # return empty if scenario doesn't have any stakeholder # return list of stakeholder belong to that scenario scenarios.objects.get(scenario_id = scenario_id) queryset = stakeholders.objects.filter( scenario=scenario_id) data = list(StakeholdersSerializer(queryset, many=True).data) data = self.add_detail(data) return Response(data, status=status.HTTP_200_OK) # return an error for non-existed scenario id except scenarios.DoesNotExist: message = {'message': 'invalid scenario id'} return Response(message, status=status.HTTP_404_NOT_FOUND) # handle request for stakeholder_id # get the stakeholder id = stakeholder_id if stakeholder_id != None: try: queryset = stakeholders.objects.filter( stakeholder=stakeholder_id) data = list(StakeholdersSerializer(queryset, many=True).data) data = self.add_detail(data) return Response(data, status=status.HTTP_200_OK) except stakeholders.DoesNotExist: message = {'message': 'invalid stakeholder id'} return Response(message, status=status.HTTP_404_NOT_FOUND) queryset = stakeholders.objects.all() data = StakeholdersSerializer(queryset, many=True).data return Response(data, status=status.HTTP_200_OK) def post(self, request, *args, **kwargs): serializer = StakeholdersSerializer(data=request.data) if serializer.is_valid(): serializer.save() stkholderid = serializer.data['stakeholder'] scenarioid = serializer.data['scenario'] stkholderversion = serializer.data['version'] queryset = issues.objects.filter(scenario_id=scenarioid) data = issuesserializer(queryset, many=True).data for item in data: itemdict = {} itemdict['stakeholder'] = stkholderid itemdict['stakeholder_version'] = stkholderversion itemdict['issue'] = item['issue'] itemdict['name'] = item['name'] itemdict['coverage_score'] = 0 print(itemdict) itemserializer = coverageSerializer(data=itemdict) if itemserializer.is_valid(): itemserializer.save() else: return Response(itemSerializer.errors, status=status.HTTP_400_BAD_REQUEST) return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) def delete(self, request, *args, **kwargs): stakeholder_id = self.request.query_params.get('stakeholder_id') if stakeholder_id != None: try: response = stakeholders.objects.get( stakeholder =stakeholder_id) response.delete() return Response({'message': 'deleted'}, status=status.HTTP_202_ACCEPTED) except stakeholders.doesnotexist: return Response({'message': 'not found'}, status=status.HTTP_404_NOT_FOUND) else: return Response({'message': 'missing id'}, status=status.HTTP_400_BAD_REQUEST) def put(self, request, *args, **kwargs): ''' put can take one object or a list for one object put { "stakeholder": 1, "name": "stakeholder 1a", "description": "description 1", "job": "job 1", "introduction": "introduction 1", "scenario": 1, "version": 1 } for list put [ { "stakeholder": 1, "name": "stakeholder 1a", "description": "description 1", "job": "job 1", "introduction": "introduction 1", "scenario": 1, "version": 1 }, { "stakeholder": 2, "name": "stakeholder 2a", "description": "description 2", "job": "job 2", "introduction": "introduction 2", "scenario": 1, "version": 1 } ] ''' data = JSONParser().parse(request) if type(data) == list: response = [] for item in data: id = item['stakeholder'] updatingitem = stakeholders.objects.get(stakeholder=id) stkholderserializer = StakeholdersSerializer( updatingitem, data=item) if stkholderserializer.is_valid(): stkholderserializer.save() response.append(stkholderserializer.data) else: return Response(response, status=status.HTTP_400_BAD_REQUEST) return Response(response, status=status.HTTP_200_OK) else: id = data['stakeholder'] updatingitem = stakeholders.objects.get(stakeholder=id) stkholderserializer = StakeholdersSerializer( updatingitem, data=data) if stkholderserializer.is_valid(): stkholderserializer.save() return Response(stkholderserializer.data, status=status.HTTP_200_OK) else: return Response(stkholderserializer.errors, status=status.HTTP_400_BAD_REQUEST) # class coverages_page(APIView): # checked - ed - 4/15/2021 class student_responses(APIView): def get(self, request, *args, **kwargs): #filter by scenario and student id scenario = self.request.query_params.get('scenario') student = self.request.query_params.get('student') filterargs = {'scenario':scenario,'student':student} responses_query = responses.objects.filter(**filterargs).values() choice_array = [] choices_array = [] choices_dict = {} #get the different actions for response in responses_query: #filter by page number name_query = pages.objects.filter(page = response["action_page"]).values() for name in name_query: name = name['page_title'] type = name['page_type'] choices_query = action_page.objects.filter(page = response["action_page"]).values() for choice in choices_query: choice_array.append(choice['choice']) chosen_query = responses.objects.filter(action_page = response["action_page"]).values() for chose in chosen_query: chosen = chose['choice'] date_taken = chose['date_taken'] #only if it is an action page choices_dict = {"name": name, "choices":choice_array, "chosen": chosen, "date_taken": date_taken } choices_array.append(choices_dict) choice_array = [] reflections_array = [] reflections_dict = {} #get the different reflections reflections_query = reflections_taken.objects.filter(**filterargs).values() for reflection in reflections_query: name_query = pages.objects.filter(page = reflection["page"]).values() for name in name_query: name = name['page_title'] type = name['page_type'] ref_questions_query = reflection_question_to_page.objects.filter(page_id = reflection["page"]).values() for question in ref_questions_query: question = question['reflection_question'] date_taken = answer['date_taken'] ref_answers_query = reflections_taken.objects.filter(response_id = reflection["response_id"]).values() for answer in ref_answers_query: reflection = answer['reflections'] # #only if it is a reflection page reflections_dict = {"name": name, "question": question, "reflection": reflection, "date_taken": date_taken} reflections_array.append(reflections_dict) data_dict = {} data_dict["choices"] = choices_array data_dict["reflections"] = reflections_array return Response(data_dict)

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null

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1

0

4fc3c6b3bac4ffbf5de1286290c334c20512556d

5,763

py

Python

src/pipelines/train.py

mnrozhkov/MLOps-demo-project

42d6fd1546345c9bf03b7882fe8e34639a62f686

[ "MIT" ]

1

2021-12-24T00:08:32.000Z

src/pipelines/train.py

mnrozhkov/MLOps-demo-project

42d6fd1546345c9bf03b7882fe8e34639a62f686

[ "MIT" ]

null

src/pipelines/train.py

mnrozhkov/MLOps-demo-project

42d6fd1546345c9bf03b7882fe8e34639a62f686

[ "MIT" ]

null

"""This script trains the model Can be run from both cmd line (argparse to read config.yaml) or imported as a module Pipelines has artifacts on the output and describe logic""" import argparse import os import catboost as ctb import joblib import json import matplotlib.pyplot as plt import pandas as pd from typing import Text import yaml from envyaml import EnvYAML from src.train.train import custom_ts_split, get_split_data from src.utils.logging import get_logger from src.evaluate.metrics import precision_at_k_score, recall_at_k_score, lift_score def train(config_path: Text) -> None: """Train model Params: config_path {Text}: path to config file """ # Import configs: # ------------------------------------------- # config = yaml.safe_load(open(config_path)) config = EnvYAML(config_path) print(config.get('base')) # base params: random_state = config['base']['random_state'] log_level = config['base']['log_level'] # features params: features_path = config['featurize']['features_path'] categories = config['featurize']['categories'] # train params: estimator_params = config['train']['catboost_params'] # estimator = config['train']['estimator'] top_K_coef = config['train']['top_K_coef'] model_path = config['train']['model_path'] raw_metrics_path = config['train']['raw_metrics_path'] train_metrics_path = config['train']['train_metrics_path'] train_plots_path = config['train']['train_plots_path'] train_metrics_png = config['train']['train_metrics_png'] # ------------------------------------------- logger = get_logger("TRAIN", log_level) # 1. load and process joint data: logger.info('Load data') features = pd.read_feather(features_path) features['month'] = pd.to_datetime(features['month']) # 2. instantiate a model: # logger.info(f'Estimator = {estimator}') logger.info('Instantiate model') clf = ctb.CatBoostClassifier( **estimator_params, cat_features=categories, random_state=random_state ) # 3. count top k instances for subsequent train and evaluations metrics_df = pd.DataFrame(columns=['test_period', 'lift', 'precision_at_k', 'recall_at_k']) top_K = int(features.shape[0] * top_K_coef) months = features.month.sort_values().unique() logger.info(f'Top_K {top_K_coef*100}% of the dataset size: {top_K}') # 4. train model k = 1 for start_train, end_train, test_period in custom_ts_split(months, train_period=1): logger.info(f'Fold {k}:') logger.info(f'Train: {start_train} - {end_train}') logger.info(f'Test: {test_period} \n') # Get train / test data for the split X_train, X_test, y_train, y_test = get_split_data(features, start_train, end_train, test_period) logger.info(f'Train shapes: X - {X_train.shape}, y - {y_train.shape}') logger.info(f'Test shapes: X - {X_test.shape}, y - {y_test.shape}') # Fit estimator clf.fit(X_train, y_train) # Predict on test y_pred = clf.predict(X_test) probas = clf.predict_proba(X_test) logger.info(f'Max probas: {probas[:, 1].max()}') # Calculate raw metrics on test per each fold: # ------------------------------------------- lift = lift_score(y_test, y_pred, probas[:, 1], top_K) precision_at_k = precision_at_k_score(y_test, y_pred, probas[:, 1], top_K) recall_at_k = recall_at_k_score(y_test, y_pred, probas[:, 1], top_K) metrics_df = metrics_df.append( dict(zip(metrics_df.columns, [test_period, lift, precision_at_k, recall_at_k])), ignore_index=True ) k += 1 logger.info(f'Precision at {top_K}: {precision_at_k}') logger.info(f'Recall at {top_K}: {recall_at_k}\n') logger.info('Save "raw" metrics for plotting') metrics_df.to_csv(raw_metrics_path, index=False) # Create and safe aggregated (min, max, std, mean) metrics: # ------------------------------------------- logger.info('Save aggregated metrics') metrics_aggs = metrics_df[['lift', 'precision_at_k', 'recall_at_k']].agg(['max', 'min', 'std', 'mean']) metrics = { f'{metric}_{agg}': metrics_aggs.loc[agg, metric] for metric in metrics_aggs.columns for agg in metrics_aggs.index } with open(os.path.join(config['base']['project_dir'], train_metrics_path), 'w') as metrics_f: json.dump(obj=metrics, fp=metrics_f, indent=4) # Generate and save data for plots: # ------------------------------------------- logger.info('Generate & save plots') plots_df = pd.DataFrame({ 'metric': list(metrics.keys()), 'value': list(metrics.values()) }) plots_df.to_csv(train_plots_path, index=False) # Make a plot using a csv above: x_labels = list(range(0, len(metrics))) plt.figure(figsize=(10, 10)) fig = plt.bar(x_labels, list(metrics.values())) plt.title('Train metrics', fontsize=14) plt.xlabel('Metrics') plt.ylabel('Values') plt.xticks(x_labels, metrics.keys(), size='small', rotation='45') plt.grid(color='k', linestyle='-', linewidth=0.5) # plt.show() plt.savefig(train_metrics_png) # Save the trained model: # ------------------------------------------- logger.info('Save model') path = os.path.join(config['base']['project_dir'], model_path) joblib.dump(clf, path) logger.info(f'Model saved to: {path}') if __name__ == '__main__': args_parser = argparse.ArgumentParser() args_parser.add_argument('--config', dest='config', required=True) args = args_parser.parse_args() train(config_path=args.config)

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null

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null

0

1

0

4fc639588c22d23a25831ae5bc48b4a8caf6594e

9,803

py

Python

sre-recipes/recipe_runner.py

joyoza/cloud-ops-sandbox

bdd550c18b91be8953ba4b57c2e2a786ff9ad59c

[ "Apache-2.0" ]

70

2019-03-13T19:45:43.000Z

2020-08-15T16:58:19.000Z

sre-recipes/recipe_runner.py

joyoza/cloud-ops-sandbox

bdd550c18b91be8953ba4b57c2e2a786ff9ad59c

[ "Apache-2.0" ]

187

2019-04-02T22:57:13.000Z

2020-08-20T20:18:10.000Z

sre-recipes/recipe_runner.py

joyoza/cloud-ops-sandbox

bdd550c18b91be8953ba4b57c2e2a786ff9ad59c

[ "Apache-2.0" ]

29

2019-04-02T18:58:38.000Z

2020-08-20T04:04:00.000Z

# Copyright 2021 Google LLC # # 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. # -*- coding: utf-8 -*- """ This file contains utility runtime classes implementing core SRE Recipes features, such as breaking and restoring microservices, printing hints, and running interactive multiple choice questions. Currently, it implements two SRE Recipe Runner: - ImplBasedRecipeRunner: runs SRE Recipe implemented via python classes. - ConfigBasedRecipeRunner: runs SRE Recipes defined as YAML configs. Refer to the class docstring for further explanations. """ import abc import importlib import requests import subprocess import yaml from inspect import isclass from os import path import utils from recipes.impl_based.base import BaseRecipeImpl # Default Load Generation Config DEFAULT_LOADGEN_USER_TYPE = "BasicHomePageViewingUser" DEFAULT_LOADGEN_USER_COUNT = 20 DEFAULT_LOADGEN_SPAWN_RATE = 1 DEFAULT_LOADGEN_TIMEOUT_SECONDS = 600 class ImplBasedRecipeRunner: """A SRE Recipe runner for running recipes implemented as class objects. Given a `recipe_name`, it tries to run `recipes/impl_based/recipe_name.py`. This runner will propgate all exceptions to the caller, and it is caller's responsibility to handle any exception and to perform any error logging. """ def __init__(self, recipe_name): self.recipe = None module = importlib.import_module(f"recipes.impl_based.{recipe_name}") for attribute_name in dir(module): attr = getattr(module, attribute_name) if isclass(attr) and attr is not BaseRecipeImpl and issubclass(attr, BaseRecipeImpl): self.recipe = attr() break if not self.recipe: raise NotImplementedError( f"No valid implementation exists for `{recipe_name}` recipe.") def get_name(self): return self.recipe.get_name() def get_description(self): return self.recipe.get_description() def run_break(self): return self.recipe.run_break() def run_restore(self): return self.recipe.run_restore() def run_hint(self): return self.recipe.run_hint() def run_verify(self): return self.recipe.run_verify() class ConfigBasedRecipeRunner: """A SRE Recipe runner for running recipes implemented using configs. Given a `recipe_name`, it tries to load `recipes/configs_based/recipe_name.yaml`. This runner will propagate all exceptions to the caller, and it is caller's responsibility to handle any exception and to perform any error logging. """ def __init__(self, recipe_name, skip_loadgen=False): filepath = path.join(path.dirname( path.abspath(__file__)), f"recipes/configs_based/{recipe_name}.yaml") with open(filepath, "r") as file: self.recipe = yaml.safe_load(file.read()) if not self.recipe: raise ValueError("Cannot parse config as YAML.") self.action_handler = ActionHandler(skip_loadgen) def get_name(self): return self.recipe.get("name", "No name found") def get_description(self): return self.recipe.get("description", "No description found") @property def config(self): return self.recipe.get("config", {}) def run_break(self): print('Deploying broken service...') for action in self.config.get("break", []): self.action_handler.handle_action(action) print('Done. Deployed broken service') def run_restore(self): print('Restoring service back to normal...') for action in self.config.get("restore", []): self.action_handler.handle_action(action) print('Done. Restored broken service to working state.') def run_hint(self): hint = self.config.get("hint", None) if hint: print(f'Here is your hint!\n\n{hint}') else: print("This recipe has no hints.") def run_verify(self): verify_config = self.config.get("verify", []) if not verify_config: raise NotImplementedError("Verify is not configured") for action in verify_config: self.action_handler.handle_action(action) class ActionHandler: """A utility helper for executing actions supported by SRE Recipe configs. Implementation Guide -------------------- 1. Map the action name to the action handler in the `__init__` method. 2. All action handlers should take exactly one argument, which is the full config specified for the action itself, as it is defined in YAML. For example: {action: "run-shell-commands", commands: ['echo Hi']} This runner will propgate all exceptions to the caller, and it is caller's responsibility to handle any exception and to perform any error logging. """ def __init__(self, skip_loadgen=False): # Action types to action handlers self.action_map = { "run-shell-commands": self.run_shell_commands, "multiple-choice-quiz": self.run_multiple_choice_quiz, "loadgen-spawn": self.loadgen_spawn, "loadgen-stop": self.loadgen_stop, } if skip_loadgen: # ignore loadgen actions when requested self.action_map["loadgen-spawn"] = lambda *args: None self.action_map['loadgen-stop'] = lambda *args: None # Reusable parameters shared between action handlers self.loadgen_ip = None def handle_action(self, config): if "action" not in config: raise ValueError("Action config missing `action` type") action_type = config["action"] if action_type not in self.action_map: raise NotImplementedError( f"Action type not implemented: {action_type}") return self.action_map[action_type](config) def init_loadgen_ip(self): if not self.loadgen_ip: self.loadgen_ip, err = utils.get_loadgen_ip() if err: raise RuntimeError(f"Failed to get loadgen IP: {err}") ############################ Action Handlers ############################### def run_shell_commands(self, config): """Runs the commands one at a time in shell. Config Paramters ---------------- commands: string[] Required. A list of shell command strings. """ for cmd in config["commands"]: output, err = utils.run_shell_command(cmd) if err: raise RuntimeError( f"Failed to run command `{cmd}`: {err}") def run_multiple_choice_quiz(self, config): """Runs an interactive multiple choice quiz. Config Paramters ---------------- prompt: string Required. The question prompt to display to the user. choices: dict[] option: string Required. The answer display text to show to the user. accept: bool Optional. If true, the choice is considered correct. """ if "prompt" not in config: raise ValueError("No prompt specified for the multiple choice.") elif "choices" not in config: raise ValueError( "No answer choices available for the multiple choice.") utils.run_interactive_multiple_choice( config["prompt"], config["choices"]) def loadgen_spawn(self, config): """ Starts spawning a load shape at specified spawn rate until a total user count is reached. Then, stop the load after a specified timesout. Config Paramters ---------------- user_type: string Optional. Same as the `sre_recipe_user_identifier` for locust tasks defined in `sre/loadgenerator/locust_tasks`. Default: BasicHomePageViewingUser. user_count: int Optional. The number of total users to spawn. Default: 20. spawn_rate: int Optional. The number of users per second to spawn. Default: 1. stop_after: int Optional. The number of seconds to spawn before stopping. Default: 600 seconds. """ self.init_loadgen_ip() user_type = config.get( "user_type", DEFAULT_LOADGEN_USER_TYPE) resp = requests.post( f"http://{self.loadgen_ip}:81/api/spawn/{user_type}", { "user_count": int(config.get("user_count", DEFAULT_LOADGEN_USER_COUNT)), "spawn_rate": int(config.get("spawn_rate", DEFAULT_LOADGEN_SPAWN_RATE)), "stop_after": int(config.get("stop_after", DEFAULT_LOADGEN_TIMEOUT_SECONDS)) }) if not resp.ok: raise RuntimeError( f"Failed to start load generation: {resp.status_code} {resp.reason}") def loadgen_stop(self, config): """Stops any active load generation produced by SRE Recipes. Config Paramters is not required. """ self.init_loadgen_ip() resp = requests.post(f"http://{self.loadgen_ip}:81/api/stop") if not resp.ok: raise RuntimeError( f"Failed to stop existing load generation: {resp.status_code} {resp.reason}")

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0.044776

0

null

0

null

0

1

0

4fc6f58b73db4f14ff029cec250fcca647c6c8f4

4,065

py

Python

backend/ctgov/api/serializers.py

ClinicalTrialsTeam/CTFrontier

d7e2558f314f6bbd9964667e12ee5655bc64215b

[ "Apache-2.0" ]

4

2021-03-07T02:16:22.000Z

2022-03-13T03:22:42.000Z

backend/ctgov/api/serializers.py

ClinicalTrialsTeam/CTFrontier

d7e2558f314f6bbd9964667e12ee5655bc64215b

[ "Apache-2.0" ]

8

2021-03-14T22:14:07.000Z

2021-04-26T17:20:56.000Z

backend/ctgov/api/serializers.py

ClinicalTrialsTeam/CTFrontier

d7e2558f314f6bbd9964667e12ee5655bc64215b

[ "Apache-2.0" ]

1

2021-03-07T02:16:39.000Z

from rest_framework import serializers from ctgov.models import ( BriefSummaries, SearchStudies, Facilities, BrowseConditions, Countries, ) from django_elasticsearch_dsl_drf.serializers import DocumentSerializer from ctgov.documents import ClinicalTrialsSearchStudies # Serializer to return Brief Summaries dataset class BriefSummariesSerializer(serializers.ModelSerializer): class Meta: model = BriefSummaries fields = ["nct", "description"] # Serializer to return Search Studies Results dataset class SearchStudiesSerializer(serializers.ModelSerializer): class Meta: model = SearchStudies fields = [ "status", "brief_title", "nct_id", "condition_name", "intervention_name", "location_name", "study_phase", "sponsor_name", "location_name", "study_brief_desc", "primary_outcome_measures", "secondary_outcome_measures", "study_start_date", "primary_completion_date", ] # Serializer to return Study Countries list class CountriesSerializer(serializers.ModelSerializer): class Meta: model = Countries fields = ["name"] # Serializer to return Study States list class StatesSerializer(serializers.ModelSerializer): class Meta: model = Facilities fields = ["state"] # Serializer to return Study Cities list class CitySerializer(serializers.ModelSerializer): class Meta: model = Facilities fields = ["city"] # Serializer to return conditions list class ConditionsSerializer(serializers.ModelSerializer): class Meta: model = BrowseConditions fields = ["mesh_term"] # Serializer to return Trial Timelines dataset class TrialTimelinesSerializer(serializers.ModelSerializer): class Meta: model = SearchStudies fields = [ "brief_title", "status", "sponsor_name", "nct_id", "study_start_date", "primary_completion_date", "study_phase", ] # Serializer to return single Study dataset class StudyDetailSerializer(serializers.ModelSerializer): class Meta: model = SearchStudies fields = [ "nct_id", "brief_title", "official_title", "study_brief_desc", "study_detailed_desc", "status", "study_phase", "study_start_date", "primary_completion_date", "study_first_posted_date", "results_first_posted_date", "last_update_posted_date", "results_submitted_qc_not_done", "results_submitted_qc_done", "study_type", "condition_name", "intervention_name", "eligibility_criteria", "eligibility_gender", "eligibility_min_age", "eligibility_max_age", "sponsor_name", "funder_type", "primary_outcome_measures", "secondary_outcome_measures", "study_ids", "document_types", "is_unapproved_device", "acronym", "healthy_volunteers", "location_name", "country_name", "city_name", "state_name", ] # Serialzer for Elastic Search document class SearchStudiesDocumentSerializer(DocumentSerializer): class Meta: document = ClinicalTrialsSearchStudies fields = [ "status", "brief_title", "nct_id", "condition_name", "intervention_name", "location_name", "study_phase", "sponsor_name", "location_name", "study_brief_desc", "primary_outcome_measures", "secondary_outcome_measures", "study_start_date", "primary_completion_date", ]

27.466216

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0.59508

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0.313253

0.034944

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null

0

null

0

1

0

4fc8f0cb502a004f5f664475459658f0253a384a

3,792

py

Python

histcensusgis/text/download_sm_crosswalk.py

graziul/hist-census-gis

558bf38cd0e444b5a91133dd70c88210da3cbbc9

[ "MIT" ]

4

2017-05-15T20:54:25.000Z

2019-01-30T19:04:24.000Z

histcensusgis/text/download_sm_crosswalk.py

graziul/hist-census-gis

558bf38cd0e444b5a91133dd70c88210da3cbbc9

[ "MIT" ]

null

histcensusgis/text/download_sm_crosswalk.py

graziul/hist-census-gis

558bf38cd0e444b5a91133dd70c88210da3cbbc9

[ "MIT" ]

1

2017-07-12T18:06:19.000Z

import re import urllib state_list = ["ri"] # Dict: add v(alue) to k(ey), create k if it doesn't exist def Dict_append(Dict, k, v) : if not k in Dict : Dict[k] = [v] else : Dict[k].append(v) # Version of Dict_append that only accepts unique v(alues) for each k(ey) def Dict_append_unique(Dict, k, v) : if not k in Dict : Dict[k] = [v] else : if not v in Dict[k] : Dict[k].append(v) def download_year(year) : #year = 1920 or year = 1940 for state_abbr in state_list : url = "http://stevemorse.org/census/%s/%s.txt" % (str(year),state_abbr) url_handle = urllib.urlopen(url) sourcetext = url_handle.readlines() url_handle.close() if year == 1940 : old_year = 1930 if year == 1920 : year = 1930 old_year = 1920 year, old_year = str(year),str(old_year) county, old_county = '','' city = '' ed, old_ed = '','' county_name,old_county_name = '','' for line in sourcetext : line = line.strip() if line[:2] == '**' or line == '' : continue if line[0] == '+' : #line defining a county number year_county = re.search("\+([0-9]+)=([0-9%]+),(.*)",line) line_year,line_county,line_county_name = year_county.group(1),year_county.group(2),year_county.group(3) if line_year == year : if line_county == '%' : #"%" sign means number is same as old number county = old_county else : county = line_county if line_county_name == '%' : county_name = old_county_name else : county_name = line_county_name if line_year == old_year : old_county = line_county old_county_name = line_county_name county_name_county_dict[county_name] = county Dict_append_unique(state_county_dict,state_abbr,county) if old_county != county or old_county_name != county_name: county_name_county_dict[old_county_name] = old_county county_change_dict[old_county_name] = county_name continue if line[0] == '^' : #cache value(s) for old_ed cache_ed = re.search("\^\*(.+)",line) old_ed = cache_ed.group(1) continue eds_city = re.search("([^*]+)\*([^*]+)\*?(.*)",line) ed,line_old_ed,line_city = eds_city.group(1),eds_city.group(2),eds_city.group(3) if line_old_ed != '^' : old_ed = line_old_ed if line_city != "" : city = line_city if line_city == "#" : # "#" clears previous value for city city = "" Dict_append_unique(ed_old_ed_dict,county+'-'+ed,old_county+'-'+old_ed) if city!= "" : Dict_append_unique(city_ed_dict,city,county+'-'+ed) Dict_append_unique(county_ed_dict,county,ed) if county != old_county: Dict_append_unique(county_ed_dict,old_county,old_ed) ed_old_ed_dict = {} #lookup "[county]-[ed]" -> list of old ed(s) corresponding city_ed_dict = {} #lookup city+state_abbr -> list of eds in city county_ed_dict = {} #lookup county number -> list of eds in county state_county_dict = {} #lookup state_abbr -> list of counties in state county_name_county_dict = {} #lookup county name+state_abbr -> county number county_change_dict = {} #lookup old_county_name -> county_name download_year(1940)

39.915789

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3,792

3.966805

0.176349

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0.083682

0.062762

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0.029289

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3,792

94

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1

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false

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0

0.0625

0

null

0

null

0

1

0

4fcbdc8b235bd4cfffdf1d92aa508c37e0145018

6,973

py

Python

model_lib/src/model.py

modzy/grpc-tensorflow-object-detection

e81b2ae60c46f48cad204934868849e97e0d4a63

[ "Apache-2.0" ]

null

model_lib/src/model.py

modzy/grpc-tensorflow-object-detection

e81b2ae60c46f48cad204934868849e97e0d4a63

[ "Apache-2.0" ]

null

model_lib/src/model.py

modzy/grpc-tensorflow-object-detection

e81b2ae60c46f48cad204934868849e97e0d4a63

[ "Apache-2.0" ]

null

import json from typing import Dict, List import os import numpy as np import tensorflow as tf import tensorflow_hub as hub """ The required output structure for a successful inference run for a models is the following JSON: { "data": { "result": <inference-result>, "explanation": <explanation-data>, "drift": <drift-data>, } } The `data` key is required and stores a dictionary which represents the output for a specific input. The only top-level key within these dictionaries that is required is `result`, however, `explanation` and `drift` are additional keys that may be included if your particular model supports drift detection or explainability. All three of these keys (`result`, `explanation`, and `drift`) are required to have a particular format in order to provide platform support. This format type must be specified in the model.yaml file for the version that you are releasing, and the structure for this format type must be followed. If no formats are specified, it is possible to define your own custom structure on a per-model basis. The required output structure for a failed inference run for a models is the following JSON: { "error_message": <error-message> } Here, all error information that you can extract can be loaded into a single string and returned. This could be a JSON string with a structured error log, or a stack trace dumped to a string. Specifications: This section details the currently supported specifications for the "result", "explanation", and "drift" fields of each successful output JSON. These correspond to specifications selected in the `resultsFormat`, `driftFormat`, `explanationFormat` of the model.yaml file for the particular version of the model. * `resultsFormat`: 1A) imageClassification "result": { "classPredictions": [ {"class": <class-1-label>, "score": <class-1-probability>}, ..., {"class": <class-n-label>, "score": <class-n-probability>} ] } * `driftFormat` 2A) imageRLE explanation: { "maskRLE": <rle-mask> } Here, the <rle-mask> is a fortran ordered run-length encoding. * `explanationFormat` 3A) ResNet50 drift: { { "layer1": <layer-data> "layer2": <layer-data> "layer3": <layer-data> "layer4": <layer-data> } } """ ROOT_DIR = os.path.dirname(os.path.abspath(__file__)) MODEL_DIR = os.path.join(ROOT_DIR, "openimages_v4_ssd_mobilenet_v2_1") def get_success_json_structure(inference_result, explanation_result, drift_result) -> Dict[str, bytes]: output_item_json = { "data": { "result": inference_result, "explanation": explanation_result, "drift": drift_result, } } return {"results.json": json.dumps(output_item_json, separators=(",", ":")).encode()} def get_failure_json_structure(error_message: str) -> Dict[str, bytes]: error_json = {"error_message": error_message} return {"error": json.dumps(error_json).encode()} class TensorflowObjectDetection: # Note: Throwing unhandled exceptions that contain lots of information about the issue is expected and encouraged # for models when they encounter any issues or internal errors. def __init__(self): """ This constructor should perform all initialization for your model. For example, all one-time tasks such as loading your model weights into memory should be performed here. This corresponds to the Status remote procedure call. """ self.detector = hub.load(MODEL_DIR).signatures['default'] def format_detections(self,result_object): # parse out what we need from result_object class_names = result_object["detection_class_entities"] scores = result_object["detection_scores"] bboxes = result_object["detection_boxes"] # store formatted detections in this list formatted_detections = [] for name, score, bbox in zip(class_names, scores, bboxes): ymin, xmin, ymax, xmax = tuple(bbox) detection = {} detection["class"] = name.decode() detection["score"] = round(score.item(), 3) detection["xmin"] = xmin.item() detection["ymin"] = ymin.item() detection["xmax"] = xmax.item() detection["ymax"] = ymax.item() formatted_detections.append(detection) formatted_results = {"detections": formatted_detections} return formatted_results def handle_single_input(self, model_input: Dict[str, bytes], detect_drift: bool, explain: bool) -> Dict[str, bytes]: """ This corresponds to the Run remote procedure call for single inputs. """ # `model_input` will have binary contents for each of the input file types specified in your model.yaml file # You are responsible for processing these files in a manner that is specific to your model, and producing # inference, drift, and explainability results where appropriate. # process image bytes using tf libary img_bytes = model_input["image"] img = tf.io.decode_image(img_bytes, channels=3) converted_img = tf.image.convert_image_dtype(img, tf.float32)[tf.newaxis, ...] results = self.detector(converted_img) # format results result = {key:value.numpy() for key,value in results.items()} inference_result = self.format_detections(result) explanation_result = None drift_result = None # structure outputs correctly output = get_success_json_structure(inference_result, explanation_result, drift_result) return output def handle_input_batch(self, model_inputs: List[Dict[str, bytes]], detect_drift, explain) -> List[Dict[str, bytes]]: """ This is an optional method that will be attempted to be called when more than one inputs to the model are ready to be processed. This enables a user to provide a more efficient means of handling inputs in batch that takes advantage of specific properties of their model. If you are not implementing custom batch processing, this method should raise a NotImplementedError. If you are implementing custom batch processing, then any unhandled exception will be interpreted as a fatal error that will result in the entire batch failing. If you would like to allow individual elements of the batch to fail without failing the entire batch, then you must handle the exception within this function, and ensure the JSON structure for messages with an error has a top level "error" key with a detailed description of the error message. This corresponds to the Run remote procedure call for batch inputs. { "error": "your error message here" } """ raise NotImplementedError

38.738889

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6,973

5.245262

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0

0.320755

0

null

0

null

0

1

0

4fce8b82f36a45eec7ceec13d644693923705d92

740

py

Python

dexbot/qt_queue/queue_dispatcher.py

Learn-code-strategies/DEXBot

ed85b12d8ad8d6ec373fd216a98e55b72f90b860

[ "MIT" ]

1

2019-11-10T06:53:35.000Z

dexbot/qt_queue/queue_dispatcher.py

g3d/DEXBot

a2b1462d78d7154cb10871a7cec9a44c8d6664de

[ "MIT" ]

null

dexbot/qt_queue/queue_dispatcher.py

g3d/DEXBot

a2b1462d78d7154cb10871a7cec9a44c8d6664de

[ "MIT" ]

1

2019-11-10T06:53:37.000Z

from PyQt5.Qt import QApplication from PyQt5.QtCore import QThread, QEvent from dexbot.qt_queue.idle_queue import idle_loop class ThreadDispatcher(QThread): def __init__(self, parent): QThread.__init__(self) self.parent = parent def run(self): while True: callback = idle_loop.get() if callback is None: break QApplication.postEvent(self.parent, _Event(callback)) def stop(self): idle_loop.put(None) self.wait() class _Event(QEvent): EVENT_TYPE = QEvent.Type(QEvent.registerEventType()) def __init__(self, callback): # Thread-safe QEvent.__init__(self, _Event.EVENT_TYPE) self.callback = callback

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0.04878

0

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0.267568

740

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24.666667

0.828413

0.014865

0

1

0.190476

false

0

0.142857

0

0.47619

0

null

0

null

0

1

0

4fd1f271a1d4fe49bf1991df1e909dc9274b04de

9,083

py

Python

google/cloud/operation/__init__.py

yukihira1992/python-cloud-core

45dcc73722846f671cc1434bebdd99d154a8c892

[ "Apache-2.0" ]

18

2020-08-06T04:01:03.000Z

2022-03-28T04:05:57.000Z

google/cloud/operation/__init__.py

yukihira1992/python-cloud-core

45dcc73722846f671cc1434bebdd99d154a8c892

[ "Apache-2.0" ]

75

2020-02-07T02:45:27.000Z

2022-03-07T21:57:52.000Z

google/cloud/operation/__init__.py

yukihira1992/python-cloud-core

45dcc73722846f671cc1434bebdd99d154a8c892

[ "Apache-2.0" ]

18

2020-02-08T13:52:05.000Z

2022-03-31T19:50:51.000Z

# Copyright 2016 Google LLC # # 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. """Wrap long-running operations returned from Google Cloud APIs.""" from typing import Dict from google.longrunning import operations_pb2 from google.protobuf import json_format _GOOGLE_APIS_PREFIX = "type.googleapis.com" _TYPE_URL_MAP: Dict[str, type] = {} def _compute_type_url(klass, prefix=_GOOGLE_APIS_PREFIX): """Compute a type URL for a klass. :type klass: type :param klass: class to be used as a factory for the given type :type prefix: str :param prefix: URL prefix for the type :rtype: str :returns: the URL, prefixed as appropriate """ name = klass.DESCRIPTOR.full_name return "%s/%s" % (prefix, name) def register_type(klass, type_url=None): """Register a klass as the factory for a given type URL. :type klass: :class:`type` :param klass: class to be used as a factory for the given type :type type_url: str :param type_url: (Optional) URL naming the type. If not provided, infers the URL from the type descriptor. :raises ValueError: if a registration already exists for the URL. """ if type_url is None: type_url = _compute_type_url(klass) if type_url in _TYPE_URL_MAP: if _TYPE_URL_MAP[type_url] is not klass: raise ValueError("Conflict: %s" % (_TYPE_URL_MAP[type_url],)) _TYPE_URL_MAP[type_url] = klass def _from_any(any_pb): """Convert an ``Any`` protobuf into the actual class. Uses the type URL to do the conversion. .. note:: This assumes that the type URL is already registered. :type any_pb: :class:`google.protobuf.any_pb2.Any` :param any_pb: An any object to be converted. :rtype: object :returns: The instance (of the correct type) stored in the any instance. """ klass = _TYPE_URL_MAP[any_pb.type_url] return klass.FromString(any_pb.value) class Operation(object): """Representation of a Google API Long-Running Operation. .. _protobuf: https://github.com/googleapis/googleapis/blob/\ 050400df0fdb16f63b63e9dee53819044bffc857/\ google/longrunning/operations.proto#L80 .. _service: https://github.com/googleapis/googleapis/blob/\ 050400df0fdb16f63b63e9dee53819044bffc857/\ google/longrunning/operations.proto#L38 .. _JSON: https://cloud.google.com/speech/reference/rest/\ v1beta1/operations#Operation This wraps an operation `protobuf`_ object and attempts to interact with the long-running operations `service`_ (specific to a given API). (Some services also offer a `JSON`_ API that maps the same underlying data type.) :type name: str :param name: The fully-qualified path naming the operation. :type client: :class:`~google.cloud.client.Client` :param client: The client used to poll for the status of the operation. If the operation was created via JSON/HTTP, the client must own a :class:`~google.cloud._http.Connection` to send polling requests. If created via protobuf, the client must have a gRPC stub in the ``_operations_stub`` attribute. :type caller_metadata: dict :param caller_metadata: caller-assigned metadata about the operation """ target = None """Instance assocated with the operations: callers may set.""" response = None """Response returned from completed operation. Only one of this and :attr:`error` can be populated. """ error = None """Error that resulted from a failed (complete) operation. Only one of this and :attr:`response` can be populated. """ metadata = None """Metadata about the current operation (as a protobuf). Code that uses operations must register the metadata types (via :func:`register_type`) to ensure that the metadata fields can be converted into the correct types. """ _from_grpc = True def __init__(self, name, client, **caller_metadata): self.name = name self.client = client self.caller_metadata = caller_metadata.copy() self._complete = False @classmethod def from_pb(cls, operation_pb, client, **caller_metadata): """Factory: construct an instance from a protobuf. :type operation_pb: :class:`~google.longrunning.operations_pb2.Operation` :param operation_pb: Protobuf to be parsed. :type client: object: must provide ``_operations_stub`` accessor. :param client: The client used to poll for the status of the operation. :type caller_metadata: dict :param caller_metadata: caller-assigned metadata about the operation :rtype: :class:`Operation` :returns: new instance, with attributes based on the protobuf. """ result = cls(operation_pb.name, client, **caller_metadata) result._update_state(operation_pb) result._from_grpc = True return result @classmethod def from_dict(cls, operation, client, **caller_metadata): """Factory: construct an instance from a dictionary. :type operation: dict :param operation: Operation as a JSON object. :type client: :class:`~google.cloud.client.Client` :param client: The client used to poll for the status of the operation. :type caller_metadata: dict :param caller_metadata: caller-assigned metadata about the operation :rtype: :class:`Operation` :returns: new instance, with attributes based on the protobuf. """ operation_pb = json_format.ParseDict(operation, operations_pb2.Operation()) result = cls(operation_pb.name, client, **caller_metadata) result._update_state(operation_pb) result._from_grpc = False return result @property def complete(self): """Has the operation already completed? :rtype: bool :returns: True if already completed, else false. """ return self._complete def _get_operation_rpc(self): """Polls the status of the current operation. Uses gRPC request to check. :rtype: :class:`~google.longrunning.operations_pb2.Operation` :returns: The latest status of the current operation. """ request_pb = operations_pb2.GetOperationRequest(name=self.name) return self.client._operations_stub.GetOperation(request_pb) def _get_operation_http(self): """Checks the status of the current operation. Uses HTTP request to check. :rtype: :class:`~google.longrunning.operations_pb2.Operation` :returns: The latest status of the current operation. """ path = "operations/%s" % (self.name,) api_response = self.client._connection.api_request(method="GET", path=path) return json_format.ParseDict(api_response, operations_pb2.Operation()) def _get_operation(self): """Checks the status of the current operation. :rtype: :class:`~google.longrunning.operations_pb2.Operation` :returns: The latest status of the current operation. """ if self._from_grpc: return self._get_operation_rpc() else: return self._get_operation_http() def _update_state(self, operation_pb): """Update the state of the current object based on operation. :type operation_pb: :class:`~google.longrunning.operations_pb2.Operation` :param operation_pb: Protobuf to be parsed. """ if operation_pb.done: self._complete = True if operation_pb.HasField("metadata"): self.metadata = _from_any(operation_pb.metadata) result_type = operation_pb.WhichOneof("result") if result_type == "error": self.error = operation_pb.error elif result_type == "response": self.response = _from_any(operation_pb.response) def poll(self): """Check if the operation has finished. :rtype: bool :returns: A boolean indicating if the current operation has completed. :raises ValueError: if the operation has already completed. """ if self.complete: raise ValueError("The operation has completed.") operation_pb = self._get_operation() self._update_state(operation_pb) return self.complete

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0

null

0

null

0

1

0

4fd2696a35b16c6c97eed2b7e1a388183c51d0e4

3,007

py

Python

src/datasets/pamap2.py

niall-twomey/har_datasets

68f142ba613ce26f67cdd6b871117f4c24ea603f

[ "MIT" ]

24

2018-12-12T08:54:52.000Z

2021-12-07T08:45:13.000Z

src/datasets/pamap2.py

niall-twomey/har_datasets

68f142ba613ce26f67cdd6b871117f4c24ea603f

[ "MIT" ]

3

2019-07-18T20:14:41.000Z

2022-03-12T01:03:28.000Z

src/datasets/pamap2.py

niall-twomey/har_datasets

68f142ba613ce26f67cdd6b871117f4c24ea603f

[ "MIT" ]

9

2018-12-12T16:18:39.000Z

2022-03-30T16:25:47.000Z

from collections import defaultdict from os.path import join import numpy as np import pandas as pd from tqdm import tqdm from src.datasets.base import Dataset from src.utils.decorators import fold_decorator from src.utils.decorators import index_decorator from src.utils.decorators import label_decorator __all__ = [ "pamap2", ] class pamap2(Dataset): def __init__(self): super(pamap2, self).__init__(name=self.__class__.__name__, unzip_path=lambda p: join(p, "Protocol")) @label_decorator def build_label(self, task, *args, **kwargs): df = pd.DataFrame(iter_pamap2_subs(path=self.unzip_path, cols=[1], desc=f"{self.identifier} Labels")) return self.meta.inv_lookup[task], df @fold_decorator def build_predefined(self, *args, **kwargs): def folder(sid, data): return np.zeros(data.shape[0]) + sid df = iter_pamap2_subs( path=self.unzip_path, cols=[1], desc=f"{self.identifier} Folds", callback=folder, columns=["fold"], ).astype(int) lookup = { 1: "train", 2: "train", 3: "test", 4: "train", 5: "train", 6: "test", 7: "train", 8: "train", 9: "test", } return df.assign(fold_0=df["fold"].apply(lookup.__getitem__))[["fold_0"]].astype("category") @index_decorator def build_index(self, *args, **kwargs): def indexer(sid, data): subject = np.zeros(data.shape[0])[:, None] + sid trial = np.zeros(data.shape[0])[:, None] + sid return np.concatenate((subject, trial, data), axis=1) df = iter_pamap2_subs( path=self.unzip_path, cols=[0], desc=f"{self.identifier} Index", callback=indexer, columns=["subject", "trial", "time"], ).astype(dict(subject=int, trial=int, time=float)) return df def build_data(self, loc, mod, *args, **kwargs): offset = dict(wrist=3, chest=20, ankle=37)[loc] + dict(accel=1, gyro=7, mag=10)[mod] df = iter_pamap2_subs( path=self.unzip_path, cols=list(range(offset, offset + 3)), desc=f"Parsing {mod} at {loc}", columns=["x", "y", "z"], ).astype(float) scale = dict(accel=9.80665, gyro=np.pi * 2.0, mag=1.0)[mod] return df.values / scale def iter_pamap2_subs(path, cols, desc, columns=None, callback=None, n_subjects=9): data = [] for sid in tqdm(range(1, n_subjects + 1), desc=desc): datum = pd.read_csv(join(path, f"subject10{sid}.dat"), delim_whitespace=True, header=None, usecols=cols).fillna( method="ffill" ) assert np.isfinite(datum.values).all() if callback: data.extend(callback(sid, datum.values)) else: data.extend(datum.values) df = pd.DataFrame(data) if columns: df.columns = columns return df

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0.041104

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3,007

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null

0

null

0

1

0

4fd295385f1b54e68df6d434899e0f6d50c545f6

8,970

py

Python

tumor_migration_analysis/analyze_TrackMate_tracks.py

agclark12/tumor_migration_analysis

c63d43306f9f381ddec04a8301fcd268a5d71c38

[ "MIT" ]

null

tumor_migration_analysis/analyze_TrackMate_tracks.py

agclark12/tumor_migration_analysis

c63d43306f9f381ddec04a8301fcd268a5d71c38

[ "MIT" ]

null

tumor_migration_analysis/analyze_TrackMate_tracks.py

agclark12/tumor_migration_analysis

c63d43306f9f381ddec04a8301fcd268a5d71c38

[ "MIT" ]

null

#!/opt/local/bin/python """ This script reads TrackMate data from .xml files and analyzes the trajectories. The dynamics parameters are written to a new csv file and histograms for persistence and mean instantaneous speed are generated. """ import os import time import xml.etree.ElementTree as ET import numpy as np import matplotlib.pyplot as plt from skimage.io._plugins import tifffile_plugin as tifffile import migration_analysis as migra import utility_functions as uf def plot_corr_vs_dist(ax,dist,corr_mean,corr_std,color): """Bins correlation vs. distance data (or any 2D data for that matter) Parameters ---------- ax : matplotlib axis the axis used for plotting dist : 1D numpy array the distance data (binned x coordinate) corr_mean : 1D numpy array the mean directional correlation data (binned) corr_mean : 1D numpy array the standard deviation of the directional correlation data (binned) color : string the matplotlib color used for plotting Returns ------- ax : matplotlib axis the axis used for plotting """ #gets rid of any nans nan_array = ~np.isnan(corr_mean) dist = dist[nan_array] corr_std = corr_std[nan_array] corr_mean = corr_mean[nan_array] #plot means ax.plot(dist, corr_mean, 'o', color=color, zorder=2, alpha=0.7) #plot std fill_y_top = np.ones(len(dist))*(corr_mean+corr_std) fill_y_bottom = np.ones(len(dist))*(corr_mean-corr_std) ax.fill_between(dist,fill_y_top,fill_y_bottom,facecolor=color,color=color,alpha=0.3,linewidth=0,zorder=1) ax.set_xlabel('Distance ($\mu$m)') ax.set_ylabel('Directional Correlation') return ax def bin_corr_vs_dist(dist_list,corr_list,n_bins=50): """Bins correlation vs. distance data (or any 2D data for that matter) Parameters ---------- dist_list : 1D list (or numpy array) the distance data corr_list : 1D list (or numpy array) the directional correlation data Returns ------- x_vals : 1D numpy array the binned distance data (centered on the bin) H_means : 1D numpy array the mean of the directional correlation at each bin H_stds : 1D numpy array the standard deviation of the directional correlation at each bin H_lens : 1D numpy array the number of data points (n) at each bin """ # converts to np arrays start_dist_list = np.array(dist_list) mean_corr_list = np.array(corr_list) # calculates the means/SDs for the binned data bins = np.linspace(np.min(start_dist_list), np.max(start_dist_list) + .000000001, n_bins) bin_id = np.digitize(start_dist_list, bins) H_means = np.array([np.nanmean(mean_corr_list[bin_id == i]) for i in range(1, len(bins))]) H_stds = np.array([np.nanstd(mean_corr_list[bin_id == i]) for i in range(1, len(bins))]) H_lens = np.array([len(mean_corr_list[bin_id == i]) for i in range(1, len(bins))]) # adjust edges x_vals = np.array([(bins[i] + bins[i + 1]) / 2. for i in range(len(bins) - 1)]) return x_vals, H_means, H_stds, H_lens def analyze_trackmate_file(img_file_path, track_file_path, time_int=1, px_size=1): """Analyzes the TrackMate data Parameters ---------- img_file_path : string path where the image file is located (must be a .tif file) track_file_path : string path where the TrackMate tracks file is located (.xml file) time_int : float time interval in minutes px_size: float pixel size in um/px """ #makes a new directory to store the data save_dir = os.path.splitext(track_file_path)[0] if not os.path.isdir(save_dir): os.mkdir(save_dir) basename = os.path.basename(save_dir) print(basename) #opens and parses the TrackMate xml file tree = ET.parse(track_file_path) root = tree.getroot() #makes some lists for collecting the tracking data print("Calculating Tracking Parameters") traj_dict_list = [] param_dict_list = [] #loops through each trajectory for i, particle in enumerate(root.findall('particle')): #sets up lists for the trajectory t = np.zeros(int(particle.attrib['nSpots'])) x = np.zeros_like(t) y = np.zeros_like(t) #gets the time and position values for the trajectory for j, detection in enumerate(particle.findall('detection')): t[j] = float(detection.attrib['t']) * time_int x[j] = float(detection.attrib['x']) * px_size y[j] = float(detection.attrib['y']) * px_size if len(t) > 3: #only analyze the tracks if there are at least 3 time points #appends the trajectory data to the trajectory list traj_dict_list.append({'track_id' : i+1, 't' : t, 'x' : x, 'y' : y}) #gets some dynamics parameters for the trajectory and appends to the param list mean_inst_speed = migra.extract_mean_inst_speed(x,y,t) persistence = migra.extract_persistence(x,y) time_lag, msd, (slope, intercept) = migra.extract_msd(x,y,t) param_dict_list.append({'track_id' : i+1, 'mean_inst_speed' : mean_inst_speed, 'persistence' : persistence, 'coeff_persist' : slope}) #extracts the directional correlation print("Getting Directional Correlation from Trajectories") start = time.time() dist_list, corr_list = migra.extract_dir_corr(traj_dict_list) end = time.time() print("Time required:", end - start) #bins the distance and correlation data and saves print("Plotting and Saving Correlation Data") dist_means, corr_means, corr_stds, corr_lens = bin_corr_vs_dist(dist_list,corr_list) data_to_write = list(zip(dist_means,corr_means,corr_stds,corr_lens)) data_to_write.insert(0,['dist_um','corr_mean','corr_std','corr_n']) uf.write_csv(data_to_write, os.path.join(save_dir, basename + '_corr_vs_dist.csv')) #plots the binned data and saves fig, ax = plt.subplots() plot_corr_vs_dist(ax,dist_means,corr_means,corr_stds,'b') plt.tight_layout() plt.savefig(os.path.join(save_dir, basename + '_corr_vs_dist.pdf')) #writes params to file print("Plotting and Saving Dynamics Parameters") key_list = ['track_id','mean_inst_speed','persistence','coeff_persist'] data_to_write = [key_list] for line in param_dict_list: data_to_write.append([line[_] for _ in key_list]) uf.write_csv(data_to_write, os.path.join(save_dir, basename + '_params.csv')) # plots a histogram of the persistence persistence_list = np.array([_['persistence'] for _ in param_dict_list]) fig,ax = plt.subplots() ax.hist(persistence_list,bins=np.linspace(0,1,20)) ax.set_ylabel('Count') ax.set_xlabel('Persistence') plt.tight_layout() plt.savefig(os.path.join(save_dir, basename + '_hist_persistence.pdf')) plt.close() # plots a histogram of the mean inst. speed speed_list = np.array([_['mean_inst_speed'] for _ in param_dict_list]) * 60. #converts to um/hour fig, ax = plt.subplots() ax.hist(speed_list,bins=np.linspace(0,20,20)) ax.set_ylabel('Count') ax.set_xlabel('Mean Inst. Speed ($\mu$m/hr)') plt.tight_layout() plt.savefig(os.path.join(save_dir, basename + '_hist_mean_inst_speed.pdf')) plt.close() #makes a plot of the trajectories print("Plotting Trajectories (this will take a long time if you have >500 trajectories)") im_stk = tifffile.imread(img_file_path) height, width = im_stk[0].shape fig, ax = plt.subplots() cm = plt.get_cmap('hot') # goes through each trajectory for j, traj in enumerate(traj_dict_list): #sets the colors for plotting n = len(traj['x']) colors = [cm(1. * i / (n - 1)) for i in range(n - 1)] ax.set_prop_cycle('color', colors) #plots the trajectory for i in range(n - 1): ax.plot(traj['x'][i:i + 2], traj['y'][i:i + 2]) #finishes the plot ax.set_xlim(0, width * px_size) ax.set_ylim(0, height * px_size) ax.set_xlabel("Distance ($\mu$m)") ax.set_ylabel("Distance ($\mu$m)") plt.tight_layout() plt.savefig(os.path.join(save_dir, basename + '_trajectories.pdf')) plt.close() def main(): """Sets up the analysis for the trajectories from TrackMate. You should update the image path, track file path, time interval and pixel size here. You should not have to change anything in the rest of the script. """ #sets some initial parameters img_file_path = './sample_data/tumor_nuclei_small/tumor_nuclei_small.tif' track_file_path = './sample_data/tumor_nuclei_small/tumor_nuclei_small_stardist_Tracks.xml' time_int = 30 #min px_size = 0.91 #um/px analyze_trackmate_file(img_file_path, track_file_path, time_int, px_size) if __name__ == "__main__": main()

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8,970

4.221653

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0.016635

0.020274

0.018194

0.316929

0.280541

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0.163057

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0

0.010115

0.217503

8,970

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0

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0.118644

0.059322

0

null

0

null

0

1

0

4fd65dd48fcff0e5a0416234249d0f79a329e39e

1,575

py

Python

libfennel/randutil.py

hyraxZK/fennel

0aeae644455057547a48422fd9a19d4564d1348f

[ "Apache-2.0" ]

3

2018-04-04T16:26:55.000Z

2021-02-27T03:08:08.000Z

libfennel/randutil.py

hyraxZK/fennel

0aeae644455057547a48422fd9a19d4564d1348f

[ "Apache-2.0" ]

1

2019-08-02T09:47:43.000Z

libfennel/randutil.py

hyraxZK/fennel

0aeae644455057547a48422fd9a19d4564d1348f

[ "Apache-2.0" ]

3

2018-10-30T09:40:10.000Z

2020-01-16T07:48:48.000Z

#!/usr/bin/python # # (C) 2017 Riad S. Wahby <rsw@cs.stanford.edu> # # rand gen utilities (split from util to break circular dep) import random from libfennel.defs import Defs import libfennel.gateprover as gp import libfennel.util as util def rand_ckt(nOutBits, nInBits): in0v = [] in1v = [] typv = [] choices = ( gp.MulGateProver , gp.AddGateProver , gp.SubGateProver , gp.OrGateProver , gp.XorGateProver , gp.NotGateProver , gp.NandGateProver , gp.NorGateProver , gp.NxorGateProver , gp.NaabGateProver ) for _ in xrange(0, 2**nOutBits): in0v.append(random.randint(0, 2**nInBits - 1)) in1v.append(random.randint(0, 2**nInBits - 1)) # XXX test muxes!!! typv.append(random.choice(choices)) return (in0v, in1v, typv) def rand_inputs(nInBits, nCopies, inLay=None): out = [] if inLay is None: inLay = [None] * (2 ** nInBits) else: nInBits = util.clog2(len(inLay)) inLay += [0] * (2 ** nInBits - len(inLay)) for _ in xrange(0, nCopies): out.append([ Defs.gen_random() if elm is None else elm % Defs.prime for elm in inLay ]) return out def rand_str(slen): ostr = "" for _ in xrange(0, slen): cval = random.randint(0, 61) if cval < 26: ostr += chr(cval + 65) elif cval < 52: ostr += chr(cval + 71) else: ostr += str(cval - 52) return ostr

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0.038417

0.041909

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0

0.035272

0.333968

1,575

64

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false

0

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0.222222

0

null

0

null

0

1

0

4fd7ccdd03065688e02ce09c4b9b0a91f1bcbd70

3,122

py

Python

app.py

clcert/bg-mixnet

1f572e639ed30e4ba8ef850ac2d922f53a6c7447

[ "Apache-2.0" ]

null

app.py

clcert/bg-mixnet

1f572e639ed30e4ba8ef850ac2d922f53a6c7447

[ "Apache-2.0" ]

1

2022-01-21T00:44:07.000Z

app.py

clcert/bg-mixnet

1f572e639ed30e4ba8ef850ac2d922f53a6c7447

[ "Apache-2.0" ]

1

2022-01-21T00:40:36.000Z

from flask import ( flash, Flask, redirect, render_template, request, send_file, url_for ) from os import makedirs from os.path import ( exists, join as p_join, realpath, split as p_split ) from werkzeug.utils import secure_filename from zipfile import ZipFile from main import ( mix as f_mix, verify as f_verify ) UPLOAD_FOLDER = p_join(p_split(realpath(__file__))[0], "data") ALLOWED_EXTENSIONS = {"json", "txt"} app = Flask(__name__) app.config["UPLOAD_FOLDER"] = UPLOAD_FOLDER app.secret_key = b"example" def check_upfolder(): if not exists(UPLOAD_FOLDER): makedirs(UPLOAD_FOLDER) def allowed_file(filename): return "." in filename and filename.rsplit(".", 1)[1].lower() in ALLOWED_EXTENSIONS def validate_files(file_dict): ret = True for key in file_dict.keys(): if file_dict[key] and allowed_file(file_dict[key].filename): continue ret = False return ret @app.route("/") def index(): return "Try /mix or /verify" @app.route("/mix", methods=("GET", "POST")) def mix(): if request.method == "POST": check_upfolder() m = int(request.form["m"]) n = int(request.form["n"]) election_file = request.files["election_file"] if election_file and allowed_file(election_file.filename): filename = secure_filename(election_file.filename) path = p_join(app.config["UPLOAD_FOLDER"], filename) election_file.save(path) outs = ["ciphers.json", "public_randoms.txt", "proof.txt"] for out in outs: out = p_join(app.config["UPLOAD_FOLDER"], out) f_mix(m, n, outs[0], outs[1], outs[2], path) res_path = p_join(app.config["UPLOAD_FOLDER"], "response.zip") zipObj = ZipFile(res_path, "w") for out in outs: zipObj.write(out) zipObj.close() return send_file(res_path, mimetype="application/zip") return render_template("mix.html") #TODO: debug verification @app.route("/verify", methods=("GET", "POST")) def verify(): if request.method == "POST": check_upfolder() m = int(request.form["m"]) n = int(request.form["n"]) files = {} files["ciphers"] = request.files["ciphers_file"] files["publics"] = request.files["publics_file"] files["proof"] = request.files["proof_file"] if validate_files(files): paths = {} for key in files.keys(): filename = secure_filename(files[key].filename) paths[key] = p_join(app.config["UPLOAD_FOLDER"], filename) files[key].save(paths[key]) data = { "valid": f_verify(m, n, paths["ciphers"], paths["publics"], paths["proof"]), "show": True } return render_template("verify.html", data=data) data = {"valid": False, "show": False} return render_template("verify.html", data=data) if __name__ == "__main__": app.run(host="127.0.0.1", port=8080, debug=True)

30.019231

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4.577608

0.272265

0.060033

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0.184547

0.170095

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0

0.006935

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3,122

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0.007687

0

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0

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0

0.009615

0

1

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false

0

0.067416

0.022472

0.213483

0

null

0

null

0

1

0

4fd91e584b61e5bb1129513cbabbd75da3205ba8

1,846

py

Python

lambda_function.py

prodipta/S3_read_and_save

202878bb992b2b2318b29e402415b724c0980cc0

[ "Apache-2.0" ]

null

lambda_function.py

prodipta/S3_read_and_save

202878bb992b2b2318b29e402415b724c0980cc0

[ "Apache-2.0" ]

null

lambda_function.py

prodipta/S3_read_and_save

202878bb992b2b2318b29e402415b724c0980cc0

[ "Apache-2.0" ]

null

import email import boto3 s3 = boto3.client('s3') s3r = boto3.resource('s3') temp_dir = "/tmp/" output_prefix = "output/" def lambda_handler(event, context): bucket = event['Records'][0]['s3']['bucket']['name'] key = event['Records'][0]['s3']['object']['key'] # ignore if it is not in mail directory, avoid recursive calls if "mail/" not in key: print("not an incoming mail") return None try: waiter = s3.get_waiter('object_exists') waiter.wait(Bucket=bucket, Key=key) obj = s3r.Bucket(bucket).Object(key) msg = email.message_from_bytes(obj.get()["Body"].read()) # quit if there is no attachments attachments = msg.get_payload() if len(attachments) < 2: print("we've got no attachment") return None # delete the first item, it will be the mail itself del attachments[0] # run over each attachments for attachment in attachments: # get the file name content_type = attachment.get('Content-Disposition') file_name = content_type.split("=")[1].replace('\"', '') print("attachment is {}".format(file_name)) # download to temp dir with the same filename with open(temp_dir + file_name, 'wb') as writefile: writefile.write(attachment.get_payload(decode=True)) # now upload to the right prefix + mail with open(temp_dir + file_name, 'rb')as data: s3.upload_fileobj(data, bucket, output_prefix+file_name) except Exception as e: # something went wrong - probably permissioning print(e) # we are done here return { 'bucket' : bucket, 'key': key }

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4.627803

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0.025194

0.02907

0.044574

0

0.013492

0.317443

1,846

57

73

32.385965

0.805556

0.179307

0

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0.027778

false

0

0.055556

0

0.166667

0.111111

0

null

0

null

0

1

0

4fd948c0ac2fd79b966285fa2f3b307c08cff2b5

3,827

py

Python

contrib/cli/great_expectations_contrib/commands.py

denimalpaca/great_expectations

0f28f3c2b3cc6fae3bc5d257c6d4d13dbcf37df0

[ "Apache-2.0" ]

1

2021-04-11T20:54:23.000Z

contrib/cli/great_expectations_contrib/commands.py

denimalpaca/great_expectations

0f28f3c2b3cc6fae3bc5d257c6d4d13dbcf37df0

[ "Apache-2.0" ]

53

2021-10-02T02:26:51.000Z

2021-12-28T20:49:25.000Z

contrib/cli/great_expectations_contrib/commands.py

denimalpaca/great_expectations

0f28f3c2b3cc6fae3bc5d257c6d4d13dbcf37df0

[ "Apache-2.0" ]

1

2021-11-29T07:37:28.000Z

import os import subprocess import sys from collections import namedtuple import click from cookiecutter.main import cookiecutter Command = namedtuple("Command", ["name", "full_command", "error_message"]) def init_cmd(url: str) -> None: """ Initializes a contributor package by pulling down the Cookiecutter template and hydrating it. """ echo("Configure your template:\n", "blue", bold=True) cookiecutter(url, overwrite_if_exists=False) echo("\nSuccessfully set up contrib package!", "green", bold=True) def check_cmd() -> None: """ Performs a series of checks on a contributor package. These include code style, testing, docstrings, and more. """ perform_check(suppress_output=False) def publish_cmd() -> None: """ Performs same checks as `check_cmd`; if they pass, the user is prompted to supply PyPi credentials. Valid inputs will result in an uploaded package. """ success = perform_check(suppress_output=True) if not success: echo( "Please run the `check` command to diagnose before publishing", "red", bold=True, ) return echo("All checks have succeeded; you are ready to publish!", "green", bold=True) publish_to_pypi() def perform_check(suppress_output: bool) -> bool: commands = [ Command( "black", "black --check .", "Please ensure that your files are linted properly with `black .`", ), Command( "isort", "isort --profile black --check .", "Please ensure that your imports are sorted properly with `isort --profile black .`", ), Command( "pytest", "pytest .", "Please ensure that you've written tests and that they all pass", ), Command( "mypy", "mypy --ignore-missing-imports --disallow-untyped-defs --show-error-codes --exclude venv .", "Please ensure that all functions are type hinted", ), ] successes = 0 for command in commands: if run_command(command, suppress_output=suppress_output): successes += 1 is_successful = successes == len(commands) color = "green" if is_successful else "red" echo( f"Summary: [{successes}/{len(commands)}] checks have passed!", color, bold=True ) return is_successful def publish_to_pypi() -> None: commands = [ Command( "wheel", "python setup.py sdist bdist_wheel", "Something went wrong when creating a wheel", ), Command( "twine", "twine upload --repository testpypi dist/*", "Something went wrong when uploading with twine", ), ] for command in commands: if not run_command(command): return echo( "Successfully uploaded package to PyPi! Congratulations on a job well done :)", "green", bold=True, ) def run_command(command: Command, suppress_output: bool = False) -> bool: # If suppressed, set STDOUT to dev/null stdout = sys.stdout if suppress_output: sys.stdout = open(os.devnull, "w") name, full_command, err = command echo(f"{name}:", "blue", bold=True) result = subprocess.run( full_command.split(" "), shell=False, stdout=sys.stdout, stderr=sys.stdout ) success = result.returncode == 0 if success: echo("[SUCCEEDED]\n", "green") else: echo(f"[FAILED] {err}\n", "red") # If reassigned before, set STDOUT back to its default value sys.stdout = stdout return success def echo(msg: str, color: str, bold: bool = False) -> None: click.echo(click.style(msg, fg=color, bold=bold))

27.934307

104

0.605435

446

3,827

5.125561

0.408072

0.024497

0.027997

0.034121

0.045494

0.026247

0

0.0011

0.28717

3,827

136

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28.139706

0.836877

0.117847

0

0.239583

0

0.010417

0.306602

0.022912

0

1

0.072917

false

0.020833

0.083333

0

0.197917

0

null

0

null

0

1

0

4fdc6a8b68b5812b4517e515328c39c7aeb1166e

914

py

Python

lib/eventio/sync.py

bboser/eventio

cdad47772d94e87a8ca8927e8d578fc7aba78266

[ "MIT" ]

6

2018-12-04T02:53:20.000Z

2020-03-08T15:42:16.000Z

lib/eventio/sync.py

bboser/eventio

cdad47772d94e87a8ca8927e8d578fc7aba78266

[ "MIT" ]

null

lib/eventio/sync.py

bboser/eventio

cdad47772d94e87a8ca8927e8d578fc7aba78266

[ "MIT" ]

null

import digitalio from .kernel import _get_kernel from .traps import _scheduler_wait, _scheduler_wake class Event: def __init__(self): self._set = False self._waitq = None def is_set(self): return self._set def clear(self): self._set = False async def wait(self): if self._set: return if not self._waitq: self._waitq = [] await _scheduler_wait(self._waitq) async def set(self): self._set = True await _scheduler_wake(self._waitq) class PinEvent(Event): def __init__(self, pin, pull=None): super().__init__() self.pin = digitalio.DigitalInOut(pin) self.pin.switch_to_input(pull=pull) self.pin.irq(handler=self._cb) def _cb(self, v): # interrupt callback, knows nothing about kernel if self._waitq: _get_kernel()._schedule(self._waitq)

23.435897

56

0.623632

116

914

4.551724

0.37931

0.119318

0.0625

0.060606

0

0.282276

914

39

57

23.435897

0.804878

0.050328

0

0.071429

0

1

0.178571

false

0

0.107143

0.035714

0.392857

0

null

0

null

0

1

0

4fe10e233e5bbd8bd614cfb551d5ab1080a6b260

1,741

py

Python

make_download.py

niall-twomey/har_datasets

68f142ba613ce26f67cdd6b871117f4c24ea603f

[ "MIT" ]

24

2018-12-12T08:54:52.000Z

2021-12-07T08:45:13.000Z

make_download.py

niall-twomey/har_datasets

68f142ba613ce26f67cdd6b871117f4c24ea603f

[ "MIT" ]

3

2019-07-18T20:14:41.000Z

2022-03-12T01:03:28.000Z

make_download.py

niall-twomey/har_datasets

68f142ba613ce26f67cdd6b871117f4c24ea603f

[ "MIT" ]

9

2018-12-12T16:18:39.000Z

2022-03-30T16:25:47.000Z

import zipfile from os import makedirs from os.path import basename from os.path import exists from os.path import join from os.path import split from os.path import splitext import requests from loguru import logger from tqdm import tqdm from src.meta import DatasetMeta from src.utils.loaders import iter_dataset_paths def unzip_data(zip_path, in_name, out_name): if exists(join(zip_path, out_name)): return with zipfile.ZipFile(join(zip_path, in_name), "r") as fil: fil.extractall(zip_path) def download_and_save(url, path, force=False, chunk_size=2 ** 12): response = requests.get(url, stream=True) fname = join(path, split(url)[1]) desc = f"Downloading {fname}..." if exists(fname): if not force: return chunks = tqdm(response.iter_content(chunk_size=chunk_size), desc=basename(desc)) with open(fname, "wb") as fil: for chunk in chunks: fil.write(chunk) def download_dataset(dataset_meta_path): dataset = DatasetMeta(dataset_meta_path) if not exists(dataset.zip_path): makedirs(dataset.zip_path) for ii, url in enumerate(dataset.meta["download_urls"]): logger.info("\t{}/{} {}".format(ii + 1, len(dataset.meta["download_urls"]), url)) download_and_save(url=url, path=dataset.zip_path) zip_name = basename(dataset.meta["download_urls"][0]) unzip_path = join(dataset.zip_path, splitext(zip_name)[0]) unzip_data(zip_path=dataset.zip_path, in_name=zip_name, out_name=unzip_path) def main(): for dataset_meta_path in iter_dataset_paths(): logger.info(f"Downloading {dataset_meta_path}") download_dataset(dataset_meta_path) if __name__ == "__main__": main()

30.54386

89

0.701321

256

1,741

4.542969

0.28125

0.060189

0.042992

0.068788

0.051591

0

0.004954

0.188397

1,741

56

90

31.089286

0.818117

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0.045455

0

0.064905

0

1

0.090909

false

0

0.272727

0

0.409091

0

null

0

null

0

1

0

4fe15f1925208e13bb0c4c6b632376f12695329d

3,533

py

Python

djangofy/djangofy.py

etpinard/djangofy

9ad1437255df66b1a8e7d5f684e56c3414f47bf5

[ "MIT" ]

1

2020-08-24T21:23:06.000Z

djangofy/djangofy.py

etpinard/djangofy

9ad1437255df66b1a8e7d5f684e56c3414f47bf5

[ "MIT" ]

null

djangofy/djangofy.py

etpinard/djangofy

9ad1437255df66b1a8e7d5f684e56c3414f47bf5

[ "MIT" ]

null

""" djangofy ========= """ TAB = " " # a tab in spaces # ------------------------------------------------------------------------------- def _make_urls(group, path_to_output_file, group_name='group', app_name='app', template_name='template'): """ group [list]: """ # out = ( "from django.conf.urls import patterns, url\n\n" "import {app_name}.views\n\n\n" "urlpatterns = patterns(\n" "{TAB}'',\n" ).format(TAB=TAB, app_name=app_name) # for page in group: item = ( 'r(?P<{group_name})/{page}$>' ).format(group_name=group_name, page=page) out += ( '{TAB}url("' + item + '",\n' '{TAB}{TAB}{app_name}' '.views.{template_name})' ).format(TAB=TAB, app_name=app_name, template_name=template_name) if page != group[-1]: out += ",\n" out += "\n)\n" with open(path_to_output_file, 'wb') as f: f.write(out) def make_urls(names, relative_urls, path_to_output_file, app_name='app', class_name='Page'): # out = ( "from django.conf.urls import patterns, url\n\n" "from {app_name}.views import {class_name}\n\n\n" "urlpatterns = patterns(\n" "{TAB}'',\n" ).format(TAB=TAB, app_name=app_name, class_name=class_name) # for name, url in zip(names, relative_urls): item = r'{url}/$'.format(url=url) out += ( '{TAB}url("' + item + '",\n' '{TAB}{TAB}{class_name}.as_view(\n' '{TAB}{TAB}{TAB}lang=\'ipython-notebooks\',\n' '{TAB}{TAB}{TAB}notebook=\'{name}\'),\n' '{TAB}{TAB}name=\'ipython-notebook-{name}\')' ).format(TAB=TAB, class_name=class_name, name=name) if name != names[-1]: out += ",\n" out += "\n)\n" with open(path_to_output_file, 'wb') as f: f.write(out) def make_sitemaps(names, relative_urls, path_to_output_file, app_name='app', template_name='template'): """ """ out = ( "import os\n\n" "from django.conf import settings\n\n\n" "def items():\n" "{TAB}items = [\n" ).format(TAB=TAB) for name, url in zip(names, relative_urls): location = "'/ipython-notebooks/{url}'".format(url=url) lmfile = ( "os.path.join(\n{TAB}{TAB}{TAB}{TAB}" "settings.TOP_DIR,\n{TAB}{TAB}{TAB}{TAB}" "'shelly',\n{TAB}{TAB}{TAB}{TAB}" "'templates',\n{TAB}{TAB}{TAB}{TAB}" "'api_docs',\n{TAB}{TAB}{TAB}{TAB}" "'includes',\n{TAB}{TAB}{TAB}{TAB}" "'ipython_notebooks',\n{TAB}{TAB}{TAB}{TAB}" "'{name}',\n{TAB}{TAB}{TAB}{TAB}" "'body.html')" ).format(url=url, name=name, TAB=TAB) out += ( "{TAB}{TAB}dict(\n" "{TAB}{TAB}{TAB}location={location},\n" "{TAB}{TAB}{TAB}lmfile={lmfile},\n" "{TAB}{TAB}{TAB}priority=0.5\n" "{TAB}{TAB})" ).format(location=location, lmfile=lmfile, TAB=TAB) if name != names[-1]: out += ",\n" out += ( "\n{TAB}]" "\n{TAB}return items" "\n" ).format(TAB=TAB) with open(path_to_output_file, 'wb') as f: f.write(out) def make_redirects(): # TODO return

25.977941

81

0.46844

426

3,533

3.746479

0.171362

0.176692

0.118421

0.081454

0.513784

0.432331

0.368421

0.327068

0.267544

0

0.00208

0.319558

3,533

135

82

26.17037

0.661814

0.040192

0

0.434783

0

0.316637

0.165176

0

0.007407

0

1

0.043478

false

0

0.065217

0.01087

0.119565

0

null

0

null

0

1

0

4fe1cb63130b1fc64ca46b9fc8d4c160a04bdb49

1,394

py

Python

Guitar Training Remote/practice/tritone_sub.py

keremkoseoglu/Python-Library

f66ab246da4eabea94596494cf2bc9b416b65b1d

[ "MIT" ]

3

2018-06-28T07:09:04.000Z

2019-03-04T14:43:52.000Z

Guitar Training Remote/practice/tritone_sub.py

keremkoseoglu/Python-Library

f66ab246da4eabea94596494cf2bc9b416b65b1d

[ "MIT" ]

null

Guitar Training Remote/practice/tritone_sub.py

keremkoseoglu/Python-Library

f66ab246da4eabea94596494cf2bc9b416b65b1d

[ "MIT" ]

5

2018-06-28T07:12:28.000Z

2021-06-03T18:20:21.000Z

from model import exercise, exercise_step from music_theory import chord from practice import abstract_practice import random class TritoneSub(abstract_practice.AbstractPractice): _SUBTITLE = "Do chords, walking bass and improv" _APPROACHES = [ "Tritone Sub - Mixo", "Tritone Sub - Jazz min" ] def get_exercise(self, quantity: int) -> exercise.Exercise: random_steps = [] for i in range(quantity): # Get chords number_of_chords = random.randint(1, 3) chords = chord.Chord().get_random_chords(number_of_chords) # Build chord text chord_txt = "" sub_txt = "" for ch in chords: if chord_txt == "": chord_txt = ch else: if sub_txt == "": sub_txt = "followed by: " else: sub_txt += " | " sub_txt += ch # Add to steps random_step = exercise_step.ExerciseStep(chord_txt, sub_txt) random_steps.append(random_step) output = exercise.Exercise(self._get_random_approach(), self._SUBTITLE, random_steps) return output def _get_random_approach(self) -> str: i = random.randint(0, len(self._APPROACHES) - 1) return self._APPROACHES[i]

30.304348

93

0.558106

150

1,394

4.933333

0.4

0.048649

0.054054

0

0.004484

0.360115

1,394

46

94

30.304348

0.825112

0.028694

0

0.060606

0

0.066617

0

1

0.060606

false

0

0.121212

0

0.333333

0

null

0

null

0

1

0

4fe3e277cb0aaebb11dd380d6970774d9b923543

1,477

py

Python

setup.py

prasannaba/COVID-19_Analysis_Library

d7788f0f6e188a6e766053a1751adbf36b4612fe

[ "MIT" ]

null

setup.py

prasannaba/COVID-19_Analysis_Library

d7788f0f6e188a6e766053a1751adbf36b4612fe

[ "MIT" ]

null

setup.py

prasannaba/COVID-19_Analysis_Library

d7788f0f6e188a6e766053a1751adbf36b4612fe

[ "MIT" ]

null

from setuptools import setup from COVID19analysis import __version__ with open('Readme.md', 'r') as f: readme = f.read() setup( name='COVID19analysis', version=__version__, packages=['COVID19analysis'], url='https://github.com/prasannaba/COVID-19_Analysis_Library', license='MIT', author='Prasanna', python_requires='>=3.7', install_requires=['bokeh>=2.3.3', 'panel>=0.11.3', 'pandas<=1.2.5', 'holoviews>=1.14.4', 'hvplot>=0.7.2', 'tqdm>=4.61.2'], author_email='prasanna.badami@hotmail.com', description='COVID19Analysis based on CSSEGISandData on GitHub', long_description=readme, long_description_content_type='text/markdown', classifiers=[ 'Development Status :: 5 - Production/Stable', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', 'Topic :: Scientific/Engineering', 'Topic :: Scientific/Engineering :: Mathematics', 'Topic :: Scientific/Engineering :: Visualization', 'Topic :: Software Development :: Libraries', 'Topic :: Software Development :: Libraries :: Python Modules', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', 'Intended Audience :: Information Technology', 'Intended Audience :: Financial and Insurance Industry' ], )

38.868421

92

0.641165

152

1,477

6.118421

0.585526

0.068817

0.080645

0.055914

0

0.032759

0.214624

1,477

37

93

39.918919

0.768966

0

0.579553

0.062965

0

1

0

false

0

0.057143

0

0.057143

0

null

0

null

0

1

0

4fe6ecf0ab0d93bd5e942e8e08086260bfb163e3

3,215

py

Python

tests/beam_benchmark_helper_test.py

bltb/PerfKitBenchmarker

903eb82d4e7ee5ed2ac2953cf6ce1b80459497ed

[ "Apache-2.0" ]

null

tests/beam_benchmark_helper_test.py

bltb/PerfKitBenchmarker

903eb82d4e7ee5ed2ac2953cf6ce1b80459497ed

[ "Apache-2.0" ]

null

tests/beam_benchmark_helper_test.py

bltb/PerfKitBenchmarker

903eb82d4e7ee5ed2ac2953cf6ce1b80459497ed

[ "Apache-2.0" ]

null

# Copyright 2014 PerfKitBenchmarker Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for beam_benchmark_helper.""" import unittest from perfkitbenchmarker import beam_benchmark_helper from perfkitbenchmarker import dpb_service class BeamBenchmarkHelperTestCase(unittest.TestCase): def test_runner_option_override_non_dataflow(self): # This is documenting the current behavior - when we add an EMR # service_type, this test should change. actual_options = [] beam_benchmark_helper.AddRunnerOptionMvnArgument( dpb_service.EMR, actual_options, None) self.assertListEqual([], actual_options) def test_runner_option_override_dataflow(self): actual_options = [] beam_benchmark_helper.AddRunnerOptionMvnArgument( dpb_service.DATAFLOW, actual_options, None) self.assertListEqual(['"--runner=TestDataflowRunner"'], actual_options) def test_runner_option_override_use_override(self): testOptionVal = "--runner=TestVal" actual_options = [] beam_benchmark_helper.AddRunnerOptionMvnArgument( dpb_service.DATAFLOW, actual_options, testOptionVal) self.assertListEqual([testOptionVal], actual_options) def test_runner_option_override_empty_override(self): testOptionVal = "" actual_options = [] beam_benchmark_helper.AddRunnerOptionMvnArgument( dpb_service.DATAFLOW, actual_options, testOptionVal) self.assertListEqual([], actual_options) def test_runner_profile_override_dataflow(self): actual_mvn_command = [] beam_benchmark_helper.AddRunnerProfileMvnArgument( dpb_service.DATAFLOW, actual_mvn_command, None) self.assertListEqual(['-Pdataflow-runner'], actual_mvn_command) def test_runner_profile_override_non_dataflow(self): # This is documenting the current behavior - when we add an EMR # service_type, this test should change. actual_mvn_command = [] beam_benchmark_helper.AddRunnerProfileMvnArgument( dpb_service.EMR, actual_mvn_command, None) self.assertListEqual([], actual_mvn_command) def test_runner_profile_override_use_override(self): testOptionVal = "testval" actual_mvn_command = [] beam_benchmark_helper.AddRunnerProfileMvnArgument( dpb_service.DATAFLOW, actual_mvn_command, testOptionVal) self.assertListEqual(['-P' + testOptionVal], actual_mvn_command) def test_runner_profile_override_empty_override(self): testOptionVal = "" actual_mvn_command = [] beam_benchmark_helper.AddRunnerProfileMvnArgument( dpb_service.DATAFLOW, actual_mvn_command, testOptionVal) self.assertListEqual([], actual_mvn_command) if __name__ == '__main__': unittest.main()

35.722222

75

0.772006

370

3,215

6.402703

0.308108

0.065851

0.081047

0.060785

0.669481

0.607851

0.556353

0.486703

0.408189

0.380329

0

0.002937

0.152722

3,215

89

76

36.123596

0.86674

0.254743

0

0.52

0

0.033277

0.012216

0

0.16

1

0.16

false

0

0.06

0

0.24

0

null

0

null

0

1

0

4fe9bd05ea772e2f1770e833100ea91c824dc3bf

719

py

Python

kartta.py

UrsaOK/supertassu

c9158f50281000f57fe14aba4115aa867a72e0ca

[ "BSD-2-Clause" ]

null

kartta.py

UrsaOK/supertassu

c9158f50281000f57fe14aba4115aa867a72e0ca

[ "BSD-2-Clause" ]

2

2015-01-18T14:51:32.000Z

2016-02-24T20:15:12.000Z

kartta.py

UrsaOK/supertassu

c9158f50281000f57fe14aba4115aa867a72e0ca

[ "BSD-2-Clause" ]

null

from merkki import Merkki class Ruutu: def __init__(self, merkki, tyhja): print("ruutu init") self.merkki = Merkki(merkki) self.tyhja = tyhja OVI = Ruutu(".", True) TYHJA = Ruutu(" ", True) SEINA = Ruutu("#", False) SUPERSEINA = Ruutu("?", False) class Kartta(list): def __init__(self): print("kartta init") super(Kartta, self).__init__() self.leveys = 80 self.korkeus = 50 for x in range(self.leveys): self.append([TYHJA] * self.korkeus) def draw(self, mihin): print("kartta draw") for x in range(self.leveys): for y in range(self.korkeus): self[x][y].merkki.draw(mihin, x, y)

23.966667

51

0.564673

90

719

4.377778

0.333333

0.081218

0.083756

0.055838

0.106599

0

0.007905

0.296245

719

29

52

24.793103

0.770751

0

0.086957

0

0.050139

0

1

0.130435

false

0

0.043478

0

0.26087

0.130435

0

null

0

null

0

1

0

4feb3f10714033df750e63992a556639520521e8

10,753

py

Python

cloudmesh_web/modules/rack.py

JulienPalard/cloudmesh

1759b88daef3a13917492d028fdabe08f03ca996

[ "Apache-2.0" ]

null

cloudmesh_web/modules/rack.py

JulienPalard/cloudmesh

1759b88daef3a13917492d028fdabe08f03ca996

[ "Apache-2.0" ]

4

2021-06-08T20:20:08.000Z

2022-03-11T23:30:22.000Z

cloudmesh_web/modules/rack.py

JulienPalard/cloudmesh

1759b88daef3a13917492d028fdabe08f03ca996

[ "Apache-2.0" ]

null

from cloudmesh_base.locations import config_file from cloudmesh.config.cm_config import cm_config, cm_config_server from cloudmesh.rack.cluster_map_heat import HeatClusterMap from cloudmesh.rack.cluster_map_service import ServiceClusterMap from cloudmesh.rack.fetch_cluster_info import FetchClusterInfo from flask import Blueprint, g, render_template, request, redirect, url_for from flask.ext.login import login_required # @UnresolvedImport from flask.ext.wtf import Form # @UnresolvedImport from pprint import pprint from sh import pwd # @UnresolvedImport from wtforms import SelectField from flask.ext.principal import Permission, RoleNeed import time from cloudmesh.rack.rack_progress import get_temperature_progress, get_service_progress import json import sys from cloudmesh_base.logger import LOGGER log = LOGGER(__file__) rack_module = Blueprint('rack_module', __name__) admin_permission = Permission(RoleNeed('admin')) # # ROUTE: rack # class RackForm(Form): # MUST create an unique selector for each different service service_rack = SelectField() temperature_rack = SelectField() all_racks_dict = { "all": ('all', 'All Clusters'), "india": ('india', 'India Cluster'), "echo": ('echo', 'Echo Cluster'), "delta": ('delta', 'Delta Cluster'), "bravo": ('bravo', 'Bravo Cluster'), } # all possible service provided all_services_list = ["service", "temperature", ] # content of each service, including label, and range of clusters # 'clusters' means the specific service can be used on some different clusters # 'select' means one attribute name of SelectField, typical name is "{service name}_rack" all_services_dict = { "service": { "label": "Service Map", "clusters": ["all", "india", "echo", "delta", "bravo", ], "select": "service_rack", }, "temperature": { "label": 'Heat Map', "clusters": ["echo", ], "select": "temperature_rack", }, } # a dict that holds all selector selector_dict = {} def initForm(self): for service in self.all_services_list: service_dict = {} service_dict["name"] = service service_dict["label"] = self.all_services_dict[service]["label"] service_dict["select"] = getattr( self, self.all_services_dict[service]["select"]) rack_list = [] for rack in self.all_services_dict[service]["clusters"]: rack_list.append(self.all_racks_dict[rack]) service_dict["select"].choices = rack_list self.selector_dict[service] = service_dict def validate_on_submit(self): return True @rack_module.route('/inventory/rack') @login_required def display_rack_home(): rack_form = RackForm() if rack_form.validate_on_submit(): rack_form.initForm() return render_template("mesh/rack/rack.html", form=rack_form, flag_home=True) @rack_module.route('/inventory/rack/mapcontainer', methods=['POST']) @login_required def display_rack_map_container(): # rack denote the rack that user selected # service denote the service user selected on the specific rack rack = request.form['select_rack'] service = request.form['select_service'] # double check to make sure rack can provide the specific service rack_form = RackForm() if rack not in rack_form.all_services_dict[service]["clusters"]: log.error("Someone try to hack the service [service: '{0}' on rack: '{1}'] provided by Rack Diagram. Just ignore it.".format( service, rack)) return redirect("/inventory/rack") return render_template( "mesh/rack/map_container.html", rack=rack, service=service, ) @rack_module.route('/inventory/rack/genmap', methods=['GET', 'POST']) @login_required def gen_rack_map(): service = request.args.get("service") rack = request.args.get("rack") # double check to make sure rack can provide the specific service rack_form = RackForm() if rack not in rack_form.all_services_dict[service]["clusters"]: log.error("Someone try to hack the service [service: '{0}' on rack: '{1}'] provided by Rack Diagram. Just ignore it.".format( service, rack)) return redirect("/inventory/rack") myfetch = FetchClusterInfo(g.user.id) map_progress = myfetch.get_map_progress(service) map_progress.set_load_map() map_progress.set_send_http_request() result = {"result": "failure", "reason": { "status": "failure", "text": "Read DB Error"}} if myfetch.start_gen_map(service, rack): result["result"] = "success" return json.dumps(result) @rack_module.route('/inventory/rack/refreshmap', methods=['GET', 'POST']) @login_required def refresh_rack_map(): service = request.args.get("service") rack = request.args.get("rack") # double check to make sure rack can provide the specific service rack_form = RackForm() if rack not in rack_form.all_services_dict[service]["clusters"]: log.error("Someone try to hack the service [service: '{0}' on rack: '{1}'] provided by Rack Diagram. Just ignore it.".format( service, rack)) return redirect("/inventory/rack") myfetch = FetchClusterInfo(g.user.id) map_progress = myfetch.get_map_progress(service) map_progress.set_refresh_map() map_progress.set_send_http_request() result = {"result": "failure", "reason": { "status": "failure", "text": "Read DB Error"}} result_dict = myfetch.start_refresh_map(service, rack) if result_dict["result"]: result["result"] = "success" elif result_dict["fresh"]: result["reason"]["status"] = "success" result["reason"]["text"] = "Data is already newest" return json.dumps(result) @rack_module.route('/inventory/rack/mapprogress', methods=['GET', 'POST']) @login_required def rack_map_progress_status(): service = request.args.get("service") result = {"text": "", "value": 0, "next": ""} myfetch = FetchClusterInfo(g.user.id) map_progress = myfetch.get_map_progress(service) if map_progress: result = map_progress.get_status() # log.debug("progress status: {0}".format(result)) if result["next"] == "loading map": result["data"] = map_progress.get_data("map_data") return json.dumps(result) @rack_module.route('/inventory/rack/map', methods=['POST']) @login_required def display_rack_map(): #### # # Flag of debug, True means generate fake data with random generator # False means fetch the real data from server #### flag_debug = False # class name means the specific class to generate map for different service type # method name means the specific method to fetch real data of different service type, # the methods are defined in class FetchClusterInfo service_options = { "temperature": { "class": HeatClusterMap, "method": "fetch_temperature_ipmi", }, "service": { "class": ServiceClusterMap, "method": "fetch_service_type", }, } # rack denote the rack user selected # service denote the service user selected on the specific rack rack = request.form['select_rack'] service = request.form['select_service'] # double check to make sure rack can provide the specific service rack_form = RackForm() if rack not in rack_form.all_services_dict[service]["clusters"]: log.error("Someone try to hack the service [service: '{0}' on rack: '{1}'] provided by Rack Diagram. Just ignore it.".format( service, rack)) return redirect("/inventory/rack") # get location of configuration file, input diag, output image dir_base = config_file("") server_config = cm_config_server() relative_dir_diag = server_config.get("cloudmesh.server.rack.input") relative_dir_image = server_config.get( "cloudmesh.server.rack.diagrams.{0}".format(service)) # log.debug("relative dir image, {0}".format(relative_dir_image)) flask_dir = "static" # guess absolute path of cloudmesh_web rack_py_dir = pwd().strip().split("/") cloudmesh_web_dir = rack_py_dir # [:-1] # log.debug("cloudmesh_web dir, {0}".format(cloudmesh_web_dir)) list_image_dir = [flask_dir] + relative_dir_image.strip().split("/") abs_dir_image = "/".join(cloudmesh_web_dir + list_image_dir) abs_dir_diag = dir_base + "/" + relative_dir_diag # dynamic generate image map_class = service_options[service]["class"]( rack, dir_base, abs_dir_diag, abs_dir_image) # get cluster server data dict_data = None if flag_debug: dict_data = map_class.genRandomValues() else: # fetch the real data .... # TODO cloudmesh.hpc.proxyserver # should we add a field in cloudmesh.yaml for the proxy server to run # pbsnodes ??? config = cm_config() user = config.get("cloudmesh.hpc.username") myfetch = FetchClusterInfo(user, "india.futuregrid.org") flag_filter = None if rack == "all" else rack # If user want to customize the action, user can set optional param here # by calling map_class.set_optional_param(value) # optional param aparam = map_class.get_optional_param() dict_data = getattr(myfetch, service_options[service]["method"])( flag_filter, aparam) # update data map_class.update(dict_data) # plot map map_class.plot() # get image names filename_image = map_class.getImageFilename() filename_legend = map_class.getLegendFilename() image_size = map_class.getImageSize() legend_size = map_class.getImageLegendSize() # log.debug("legend size is: {0}".format(legend_size)) abs_web_path_image = "/".join([""] + list_image_dir + [filename_image]) abs_web_path_legend = "/".join([""] + list_image_dir + [filename_legend]) img_flag = "?" + str(time.time()) return render_template("mesh/rack/rack.html", flag_home=False, rack=rack, imageWidth=image_size["width"], imageHeight=image_size["height"], legendWidth=legend_size["width"], legendHeight=legend_size["height"], service=service, imageFilename=abs_web_path_image + img_flag, legendFilename=abs_web_path_legend + img_flag )

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0.351084

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0

null

0

null

0

1

0

4feefc3dff38a87a277d1dfa1f890a31090eb36f

738

py

Python

setup.py

xiaoxq/pyspark-utils

705d9f047519881bb07f0bee0db863111508b59b

[ "Apache-2.0" ]

9

2019-04-03T21:31:50.000Z

2021-07-22T06:07:02.000Z

setup.py

xiaoxq/pyspark-utils

705d9f047519881bb07f0bee0db863111508b59b

[ "Apache-2.0" ]

null

setup.py

xiaoxq/pyspark-utils

705d9f047519881bb07f0bee0db863111508b59b

[ "Apache-2.0" ]

1

2019-12-12T12:55:57.000Z

#!/usr/bin/env python """The missing PySpark utils steup file.""" import setuptools with open("README.rst", "r") as fh: long_description = fh.read() setuptools.setup( name="pyspark_utils", version="1.8.0", license="Apache License Version 2.0", author="Xiangquan Xiao", author_email="xiaoxiangquan@gmail.com", description="The missing PySpark utils", long_description=long_description, url="https://github.com/xiaoxq/pyspark-utils", packages=setuptools.find_packages(), classifiers=[ "Programming Language :: Python", "License :: OSI Approved :: Apache Software License", "Operating System :: OS Independent", ], install_requires=[ "absl-py", ], )

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null

0

null

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1

0

4ff0c33b625a3b17c41a51d1fc61857295c864cf

6,467

py

Python

theia/ide/admin/cli/anubis/assignment/pipeline.py

synoet/Anubis

051888a88e37c67e5e772245604c79ceb4db8764

[ "MIT" ]

2

2022-02-24T17:39:27.000Z

2022-02-25T02:14:06.000Z

theia/ide/admin/cli/anubis/assignment/pipeline.py

synoet/Anubis

051888a88e37c67e5e772245604c79ceb4db8764

[ "MIT" ]

null

theia/ide/admin/cli/anubis/assignment/pipeline.py

synoet/Anubis

051888a88e37c67e5e772245604c79ceb4db8764

[ "MIT" ]

null

#!/usr/bin/env python3 import json import logging import os import traceback import git import requests import yaml root_logger = logging.getLogger() root_logger.setLevel(logging.DEBUG) root_logger.addHandler(logging.StreamHandler()) def post(path: str, data: dict, params=None): if params is None: params = {} headers = {'Content-Type': 'application/json'} params['token'] = TOKEN if DEBUG: logging.info("post: {} data: {}".format(path, data)) return None # Attempt to contact the pipeline API try: res = requests.post( 'http://pipeline-api:5000' + path, headers=headers, params=params, json=data, ) except: logging.error('UNABLE TO REPORT POST TO PIPELINE API') exit(0) # If the call to the api failed we're in trouble, # and need to abort. if res.status_code != 200: logging.error('UNABLE TO REPORT POST TO PIPELINE API') exit(0) return res def report_panic(message: str, traceback: str, ): """ Report and error to the API :param message: error message :param traceback: optional traceback :return: """ data = { 'token': TOKEN, 'commit': COMMIT, 'message': message, 'traceback': traceback, } print(traceback) logging.info('report_error {}'.format(json.dumps(data, indent=2))) post('/pipeline/report/panic/{}'.format(SUBMISSION_ID), data) try: import assignment except ImportError: report_panic('Unable to import assignment', traceback.format_exc()) exit(0) from utils import registered_tests, build_function from utils import fix_permissions, Panic, DEBUG git_creds = os.environ.get('GIT_CRED', default=None) if git_creds is not None: del os.environ['GIT_CRED'] with open(os.environ.get('HOME') + '/.git-credentials', 'w') as f: f.write(git_creds) f.close() with open(os.environ.get('HOME') + '/.gitconfig', 'w') as f: f.write('[credential]\n') f.write('\thelper = store\n') f.close() TOKEN = os.environ.get('TOKEN') COMMIT = os.environ.get('COMMIT') GIT_REPO = os.environ.get('GIT_REPO') SUBMISSION_ID = os.environ.get('SUBMISSION_ID') del os.environ['TOKEN'] def report_state(state: str, params=None): """ Report a state update for the current submission :param params: :param state: text representation of state :return: """ data = { 'token': TOKEN, 'commit': COMMIT, 'state': state, } logging.info('report_state {}'.format(json.dumps(data, indent=2))) post('/pipeline/report/state/{}'.format(SUBMISSION_ID), data, params=params) def report_build_results(stdout: str, passed: bool): """ Report the results of a given build. :param stdout: :param passed: :return: """ data = { 'token': TOKEN, 'commit': COMMIT, # 'stdout': base64.b16encode(stdout).decode(), 'stdout': stdout, 'passed': passed, } logging.info('report_build {}'.format(json.dumps(data, indent=2))) post('/pipeline/report/build/{}'.format(SUBMISSION_ID), data) def report_test_results(test_name: str, stdout: str, message: str, passed: bool): """ Report a single test result to the pipeline API. :param test_name: :param stdout: :param message: :param passed: :return: """ data = { 'token': TOKEN, 'commit': COMMIT, 'test_name': test_name, # 'stdout': base64.b16encode(stdout).decode(), 'stdout': stdout, 'message': message, 'passed': passed, } logging.info('report_test_results {}'.format(json.dumps(data, indent=2))) post('/pipeline/report/test/{}'.format(SUBMISSION_ID), data) def get_assignment_data() -> dict: """ Load the assignment metadata out from the assignment yaml file :return: """ # Figure out filename assignment_filename = None for assignment_filename_option in ['meta.yml', 'meta.yaml']: if os.path.isfile(assignment_filename_option): assignment_filename = assignment_filename_option break # Make sure we figured out the metadata filename if assignment_filename is None: report_panic('No meta.yml was found', '') exit(0) # Load yaml with open(assignment_filename, 'r') as f: try: assignment_data = yaml.safe_load(f.read()) except yaml.YAMLError: report_panic('Unable to read assignment yaml', traceback.format_exc()) logging.info(assignment_data) return assignment_data def clone(): """ Clone the assigment repo into the student folder. File permissions will need to be updated. :return: """ report_state('Cloning repo') # Clone try: repo = git.Repo.clone_from(GIT_REPO, './student') if COMMIT.lower() != 'null': repo.git.checkout(COMMIT) except git.exc.GitCommandError: report_panic('Git error', traceback.format_exc()) exit(0) fix_permissions() os.system('rm -rf ./student/.git') os.system('rm -rf /home/anubis/.git-credentials') os.system('rm -rf /home/anubis/.gitconfig') def run_build(assignment_data: dict): """ Build the student repo. :param assignment_data: assignment meta :return: """ # build report_state('Running Build...') result = build_function() report_build_results(result.stdout, result.passed) if not result.passed: exit(0) def run_tests(assignment_data: dict): """ Run the assignment test scripts. Update submission state as you go. :param assignment_data: :return: """ # Tests for test_name in registered_tests: report_state('Running test: {}'.format(test_name)) result = registered_tests[test_name]() report_test_results(test_name, result.stdout, result.message, result.passed) def main(): try: assignment_data = get_assignment_data() clone() os.chdir('./student') run_build(assignment_data) run_tests(assignment_data) report_state('Finished!', params={'processed': '1'}) except Panic as e: report_panic(repr(e), traceback.format_exc()) except Exception as e: report_panic(repr(e), traceback.format_exc()) if __name__ == '__main__': main()

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84

0.626875

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0.171515

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0.109284

0.087528

0.024285

0

0.005531

0.24509

6,467

254

85

25.46063

0.804179

0.167311

0

0.239726

0

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0

1

0.068493

false

0.047945

0.082192

0

0.171233

0.006849

0

null

0

null

0

1

0

4ff20bbd47aa0c170d3217fde2abcab9c8fbd137

2,193

py

Python

eval_image_classifier.py

kurnianggoro/Deep-Mutual-Learning

34a20583debe4e0dab1d9856db69bed278c5c011

[ "MIT" ]

317

2018-03-28T02:11:23.000Z

2022-03-18T08:32:27.000Z

eval_image_classifier.py

SaintLogos1234/Deep-Mutual-Learning

34a20583debe4e0dab1d9856db69bed278c5c011

[ "MIT" ]

19

2018-04-11T02:48:29.000Z

2021-07-09T11:03:19.000Z

eval_image_classifier.py

SaintLogos1234/Deep-Mutual-Learning

34a20583debe4e0dab1d9856db69bed278c5c011

[ "MIT" ]

65

2018-04-23T01:52:45.000Z

2022-03-06T01:49:22.000Z

""" Generic evaluation script that evaluates a model using a given dataset. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf import eval_models from datasets.utils import * slim = tf.contrib.slim tf.app.flags.DEFINE_string('dataset_name', 'market1501', 'The name of the dataset to load.') tf.app.flags.DEFINE_string('split_name', 'test', 'The name of the train/test split.') tf.app.flags.DEFINE_string('dataset_dir', None, 'The directory where the dataset files are stored.') tf.app.flags.DEFINE_string('checkpoint_dir', None, 'The directory where the model was written to or an absolute path to a ' 'checkpoint file.') tf.app.flags.DEFINE_string('eval_dir', 'results', 'Directory where the results are saved to.') tf.app.flags.DEFINE_string('model_name', 'mobilenet_v1', 'The name of the architecture to evaluate.') tf.app.flags.DEFINE_integer('num_networks', 2, 'Number of Networks') tf.app.flags.DEFINE_integer('num_classes', 751, 'The number of classes.') tf.app.flags.DEFINE_integer('batch_size', 1, 'The number of samples in each batch.') tf.app.flags.DEFINE_string('preprocessing_name', None, 'The name of the preprocessing to use. If left ' 'as `None`, then the model_name flag is used.') tf.app.flags.DEFINE_integer('num_preprocessing_threads', 1, 'The number of threads used to create the batches.') tf.app.flags.DEFINE_float('moving_average_decay', 0.9999, 'The decay to use for the moving average.' 'If left as None, then moving averages are not used.') ######################### FLAGS = tf.app.flags.FLAGS def main(_): # create folders mkdir_if_missing(FLAGS.eval_dir) # test eval_models.evaluate() if __name__ == '__main__': tf.app.run()

31.782609

99

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2,193

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0.355072

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0.102605

0.151539

0.280189

0.149961

0

0.010329

0.293662

2,193

68

100

32.25

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0.041952

0

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false

0

0.15

0

0.175

0.025

0

null

0

null

0

1

0

4ff34a06c77e4b0809fa1c64b42511f3762f61e0

2,776

py

Python

tests/cli/test_new.py

deeplearninc/auger-ai

b50af35e8ea28b528ec233a2f4a8d4e412059be9

[ "MIT" ]

null

tests/cli/test_new.py

deeplearninc/auger-ai

b50af35e8ea28b528ec233a2f4a8d4e412059be9

[ "MIT" ]

25

2019-07-09T04:26:19.000Z

2020-07-21T06:43:25.000Z

tests/cli/test_new.py

deeplearninc/auger-ai

b50af35e8ea28b528ec233a2f4a8d4e412059be9

[ "MIT" ]

1

2019-07-09T15:19:13.000Z

import os from auger.cli.cli import cli from auger.api.utils.config import Config class TestNewCommand(): def test_minimal_arguments_successfull_creation(self, runner, isolated): # successful status result = runner.invoke(cli, ['new', 'test_project']) assert result.exit_code == 0 # directory created target_dir = os.path.join(os.getcwd(), 'test_project') assert os.path.exists(target_dir) and os.path.isdir(target_dir) # config file exists config_file = os.path.join(target_dir, 'auger.yaml') assert os.path.exists(config_file) # config contains proper data config = Config().load('test_project') assert config.get('name', '') == 'test_project' def test_project_with_given_name_already_exists( self, runner, log, project): os.chdir('..') runner.invoke(cli, ['new', 'test_project']) result = runner.invoke(cli, ['new', 'test_project']) assert result.exit_code != 0 assert (log.records[-1].message == "Can't create 'test_project'. Folder already exists.") def test_nested_project_forbidden(self, runner, log, project): result = runner.invoke(cli, ['new', 'test_project']) assert result.exit_code != 0 assert (log.records[-1].message == "Can't create 'test_project' inside a project." " './auger.yaml' already exists") def test_full_set_of_arguments(self, log, runner, isolated, project): os.chdir('..') result = runner.invoke( cli, [ 'new', 'new_project', '--model-type', 'regression', '--target', 'target_column', '--source', 'test_project/iris.csv']) assert result.exit_code == 0 config = Config().load('new_project') assert config.get('model_type', '') == 'regression' assert config.get('target', '') == 'target_column' assert config.get('source', '') == os.path.join( os.getcwd(), 'test_project', 'iris.csv') def test_bad_source(self, log, runner, isolated): result = runner.invoke( cli, ['new', 'test_project', '--source', 'not_existing_file.csv']) assert result.exit_code != 0 assert log.messages[-1].startswith("Can't find file to import:") def test_source_wrong_extension(self, log, runner, isolated): result = runner.invoke( cli, ['new', 'test_project', '--source', 'file_with_wrong.extension']) assert result.exit_code != 0 assert log.messages[-1] ==\ 'Source file has to be one of the supported fomats: .csv, .arff, .gz, .bz2, .zip, .xz, .json, .xls, .xlsx, .feather, .h5, .hdf5'

39.657143

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4.831832

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0.095712

0.065258

0.07831

0.37601

0.361094

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0.294593

0.246116

0

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69

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0

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0

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0

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1

0.115385

false

0

0.076923

0

0.211538

0

null

0

null

0

1

0

4ff4d9710a1d2817b836253d41e8fd15539f9501

13,090

py

Python

enn_zoo/enn_zoo/microrts/__init__.py

Miffyli/incubator

35c920b31fd0ed6cabdcb536201b39f31c3d9f03

[ "Apache-2.0", "MIT" ]

null

enn_zoo/enn_zoo/microrts/__init__.py

Miffyli/incubator

35c920b31fd0ed6cabdcb536201b39f31c3d9f03

[ "Apache-2.0", "MIT" ]

null

enn_zoo/enn_zoo/microrts/__init__.py

Miffyli/incubator

35c920b31fd0ed6cabdcb536201b39f31c3d9f03

[ "Apache-2.0", "MIT" ]

null

from dataclasses import dataclass from tokenize import String from typing import Any, Dict, List, Mapping, MutableMapping, Optional, Sequence, Tuple import random from entity_gym.environment.environment import EntityObs import numpy as np import numpy.typing as npt from copy import deepcopy import os import gym_microrts from gym_microrts import microrts_ai import xml.etree.ElementTree as ET import json from PIL import Image from entity_gym.environment import ( CategoricalAction, CategoricalActionMask, Entity, Environment, EpisodeStats, ObsSpace, CategoricalActionSpace, ActionSpace, Observation, Action, VecEnv, ) import jpype from jpype.imports import registerDomain import jpype.imports from jpype.types import JArray, JInt class GymMicrorts(Environment): """ A real-time strategy environment for microrts. See https://github.com/santiontanon/microrts Light grey squares are bases, dark grey squares are barracks, green squares are resources, colored circles are combat units, and grey circles are workers that harvest resources. Args: map_path: the path to the map, see the list of supported maps [here](https://github.com/vwxyzjn/microrts/tree/52d17e58592722889197aeee03fffafb154cfb8c/maps) reward_weight: the weight mutiplied to each each reward functions, which are in order: - win/loss reward: + 1 for win, - 1 for loss, 0 for tie - resource gather reward: + 1 for each resource gathered and +1 for returned - produce worker reward: + 1 for each worker produced - produce building reward: + 1 for each building produced - attack reward: + 1 for each attack action - produce combat unit reward: + 1 for each combat unit produced """ def __init__( self, map_path: str = "maps/10x10/basesTwoWorkers10x10.xml", reward_weight: List[float] = [10.0, 1.0, 1.0, 0.2, 1.0, 4.0], ): self.map_path = map_path self.reward_weight = np.array(reward_weight) self.step = 0 # read map self.microrts_path = os.path.join(gym_microrts.__path__[0], "microrts") root = ET.parse(os.path.join(self.microrts_path, self.map_path)).getroot() self.height = int(root.get("height")) # type: ignore self.width = int(root.get("width")) # type: ignore # launch the JVM if not jpype._jpype.isStarted(): registerDomain("ts", alias="tests") registerDomain("ai") jars = [ "microrts.jar", "lib/bots/Coac.jar", "lib/bots/Droplet.jar", "lib/bots/GRojoA3N.jar", "lib/bots/Izanagi.jar", "lib/bots/MixedBot.jar", "lib/bots/TiamatBot.jar", "lib/bots/UMSBot.jar", "lib/bots/mayariBot.jar", # "MindSeal.jar" ] for jar in jars: jpype.addClassPath(os.path.join(self.microrts_path, jar)) jpype.startJVM(convertStrings=False) # start microrts client from rts.units import UnitTypeTable self.real_utt = UnitTypeTable() from ai.rewardfunction import ( RewardFunctionInterface, WinLossRewardFunction, ResourceGatherRewardFunction, AttackRewardFunction, ProduceWorkerRewardFunction, ProduceBuildingRewardFunction, ProduceCombatUnitRewardFunction, ) self.rfs = JArray(RewardFunctionInterface)( [ WinLossRewardFunction(), ResourceGatherRewardFunction(), ProduceWorkerRewardFunction(), ProduceBuildingRewardFunction(), AttackRewardFunction(), ProduceCombatUnitRewardFunction(), ] ) self.rfs_names = [str(rf) for rf in self.rfs] self.ai2s = [microrts_ai.coacAI for _ in range(1)] from ts.entity import JNIEntityClient as Client from ai.core import AI self.client = Client( self.rfs, os.path.expanduser(self.microrts_path), self.map_path, self.ai2s[0](self.real_utt), self.real_utt, False, ) # get the unit type table self.utt = json.loads(str(self.client.sendUTT())) @classmethod def obs_space(cls) -> ObsSpace: return ObsSpace( { "Resource": Entity(["x", "y"]), "Base": Entity(["x", "y"]), "Barracks": Entity(["x", "y"]), "Worker": Entity(["x", "y"]), "Light": Entity(["x", "y"]), "Heavy": Entity(["x", "y"]), "Ranged": Entity(["x", "y"]), } ) @classmethod def action_space(cls) -> Dict[str, ActionSpace]: return { "unit_action": CategoricalActionSpace( choices=[ "move_up", "move_right", "move_down", "move_left", "harvest_up", "harvest_right", "harvest_down", "harvest_left", "return_up", "return_right", "return_down", "return_left", "produce_base_up", "produce_base_right", "produce_base_down", "produce_base_left", "produce_barrack_up", "produce_barrack_right", "produce_barrack_down", "produce_barrack_left", ] + [ f"attack_location_{i}" for i in range(49) ], # the attack trange is a 7x7 relative grid ), "base_action": CategoricalActionSpace( choices=[ "produce_worker_up", "produce_worker_right", "produce_worker_down", "produce_worker_left", ], ), "barrack_action": CategoricalActionSpace( choices=[ "produce_light_up", "produce_light_right", "produce_light_down", "produce_light_left", "produce_heavy_up", "produce_heavy_right", "produce_heavy_down", "produce_heavy_left", "produce_ranged_up", "produce_ranged_right", "produce_ranged_down", "produce_ranged_left", ], ), } def render(self, **kwargs: Any) -> npt.NDArray[np.uint8]: if "mode" in kwargs and kwargs["mode"] == "rgb_array": bytes_array = np.array(self.client.render(True)) image = Image.frombytes("RGB", (640, 640), bytes_array) return np.array(image)[:, :, ::-1] else: return self.client.render(False) # type: ignore def reset(self) -> Observation: self.step = 0 self.returns = np.zeros(len(self.rfs)) response = self.client.reset(0) unit_action_actor_ids = np.array(response.observation[8]) unit_action_actor_masks = np.array(response.observation[9], dtype=np.bool8) base_action_actor_ids = np.array(response.observation[10]) base_action_actor_masks = np.array(response.observation[11], dtype=np.bool8) barrack_action_actor_ids = np.array(response.observation[12]) barrack_action_actor_masks = np.array(response.observation[13], dtype=np.bool8) return Observation.from_entity_obs( entities=self.generate_entities(response), actions={ "unit_action": CategoricalActionMask( actor_ids=unit_action_actor_ids, # type: ignore mask=unit_action_actor_masks, ), "base_action": CategoricalActionMask( actor_ids=base_action_actor_ids, # type: ignore mask=base_action_actor_masks, ), "barrack_action": CategoricalActionMask( actor_ids=barrack_action_actor_ids, # type: ignore mask=barrack_action_actor_masks, ), }, reward=response.reward @ self.reward_weight, done=response.done[0], end_of_episode_info=EpisodeStats( length=self.step, total_reward=float(self.reward_weight @ self.returns) ) if response.done[0] else None, ) def act(self, action: Mapping[str, Action]) -> Observation: game_over = False self.step += 1 unit_action_actors: Sequence[Any] = [] unit_actions: npt.NDArray[np.int64] = np.empty(0, dtype=np.int64) base_action_actors: Sequence[Any] = [] base_actions: npt.NDArray[np.int64] = np.empty(0, dtype=np.int64) barrack_action_actors: Sequence[Any] = [] barrack_actions: npt.NDArray[np.int64] = np.empty(0, dtype=np.int64) if "unit_action" in action and isinstance( action["unit_action"], CategoricalAction ): unit_action_actors = action["unit_action"].actors unit_actions = action["unit_action"].actions if "base_action" in action and isinstance( action["base_action"], CategoricalAction ): base_action_actors = action["base_action"].actors base_actions = action["base_action"].actions if "barrack_action" in action and isinstance( action["barrack_action"], CategoricalAction ): barrack_action_actors = action["barrack_action"].actors barrack_actions = action["barrack_action"].actions response = self.client.gameStep( unit_action_actors, unit_actions, base_action_actors, base_actions, barrack_action_actors, barrack_actions, 0, ) unit_action_actor_ids = np.array(response.observation[8]) unit_action_actor_masks = None if len(unit_action_actor_ids) > 0: unit_action_actor_masks = np.array(response.observation[9], dtype=np.bool8) base_action_actor_ids = np.array(response.observation[10]) base_action_actor_masks = None if len(base_action_actor_ids) > 0: base_action_actor_masks = np.array(response.observation[11], dtype=np.bool8) barrack_action_actor_ids = np.array(response.observation[12]) barrack_action_actor_masks = None if len(barrack_action_actor_ids) > 0: barrack_action_actor_masks = np.array( response.observation[13], dtype=np.bool8 ) self.returns += response.reward return Observation.from_entity_obs( entities=self.generate_entities(response), actions={ "unit_action": CategoricalActionMask( actor_ids=unit_action_actor_ids, # type: ignore mask=unit_action_actor_masks, ), "base_action": CategoricalActionMask( actor_ids=base_action_actor_ids, # type: ignore mask=base_action_actor_masks, ), "barrack_action": CategoricalActionMask( actor_ids=barrack_action_actor_ids, # type: ignore mask=barrack_action_actor_masks, ), }, reward=response.reward @ self.reward_weight, done=response.done[0], end_of_episode_info=EpisodeStats( length=self.step, total_reward=float(self.reward_weight @ self.returns), metrics=dict( zip( [f"charts/episodic_return/{item}" for item in self.rfs_names], self.returns, ) ), ) if response.done[0] else None, ) def generate_entities(self, response: Any) -> Mapping[str, Optional[EntityObs]]: entities: MutableMapping[str, Optional[EntityObs]] = {} for entity_type, observation in zip( ["Resource", "Base", "Barracks", "Worker", "Light", "Heavy", "Ranged"], response.observation, ): observation = np.array(observation).astype(np.float32) if len(observation) > 0: entities[entity_type] = EntityObs( features=observation[:, 1:], ids=observation[:, 0].astype(np.int32) ) return entities def __del__(self) -> None: self.client.close()

37.723343

164

0.559664

1,305

13,090

5.403831

0.206897

0.046795

0.029779

0.044243

0.323313

0.298639

0.268009

0.259075

0

0.015419

0.345989

13,090

346

165

37.83237

0.808317

0.090298

0

0.232323

0

0.103028

0.014465

0

1

0.026936

false

0

0.077441

0.006734

0.131313

0

null

0

null

0

1

0

4ff8cae0f2cae43548c5258dd28dcf5612f9a7f7

289

py

Python

Python/07. Collections/05. Word Order/Solution.py

AdityaSingh17/HackerRank-Solutions

65b7fcd6e82be242fcc7e5b1771941206a8b7940

[ "MIT" ]

null

Python/07. Collections/05. Word Order/Solution.py

AdityaSingh17/HackerRank-Solutions

65b7fcd6e82be242fcc7e5b1771941206a8b7940

[ "MIT" ]

null

Python/07. Collections/05. Word Order/Solution.py

AdityaSingh17/HackerRank-Solutions

65b7fcd6e82be242fcc7e5b1771941206a8b7940

[ "MIT" ]

null

# Word Order # Problem Link: https://www.hackerrank.com/challenges/word-order/problem from collections import OrderedDict words = OrderedDict() for _ in range(int(input())): word = input() words.setdefault(word, 0) words[word] += 1 print(len(words)) print(*words.values())

19.266667

72

0.698962

38

289

5.289474

0.657895

0.089552

0.159204

0

0.008163

0.152249

289

14

73

20.642857

0.812245

0.280277

0

1

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false

0

0.125

0

0.125

0.25

0

null

0

null

0

1

0

4ffde2f06494b47edff9a4bc601d3565042d59f0

1,166

py

Python

recap_utils/text.py

ReCAP-UTR/Utils

10f2912a91f8bbfb1ede818e240a3ba7cf767656

[ "Apache-2.0" ]

null

recap_utils/text.py

ReCAP-UTR/Utils

10f2912a91f8bbfb1ede818e240a3ba7cf767656

[ "Apache-2.0" ]

null

recap_utils/text.py

ReCAP-UTR/Utils

10f2912a91f8bbfb1ede818e240a3ba7cf767656

[ "Apache-2.0" ]

null

import shutil from pathlib import Path import deepl_pro as dl import typer from recap_utils import model cli = typer.Typer() @cli.command() def translate( folder_in: Path, folder_out: Path, source_lang: str, target_lang: str, auth_key: str, input_glob: str, output_suffix: str, clean: bool = False, overwrite: bool = False, start: int = 1, ) -> None: if clean: shutil.rmtree(folder_out) folder_out.mkdir() paths = model.PathPair.create(folder_in, folder_out, input_glob, output_suffix) translator = dl.Translator( auth_key, dl.Language(source_lang), dl.Language(target_lang) ) with typer.progressbar( paths[start - 1 :], item_show_func=model.PathPair.label, show_pos=True, ) as bar: for path_pair in bar: if overwrite or not path_pair.target.exists(): with path_pair.source.open("r") as file: source_text = file.read() target_text = translator.translate_text(source_text) with path_pair.target.open("w") as file: file.write(target_text)

24.291667

83

0.621784

151

1,166

4.602649

0.443709

0.051799

0.040288

0

0.002398

0.284734

1,166

47

84

24.808511

0.830935

0

0.001715

0

1

0.026316

false

0

0.131579

0

0.157895

0

null

0

null

0

1

0

8b00c152dd7573d50b0538c91b16535244efb283

1,613

py

Python

django_cbv_utils/forms/clean.py

okwrtdsh/django_cbv_utils

6858f53dda65c79e2201a67ba34d3885b3f11e22

[ "MIT" ]

null

django_cbv_utils/forms/clean.py

okwrtdsh/django_cbv_utils

6858f53dda65c79e2201a67ba34d3885b3f11e22

[ "MIT" ]

null

django_cbv_utils/forms/clean.py

okwrtdsh/django_cbv_utils

6858f53dda65c79e2201a67ba34d3885b3f11e22

[ "MIT" ]

null

class RequiredMixin(object): multiple_required_list = [] chain_required_list = [] def get_multiple_required_list(self): return self.multiple_required_list def get_chain_required_list(self): return self.chain_required_list def multiple_required( self, cleaned_data, fields, func=lambda l: not any(l), msg=None): """ 複数の入力による必須項目の判定 defaultはいずれか必須 """ if msg is None: msg = "{}のいずれかの入力が必須です。".format( "、".join(self.fields[f].label for f in fields)) cleaned_fields = (cleaned_data.get(f) for f in fields) if func(cleaned_fields): for f in fields: self.add_error(f, msg) def chain_required( self, cleaned_data, trigger, fields, func=bool, msg=None): """ triggerが条件を満たす場合に入力を必須にする """ if msg is None: msg = "このフィールドは必須です。" if isinstance(trigger, (list, tuple)): cleaned_trigger = (cleaned_data.get(f) for f in trigger) else: cleaned_trigger = cleaned_data.get(trigger) if func(cleaned_trigger): for f in fields: if not cleaned_data.get(f): self.add_error(f, msg) def clean(self): cleaned_data = super().clean() for kwargs in self.get_multiple_required_list(): self.multiple_required(cleaned_data, **kwargs) for kwargs in self.get_chain_required_list(): self.chain_required(cleaned_data, **kwargs) return cleaned_data

32.26

68

0.584625

185

1,613

4.875676

0.237838

0.121951

0.033259

0.053215

0.359202

0.088692

0.046563

0

0.323001

1,613

49

69

32.918367

0.826007

0.034718

0

0.162162

0

0.019973

0

1

0.135135

false

0

0.054054

0.297297

0

null

0

null

0

1

0

8b04e2c43a95b31379b3c5f312a7366fcd858adf

9,406

py

Python

SUNIWARD.py

TracyCuiq/S-UNIWARD-python

d6fa096472af0f5a3ce3d83b72041817629710b8

[ "MIT" ]

7

2020-04-28T02:37:15.000Z

2021-10-18T07:43:11.000Z

SUNIWARD.py

TracyCuiq/S-UNIWARD-python

d6fa096472af0f5a3ce3d83b72041817629710b8

[ "MIT" ]

1

2020-07-06T03:37:21.000Z

SUNIWARD.py

TracyCuiq/S-UNIWARD-python

d6fa096472af0f5a3ce3d83b72041817629710b8

[ "MIT" ]

null

import numpy as np import matplotlib.pyplot as plt import random from scipy.signal import convolve2d import math from scipy import misc import os from PIL import Image from numba import jit import cv2 import scipy.misc np.set_printoptions(threshold=np.inf) def S_UNIWARD(coverPath, payload): sgm = 1 ## Get 2D wavelet filters - Daubechies 8 # 1D high pass decomposition filter hpdf_list = [-0.0544158422, 0.3128715909, -0.6756307363, 0.5853546837, 0.0158291053, -0.2840155430, -0.0004724846, 0.1287474266, 0.0173693010, -0.0440882539, - 0.0139810279, 0.0087460940, 0.0048703530, -0.0003917404, -0.0006754494, -0.0001174768] # 1D low pass decomposition filter hpdf_len = range(0, len(hpdf_list)) hpdf_list_reverse = hpdf_list[::-1] lpdf_list = hpdf_list for i in range(len(hpdf_list)): lpdf_list[i] = ((-1) ** hpdf_len[i]) * hpdf_list_reverse[i] hpdf_array = np.array([hpdf_list]) lpdf_array = np.array([lpdf_list]) lpdf = lpdf_array.reshape(len(lpdf_list), 1) hpdf = hpdf_array.reshape(len(hpdf_list), 1) # construction of 2D wavelet filters F1 = lpdf * hpdf_array F2 = hpdf * lpdf_array F3 = hpdf * hpdf_array W_F = np.zeros((F1.shape[0], F1.shape[0], 3)) W_F[:, :, 0] = F1 W_F[:, :, 1] = F2 W_F[:, :, 2] = F3 ## Get embedding costs # initialization cover = scipy.misc.imread(coverPath, flatten=False, mode='RGB') wetCost = 100000000 k, l, _ = cover.shape # add padding S1, _1 = F1.shape S2, _2 = F2.shape S3, _3 = F3.shape padSize = max(S1, S2, S3) coverPadded = np.zeros((k + padSize * 2, l + padSize * 2, 3)) for i in range(3): coverPadded[:, :, i] = np.lib.pad(cover[:, :, i], padSize, 'symmetric') xi = np.zeros((k + padSize * 2, l + padSize * 2, 3)) x = np.zeros((k, l, 3)) for i in range(3): # compute residual R = convolve2d(coverPadded[:, :, i], W_F[:, :, i], mode='same') xi[:, :, i] = convolve2d(1. / (np.abs(R) + sgm), np.rot90(abs(W_F[:, :, i]), 2), mode='same') # correct the suitability shift if filter size is even if S1 % 2 == 0: xi[:, :, i] = np.roll(xi[:, :, i], [1, 0]) xi[:, :, i] = np.roll(xi[:, :, i], [0, 1]) # remove padding S_xi, __xi = xi[:, :, i].shape x[:, :, i] = xi[(S_xi - k) / 2: -(S_xi - k) / 2, (__xi - l) / 2: -(__xi - l) / 2, i] # compute embedding costs \rho rho = np.zeros((k, l)) rho = x[:, :, 0] + x[:, :, 1] + x[:, :, 2] # adjust embedding costs a, b = np.where(rho > wetCost) for i in range(len(a)): rho[a[i], b[i]] = wetCost # threshold on the costs a, b = np.where(np.isnan(rho)) for i in range(len(a)): rho[a[i], b[i]] = wetCost # if all xi{} are zero threshold the cost #k, k_ = rho.shape rhoP1 = np.zeros((k, l, 3)) rhoM1 = np.zeros((k, l, 3)) for i in range(3): rhoP1[:,:,i] = rho rhoM1[:,:,i] = rho #a, b, c = np.where(cover - 255.0 <= 0.1) a, b, c = np.where(cover == 255) for i in range(len(a)): rhoP1[a[i], b[i], c[i]] = wetCost # do not embed +1 if the pixel has max value #a, b, c = np.where(cover - 0 <= 0.1) a, b, c = np.where(cover == 0) for i in range(len(a)): rhoM1[a[i], b[i], c[i]] = wetCost # do not embed -1 if the pixel has min value ## Embedding simulator ## cover_len = len(cover[:, :, 0]) * len(cover[:, :, 0]) stego = cover print(rhoP1) for i in range(3): stego[:, :, i] = EmbeddingSimulator_singel(cover[:, :, i], rhoP1[:, :, i], rhoM1[:, :, i], payload * cover_len, fixEmbeddingChanges=False) return stego # TODO def EmbeddingSimulator(x, rhoP1, rhoM1, m, fixEmbeddingChanges=False): cover_len = len(x[:, :, 0]) * len(x[:, :, 0]) l = cal_lambda(rhoP1, rhoM1, m, cover_len) randChange = random.random(x.shape) y = x def EmbeddingSimulator_singel(x, rhoP1, rhoM1, m, fixEmbeddingChanges=False): w, h = x.shape cover_len = (w * h) l = cal_lambda_(rhoP1, rhoM1, m, cover_len) shape = rhoP1.shape pChangeP1 = [(math.exp(-l * rhoP1[i][j])) / (1 + math.exp(-l * rhoP1[i][j]) + math.exp(-l * rhoM1[i][j])) for j in range(shape[1]) for i in range(shape[0])] pChangeM1 = [(math.exp(-l * rhoM1[i][j])) / (1 + math.exp(-l * rhoP1[i][j]) + math.exp(-l * rhoM1[i][j])) for j in range(shape[1]) for i in range(shape[0])] pChangeP1_array = np.array(pChangeP1).reshape(shape[1], shape[0]).T pChangeM1_array = np.array(pChangeM1).reshape(shape[1], shape[0]).T if fixEmbeddingChanges == True: np.random.seed(139187) randChange = np.random.rand(w, h) y = x arr0, _0 = np.where(randChange < pChangeP1_array) for i in range(len(arr0)): y[arr0[i]][_0[i]] += 1 arr1, _1 = np.where((randChange >= pChangeP1_array) & (randChange < pChangeP1_array + pChangeM1_array)) for i in range(len(arr1)): y[arr1[i]][_1[i]] -= 1 return y # TODO def cal_lambda(rhoP1, rhoM1, message_length, n): l3 = 1e+3 m3 = math.ceil(message_length) iterations = 0 while m3 > message_length: pP1 = rhoP1 pM1 = rhoM1 shape = pP1.shape l3 = l3 * 2 pP1 = [ (math.exp(-l3 * rhoP1[i][j][k])) / (1 + math.exp(-l3 * rhoP1[i][j][k]) + math.exp(-l3 * rhoM1[i][j][k])) for k in range(shape[2]) for j in range(shape[1]) for i in range(shape[0])] # list pM1 = [ (math.exp(-l3 * rhoM1[i][j][k])) / (1 + math.exp(-l3 * rhoP1[i][j][k]) + math.exp(-l3 * rhoM1[i][j][k])) for k in range(shape[2]) for j in range(shape[1]) for i in range(shape[0])] # list pP1_array = (np.array(pP1)).reshape(shape[0], shape[1], shape[2]) pM1_array = (np.array(pM1)).reshape(shape[0], shape[1], shape[2]) m3 = ternary_entropyf_4list(pP1, pM1) iterations = iterations + 1 if iterations > 10: return l3 return 0 def cal_lambda_(rhoP1, rhoM1, message_length, n): l3 = 1e+3 m3 = math.ceil(message_length) iterations = 0 while m3 > message_length: pP1 = rhoP1 pM1 = rhoM1 # shape = lambda x: pP1.shape if pP1.shape == pM1.shape else 0 shape = pP1.shape l3 = l3 * 2 pP1 = [(math.exp(-l3 * rhoP1[i][j])) / (1 + math.exp(-l3 * rhoP1[i][j]) + math.exp(-l3 * rhoM1[i][j])) for j in range(shape[1]) for i in range(shape[0])] # list pM1 = [(math.exp(-l3 * rhoM1[i][j])) / (1 + math.exp(-l3 * rhoP1[i][j]) + math.exp(-l3 * rhoM1[i][j])) for j in range(shape[1]) for i in range(shape[0])] # list pP1_array = (np.array(pP1)).reshape(shape[1], shape[0]).T pM1_array = (np.array(pM1)).reshape(shape[1], shape[0]).T m3 = ternary_entropyf_4list(pP1, pM1) iterations = iterations + 1 if iterations > 10: return l3 l1 = 0 m1 = n l = 0 alpha = message_length / n # limit search to 30 iterations # and require that relative payload embedded is roughly within 1/1000 of the required relative payload while (m1 - m3) / n > alpha / 1000.0 and iterations < 30: l = l1 + (l3 - l1) / 2 pP1 = [(math.exp(-l * rhoP1[i][j])) / (1 + math.exp(-l * rhoP1[i][j]) + math.exp(-l * rhoM1[i][j])) for j in range(shape[1]) for i in range(shape[0])] pM1 = [(math.exp(-l * rhoM1[i][j])) / (1 + math.exp(-l * rhoP1[i][j]) + math.exp(-l * rhoM1[i][j])) for j in range(shape[1]) for i in range(shape[0])] m2 = ternary_entropyf_4list(pP1, pM1) if m2 < message_length: l3 = l m3 = m2 else: l1 = l m1 = m2 iterations = iterations + 1 return 0 def ternary_entropyf(pP1_, pM1_): p0 = pP1_ shape = p0.shape p0 = [1 - pP1_[i][j] - pM1_[i][j] for j in range(shape[1]) for i in range(shape[0])] ptemp = np.concatenate([[p0], [pP1_], [pM1_]]) _, m, n = ptemp.shape p = np.reshape(ptemp, _ * m * n, 1) H = (-(p[i] * math.log(p[i])) for i in range(_ * m * n)) Ht = sum(H) return Ht def ternary_entropyf_4list(pP1_, pM1_): p0 = [1 - pP1_[i] - pM1_[i] for i in range(len(pP1_))] p = p0 + pP1_ + pM1_ Ht = 0 for i in range(len(p)): if p[i] != 0: H = -(p[i] * math.log(p[i])) Ht += H # Ht = sum(H) return Ht coverPath = './sample' stegoPath = './stego' for home, dirs, files in os.walk(coverPath): for file in files: if not file.startswith('.'): imgpath = os.path.join(home, file) print(imgpath) #img = misc.imread(imgpath) img = Image.open(imgpath) #if img.ndim == 3: if len(img.split())== 3: stego = S_UNIWARD(imgpath, 0.4) stegoname = os.path.join(stegoPath, file) misc.imsave(stegoname, stego) #misc.imsave(stegoname, stego-img) plt.subplot(121) plt.imshow(img) plt.subplot(122) plt.imshow(stego) plt.show()

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8b06db32e78be673f09554f2ce608ac83895e9bf

1,463

py

Python

Boatwright_et_al.,2018/assembly_and_qc_scripts/drosophila_scripts/blast/parseBlastResultsForLocation.py

BBarbazukLab/papers

fc77bcae17d475da99d758407be3ff7f9b298c3d

[ "MIT" ]

3

2018-09-18T15:22:25.000Z

2019-07-10T17:57:42.000Z

Boatwright_et_al.,2018/assembly_and_qc_scripts/drosophila_scripts/blast/parseBlastResultsForLocation.py

BBarbazukLab/papers

fc77bcae17d475da99d758407be3ff7f9b298c3d

[ "MIT" ]

null

Boatwright_et_al.,2018/assembly_and_qc_scripts/drosophila_scripts/blast/parseBlastResultsForLocation.py

BBarbazukLab/papers

fc77bcae17d475da99d758407be3ff7f9b298c3d

[ "MIT" ]

4

2018-12-01T15:05:15.000Z

2019-12-17T13:43:55.000Z

#!/usr/bin/env python # This script parses BLAST output to remove exact, self-hits. # Output includes query, subject, percent identity, query start, # query end, subject start, subject end, and the e-value in a # BED formatted file. #AMR 03/28/2013 import csv import operator with open('/project/ambiguity/blast_results.tsv', 'rb') as input: with open('/project/ambiguity/blast_ambig_regions.bed', 'wb') as output: input_read = csv.reader(input, delimiter='\t') input_sort = sorted(input_read, key=operator.itemgetter(0)) # Sorts the input file by fusion_id for row in input_sort: query=row[0] subject=row[1] per_identity=row[2] q_start=int(row[6])-1 #BED files are 0-based, and BLAST results are 1-based, so 1 must be subtracted. q_end=row[7] s_start=int(row[8])+1 #BED files are 0-based, and BLAST results are 1-based, so 1 must be subtracted. s_end=row[9] e_value=row[10] if query==subject and per_identity=='100.00': continue else: output.write(query+'\t') #output.write(subject+'\t') #output.write(per_identity+'\t') output.write(str(q_start)+'\t') output.write(q_end+'\t') #output.write(str(s_start)+'\t') #output.write(s_end+'\t') output.write(e_value+'\n')

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null

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null

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1

0

8b07634e37eaf0bbc99e3ff4b057bb8cd1ffb567

6,138

py

Python

medium/1801-number-of-orders-in-the-backlog.py

wanglongjiang/leetcode

c61d2e719e81575cfb5bde9d64e15cee7cf01ef3

[ "MIT" ]

2

2021-03-14T11:38:26.000Z

2021-03-14T11:38:30.000Z

medium/1801-number-of-orders-in-the-backlog.py

wanglongjiang/leetcode

c61d2e719e81575cfb5bde9d64e15cee7cf01ef3

[ "MIT" ]

null

medium/1801-number-of-orders-in-the-backlog.py

wanglongjiang/leetcode

c61d2e719e81575cfb5bde9d64e15cee7cf01ef3

[ "MIT" ]

1

2022-01-17T19:33:23.000Z

''' 积压订单中的订单总数给你一个二维整数数组 orders ，其中每个 orders[i] = [pricei, amounti, orderTypei] 表示有 amounti 笔类型为 orderTypei 、价格为 pricei 的订单。订单类型 orderTypei 可以分为两种： 0 表示这是一批采购订单 buy 1 表示这是一批销售订单 sell 注意，orders[i] 表示一批共计 amounti 笔的独立订单，这些订单的价格和类型相同。对于所有有效的 i ，由 orders[i] 表示的所有订单提交时间均早于 orders[i+1] 表示的所有订单。存在由未执行订单组成的积压订单。积压订单最初是空的。提交订单时，会发生以下情况：如果该订单是一笔采购订单 buy ，则可以查看积压订单中价格最低的销售订单 sell 。如果该销售订单 sell 的价格低于或等于当前采购订单 buy 的价格，则匹配并执行这两笔订单，并将销售订单 sell 从积压订单中删除。否则，采购订单 buy 将会添加到积压订单中。反之亦然，如果该订单是一笔销售订单 sell ，则可以查看积压订单中价格最高的采购订单 buy 。如果该采购订单 buy 的价格高于或等于当前销售订单 sell 的价格，则匹配并执行这两笔订单，并将采购订单 buy 从积压订单中删除。否则，销售订单 sell 将会添加到积压订单中。输入所有订单后，返回积压订单中的订单总数。由于数字可能很大，所以需要返回对 109 + 7 取余的结果。 1 <= orders.length <= 10^5 orders[i].length == 3 1 <= pricei, amounti <= 10^9 orderTypei 为 0 或 1 ''' from typing import List ''' 思路1、最大堆、最小堆。构造采购订单的最大堆，销售订单的最小堆。遍历订单list 1、遇到采购订单，先在销售订单堆里面查找，如果最小堆里没有满足需求的订单，将采购订单加入最大堆。 2、遇到销售订单，先在采购订单堆里面查找，如果最大堆里没有满足需求的订单，将销售订单加入最小堆。所有的订单都处理完之后，返回2个堆中订单数之和时间复杂度：最坏情况下O(nlogn)，这种情况下所有订单都入堆。10^6。空间复杂度：最坏情况下O(n) ''' class Solution: def getNumberOfBacklogOrders(self, orders: List[List[int]]) -> int: buyOrders, sellOrders = MaxHeap(), MinHeap() # 采购是最大堆，销售是最小堆 for order in orders: if order[2] == 0: # 当前订单为采购订单，需要从销售订单里面查找最小值 while sellOrders.notEmpty() and sellOrders.getMin()[0] <= order[0]: # 如果价格最低的销售订单小于等于当前采购订单价格，执行订单 sellOrder = sellOrders.getMin() if sellOrder[1] < order[1]: # 订单数量大于当前销售订单数量，需要删除当前销售订单，当前订单数量减去销售订单数量 order[1] -= sellOrder[1] sellOrders.extractMin() elif sellOrder[1] > order[1]: # 销售订单数量大于当前订单数量，当前订单处理完毕，销售订单减去数量 sellOrder[1] -= order[1] order[1] = 0 break else: # 当前订单数等于销售订单数，需要删除销售订单,当前订单处理完成 sellOrders.extractMin() order[1] = 0 break if order[1] > 0: # 当前订单未处理完毕，需要加入采购订单 buyOrders.insert(order) else: # 当前订单为销售订单，需要从采购订单里面查找最大值，基本与上面的采购订单逻辑互为镜像 while buyOrders.notEmpty() and buyOrders.getMax()[0] >= order[0]: # 如果价格最高的采购订单大于等于当前销售订单价格，执行订单 buyOrder = buyOrders.getMax() if buyOrder[1] < order[1]: # 订单数量大于当前采购订单数量，需要删除当前采购订单，当前订单数量减去采购订单数量 order[1] -= buyOrder[1] buyOrders.extractMin() elif buyOrder[1] > order[1]: # 采购订单数量大于当前订单数量，当前订单处理完毕，采购订单减去数量 buyOrder[1] -= order[1] order[1] = 0 break else: # 当前订单数等于采购订单数，需要删除采购订单,当前订单处理完成 buyOrders.extractMin() order[1] = 0 break if order[1] > 0: # 当前订单未处理完毕，需要加入销售订单 sellOrders.insert(order) # 所有的订单都处理完成之后，统计剩余的订单数 ans = sum([item[1] for item in buyOrders.heap]) ans += sum([item[1] for item in sellOrders.heap]) return ans % (10**9 + 7) class MaxHeap: def __init__(self): self.heap = [] self.size = 0 # 向堆中插入值 def insert(self, item): self.heap.append(item) i = self.size self.size += 1 while i > 0 and self.heap[self.parent(i)][0] < item[0]: # 将大于父节点的值向上提升 self.heap[i], self.heap[self.parent(i)] = self.heap[self.parent(i)], self.heap[i] i = self.parent(i) # 从堆中删除最大元素并返回 def extractMin(self): i = self.heap[0] self.size -= 1 last = self.heap.pop() if self.size: self.heap[0] = last self.maxHeapify(0) return i # 保持最大堆的性质 def maxHeapify(self, i): left = 2 * i + 1 right = 2 * i + 2 minIndex = i # 如果左、右子节点大于父节点，不满足最大堆性质，需要将父节点与左或右节点交换，使之满足最大堆性质 if left < self.size and self.heap[left][0] > self.heap[minIndex][0]: minIndex = left if right < self.size and self.heap[right][0] > self.heap[minIndex][0]: minIndex = right if minIndex != i: self.heap[minIndex], self.heap[i] = self.heap[i], self.heap[minIndex] self.maxHeapify(minIndex) # 交换后子节点可能不满足最大堆性质，需要递归向下执行 # 求父节点的索引 def parent(self, i): return (i - 1) // 2 def getMax(self): return self.heap[0] def notEmpty(self): return self.size > 0 class MinHeap: def __init__(self): self.heap = [] self.size = 0 # 向堆中插入值 def insert(self, item): self.heap.append(item) i = self.size self.size += 1 while i > 0 and self.heap[self.parent(i)][0] > item[0]: # 将小于父节点的值向上提升 self.heap[i], self.heap[self.parent(i)] = self.heap[self.parent(i)], self.heap[i] i = self.parent(i) # 从堆中删除最小元素并返回 def extractMin(self): i = self.heap[0] self.size -= 1 last = self.heap.pop() if self.size: self.heap[0] = last self.minHeapify(0) return i # 保持最小堆的性质 def minHeapify(self, i): left = 2 * i + 1 right = 2 * i + 2 minIndex = i # 如果左、右子节点小于父节点，不满足最小堆性质，需要将父节点与左或右节点交换，使之满足最小堆性质 if left < self.size and self.heap[left][0] < self.heap[minIndex][0]: minIndex = left if right < self.size and self.heap[right][0] < self.heap[minIndex][0]: minIndex = right if minIndex != i: self.heap[minIndex], self.heap[i] = self.heap[i], self.heap[minIndex] self.minHeapify(minIndex) # 交换后子节点可能不满足最小堆性质，需要递归向下执行 # 求父节点的索引 def parent(self, i): return (i - 1) // 2 def getMin(self): return self.heap[0] def notEmpty(self): return self.size > 0 s = Solution() print(s.getNumberOfBacklogOrders([[10, 5, 0], [15, 2, 1], [25, 1, 1], [30, 4, 0]])) print(s.getNumberOfBacklogOrders([[7, 1000000000, 1], [15, 3, 0], [5, 999999995, 0], [5, 1, 1]]))

33.358696

115

0.562398

717

6,138

4.803347

0.277545

0.088269

0.036585

0.031359

0.382695

0.37108

0.357724

0

0.036664

0.320137

6,138

183

116

33.540984

0.788641

0.234441

0

0.634783

0

1

0.130435

false

0

0.008696

0.052174

0.243478

0.017391

0

null

0

null

0

1

0

8b09e08df5407786baf6f2c99080da13eca9eb0e

943

py

Python

Solutions/Problem_Statement_11_Solution.py

bhaktee01ugale/Hacktoberfest_Moz_Cummins

d8f5cb503c0df48ebae7fd927b812e145f121279

[ "MIT" ]

11

2021-10-01T09:02:23.000Z

2022-02-18T17:21:38.000Z

Solutions/Problem_Statement_11_Solution.py

bhaktee01ugale/Hacktoberfest_Moz_Cummins

d8f5cb503c0df48ebae7fd927b812e145f121279

[ "MIT" ]

100

2021-09-28T11:45:37.000Z

2021-11-02T05:47:41.000Z

Solutions/Problem_Statement_11_Solution.py

bhaktee01ugale/Hacktoberfest_Moz_Cummins

d8f5cb503c0df48ebae7fd927b812e145f121279

[ "MIT" ]

68

2021-09-26T11:47:23.000Z

2022-02-18T17:09:13.000Z

# Write a function howSum (targetSum, numbers) that takes in a targetSum and an array of numbers of arguments. # The function should return an array containing any combination of elements that add up to exactly the targetSum. # If there is no combination that adds up to the targetSum, then return null. # If there are many combinations then return any single one. A Number in numbers can be repeated any number of times to give the targetSum. def howSum(targetSum,numbers,htable={}): if targetSum in htable: return htable[targetSum] if targetSum==0: return [] if targetSum<0: return None for num in numbers: rem= targetSum-num remres= howSum(rem,numbers,htable) if (remres !=None): newarr=remres.copy() newarr.append(num) htable[targetSum]=newarr return htable[targetSum] htable[targetSum]=None return None

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0

null

0

null

0

1

0

8b12442e6d705f6084e9703508feba4841dc204c

1,989

py

Python

src/c_net.py

PlebeianDev/Bookshelf-Format-Parser

6ead6db3dac5c7568a7f1e5f35ee9ddc62fc01e1

[ "MIT" ]

null

src/c_net.py

PlebeianDev/Bookshelf-Format-Parser

6ead6db3dac5c7568a7f1e5f35ee9ddc62fc01e1

[ "MIT" ]

null

src/c_net.py

PlebeianDev/Bookshelf-Format-Parser

6ead6db3dac5c7568a7f1e5f35ee9ddc62fc01e1

[ "MIT" ]

null

import sys class Net: """ Defines a net object according to bookshelf format """ counter = -1 def __init__(self): Net.counter += 1 self.name = None self.cells = [] # list of cells-in-net names self.net_degree = 0 self.area = 0.0 self.left_x = 0.0 self.low_y = 0.0 self.right_x = 0.0 self.high_y = 0.0 self.hpwl = 0.0 self.id = Net.counter def calculate_net_area(self): return abs((self.high_y - self.low_y) * (self.right_x - self.left_x)) def make_cells_list(self, cells_from_file: set): self.cells = cells_from_file def calculate_net_corners(self, cells: {}): low_y = sys.float_info.max left_x = sys.float_info.max high_y = sys.float_info.min right_x = sys.float_info.min for cell_name in self.cells: if cells[cell_name].low_y <= low_y: low_y = cells[cell_name].low_y if cells[cell_name].left_x <= left_x: left_x = cells[cell_name].left_x if cells[cell_name].high_y >= high_y: high_y = cells[cell_name].high_y if cells[cell_name].right_x >= right_x: right_x = cells[cell_name].right_x self.left_x = left_x self.low_y = low_y self.high_y = high_y self.right_x = right_x def calculate_hpwl(self): h = self.high_y - self.low_y w = self.right_x - self.left_x self.hpwl = h + w def generate_net(self, nets_dict: dict, cells_list: list, nets_index: dict): """ Custom net constructor compatible to info given by file-parsing :param nets_dict: :param cells_list: :param nets_index: :return: """ self.name = nets_index[self.id] tmp = nets_dict[self.name] self.make_cells_list(tmp)

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1,989

3.554007

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0.101961

0.058824

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0.070588

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0.351936

1,989

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0.222222

0

null

0

null

0

1

0

8b12549806fd848f9a9bc11c2c0d0a7049d040eb

2,510

py

Python

appengine_module/gae_ts_mon/handlers.py

mithro/chromium-infra

d27ac0b230bedae4bc968515b02927cf9e17c2b7

[ "BSD-3-Clause" ]

null

appengine_module/gae_ts_mon/handlers.py

mithro/chromium-infra

d27ac0b230bedae4bc968515b02927cf9e17c2b7

[ "BSD-3-Clause" ]

null

appengine_module/gae_ts_mon/handlers.py

mithro/chromium-infra

d27ac0b230bedae4bc968515b02927cf9e17c2b7

[ "BSD-3-Clause" ]

null

# Copyright 2015 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import datetime import logging import webapp2 from google.appengine.ext import ndb from infra_libs.ts_mon import shared from infra_libs.ts_mon.common import interface def find_gaps(num_iter): """Generate integers not present in an iterable of integers. Caution: this is an infinite generator. """ next_num = -1 for n in num_iter: next_num += 1 while next_num < n: yield next_num next_num += 1 while True: next_num += 1 yield next_num def _assign_task_num(time_fn=datetime.datetime.utcnow): expired_keys = [] unassigned = [] used_task_nums = [] time_now = time_fn() expired_time = time_now - datetime.timedelta( seconds=shared.INSTANCE_EXPIRE_SEC) for entity in shared.Instance.query(): # Don't reassign expired task_num right away to avoid races. if entity.task_num >= 0: used_task_nums.append(entity.task_num) # At the same time, don't assign task_num to expired entities. if entity.last_updated < expired_time: expired_keys.append(entity.key) shared.expired_counter.increment() logging.debug( 'Expiring %s task_num %d, inactive for %s', entity.key.id(), entity.task_num, time_now - entity.last_updated) elif entity.task_num < 0: shared.started_counter.increment() unassigned.append(entity) logging.debug('Found %d expired and %d unassigned instances', len(expired_keys), len(unassigned)) used_task_nums = sorted(used_task_nums) for entity, task_num in zip(unassigned, find_gaps(used_task_nums)): entity.task_num = task_num logging.debug('Assigned %s task_num %d', entity.key.id(), task_num) futures_unassigned = ndb.put_multi_async(unassigned) futures_expired = ndb.delete_multi_async(expired_keys) ndb.Future.wait_all(futures_unassigned + futures_expired) logging.debug('Committed all changes') class SendHandler(webapp2.RequestHandler): def get(self): if self.request.headers.get('X-Appengine-Cron') != 'true': self.abort(403) with shared.instance_namespace_context(): _assign_task_num() for name, callback in shared.global_metrics_callbacks.iteritems(): logging.debug('Invoking callback %s', name) callback() app = webapp2.WSGIApplication([ (r'/internal/cron/ts_mon/send', SendHandler), ], debug=True)

29.880952

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2,510

4.831461

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0.045349

0.017442

0.02093

0

0.007866

0.189641

2,510

83

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0.837758

0.149402

0

0.086207

0

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0.012264

0

1

0.051724

false

0

0.103448

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0

null

0

null

0

1

0

8b12e8fd1b8be9f518f4ed422d7d1347bdaadf1c

4,719

py

Python

deepvariant/realigner/window_selector_test.py

ruif2009/deepvariant

c7fd07016577c253f81ef253aed65c416e4c0ef7

[ "BSD-3-Clause" ]

null

deepvariant/realigner/window_selector_test.py

ruif2009/deepvariant

c7fd07016577c253f81ef253aed65c416e4c0ef7

[ "BSD-3-Clause" ]

null

deepvariant/realigner/window_selector_test.py

ruif2009/deepvariant

c7fd07016577c253f81ef253aed65c416e4c0ef7

[ "BSD-3-Clause" ]

1

2022-02-03T21:54:57.000Z

# Copyright 2017 Google Inc. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions # are met: # # 1. Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # # 3. Neither the name of the copyright holder nor the names of its # contributors may be used to endorse or promote products derived from this # software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF # SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. """Tests for deepvariant.realigner.window_selector.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from absl.testing import absltest from third_party.nucleus.protos import range_pb2 from third_party.nucleus.testing import test_utils from deepvariant.protos import realigner_pb2 from deepvariant.realigner.window_selector import WindowSelector class WindowSelectorTest(absltest.TestCase): def test_ws_config(self): return realigner_pb2.RealignerOptions.WindowSelectorOptions( min_num_supporting_reads=2, max_num_supporting_reads=10, min_mapq=20, min_base_quality=20, min_windows_distance=4) def test_process_read(self): """Test WindowSelector.process_read().""" window = WindowSelector(self.test_ws_config()) ref = 'A' * 100 read_1 = test_utils.make_read( 'AAGA', start=10, cigar='4M', quals=[64] * 4, name='read_1') read_2 = test_utils.make_read( 'AAGTA', start=10, cigar='2M2I1M', quals=[64] * 5, name='read_2') read_3 = test_utils.make_read( 'AAA', start=10, cigar='2M2D1M', quals=[64] * 3, name='read_3') read_4 = test_utils.make_read( 'TGATAC', start=10, cigar='2S3M1S', quals=[64] * 6, name='read_4') read_5 = test_utils.make_read( 'AAGA', start=10, cigar='2M1X1M', quals=[64] * 4, name='read_5') self.assertEqual(list(window.process_read(ref, read_1)), [12]) self.assertEqual(list(window.process_read(ref, read_2)), [10, 11, 12, 13]) self.assertEqual(list(window.process_read(ref, read_3)), [12, 13]) self.assertEqual(list(window.process_read(ref, read_4)), [8, 9, 11, 13]) self.assertEqual(list(window.process_read(ref, read_5)), [12]) def test_candidate_pos_low_qual(self): """Test WindowSelector.process_read() with reads of low quality.""" window = WindowSelector(self.test_ws_config()) ref = 'A' * 100 read_1 = test_utils.make_read( 'AAGA', start=10, cigar='4M', quals=[64, 64, 10, 30], name='read_1') read_2 = test_utils.make_read( 'AAGTA', start=10, cigar='2M2I1M', quals=[64, 64, 10, 30, 64], name='read_2') read_3 = test_utils.make_read( 'TGATAC', start=10, cigar='2S3M1S', quals=[64, 10, 64, 64, 64, 64], name='read_3') read_4 = test_utils.make_read( 'AAGA', start=10, cigar='2M1X1M', quals=[64, 64, 30, 10], name='read_4') self.assertEqual(list(window.process_read(ref, read_1)), []) self.assertEqual(list(window.process_read(ref, read_2)), [11, 13]) self.assertEqual(list(window.process_read(ref, read_3)), [8, 11, 13]) self.assertEqual(list(window.process_read(ref, read_4)), [12]) def test_windows(self): """Test WindowSelector.windows().""" window = WindowSelector(self.test_ws_config()) candidates = {0: 2, 2: 4, 3: 11, 8: 3} self.assertEqual( list(window.windows(candidates, 'ref', 0)), [ range_pb2.Range(reference_name='ref', start=-4, end=6), range_pb2.Range(reference_name='ref', start=4, end=12) ]) if __name__ == '__main__': absltest.main()

39

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0.700996

671

4,719

4.757079

0.304024

0.041353

0.059524

0.078321

0.426692

0.384085

0.372807

0.27099

0

0.050649

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4,719

120

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0.119403

0.014925

0.208955

0.014925

0

null

0

null

0

1

0

8b1354634de1b6853d29a1c3908b67f6aae8fd67

1,973

py

Python

myapi.py

madhav06/FastAPI_for_Beginner

5c408f450a4b9e08f4cf9db7f2312e4510c2a151

[ "Apache-2.0" ]

null

myapi.py

madhav06/FastAPI_for_Beginner

5c408f450a4b9e08f4cf9db7f2312e4510c2a151

[ "Apache-2.0" ]

null

myapi.py

madhav06/FastAPI_for_Beginner

5c408f450a4b9e08f4cf9db7f2312e4510c2a151

[ "Apache-2.0" ]

null

from typing import Optional from fastapi import FastAPI, Path from pydantic import BaseModel app = FastAPI() students = { 1: { "name": "john", "age": 17, "year": "year 2019" } } ''' GET - GET an Information POST - Create Something new PUT - Update DELETE - Delete something ''' class Student(BaseModel): name: str age: int year: str class UpdateStudent(BaseModel): name: Optional[str] = None age: Optional[int] = None year: Optional[str] = None @app.get("/") def index(): return { "name": "First Data" } @app.get("/get-student/{student_id}") def get_student(student_id: int = Path(None, description="The ID of the student you want here.", gt=0)): return students[student_id] @app.get("/get-by-name/{student_id}") def get_student(*, student_id:int, name: Optional[str] = None, test: int): for student_id in students: if students[student_id]["name"] == name: return students[student_id] return {"Data": "Not found"} @app.post("/create-student/{student_id}") def create_student(student_id: int, student: Student): if student_id in students: return {"Error": "Student Exists"} students[student_id] = student return students[student_id] @app.put("/update-student/{student_id}") def update_student(student_id: int, student: UpdateStudent): if student_id not in students: return {"Error": "Student does not exists"} if student.name != None: students[student_id].name = student.name if student.age != None: students[student_id].age = student.age if student.year != None: students[student_id].year = student.year return students[student_id] @app.delete("/delete-student/{student_id}") def delete_student(student_id: int): if student_id not in students: return {"Error": "Student does not exists."} del students[student_id] return {"Message": "Student deleted successfully."}

24.974684

104

0.659909

260

1,973

4.896154

0.234615

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0.133543

0.074627

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0

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0.207299

1,973

79

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0.808824

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0

1

0.111111

false

0

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0.037037

0.5

0

null

0

null

0

1

0

8b149868c0ca680e4123557f7080e18cf0b161ce

1,601

py

Python

music/forms.py

amin-da71/Benbb96

0c9e37425d0665e403ba6fecf0c4b17669c29ada

[ "MIT" ]

null

music/forms.py

amin-da71/Benbb96

0c9e37425d0665e403ba6fecf0c4b17669c29ada

[ "MIT" ]

13

2021-02-13T20:15:18.000Z

2022-03-11T23:57:07.000Z

music/forms.py

amin-da71/Benbb96

0c9e37425d0665e403ba6fecf0c4b17669c29ada

[ "MIT" ]

null

from django import forms from django_select2.forms import ModelSelect2Widget, ModelSelect2MultipleWidget from music.models import Lien, LienPlaylist, Musique, Artiste, Style, Playlist class MusiqueForm(forms.ModelForm): class Meta: model = Musique fields = ('titre', 'artiste', 'featuring', 'remixed_by', 'styles', 'album', 'label', 'playlists') widgets = { 'artiste': ModelSelect2Widget(queryset=Artiste.objects.all(), search_fields=['nom_artiste__icontains']), 'featuring': ModelSelect2MultipleWidget( queryset=Artiste.objects.all(), search_fields=['nom_artiste__icontains'] ), 'remixed_by': ModelSelect2Widget(queryset=Artiste.objects.all(), search_fields=['nom_artiste__icontains']), 'styles': ModelSelect2MultipleWidget( queryset=Style.objects.all(), search_fields=['nom__startswith'] ), 'playlists': ModelSelect2MultipleWidget( queryset=Playlist.objects.all(), search_fields=['nom__icontains'], attrs={'data-minimum-input-length': 0} ), } class BaseLienForm(forms.ModelForm): class Meta: fields = ('url', 'plateforme') widgets = { 'url': forms.TextInput(attrs={'class': 'form-control'}), 'plateforme': forms.Select(attrs={'class': 'form-control'}) } class LienForm(BaseLienForm): class Meta(BaseLienForm.Meta): model = Lien class LienPlaylistForm(BaseLienForm): class Meta(BaseLienForm.Meta): model = LienPlaylist

36.386364

119

0.640225

142

1,601

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0

null

0

null

0

1

0

8b165bbd672e68d9449efa107574ea5f5b8f291b

5,231

py

Python

spin/side_to_side_spin.py

otaviocv/spin

04ec49b62a81b973c0553a0f808aa021c5c83294

[ "MIT" ]

null

spin/side_to_side_spin.py

otaviocv/spin

04ec49b62a81b973c0553a0f808aa021c5c83294

[ "MIT" ]

1

2019-10-26T12:42:59.000Z

spin/side_to_side_spin.py

otaviocv/spin

04ec49b62a81b973c0553a0f808aa021c5c83294

[ "MIT" ]

null

"""Side to side SPIN Module.""" import numpy as np from .utils import spin_energy, random_permutation_matrix class SideToSideSPIN(): """Side to side SPIN clustering method. Parameters ---------- random_starts : int, optional (default=5) The number of different initial random permutations that will generated. max_iter : int, optional (default=100) The maximum number of iterations of each round of sorting. verbose : boolean, optional (default=False) Flag indicating to show logs and information during the SPIN process. Attributes ---------- distances_ : array, shape (n, n) The original distances matrix provided. permutation_ : array, shape (n, n) Permutation matrix that can be applied to the original distances matrix to get to the ordered distances matrix. ordered_distances_ : array, shape (n, n) Distances matrix reordered by the permutation matrix. Before run this is the original distance matrix. References ---------- D. Tsafrir, I. Tsafrir, L. Ein-Dor, O. Zuk, D.A. Notterman, E. Domany, Sortiug points into neighborhoods (SPIN): data analysis and visualization by ordering distance matrices, Bioinformatics, Volume 21, Issue 10, , Pages 2301–2308, https://doi.org/10.1093/bioinformatics/bti329 """ def __init__(self, random_starts=5, max_iter=100, verbose=False): self.random_starts = random_starts self.max_iter = max_iter self.verbose = verbose def run(self, X): """Execute the Side To Side sorting. Parameters ---------- X : array, shape (n, n) Returns ------- self : SideToSideSPIN The object itself containing the ordered distances matrix. """ if X.shape[0] != X.shape[1]: raise ValueError("The SPIN method only works with square matrices." f"You provided a matrix of shape {X.shape}.") print("Setup") self.size_ = X.shape[0] self.distances_ = X self.permutation_ = np.identity(self.size_) self.ordered_distances_ = self.permutation_.dot(X) \ .dot(self.permutation_.T) assert np.array_equal(self.distances_, self.ordered_distances_) self.increasing_vector_ = np.array([i-(self.size_+1)/2 for i in range(self.size_)]) \ .reshape(-1, 1) self.weight_matrix_ = self.increasing_vector_ \ .dot(self.increasing_vector_.T) print(self.weight_matrix_) self.energy_ = spin_energy(self.ordered_distances_, self.weight_matrix_) print(f"Initial energy: {self.energy_}") print("Actual spin") for i in range(self.random_starts): initial_permutation = random_permutation_matrix(self.size_) print(initial_permutation[:5, :5]) permutation = side_to_side(self.distances_, self.increasing_vector_, initial_permutation, self.max_iter, self.verbose) if np.array_equal(permutation, initial_permutation): print("They are equal.") ordered_distances = permutation.dot(self.distances_) \ .dot(permutation.T) energy = spin_energy(ordered_distances, self.weight_matrix_) print(f"{i}: {energy}") if energy < self.energy_: self.permutation_ = permutation self.ordered_distances_ = ordered_distances self.energy_ = energy def side_to_side(distances, strictly_increasing_vector, initial_permutation, max_iter=100, verbose=False): """Side To Side SPIN algorithm. Parameters ---------- distances : np.array, shape [n, n] Distance symmetric square matrix. strictly_increasing_vector : np.array, shape [n] A vector with strictly increasing elements with the same dimension as the distance matrix. initial_permutation : array, shape [n ,n] The initial permutation matrix. max_iter : int, default=100 Maximum number of iterations. verbose : bool Verbosity flag, if it is true print useful information about the process. Returns ------- permutation : np.array, shape [n, n] Permutation matrix with the same dimensions of the distance matrix. """ X = strictly_increasing_vector permutation = initial_permutation.copy() for i in range(max_iter): print(".", end="") S = distances.dot(X).flatten() reverse_index_sort = (S).argsort()[::-1] new_permutation = np.identity(distances.shape[0])[reverse_index_sort] if np.all(new_permutation.dot(S) == permutation.dot(S)): break permutation = new_permutation X = permutation.dot(X) return permutation

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0.294828

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0.029314

0.027981

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0.025316

0

0.012882

0.317339

5,231

135

80

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0.827499

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0

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1

0.05

false

0

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0

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0.133333

0

null

0

null

0

1

0

8b16a8a0c1bd81ea5cb86890226cf0055745db26

1,071

py

Python

oocli/entrypoint.py

enigma0Z/python-object-oriented-cli

2122ab0b4ab1bec35f36e9ad8d4437dc3056f484

[ "MIT" ]

null

oocli/entrypoint.py

enigma0Z/python-object-oriented-cli

2122ab0b4ab1bec35f36e9ad8d4437dc3056f484

[ "MIT" ]

null

oocli/entrypoint.py

enigma0Z/python-object-oriented-cli

2122ab0b4ab1bec35f36e9ad8d4437dc3056f484

[ "MIT" ]

null

#!/usr/bin/env python3 """ oocli.entrypoint -------------------- """ import sys from . import base class Command(base.Command): """ Entrypoint - Defines the entrypoint for your program and processes sys.argv into said entrypoint """ def __init__(self, description=None, command=None): super().__init__(name=sys.argv[0], description=description) assert isinstance(command, base.Command) self.command = command def do(self): """ Execute the entrypoint command's .do() method, and translate bool return values for Linux's sanity (0 is true, 1 is false). """ #pylint: disable=arguments-differ returnCode = self.command.do(*sys.argv[1:]) # Translate into zero/nonzero return codes # Linux, zero is true, nonzero is false if isinstance(returnCode, bool): if returnCode: sys.exit(0) else: sys.exit(1) else: # String and int are handled correctly sys.exit(returnCode)

26.775

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0.5

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0.057508

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0.29225

1,071

39

101

27.461538

0.816623

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1

0.125

false

0

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0

0.3125

0

null

0

null

0

1

0

8b1764db3ef7dd93f665da1fea8a6fb564297ced

1,251

py

Python

python plotting/full_apd_time_in_AF_plot.py

pm2111/Heart-Defibrillation-Project

48ea3570c360aac7c3ff46354891998f4f364fab

[ "MIT" ]

null

python plotting/full_apd_time_in_AF_plot.py

pm2111/Heart-Defibrillation-Project

48ea3570c360aac7c3ff46354891998f4f364fab

[ "MIT" ]

null

python plotting/full_apd_time_in_AF_plot.py

pm2111/Heart-Defibrillation-Project

48ea3570c360aac7c3ff46354891998f4f364fab

[ "MIT" ]

null

import numpy as np import matplotlib.pyplot as plt import os path = "0.17_restitution_200_healthy_pacemaker__100000.txt" filenames = [] for f in os.listdir(os.getcwd()): if not f.startswith('.'): filenames.append( "/" + f ) horizontal = 100 L = 200 #system size total_time = 100000. # = os.listdir(path) runs = 4 num_nu = np.size(filenames)/runs nu_min = 0.1 nu_max = .22 fraction = np.zeros((num_nu,runs)) cells = np.zeros((200,200)) j = 0 fib_time = np.zeros(np.size(filenames)) full = np.zeros((2,40)) data = np.genfromtxt(os.getcwd()+"/average_time_in_af.txt") data1 = np.genfromtxt(os.getcwd()+"/average_time_in_af_res1.txt") """np.insert(data,0,np.zeros(8)) np.insert(data,-1,np.zeros(8)) np.insert(data1,0,np.zeros(8)) np.insert(data1,-1,np.zeros(8))""" np.append(data,np.zeros(3)) nu = np.linspace(.09,.22,13) plt.figure() plt.plot(data,"o",label = "no restitution") plt.plot(data1,"o", label = "moderate restitution") plt.legend() plt.xlabel("nu") plt.ylabel("average duration of AF") #plt.title( "Fracion of time spent in excited regime for nu = " ) plt.grid() plt.show() #LOOK FOR: #average duration of episode (counter) #P risk: add column and divide by time (length of array)"""

20.177419

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0.672262

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3.951923

0.442308

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0.05566

0.152678

1,251

61

66

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0.09375

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null

0

null

0

1

0

8b17beb8458cfb645d1fc05c4a70ff154e3e4a58

2,339

py

Python

SIDRE/sort.py

joshwalawender/SIDRE

6f6b78414180c433a7fc4ac504373e1d87501c26

[ "BSD-2-Clause" ]

1

2018-07-08T14:44:24.000Z

SIDRE/sort.py

joshwalawender/SIDRE

6f6b78414180c433a7fc4ac504373e1d87501c26

[ "BSD-2-Clause" ]

null

SIDRE/sort.py

joshwalawender/SIDRE

6f6b78414180c433a7fc4ac504373e1d87501c26

[ "BSD-2-Clause" ]

null

import os import re import ccdproc as ccd import astropy.units as u from astropy import table from .config import get_config def get_ImageFileCollection(filepath): ''' Given a directory path with FITS files in it, use the header keywords (hard coded in this function) to categorize each file as one of: Science: A science exposure Bias: A bias frame Dark: A dark frame Flat: A flat field frame (twilight or dome) Rejected: A file that has been rejection for any reason. Uncategorized: A file which was not categorized as one of the above. A column called "CATEGORY" is added to the `ImageFileCollection.summary` table and populated with a string of the above category. This method can be replaced to customize the code to any particular header or metadata convention. ''' assert os.path.exists(os.path.abspath(filepath)) temperature_deadband = get_config().get('TemperatureDeadband', 1.0) keywords = ['EXPTIME', 'SET-TEMP', 'CCD-TEMP', 'XBINNING', 'YBINNING', 'IMAGETYP', 'OBJECT', 'DATE-OBS'] ifc = ccd.ImageFileCollection(filepath, keywords=keywords) ifc.summary.add_column(table.Column(data=['']*len(ifc.summary), name='CATEGORY', dtype='a12')) for i,entry in enumerate(ifc.summary): tempdiff = float(entry['SET-TEMP']) - float(entry['CCD-TEMP']) if abs(tempdiff) > temperature_deadband: ifc.summary[i]['CATEGORY'] = b'Rejected' elif re.search('Light Frame', entry['IMAGETYP'], flags=re.IGNORECASE): ifc.summary[i]['CATEGORY'] = b'Science' elif re.search('Bias Frame', entry['IMAGETYP'], flags=re.IGNORECASE): ifc.summary[i]['CATEGORY'] = b'Bias' elif re.search('Dark Frame', entry['IMAGETYP'], flags=re.IGNORECASE): ifc.summary[i]['CATEGORY'] = b'Dark' elif re.search('Flat', entry['IMAGETYP'], flags=re.IGNORECASE): ifc.summary[i]['CATEGORY'] = b'Flat' else: ifc.summary[i]['CATEGORY'] = b'Uncategorized' return ifc def get_image_table(filepath, type): ifc = get_ImageFileCollection(filepath) bytype = ifc.summary.group_by('CATEGORY') typelist = bytype.groups[bytype.groups.keys['CATEGORY'] == type] return typelist

38.344262

79

0.652416

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2,339

5.019868

0.423841

0.065963

0.043536

0.075198

0.168206

0.141821

0

0.002219

0.229158

2,339

60

80

38.983333

0.838602

0.273621

0

0.170552

0

0.029412

1

0.058824

false

0

0.176471

0

0.294118

0

null

0

null

0

1

0

8b17d0be018adb93b11563e8419966be49d28784

910

py

Python

server/vo/request/ocr_request_vo.py

sesmond/Detectron

d3f7459fdc0fca2182897fb8acba243010914eb5

[ "Apache-2.0" ]

null

server/vo/request/ocr_request_vo.py

sesmond/Detectron

d3f7459fdc0fca2182897fb8acba243010914eb5

[ "Apache-2.0" ]

null

server/vo/request/ocr_request_vo.py

sesmond/Detectron

d3f7459fdc0fca2182897fb8acba243010914eb5

[ "Apache-2.0" ]

null

class OcrRequest: """ OCR 请求报文 """ # 检测model（ctpn/psenet等） detect_model = '' # 二值化阈值 threshold = None # 是否返回debug图片 do_verbose = False # 是否做文字矫正 do_correct = False # 是否做版面行分析 do_layout = False # 要识别的图片（base64格式） img = '' def __str__(self): return "detect_model:%s," \ "threshold:%r," \ "do_verbose:%r," \ "do_correct:%r," \ "do_layout:%r," \ "img:%r," \ "" % \ (self.detect_model, self.threshold, self.do_verbose, self.do_correct, self.do_layout, len(self.img)) if __name__ == '__main__': req =OcrRequest() req.do_layout=False # req.detect_model="psenet" # print(req.__str__()) # print(req) # logger.info("qingca shu:%s",req)

22.75

38

0.473626

88

910

4.556818

0.454545

0.109726

0.064838

0

0.003636

0.395604

910

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0.041667

false

0

0.041667

0.375

0

null

0

null

0

1

0

8b1846d27ef55491d1f71eac99ddd48f40a267a9

3,819

py

Python

scraping/scraper.py

vnurhaqiqi/scraping-cnbcindonesia-api

eae9842eafec1a578736a7d20829f996382a8ee2

[ "MIT" ]

2

2021-09-09T07:03:55.000Z

2022-02-08T00:44:41.000Z

scraping/scraper.py

vnurhaqiqi/scraping-cnbcindonesia-api

eae9842eafec1a578736a7d20829f996382a8ee2

[ "MIT" ]

1

2022-01-07T01:33:02.000Z

2022-01-07T07:55:40.000Z

scraping/scraper.py

vnurhaqiqi/scraping-cnbcindonesia-api

eae9842eafec1a578736a7d20829f996382a8ee2

[ "MIT" ]

null

from builtins import Exception from bs4 import BeautifulSoup from requests import get from helpers.helpers import * class Scraper(): def scraping_data(self, url): web_data = get(url) if web_data.status_code == 200: soup = BeautifulSoup(web_data.text, 'html.parser') contents = soup.find_all('article') news_data = {'headline': {}, 'total_news': 0, 'news': []} # get headline news headline_content = soup.find('article', id='hl') try: news_data['headline']['title'] = headline_content.find('h1').text news_data['headline']['label'] = headline_content.find('span', class_='label').text headline_release_updated = headline_content.find('span', class_='date') \ .text.replace(news_data['headline']['label'] + ' ', '') news_data['headline']['release_updated'] = headline_release_updated news_data['headline']['url'] = headline_content.find('a', href=True).get('href') news_data['headline']['img_url'] = headline_content.find('img').get('src') except Exception as e: pass # get all news articles for content in contents: try: title = content.find('h2').text news_label = content.find('span', class_='label').text time_desc = content.find('span', class_='date').text.replace(news_label, '').split(' ')[4:8] release_updated = ' '.join(time_desc) news_url = content.find('a', href=True).get('href') img_url = content.find('img').get('src') news_data['news'].append({ 'title': title, 'label': news_label, 'release_updated': release_updated, 'url': news_url, 'img_url': img_url }) except Exception as e: continue news_data['total_news'] = len(news_data['news']) return news_data elif web_data.status_code == 404: return False def get_data_from_page(self, path=None): url_path = SOURCE_URL + path if path else SOURCE_URL res = self.scraping_data(url_path) return res def get_data_by_query(self, query=None): url_path = SOURCE_URL + 'search?query={}'.format(query) if query else SOURCE_URL res = self.scraping_data(url_path) return res def scraping_data_detail(self, url): web_data = get(url) if web_data.status_code == 200: soup = BeautifulSoup(web_data.text, 'html.parser') try: header = soup.find('div', class_='jdl') title = header.find('h1').text author_class = header.find('div', class_='author').text.split(' ') label = author_class[0] author = ' '.join(author_class[2:]) release_date = header.find('div', class_='date').text detail_text_class = soup.find('div', class_='detail_text') texts = detail_text_class.find_all('p') news_content = ' '.join([text.text for text in texts]) news_content_data = { 'title': title, 'label': label, 'author': author, 'release_date': release_date, 'content': news_content } return news_content_data except Exception as e: return {'status': 400} elif web_data.status_code == 404: return False

37.07767

112

0.523959

411

3,819

4.635037

0.218978

0.046194

0.058793

0.035696

0.324409

0.274016

0.24357

0.215223

0.137533

0

0.009764

0.356376

3,819

102

113

37.441176

0.765256

0.010212

0

0.285714

0

0.095843

0

1

0.051948

false

0.012987

0.051948

0

0.207792

0

null

0

null

0

1

0

8b1a95dd21d4df6514b5079162f09a28b0bbc4f9

1,555

py

Python

vkapi/incoming_message.py

kalinochkind/vkbot

306a244cb15745057fd838cd7c3163f0b6754d4b

[ "MIT" ]

39

2015-12-18T20:02:35.000Z

2021-12-01T13:43:08.000Z

vkapi/incoming_message.py

kalinochkind/vkbot

306a244cb15745057fd838cd7c3163f0b6754d4b

[ "MIT" ]

5

2016-01-31T19:33:10.000Z

2017-11-27T04:18:32.000Z

vkapi/incoming_message.py

kalinochkind/vkbot

306a244cb15745057fd838cd7c3163f0b6754d4b

[ "MIT" ]

16

2015-11-21T19:34:36.000Z

2021-05-09T20:30:24.000Z

from .utils import CONF_START, doc_types, cached_property class IncomingMessage: def __init__(self, data, method=''): self.id = data.get('id') self.date = data['date'] self.body = data.get('text', '') self.user_id = data['from_id'] if 'peer_id' in data: self.chat_id = data['peer_id'] - CONF_START if data['peer_id'] > CONF_START else None else: self.chat_id = None self.action = data.get('action') self.attachments = data.get('attachments', []) self._fwd_messages_raw = data.get('fwd_messages', []) if 'reply_message' in data: self._fwd_messages_raw.append(data['reply_message']) self.method = method self.is_sticker = False self.is_voice = False for att in self.attachments: if att['type'] == 'sticker': self.is_sticker = True if att['type'] == 'doc' and att['doc']['type'] == doc_types.AUDIO: self.is_voice = True def _construct_forwarded_message(self, data): return self.__class__(data) @property def peer_id(self): if self.chat_id is not None: return CONF_START + self.chat_id return self.user_id @property def is_chat(self): return self.chat_id is not None @cached_property def fwd_messages(self): fwd_messages = [self._construct_forwarded_message(data) for data in self._fwd_messages_raw] del self._fwd_messages_raw return fwd_messages

32.395833

99

0.604502

204

1,555

4.328431

0.25

0.09966

0.056625

0.08154

0.08607

0.043035

0

0.285531

1,555

47

100

33.085106

0.794779

0

0.051282

0

0.075884

0

1

0.128205

false

0

0.025641

0.051282

0.307692

0

null

0

null

0

1

0

8b1aac57c08259b9336e1a7e93c2b22f68d4fe57

1,759

py

Python

show_data.py

wtyhub/University1652-Baseline

26becc2b73b74bd9e7c7de31f9d7f6baebbd64c8

[ "MIT" ]

41

2021-02-25T11:21:48.000Z

2022-03-15T10:41:04.000Z

show_data.py

gold-pipe/University1652-Baseline

bad3c7555decf8e5213bfdda85dc317057ff3cc2

[ "MIT" ]

5

2021-03-04T12:00:04.000Z

2021-05-06T06:10:21.000Z

show_data.py

gold-pipe/University1652-Baseline

bad3c7555decf8e5213bfdda85dc317057ff3cc2

[ "MIT" ]

1

2022-02-21T07:50:26.000Z

import sys import torch import os import numpy as np from PIL import Image #target_root = 'data/train/drone' #target_root = 'data/train/street' #target_root = 'data/train/satellite' target_root = 'data/train/google' def pad(inp, pad = 3): #print(inp.size) h, w = inp.size bg = np.zeros((h+2*pad, w+2*pad, len(inp.mode))) bg[pad:pad+h, pad:pad+w, :] = inp return bg count = 0 ncol = 20 nrow = 25 npad = 3 im = {} white_col = np.ones( (128+2*npad,24,3))*255 for folder_name in os.listdir(target_root): folder_root = target_root + '/' + folder_name if not os.path.isdir(folder_root): continue for img_name in os.listdir(folder_root): input1 = Image.open(folder_root + '/' + img_name) input1 = input1.convert('RGB') print(folder_root + '/' + img_name) input1 = input1.resize( (128, 128)) # Start testing tmp = pad(input1, pad=npad) if count%ncol == 0: im[count//ncol] = tmp else: im[count//ncol] = np.concatenate((im[count//ncol], white_col, tmp), axis=1) count +=1 if 'drone' in target_root: break if count > nrow*ncol: break first_row = np.ones((128+2*npad,128+2*npad,3))*255 white_row = np.ones( (24,im[0].shape[1],3))*255 for i in range(nrow): if i == 0: pic = im[0] else: pic = np.concatenate((pic, im[i]), axis=0) pic = np.concatenate((pic, white_row), axis=0) #first_row = np.concatenate((first_row, white_col, im[i][0:256+2*npad, 0:256+2*npad, 0:3]), axis=1) #pic = np.concatenate((first_row, white_row, pic), axis=0) pic = Image.fromarray(pic.astype('uint8')) pic.save('sample_%s.jpg'%os.path.basename(target_root)) #pic.save('sample.jpg')

28.836066

103

0.6083

283

1,759

3.678445

0.300353

0.076849

0.053794

0.073007

0.150817

0.055716

0

0.053756

0.22797

1,759

60

104

29.316667

0.712813

0.174531

0

0.086957

0

0.031856

0

1

0.021739

false

0

0.108696

0

0.152174

0.021739

0

null

0

null

0

1

0

8b1ab4cbf0d4db7f695d403b5c435f7c2fa3dae1

4,223

py

Python

csi/controllerserver.py

Madhu-1/kadalu

4243d711ece08c3ac06a9a079628a78cb94f3b1c

[ "Apache-2.0" ]

null

csi/controllerserver.py

Madhu-1/kadalu

4243d711ece08c3ac06a9a079628a78cb94f3b1c

[ "Apache-2.0" ]

null

csi/controllerserver.py

Madhu-1/kadalu

4243d711ece08c3ac06a9a079628a78cb94f3b1c

[ "Apache-2.0" ]

null

""" controller server implementation """ import os import csi_pb2 import csi_pb2_grpc from utils import mount_glusterfs, execute, get_pv_hosting_volumes, \ PV_TYPE_SUBVOL, PV_TYPE_VIRTBLOCK, is_space_available HOSTVOL_MOUNTDIR = "/mnt" GLUSTERFS_CMD = "/usr/sbin/glusterfs" MOUNT_CMD = "/usr/bin/mount" UNMOUNT_CMD = "/usr/bin/umount" MKFS_XFS_CMD = "/usr/sbin/mkfs.xfs" class ControllerServer(csi_pb2_grpc.ControllerServicer): """ ControllerServer object is responsible for handling host volume mount and PV creation. Ref:https://github.com/container-storage-interface/spec/blob/master/spec.md """ def CreateVolume(self, request, context): pvsize = request.capacity_range.required_bytes # TODO: Check the available space under lock host_volumes = get_pv_hosting_volumes() hostvol = "" for hvol in host_volumes: mntdir = os.path.join(HOSTVOL_MOUNTDIR, hvol) # Try to mount the Host Volume, handle failure if already mounted mount_glusterfs(hvol, mntdir) if is_space_available(mntdir, pvsize): hostvol = hvol break if hostvol == "": raise Exception("no Hosting Volumes available, add more storage") pvtype = PV_TYPE_SUBVOL for vol_capability in request.volume_capabilities: # using getattr to avoid Pylint error single_node_writer = getattr(csi_pb2.VolumeCapability.AccessMode, "SINGLE_NODE_WRITER") if vol_capability.access_mode.mode == single_node_writer: pvtype = PV_TYPE_VIRTBLOCK volpath = os.path.join(HOSTVOL_MOUNTDIR, hostvol, pvtype, request.name) if pvtype == PV_TYPE_VIRTBLOCK: # Create a file with required size os.makedirs(os.path.dirname(volpath), exist_ok=True) volpath_fd = os.open(volpath, os.O_CREAT | os.O_RDWR) os.close(volpath_fd) os.truncate(volpath, pvsize) # TODO: Multiple FS support based on volume_capability mount option execute(MKFS_XFS_CMD, volpath) else: # Create a subdir os.makedirs(volpath) # TODO: Set BackendQuota using RPC to sidecar # container of each glusterfsd pod return csi_pb2.CreateVolumeResponse( volume={ "volume_id": request.name, "capacity_bytes": pvsize, "volume_context": { "hostvol": hostvol, "pvtype": pvtype, "fstype": "xfs" } } ) def DeleteVolume(self, request, context): hostvol = request.volume_context.get("hostvol", "") mntdir = os.path.join(HOSTVOL_MOUNTDIR, hostvol) # Try to mount the Host Volume, handle # failure if already mounted mount_glusterfs(hostvol, mntdir) # TODO: get pvtype from storage class pvtype = request.volume_context.get("pvtype", "") volpath = os.path.join(mntdir, pvtype, request.name) if pvtype == PV_TYPE_VIRTBLOCK: os.remove(volpath) else: os.removedirs(volpath) return csi_pb2.DeleteVolumeResponse() def ValidateVolumeCapabilities(self, request, context): # TODO pass def ListVolumes(self, request, context): # TODO # Mount hostvol # Listdir and return the list # Volume capacity need to be stored somewhere pass def ControllerGetCapabilities(self, request, context): # using getattr to avoid Pylint error capability_type = getattr( csi_pb2.ControllerServiceCapability.RPC, "Type").Value return csi_pb2.ControllerGetCapabilitiesResponse( capabilities=[ { "rpc": { "type": capability_type("CREATE_DELETE_VOLUME") } }, { "rpc": { "type": capability_type("LIST_VOLUMES") } } ] )

33.515873

79

0.590339

437

4,223

5.528604

0.370709

0.019868

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0.154387

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0

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0.330571

4,223

125

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33.784

0.851786

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0.061728

false

0.024691

0.049383

0

0.160494

0

null

0

null

0

1

0

8b1ce4d69b758884aef660664de6367d1e512475

2,164

py

Python

cpmpy/among_seq.py

hakank/hakank

313e5c0552569863047f6ce9ae48ea0f6ec0c32b

[ "MIT" ]

279

2015-01-10T09:55:35.000Z

2022-03-28T02:34:03.000Z

cpmpy/among_seq.py

hakank/hakank

313e5c0552569863047f6ce9ae48ea0f6ec0c32b

[ "MIT" ]

10

2017-10-05T15:48:50.000Z

2021-09-20T12:06:52.000Z

cpmpy/among_seq.py

hakank/hakank

313e5c0552569863047f6ce9ae48ea0f6ec0c32b

[ "MIT" ]

83

2015-01-20T03:44:00.000Z

2022-03-13T23:53:06.000Z

""" Global constraint among_seq in cpmpy. From Global constraint catalog: http://www.emn.fr/x-info/sdemasse/gccat/Camong_seq.html ''' Constraint among_seq(LOW,UP,SEQ,VARIABLES,VALUES) Purpose Constrains all sequences of SEQ consecutive variables of the collection VARIABLES to take at least LOW values in VALUES and at most UP values in VALUES. Example ( 1,2,4,<9,2,4,5,5,7,2>, <0,2,4,6,8> ) The among_seq constraint holds since the different sequences of 4 consecutive variables contains respectively 2, 2, 1 and 1 even numbers. ''' Model created by Hakan Kjellerstrand, hakank@hakank.com See also my cpmpy page: http://www.hakank.org/cpmpy/ """ import sys import numpy as np from cpmpy import * from cpmpy.solvers import * from cpmpy_hakank import * def among_seq_test(xval=None): n = 7 # The set as a list v = [0,2,4,6,8] # variables x = intvar(0,9,shape=n,name="x") low = intvar(0,n-1,name="low") high = intvar(0,n-1,name="high") # Note: seqlen cannot be a decision variable since # it's used together with range (in this implementation) # seqlen = intvar(1,n-1,name="seqlen") # low = 1 # high = 2 seqlen = 4 # constraints if xval == None: model = Model([AllDifferent(x), increasing(x), among_seq(low,high,seqlen,x,v), low == 1, high == 2, ]) else: model = Model([x == xval, among_seq(low,high,seqlen,x,v), ]) # ortools_wrapper2(model,[x,[low,high]]) ss = CPM_ortools(model) num_solutions = 0 while ss.solve() is not False: num_solutions += 1 print("x:", x.value()) print("low:",low.value(),"high:",high.value(),"seqlen:",seqlen) get_different_solution(ss,list(x)+[low,high]) print("num_solutions:",num_solutions) print("No fixed x but fixed low=1, high=2, and seqlen=4:") xval = None among_seq_test(xval) xval=[9,2,4,5,5,7,2] print(f"\nFixed x = {xval} . No fixed low or hig. seqlen=4") among_seq_test(xval)

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null

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0

8b1f86bfb12bf0609bdbdbeb6c764ecbc1838d24

1,878

py

Python

Array/Surrounded_Regions.py

shua2018ti/Google

3a9847e0c60d887d15eb4b0d4d8ebf51e464df1b

[ "MIT" ]

87

2015-07-15T20:41:09.000Z

2022-03-08T13:55:38.000Z

Array/Surrounded_Regions.py

shua2018ti/Google

3a9847e0c60d887d15eb4b0d4d8ebf51e464df1b

[ "MIT" ]

59

2015-03-19T22:26:41.000Z

2015-07-25T17:58:08.000Z

Array/Surrounded_Regions.py

shua2018ti/Google

3a9847e0c60d887d15eb4b0d4d8ebf51e464df1b

[ "MIT" ]

45

2015-07-15T20:41:12.000Z

2022-02-01T20:18:07.000Z

''' Given a 2D board containing 'X' and 'O', capture all regions surrounded by 'X'. A region is captured by flipping all 'O's into 'X's in that surrounded region. For example, X X X X X O O X X X O X X O X X After running your function, the board should be: X X X X X X X X X X X X X O X X ''' class Solution: # @param {character[][]} board # @return {void} Do not return anything, modify board in-place instead. def solve(self, board): if not board: return queue = [] m = len(board); n = len(board[0]) for i in xrange(m): self.dfs(i, 0, board, queue) self.dfs(i, n-1, board, queue) for j in xrange(1, n-1): self.dfs(m-1, j, board, queue) self.dfs(0, j, board, queue) for i in xrange(m): for j in xrange(n): if board[i][j] == 'O': board[i][j] = 'X' elif board[i][j] == 'J': board[i][j] = 'O' def dfs(self, x, y, board, queue): self.check(x, y, board, queue) while queue: i, j = queue.pop() self.check(i+1, j, board, queue) # 注意这里不是用dfs,用check self.check(i-1, j, board, queue) self.check(i, j+1, board, queue) self.check(i, j-1, board, queue) def check(self, x, y, board, queue): if x < 0 or x >= len(board) or y < 0 or y >= len(board[0]) or board[x][y] != 'O': return queue.append((x,y)) board[x][y] = 'J' # 解题思路: # instead of go through every node in the board, we only need to go through the edge # of the board, if there is 'O' in the edge, then find all the adjecent 'O', make it # as 'J', then go through the board again, if the 'O', will mark it as 'X', if 'J', # mark it as 'O'

29.34375

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0.51065

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0.046924

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null

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null

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1

0

8b1fe8e9f49cf4b8c60a865d5fd71e372cf52fa6

1,884

py

Python

appengine/components/components/auth/testing.py

maruel/swarming

8ab7568635fcbfd85a01884b64704fc2a1ac13c7

[ "Apache-2.0" ]

74

2015-04-01T02:35:15.000Z

2021-12-17T22:10:56.000Z

appengine/components/components/auth/testing.py

maruel/swarming

8ab7568635fcbfd85a01884b64704fc2a1ac13c7

[ "Apache-2.0" ]

123

2015-04-01T04:02:57.000Z

2022-03-02T12:49:55.000Z

appengine/components/components/auth/testing.py

maruel/swarming

8ab7568635fcbfd85a01884b64704fc2a1ac13c7

[ "Apache-2.0" ]

32

2015-04-03T01:40:47.000Z

2021-11-13T15:20:13.000Z

# Copyright 2019 The LUCI Authors. All rights reserved. # Use of this source code is governed under the Apache License, Version 2.0 # that can be found in the LICENSE file. """Utilities for internal components.auth tests.""" import collections import logging from components.auth import api from components.auth import config from components.auth import delegation from components.auth import model from test_support import test_case # Mocked subset of config tuple returned by config.ensure_configured(). _MockedConfig = collections.namedtuple('_MockedConfig', [ 'USE_PROJECT_IDENTITIES' ]) class TestCase(test_case.TestCase): """Test case with a separate auth context and captured logging.""" # pylint: disable=unused-argument def setUp(self): super(TestCase, self).setUp() api.reset_local_state() self.logged_errors = [] self.mock( logging, 'error', lambda *args, **kwargs: self.logged_errors.append((args, kwargs))) self.logged_warnings = [] self.mock( logging, 'warning', lambda *args, **kwargs: self.logged_warnings.append((args, kwargs))) self.trusted_signers = {'user:token-server@example.com': self} self.mock(delegation, 'get_trusted_signers', lambda: self.trusted_signers) # Implements CertificateBundle interface, as used by get_trusted_signers. def check_signature(self, blob, key_name, signature): return True def mock_config(self, **kwargs): """Mocks result of config.ensure_configured() call.""" self.mock(config, 'ensure_configured', lambda: _MockedConfig(**kwargs)) @staticmethod def mock_group(group, members): """Creates new group entity in the datastore.""" members = [ model.Identity.from_bytes(m) if isinstance(m, basestring) else m for m in members ] model.AuthGroup(key=model.group_key(group), members=members).put()

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false

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0.371429

0

null

0

null

0

1

0

8b23579389559c2d609641d615bb6c487bbe1594

19,397

py

Python

pyNastran/op2/op2_interface/random_results.py

ACea15/pyNastran

5ffc37d784b52c882ea207f832bceb6b5eb0e6d4

[ "BSD-3-Clause" ]

1

2021-08-02T09:49:24.000Z

pyNastran/op2/op2_interface/random_results.py

ACea15/pyNastran

5ffc37d784b52c882ea207f832bceb6b5eb0e6d4

[ "BSD-3-Clause" ]

1

2021-06-07T16:33:59.000Z

pyNastran/op2/op2_interface/random_results.py

ACea15/pyNastran

5ffc37d784b52c882ea207f832bceb6b5eb0e6d4

[ "BSD-3-Clause" ]

1

2021-10-14T03:52:44.000Z

from typing import Dict, Any import numpy as np class RandomObjects: prefix = '' postfix = '' def __init__(self): self.displacements = {} self.velocities = {} self.accelerations = {} self.load_vectors = {} self.spc_forces = {} self.mpc_forces = {} self.crod_force = {} self.conrod_force = {} self.ctube_force = {} self.cbar_force = {} self.cbeam_force = {} self.cbush_stress = {} self.cbush_strain = {} self.crod_stress = {} self.conrod_stress = {} self.ctube_stress = {} self.cbar_stress = {} self.cbeam_stress = {} self.crod_strain = {} self.conrod_strain = {} self.ctube_strain = {} self.cbar_strain = {} self.cbeam_strain = {} self.ctetra_strain = {} self.cpenta_strain = {} self.chexa_strain = {} self.ctetra_stress = {} self.cpenta_stress = {} self.chexa_stress = {} self.celas1_stress = {} self.celas2_stress = {} self.celas3_stress = {} self.celas4_stress = {} self.celas1_strain = {} self.celas2_strain = {} self.celas3_strain = {} self.celas4_strain = {} self.celas1_force = {} self.celas2_force = {} self.celas3_force = {} self.celas4_force = {} self.ctria3_force = {} self.ctria6_force = {} self.ctriar_force = {} self.cquad4_force = {} self.cquad8_force = {} self.cquadr_force = {} self.ctria3_stress = {} self.ctria6_stress = {} self.cquad4_stress = {} self.cquad8_stress = {} self.cquadr_stress = {} self.ctriar_stress = {} self.ctria3_strain = {} self.ctria6_strain = {} self.cquad4_strain = {} self.cquad8_strain = {} self.cquadr_strain = {} self.ctriar_strain = {} self.cbend_stress = {} self.cbend_strain = {} self.cbend_force = {} self.cshear_stress = {} self.cshear_strain = {} self.cshear_force = {} self.cbush_force = {} self.cdamp1_force = {} self.cdamp2_force = {} self.cdamp3_force = {} self.cdamp4_force = {} self.cvisc_force = {} self.cquad4_composite_stress = {} self.cquad8_composite_stress = {} self.cquadr_composite_stress = {} self.ctria3_composite_stress = {} self.ctria6_composite_stress = {} self.ctriar_composite_stress = {} self.cquad4_composite_strain = {} self.cquad8_composite_strain = {} self.cquadr_composite_strain = {} self.ctria3_composite_strain = {} self.ctria6_composite_strain = {} self.ctriar_composite_strain = {} def get_table_types(self): tables = [ 'displacements', 'velocities', 'accelerations', 'load_vectors', 'spc_forces', 'mpc_forces', 'celas1_force', 'celas2_force', 'celas3_force', 'celas4_force', 'crod_force', 'conrod_force', 'ctube_force', 'cbar_force', 'cbeam_force', 'cquad4_force', 'cquad8_force', 'cquadr_force', 'ctria3_force', 'ctria6_force', 'ctriar_force', 'celas1_stress', 'celas2_stress', 'celas3_stress', 'celas4_stress', 'crod_stress', 'conrod_stress', 'ctube_stress', 'cbar_stress', 'cbeam_stress', 'ctria3_stress', 'ctriar_stress', 'ctria6_stress', 'cquadr_stress', 'cquad4_stress', 'cquad8_stress', 'ctetra_stress', 'cpenta_stress', 'chexa_stress', 'celas1_strain', 'celas2_strain', 'celas3_strain', 'celas4_strain', 'crod_strain', 'conrod_strain', 'ctube_strain', 'cbar_strain', 'cbeam_strain', 'ctria3_strain', 'ctriar_strain', 'ctria6_strain', 'cquadr_strain', 'cquad4_strain', 'cquad8_strain', 'ctetra_strain', 'cpenta_strain', 'chexa_strain', 'cquad4_composite_stress', 'cquad8_composite_stress', 'cquadr_composite_stress', 'ctria3_composite_stress', 'ctria6_composite_stress', 'ctriar_composite_stress', 'cquad4_composite_strain', 'cquad8_composite_strain', 'cquadr_composite_strain', 'ctria3_composite_strain', 'ctria6_composite_strain', 'ctriar_composite_strain', 'cbend_stress', 'cbend_strain', 'cbend_force', 'cbush_stress', 'cbush_strain', 'cshear_stress', 'cshear_strain', 'cshear_force', 'cbush_force', 'cdamp1_force', 'cdamp2_force', 'cdamp3_force', 'cdamp4_force', 'cvisc_force', ] return [self.prefix + table + self.postfix for table in tables] class PSDObjects(): """storage class for the ATO objects""" prefix = 'psds.' postfix = '' def __init__(self): self.displacements = {} self.velocities = {} self.accelerations = {} self.spc_forces = {} self.load_vectors = {} self.force = {} self.stress = {} self.strain = {} def get_table_types(self): tables = self._tables() return [self.prefix + table + self.postfix for table in tables] def _tables(self): tables = [ 'displacements', 'velocities', 'accelerations', 'spc_forces', 'load_vectors', 'force', 'stress', 'strain', ] return tables def get_results(self): tables = self._tables() results = {} for table in tables: result = getattr(self, table) if result: results[table] = result return results def get_stats(self, short=True): msg = '' psds_dict = self.get_results() for result_type, slot in psds_dict.items(): npsds = len(slot) if short: msg += f'op2_results.psds.{result_type}; n={npsds}\n' else: ipsd = 0 msg += f'op2_results.psds.{result_type}:\n' msg += f' # (subtitle, analysis_code, stress_strain_flag, node, dof)\n' for key in slot: msg += f' {key}\n' if ipsd == 10: msg += f' ... npsds={npsds}\n' break ipsd += 1 msg += '\n' return msg def get_psds_by_subtitles(self) -> Dict[Any, Any]: psd_results = self.get_results() if not psd_results: return {} from collections import defaultdict psds_subtitle = defaultdict(dict) for res_type, psds in psd_results.items(): for key, psd in psds.items(): (subtitle, nid, dof) = key psds_subtitle[subtitle][(res_type, nid, dof)] = psd return psds_subtitle def plot(self): psds_subtitle = self.get_psds_by_subtitles() if not psds_subtitle: return import matplotlib.pyplot as plt for subtitle, psds in psds_subtitle.items(): fig = plt.figure(1) for (res_type, nid, dof), psd in psds.items(): freqs, psd = psd[:, 0], psd[:, 1] plt.plot(freqs, psd, name=f'(restype,nid,dof)=({res_type}, {nid}, {dof})') plt.legend() plt.show() def write_f06(self, f06): psds_subtitle = self.get_psds_by_subtitles() if not psds_subtitle: return psd_type_map = { 'displacements' : 'DISP', 'velocities' : 'VELO', 'accelerations' : 'ACCE', 'load_vectors' : 'OLOAD', 'spc_forces' : 'SPCF', 'force' : 'EL FOR', 'stress' : 'EL STR', 'strain' : 'STRAIN', } from scipy.integrate import trapz for subtitle, psds in psds_subtitle.items(): f06.write(subtitle + '\n') f06.write('0 X Y - O U T P U T S U M M A R Y ( A U T O O R P S D F )\n') f06.write('0 PLOT CURVE FRAME CURVE ID./ RMS NO. POSITIVE XMIN FOR XMAX FOR YMIN FOR X FOR YMAX FOR X FOR*\n') f06.write(' TYPE TYPE NO. PANEL : GRID ID VALUE CROSSINGS ALL DATA ALL DATA ALL DATA YMIN ALL DATA YMAX\n') #fig = plt.figure(1) for (res_type, nid, dof), psd in psds.items(): try: psd_type = psd_type_map[res_type] except KeyError: raise NotImplementedError(f'res_type = {res_type}') #psd_type = analysis_code #rms_value = 2.879461E+00 #no_crossings = 2.879461E+00 #no_crossings = np.nan freqs, psd = psd[:, 0], psd[:, 1] #plt.plot(freqs, psd, name=f'(restype,nid,dof)=({res_type}, {nid}, {dof})') ymin = psd.min() ymax = psd.max() imin = np.where(psd == ymin)[0][0] imax = np.where(psd == ymax)[0][0] xmin = freqs[imin] xmax = freqs[imax] fmin = freqs.min() fmax = freqs.max() # If you want the RMS value, this is computed as RMS = SQRT(SUM(PSD*DF)) and, # where DF is the spectral resolution, where you integarate from Fmin to Fmax, # i.e. your lowest and highest analysis frequency of interest, respectively. psd_f = trapz(psd, freqs) rms = psd_f ** 0.5 if psd_f == 0.0: # really this is nan, but that's Nastran for you no_crossings = 0.0 else: f2_psd_f = trapz(freqs**2 * psd, freqs) no_crossings = (f2_psd_f / psd_f) ** 0.5 # Hz #print('ymin=%s ymax=%s xmin=%s xmax=%s fmin=%s fmax=%s' % (ymin, ymax, xmin, xmax, fmin, fmax)) #'0 X Y - O U T P U T S U M M A R Y ( A U T O O R P S D F )' #'0 PLOT CURVE FRAME CURVE ID./ RMS NO. POSITIVE XMIN FOR XMAX FOR YMIN FOR X FOR YMAX FOR X FOR*' #' TYPE TYPE NO. PANEL : GRID ID VALUE CROSSINGS ALL DATA ALL DATA ALL DATA YMIN ALL DATA YMAX' #' PSDF ACCE 0 9400703( 5) 2.879461E+00 8.191217E+02 2.000E+01 2.000E+03 4.476E-06 7.900E+01 1.474E+00 3.980E+01' f06.write('0 \n') f06.write(f' PSDF {psd_type:6s} 0 {nid:8d}( {dof:2d}) {rms:8.6E} {no_crossings:9.6E} {fmin:9.3E} {fmax:9.3E} {ymin:9.3E} {xmin:9.3E} {ymax:9.3E} {xmax:9.3E}\n') #plt.legend() #plt.show() class AutoCorrelationObjects(RandomObjects): """storage class for the ATO objects""" prefix = 'ato.' #postfix = '' class PowerSpectralDensityObjects(RandomObjects): """storage class for the PSD objects""" prefix = 'psd.' #postfix = '' class RootMeansSquareObjects(RandomObjects): """storage class for the RMS objects""" prefix = 'rms.' #postfix = '' class CumulativeRootMeansSquareObjects(RandomObjects): """storage class for the CRMS objects""" prefix = 'crm.' #postfix = '' class NumberOfCrossingsObjects(RandomObjects): """storage class for the NO objects""" prefix = 'no.' #postfix = '' class RAECONS: """storage class for the RAECONS objects""" def __init__(self): self.ctria3_strain = {} self.cquad4_strain = {} self.chexa_strain = {} def get_table_types(self): tables = [ 'chexa_strain', 'ctria3_strain', 'cquad4_strain', ] return ['RAECONS.' + table for table in tables] class RASCONS: """storage class for the RASCONS objects""" def __init__(self): self.ctetra_stress = {} self.cpenta_stress = {} self.chexa_stress = {} self.ctetra_strain = {} self.cpenta_strain = {} self.chexa_strain = {} self.ctria3_stress = {} self.ctria6_stress = {} self.cquad4_stress = {} self.cquad8_stress = {} self.cquadr_stress = {} self.ctriar_stress = {} self.ctria3_strain = {} self.ctria6_strain = {} self.cquad4_strain = {} self.cquad8_strain = {} self.cquadr_strain = {} self.ctriar_strain = {} def get_table_types(self): tables = [ # OES - isotropic CTRIA3/CQUAD4 stress 'ctria3_stress', 'ctriar_stress', 'ctria6_stress', 'cquadr_stress', 'cquad4_stress', 'cquad8_stress', # OES - isotropic CTRIA3/CQUAD4 strain 'ctria3_strain', 'ctriar_strain', 'ctria6_strain', 'cquadr_strain', 'cquad4_strain', 'cquad8_strain', 'ctetra_stress', 'chexa_stress', 'cpenta_stress', 'ctetra_strain', 'chexa_strain', 'cpenta_strain', ] return ['RASCONS.' + table for table in tables] class RAPCONS: """storage class for the RAPCONS objects""" def __init__(self): self.cquad4_composite_stress = {} self.cquad8_composite_stress = {} self.cquadr_composite_stress = {} self.ctria3_composite_stress = {} self.ctria6_composite_stress = {} self.ctriar_composite_stress = {} def get_table_types(self): tables = [ 'cquad4_composite_stress', 'cquad8_composite_stress', 'cquadr_composite_stress', 'ctria3_composite_stress', 'ctria6_composite_stress', 'ctriar_composite_stress', #'cquad4_composite_strain', #'cquad8_composite_strain', #'cquadr_composite_strain', #'ctria3_composite_strain', #'ctria6_composite_strain', #'ctriar_composite_strain', ] return ['RAPCONS.' + table for table in tables] class RAPEATC: """storage class for the RAPEATC objects""" def __init__(self): self.cquad4_composite_stress = {} self.cquad8_composite_stress = {} self.cquadr_composite_stress = {} self.ctria3_composite_stress = {} self.ctria6_composite_stress = {} self.ctriar_composite_stress = {} def get_table_types(self): tables = [ 'cquad4_composite_stress', 'cquad8_composite_stress', 'cquadr_composite_stress', 'ctria3_composite_stress', 'ctria6_composite_stress', 'ctriar_composite_stress', #'cquad4_composite_strain', #'cquad8_composite_strain', #'cquadr_composite_strain', #'ctria3_composite_strain', #'ctria6_composite_strain', #'ctriar_composite_strain', ] return ['RAPEATC.' + table for table in tables] class RAFCONS: """storage class for the RAFCONS objects""" def __init__(self): self.cbar_force = {} self.cquad4_force = {} self.cbush_force = {} def get_table_types(self): tables = [ 'cbar_force', 'cquad4_force', 'cbush_force', ] return ['RAFCONS.' + table for table in tables] class RAGCONS: """storage class for the RAGCONS objects""" def __init__(self): self.grid_point_forces = {} def get_table_types(self): tables = [ 'grid_point_forces', ] return ['RAGCONS.' + table for table in tables] class RAGEATC: """storage class for the RAGEATC objects""" def __init__(self): self.grid_point_forces = {} def get_table_types(self): tables = [ 'grid_point_forces', ] return ['RAGEATC.' + table for table in tables] class RANCONS: """storage class for the RANCONS objects""" def __init__(self): self.cbar_strain_energy = {} self.cbush_strain_energy = {} self.chexa_strain_energy = {} self.ctria3_strain_energy = {} self.cquad4_strain_energy = {} def get_table_types(self): tables = [ 'cbar_strain_energy', 'cbush_strain_energy', 'chexa_strain_energy', 'ctria3_strain_energy', 'cquad4_strain_energy', ] return ['RANCONS.' + table for table in tables] class RADEFFM: """storage class for the RADEFFM objects""" def __init__(self): self.eigenvectors = {} def get_table_types(self): tables = [ 'eigenvectors', ] return ['RADEFFM.' + table for table in tables] class RADCONS: def __init__(self): self.eigenvectors = {} def get_table_types(self): tables = [ 'eigenvectors', ] return ['RADCONS.' + table for table in tables] class RADEATC: """storage class for the RADEATC objects""" def __init__(self): self.eigenvectors = {} def get_table_types(self): tables = [ 'eigenvectors', ] return ['RADEATC.' + table for table in tables] class RANEATC: """storage class for the RANEATC objects""" def __init__(self): self.cbar_strain_energy = {} self.cbush_strain_energy = {} self.chexa_strain_energy = {} self.ctria3_strain_energy = {} self.cquad4_strain_energy = {} def get_table_types(self): tables = [ 'cbar_strain_energy', 'cbush_strain_energy', 'chexa_strain_energy', 'ctria3_strain_energy', 'cquad4_strain_energy', ] return ['RANEATC.' + table for table in tables] class ROUGV1: """storage class for the ROUGV1 objects""" def __init__(self): self.displacements = {} self.velocities = {} self.accelerations = {} self.eigenvectors = {} def get_table_types(self): tables = [ 'displacements', 'velocities', 'accelerations', 'eigenvectors', ] return ['ROUGV1.' + table for table in tables] class RAFEATC: """storage class for the RAFEATC objects""" def __init__(self): self.cbar_force = {} self.cquad4_force = {} self.cbush_force = {} def get_table_types(self): tables = [ 'cbar_force', 'cquad4_force', 'cbush_force', ] return ['RAFEATC.' + table for table in tables] class RASEATC: """storage class for the RASEATC objects""" def __init__(self): self.chexa_stress = {} self.cquad4_stress = {} def get_table_types(self): tables = [ 'chexa_stress', 'cquad4_stress', ] return ['RASEATC.' + table for table in tables] class RAEEATC: """storage class for the RAEEATC objects""" def __init__(self): self.chexa_strain = {} self.ctria3_strain = {} self.cquad4_strain = {} def get_table_types(self): tables = [ 'chexa_strain', 'ctria3_strain', 'cquad4_strain', ] return ['RAEEATC.' + table for table in tables]

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0.232143

0

null

0

null

0

1

0

8b24c9cba2b46c498766a19c58c260ffa0ca6a3b

6,656

py

Python

src/data/prepare_language_modelling.py

abrinkmann/productCategorization

75732e4b1c9da941a793db80b5fe2245bae45e87

[ "MIT" ]

5

2021-06-24T12:12:17.000Z

2022-01-22T08:19:30.000Z

src/data/prepare_language_modelling.py

abrinkmann/productCategorization

75732e4b1c9da941a793db80b5fe2245bae45e87

[ "MIT" ]

null

src/data/prepare_language_modelling.py

abrinkmann/productCategorization

75732e4b1c9da941a793db80b5fe2245bae45e87

[ "MIT" ]

1

2022-03-11T16:00:13.000Z

import logging import os from pathlib import Path import click import pandas as pd from src.data.preprocessing import preprocess @click.command() @click.option('--dataset_name', help='Dataset which you like to prepare for language modelling') @click.option('--additional_ds_path', help='Additional dataset for language modelling') @click.option('--additional_ds_suffix', help='Suffix to identify the additional ds') def main(dataset_name, additional_ds_path, additional_ds_suffix): """ Runs data processing scripts to turn raw data from (../raw) into cleaned data ready to be analyzed (saved in ../processed). """ dataset = load_dataset(dataset_name) #Check if additional dataset information is provided if not (additional_ds_path is None) and not (additional_ds_suffix is None): df_additional_ds = pd.read_csv(additional_ds_path, sep=';') else: df_additional_ds = None generate_datasets_for_language_modelling(dataset, dataset_name, df_additional_ds, additional_ds_suffix) def load_dataset(dataset_name): """Load dataset for the given experiments""" logger = logging.getLogger(__name__) data_dir = os.environ['DATA_DIR'] data_dir = Path(data_dir) splits = ['train', 'validate'] dataset = {} for split in splits: relative_path = 'data/processed/{}/split/raw/{}_data_{}.pkl'.format(dataset_name, split, dataset_name) file_path = data_dir.joinpath(relative_path) dataset[split] = pd.read_pickle(file_path) logger.info('Loaded dataset {}!'.format(dataset_name)) return dataset def generate_datasets_for_language_modelling(dataset, dataset_name, df_additional_ds, additional_ds_suffix): logger = logging.getLogger(__name__) data_dir = os.environ['DATA_DIR'] data_dir = Path(data_dir) configurations = [] config_1 = {'category': True, 'category_reverse': False, 'description': True, 'multiple_rows': True, 'additional_ds': True} configurations.append(config_1) for config in configurations: # Make sure that an additional dataset is properly provided if requested if df_additional_ds is None and additional_ds_suffix: config['additional_ds'] = False generate_and_store_single_dataset_for_language_modelling(dataset, dataset_name, data_dir, config, df_additional_ds, additional_ds_suffix) def generate_and_store_single_dataset_for_language_modelling(dataset, dataset_name, data_dir, config, df_additional_ds, additional_ds_suffix): logger = logging.getLogger(__name__) suffix = 'title' for key in config: if config[key]: suffix = '{}_{}'.format(suffix, key) if not (additional_ds_suffix is None) and config['additional_ds']: suffix = '{}_{}'.format(suffix, additional_ds_suffix) for split in dataset: relative_path = 'data/processed/{}/language-modelling/{}_language_modelling_{}_with_{}.txt'.format(dataset_name, split, dataset_name, suffix) file_path = data_dir.joinpath(relative_path) with open(file_path, 'w') as file: for index, row in dataset[split].iterrows(): #preprocess values prep_title = preprocess(row['title']) line = '{}'.format(prep_title) if config['category']: categories = row['path_list'].split('>') categories = [value.split('_')[1] for value in categories] categories = [preprocess(value) for value in categories] new_line = prepare_category(config,categories,line) if config['multiple_rows']: write_dataset_to_file(file,new_line) else: line = new_line if config['description']: new_line = prepare_description(row['description'], line) if config['multiple_rows']: write_dataset_to_file(file, new_line) else: line = new_line if not config['multiple_rows']: write_dataset_to_file(file, line) if split == 'train' and config['additional_ds']: for index, row in df_additional_ds.iterrows(): line = preprocess(row['Title']) categories = [] if row['Category'] is not None and type(row['Category']) is str: categories.append(row['Category']) if row['Breadcrumb'] is not None and type(row['Breadcrumb']) is str: categories.append(row['Breadcrumb']) if row['BreadcrumbList'] is not None and type(row['BreadcrumbList']) is str: categories.append(row['BreadcrumbList']) if len(categories) > 0 and config['category']: new_line = prepare_category(config, categories, line) if config['multiple_rows']: write_dataset_to_file(file, new_line) else: line = new_line if type(row['Description']) is str and config['description']: new_line = prepare_description(row['Description'], line) if config['multiple_rows']: write_dataset_to_file(file, new_line) else: line = new_line file.write('{}\n'.format(line)) logger.info('File {} created for Language Modelling!'.format(relative_path)) def prepare_category(config, categories, line): if config['category_reverse']: categories.reverse() prep_catgories = ' '.join(categories) new_line = '{} - {}'.format(line, prep_catgories) return new_line def prepare_description(description, line): description_values = description.split('.') preprocessed_description_values = [] for value in description_values: if len(value) > 4: preprocessed_description_values.append(preprocess(value)) new_line = '{} - {}'.format(line, '. '.join(preprocessed_description_values)) return new_line def write_dataset_to_file(file, line): line = '{}\n'.format(line) file.write(line) if __name__ == '__main__': log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s' logging.basicConfig(level=logging.INFO, format=log_fmt) main()

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0.135593

0

null

0

null

0

1

0

8b25f4fb270018c7e67c4a8b1dfad4619b36e0e5

1,591

py

Python

demo_01/01_Sensors.py

vcubells/iot_supermercado

9b850fcd971fd5053515cc16c0834bf836af6155

[ "MIT" ]

3

2019-10-29T14:27:35.000Z

2022-01-20T23:29:16.000Z

demo_01/01_Sensors.py

vcubells/iot_supermercado

9b850fcd971fd5053515cc16c0834bf836af6155

[ "MIT" ]

2

2019-10-28T03:30:12.000Z

2021-06-02T00:31:56.000Z

demo_02/01_Sensors.py

vcubells/iot_supermercado

9b850fcd971fd5053515cc16c0834bf836af6155

[ "MIT" ]

1

2019-10-31T17:24:49.000Z

import RPi.GPIO as GPIO import time import pyrebase import subprocess from datetime import datetime from pprint import pprint import sys import time import Adafruit_DHT # Configuracion del tipo de sensor DHT sensor = Adafruit_DHT.DHT11 #humedad pin = 23 #button camera chanel = 10 #led_pin led_pin=12 #button presencia alimento chanelFood = 8 flagFood = False GPIO.setwarnings(False) # Ignore warning for now GPIO.setmode(GPIO.BOARD) # Use physical pin numbering GPIO.setup(chanel, GPIO.IN, pull_up_down=GPIO.PUD_DOWN) # Set pin 10 to be an input pin and set initial value to be pulled low (off) GPIO.setup(led_pin, GPIO.OUT) def callbackCamera(chanel): if GPIO.input(chanel) == GPIO.HIGH: subprocess.call(['fswebcam -r 640x480 --no-banner /home/pi/Desktop/image.jpg', '-1'], shell=True) #delete photo. #subprocess.call(['rm /home/pi/Desktop/image.jpg', '-1'], shell=True) def humCallback(pin): humedad, temperatura = Adafruit_DHT.read_retry(sensor, pin) if temperatura >21: GPIO.output(led_pin, GPIO.HIGH) else: GPIO.output(led_pin, GPIO.LOW) def button_callback(): print(flagFood) if GPIO.input(8) == 0 and flagFood == False: print("Slot 1: Vacio") self.flagFood = True time.sleep(1) if GPIO.input(8) == 1 and flagFood == False: flagFood = True print("Slot 1: Coca-Cola") time.sleep(1) while True: humCallback(pin) button_callback()

27.912281

145

0.638592

215

1,591

4.660465

0.465116

0.02994

0.035928

0.101796

0.061876

0

0.024681

0.261471

1,591

56

146

28.410714

0.828085

0.184789

0

0.097561

0

0.069984

0.020218

0

1

0.073171

false

0

0.219512

0

0.292683

0.097561

0

null

0

null

0

1

0

8b27a2fec3b8fe8db08bac8d780a90de627046a6

1,152

py

Python

app.py

w-lindvall/weather_check

78881a0901da8f363b4e53378c4d70cdba02263f

[ "MIT" ]

null

app.py

w-lindvall/weather_check

78881a0901da8f363b4e53378c4d70cdba02263f

[ "MIT" ]

null

app.py

w-lindvall/weather_check

78881a0901da8f363b4e53378c4d70cdba02263f

[ "MIT" ]

null

import datetime from time import sleep import dht11 from picamera import PiCamera import RPi.GPIO as GPIO # initialize GPIO GPIO.setwarnings(False) GPIO.setmode(GPIO.BCM) GPIO.cleanup() camera = PiCamera() check = dht11.DHT11(pin=17) # set output pin number to match setup while True: result = check.read() if result.is_valid(): camera.start_preview() sleep(5) # wait 5 seconds to allow for camera to correct exposure camera.annotate_text = (datetime.datetime.now().strftime('%d-%m-%y %H:%M') + '\n' + '=' * 20 + '\n' + '-{} C'.format(result.temperature) + '\n' + '-{}%'.format(result.humidity)) camera.capture(('/home/pi/Desktop/{}.jpg' .format('weather_check-' + datetime.datetime.now().strftime( '%d_%m_%y-%H_%M')))) camera.stop_preview() sleep(255) # wait about 5 minutes until next loop

31.135135

82

0.490451

119

1,152

4.680672

0.579832

0.050269

0.068223

0.096948

0.114901

0

0.022792

0.390625

1,152

36

83

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0.022931

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1

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false

0

0.178571

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0.178571

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null

0

null

0

1

0

8b2a4d307a290f21bfe4f3c97478d6f00ddefec6

4,621

py

Python

test-backend.py

Drazcmd/Comp431BackendFinal

767c79b1e00172ce1be895ac01af832a4684d516

[ "MIT" ]

null

test-backend.py

Drazcmd/Comp431BackendFinal

767c79b1e00172ce1be895ac01af832a4684d516

[ "MIT" ]

null

test-backend.py

Drazcmd/Comp431BackendFinal

767c79b1e00172ce1be895ac01af832a4684d516

[ "MIT" ]

null

#!/usr/bin/env python import requests, json, sys, pprint pp = pprint.PrettyPrinter(indent=4) class cc: HEADER = '\033[95m' BLUE = '\033[94m' GREEN = '\033[92m' YELLOW = '\033[93m' FAIL = '\033[91m' ENDC = '\033[0m' BOLD = '\033[1m' UNDERLINE = '\033[4m' def get(endpoint): url = config["backend"] + endpoint r = requests.get(url) if r.status_code != 200: print(cc.FAIL + ("ERROR: For GET %s received %d response code " % (endpoint, r.status_code)) + str(r.text) + cc.ENDC) sys.exit(1) return json.loads(r.text) def put(endpoint): url = config["backend"] + endpoint r = requests.put(url) if r.status_code != 200: print(cc.FAIL + ("ERROR: For PUT %s received %d response code " % (endpoint, r.status_code)) + str(r.text) + cc.ENDC) sys.exit(1) return json.loads(r.text) def getArticles(articleId=None): endpoint = '/articles' if articleId is not None: endpoint = (endpoint + "/%d") % articleId return checkArticles(get(endpoint)) def checkArticles(result): if "articles" not in result: print(cc.FAIL + "ERROR: GET /articles did not have \"articles\" entry" + cc.ENDC) print(result) return [] else: return result["articles"] def addArticle(body): r = requests.post(config["backend"] + "/article", json={'text':body}) return checkArticles( json.loads(r.text) ) def msg(message): print(cc.BLUE + message + cc.ENDC) ################################################ if len(sys.argv) < 2: print("usage: %s README.json" % sys.argv[0]) sys.exit(1) with open(sys.argv[1], 'r') as f: config = json.loads(f.read()) for key in config.keys(): if config[key].endswith('/'): config[key] = (config[key])[:-1] print(cc.YELLOW + ("Checking for %s site %s" % (config['netid'], config['backend'])) + cc.ENDC) ###################################### # inital GET r = get("/") msg("GET /") pp.pprint(r) # GET /articles articles = getArticles() msg("GET /articles") pp.pprint(articles) if len(articles) < 3: print(cc.FAIL + ("FAIL: Expected at least 3 articles from GET /articles but found %d " % len(articles)) + cc.ENDC) else: print(cc.GREEN + ("OK: GET /articles returned %d articles, expecting at least 3" % len(articles)) + cc.ENDC) ###################################### # add a new article body = "Hello World!" newArticles = addArticle(body) msg("POST /article -d " + body) pp.pprint(newArticles) if len(newArticles) is not 1: print(cc.FAIL + ("FAIL: Expected 1 new article added but found %d articles" % len(newArticles)) + cc.ENDC) else: newArticleId = newArticles[0]['id'] print(cc.GREEN + ("OK: POST /article returned one new article with id=%d" % newArticleId) + cc.ENDC) if newArticles[0]['text'] != body: print(cc.FAIL + ("FAIL: Article did not have the correct body message: %s vs %s" % (newArticles[0]['text'], body)) + cc.ENDC) else: print(cc.GREEN + ("OK: article body was correct") + cc.ENDC) ###################################### # get that new article by itself getNewArticle = getArticles(newArticleId) msg("GET /articles/%d" % newArticleId) pp.pprint(getNewArticle) if len(getNewArticle) is not 1: print(cc.FAIL + ("FAIL: Expected to get the one article that was added but found %d articles" % len(getNewArticle)) + cc.ENDC) else: print(cc.GREEN + ("OK: GET /articles/%d got the new article" % newArticleId) + cc.ENDC) if getNewArticle[0]['text'] != newArticles[0]['text'] or newArticles[0]['text'] != body: print(cc.FAIL + ("FAIL: Article did not have the correct text message: %s" % getNewArticle[0]['text']) + cc.ENDC) else: print(cc.GREEN + ("OK: article text was correct") + cc.ENDC) ###################################### # confirm that we only added one article articles2 = getArticles() msg("GET /articles") pp.pprint(articles2) if len(articles2) is not len(articles) + 1: print(cc.FAIL + ("FAIL: Expected one new article added but found %d + 1 = %d" % (len(articles), len(articles2))) + cc.ENDC) else: print(cc.GREEN + ("OK: GET /articles returned one additional article") + cc.ENDC) ###################################### print(cc.YELLOW + ('Testing stubs...') + cc.ENDC) # Stubs for e in [ "/headlines", "/headlines/"+config['netid'], "/email", "/email/"+config['netid'], "/zipcode", "/zipcode/"+config['netid'], "/avatars", "/avatars/" + config['netid'] ]: msg("GET " + e) pp.pprint(get(e)) ## done print(cc.YELLOW + ('COMPLETE!') + cc.ENDC)

35.007576

178

0.591863

615

4,621

4.44065

0.226016

0.0487

0.03625

0.032955

0.332845

0.318198

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0.167704

0

0.018853

0.196494

4,621

131

179

35.274809

0.716671

0.031162

0

0.185567

0

0.273759

0

1

0.061856

false

0

0.010309

0

0.226804

0.298969

0

null

0

null

0

1

0

8b2b29b944bd51adeeab734c224ec38b5ca49934

1,553

py

Python

robustbench/eval.py

dedeswim/robustbench

afdaaab9ddd89bc689420b6a9ee7a48d98defc4d

[ "MIT" ]

1

2020-11-14T10:18:38.000Z

robustbench/eval.py

GeoffNN/robustbench

34e5f426266bf78d72e149efdade7f32622aff19

[ "MIT" ]

null

robustbench/eval.py

GeoffNN/robustbench

34e5f426266bf78d72e149efdade7f32622aff19

[ "MIT" ]

null

import argparse import torch from robustbench.utils import load_model, clean_accuracy from robustbench.data import load_cifar10 def parse_args(): parser = argparse.ArgumentParser() parser.add_argument('--model_name', type=str, default='Carmon2019Unlabeled') parser.add_argument('--norm', type=str, default='Linf') parser.add_argument('--eps', type=float, default=8/255) parser.add_argument('--n_ex', type=int, default=100, help='number of examples to evaluate on') parser.add_argument('--batch_size', type=int, default=500, help='batch size for evaluation') parser.add_argument('--data_dir', type=str, default='./data', help='where to store downloaded datasets') parser.add_argument('--model_dir', type=str, default='./models', help='where to store downloaded models') parser.add_argument('--device', type=str, default='cuda:0', help='device to use for computations') args = parser.parse_args() return args if __name__ == '__main__': args = parse_args() device = torch.device(args.device) x_test, y_test = load_cifar10(args.n_ex, args.data_dir) x_test, y_test = x_test.to(device), y_test.to(device) model = load_model(args.model_name, args.model_dir, args.norm).to(device).eval() acc = clean_accuracy(model, x_test, y_test, batch_size=args.batch_size, device=device) print('Clean accuracy: {:.2%}'.format(acc)) adversary = AutoAttack(model, norm=args.norm, eps=args.eps, version='standard', device=device) x_adv = adversary.run_standard_evaluation(x_test, y_test)

43.138889

109

0.722473

224

1,553

4.790179

0.330357

0.067102

0.126747

0.037279

0.048462

0

0.014859

0.13329

1,553

35

110

44.371429

0.782318

0

0.196394

0

1

0.038462

false

0

0.153846

0

0.230769

0.038462

0

null

0

null

0

1

0

8b2bd46ff544bd973934ac2848e266641de5778e

12,943

py

Python

neutron_lbaas/tests/unit/drivers/octavia/test_octavia_driver.py

bdrich/neutron-lbaas

b4711abfe0207c4fdd5d7fb7ecbf017e753abbfd

[ "Apache-2.0" ]

null

neutron_lbaas/tests/unit/drivers/octavia/test_octavia_driver.py

bdrich/neutron-lbaas

b4711abfe0207c4fdd5d7fb7ecbf017e753abbfd

[ "Apache-2.0" ]

null

neutron_lbaas/tests/unit/drivers/octavia/test_octavia_driver.py

bdrich/neutron-lbaas

b4711abfe0207c4fdd5d7fb7ecbf017e753abbfd

[ "Apache-2.0" ]

null

# Copyright 2015, Banashankar Veerad, Copyright IBM Corporation # # 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 mock from oslo_config import cfg from neutron import context from neutron_lbaas.drivers.octavia import driver from neutron_lbaas.services.loadbalancer import data_models from neutron_lbaas.tests.unit.db.loadbalancer import test_db_loadbalancerv2 class ManagerTest(object): def __init__(self, parent, manager, mocked_req): self.parent = parent self.context = parent.context self.driver = parent.driver self.manager = manager self.mocked_req = mocked_req def create(self, model, url, args): self.manager.create(self.context, model) self.mocked_req.post.assert_called_with(url, args) def update(self, old_model, model, url, args): self.manager.update(self.context, old_model, model) self.mocked_req.put.assert_called_with(url, args) def delete(self, model, url): self.manager.delete(self.context, model) self.mocked_req.delete.assert_called_with(url) # TODO(Banashankar) : Complete refresh function. Need more info. def refresh(self): pass # TODO(Banashankar): Complete stats function. Need more info. def stats(self): pass class BaseOctaviaDriverTest(test_db_loadbalancerv2.LbaasPluginDbTestCase): # Copied it from Brocade's test code :/ def _create_fake_models(self): # This id is used for all the entities. id = 'test_id' lb = data_models.LoadBalancer(id=id) sni_container = data_models.SNI(listener_id=id) listener = data_models.Listener(id=id, loadbalancer=lb, sni_containers=[sni_container]) pool = data_models.Pool(id=id, listener=listener) member = data_models.Member(id=id, pool=pool) hm = data_models.HealthMonitor(id=id, pool=pool) lb.listeners = [listener] listener.default_pool = pool pool.members = [member] pool.healthmonitor = hm return lb def setUp(self): super(BaseOctaviaDriverTest, self).setUp() self.context = context.get_admin_context() self.plugin = mock.Mock() self.driver = driver.OctaviaDriver(self.plugin) # mock of rest call. self.driver.req = mock.Mock() self.lb = self._create_fake_models() class TestOctaviaDriver(BaseOctaviaDriverTest): def test_allocates_vip(self): self.addCleanup(cfg.CONF.clear_override, 'allocates_vip', group='octavia') cfg.CONF.set_override('allocates_vip', True, group='octavia') test_driver = driver.OctaviaDriver(self.plugin) self.assertTrue(test_driver.load_balancer.allocates_vip) def test_load_balancer_ops(self): m = ManagerTest(self, self.driver.load_balancer, self.driver.req) lb = self.lb # urls for assert test. lb_url = '/v1/loadbalancers' lb_url_id = '/v1/loadbalancers/' + lb.id # Create LB test # args for create assert. args = { 'id': lb.id, 'name': lb.name, 'description': lb.description, 'enabled': lb.admin_state_up, 'project_id': lb.tenant_id, 'vip': { 'subnet_id': lb.vip_subnet_id, 'ip_address': lb.vip_address, 'port_id': lb.vip_port_id, } } m.create(lb, lb_url, args) # Update LB test # args for update assert. args = args = { 'name': lb.name, 'description': lb.description, 'enabled': lb.admin_state_up, } m.update(lb, lb, lb_url_id, args) # delete LB test m.delete(lb, lb_url_id) # TODO(Banashankar) : refresh n stats fucntions are not yet done. #m.refresh() #m.stats() def test_listener_ops(self): m = ManagerTest(self, self.driver.listener, self.driver.req) listener = self.lb.listeners[0] # urls for assert test. list_url = '/v1/loadbalancers/%s/listeners' % listener.loadbalancer.id list_url_id = list_url + '/%s' % (listener.id) # Create Listener test. # args for create and update assert. sni_containers = [sni.tls_container_id for sni in listener.sni_containers] args = { 'id': listener.id, 'name': listener.name, 'description': listener.description, 'enabled': listener.admin_state_up, 'protocol': listener.protocol, 'protocol_port': listener.protocol_port, 'connection_limit': listener.connection_limit, 'tls_certificate_id': listener.default_tls_container_id, 'sni_containers': sni_containers, 'project_id': listener.tenant_id } m.create(listener, list_url, args) # Update listener test. del args['id'] del args['project_id'] m.update(listener, listener, list_url_id, args) # Delete listener. m.delete(listener, list_url_id) def test_pool_ops(self): m = ManagerTest(self, self.driver.pool, self.driver.req) pool = self.lb.listeners[0].default_pool # urls for assert test. pool_url = '/v1/loadbalancers/%s/listeners/%s/pools' % ( pool.listener.loadbalancer.id, pool.listener.id) pool_url_id = pool_url + "/%s" % pool.id # Test create pool. # args for create and update assert. args = { 'id': pool.id, 'name': pool.name, 'description': pool.description, 'enabled': pool.admin_state_up, 'protocol': pool.protocol, 'lb_algorithm': pool.lb_algorithm, 'project_id': pool.tenant_id } if pool.session_persistence: args['session_persistence'] = { 'type': pool.session_persistence.type, 'cookie_name': pool.session_persistence.cookie_name, } m.create(pool, pool_url, args) # Test update pool. del args['id'] del args['project_id'] m.update(pool, pool, pool_url_id, args) # Test pool delete. m.delete(pool, pool_url_id) def test_member_ops(self): m = ManagerTest(self, self.driver.member, self.driver.req) member = self.lb.listeners[0].default_pool.members[0] # urls for assert. mem_url = '/v1/loadbalancers/%s/listeners/%s/pools/%s/members' % ( member.pool.listener.loadbalancer.id, member.pool.listener.id, member.pool.id) mem_url_id = mem_url + "/%s" % member.id # Test Create member. # args for create assert. args = { 'id': member.id, 'enabled': member.admin_state_up, 'ip_address': member.address, 'protocol_port': member.protocol_port, 'weight': member.weight, 'subnet_id': member.subnet_id, 'project_id': member.tenant_id } m.create(member, mem_url, args) # Test member update. # args for update assert. args = { 'enabled': member.admin_state_up, 'protocol_port': member.protocol_port, 'weight': member.weight, } m.update(member, member, mem_url_id, args) # Test member delete. m.delete(member, mem_url_id) def test_health_monitor_ops(self): m = ManagerTest(self, self.driver.health_monitor, self.driver.req) hm = self.lb.listeners[0].default_pool.healthmonitor # urls for assert. hm_url = '/v1/loadbalancers/%s/listeners/%s/pools/%s/healthmonitor' % ( hm.pool.listener.loadbalancer.id, hm.pool.listener.id, hm.pool.id) # Test HM create. # args for create and update assert. args = { 'type': hm.type, 'delay': hm.delay, 'timeout': hm.timeout, 'rise_threshold': hm.max_retries, 'fall_threshold': hm.max_retries, 'http_method': hm.http_method, 'url_path': hm.url_path, 'expected_codes': hm.expected_codes, 'enabled': hm.admin_state_up, 'project_id': hm.tenant_id } m.create(hm, hm_url, args) # Test HM update del args['project_id'] m.update(hm, hm, hm_url, args) # Test HM delete m.delete(hm, hm_url) class TestThreadedDriver(BaseOctaviaDriverTest): def setUp(self): super(TestThreadedDriver, self).setUp() cfg.CONF.set_override('request_poll_interval', 1, group='octavia') cfg.CONF.set_override('request_poll_timeout', 5, group='octavia') self.driver.req.get = mock.MagicMock() self.succ_completion = mock.MagicMock() self.fail_completion = mock.MagicMock() self.context = mock.MagicMock() ctx_patcher = mock.patch('neutron.context.get_admin_context', return_value=self.context) ctx_patcher.start() self.addCleanup(ctx_patcher.stop) self.driver.load_balancer.successful_completion = ( self.succ_completion) self.driver.load_balancer.failed_completion = self.fail_completion def test_thread_op_goes_active(self): self.driver.req.get.side_effect = [ {'provisioning_status': 'PENDING_CREATE'}, {'provisioning_status': 'ACTIVE'} ] driver.thread_op(self.driver.load_balancer, self.lb) self.succ_completion.assert_called_once_with(self.context, self.lb, delete=False) self.assertEqual(0, self.fail_completion.call_count) def test_thread_op_goes_deleted(self): self.driver.req.get.side_effect = [ {'provisioning_status': 'PENDING_DELETE'}, {'provisioning_status': 'DELETED'} ] driver.thread_op(self.driver.load_balancer, self.lb, delete=True) self.succ_completion.assert_called_once_with(self.context, self.lb, delete=True) self.assertEqual(0, self.fail_completion.call_count) def test_thread_op_goes_error(self): self.driver.req.get.side_effect = [ {'provisioning_status': 'PENDING_CREATE'}, {'provisioning_status': 'ERROR'} ] driver.thread_op(self.driver.load_balancer, self.lb) self.fail_completion.assert_called_once_with(self.context, self.lb) self.assertEqual(0, self.succ_completion.call_count) def test_thread_op_a_times_out(self): cfg.CONF.set_override('request_poll_timeout', 1, group='octavia') self.driver.req.get.side_effect = [ {'provisioning_status': 'PENDING_CREATE'} ] driver.thread_op(self.driver.load_balancer, self.lb) self.fail_completion.assert_called_once_with(self.context, self.lb) self.assertEqual(0, self.succ_completion.call_count) def test_thread_op_updates_vip_when_vip_delegated(self): cfg.CONF.set_override('allocates_vip', True, group='octavia') expected_vip = '10.1.1.1' self.driver.req.get.side_effect = [ {'provisioning_status': 'PENDING_CREATE', 'vip': {'ip_address': ''}}, {'provisioning_status': 'ACTIVE', 'vip': {'ip_address': expected_vip}} ] driver.thread_op(self.driver.load_balancer, self.lb, lb_create=True) self.succ_completion.assert_called_once_with(self.context, self.lb, delete=False, lb_create=True) self.assertEqual(expected_vip, self.lb.vip_address)

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0.588117

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12,943

4.945873

0.169824

0.035568

0.021341

0.024077

0.36156

0.311081

0.253762

0.207934

0.185226

0.152394

0

0.003699

0.31067

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false

0.008032

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0

0.124498

0

null

0

null

0

1

0

8b2bea0330bb4f6054006045716aef8aee59015e

1,863

py

Python

semiring.py

dodgejesse/rational-recurrences

4d126903399cc4a86734733d037a9bb7c5dda93d

[ "MIT" ]

7

2019-09-09T06:25:20.000Z

2020-03-21T13:53:43.000Z

semiring.py

dodgejesse/rational-recurrences

4d126903399cc4a86734733d037a9bb7c5dda93d

[ "MIT" ]

1

2020-12-13T14:26:03.000Z

semiring.py

dodgejesse/rational-recurrences

4d126903399cc4a86734733d037a9bb7c5dda93d

[ "MIT" ]

1

2019-11-24T12:47:21.000Z

import torch def identity(x): return x def zero(data, *size): return data.new(*size).zero_() def one(data, *size): return data.new(*size).zero_() + 1. def neg_infinity(data, *size): return -100 * one(data, *size) class Semiring: def __init__(self, type, zero, one, plus, times, conditional_times, from_float, to_float, activation): self.type = type self.zero = zero self.one = one self.plus = plus self.times = times self.conditional_times = conditional_times self.from_float = from_float self.to_float = to_float self.activation = activation # element-wise plus, times PlusTimesSemiring = \ Semiring( 0, zero, one, torch.add, torch.mul, torch.mul, identity, identity, identity ) # element-wise max, plus MaxPlusSemiring = \ Semiring( 1, neg_infinity, zero, torch.max, torch.add, lambda x,y: x, identity, identity, torch.sigmoid ) # element-wise max, times. in log-space MaxTimesSemiring = \ Semiring( 2, neg_infinity, one, torch.max, torch.mul, lambda x,y: x, identity, identity, torch.sigmoid ) def LogSum(x, y): return torch.log(torch.exp(x) + torch.exp(y)) # element-wise max, times. in log-space LogSemiring = \ Semiring( 3, neg_infinity, zero, # lambda x, y: torch.log(torch.exp(x) + torch.exp(y)), LogSum, torch.add, lambda x,y: x, identity, identity, torch.sigmoid )

19.40625

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4.592965

0.236181

0.087527

0.035011

0.02954

0.322757

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0

0.007188

0.402576

1,863

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63

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0.814016

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0.075949

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0

0.012658

0.063291

0.164557

0

null

0

null

0

1

0

8b2e122bf3ed314d93abd5a384da45184c0aff9c

1,470

py

Python

examples/6_capacitive_touch/code.py

fasteddy516/CircuitPython_GamepadXL

63626ff04cbe205510620801fe492d73c63e703d

[ "MIT" ]

1

2021-12-23T18:40:18.000Z

examples/6_capacitive_touch/code.py

fasteddy516/CircuitPython_GamepadXL

63626ff04cbe205510620801fe492d73c63e703d

[ "MIT" ]

7

2021-08-18T16:34:12.000Z

2021-12-23T08:35:28.000Z

examples/6_capacitive_touch/code.py

fasteddy516/CircuitPython_JoystickXL

63626ff04cbe205510620801fe492d73c63e703d

[ "MIT" ]

null

""" JoystickXL Example #6 - Capacitive Touch (8 buttons and 1 hat switch). This example uses an MPR121 12-Key Capacitive Touch Sensor Breakout (https://www.adafruit.com/product/1982), and requires the `adafruit_mpr121` and `adafruit_bus_device` libraries from the CircuitPython Library Bundle. Tested on an Adafruit Metro M4 Express, but should work on other CircuitPython boards with a sufficient quantity/type of pins. * 3V, G, SCL, SDA from CircuitPython board to MPR121 board * Buttons are on MPR121 inputs 0-7 * Hat Switch is on MPR121 inputs 8-11 (8=UP, 9=DOWN, 10=LEFT, 11=RIGHT) Don't forget to copy boot.py from the example folder to your CIRCUITPY drive. """ import adafruit_mpr121 import board # type: ignore (this is a CircuitPython built-in) import busio # type: ignore (this is a CircuitPython built-in) from joystick_xl.inputs import Button, Hat from joystick_xl.joystick import Joystick # Set up I2C MPR121 capacitive touch sensor i2c = busio.I2C(board.SCL, board.SDA) mpr121 = adafruit_mpr121.MPR121(i2c) # Set up JoystickXL! js = Joystick() # The MPR121 library returns True when a capacitive touch channel is activated. This # makes it "active high", so we set `active_low` to False for i in range(8): js.add_input(Button(mpr121[i], active_low=False)) js.add_input( Hat( up=mpr121[8], down=mpr121[9], left=mpr121[10], right=mpr121[11], active_low=False, ) ) while True: js.update()

30.625

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0.472103

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0.0394

0.030019

0.069418

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0.180272

1,470

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0.238095

0

null

0

null

0

1

0

8b343ec3681fb404a7c7b9240fc57669b03d1fb5

2,216

py

Python

urbanairship/experiments/variant.py

rodsenra/python-library

bd3fb129ee0eb72265f6d0f2f03fd9e8184dcac0

[ "Apache-2.0" ]

null

urbanairship/experiments/variant.py

rodsenra/python-library

bd3fb129ee0eb72265f6d0f2f03fd9e8184dcac0

[ "Apache-2.0" ]

null

urbanairship/experiments/variant.py

rodsenra/python-library

bd3fb129ee0eb72265f6d0f2f03fd9e8184dcac0

[ "Apache-2.0" ]

null

class Variant(object): """The variants for the experiment. An experiment must have at least 1 variant and no more than 26. """ def __init__(self, push, description=None, name=None, schedule=None, weight=None ): """ :keyword push: [required] A push object without audience and device_types fields. These two fields are not allowed because they are already defined in the experiment object :keyword description: [optional] A description of the variant. :keyword name: [optional] A name for the variant unless either message or in_app is present. You can provide an alert and any platform overrides that apply to the device_type platforms you specify. :keyword schedule: [optional] The time when the push notification should be sent :keyword weight: [optional] The proportion of the audience that will receive this variant. Defaults to 1. """ self.push = push self.description = description self.name = name self.schedule = schedule self.weight = weight @property def description(self): if not self._description: return None return self._description @description.setter def description(self, value): if not isinstance(value, str): TypeError( 'the description must be type string' ) self._description = value @property def name(self): if not self._name: return None return self._name @name.setter def name(self, value): if not isinstance(value, str): TypeError( 'the name must be a string type' ) self._name = value @property def weight(self): if not self._weight: return None return self._weight @weight.setter def weight(self, value): if not isinstance(value, int): TypeError( 'the value must be a integer type' ) self._weight = value

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2,216

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0.093301

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0

0.002849

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2,216

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0

0.285714

0

null

0

null

0

1

0

8b35915e56f7da506994b2940d5b12de39f029a2

11,278

py

Python

creator/utils.py

MeTeoRise/chatbot_automation

6dfbbdbf8b71219b35052c6549ff32347a6248be

[ "MIT" ]

3

2022-03-04T10:18:29.000Z

2022-03-23T20:16:01.000Z

creator/utils.py

MeTeoRise/chatbot_automation

6dfbbdbf8b71219b35052c6549ff32347a6248be

[ "MIT" ]

null

creator/utils.py

MeTeoRise/chatbot_automation

6dfbbdbf8b71219b35052c6549ff32347a6248be

[ "MIT" ]

null

import os import io import socket import yaml from rasa.shared.nlu.training_data.loading import load_data class MyDumper(yaml.SafeDumper): def write_line_break(self, data=None): super().write_line_break(data) if len(self.indents) == 1: super().write_line_break() def chatbot_create(name): cmd = "cd chatbots && mkdir \"{0}\" && cd \"{0}\" && rasa init --no-prompt&".format(name) os.system(cmd) def chatbot_delete(name): cmd = "cd chatbots && rm -r \"{0}\"".format(name) os.system(cmd) def chatbot_train(chatbot, intents, examples, responses, utterances, stories, steps, rules, actions, forms, slots): write_intents(chatbot, intents, examples) write_responses(chatbot, responses, utterances) write_stories(chatbot, stories, steps) write_rules(chatbot, rules, forms, slots) write_actions(chatbot, actions) write_policies(chatbot) write_domain(chatbot, intents, responses, utterances, actions, forms, slots) clear_models(chatbot) cmd = "cd chatbots && cd \"{0}\" && rasa train&".format(chatbot.name) os.system(cmd) def chatbot_start(chatbot, actions): cmd = "cd chatbots && cd \"{0}\" && rasa run -m models --enable-api --cors \"*\" --debug&".format(chatbot.name) os.system(cmd) if len(list(actions)) != 0: cmd = "cd chatbots && cd \"{0}\" && rasa run actions --cors \"*\" --debug&".format(chatbot.name) os.system(cmd) def chatbot_stop(): if check_chatbot() == 0: cmd = "kill $(lsof -t -i:5005)" os.system(cmd) if check_chatbot_actions() == 0: cmd = "kill $(lsof -t -i:5055)" os.system(cmd) def check_chatbot(): a_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) location = ("127.0.0.1", 5005) result_of_check = a_socket.connect_ex(location) a_socket.close() return result_of_check def check_chatbot_actions(): a_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) location = ("127.0.0.1", 5055) result_of_check = a_socket.connect_ex(location) a_socket.close() return result_of_check def write_intents(chatbot, intents, examples): path = "chatbots/" + chatbot.name + "/data/nlu.yml" intents_list = [] examples_list = [] intents = list(intents) examples = list(examples) for i in intents: intents_list.append(list(i)) for i in examples: examples_list.append(list(i)) intents = intents_list[:] examples = examples_list[:] merged = {} for i in intents: merged[i[1]] = [] for j in examples: if i[0] == j[0]: merged[i[1]].append(j[1]) diction = dict() diction['version'] = '2.0' diction['nlu'] = [] for i in range(len(intents)): diction['nlu'].append({"intent": intents[i][1]}) diction['nlu'][i]['examples'] = yaml.dump(merged[intents[i][1]]) f = open(path, 'w+') yaml.dump(diction, f, Dumper=MyDumper, sort_keys=False) def write_stories(chatbot, stories, steps): path = "chatbots/" + chatbot.name + "/data/stories.yml" stories_list = [] steps_list = [] stories = list(stories) steps = list(steps) for i in stories: stories_list.append(list(i)) for i in steps: steps_list.append(list(i)) stories = stories_list[:] steps = steps_list[:] merged = {} for i in stories: merged[i[1]] = [] for j in steps: if i[0] == j[5]: if j[0] is not None: merged[i[1]].append({'intent': j[0]}) if j[1] is not None: merged[i[1]].append({'action': j[1]}) if j[2] is not None: merged[i[1]].append({'action': j[2]}) if j[3] is not None: merged[i[1]].append({'action': j[3]}) merged[i[1]].append({'active_loop': j[3]}) diction = dict() diction['version'] = '2.0' diction['stories'] = [] for i in range(len(stories)): diction['stories'].append({"story": stories[i][1]}) diction['stories'][i]['steps'] = merged[stories[i][1]] f = open(path, 'w+') yaml.dump(diction, f, Dumper=MyDumper, sort_keys=False) def write_responses(chatbot, responses, utterances): path = "chatbots/" + chatbot.name + "/data/responses.yml" responses_list = [] utterances_list = [] responses = list(responses) utterances = list(utterances) for i in responses: responses_list.append(list(i)) for i in utterances: utterances_list.append(list(i)) responses = responses_list[:] utterances = utterances_list[:] merged = {} for i in responses: merged[i[1]] = [] for idx, j in enumerate(utterances): if i[0] == j[0]: merged[i[1]].append({'text': j[1]}) if j[2] is not None: merged[i[1]][idx-1]['image'] = j[2] diction = dict() diction['responses'] = dict() for i in range(len(responses)): diction['responses'][responses[i][1]] = merged[responses[i][1]] f = open(path, 'w+') yaml.dump(diction, f, Dumper=MyDumper, sort_keys=False) def write_rules(chatbot, rules, forms, slots): path = "chatbots/" + chatbot.name + "/data/rules.yml" rules_list = [] rules = list(rules) for i in rules: rules_list.append(list(i)) rules = rules_list[:] diction = dict() diction['version'] = '2.0' diction['rules'] = [] for i in range(len(rules)): diction['rules'].append({"rule": rules[i][0]}) diction['rules'][i]['steps'] = [] diction['rules'][i]['steps'].append({"intent": rules[i][1]}) diction['rules'][i]['steps'].append({"action": rules[i][2]}) for i in range(len(forms)): diction['rules'].append({"rule": "Activate form"}) diction['rules'][2*i+len(rules)]['steps'] = [] diction['rules'][2*i+len(rules)]['steps'].append({"intent": forms[i][2]}) diction['rules'][2*i+len(rules)]['steps'].append({"action": forms[i][1]}) diction['rules'][2*i+len(rules)]['steps'].append({"active_loop": forms[i][1]}) diction['rules'].append({"rule": "Submit form"}) diction['rules'][2*i+1+len(rules)]['condition'] = [] diction['rules'][2*i+1+len(rules)]['condition'].append({"active_loop": forms[i][1]}) diction['rules'][2*i+1+len(rules)]['steps'] = [] diction['rules'][2*i+1+len(rules)]['steps'].append({"action": forms[i][1]}) diction['rules'][2*i+1+len(rules)]['steps'].append({"active_loop": None}) diction['rules'][2*i+1+len(rules)]['steps'].append({"action": "utter_submit"}) f = open(path, 'w+') yaml.dump(diction, f, Dumper=MyDumper, sort_keys=False) def write_actions(chatbot, actions): path = "chatbots/" + chatbot.name + "/actions/actions.py" actions_file = open(path, "w") actions = list(actions) actions_file.write("from typing import Any, Text, Dict, List\n\n") actions_file.write("from rasa_sdk import Action, Tracker\nfrom rasa_sdk.executor import CollectingDispatcher\n\n") for action in actions: actions_file.write("\nclass Action{0}(Action):\n\n".format(action[0])) actions_file.write(" def name(self) -> Text:\n") actions_file.write(' return "action_{0}"\n\n'.format(action[0].lower())) actions_file.write(" def run(self, dispatcher: CollectingDispatcher,\n") actions_file.write(" tracker: Tracker,\n") actions_file.write(" domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:\n\n") for line in action[1].split("\n"): actions_file.write(" {0}\n\n".format(line)) actions_file.write(" return []\n\n") def write_policies(obj): path = "chatbots/" + obj.name + "/config.yml" source = "chatbots/default/config.yml" cmd = "cp -fr {0} \"{1}\"&".format(source, path) os.system(cmd) def write_domain(chatbot, intents, responses, utterances, actions, forms, slots): path = "chatbots/" + chatbot.name + "/domain.yml" nlu_path = "chatbots/" + chatbot.name + "/data/nlu.yml" data = load_data(nlu_path) entities = list(data.entities) intents = list(intents) responses = list(responses) actions = list(actions) forms = list(forms) slots = list(slots) intents_list = [] responses_list = [] utterances_list = [] forms_list = [] slots_list = [] for i in intents: intents_list.append(list(i)) for i in responses: responses_list.append(list(i)) for i in utterances: utterances_list.append(list(i)) for i in forms: forms_list.append(list(i)) for i in slots: slots_list.append(list(i)) utterances = utterances_list[:] intents = intents_list[:] responses = responses_list[:] forms = forms_list[:] slots = slots_list[:] merged = {} for i in responses: merged[i[1]] = [] for idx, j in enumerate(utterances): if i[0] == j[0]: merged[i[1]].append({'text': j[1]}) if j[2] is not None: merged[i[1]][idx-1]['image'] = j[2] merged_forms = {} for i in forms: merged_forms[i[1]] = dict() for idx, j in enumerate(slots): if i[0] == j[4]: merged_forms[i[1]][j[0]] = [] merged_forms[i[1]][j[0]].append({'type': 'from_text'}) diction = dict() diction['version'] = '2.0' diction['intents'] = [] for i in range(len(intents)): diction['intents'].append(intents[i][1]) diction['entities'] = [] for i in range(len(entities)): diction['entities'].append(entities[i]) diction['slots'] = dict() for i in range(len(slots)): slot_dict = dict() slot_dict['type'] = slots[i][1] slot_dict['influence_conversation'] = slots[i][2] diction['slots'][slots[i][0]] = slot_dict diction['responses'] = dict() for i in range(len(responses)): diction['responses'][responses[i][1]] = merged[responses[i][1]] diction['actions'] = [] for i in range(len(actions)): diction['actions'].append("{0}".format(actions[i][0].lower())) diction['forms'] = dict() for i in range(len(forms)): diction['forms'][forms[i][1]] = merged_forms[forms[i][1]] diction['session_config'] = dict() diction['session_config']['session_expiration_time'] = 60 diction['session_config']['carry_over_slots_to_new_session'] = True f = open(path, 'w+') yaml.dump(diction, f, Dumper=MyDumper, sort_keys=False) def clear_models(chatbot): cmd = "cd chatbots && cd \"{0}\" && cd models && rm *".format(chatbot.name) os.system(cmd) # TODO Pass intents to signals def read_default_intents(chatbot): default_intents = "chatbots/default/data/nlu.yml" data = load_data(default_intents) intents = data.intents return intents # TODO Read default stories and pass them to signals def read_default_stories(): default_intents = "chatbots/default/data/stories.yml" data = load_data(default_intents) intents = data.intents return intents

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null

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1

0

8b38978d010f03a17b04862154c277cb73cd65d9

2,332

py

Python

formlib/templates/__dmpcache__/form.htm.py

brandenclark/413-Final

d606f825bd1a9cf703e4907fc7b704f7df8d205b

[ "MIT" ]

null

formlib/templates/__dmpcache__/form.htm.py

brandenclark/413-Final

d606f825bd1a9cf703e4907fc7b704f7df8d205b

[ "MIT" ]

null

formlib/templates/__dmpcache__/form.htm.py

brandenclark/413-Final

d606f825bd1a9cf703e4907fc7b704f7df8d205b

[ "MIT" ]

null

# -*- coding:utf-8 -*- from mako import runtime, filters, cache UNDEFINED = runtime.UNDEFINED STOP_RENDERING = runtime.STOP_RENDERING __M_dict_builtin = dict __M_locals_builtin = locals _magic_number = 10 _modified_time = 1524253334.9406211 _enable_loop = True _template_filename = '/Users/brand/Desktop/finalexam/formlib/templates/form.htm' _template_uri = 'form.htm' _source_encoding = 'utf-8' import django_mako_plus _exports = [] def render_body(context,**pageargs): __M_caller = context.caller_stack._push_frame() try: __M_locals = __M_dict_builtin(pageargs=pageargs) self = context.get('self', UNDEFINED) csrf_input = context.get('csrf_input', UNDEFINED) extra = context.get('extra', UNDEFINED) form = context.get('form', UNDEFINED) __M_writer = context.writer() __M_writer(str( django_mako_plus.links(self) )) __M_writer('\n\n<div class="form-container">\n <form id="') __M_writer(str( form.form_id )) __M_writer('" action="') __M_writer(str( form.form_action or '' )) __M_writer('" method="') __M_writer(str( form.form_method )) __M_writer('">\n\n') __M_writer(' ') __M_writer(str( csrf_input )) __M_writer('\n\n') __M_writer(' ') __M_writer(str( form.as_p() )) __M_writer('\n\n') if extra: __M_writer(' ') __M_writer(str( extra )) __M_writer('\n') __M_writer('\n') if form.submit_text is not None: __M_writer(' <p class="text-center"><button type="submit" class="btn btn-primary">') __M_writer(filters.html_escape(str( form.submit_text ))) __M_writer('</button></p>\n') __M_writer('\n </form>\n</div>\n') return '' finally: context.caller_stack._pop_frame() """ __M_BEGIN_METADATA {"filename": "/Users/brand/Desktop/finalexam/formlib/templates/form.htm", "uri": "form.htm", "source_encoding": "utf-8", "line_map": {"17": 0, "26": 3, "27": 3, "28": 6, "29": 6, "30": 6, "31": 6, "32": 6, "33": 6, "34": 9, "35": 9, "36": 9, "37": 12, "38": 12, "39": 12, "40": 15, "41": 16, "42": 16, "43": 16, "44": 18, "45": 20, "46": 21, "47": 21, "48": 21, "49": 23, "55": 49}} __M_END_METADATA """

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0.408946

0.128492

0.055866

0.051077

0.233839

0.177175

0.132482

0

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2,332

59

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null

0

null

0

1

0

8b38a1b4b8772554293e9955f47a3488fe3192be

580

py

Python

app.py

nurhasanhilmi/GOA-SVM-for-GPT-Classification

ccc2356957654477930edf33b384a199ac8b707c

[ "MIT" ]

null

app.py

nurhasanhilmi/GOA-SVM-for-GPT-Classification

ccc2356957654477930edf33b384a199ac8b707c

[ "MIT" ]

1

2021-08-19T07:42:40.000Z

2021-08-22T08:14:55.000Z

app.py

nurhasanhilmi/GOA-SVM-for-GPT-Classification

ccc2356957654477930edf33b384a199ac8b707c

[ "MIT" ]

null

import streamlit as st from multiapp import MultiApp from apps import app_unoptimized_svm ,app_goa_svm, app_grid_search_svm, app_dataset, app_saved_model, app_gpt_classification # import app modules here app = MultiApp() # Add all application here app.add_app("GOA-SVM", app_goa_svm.app) app.add_app("Grid Search-SVM", app_grid_search_svm.app) app.add_app("Unoptimized SVM", app_unoptimized_svm.app) app.add_app("Saved Models", app_saved_model.app) app.add_app("Dataset", app_dataset.app) app.add_app("GPT Classification", app_gpt_classification.app) # The main app app.run()

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null

0

null

0

1

0

8b39056fdec027e94bea7ccb868554665f22f2e9

16,695

py

Python

apps/invoicing/forms.py

karpiq24/django-klima-kar

e62e79c66053749e249f55e1ab47f810f449f0aa

[ "MIT" ]

2

2018-01-23T22:38:57.000Z

2019-07-14T08:59:19.000Z

apps/invoicing/forms.py

karpiq24/django-klima-kar

e62e79c66053749e249f55e1ab47f810f449f0aa

[ "MIT" ]

237

2018-08-15T23:13:52.000Z

2022-01-13T13:08:50.000Z

apps/invoicing/forms.py

karpiq24/django-klima-kar

e62e79c66053749e249f55e1ab47f810f449f0aa

[ "MIT" ]

null

from dal import autocomplete from extra_views import InlineFormSetFactory from django import forms from django.urls import reverse from django.forms.models import model_to_dict from django.db.models import Q from KlimaKar.widgets import PrettySelect from KlimaKar.forms import ToggleInput from apps.invoicing.models import ( Contractor, SaleInvoice, SaleInvoiceItem, ServiceTemplate, RefrigerantWeights, CorrectiveSaleInvoice, ) from apps.warehouse.models import Ware from apps.commission.models import CommissionItem, CommissionFile class EnableDisableDateInput(forms.DateInput): template_name = "invoicing/sale_invoice/date_field.html" class SaleInvoiceModelForm(forms.ModelForm): contractor = forms.ModelChoiceField( label="Kontrahent", queryset=Contractor.objects.all(), widget=autocomplete.ModelSelect2( url="invoicing:contractor_autocomplete_create" ), ) generate_pdf = forms.BooleanField( label="Wydruk po zapisie", widget=forms.HiddenInput(), required=False ) contractor_modified = forms.BooleanField(widget=forms.HiddenInput(), required=False) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields["number"].widget.attrs.update( {"placeholder": "Podaj numer faktury"} ) self.fields["contractor"].widget.attrs.update( {"data-placeholder": "Podaj nazwę, NIP albo numer telefonu"} ) self.fields["issue_date"].widget.attrs.update({"placeholder": "Wybierz datę"}) self.fields["issue_date"].widget.attrs.update({"class": "date-input"}) self.fields["completion_date"].widget.attrs.update( {"placeholder": "Wybierz datę"} ) self.fields["completion_date"].widget.attrs.update({"class": "date-input"}) self.fields["payment_date"].widget.attrs.update({"placeholder": "Wybierz datę"}) self.fields["payment_date"].widget.attrs.update({"class": "date-input"}) self.fields["payment_type_other"].widget.attrs.update( {"placeholder": "Podaj formę płatności"} ) self.fields["calculation"].disabled = True # TODO: Brutto contractor = self.initial.get("contractor") if contractor: self.fields["contractor"].initial = contractor def clean(self): cleaned_data = super().clean() number = cleaned_data["number"] if self.instance and self.instance.number == number: return cleaned_data else: invoice_type = cleaned_data["invoice_type"] invoices = SaleInvoice.objects.filter(invoice_type=invoice_type) if invoice_type == SaleInvoice.TYPE_VAT: invoices = ( invoices | SaleInvoice.objects.filter(invoice_type=SaleInvoice.TYPE_WDT) ).distinct() elif invoice_type == SaleInvoice.TYPE_WDT: invoices = ( invoices | SaleInvoice.objects.filter(invoice_type=SaleInvoice.TYPE_VAT) ).distinct() elif invoice_type == SaleInvoice.TYPE_PRO_FORMA: invoices = ( invoices | SaleInvoice.objects.filter( invoice_type=SaleInvoice.TYPE_WDT_PRO_FORMA ) ).distinct() elif invoice_type == SaleInvoice.TYPE_WDT_PRO_FORMA: invoices = ( invoices | SaleInvoice.objects.filter( invoice_type=SaleInvoice.TYPE_PRO_FORMA ) ).distinct() if invoices.filter(number=number).exists(): self.add_error("number", "Faktura o tym numerze już istnieje.") return cleaned_data class Meta: model = SaleInvoice fields = [ "issue_date", "completion_date", "invoice_type", "number", "contractor", "payment_type", "payment_date", "payment_type_other", "comment", "tax_percent", "calculation", ] widgets = { "comment": forms.Textarea(attrs={"rows": 2}), "payment_date": EnableDisableDateInput(), "invoice_type": forms.HiddenInput(), "tax_percent": forms.HiddenInput(), "payment_type": PrettySelect(), "calculation": PrettySelect(), } class CorrectiveSaleInvoiceModelForm(SaleInvoiceModelForm): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields["contractor"].disabled = True self.fields["completion_date"].disabled = True self.fields["calculation"].disabled = True class Meta: model = CorrectiveSaleInvoice fields = [ "issue_date", "completion_date", "invoice_type", "number", "contractor", "payment_type", "payment_date", "payment_type_other", "comment", "tax_percent", "original_invoice", "reason", "calculation", ] widgets = { "comment": forms.Textarea(attrs={"rows": 2}), "reason": forms.Textarea(attrs={"rows": 2}), "payment_date": EnableDisableDateInput(), "invoice_type": forms.HiddenInput(), "original_invoice": forms.HiddenInput(), "tax_percent": forms.HiddenInput(), "payment_type": PrettySelect(), "calculation": PrettySelect(), } class NipInput(forms.TextInput): template_name = "invoicing/contractor/nip_field.html" class Media: js = ("js/invoicing/contractor-gus.js",) def __init__(self, *args, **kwargs): self.prefix = kwargs.pop("prefix") super().__init__(*args, **kwargs) def get_context(self, name, value, attrs, *args, **kwargs): context = super().get_context(name, value, attrs) context["url"] = reverse("invoicing:contractor_gus") context["prefix"] = self.prefix return context class ContractorModelForm(forms.ModelForm): ignore_duplicated_phone = forms.CharField( required=False, widget=forms.HiddenInput() ) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) if self.instance and self.instance.is_locked: self.fields["nip"].disabled = True self.fields[ "nip" ].help_text = "Ten kontrahent ma przypisaną fakturę, zamiast edytować numer NIP, dodaj nowego kontrahenta." self.fields["name"].widget.attrs.update({"placeholder": "Podaj nazwę"}) if self.instance and self.instance.nip_prefix: nip_prefix = self.instance.nip_prefix else: nip_prefix = "" self.fields["nip"].widget = NipInput(prefix=nip_prefix) self.fields["nip"].widget.attrs.update({"placeholder": "Podaj NIP"}) self.fields["address_1"].widget.attrs.update({"placeholder": "Podaj adres"}) self.fields["address_2"].widget.attrs.update({"placeholder": "Podaj adres"}) self.fields["city"].widget.attrs.update({"placeholder": "Podaj miasto"}) self.fields["postal_code"].widget.attrs.update( {"placeholder": "Podaj kod pocztowy"} ) self.fields["email"].widget.attrs.update({"placeholder": "Podaj adres e-mail"}) self.fields["phone_1"].widget.attrs.update( {"placeholder": "Podaj numer telefonu"} ) self.fields["phone_2"].widget.attrs.update( {"placeholder": "Podaj numer telefonu"} ) self.fields["bdo_number"].widget.attrs.update( {"placeholder": "Podaj numer BDO"} ) class Meta: model = Contractor fields = [ "nip_prefix", "nip", "name", "city", "postal_code", "address_1", "address_2", "email", "phone_1", "phone_2", "bdo_number", "ignore_duplicated_phone", ] widgets = {"nip_prefix": forms.HiddenInput()} class Media: js = ("js/invoicing/contractor-form.js",) def clean_nip(self): nip = self.cleaned_data["nip"] if self.instance and self.instance.is_locked: return self.instance.nip return nip def clean_nip_prefix(self): nip_prefix = self.cleaned_data["nip_prefix"] if self.instance and self.instance.is_locked: return self.instance.nip_prefix return nip_prefix def clean_phone_1(self): data = self.cleaned_data["phone_1"] if data: data = data.replace(" ", "") if not bool(self.data.get("ignore_duplicated_phone", "False")): self._check_duplicate_phones(data) return data def clean_phone_2(self): data = self.cleaned_data["phone_2"] if data: data = data.replace(" ", "") if not bool(self.data.get("ignore_duplicated_phone", "False")): self._check_duplicate_phones(data) return data def _check_duplicate_phones(self, number): queryset = Contractor.objects.filter(Q(phone_1=number) | Q(phone_2=number)) if self.instance and self.instance.pk: queryset = queryset.exclude(pk=self.instance.pk) if queryset.exists(): raise forms.ValidationError( "Podany numer jest już przypisany do innego kontrahenta.", code="duplicated_phone", params=[queryset.first().as_json()], ) class SaleInvoiceItemModelForm(forms.ModelForm): ware = forms.ModelChoiceField( label="Towar", queryset=Ware.objects.all(), required=False, widget=autocomplete.ModelSelect2(url="warehouse:ware_autocomplete"), ) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields["name"].widget.attrs.update({"placeholder": "Podaj nazwę"}) self.fields["name"].widget.attrs.update({"class": "item-name"}) self.fields["description"].widget.attrs.update({"placeholder": "Podaj opis"}) self.fields["description"].widget.attrs.update({"class": "item-description"}) self.fields["quantity"].widget.attrs.update({"placeholder": "Ilość"}) self.fields["quantity"].widget.attrs.update({"class": "item-quantity"}) self.fields["price_netto"].widget.attrs.update({"placeholder": "Netto"}) self.fields["price_netto"].widget.attrs.update({"class": "item-netto"}) self.fields["price_brutto"].widget.attrs.update({"placeholder": "Brutto"}) self.fields["price_brutto"].widget.attrs.update({"class": "item-brutto"}) self.fields["ware"].widget.attrs.update({"data-placeholder": "Wybierz towar"}) self.fields["ware"].widget.attrs.update({"class": "item-ware"}) class Meta: model = SaleInvoiceItem fields = [ "name", "description", "quantity", "price_netto", "price_brutto", "ware", ] localized_fields = ["price_netto", "price_brutto", "quantity"] class SaleInvoiceItemsInline(InlineFormSetFactory): model = SaleInvoiceItem form_class = SaleInvoiceItemModelForm factory_kwargs = {"extra": 20} def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.commission = self.kwargs.get("commission", None) self.value_type = self.kwargs.get("value_type", None) self.original_invoice = self.kwargs.get("original_invoice", None) def get_initial(self): if not self.object and self.original_invoice: items = SaleInvoiceItem.objects.filter(sale_invoice=self.original_invoice) initial = [model_to_dict(item) for item in items] return initial if not self.object and self.commission: items = CommissionItem.objects.filter(commission=self.commission) initial = [self._commission_item_to_dict(item) for item in items] return initial return self.initial[:] def _commission_item_to_dict(self, item): d = model_to_dict(item, exclude=["id", "commission"]) if self.value_type == "NETTO": d["price_netto"] = d.pop("price") else: d["price_brutto"] = d.pop("price") return d class AlwaysChangedModelForm(forms.ModelForm): """ Force saving RefrigerantWeightsInline formset with default values """ def has_changed(self): return True class RefrigerantWeightsInline(InlineFormSetFactory): model = RefrigerantWeights factory_kwargs = {"max_num": 1, "min_num": 1, "extra": 0, "can_delete": False} form_class = AlwaysChangedModelForm fields = "__all__" class ServiceTemplateModelForm(forms.ModelForm): ware = forms.ModelChoiceField( label="Towar", queryset=Ware.objects.all(), required=False, widget=autocomplete.ModelSelect2(url="warehouse:ware_autocomplete"), ) services = forms.ModelMultipleChoiceField( label="Usługi", queryset=ServiceTemplate.objects.all(), required=False, widget=autocomplete.ModelSelect2Multiple( url="invoicing:service_template_autocomplete" ), ) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields["name"].widget.attrs.update({"placeholder": "Podaj nazwę"}) self.fields["ware_filter"].widget.attrs.update( {"placeholder": "Podaj nazwę towaru"} ) self.fields["button_name"].widget.attrs.update( {"placeholder": "Podaj nazwę przycisku"} ) self.fields["name"].widget.attrs.update({"class": "item-name"}) self.fields["description"].widget.attrs.update({"placeholder": "Podaj opis"}) self.fields["description"].widget.attrs.update({"class": "item-description"}) self.fields["quantity"].widget.attrs.update({"placeholder": "Podaj ilość"}) self.fields["quantity"].widget.attrs.update({"class": "item-quantity"}) self.fields["price_netto"].widget.attrs.update( {"placeholder": "Podaj cenę netto"} ) self.fields["price_netto"].widget.attrs.update({"class": "item-netto"}) self.fields["price_brutto"].widget.attrs.update( {"placeholder": "Podaj cenę brutto"} ) self.fields["price_brutto"].widget.attrs.update({"class": "item-brutto"}) self.fields["ware"].widget.attrs.update({"data-placeholder": "Wybierz towar"}) self.fields["ware"].widget.attrs.update({"class": "item-ware"}) self.fields["services"].widget.attrs.update( {"data-placeholder": "Wybierz usługi"} ) class Meta: model = ServiceTemplate fields = [ "name", "description", "quantity", "price_netto", "price_brutto", "ware", "button_color", "display_as_button", "button_name", "is_ware_service", "ware_filter", "is_group", "services", ] widgets = { "display_as_button": ToggleInput, "is_ware_service": ToggleInput, "is_group": ToggleInput, } localized_fields = ["price_netto", "price_brutto", "quantity"] class EmailForm(forms.Form): recipient = forms.EmailField(label="Do") subject = forms.CharField(label="Temat") message = forms.CharField(widget=forms.Textarea, label="Treść") sale_invoice = forms.ModelChoiceField( queryset=SaleInvoice.objects.none(), widget=forms.HiddenInput() ) files = forms.ModelMultipleChoiceField( queryset=CommissionFile.objects.none(), label="Pliki", required=False ) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.fields["sale_invoice"].queryset = SaleInvoice.objects.filter( pk=self.initial["sale_invoice"].pk ) self.fields["files"].queryset = CommissionFile.objects.filter( commission__sale_invoices=self.initial["sale_invoice"] ) if not self.fields["files"].queryset.exists(): self.fields["files"].widget = forms.HiddenInput()

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0.207071

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null

0

null

0

1

0

8b397e52975595e4604862b4354dceb45600a27d

1,731

bzl

Python

tools/javacc.bzl

sgammon/closure-stylesheets

7a107fda2336060a6bb02227ff7b9ef525f74ece

[ "Apache-2.0" ]

1

2019-06-15T04:55:55.000Z

tools/javacc.bzl

Bloombox/closure-stylesheets

716aed6cde8772d8f119e813c1b48fb3a13d974c

[ "Apache-2.0" ]

null

tools/javacc.bzl

Bloombox/closure-stylesheets

716aed6cde8772d8f119e813c1b48fb3a13d974c

[ "Apache-2.0" ]

null

## Copyright 2018 The Closure Stylesheets 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. def _declare_output_files(ctx, files): if len(files) < 1: fail("files must not be empty.") sources = [] for file in files: sources.append(ctx.actions.declare_file(file)) return struct( files = sources, path = '/'.join(sources[0].path.split('/')[:-1]), ) def _javacc_impl(ctx): outputs = _declare_output_files(ctx, ctx.attr.outs) args = [ '-OUTPUT_DIRECTORY=%s' % outputs.path, ctx.file.src.path, ] ctx.actions.run( inputs = [ctx.file.src], outputs = outputs.files, arguments = args, executable = ctx.executable._compiler, ) return struct( files = depset(outputs.files), ) javacc = rule( implementation = _javacc_impl, output_to_genfiles = True, attrs={ "src": attr.label( mandatory = True, allow_files = [".jj"], single_file = True, ), "outs": attr.string_list( mandatory = True, ), "_compiler": attr.label( default = Label("@javacc//:javacc"), executable = True, cfg = "host", ), }, )

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null

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null

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1

0

8b39e6d8d610f45267b9579e7529ef1e138da10a

8,924

py

Python

tests/test_transitions_anyio.py

MicahLyle/transitions-anyio

b581dfebdfd8641adec285db6b4f7e34287eb309

[ "MIT" ]

4

2021-01-07T16:33:53.000Z

2021-09-19T20:14:26.000Z

tests/test_transitions_anyio.py

MicahLyle/transitions-anyio

b581dfebdfd8641adec285db6b4f7e34287eb309

[ "MIT" ]

4

2020-10-12T17:01:53.000Z

2021-06-24T10:22:16.000Z

tests/test_transitions_anyio.py

thedrow/transitions-anyio

ff97c7e7a0298bb3ed8cd05ec56f8b13a5ddfdac

[ "MIT" ]

1

2021-06-20T21:10:10.000Z

from unittest.mock import MagicMock import anyio import pytest from transitions import MachineError from transitions_anyio import HierarchicalAnyIOMachine pytestmark = pytest.mark.anyio async def await_true(): await anyio.sleep(0.1) return True async def await_false(): await anyio.sleep(0.1) return False def synced_true(): return True async def cancel_soon(): await anyio.sleep(1) raise TimeoutError("Callback was not cancelled!") async def call_delayed(func, time): await anyio.sleep(time) await func() class DummyModel(object): pass async def test_async_machine_cb(m): mock = MagicMock() async def async_process(): await anyio.sleep(0.1) mock() m.after_state_change = async_process await m.go() assert m.state == 'B' mock.assert_called_once_with() async def test_async_condition(m): m.add_transition('proceed', 'A', 'C', conditions=await_true, unless=await_false) await m.proceed() assert m.state == 'C' async def test_async_enter_exit(m): enter_mock = MagicMock() exit_mock = MagicMock() async def async_enter(): await anyio.sleep(0.1) enter_mock() async def async_exit(): await anyio.sleep(0.1) exit_mock() m.on_exit_A(async_exit) m.on_enter_B(async_enter) await m.go() enter_mock.assert_called_once_with() exit_mock.assert_called_once_with() async def test_async_conditions(m): mock = MagicMock() m.add_transition('proceed', 'A', 'C', conditions=synced_true, after=mock) await m.proceed() assert m.state == 'C' mock.assert_called_once_with() async def test_multiple_models(machine_cls): m1 = machine_cls(states=['A', 'B', 'C'], initial='A', name="m1") m2 = machine_cls(states=['A'], initial='A', name='m2') m1.add_transition(trigger='go', source='A', dest='B', before=cancel_soon) m1.add_transition(trigger='fix', source='A', dest='C', after=cancel_soon) m1.add_transition(trigger='check', source='C', dest='B', conditions=await_false) m1.add_transition(trigger='reset', source='C', dest='A') m2.add_transition(trigger='go', source='A', dest=None, conditions=m1.is_C, after=m1.reset) async with anyio.create_task_group() as tg: tg.start_soon(m1.go) tg.start_soon(call_delayed, m1.fix, 0.05) tg.start_soon(call_delayed, m1.check, 0.07) tg.start_soon(call_delayed, m2.go, 0.1) assert m1.is_A() async def test_async_callback_arguments(m): async def process(should_fail=True): if should_fail is not False: raise ValueError("should_fail has been set") m.on_enter_B(process) with pytest.raises(ValueError): await m.go() await m.to_A() await m.go(should_fail=False) async def test_async_callback_event_data(machine_cls): state_a = machine_cls.state_cls('A') state_b = machine_cls.state_cls('B') def sync_condition(event_data): return event_data.state == state_a async def async_conditions(event_data): return event_data.state == state_a async def async_callback(event_data): assert event_data.state == state_b def sync_callback(event_data): assert event_data.state == state_b m = machine_cls(states=[state_a, state_b], initial='A', send_event=True) m.add_transition('go', 'A', 'B', conditions=[sync_condition, async_conditions], after=[sync_callback, async_callback]) m.add_transition('go', 'B', 'A', conditions=sync_condition) await m.go() assert m.is_B() is True await m.go() assert m.is_B() is True async def test_async_callback_trigger(machine_cls): mock_processed = MagicMock() async def on_event(event_data): await event_data.model.to_C() mock_processed() m = machine_cls(states=['A', 'B', 'C'], transitions=[dict(trigger='go', source='A', dest='B', after=on_event)], initial='A', send_event=True) await m.go() assert m.is_C() assert mock_processed.called async def test_async_invalid_triggers(m): await m.to_B() with pytest.raises(MachineError): await m.go() m.ignore_invalid_triggers = True await m.go() assert m.is_B() is True async def test_async_dispatch(machine_cls): model1 = DummyModel() model2 = DummyModel() model3 = DummyModel() machine = machine_cls(model=None, states=['A', 'B', 'C'], transitions=[['go', 'A', 'B'], ['go', 'B', 'C'], ['go', 'C', 'A']], initial='A') machine.add_model(model1) machine.add_model(model2, initial='B') machine.add_model(model3, initial='C') await machine.dispatch('go') assert model1.is_B() is True assert 'C' == model2.state assert machine.initial == model3.state # @pytest.mark.xfail(reason="we should investigate") async def test_queued(machine_cls): states = ['A', 'B', 'C', 'D'] # Define with list of dictionaries async def change_state(machine): assert machine.state == 'A' if machine.has_queue: await machine.run(machine=machine) assert machine.state == 'A' else: with pytest.raises(MachineError): await machine.run(machine=machine) async def raise_machine_error(event_data): assert event_data.machine.has_queue is True await event_data.model.to_A() event_data.machine._queued = False await event_data.model.to_C() async def raise_exception(event_data): await event_data.model.to_C() raise ValueError("Clears queue") transitions = [ {'trigger': 'walk', 'source': 'A', 'dest': 'B', 'before': change_state}, {'trigger': 'run', 'source': 'B', 'dest': 'C'}, {'trigger': 'sprint', 'source': 'C', 'dest': 'D'} ] m = machine_cls(states=states, transitions=transitions, initial='A') await m.walk(machine=m) assert 'B' == m.state m = machine_cls(states=states, transitions=transitions, initial='A', queued=True) await m.walk(machine=m) assert 'C' == m.state m = machine_cls(states=states, initial='A', queued=True, send_event=True, before_state_change=raise_machine_error) with pytest.raises(MachineError): await m.to_C() m = machine_cls(states=states, initial='A', queued=True, send_event=True) m.add_transition('go', 'A', 'B', after='go') m.add_transition('go', 'B', 'C', before=raise_exception) with pytest.raises(ValueError): await m.go() assert 'B' == m.state async def test_callback_order(machine_cls): finished = [] class Model: async def before(self): await anyio.sleep(0.1) finished.append(2) async def after(self): await anyio.sleep(0.1) finished.append(3) async def after_state_change(): finished.append(4) async def before_state_change(): finished.append(1) model = Model() m = machine_cls( model=model, states=['start', 'end'], after_state_change=after_state_change, before_state_change=before_state_change, initial='start', ) m.add_transition('transit', 'start', 'end', after='after', before='before') await model.transit() assert finished == [1, 2, 3, 4] async def test_nested_async(): mock = MagicMock() async def sleep_mock(): await anyio.sleep(0.1) mock() states = ['A', 'B', {'name': 'C', 'children': ['1', {'name': '2', 'children': ['a', 'b'], 'initial': 'a'}, '3'], 'initial': '2'}] transitions = [{'trigger': 'go', 'source': 'A', 'dest': 'C', 'after': [sleep_mock] * 100}] machine = HierarchicalAnyIOMachine(states=states, transitions=transitions, initial='A') await machine.go() assert 'C{0}2{0}a'.format(machine.state_cls.separator) == machine.state assert 100 == mock.call_count async def test_parallel_async(): states = ['A', 'B', {'name': 'P', 'parallel': [ {'name': '1', 'children': ['a'], 'initial': 'a'}, {'name': '2', 'children': ['b', 'c'], 'initial': 'b'}, {'name': '3', 'children': ['x', 'y', 'z'], 'initial': 'y'}]}] machine = HierarchicalAnyIOMachine(states=states, initial='A') await machine.to_P() assert [ 'P{0}1{0}a'.format(machine.state_cls.separator), 'P{0}2{0}b'.format(machine.state_cls.separator), 'P{0}3{0}y'.format(machine.state_cls.separator) ] == machine.state await machine.to_B() assert machine.is_B() is True

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8,924

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0

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0.004545

0

null

0

null

0

1

0

8b3a120d3d802f1bacae4d23b235c03a8bccc3c2

6,263

py

Python

ditto/scripts/chat_bot.py

Kvoti/ditto

eb4efb241e54bf679222d14afeb71d9d5441c122

[ "BSD-3-Clause" ]

null

ditto/scripts/chat_bot.py

Kvoti/ditto

eb4efb241e54bf679222d14afeb71d9d5441c122

[ "BSD-3-Clause" ]

9

2015-11-10T15:17:22.000Z

2015-11-12T11:07:02.000Z

ditto/scripts/chat_bot.py

Kvoti/ditto

eb4efb241e54bf679222d14afeb71d9d5441c122

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ Chat admin bot to open and close the chatroom. Run via cron. SleekXMPP: The Sleek XMPP Library Copyright (C) 2010 Nathanael C. Fritz This file is part of SleekXMPP. See the file LICENSE for copying permission. """ import sys import logging import getpass from optparse import OptionParser from time import sleep import sleekxmpp import chat.utils # Python versions before 3.0 do not use UTF-8 encoding # by default. To ensure that Unicode is handled properly # throughout SleekXMPP, we will set the default encoding # ourselves to UTF-8. if sys.version_info < (3, 0): from sleekxmpp.util.misc_ops import setdefaultencoding setdefaultencoding('utf8') else: raw_input = input # Need to query the domain here as doing it inside SendMsgBot doesnt work DOMAIN = chat.utils.domain() class SendMsgBot(sleekxmpp.ClientXMPP): def __init__(self, jid, password, actions): self.me = jid self.actions = actions sleekxmpp.ClientXMPP.__init__(self, jid, password) # The session_start event will be triggered when # the bot establishes its connection with the server # and the XML streams are ready for use. We want to # listen for this event so that we we can initialize # our roster. self.add_event_handler("session_start", self.start, threaded=True) def start(self, event): """ Process the session_start event. Typical actions for the session_start event are requesting the roster and broadcasting an initial presence stanza. Arguments: event -- An empty dictionary. The session_start event does not provide any additional data. """ self.send_presence() self.get_roster() for action in self.actions: room = "%s@muc.%s" % (action['room'].slug, DOMAIN) self.plugin['xep_0045'].joinMUC(room, "chatadmin", # If a room password is needed, use: # password=the_room_password, pfrom=self.me, wait=True) if action['action'] == 'open': config = self.plugin['xep_0045'].getRoomConfig(room) if action['members']: logging.warn('setting member only %s' % room) config.field['muc#roomconfig_membersonly']['value'] = 1 else: config.field['muc#roomconfig_membersonly']['value'] = 0 self.plugin['xep_0045'].configureRoom(room, ifrom=self.me, form=config) for member in action['members']: self.plugin['xep_0045'].setAffiliation( room, ifrom=self.me, jid=jid(member) ) else: # TODO maybe destroy is too strong here, should just set # unusable password or set to private room with no # participants? self.plugin['xep_0045'].destroy(room, ifrom=self.me) if action['action'] == 'open': action['room'].is_opened = True action['room'].is_closed = False else: action['room'].is_closed = True action['room'].is_opened = False action['room'].save() self.disconnect(wait=True) def jid(username): return "%s@%s" % (username, DOMAIN) def run(): # Setup logging. logging.basicConfig(level=logging.DEBUG, format='%(levelname)-8s %(message)s') # Iterate over the chatrooms in the django db and see which need # opened or closed actions = [] for room in chat.models.Room.objects.all(): if room.is_open() and not room.is_opened: # we set the members of the room once when we open it, we # don't keep checking if role changes mean changes to the # member list. # TODO maybe we should? # TODO can we use the chatserver idea of role? # TODO this could get very big, probably *need* to do something # smarter than using explicit member list members = list(room.members().values_list('username', flat=True)) actions.append({'room': room, 'action': 'open', 'members': members}) elif not room.is_open() and not room.is_closed: actions.append({'room': room, 'action': 'close'}) # TESTING import os if 'OPEN' in os.environ: room = chat.models.Room.objects.get(slug='main') actions = [{'room': room, 'action': 'open', 'members': []}] elif 'CLOSE' in os.environ: room = chat.models.Room.objects.get(slug='main') actions = [{'room': room, 'action': 'close'}] #################### # Setup the EchoBot and register plugins. Note that while plugins may # have interdependencies, the order in which you register them does # not matter. xmpp = SendMsgBot(jid("mark"), chat.utils.password("mark"), actions) xmpp.register_plugin('xep_0030') # Service Discovery xmpp.register_plugin('xep_0199') # XMPP Ping xmpp.register_plugin('xep_0045') # If you are working with an OpenFire server, you may need # to adjust the SSL version used: # xmpp.ssl_version = ssl.PROTOCOL_SSLv3 # If you want to verify the SSL certificates offered by a server: # xmpp.ca_certs = "path/to/ca/cert" # Connect to the XMPP server and start processing XMPP stanzas. if xmpp.connect((chat.utils.server(), 5222)): # If you do not have the dnspython library installed, you will need # to manually specify the name of the server if it does not match # the one in the JID. For example, to use Google Talk you would # need to use: # # if xmpp.connect(('talk.google.com', 5222)): # ... xmpp.process(block=True) print("Done") else: print("Unable to connect.")

36.841176

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0.021655

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0

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0

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0

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false

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0.025

0

null

0

null

0

1

0

8b3a1e66bfa48a8241c8827793551ccbe10ec13f

25,104

py

Python

peripheral/aic_11051/config/aic.py

Unitek-KL/csp

2ac7ba59465f23959e51d2f16a5712b57b79ef5f

[ "0BSD" ]

null

peripheral/aic_11051/config/aic.py

Unitek-KL/csp

2ac7ba59465f23959e51d2f16a5712b57b79ef5f

[ "0BSD" ]

null

peripheral/aic_11051/config/aic.py

Unitek-KL/csp

2ac7ba59465f23959e51d2f16a5712b57b79ef5f

[ "0BSD" ]

null

"""***************************************************************************** * Copyright (C) 2019 Microchip Technology Inc. and its subsidiaries. * * Subject to your compliance with these terms, you may use Microchip software * and any derivatives exclusively with Microchip products. It is your * responsibility to comply with third party license terms applicable to your * use of third party software (including open source software) that may * accompany Microchip software. * * THIS SOFTWARE IS SUPPLIED BY MICROCHIP "AS IS". NO WARRANTIES, WHETHER * EXPRESS, IMPLIED OR STATUTORY, APPLY TO THIS SOFTWARE, INCLUDING ANY IMPLIED * WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY, AND FITNESS FOR A * PARTICULAR PURPOSE. * * IN NO EVENT WILL MICROCHIP BE LIABLE FOR ANY INDIRECT, SPECIAL, PUNITIVE, * INCIDENTAL OR CONSEQUENTIAL LOSS, DAMAGE, COST OR EXPENSE OF ANY KIND * WHATSOEVER RELATED TO THE SOFTWARE, HOWEVER CAUSED, EVEN IF MICROCHIP HAS * BEEN ADVISED OF THE POSSIBILITY OR THE DAMAGES ARE FORESEEABLE. TO THE * FULLEST EXTENT ALLOWED BY LAW, MICROCHIP'S TOTAL LIABILITY ON ALL CLAIMS IN * ANY WAY RELATED TO THIS SOFTWARE WILL NOT EXCEED THE AMOUNT OF FEES, IF ANY, * THAT YOU HAVE PAID DIRECTLY TO MICROCHIP FOR THIS SOFTWARE. *****************************************************************************""" from os.path import join Log.writeInfoMessage( "Loading Interrupt Manager for " + Variables.get( "__PROCESSOR" ) ) ################################################################################ #### Public Globals -- variables used in this module and accessible from other files ################################################################################ global getInterruptName global interruptNamespace global interruptSymbolEnable global interruptSymbolHandler global interruptSymbolHandlerLock global interruptLastNameEnable global interruptLastNameHandler global interruptLastNameLock interruptNamespace = "core" interruptLastNameEnable = "_INTERRUPT_ENABLE" interruptLastNameHandler = "_INTERRUPT_HANDLER" interruptLastNameLock = "_INTERRUPT_HANDLER_LOCK" ################################################################################ global showSharedVectorsInMenu global numSharedVectors global sharedVectors global subVectorToSharedVector showSharedVectorsInMenu = False numSharedVectors = 0 sharedVectors = {} subVectorToSharedVector = {} ################################################################################ #### Static Globals -- variables intended to be used inside this file only ################################################################################ # not currently public global interruptsChildren global interruptLastNameMapType global interruptLastNameVector global interruptLastNameSrcType global interruptLastNamePriority global aicMenuTitle global aicRedirectionVisibility global aicMapTypeVisibility global aicPriorityOutputMode global aicPriorityChoices global aicSrcTypes global aicMinPriorityName global aicMaxPriorityName interruptLastNameMapType = "_INTERRUPT_MAP_TYPE" interruptLastNameVector = "_INTERRUPT_VECTOR" interruptLastNameSrcType = "_INTERRUPT_SRC_TYPE" interruptLastNamePriority = "_INTERRUPT_PRIORITY" interruptsChildren = ATDF.getNode( "/avr-tools-device-file/devices/device/interrupts" ).getChildren() aicMenuTitle = "" aicRedirectionVisibility = False aicMapTypeVisibility = False aicPriorityOutputMode = "" aicPriorityChoices = [] aicSrcTypes = [] aicMinPriorityName = "" aicMaxPriorityName = "" aicCodeGenerationDependencies = [] neverSecureList = [] alwaysSecureList = [] programmedSecureList = [] externalList = [] ################################################################################ #### Global Methods ################################################################################ def getInterruptName( interruptNode ): if "header:alternate-name" in interruptNode.getAttributeList(): retval = interruptNode.getAttribute( "header:alternate-name" ) else: retval = interruptNode.getAttribute( "name" ) return( str( retval ) ) ################################################################################ #### Local Methods ################################################################################ def getInterruptDescription( interruptNode ): if "header:alternate-caption" in interruptNode.getAttributeList(): retval = interruptNode.getAttribute( "header:alternate-caption" ) else: retval = interruptNode.getAttribute( "caption" ) return( str( retval ) ) global getNameValueCaptionTuple def getNameValueCaptionTuple( aGroupName, aTupleArray ): choiceNode = ATDF.getNode("/avr-tools-device-file/modules/module@[name=\"AIC\"]/value-group@[name=\"" + aGroupName + "\"]") if choiceNode: choiceValues = choiceNode.getChildren() del aTupleArray[:] for ii in range( 0, len( choiceValues ) ): aTupleArray.append( ( choiceValues[ ii ].getAttribute("name"), choiceValues[ ii ].getAttribute("value"), choiceValues[ ii ].getAttribute("caption") ) ) def getTupleNameContaining( aTupleArray, aString ): tupleName = "" if len( aTupleArray ): tupleName = aTupleArray[ 0 ][ 0 ] aString = aString.upper() for tuple in aTupleArray: if( aString in tuple[ 0 ].upper() ): tupleName = tuple[ 0 ] break return tupleName def aicMapTypeRedirectionCallback( aicMapType, eventDictionary ): if( True == eventDictionary[ "value" ] ): # Mapping Secure to NonSecure if( ("AlwaysSecure" == aicMapType.getDefaultValue()) or ("Secure" == aicMapType.getDefaultValue()) ): aicMapType.setValue( "RedirectedToNonSecure", 1 ) # make change evident for user else: if( ("AlwaysSecure" == aicMapType.getDefaultValue()) or ("Secure" == aicMapType.getDefaultValue()) ): aicMapType.clearValue() # restore the default value def priorityMapTypeCallback( aicVectorPriority, eventDictionary ): global aicMaxPriorityName if( ("AlwaysSecure" == eventDictionary[ "value" ]) or ("Secure" == eventDictionary[ "value" ]) ): aicVectorPriority.setSelectedKey( aicMaxPriorityName, 0 ) aicVectorPriority.setVisible( False ) else: aicVectorPriority.setVisible( True ) def aicCodeGenerationCallback( aicCodeGeneration, eventDictionary ): global interruptLastNameEnable # Interrupt enables and map type determine the code generation to be done later secureCount = 0 nonSecureCount = 0 for interrupt in interruptsChildren: interruptName = getInterruptName( interrupt ) component = aicCodeGeneration.getComponent() enableSymbol = component.getSymbolByID( interruptName + interruptLastNameEnable ) if( enableSymbol.getValue() ): mapTypeSymbol = component.getSymbolByID( interruptName + interruptLastNameMapType ) if( ("NeverSecure" == mapTypeSymbol.value) or ("NonSecure" == mapTypeSymbol.value) or ("RedirectedToNonSecure" == mapTypeSymbol.value) ): nonSecureCount = nonSecureCount + 1 else: secureCount = secureCount + 1 if secureCount and nonSecureCount: aicCodeGeneration.setValue( "AICandSAIC", 0xFF ) elif nonSecureCount: aicCodeGeneration.setValue( "AIC", 0xFF ) elif secureCount: aicCodeGeneration.setValue( "SAIC", 0xFF ) else: aicCodeGeneration.setValue( "NONE", 0xFF ) global aicVectorEnableCallback def aicVectorEnableCallback( aicVectorEnable, eventDictionary ): global sharedVectors desiredValue = eventDictionary[ "value" ] interrupt = eventDictionary[ "id" ].replace( interruptLastNameLock, "" ).replace( interruptLastNameEnable, "" ) aicVectorEnable.setReadOnly( True ) if aicVectorEnable.getDefaultValue() == desiredValue: aicVectorEnable.clearValue() else: aicVectorEnable.setValue( desiredValue, 1 ) aicVectorEnable.setReadOnly( False ) sharedInterrupt = subVectorToSharedVector.get( interrupt ) if( sharedInterrupt ): # check if any sibling is enabled component = aicVectorEnable.getComponent() desiredValue = False for elem in sharedVectors[ sharedInterrupt ]: vectorEnable = component.getSymbolByID( elem + interruptLastNameEnable ) if vectorEnable and vectorEnable.getValue(): desiredValue = True aicVectorEnable = component.getSymbolByID( sharedInterrupt + interruptLastNameEnable ) aicVectorEnable.setValue( desiredValue, 1 ) def setupEnableAndHandler( component, anInterrupt, aicVectorEnable, aicVectorHandler ): global sharedVectors enableDependencies = [] interruptName = getInterruptName( anInterrupt ) moduleInstance = anInterrupt.getAttribute( "module-instance" ).split() sharedVectorMaxShares = len( moduleInstance ) if 1 < sharedVectorMaxShares: aicVectorHandler.setReadOnly( True ) aicVectorHandler.setValue( interruptName + "_SharedHandler", 0 ) aicVectorHandler.setReadOnly( False ) sharedVectors[ interruptName ] = moduleInstance aicVectorHandler.setVisible( False ) for elem in moduleInstance: subVectorToSharedVector[ elem ] = interruptName subVectorEnable = component.createBooleanSymbol( elem + interruptLastNameEnable, aicVectorEnable ) subVectorEnable.setLabel( "Enable " + elem ) subVectorEnable.setDefaultValue( False ) subVectorEnable.setDependencies( aicVectorEnableCallback, [elem + interruptLastNameLock] ) enableDependencies.append( elem + interruptLastNameEnable ) # Parent enable depends on children subVectorHandlerLock = component.createBooleanSymbol( elem + interruptLastNameLock, subVectorEnable ) subVectorHandlerLock.setDefaultValue( False ) subVectorHandlerLock.setVisible( False ) subVectorHandler = component.createStringSymbol( elem + interruptLastNameHandler, subVectorEnable ) subVectorHandler.setLabel( elem + " Handler" ) subVectorHandler.setDefaultValue( elem + "_Handler" ) enableDependencies.append( interruptName + interruptLastNameLock ) aicVectorEnable.setDependencies( aicVectorEnableCallback, enableDependencies ) def setupSharedVectorFtlSymbols( component, anInterrupt, aicVectorEnable ): global showSharedVectorsInMenu global numSharedVectors interruptName = getInterruptName( anInterrupt ) moduleInstance = anInterrupt.getAttribute( "module-instance" ).split() numShares = len( moduleInstance ) if 1 < numShares: numSharedVectors = numSharedVectors + 1 # SHARED_VECTOR_N = "name", e.g. SHARED_VECTOR_1 = "SYSC" # Create a generic shared handler symbol with a value indicating the HANDLER sharedVector = component.createStringSymbol( "SHARED_VECTOR_" + str( numSharedVectors - 1 ), aicVectorEnable ) Database.clearSymbolValue( "core", interruptName + "SHARED_VECTOR_" + str( numSharedVectors - 1 ) ) sharedVector.setDefaultValue( interruptName ) sharedVector.setVisible( False ) sharedVectorNumShares = component.createIntegerSymbol( interruptName + "_NUM_SHARES", sharedVector ) sharedVectorNumShares.setMin( numShares ) sharedVectorNumShares.setMax( numShares ) Database.clearSymbolValue( "core", interruptName + "_NUM_SHARES" ) sharedVectorNumShares.setValue( numShares, 0 ) sharedVectorNumShares.setVisible( showSharedVectorsInMenu ) # Create symbols for the shared handler names # {SHARED_VECTOR_#}_HANDLER_#, e.g. # SYSC_HANDLER_0 = "PMC" ==> PMC_InterruptHandler # SYSC_HANDLER_1 = "RSTC" ==> RSTC_InterruptHandler # SYSC_HANDLER_2 = "RTC" ==> RTC_InterruptHandler ii = 0 for elem in moduleInstance: shareName = component.createStringSymbol( interruptName + "_SHARE_" + str( ii ), aicVectorEnable ) shareName.setDefaultValue( elem ) shareName.setVisible( showSharedVectorsInMenu ) ii = ii + 1 def formAicPyGlobalData( theProcessor, theCoreComponent ): global getNameValueCaptionTuple global aicMenuTitle global aicRedirectionVisibility global aicMapTypeVisibility global aicPriorityOutputMode global aicPriorityChoices global aicSrcTypes aicPriorityOutputMode = "Value" aicPrioritySymbolStem = "PRIORITY" getNameValueCaptionTuple( "AIC_SMR__" + aicPrioritySymbolStem, aicPriorityChoices ) if not len( aicPriorityChoices ): aicPrioritySymbolStem = "PRIOR" getNameValueCaptionTuple( "AIC_SMR__" + aicPrioritySymbolStem, aicPriorityChoices ) if not len( aicPriorityChoices ): # still not found in the atdf; so set some defaults aicPriorityChoices.append( ( "MINIMUM", "0x0", "Minimum priority" ) ) aicPriorityChoices.append( ( "VERY_LOW", "0x1", "Very low priority" ) ) aicPriorityChoices.append( ( "LOW", "0x2", "Low priority" ) ) aicPriorityChoices.append( ( "MEDIUM_LOW", "0x3", "Medium priority" ) ) aicPriorityChoices.append( ( "MEDIUM_HIGH","0x4", "Medium high priority" ) ) aicPriorityChoices.append( ( "HIGH", "0x5", "High priority" ) ) aicPriorityChoices.append( ( "VERY_HIGH", "0x6", "Very high priority" ) ) aicPriorityChoices.append( ( "MAXIMUM", "0x7", "Maximum priority" ) ) aicSmrPrioritySymbol = theCoreComponent.createStringSymbol( "AIC_SMR_PRIORITY_SYMBOL", None ) aicSmrPrioritySymbol.setDefaultValue( "AIC_SMR_" + aicPrioritySymbolStem ) aicSmrPrioritySymbol.setVisible( False ) # aicSrcTypeSymbolStem = "SRCTYPE" getNameValueCaptionTuple( "AIC_SMR__" + aicSrcTypeSymbolStem, aicSrcTypes ) aicSmrSrcTypeSymbol = theCoreComponent.createStringSymbol( "AIC_SMR_SRCTYPE_SYMBOL", None ) aicSmrSrcTypeSymbol.setDefaultValue( "AIC_SMR_" + aicSrcTypeSymbolStem ) aicSmrSrcTypeSymbol.setVisible( False ) # if "SAMA5" in theProcessor: aicMenuTitle = "Interrupts (AIC/SAIC)" aicRedirectionVisibility = True aicMapTypeVisibility = True neverSecureList = [ '49', '62' ] alwaysSecureList = [ '0', '14', '15', '16', '18', '51', '61', '68', '69', '70' ] programmedSecureList = [] # Todo create map interface to populate this list externalList = [ '0', '49' ] # '2', '56', '57', '64', '65', '66', '67', '71', '72' have been subsumed data sheet peripheral table is misleading elif "SAM9X60" in theProcessor: aicMenuTitle = "Interrupts" aicRedirectionVisibility = False aicMapTypeVisibility = False neverSecureList = [ str( ii ) for ii in list( range( 0, 50 ) ) ] # '0', '1',...'49' alwaysSecureList = [] programmedSecureList = [] externalList = [ '0', '31' ] ################################################################################ #### Component ################################################################################ theProcessor = Variables.get("__PROCESSOR") formAicPyGlobalData( theProcessor, coreComponent ) aicMinPriorityName = getTupleNameContaining( aicPriorityChoices, "min" ) aicMaxPriorityName = getTupleNameContaining( aicPriorityChoices, "max" ) aicMenu = coreComponent.createMenuSymbol( "AIC_MENU", cortexMenu ) aicMenu.setLabel( aicMenuTitle ) aicMenu.setDescription( "Configuration for AIC Initialization" ) ### Symbol for interrupt redirection decision aicRedirection = coreComponent.createBooleanSymbol( "SECURE_TO_NONSECURE_REDIRECTION", aicMenu ) aicRedirection.setLabel( "Secure to NonSecure Redirection" ) aicRedirection.setDefaultValue( True ) aicRedirection.setVisible( aicRedirectionVisibility ) aicVectorMax = coreComponent.createIntegerSymbol( "AIC_VECTOR_MAX", aicMenu ) aicVectorMax.setDefaultValue( Interrupt.getMaxInterruptID() ) aicVectorMax.setVisible( False ) aicVectorMax = coreComponent.createIntegerSymbol( "AIC_VECTOR_MIN", aicMenu ) aicVectorMax.setDefaultValue( Interrupt.getMinInterruptID() ) aicVectorMax.setVisible( False ) for interrupt in interruptsChildren: interruptName = getInterruptName( interrupt ) aicNumber = str( interrupt.getAttribute( "index" ) ) if aicNumber in neverSecureList: # secure to nonSecure redirection will have no effect mapTypeDefault = "NeverSecure" elif aicNumber in alwaysSecureList: # secure to nonSecure redirection will disable and hide these mapTypeDefault = "AlwaysSecure" elif aicNumber in programmedSecureList: # secure to nonSecure redirection will change mapType to 'RedirectedToNonSecure' and set highest priority mapTypeDefault = "Secure" else: # programmed nonSecure # secure to nonSecure redirection will have no effect mapTypeDefault = "NonSecure" # only for use by the aic ftl code aicInterruptFirstName = coreComponent.createStringSymbol( "AIC_FIRST_NAME_KEY" + aicNumber, None ) aicInterruptFirstName.setDefaultValue( interruptName ) aicInterruptFirstName.setVisible( False ) ### aicVectorEnable = coreComponent.createBooleanSymbol( interruptName + interruptLastNameEnable, aicMenu ) aicVectorEnable.setLabel( "Enable " + aicNumber + " -- " + getInterruptDescription( interrupt ) ) aicVectorEnable.setDefaultValue( False ) ### if (aicNumber in externalList): vectorPreCursor = "External Vector: " else: vectorPreCursor = "Internal Vector: " aicVectorSourceGUILabel = coreComponent.createCommentSymbol( interruptName + "_INTERRUPT_VECTOR_LABEL", aicVectorEnable ) aicVectorSourceGUILabel.setLabel( vectorPreCursor + interruptName + "_IRQn" ) # This is the same as aicVectorSourceGUILabel but creates a .var assignment accessible in plib_aic.c.ftl aicVectorSource = coreComponent.createStringSymbol( interruptName + interruptLastNameVector, aicVectorEnable ) aicVectorSource.setDefaultValue( interruptName + "_IRQn" ) aicVectorSource.setVisible( False ) ### aicVectorLock = coreComponent.createBooleanSymbol( interruptName + interruptLastNameLock, aicVectorEnable ) aicVectorLock.setDefaultValue( False ) aicVectorLock.setVisible( False ) aicVectorHandler = coreComponent.createStringSymbol( interruptName + interruptLastNameHandler, aicVectorEnable ) aicVectorHandler.setLabel( "Handler" ) aicVectorHandler.setDefaultValue( interruptName + "_Handler" ) ### setupEnableAndHandler( coreComponent, interrupt, aicVectorEnable, aicVectorHandler ) setupSharedVectorFtlSymbols( coreComponent, interrupt, aicVectorEnable ) # aicMapType = coreComponent.createStringSymbol( interruptName + interruptLastNameMapType, aicVectorEnable ) aicMapType.setLabel( "Map Type" ) aicMapType.setDefaultValue( mapTypeDefault ) aicMapType.setVisible( aicMapTypeVisibility ) aicMapType.clearValue() aicMapType.setReadOnly( True ) aicMapType.setDependencies( aicMapTypeRedirectionCallback, [ "SECURE_TO_NONSECURE_REDIRECTION" ] ) aicVectorSourceType = coreComponent.createKeyValueSetSymbol( interruptName + interruptLastNameSrcType, aicVectorEnable ) aicVectorSourceType.setLabel( "Source Type" ) for tupleElem in aicSrcTypes: if (aicNumber not in externalList) and ("internal" not in tupleElem[ 2 ]): continue aicVectorSourceType.addKey( tupleElem[ 0 ], tupleElem[ 1 ], tupleElem[ 2 ] ) aicVectorSourceType.setOutputMode( "Key" ) aicVectorSourceType.setDisplayMode( "Description" ) aicVectorSourceType.setDefaultValue( 0 ) aicVectorSourceType.setSelectedKey( str( aicSrcTypes[ 0 ][ 0 ] ), 0 ) aicVectorPriority = coreComponent.createKeyValueSetSymbol( interruptName + interruptLastNamePriority, aicVectorEnable ) aicVectorPriority.setLabel( "Priority" ) for tupleElem in aicPriorityChoices: aicVectorPriority.addKey( tupleElem[ 0 ], tupleElem[ 1 ], tupleElem[ 2 ] ) aicVectorPriority.setOutputMode( aicPriorityOutputMode ) aicVectorPriority.setDisplayMode( "Description" ) aicVectorPriority.setDefaultValue( 0 ) if( ("AlwaysSecure" == aicMapType.value) or ("Secure" == aicMapType.value) ): aicVectorPriority.setSelectedKey( aicMaxPriorityName, 0 ) aicVectorPriority.setVisible( False ) # fiq interrupts do not have a priority, but if the get forced nonSecure we want a reasonable value else: aicVectorPriority.setSelectedKey( aicMinPriorityName, 0 ) aicVectorPriority.setDependencies( priorityMapTypeCallback, [ interruptName + interruptLastNameMapType ] ) aicCodeGenerationDependencies.append( interruptName + interruptLastNameEnable ) # add to dependency list for code generation symbol aicCodeGenerationDependencies.append( interruptName + interruptLastNameMapType ) # add to dependency list for code generation symbol ### aicNumSharedVectors = coreComponent.createIntegerSymbol( "NUM_SHARED_VECTORS", aicMenu ) aicNumSharedVectors.setMin( numSharedVectors ) aicNumSharedVectors.setMax( numSharedVectors ) Database.clearSymbolValue( "core", "NUM_SHARED_VECTORS" ) aicNumSharedVectors.setValue( numSharedVectors, 1 ) aicNumSharedVectors.setVisible( showSharedVectorsInMenu ) ### Symbol for code generation decisions aicCodeGeneration = coreComponent.createComboSymbol( "AIC_CODE_GENERATION", aicMenu, [ "NONE", "AIC", "SAIC", "AICandSAIC" ] ) aicCodeGeneration.setDefaultValue( "NONE" ) aicCodeGeneration.setDependencies( aicCodeGenerationCallback, aicCodeGenerationDependencies ) aicCodeGeneration.setVisible( False ) ### aicRedirection.setValue( True, 0 ) # stimulate a aicMapTypeRedirectionCallback() by setting the aicRedirection value aicRedirection.setReadOnly( True ) ############################################################################ #### Code Generation ############################################################################ configName = Variables.get( "__CONFIGURATION_NAME" ) aicSystemDefFile = coreComponent.createFileSymbol( "SYSTEM_AIC_DEFINITIONS", None ) aicSystemDefFile.setType( "STRING" ) aicSystemDefFile.setSourcePath( "../peripheral/aic_11051/templates/system/definitions.h.ftl" ) aicSystemDefFile.setOutputName( "core.LIST_SYSTEM_DEFINITIONS_H_INCLUDES" ) aicSystemDefFile.setMarkup( True ) aicSystemInitFile = coreComponent.createFileSymbol( "SYS_AIC_INITIALIZE", None ) aicSystemInitFile.setType( "STRING" ) aicSystemInitFile.setSourcePath( "../peripheral/aic_11051/templates/system/initialization.c.ftl" ) aicSystemInitFile.setOutputName( "core.LIST_SYSTEM_INIT_C_SYS_INITIALIZE_PERIPHERALS" ) aicSystemInitFile.setMarkup( True ) aicSystemIntWeakHandleFile = coreComponent.createFileSymbol( "AIC_WEAK_HANDLERS", None ) aicSystemIntWeakHandleFile.setType( "STRING" ) aicSystemIntWeakHandleFile.setSourcePath( "../peripheral/aic_11051/templates/system/interrupt_weak_handlers.h.ftl" ) aicSystemIntWeakHandleFile.setOutputName( "core.LIST_SYSTEM_INTERRUPT_WEAK_HANDLERS" ) aicSystemIntWeakHandleFile.setMarkup( True ) aicSharedHandlerFile = coreComponent.createFileSymbol( "AIC_SHARED_HANDLERS", None ) aicSharedHandlerFile.setType( "STRING" ) aicSharedHandlerFile.setSourcePath( "../peripheral/aic_11051/templates/system/interrupt_shared_handlers.h.ftl" ) aicSharedHandlerFile.setOutputName( "core.LIST_SYSTEM_INTERRUPT_SHARED_HANDLERS" ) aicSharedHandlerFile.setMarkup( True ) aicSourceFile = coreComponent.createFileSymbol( "AIC_SOURCE", None ) aicSourceFile.setType( "SOURCE" ) aicSourceFile.setProjectPath( "config/" + configName + "/peripheral/aic/" ) aicSourceFile.setSourcePath( "../peripheral/aic_11051/templates/plib_aic.c.ftl" ) aicSourceFile.setDestPath( "/peripheral/aic/" ) aicSourceFile.setOutputName( "plib_aic.c" ) aicSourceFile.setMarkup( True ) aicSourceFile.setOverwrite( True ) aicSourceFile.setEnabled( True ) aicHeaderFile = coreComponent.createFileSymbol( "AIC_HEADER", None ) aicHeaderFile.setType( "HEADER" ) aicHeaderFile.setProjectPath( "config/" + configName + "/peripheral/aic/" ) aicHeaderFile.setSourcePath( "../peripheral/aic_11051/templates/plib_aic.h.ftl" ) aicHeaderFile.setDestPath( "/peripheral/aic/" ) aicHeaderFile.setOutputName( "plib_aic.h" ) aicHeaderFile.setMarkup( True ) aicHeaderFile.setOverwrite( True ) aicHeaderFile.setEnabled( True )

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null

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null

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8b3af0e86d5663788d4b0dfe5890096086d9ac78

765

py

Python

etl/utils/__init__.py

cfh294/ElectionModeling

714da9ea004f042f9f775804168e3761e34f64f0

[ "MIT" ]

null

etl/utils/__init__.py

cfh294/ElectionModeling

714da9ea004f042f9f775804168e3761e34f64f0

[ "MIT" ]

null

etl/utils/__init__.py

cfh294/ElectionModeling

714da9ea004f042f9f775804168e3761e34f64f0

[ "MIT" ]

null

""" Some utility functions """ from sqlalchemy.orm import sessionmaker from sqlalchemy import create_engine from models import Election, ElectionType, PoliticalParty, Campaign database_string = "sqlite:///election.db" def get_session(cnxn_string): return sessionmaker( create_engine(cnxn_string) )() def get_campaign(session, year, party_id, election_type="PRESIDENTIAL", cand_name=None): election = session.query(Election).filter_by( election_type=session.query(ElectionType).filter_by(code=election_type).first(), year=year ).first() pp = session.query(PoliticalParty).filter_by(code=party_id).first() return session.query(Campaign).filter_by( political_party=pp, election=election ).first()

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null

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8b3bf65902f5df3d7d2afeef5fe91c29fecdf077

711

py

Python

tests/test_validators.py

ridone6/AVWX-API

615f27df5c3c0e8ecdbfd0bba67fe54f65e63f6d

[ "MIT" ]

null

tests/test_validators.py

ridone6/AVWX-API

615f27df5c3c0e8ecdbfd0bba67fe54f65e63f6d

[ "MIT" ]

null

tests/test_validators.py

ridone6/AVWX-API

615f27df5c3c0e8ecdbfd0bba67fe54f65e63f6d

[ "MIT" ]

1

2020-09-23T10:33:56.000Z

""" Michael duPont - michael@mdupont.com tests/test_validators.py - Test parameter validators """ # library import pytest from voluptuous import Invalid # module import avwx_api.validators as validators def test_splitin(): """ Tests that SplitIn returns a split string only containing certain values """ validator = validators.SplitIn(("test", "values", "here")) good_strings = ("test,values,here", "here", "values,test") for string in good_strings: assert string.split(",") == validator(string) bad_strings = ("testvalues", "test,stuff", "crazy,nulls", "what?" "really,") for string in bad_strings: with pytest.raises(Invalid): validator(string)

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0.058577

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711

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0.333333

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null

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null

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1

0

8b3cb1567dcbf6e80a939bd6354346e43a2a18ad

314

py

Python

yacht/utils/misc.py

IusztinPaul/portfolio-management

42cb9d046201fedcc3e3b522af04c32cfcc571ed

[ "MIT" ]

1

2021-07-22T13:44:20.000Z

yacht/utils/misc.py

IusztinPaul/portfolio-management

42cb9d046201fedcc3e3b522af04c32cfcc571ed

[ "MIT" ]

null

yacht/utils/misc.py

IusztinPaul/portfolio-management

42cb9d046201fedcc3e3b522af04c32cfcc571ed

[ "MIT" ]

null

def calc_chunksize(n_workers, len_iterable, factor=4): """Calculate chunksize argument for Pool-methods. Resembles source-code within `multiprocessing.pool.Pool._map_async`. """ chunksize, extra = divmod(len_iterable, n_workers * factor) if extra: chunksize += 1 return chunksize

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0

0.4

0

null

0

null

0

1

0

8b3de86420a3a5739ac46c06ed28a78c9136f086

3,514

py

Python

old_version/PITF_old.py

JasonLC506/CollaborativeFiltering

055b9c2494c89357a269a8e0a1b5b2ed91aa0eae

[ "MIT" ]

1

2020-07-28T09:49:59.000Z

old_version/PITF_old.py

JasonLC506/CollaborativeFiltering

055b9c2494c89357a269a8e0a1b5b2ed91aa0eae

[ "MIT" ]

null

old_version/PITF_old.py

JasonLC506/CollaborativeFiltering

055b9c2494c89357a269a8e0a1b5b2ed91aa0eae

[ "MIT" ]

null

""" pairwise interaction tensor factorization (PITF) model, pairwise comapison among tags and pairwise decomposition of tensor by user-tag and item-tag additively, based on Rendle, S. and Schmidt-Thieme, L., 2010, February. Pairwise interaction tensor factorization for personalized tag recommendation. In Proceedings of the third ACM international conference on Web search and data mining (pp. 81-90). ACM. [1] """ import numpy as np from CDMultiClass import CD SCALE = 0.01 class PITF(CD): def __init__(self): CD.__init__(self) self.r_u = None self.r_v = None self.lamda = 0.000 self.SCALE = SCALE def basicInitialize(self): self.r_u = np.random.normal(0.0, self.SCALE, size = (self.L, self.k)) self.r_v = np.random.normal(0.0, self.SCALE, size = (self.L, self.k)) def update(self, instance, isamp): uid, iid, lid = instance lid_neg_list = [i for i in range(self.L)] del lid_neg_list[lid] m = np.tensordot(self.r_u, self.u[uid], axes = (1,0)) + np.tensordot(self.r_v, self.v[iid], axes = (1,0)) delt_u = np.zeros(self.k, dtype=np.float64) delt_v = np.zeros(self.k, dtype=np.float64) delt_r_u = np.zeros([self.L, self.k], dtype=np.float64) delt_r_v = np.zeros([self.L, self.k], dtype=np.float64) for lid_neg in lid_neg_list: delt = (1.0 - sigmoid(m[lid] - m[lid_neg])) delt_u += (delt * (self.r_u[lid] - self.r_u[lid_neg]) - self.lamda * self.u[uid]) delt_v += (delt * (self.r_v[lid] - self.r_v[lid_neg]) - self.lamda * self.v[iid]) delt_r_u[lid] += (delt * self.u[uid] - self.lamda * self.r_u[lid]) delt_r_u[lid_neg] += (- delt * self.u[uid] - self.lamda * self.r_u[lid_neg]) delt_r_v[lid] += (delt * self.v[iid] - self.lamda * self.r_v[lid]) delt_r_v[lid_neg] += (- delt * self.v[iid] - self.lamda * self.r_v[lid_neg]) # update # self.u[uid] += (self.SGDstep * delt_u) self.v[iid] += (self.SGDstep * delt_v) self.r_u += (self.SGDstep * delt_r_u) self.r_v += (self.SGDstep * delt_r_v) return self def loss(self, test): losssum = 0.0 Nsamp = 0 for samp in test.sample(random=False): losssum += self.lossSingle(samp) Nsamp += 1 for uid in self.u.keys(): losssum = losssum + self.lamda * np.power(np.linalg.norm(self.u[uid]),2) for iid in self.v.keys(): losssum = losssum + self.lamda * np.power(np.linalg.norm(self.v[iid]),2) losssum = losssum + self.lamda * (np.power(np.linalg.norm(self.r_u), 2) + np.power(np.linalg.norm(self.r_v), 2)) return losssum / Nsamp def lossSingle(self, instance): uid, iid, lid = instance self.initialize(uid,iid,predict=True) m = np.tensordot(self.r_u, self.u[uid], axes = (1,0)) + np.tensordot(self.r_v, self.v[iid], axes = (1,0)) lid_neg_list = [i for i in range(self.L)] del lid_neg_list[lid] loss = 0.0 for lid_neg in lid_neg_list: loss += np.log(sigmoid(m[lid] - m[lid_neg])) loss = - loss return loss def predict(self, uid, iid, distribution = False): self.initialize(uid, iid, predict=True) m = np.tensordot(self.r_u, self.u[uid], axes = (1,0)) + np.tensordot(self.r_v, self.v[iid], axes = (1,0)) return np.argmax(m) def sigmoid(a): return 1.0 / (1.0 + np.exp(-a))

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238

0.594195

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3,514

3.533333

0.194737

0.054618

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0.047666

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0.398709

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0.255265

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null

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null

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1

0

8b3f8a7ed1ad3b93c99803e80ebfd47461faecd4

4,572

py

Python

hand_eye_calibration/python/hand_eye_calibration/hand_eye_calibration_plotting_tools.py

Chatoyant19/handeye_calibration

590c93eba0fef835d0be6da0d750f71e4891a8fb

[ "BSD-3-Clause" ]

333

2017-09-25T03:24:05.000Z

2022-03-31T12:09:13.000Z

hand_eye_calibration/python/hand_eye_calibration/hand_eye_calibration_plotting_tools.py

bygreencn/hand_eye_calibration

5d5077572d650a5491040a4a90d98850df4cf068

[ "BSD-3-Clause" ]

40

2017-09-15T13:39:20.000Z

2021-11-24T15:44:03.000Z

hand_eye_calibration/python/hand_eye_calibration/hand_eye_calibration_plotting_tools.py

bygreencn/hand_eye_calibration

5d5077572d650a5491040a4a90d98850df4cf068

[ "BSD-3-Clause" ]

108

2017-09-19T02:34:35.000Z

2022-03-18T10:08:34.000Z

import matplotlib.pyplot as plt from matplotlib.patches import FancyArrowPatch from mpl_toolkits.mplot3d import (proj3d, Axes3D) import copy import numpy as np import tf from hand_eye_calibration.dual_quaternion import DualQuaternion from hand_eye_calibration.quaternion import Quaternion class Arrow3D(FancyArrowPatch): def __init__(self, xs, ys, zs, *args, **kwargs): FancyArrowPatch.__init__(self, (0, 0), (0, 0), *args, **kwargs) self._verts3d = xs, ys, zs def draw(self, renderer): xs3d, ys3d, zs3d = self._verts3d xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M) self.set_positions((xs[0], ys[0]), (xs[1], ys[1])) FancyArrowPatch.draw(self, renderer) def compute_bbox_3D(poses_list): bbox_min = np.zeros((len(poses_list), 3)) bbox_max = np.zeros((len(poses_list), 3)) for i in range(0, len(poses_list)): poses = poses_list[i] bbox_min[i, :] = np.amin(poses[:, 0:3], axis=0) bbox_max[i, :] = np.amax(poses[:, 0:3], axis=0) return (np.amax(bbox_max, axis=0), np.amin(bbox_min, axis=0)) def plot_poses(poses_list, plot_arrows=True, title="", blocking=True): title_position = 1.05 fig = plt.figure() plt.clf() ax = Axes3D(fig) if title: fig.suptitle(title, fontsize='24') colors = ['r', 'g', 'b', 'c', 'm', 'k'] num_colors = len(colors) assert len(poses_list) < num_colors, ( "Need to define more colors to plot more trajectories!") (bbox_max, bbox_min) = compute_bbox_3D(poses_list) arrow_size = np.linalg.norm(bbox_max - bbox_min) * 0.05 arrow_width = 2 axis_min = np.amin(bbox_min) axis_max = np.amax(bbox_max) ax.set_xlim3d(axis_min, axis_max) ax.set_ylim3d(axis_min, axis_max) ax.set_zlim3d(axis_min, axis_max) for i in range(0, len(poses_list)): poses = poses_list[i].copy() # Plot line. positions = ax.plot(xs=poses[:, 0], ys=poses[:, 1], zs=poses[:, 2], color=colors[i]) for pose in poses: # Position point ax.plot([pose[0]], [pose[1]], [pose[2]], 'o', markersize=5, color=colors[i], alpha=0.5) if not plot_arrows: continue rotation_quaternion = Quaternion(q=pose[3:7]) x_rotated = rotation_quaternion.rotate_vector([1, 0, 0, 0]) x_rotated *= arrow_size a = Arrow3D( [pose[0], pose[0] + x_rotated[0] ], [pose[1], pose[1] + x_rotated[1]], [pose[2], pose[2] + x_rotated[2]], mutation_scale=20, lw=arrow_width, arrowstyle="-|>", color="r") ax.add_artist(a) y_rotated = rotation_quaternion.rotate_vector([0, 1, 0, 0]) y_rotated *= arrow_size a = Arrow3D( [pose[0], pose[0] + y_rotated[0] ], [pose[1], pose[1] + y_rotated[1]], [pose[2], pose[2] + y_rotated[2]], mutation_scale=20, lw=arrow_width, arrowstyle="-|>", color="g") ax.add_artist(a) z_rotated = rotation_quaternion.rotate_vector([0, 0, 1, 0]) z_rotated *= arrow_size a = Arrow3D( [pose[0], pose[0] + z_rotated[0] ], [pose[1], pose[1] + z_rotated[1]], [pose[2], pose[2] + z_rotated[2]], mutation_scale=20, lw=arrow_width, arrowstyle="-|>", color="b") ax.add_artist(a) ax.auto_scale_xyz([axis_min, axis_max], [ axis_min, axis_max], [axis_min, axis_max]) plt.show(block=blocking) def plot_alignment_errors(errors_position, rmse_pose, errors_orientation, rmse_orientation, blocking=True): assert np.array_equal(errors_position.shape, errors_orientation.shape) num_error_values = errors_position.shape[0] title_position = 1.05 fig = plt.figure() a1 = fig.add_subplot(2, 1, 1) fig.suptitle("Alignment Evaluation", fontsize='24') a1.set_title( "Red = Position Error Norm [m] - Black = RMSE", y=title_position) plt.plot(errors_position, c='r') plt.plot(rmse_pose * np.ones((num_error_values, 1)), c='k') a2 = fig.add_subplot(2, 1, 2) a2.set_title( "Red = Absolute Orientation Error [Degrees] - Black = RMSE", y=title_position) plt.plot(errors_orientation, c='r') plt.plot(rmse_orientation * np.ones((num_error_values, 1)), c='k') if plt.get_backend() == 'TkAgg': mng = plt.get_current_fig_manager() max_size = mng.window.maxsize() max_size = (max_size[0], max_size[1] * 0.45) mng.resize(*max_size) fig.tight_layout() plt.subplots_adjust(left=0.025, right=0.975, top=0.8, bottom=0.05) plt.show(block=blocking)

31.102041

84

0.627734

686

4,572

3.975219

0.249271

0.033003

0.025669

0.030803

0.380271

0.296296

0.20022

0.179685

0.121012

0.083608

0

0.040011

0.218285

4,572

146

85

31.315068

0.722999

0.005468

0

0.2

0

0.045344

0

0.017391

1

0.043478

false

0

0.069565

0

0.130435

0

null

0

null

0

1

0

8b403f2a06db8daf6d77e02536351a2ffa3d1999

2,049

py

Python

utils/DataFormatter.py

kaantecik/covid-prediction

8d2a788cc93d07b4bfcffb9480b747e41e13848f

[ "MIT" ]

1

2021-05-05T06:47:57.000Z

utils/DataFormatter.py

kaantecik/covid-prediction

8d2a788cc93d07b4bfcffb9480b747e41e13848f

[ "MIT" ]

null

utils/DataFormatter.py

kaantecik/covid-prediction

8d2a788cc93d07b4bfcffb9480b747e41e13848f

[ "MIT" ]

null

import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.metrics import mean_absolute_error class DataFormatter(object): @staticmethod def get_data(country=None, path=None): df = pd.read_csv(path) df = df.drop(columns=["Province/State", "Lat", "Long"]) df = (df.melt(id_vars=['Country/Region'], var_name='Date', value_name='Cases').assign(Date=lambda x: pd.to_datetime(x['Date']))) index = pd.date_range(start='2020-1-22', end='2021-4-27', freq="D") if country: df = df.loc[df['Country/Region'] == country] df = df.reset_index() df = df.drop(columns=["index"]) df = pd.Series([value['Cases'] for key, value in df.iterrows()], index=index) return df else: data = [] for date in index: case = int(df.loc[df['Date'] == date].sum(axis=0).values[1]) data.append(case) total_cases = pd.Series(data, index=index) return total_cases @staticmethod def mse(actual, predicted): difference_array = np.subtract(actual, predicted) squared_array = np.square(difference_array) mse = squared_array.mean() return mse @staticmethod def mae(actual, predicted): return mean_absolute_error(actual, predicted) @staticmethod def r_square(actual, predicted): correlation_matrix = np.corrcoef(actual, predicted) correlation_xy = correlation_matrix[0, 1] r_squared = correlation_xy ** 2 return round(r_squared, 5) @staticmethod def draw(data, forecast): plt.figure(figsize=(12, 8)) plt.plot(data, marker='o', color='black') plt.plot(forecast, marker='o', color='blue') line1, = plt.plot(data, marker='o', color='black') line2, = plt.plot(forecast, marker='o', color='blue') plt.legend([line1, line2], ['Test', 'Forecast']) plt.show()

34.15

108

0.584675

254

2,049

4.61811

0.440945

0.076726

0.040921

0.025575

0.100597

0

0.018268

0.278673

2,049

59

109

34.728814

0.775372

0

0.1

0

0.062958

0

1

0.1

false

0

0.08

0.02

0.3

0

null

0

null

0

1

0

8b43f5ce83fe89d5b91dcaf42b2b3a83264d1771

566

py

Python

tools/token_types.py

RiatTahiri/gabbs

b0a9acc2fb868a8037ee3e2eee9134d31cca411d

[ "MIT" ]

null

tools/token_types.py

RiatTahiri/gabbs

b0a9acc2fb868a8037ee3e2eee9134d31cca411d

[ "MIT" ]

null

tools/token_types.py

RiatTahiri/gabbs

b0a9acc2fb868a8037ee3e2eee9134d31cca411d

[ "MIT" ]

null

from enum import Enum class Types(Enum): LEFT_PAREN = 101 RIGHT_PAREN = 102 LEFT_BRACE = 103 RIGHT_BRACE = 104 COMMA = 105 DOT = 106 MINUS = 107 PLUS = 108 SEMICOLON = 109 SLASH = 110 STAR = 111 BANG, BANG_EQUAL, EQUAL, EQUAL_EQUAL, GREATER, GREATER_EQUAL, LESS, LESS_EQUAL, IDENTIFIER, STRING, NUMBER, AND, CLASS, ELSE, FALSE, FUN, FOR, IF, NIL, OR, PRINT, RETURN, SUPER, THIS, TRUE, VAR, WHILE, EOF = -0

12.304348

21

0.519435

66

566

4.333333

0.772727

0.104895

0

0.10089

0.404594

566

46

22

12.304348

0.747774

0

1

0

false

0

0.02439

0

0.341463

0

null

0

null

0

1

0

8b479e6fd1fb470817da900e89adc53b74973c6b

224

py

Python

example.py

leitao-bcc/studious-engine

a38b04e9f70b82c1451ba5bfc20c26a0a190d9b1

[ "Unlicense" ]

null

example.py

leitao-bcc/studious-engine

a38b04e9f70b82c1451ba5bfc20c26a0a190d9b1

[ "Unlicense" ]

null

example.py

leitao-bcc/studious-engine

a38b04e9f70b82c1451ba5bfc20c26a0a190d9b1

[ "Unlicense" ]

null

from os import getcwd from race.race import Racing def main(): racing_obj = Racing() racing_obj.parser_logfile('{}/data/log_example'.format(getcwd())) print(racing_obj) if __name__ == "__main__": main()

16

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0.683036

30

224

4.666667

0.6

0.192857

0

0.183036

224

14

70

16

0.765027

0

0.12

0

1

0.125

false

0

0.25

0

0.375

0.125

0

null

0

null

0

1

0

8b4b27460ec741891e3e3e6b670a42d8a780ce8b

909

py

Python

backend/run.py

codestrange/calendario-matcom

fa5a742d3ae3e8f6c7635022a6984409b731ea92

[ "MIT" ]

8

2019-02-12T20:03:03.000Z

2020-09-08T03:51:25.000Z

backend/run.py

codestrange/calendario-matcom

fa5a742d3ae3e8f6c7635022a6984409b731ea92

[ "MIT" ]

11

2021-02-01T05:17:42.000Z

2021-04-27T05:13:46.000Z

backend/run.py

codestrange/calendario-matcom

fa5a742d3ae3e8f6c7635022a6984409b731ea92

[ "MIT" ]

4

2019-03-06T22:13:56.000Z

2021-02-03T05:37:43.000Z

from os import getenv from app import create_app from app.database import db, Course, Event, Group, Interval, Local, Notification, Option, \ Permission, Resource, Role, Student, Tag, Teacher, User, Vote, UserGroupNotification app = create_app(getenv('FLASK_CONFIG') or 'default') @app.shell_context_processor def make_shell_context(): return dict(app=app, db=db, Course=Course, Event=Event, Group=Group, Interval=Interval, Local=Local, Notification=Notification, Option=Option, Permission=Permission, Resource=Resource, Role=Role, Student=Student, Tag=Tag, Teacher=Teacher, User=User, Vote=Vote, UserGroupNotification=UserGroupNotification) @app.cli.command() def init(): insert(Role, 'roles') insert(Interval, 'intervals') def insert(model, name): print(f'Inserting {name} ...') model.insert() print(f'Inserted {name} - OK')

33.666667

93

0.706271

110

909

5.772727

0.436364

0.022047

0

0.172717

909

26

94

34.961538

0.844415

0

0.080308

0

1

0.157895

false

0

0.157895

0.052632

0.368421

0.105263

0

null

0

null

0

1

0

8b4b47722179eef3ae76ed74451ae1ccc107cfc2

3,955

py

Python

core/modules/config.py

tangb/cleep-desktop

7e333b0ce8445fad86216c4b51b1ade8c21695fd

[ "MIT" ]

2

2020-07-31T13:24:05.000Z

2022-03-10T08:44:06.000Z

core/modules/config.py

tangb/cleep-desktop

7e333b0ce8445fad86216c4b51b1ade8c21695fd

[ "MIT" ]

6

2020-04-09T16:44:28.000Z

2022-02-22T11:26:24.000Z

core/modules/config.py

tangb/cleep-desktop

7e333b0ce8445fad86216c4b51b1ade8c21695fd

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -* from functools import reduce from core.utils import CleepDesktopModule class Config(CleepDesktopModule): """ Config module. Handles application configuration """ def __init__(self, context, app_config, debug_enabled): """ Constructor Args: context (AppContext): application context app_config (AppConfig): application config instance debug_enabled (bool): True if debug is enabled """ CleepDesktopModule.__init__(self, context, debug_enabled) # members self.app_config = app_config def set_config_value(self, key, value): """ Save specified value on specified key Args: key (string): key to update. Can be a deep key like xxx.yyy.zzz Returns: bool: True if value updated """ def walk(node, keys, value): key = keys.pop(0) if len(keys)==0: # leaf, update value if key in node.keys(): node[key] = value return True else: # self.context.main_logger.debug('+++++++++ Key "%s" not found' % key) return False elif key in node.keys(): return walk(node[key], keys, value) else: # self.context.main_logger.debug('----------Key "%s" not found' % key) return False config = self.app_config.load_config() if walk(config, key.split('.'), value): return self.set_config(config) return False def set_config(self, config): """ Save config file. Args: config (dict): config to save. Returns: bool: True if file successfully saved, False otherwise """ old = self.app_config.load_config() # process debug flag if old['cleep']['debug']!=config['cleep']['debug']: if config['cleep']['debug']: self.context.main_logger.setLevel(True) for _, module in self.context.modules.items(): module.set_debug(True) else: self.context.main_logger.setLevel(False) for _, module in self.context.modules.items(): module.set_debug(False) # process crashreport flag if old['cleep']['crashreport']!=config['cleep']['crashreport']: if config['cleep']['crashreport']: self.crash_report.enable() else: self.crash_report.disable() return self.app_config.save_config(config) def get_config_value(self, key): """ Return config value for specified key Args: key (string): config key. Can be deep key like xxx.yyy.zzz Returns: any: config key value """ config = self.app_config.load_config() return self.__deep_get(config, key) def get_config(self): """ Returns config Returns: dict: config file content """ return { 'config': self.app_config.load_config(), 'logs': self.context.log_filepath, 'cachedir': self.context.paths.cache, } def __deep_get(self, dictionary, keys, default=None): """ Deep dict value get with complex key "part1.part2.part3" Note: https://stackoverflow.com/a/46890853 Args: dictionnary: dict to search onto keys (string): key (x.x.x) default (any): default value when nothing found Returns: any: value or default if not found """ return reduce(lambda d, key: d.get(key, default) if isinstance(d, dict) else default, keys.split("."), dictionary)

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427

3,955

4.871194

0.29274

0.052885

0.0375

0.040385

0.236538

0.183654

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0.1

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0.356511

3,955

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0.811788

0.312263

0

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0

0.041684

0

1

0.137255

false

0

0.039216

0

0.392157

0

null

0

null

0

1

0

8b4ba1e1247e6d819ae250ab5b176460d8aa3e9b

4,285

py

Python

example.py

brego81/Legrand-BTicino-Python-API

e1c2eb1677fd356306c0755e677a957c108f6b6e

[ "Apache-2.0" ]

null

example.py

brego81/Legrand-BTicino-Python-API

e1c2eb1677fd356306c0755e677a957c108f6b6e

[ "Apache-2.0" ]

1

2022-01-06T17:18:19.000Z

2022-01-09T10:26:00.000Z

example.py

brego81/Legrand-BTicino-Python-API

e1c2eb1677fd356306c0755e677a957c108f6b6e

[ "Apache-2.0" ]

null

from LegrandBiticinoAPI import LegrandBiticinoAPI import pprint as pp import datetime API = LegrandBiticinoAPI() # Test the API using and echo endpoint as per documentation # https://portal.developer.legrand.com/docs/services/echo-api/operations/create-resource out = API.echo() if out['status_code'] == 200: print("It works fine!") else: raise SystemExit("ERROR: " + str(out['status_code'])) # Plants - Operation used to retrieve all the plants associated to a user. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Plants plants = API.get_plants() plantId = plants['text']['plants'][0]['id'] print("plantId = " + str(plantId)) # Topology - Operation used to retrieve the complete topology of a plant. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Topology modules = API.get_topology(plantId) moduleId = modules['text']['plant']['modules'][0]['id'] print("moduleId = " + str(moduleId)) # Chronothermostat Measures - Operation used to retrieve the measured temperature and humidity detected by a chronothermostat. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Chronothermostat-Measures out = API.get_chronothermostat_measures(plantId, moduleId) if out['status_code'] == 200: print('Chronothermostat measures = ') pp.pprint(out['text']) else: raise SystemExit("ERROR -> " + str(out)) # Chronothermostat ProgramList - Operation used to retrieve the list of programs managed by a chronothermostat. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Chronothermostat-ProgramList out = API.get_chronothermostat_programlist(plantId, moduleId) if out['status_code'] == 200: print('Chronothermostat programlist = ') pp.pprint(out['text']) else: raise SystemExit("ERROR -> " + str(out)) # Get Chronothermostat Status - Operation used to retrieve the complete status of a chronothermostat. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Get-Chronothermostat-Status status = API.get_chronothermostat_status(plantId, moduleId) if out['status_code'] == 200: print('Chronothermostat status = ') pp.pprint(status['text']) else: raise SystemExit("ERROR -> " + str(status)) # As example, we want to set to AUTOMATIC if a temeprature is manually defined if status['text']['chronothermostats'][0]['mode'] != 'AUTOMATIC': print("setPoint = " + status['chronothermostats'][0]['setPoint']['value'] + "\n") data = { "function": "heating", "mode": "AUTOMATIC", "setPoint": { "value": "18.20000", "unit": "C" }, "programs": [ { "number": 1 }], "activationTime": datetime.datetime.now().strftime("%Y-%m-%dT%H:%M:%S") } # Set Chronothermostat Status - Operation used to set the status of a chronothermostat. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Set-Chronothermostat-Status out = API.set_chronothermostat_status(plantId, moduleId, data) print(str(out) + "\n") # Get subscriptions to C2C notifications - Operation used to get subscriptions of a user to get Cloud2Cloud notifications of a plant. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Get-subscriptions-to-C2C-notifications subscriptions = API.get_subscriptions_C2C_notifications() if subscriptions['status_code'] == 204: print("No subscription associated with this user") elif subscriptions['status_code'] == 200: pp.pprint(subscriptions['text']) # Subscribe to C2C notifications - Operation used to subscribe a user to get Cloud2Cloud notifications of a plant. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Subscribe-to-C2C-notifications data = {"EndPointUrl": "http://www.example.com"} out = API.set_subscribe_C2C_notifications(plantId, data) print(str(out['status_code']) + " " + out['text']) # Delete subscription to C2C notifications - Operation used to delete the subscription of a user to get Cloud2Cloud notifications of a plant. # https://portal.developer.legrand.com/docs/services/smartherV2/operations/Delete-subscription-to-C2C-notifications subscriptionId = '123' out = API.delete_subscribe_C2C_notifications(plantId, subscriptionId) print(str(out['status_code']) + " " + out['text'])

49.825581

141

0.744457

532

4,285

5.943609

0.225564

0.034788

0.063251

0.085389

0.517078

0.450032

0.370651

0.339658

0.268817

0

0.014358

0.122287

4,285

86

142

49.825581

0.826376

0.482614

0

0.259259

0

0.257741

0

1

0

false

0

0.055556

0

0.055556

0.296296

0

null

0

null

0

1

0

8c68d7cb9c3f3209998f1769aded9bdf8c7b676c

3,417

py

Python

tst/test_fbmatrix.py

sharky5102/fbmatrix

6558e1b249d94908d92a6475b07ebf9beae776a1

[ "BSD-2-Clause" ]

4

2021-01-31T07:06:33.000Z

2022-01-22T09:28:21.000Z

tst/test_fbmatrix.py

sharky5102/fbmatrix

6558e1b249d94908d92a6475b07ebf9beae776a1

[ "BSD-2-Clause" ]

3

2021-03-02T20:31:41.000Z

2021-12-18T12:52:59.000Z

tst/test_fbmatrix.py

sharky5102/fbmatrix

6558e1b249d94908d92a6475b07ebf9beae776a1

[ "BSD-2-Clause" ]

3

2021-08-02T17:10:24.000Z

2022-02-14T11:24:49.000Z

import sys import numpy as np import OpenGL.GL as gl import OpenGL.GLUT as glut import time import fbo import signal import displays.ws2811 import displays.hub75e import geometry.simple import assembly.tree import fbmatrix import unittest from OpenGL.GL.EXT.framebuffer_object import * def hub75_decompose(data): pixels = np.frombuffer(data, dtype=[('r', 'B'), ('g', 'B'), ('b', 'B'), ('a', 'B')]) channels = { 'D': ('r', 0), 'LAT': ('r', 1), 'A': ('r', 2), 'B2': ('r', 3), 'E': ('r', 4), 'B': ('r', 6), 'C': ('r', 7), 'R2': ('g', 0), 'G1': ('g', 1), 'G2': ('g', 4), 'CLK': ('g', 5), 'OE': ('b', 0), 'R1': ('b', 1), 'B1': ('b', 2) } output = {} for name, source in channels.items(): channel = np.bitwise_and(pixels[source[0]], 1 << source[1]) channel = np.where(channel > 0, np.ubyte(ord('1')), np.ubyte(ord('_'))) output[name] = channel.tobytes().decode('utf-8') return output def scanlines(data, stride): if len(data) % stride != 0: raise RuntimeError('Data len %d not divisible by stride %d' % (len(data), stride)) end = len(data) for i in range(0, int(len(data)/stride)): yield data[end-(i+1)*stride:end-i*stride] def parseFrameData(data, width): for scanline in scanlines(data, width * 4): yield hub75_decompose(scanline) def hub75ToText(data, width): n = 0; for decomposed in parseFrameData(data, width): yield 'Scanline %d' % n for chan in [ 'A', 'B', 'C', 'D', 'E', 'OE', 'LAT', 'CLK', 'R1', 'G1', 'B1', 'R2', 'G2', 'B2' ]: yield('%05s %s' % (chan, decomposed[chan])) n+=1 class TestHub75(unittest.TestCase): height = 194 width = 4096 maxDiff = None def setup(self): pass def testPatternWhite(self): gl.glClearColor(1,1,1,1) gl.glClear(gl.GL_COLOR_BUFFER_BIT | gl.GL_DEPTH_BUFFER_BIT) def writeFrameData(self, filename, data): with open(filename, 'wt') as f: for line in hub75ToText(data, self.width): f.write(line + '\n') def assertFrameData(self, filename, data): self.writeFrameData(filename + '.new', data) with open(filename, 'rt') as f: for expected, actual in zip(f.readlines(), hub75ToText(data, self.width)): self.assertEquals(expected.rstrip(), actual) def testSimple16Scan(self): self.renderer = fbmatrix.renderer() screen = fbo.FBO(self.width, self.height) with screen: self.renderer.render = lambda: self.testPatternWhite() self.renderer.display() data = gl.glReadPixels(0, 0, 4096, 194, gl.GL_RGBA, gl.GL_UNSIGNED_BYTE, None); self.assertFrameData('tst/data/hub75_32x32_white.txt', data) def testFieldFirstOrder(self): self.renderer = fbmatrix.renderer(order='field-first') screen = fbo.FBO(self.width, self.height) with screen: self.renderer.render = lambda: self.testPatternWhite() self.renderer.display() data = gl.glReadPixels(0, 0, 4096, 194, gl.GL_RGBA, gl.GL_UNSIGNED_BYTE, None); self.assertFrameData('tst/data/hub75_fieldfirst_32x32_white.txt', data)

29.973684

104

0.560433

433

3,417

4.371824

0.34642

0.012678

0.020602

0.02113

0.234548

0.20074

0

0.04099

0.2789

3,417

113

105

30.238938

0.727273

0

0.113636

0

0.066452

0.020785

0

0.045455

1

0.113636

false

0.011364

0.159091

0

0.329545

0

null

0

null

0

1

0

8c6e96f01c0a7304a221f7c9aae7d4b2f501a42a

8,181

py

Python

keystone-moon/keystone/catalog/routers.py

hashnfv/hashnfv-moon

daaba34fa2ed4426bc0fde359e54a5e1b872208c

[ "Apache-2.0" ]

null

keystone-moon/keystone/catalog/routers.py

hashnfv/hashnfv-moon

daaba34fa2ed4426bc0fde359e54a5e1b872208c

[ "Apache-2.0" ]

1

2019-08-18T09:25:49.000Z

keystone-moon/keystone/catalog/routers.py

hashnfv/hashnfv-moon

daaba34fa2ed4426bc0fde359e54a5e1b872208c

[ "Apache-2.0" ]

1

2021-03-21T11:38:30.000Z

# Copyright 2012 OpenStack Foundation # # 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 functools from keystone.catalog import controllers from keystone.common import json_home from keystone.common import router from keystone.common import wsgi build_resource_relation = functools.partial( json_home.build_v3_extension_resource_relation, extension_name='OS-EP-FILTER', extension_version='1.0') build_parameter_relation = functools.partial( json_home.build_v3_extension_parameter_relation, extension_name='OS-EP-FILTER', extension_version='1.0') ENDPOINT_GROUP_PARAMETER_RELATION = build_parameter_relation( parameter_name='endpoint_group_id') class Routers(wsgi.RoutersBase): """API for the keystone catalog. The API Endpoint Filter looks like:: PUT /OS-EP-FILTER/projects/{project_id}/endpoints/{endpoint_id} GET /OS-EP-FILTER/projects/{project_id}/endpoints/{endpoint_id} HEAD /OS-EP-FILTER/projects/{project_id}/endpoints/{endpoint_id} DELETE /OS-EP-FILTER/projects/{project_id}/endpoints/{endpoint_id} GET /OS-EP-FILTER/endpoints/{endpoint_id}/projects GET /OS-EP-FILTER/projects/{project_id}/endpoints GET /OS-EP-FILTER/projects/{project_id}/endpoint_groups GET /OS-EP-FILTER/endpoint_groups POST /OS-EP-FILTER/endpoint_groups GET /OS-EP-FILTER/endpoint_groups/{endpoint_group_id} HEAD /OS-EP-FILTER/endpoint_groups/{endpoint_group_id} PATCH /OS-EP-FILTER/endpoint_groups/{endpoint_group_id} DELETE /OS-EP-FILTER/endpoint_groups/{endpoint_group_id} GET /OS-EP-FILTER/endpoint_groups/{endpoint_group_id}/projects GET /OS-EP-FILTER/endpoint_groups/{endpoint_group_id}/endpoints PUT /OS-EP-FILTER/endpoint_groups/{endpoint_group}/projects/ {project_id} GET /OS-EP-FILTER/endpoint_groups/{endpoint_group}/projects/ {project_id} HEAD /OS-EP-FILTER/endpoint_groups/{endpoint_group}/projects/ {project_id} DELETE /OS-EP-FILTER/endpoint_groups/{endpoint_group}/projects/ {project_id} """ PATH_PREFIX = '/OS-EP-FILTER' PATH_PROJECT_ENDPOINT = '/projects/{project_id}/endpoints/{endpoint_id}' PATH_ENDPOINT_GROUPS = '/endpoint_groups/{endpoint_group_id}' PATH_ENDPOINT_GROUP_PROJECTS = PATH_ENDPOINT_GROUPS + ( '/projects/{project_id}') def append_v3_routers(self, mapper, routers): regions_controller = controllers.RegionV3() endpoint_filter_controller = controllers.EndpointFilterV3Controller() endpoint_group_controller = controllers.EndpointGroupV3Controller() project_endpoint_group_controller = ( controllers.ProjectEndpointGroupV3Controller()) routers.append(router.Router(regions_controller, 'regions', 'region', resource_descriptions=self.v3_resources)) # Need to add an additional route to support PUT /regions/{region_id} mapper.connect( '/regions/{region_id}', controller=regions_controller, action='create_region_with_id', conditions=dict(method=['PUT'])) routers.append(router.Router(controllers.ServiceV3(), 'services', 'service', resource_descriptions=self.v3_resources)) routers.append(router.Router(controllers.EndpointV3(), 'endpoints', 'endpoint', resource_descriptions=self.v3_resources)) self._add_resource( mapper, endpoint_filter_controller, path=self.PATH_PREFIX + '/endpoints/{endpoint_id}/projects', get_action='list_projects_for_endpoint', rel=build_resource_relation(resource_name='endpoint_projects'), path_vars={ 'endpoint_id': json_home.Parameters.ENDPOINT_ID, }) self._add_resource( mapper, endpoint_filter_controller, path=self.PATH_PREFIX + self.PATH_PROJECT_ENDPOINT, get_head_action='check_endpoint_in_project', put_action='add_endpoint_to_project', delete_action='remove_endpoint_from_project', rel=build_resource_relation(resource_name='project_endpoint'), path_vars={ 'endpoint_id': json_home.Parameters.ENDPOINT_ID, 'project_id': json_home.Parameters.PROJECT_ID, }) self._add_resource( mapper, endpoint_filter_controller, path=self.PATH_PREFIX + '/projects/{project_id}/endpoints', get_action='list_endpoints_for_project', rel=build_resource_relation(resource_name='project_endpoints'), path_vars={ 'project_id': json_home.Parameters.PROJECT_ID, }) self._add_resource( mapper, endpoint_group_controller, path=self.PATH_PREFIX + '/projects/{project_id}/endpoint_groups', get_action='list_endpoint_groups_for_project', rel=build_resource_relation( resource_name='project_endpoint_groups'), path_vars={ 'project_id': json_home.Parameters.PROJECT_ID, }) self._add_resource( mapper, endpoint_group_controller, path=self.PATH_PREFIX + '/endpoint_groups', get_action='list_endpoint_groups', post_action='create_endpoint_group', rel=build_resource_relation(resource_name='endpoint_groups')) self._add_resource( mapper, endpoint_group_controller, path=self.PATH_PREFIX + self.PATH_ENDPOINT_GROUPS, get_head_action='get_endpoint_group', patch_action='update_endpoint_group', delete_action='delete_endpoint_group', rel=build_resource_relation(resource_name='endpoint_group'), path_vars={ 'endpoint_group_id': ENDPOINT_GROUP_PARAMETER_RELATION }) self._add_resource( mapper, project_endpoint_group_controller, path=self.PATH_PREFIX + self.PATH_ENDPOINT_GROUP_PROJECTS, get_head_action='get_endpoint_group_in_project', put_action='add_endpoint_group_to_project', delete_action='remove_endpoint_group_from_project', rel=build_resource_relation( resource_name='endpoint_group_to_project_association'), path_vars={ 'project_id': json_home.Parameters.PROJECT_ID, 'endpoint_group_id': ENDPOINT_GROUP_PARAMETER_RELATION }) self._add_resource( mapper, endpoint_group_controller, path=self.PATH_PREFIX + self.PATH_ENDPOINT_GROUPS + ( '/projects'), get_action='list_projects_associated_with_endpoint_group', rel=build_resource_relation( resource_name='projects_associated_with_endpoint_group'), path_vars={ 'endpoint_group_id': ENDPOINT_GROUP_PARAMETER_RELATION }) self._add_resource( mapper, endpoint_group_controller, path=self.PATH_PREFIX + self.PATH_ENDPOINT_GROUPS + ( '/endpoints'), get_action='list_endpoints_associated_with_endpoint_group', rel=build_resource_relation( resource_name='endpoints_in_endpoint_group'), path_vars={ 'endpoint_group_id': ENDPOINT_GROUP_PARAMETER_RELATION })

44.704918

78

0.663

893

8,181

5.701008

0.160134

0.112355

0.043214

0.042428

0.672952

0.593597

0.546455

0.514241

0.45001

0.308387

0

0.003911

0.249847

8,181

182

79

44.950549

0.825648

0.237379

0

0.439024

0

0.190912

0.123897

0

1

0.00813

false

0

0.04065

0

0.089431

0

null

0

null

0

1

0

8c7093c6406e83e10ac8bb087f77ed632e0fff46

1,520

py

Python

Notebooks/Brain-Tumor-Detection/displayTumor.py

Abhijit2505/Grokking-Machine-Learning-

e088eeecacaa93d0bc87478b20d3401b5699224e

[ "MIT" ]

43

2020-12-18T17:18:22.000Z

2022-03-10T08:09:45.000Z

Notebooks/Brain-Tumor-Detection/displayTumor.py

Abhijit2505/Grokking-Machine-Learning-

e088eeecacaa93d0bc87478b20d3401b5699224e

[ "MIT" ]

232

2020-12-24T20:33:30.000Z

2021-05-28T16:03:13.000Z

Notebooks/Brain-Tumor-Detection/displayTumor.py

Abhijit2505/Grokking-Machine-Learning-

e088eeecacaa93d0bc87478b20d3401b5699224e

[ "MIT" ]

94

2020-12-21T18:17:36.000Z

2021-12-14T17:37:56.000Z

import numpy as np import cv2 as cv class DisplayTumor: curImg = 0 Img = 0 def readImage(self, img): self.Img = np.array(img) self.curImg = np.array(img) gray = cv.cvtColor(np.array(img), cv.COLOR_BGR2GRAY) self.ret, self.thresh = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV + cv.THRESH_OTSU) def getImage(self): return self.curImg # noise removal def removeNoise(self): self.kernel = np.ones((3, 3), np.uint8) opening = cv.morphologyEx(self.thresh, cv.MORPH_OPEN, self.kernel, iterations=2) self.curImg = opening def displayTumor(self): # sure background area sure_bg = cv.dilate(self.curImg, self.kernel, iterations=3) # Finding sure foreground area dist_transform = cv.distanceTransform(self.curImg, cv.DIST_L2, 5) ret, sure_fg = cv.threshold(dist_transform, 0.7 * dist_transform.max(), 255, 0) # Find unknown region sure_fg = np.uint8(sure_fg) unknown = cv.subtract(sure_bg, sure_fg) # Marker labelling ret, markers = cv.connectedComponents(sure_fg) # Add one to all labels so that sure background is not 0, but 1 markers = markers + 1 # Now mark the region of unknown with zero markers[unknown == 255] = 0 markers = cv.watershed(self.Img, markers) self.Img[markers == -1] = [255, 0, 0] tumorImage = cv.cvtColor(self.Img, cv.COLOR_HSV2BGR) self.curImg = tumorImage

31.666667

97

0.628289

208

1,520

4.509615

0.403846

0.063966

0.031983

0

0.032374

0.268421

1,520

48

98

31.666667

0.811151

0.133553

0

1

0.137931

false

0

0.068966

0.034483

0.344828

0

null

0

null

0

1

0

8c7265999435df509fcf7bb2ce25c3a081ad847b

3,196

py

Python

macaw/core/mrc/drqa_mrc.py

SouvickG/macaw

7d55d25c364118d45e3d62f05a29d912be2ebe9c

[ "MIT" ]

146

2019-12-19T23:15:58.000Z

2022-03-18T02:48:48.000Z

macaw/core/mrc/drqa_mrc.py

SouvickG/macaw

7d55d25c364118d45e3d62f05a29d912be2ebe9c

[ "MIT" ]

6

2020-02-11T11:43:32.000Z

2022-02-14T16:11:38.000Z

macaw/core/mrc/drqa_mrc.py

SouvickG/macaw

7d55d25c364118d45e3d62f05a29d912be2ebe9c

[ "MIT" ]

43

2019-12-21T08:40:25.000Z

2022-01-10T08:14:35.000Z

import os import sys from abc import ABC, abstractmethod import drqa from drqa.reader import Predictor """ A wrapper to the DrQA model from FAIR: https://github.com/facebookresearch/DrQA Authors: Hamed Zamani (hazamani@microsoft.com) """ from macaw.core.retrieval.doc import Document class MRC(ABC): @abstractmethod def __init__(self, params): """ An abstract class for machine reading comprehension models implemented in Macaw. Args: params(dict): A dict containing some mandatory and optional parameters. """ self.params = params @abstractmethod def get_results(self, conv_list, doc): """ This method is called to get the answer(s) to a question. Args: conv_list(list): List of util.msg.Message, each corresponding to a conversational message from / to the user. This list is in reverse order, meaning that the first elements is the last interaction made by user. doc(Document): A document (core.retrieval.doc.Document) that potentially contains the answer. Returns: The inherited class should implements this method and return a list of Documents each containing a candidate answer and its confidence score. """ pass class DrQA(MRC): def __init__(self, params): """ A machine reading comprehension model based on DrQA (https://github.com/facebookresearch/DrQA). Args: params(dict): A dict of parameters. Required parameters are: 'mrc_path': The path to the DrQA repository. 'corenlp_path': The path to the Stanford's corenlp toolkit. DrQA requires corenlp. 'mrc_model_path': The path to the learned DrQA parameters. 'qa_results_requested': The maximum number of candidate answers that should be found by DrQA. """ super().__init__(params) sys.path.insert(0, self.params['mrc_path']) drqa.tokenizers.set_default('corenlp_classpath', os.path.join(self.params['corenlp_path'], '*')) self.predictor = Predictor(self.params['mrc_model_path'], tokenizer='simple', num_workers=0, normalize=False) def get_results(self, conv_list, doc): """ This method returns the answers to the question. Args: conv_list(list): List of util.msg.Message, each corresponding to a conversational message from / to the user. This list is in reverse order, meaning that the first elements is the last interaction made by user. doc(Document): A document (core.retrieval.doc.Document) that potentially contains the answer. Returns: Returns a list of Documents each containing a candidate answer and its confidence score. The length of this list is less than or equal to the parameter 'qa_results_requested'. """ q = conv_list[0].text predictions = self.predictor.predict(doc, q, None, self.params['qa_results_requested']) results = [] for i, p in enumerate(predictions, 1): results.append(Document(None, None, p[0], p[1])) return results

37.6

120

0.663329

416

3,196

5.009615

0.341346

0.019194

0.023033

0.018714

0.426104

0.352207

0.315739

0

0.002527

0.257197

3,196

84

121

38.047619

0.875316

0.544743

0

0.230769

0

0.07457

0

1

0.153846

false

0.038462

0.230769

0

0.5

0

null

0

null

0

1

0

8c72dc73b844c661f77097244741e4573ea0a98e

463

py

Python

LeetCode/Easy/implement_strstr.py

CajetanP/programming-exercises

aee01ff3208ab14e7d0e0a7077798342123bc3e6

[ "MIT" ]

1

2017-06-23T16:39:17.000Z

LeetCode/Easy/implement_strstr.py

CajetanP/coding-exercises

aee01ff3208ab14e7d0e0a7077798342123bc3e6

[ "MIT" ]

10

2021-05-09T00:06:22.000Z

2021-09-02T12:07:41.000Z

LeetCode/Easy/implement_strstr.py

mrkajetanp/programming-exercises

aee01ff3208ab14e7d0e0a7077798342123bc3e6

[ "MIT" ]

null

#!/usr/bin/env python3 def strStr(haystack: str, needle: str) -> int: if len(needle) == 0: return 0 if len(haystack) == 0: return -1 for i in range(len(haystack)): if i+len(needle) > len(haystack): return -1 for j in range(len(needle)): if needle[j] == haystack[i+j]: if j == len(needle)-1: return i else: break return -1

21.045455

46

0.464363

60

463

3.583333

0.366667

0.167442

0.093023

0

0.029304

0.410367

463

21

47

22.047619

0.758242

0.045356

0

0.2

0

1

0.066667

false

0

0.4

0

null

0

null

0

1

0

8c7381c4fc0f9e79f1152b55fbb18bb5f202027f

1,174

py

Python

automation/create_db.py

kartikeyas00/cowin-automate

e32c1d5187349d9e68e8a0dc4325adedf49d7a1e

[ "MIT" ]

15

2021-05-26T13:51:33.000Z

2022-03-28T15:48:49.000Z

automation/create_db.py

krish-ag/cowin-automate

fa824ccdb7004893f12e4f15c3a22959f3916a3a

[ "MIT" ]

1

2021-05-24T05:28:35.000Z

2021-05-24T08:55:53.000Z

automation/create_db.py

kartikeyas00/cowin-automate

e32c1d5187349d9e68e8a0dc4325adedf49d7a1e

[ "MIT" ]

3

2021-05-24T03:52:09.000Z

2021-05-27T04:49:00.000Z

from automation.read_config import DATBASE_URL from sqlite3 import Error from automation.utils import create_connection SQL_CREATE_DAILY_STATISTICS = """ CREATE TABLE IF NOT EXISTS daily_statistics ( id integer PRIMARY KEY, district_name text NOT NULL, min_age_limit integer NOT NULL, vaccine text NOT NULL, available_capacity integer NOT NULL, timestamp datetime ); """ def create_table(conn, create_table_sql): """ Create table from the create_table_sql statement. Parameters ---------- conn : sqlite3.Connection Sqlite3 connection object. create_table_sql : str Create table sql statement. Returns ------- None. """ try: c = conn.cursor() c.execute(create_table_sql) conn.commit() except Error as e: conn.rollback() print(e) def run(): conn = create_connection(DATBASE_URL) # create table if conn is not None: # create daily_statistics table create_table(conn, SQL_CREATE_DAILY_STATISTICS) else: print("Error! cannot create the database connection.")

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0.642249

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1,174

5.268116

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0.283646

1,174

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63

22.150943

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0.074074

0

null

0

null

0

1

0

8c7486ea7b4fa9b8b9465470a75b89af68eb25e2

411

py

Python

users/urls.py

amjadcp/bookingLine-grpA-miniProject

f57fc06f85edfb08f9c170757fddbf7b6de6f35a

[ "PostgreSQL", "Unlicense", "MIT" ]

null

users/urls.py

amjadcp/bookingLine-grpA-miniProject

f57fc06f85edfb08f9c170757fddbf7b6de6f35a

[ "PostgreSQL", "Unlicense", "MIT" ]

null

users/urls.py

amjadcp/bookingLine-grpA-miniProject

f57fc06f85edfb08f9c170757fddbf7b6de6f35a

[ "PostgreSQL", "Unlicense", "MIT" ]

null

from django.urls import path from .views import * app_name='users' urlpatterns = [ path('signup-client', signup_client, name='signup-client'), path('signup-serviceprovider', signup_serviceprovider, name='signup-serviceprovider'), path('profile', profile, name='profile'), path('dashboard', dashboard, name='dashboard'), path('dashboard-client', dashboard_client, name='dashboard-client'), ]

37.363636

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0.725061

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411

6.391304

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0.122449

0

0.116788

411

11

91

37.363636

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0

0.337379

0.106796

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1

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false

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0.2

0

0.2

0

null

0

null

0

1

0

8c7753814f7329c609a7c87d2124c9854cf924ef

905

py

Python

setup.py

AlbertoMira/Project

38289707475252235098499174bb59b794a480d8

[ "MIT" ]

null

setup.py

AlbertoMira/Project

38289707475252235098499174bb59b794a480d8

[ "MIT" ]

null

setup.py

AlbertoMira/Project

38289707475252235098499174bb59b794a480d8

[ "MIT" ]

null

import re import ast from setuptools import setup _version_re = re.compile(r'__version__\s+=\s+(.*)') with open('preprocessing/__init__.py', 'rb') as f: version = str(ast.literal_eval(_version_re.search( f.read().decode('utf-8')).group(1))) setup( name='Project2', version=version, description='Import, preprocess and interpret EMG data for hand prosthesis', url='https://github.com/AlbertoMira/Project.git', license='MIT', author='Alberto Mira Criado, Johannes Payr', author_email=' ma8237@mci4me.at, j.payr@mci4me.at', platforms='any', packages=[ 'preprocessing' ], install_requires=[ 'numpy', 'scipy', 'click' ], entry_points=''' [console_scripts] preprocess=preprocessing.main:main ''' )

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905

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0.03629

0

0.014151

0.297238

905

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85

23.815789

0.765723

0

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0.089602

0

1

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false

0

0.137931

0

0.137931

0

null

0

null

0

1

0

8c7a40598f725b8f3ad34f2dba276b032d2670d2

2,283

py

Python

Today.py

U-Sharma/Today

185b117b9c34fc2a0f94a7909d17da3b3ce3e0e3

[ "MIT" ]

1

2019-06-04T11:46:14.000Z

Today.py

U-Sharma/Today

185b117b9c34fc2a0f94a7909d17da3b3ce3e0e3

[ "MIT" ]

null

Today.py

U-Sharma/Today

185b117b9c34fc2a0f94a7909d17da3b3ce3e0e3

[ "MIT" ]

null

# Datetime 1 from datetime import date def is_leap(ayear): # returns True if ayear is leap and False otherwise ayear = int(ayear) if ayear%400 == 0: return True elif ayear%100 == 0: return False elif ayear%4 == 0: return True else: return False def what_day_today(): # returns the day today date_today = date.today() # today's date year_today = int(date_today.year) # this year month_today = int(date_today.month) # this month day_today = int(date_today.day) # this day in this month days_total = day_today # Initialize days_total month_ = month_today - 1 # Initianize month_ which is number of months past this year year_ = year_today - 1 # Initianize year_ which is number of years past while month_ > 0: # Looping through month_ to calculate days past this year if month_ == 2: # For a february if is_leap(year_today): # In a leap year days_total += 29 # Add 29 days to days_total else: # Not in a leap year days_total += 28 # Add 28 days to days_total elif month_ == 1 or month_ == 3 or month_ == 5 or month_ == 7 or month_ == 8 or month_ == 10 or month_ == 12: # For the months with 31 days days_total += 31 # Add 31 to days_total else: # For the months with 30 days days_total += 30 # Add 30 to days_total month_ -= 1 # Move to the previous month while year_ >= 1970: # Looping through year_ to calculate number of days past from 1970 if is_leap(year_): # For a leap year days_total += 366 # Add 366 to days_total else: # For a year which is not leap days_total += 365 # Add 365 days to days_total year_ -= 1 # Move to the previous year # It was wednesday on 1st Jan 1970 if days_total%7 == 0: print("Wednesday") elif days_total%7 == 1: print("Thursday") elif days_total%7 == 2: print("Friday") elif days_total%7 == 3: print("Saturday") elif days_total%7 == 4: print("Sunday") elif days_total%7 == 5: print("Monday") else: print("Tuesday") what_day_today()

39.362069

148

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2,283

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2,283

58

149

39.362069

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0

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0

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0

1

0.039216

false

0

0.019608

0

0.137255

0

null

0

null

0

1

0

8c7c0ef0d22188d4f2f1d359d75764702b46655e

1,804

py

Python

msbdev/views.py

mattburlage/msb.dev

b2c574646d5ada35fbe5a236cbb1dec3793f4995

[ "MIT" ]

null

msbdev/views.py

mattburlage/msb.dev

b2c574646d5ada35fbe5a236cbb1dec3793f4995

[ "MIT" ]

null

msbdev/views.py

mattburlage/msb.dev

b2c574646d5ada35fbe5a236cbb1dec3793f4995

[ "MIT" ]

null

from django.shortcuts import render from rest_framework import status from rest_framework.decorators import api_view from rest_framework.response import Response from msbdev.models import AppSetting, ContactForm, TextCopy, WorkItem from msbdev.serializers import ContactFormSerializer def index(request): """ Handle standard page view""" # Render template context = { 'show_numbers': AppSetting.get_setting('show_numbers'), 'show_cur_numbers': AppSetting.get_setting('show_cur_numbers'), 'about_me_text': TextCopy.get_html('about_me_text'), 'work_items': WorkItem.objects.filter(active=True).order_by('order'), } return render(request, 'msbdev/msbdev2.html', context) def index2(request): """ Handle standard page view""" # Render template return render(request, 'msbdev/msbdev3.html') @api_view(['POST']) def submit_form(request): serializer = ContactFormSerializer(data=request.data) if serializer.is_valid(): email = serializer.validated_data['email'] note = serializer.validated_data['note'] try: if email in AppSetting.objects.get(name="EMAIL_BLACKLIST").content: return Response(status=status.HTTP_401_UNAUTHORIZED) except AppSetting.DoesNotExist: pass existing_form = ContactForm.objects.filter(email=email, note=note) if existing_form: existing_form = existing_form[0] existing_form.copies += 1 existing_form.save() return Response(data=serializer.data, status=status.HTTP_200_OK) serializer.save() return Response(data=serializer.data, status=status.HTTP_200_OK) else: return Response(data=serializer.errors, status=status.HTTP_400_BAD_REQUEST)

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1,804

5.851675

0.392345

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0.068684

0.214227

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0

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0.201774

1,804

55

84

32.8

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0.081081

false

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0

0.405405

0

null

0

null

0

1

0

8c7c4372702da805ee0f1b31fd8aadb800975492

2,599

py

Python

take_snapshot.py

LightningAA/YouTube-Playlist-Snapshot

46a90659fb099ee1e17780d10c9ac9b3b3e68240

[ "MIT" ]

1

2021-09-16T17:52:19.000Z

take_snapshot.py

LightningAA/YouTube-Playlist-Snapshot

46a90659fb099ee1e17780d10c9ac9b3b3e68240

[ "MIT" ]

null

take_snapshot.py

LightningAA/YouTube-Playlist-Snapshot

46a90659fb099ee1e17780d10c9ac9b3b3e68240

[ "MIT" ]

null

# https://pypi.org/project/requests/ import requests import json from datetime import datetime import os api_key = input('Enter your api key: (you can get one at https://console.developers.google.com/)\n') #api_key = 'hard_coded_api_key' playlist_id = input('Enter your playlist id:\n') #playlist_id = 'hard_coded_playlist_id' payload = {'part': 'snippet', 'playlistId': playlist_id, 'maxResults': 50, 'pageToken': None, 'key': api_key} response = requests.get('https://youtube.googleapis.com/youtube/v3/playlistItems', params=payload) response_json = response.json() videos_in_playlist = [] videos_processed = 0 while True: video_ids = [] for item in response_json['items']: video_ids.append(item['snippet']['resourceId']['videoId']) # make HTTP GET request video_payload = {'part': 'snippet', 'maxResults': 50, 'id': ','.join(video_ids), 'key': api_key} video_response = requests.get('https://youtube.googleapis.com/youtube/v3/videos', params=video_payload) video_response.raise_for_status() video_json = video_response.json() for video_resource in video_json['items']: video_snippet = video_resource['snippet'] videos_in_playlist.append({'title': video_snippet['title'], 'channelTitle': video_snippet['channelTitle']}) if not 'previousPageToken' in response_json and not 'nextPageToken' in response_json: break payload['pageToken'] = response_json['nextPageToken'] response = requests.get('https://youtube.googleapis.com/youtube/v3/playlistItems', params=payload) response.raise_for_status() response_json = response.json() videos_processed += response_json['pageInfo']['resultsPerPage'] print(str(videos_processed) + ' of ' + str(response_json['pageInfo']['totalResults']) + ' videos processed.', end='\r', flush=True) # get playlist name playlist_payload = {'part': 'snippet', 'id': playlist_id, 'key': api_key} playlist_response = requests.get("https://youtube.googleapis.com/youtube/v3/playlists", playlist_payload) playlist_response.raise_for_status() playlist_json = playlist_response.json() playlist_name = playlist_json['items'][0]['snippet']['title'] playlist_snapshot_count = len([f for f in os.listdir('.') if os.path.isfile(f) and f.startswith(playlist_name)]) snapshot_file_name = f"{playlist_name} Snapshot #{playlist_snapshot_count + 1}.json" with open(snapshot_file_name, 'w') as file: file.write(json.dumps({'timeTaken': datetime.now().isoformat(), 'playlistId': playlist_id, 'videos': videos_in_playlist})) print('Finished taking snapshot sucessfully.')

43.316667

135

0.727588

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5.446108

0.314371

0.079164

0.041781

0.052776

0.182518

0.153931

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0

0.004833

0.124279

2,599

60

136

43.316667

0.794376

0.054636

0

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0

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0.299755

0.010196

0

1

0

false

0

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0

null

0

null

0

1

0

8c7da5a8ffd720e5cba6875c433374448d66b500

1,408

py

Python

libc/AOR_v20.02/math/tools/plot.py

mkinsner/llvm

589d48844edb12cd357b3024248b93d64b6760bf

[ "Apache-2.0" ]

2,338

2018-06-19T17:34:51.000Z

2022-03-31T11:00:37.000Z

libc/AOR_v20.02/math/tools/plot.py

mkinsner/llvm

589d48844edb12cd357b3024248b93d64b6760bf

[ "Apache-2.0" ]

3,740

2019-01-23T15:36:48.000Z

2022-03-31T22:01:13.000Z

libc/AOR_v20.02/math/tools/plot.py

mkinsner/llvm

589d48844edb12cd357b3024248b93d64b6760bf

[ "Apache-2.0" ]

500

2019-01-23T07:49:22.000Z

2022-03-30T02:59:37.000Z

#!/usr/bin/env python # ULP error plot tool. # # Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. # See https://llvm.org/LICENSE.txt for license information. # SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception import numpy as np import matplotlib.pyplot as plt import sys import re # example usage: # build/bin/ulp -e .0001 log 0.5 2.0 2345678 | math/tools/plot.py def fhex(s): return float.fromhex(s) def parse(f): xs = [] gs = [] ys = [] es = [] # Has to match the format used in ulp.c r = re.compile(r'[^ (]+$([^ )]*)$ got ([^ ]+) want ([^ ]+) [^ ]+ ulp err ([^ ]+)') for line in f: m = r.match(line) if m: x = fhex(m.group(1)) g = fhex(m.group(2)) y = fhex(m.group(3)) e = float(m.group(4)) xs.append(x) gs.append(g) ys.append(y) es.append(e) elif line.startswith('PASS') or line.startswith('FAIL'): # Print the summary line print(line) return xs, gs, ys, es def plot(xs, gs, ys, es): if len(xs) < 2: print('not enough samples') return a = min(xs) b = max(xs) fig, (ax0,ax1) = plt.subplots(nrows=2) es = np.abs(es) # ignore the sign emax = max(es) ax0.text(a+(b-a)*0.7, emax*0.8, '%s\n%g'%(emax.hex(),emax)) ax0.plot(xs,es,'r.') ax0.grid() ax1.plot(xs,ys,'r.',label='want') ax1.plot(xs,gs,'b.',label='got') ax1.grid() ax1.legend() plt.show() xs, gs, ys, es = parse(sys.stdin) plot(xs, gs, ys, es)

22.349206

85

0.609375

255

1,408

3.364706

0.466667

0.027972

0.034965

0.04662

0.027972

0

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0.18821

1,408

62

86

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false

0.022222

0.088889

0.022222

0.222222

0.044444

0

null

0

null

0

1

0

8c7dcb29d1059858eefa9223cd4270409a444b6c

9,667

py

Python

espa_validation/validate_data/qa_images.py

jakebrinkmann/lagoon-vampire-bat

799050568741f5aa22f36d3b5be8dbee935e5926

[ "Unlicense" ]

null

espa_validation/validate_data/qa_images.py

jakebrinkmann/lagoon-vampire-bat

799050568741f5aa22f36d3b5be8dbee935e5926

[ "Unlicense" ]

null

espa_validation/validate_data/qa_images.py

jakebrinkmann/lagoon-vampire-bat

799050568741f5aa22f36d3b5be8dbee935e5926

[ "Unlicense" ]

null

# qa_images.py import os import logging import numpy as np def do_diff(test, mast, nodata=False): """Do image diff, break if the grids are not the same size. Args: test <numpy.ndarray>: array of test raster mast <numpy.ndarray>: array of master raster """ if nodata: test = np.ma.masked_where(test == nodata, test) mast = np.ma.masked_where(mast == nodata, mast) logging.info("Making nodata value {0} from diff calc.".format(nodata)) try: ## TODO: Figure out why some bands cannot be compared correctly. diff = test.astype(np.float) - mast.astype(np.float) return diff except (ValueError, AttributeError, TypeError) as e: logging.warning("Error: {0}".format(e)) import pdb; pdb.set_trace() return False def call_stats(test, mast, rast_arr, fn_out, dir_out, rast_num=0): """Call stats function(s) if data are valid Args: test <str>: name of test file mast <str>: name of master file rast_arr <numpy.ndarray>: array of target raster fn_out <str>: file path of image dir_out <str>: path to output directory rast_num <int>: individual number of image (default=0) nodata <int>: no data value (default=-9999) """ import os import espa_validation.validate_data.stats from espa_validation.validate_data.file_io import ImWrite if isinstance(rast_arr, (np.ndarray, np.ma.core.MaskedArray)): if np.any(rast_arr != 0): logging.warning("Image difference found!") logging.warning("Test: {0} | Master: {1}".format(test, mast)) # find file name (for saving plot) fout = fn_out.split(os.sep)[-1] # do stats of difference stats.img_stats(test, mast, rast_arr, os.path.dirname(fn_out), fout, dir_out, rast_num) # plot diff image ImWrite.plot_diff_image(test, mast, rast_arr, fout, "diff_" + str(rast_num), dir_out) # plot abs diff image ImWrite.plot_diff_image(test, mast, rast_arr, fout, "abs_diff_" + str(rast_num), dir_out, do_abs=True) # plot diff histograms ImWrite.plot_hist(test, mast, rast_arr, fout, "diff_" + str(rast_num), dir_out) else: logging.info("Binary data match.") else: logging.warning("Target raster is not a valid numpy array or numpy " "masked array. Cannot run statistics!") class ArrayImage: @staticmethod def check_images(test, mast): """Read in a generic (non-geographic) image, like JPEG, and do a diff Return diff raster if actually different Args: test <str>: path to test image mast <str>: path to master image """ try: from scipy.misc import imread except ImportError: from scipy.ndimage import imread # read images try: test_im = imread(test) mast_im = imread(mast) except ImportError: logging.warning("Likely missing Python Image Library (PIL).") # try Scikit Image from skimage.io import imread try: mast_im = imread(mast) test_im = imread(test) except (ValueError, TypeError, ImportError): logging.warning("Not able to open image with skimag.io. Likely" " missing image library.") return None # check diff try: diff_im = do_diff(test_im, mast_im) if len(np.nonzero(diff_im)) > 3: logging.error("Values differ between {0} and {1}.". format(test, mast)) return diff_im else: logging.info("Values equivalent between {0} and {1}.". format(test, mast)) return None except ValueError: logging.error("Image {0} and {1} are not the same dimensions.". format(test, mast)) def sha256_checksum(filename, block_size=65536): import hashlib sha256 = hashlib.sha256() with open(filename, 'rb') as f: for block in iter(lambda: f.read(block_size), b''): sha256.update(block) return sha256.hexdigest() class GeoImage: @staticmethod def check_images(test, mast, dir_out, ext, include_nd=False): """Compare the test and master images, both for their raw contents and geographic parameters. If differences exist, produce diff plot + CSV stats file. Args: test <str>: path to test image mast <str>: path to master image dir_out <str>: path to output directory ext <str>: file extension include_nd <bool>: incl. nodata values in file cmp (default=False) """ from espa_validation.validate_data.image_io import RasterIO, RasterCmp from espa_validation.validate_data.file_io import Cleanup, Find from itertools import zip_longest print("Checking {0} files...".format(ext)) # clean up non-matching files test, mast = Cleanup.remove_nonmatching_files(test, mast) # make sure there are actually files to check if mast is None or test is None: logging.error("No {0} files to check in test and/or mast " "directories.".format(ext)) return False print('+++++ %100s +++++ %100s' % ('TESTING', 'MASTER')) for n, (i, j) in enumerate(zip_longest(test, mast)): logging.debug('%2d: [%100s] %2d: [%100s]' % (n, os.path.basename(str(i)), n, os.path.basename(str(j)))) order = zip_longest(range(len(test)), range(len(mast))) # if raw_input('Need to re-order the comparisons? (Y/[n]): ') == 'Y': # order = input('Enter new indexing ([0,9], [1,2], [2,1]...)\n\n: ') # do other comparison checks, return stats + plots if diffs exist for (ix, jx) in order: i, j = test[ix], mast[jx] logging.info("Checking Test {0} against Master {1}".format(i, j)) if os.path.getsize(i) == os.path.getsize(j): hash1, hash2 = sha256_checksum(i), sha256_checksum(j) if hash1 == hash2: logging.info("Geo files {0} and {1} are the same size and hash ({2})".format(i, j, hash1)) continue # Open each raster ds_test = RasterIO.open_raster(i) ds_mast = RasterIO.open_raster(j) # Compare various raster parameters status = [] status.append(RasterCmp.compare_proj_ref(ds_test, ds_mast)) status.append(RasterCmp.compare_geo_trans(ds_test, ds_mast)) status.append(RasterCmp.extent_diff_cols(ds_test, ds_mast)) status.append(RasterCmp.extent_diff_rows(ds_test, ds_mast)) # If any above tests fail, go to next iteration if any(stat == False for stat in status): continue # Count number of sub-bands in the files d_range = Find.count(i, ds_test, j, ds_mast, ext) if d_range is None: logging.critical("Number of files different; data cannot be " "tested successfully.") continue # if sub-bands exist, read them one-by-one and do diffs + stats if d_range > 1: for ii in range(0, d_range): # Get the first band from each raster if ext == ".img": logging.info("Reading sub-band {0} from .img {1}...".format(ii, i)) ds_tband = RasterIO.read_band_as_array(ds_test, ii) ds_mband = RasterIO.read_band_as_array(ds_mast, ii) else: logging.info("Reading .hdf/.nc SDS {0} from file {1}...".format(ii, i)) sds_tband = RasterIO.open_raster(RasterIO.get_sds(ds_test)[ii][0]) sds_mband = RasterIO.open_raster(RasterIO.get_sds(ds_mast)[ii][0]) ds_tband, t_nd = RasterIO.read_band_as_array(sds_tband) ds_mband, m_nd = RasterIO.read_band_as_array(sds_mband) # do diff if type(t_nd) is type(None) or include_nd: diff = do_diff(ds_tband, ds_mband) else: diff = do_diff(ds_tband, ds_mband, nodata=int(t_nd)) # call stats functions to write out results/plots/etc. call_stats(i, j, diff, i, dir_out, rast_num=ii) else: # else it's a singleband raster logging.info("Reading {0}...".format(i)) # read in band as array ds_tband, t_nd = RasterIO.read_band_as_array(ds_test) ds_mband, m_nd = RasterIO.read_band_as_array(ds_mast) # do diff if type(t_nd) is type(None) or include_nd: diff = do_diff(ds_tband, ds_mband) else: diff = do_diff(ds_tband, ds_mband, nodata=int(t_nd)) # call stats functions to write out results/plots/etc. call_stats(i, j, diff, i, dir_out)

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null

0

null

0

1

0

8c7f25e891fd7d2f2b9e55adb1773dc050888db1

1,818

py

Python

tests/test_ifcollector.py

jgrugru/ifcollector

bb9153f6a06ff81a86c3ea2a0b4db2c7e8451dd4

[ "MIT" ]

null

tests/test_ifcollector.py

jgrugru/ifcollector

bb9153f6a06ff81a86c3ea2a0b4db2c7e8451dd4

[ "MIT" ]

null

tests/test_ifcollector.py

jgrugru/ifcollector

bb9153f6a06ff81a86c3ea2a0b4db2c7e8451dd4

[ "MIT" ]

null

from pytest import mark, raises from re import search from ifcollector import ifandstatement, iforstatement, CannotEvaluateExpression def matches_email_regex(value): match_object = search(r"^(\w|\.|\_|\-)+[@](\w|\_|\-|\.)+[.]\w{2,3}$", value) return bool(match_object) is_valid_test_str = [ str.isalnum, "len(value) > 5", "value == 'Testing'", lambda value: value == "Testing", ] is_valid_gmail = [ "len(value) > 5", "'@' in value", matches_email_regex, "'gmail.com' in value", lambda value: bool(search(r"^(\w|\.|\_|\-)+[@](\w|\_|\-|\.)+[.]\w{2,3}$", value)), ] @mark.parametrize( "value, ifstatement, expression_list, expected_result", [ ("Test String", ifandstatement, is_valid_test_str, False), ("Test ", ifandstatement, is_valid_test_str, False), ("Testing", ifandstatement, is_valid_test_str, True), ("Testing1", ifandstatement, is_valid_test_str, False), ("Test String", iforstatement, is_valid_test_str, True), ("Test ", iforstatement, is_valid_test_str, False), ("Testing", iforstatement, is_valid_test_str, True), ("Testing1", iforstatement, is_valid_test_str, True), ("jeff.gruenbaum@gmail.com", ifandstatement, is_valid_gmail, True), ("jeff.gruenbaum@yahoo.com", ifandstatement, is_valid_gmail, False), ("@gmail.com", ifandstatement, is_valid_gmail, False), (" @gmail.com", ifandstatement, is_valid_gmail, False), ], ) def test_ifstatements(value, ifstatement, expression_list, expected_result): assert ifstatement(value, *expression_list, debug=True) == expected_result def test_CannotEvaluateExpression(): with raises(CannotEvaluateExpression): ifandstatement("Test String", lambda x, y: print("I am the lambda"), debug=True)

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1,818

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0.02439

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null

0

null

0

1

0

8c7f835cd12e745e1bc1ba6d7ed4716788846c28

698

py

Python

keras_dgl/layers/graph_ops.py

michael-cowan/keras-deep-graph-learning

36854d374df931d063ada1c7ea3a5a2d67d3a8e4

[ "MIT" ]

100

2018-05-23T17:31:31.000Z

2022-03-28T14:17:19.000Z

keras_dgl/layers/graph_ops.py

michael-cowan/keras-deep-graph-learning

36854d374df931d063ada1c7ea3a5a2d67d3a8e4

[ "MIT" ]

9

2018-12-03T06:50:20.000Z

2021-07-15T10:15:48.000Z

keras_dgl/layers/graph_ops.py

michael-cowan/keras-deep-graph-learning

36854d374df931d063ada1c7ea3a5a2d67d3a8e4

[ "MIT" ]

55

2018-11-20T12:54:07.000Z

2022-03-29T09:54:25.000Z

import keras.backend as K import tensorflow as tf def graph_conv_op(x, num_filters, graph_conv_filters, kernel): if len(x.get_shape()) == 2: conv_op = K.dot(graph_conv_filters, x) conv_op = tf.split(conv_op, num_filters, axis=0) conv_op = K.concatenate(conv_op, axis=1) elif len(x.get_shape()) == 3: conv_op = K.batch_dot(graph_conv_filters, x) conv_op = tf.split(conv_op, num_filters, axis=1) conv_op = K.concatenate(conv_op, axis=2) else: raise ValueError('x must be either 2 or 3 dimension tensor' 'Got input shape: ' + str(x.get_shape())) conv_out = K.dot(conv_op, kernel) return conv_out

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698

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null

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null

0

1

0

8c8177220839df80a0eb470e5d230d3192332127

4,661

py

Python

parsl/app/app_factory.py

Xarthisius/parsl

fdaef6e5c97365f32591fba987e7653df5ef3e2b

[ "Apache-2.0" ]

null

parsl/app/app_factory.py

Xarthisius/parsl

fdaef6e5c97365f32591fba987e7653df5ef3e2b

[ "Apache-2.0" ]

null

parsl/app/app_factory.py

Xarthisius/parsl

fdaef6e5c97365f32591fba987e7653df5ef3e2b

[ "Apache-2.0" ]

null

"""Centralize app object creation.""" import logging from inspect import getsource from hashlib import md5 from inspect import signature from parsl.app.bash_app import BashApp from parsl.app.python_app import PythonApp from parsl.app.errors import InvalidAppTypeError logger = logging.getLogger(__name__) class AppFactory(object): """AppFactory streamlines creation of apps.""" def __init__(self, app_class, func, data_flow_kernel=None, cache=False, executors='all', walltime=60): """Construct an AppFactory for a particular app_class. Args: - app_class(Class) : An app class - func(Function) : The function to execute Kwargs: - data_flow_kernel(DataFlowKernel) : The DataFlowKernel which will manage app execution. - walltime(int) : Walltime in seconds, default=60 - executors (str|list) : Labels of the executors that this app can execute over. Default is 'all'. - cache (Bool) : Enable caching of app. Returns: An AppFactory Object """ self.__name__ = func.__name__ self.app_class = app_class self.data_flow_kernel = data_flow_kernel self.func = func self.status = 'created' self.walltime = walltime self.executors = executors self.sig = signature(func) self.cache = cache # Function source hashing is done here to avoid redoing this every time # the app is called. if cache is True: try: fn_source = getsource(func) except OSError: logger.debug("Unable to get source code for AppCaching. Recommend creating module") fn_source = func.__name__ self.func_hash = md5(fn_source.encode('utf-8')).hexdigest() else: self.func_hash = func.__name__ def __call__(self, *args, **kwargs): """Create a new object of app_class with the args, execute the app_object and return the futures. Args: Arbitrary args to the decorated function Kwargs: Arbitrary kwargs to the decorated function Returns: (App_Future, [Data_Futures...]) The call is mostly pass through """ # Create and call the new App object app_obj = self.app_class(self.func, data_flow_kernel=self.data_flow_kernel, executors=self.executors, walltime=self.walltime, cache=self.cache, fn_hash=self.func_hash) return app_obj(*args, **kwargs) def __repr__(self): return self.__str__() def __str__(self): return '<class %s"%s for %s>' % (self.app_class.__name__, self.__class__.__name__, self.__name__) class AppFactoryFactory(object): """An instance AppFactoryFactory will be factory that creates object of a particular kind. AppFactoryFactory has the various apps registered with it, and it will return an AppFactory that constructs objects of a specific kind. """ def __init__(self, name): """Constructor. Args: name(string) : Name for the appfactory Returns: object(AppFactoryFactory) """ self.name = name self.apps = {'bash': BashApp, 'python': PythonApp} def make(self, kind, func, data_flow_kernel=None, **kwargs): """Creates a new App of the kind specified. Args: kind(string) : For now only(bash|python) data_flow_kernel(DataFlowKernel) : The DataFlowKernel which will manage app execution. func(Function) : The function to execute Kwargs: Walltime(int) : Walltime in seconds Arbritrary kwargs passed onto the AppFactory Raises: InvalidAppTypeError Returns: An AppFactory object bound to the specific app_class kind """ if kind in self.apps: return AppFactory(self.apps[kind], func, data_flow_kernel=data_flow_kernel, **kwargs) else: logger.error("AppFactory:%s Invalid app kind requested : %s ", self.name, kind) raise InvalidAppTypeError( "AppFactory:%s Invalid app kind requested : %s ", self.name, kind)

33.292857

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0.579489

510

4,661

5.094118

0.292157

0.030793

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0.322034

0

null

0

null

0

1

0

8c83ca186957fc9af62d9f2f84e4116c77bc9153

3,790

py

Python

src/model/layers.py

luyiyun/MCluster-VAEs

15e33e79a7e03859370b21a7cfdd843739a78992

[ "MIT" ]

null

src/model/layers.py

luyiyun/MCluster-VAEs

15e33e79a7e03859370b21a7cfdd843739a78992

[ "MIT" ]

null

src/model/layers.py

luyiyun/MCluster-VAEs

15e33e79a7e03859370b21a7cfdd843739a78992

[ "MIT" ]

null

from math import sqrt import torch import torch.nn as nn ACT = nn.GELU() # ACT = nn.LeakyReLU() class ParallelModule(nn.Module): def __init__(self, *submodels): super().__init__() self._submodels = nn.ModuleList(submodels) def forward(self, xs): feats = [self._submodels[i](x) for i, x in enumerate(xs)] return feats class ConcatModule(nn.Module): def __init__(self, *submodels): super().__init__() self._submodels = nn.ModuleList(submodels) def forward(self, xs): feats = [self._submodels[i](x) for i, x in enumerate(xs)] return torch.cat(feats, dim=1) class SplitModule(nn.Module): def __init__(self, *dims): super().__init__() self._dims = dims self._cumsum = [] s = 0 for d in dims: s += d self._cumsum.append(s) def forward(self, x): if len(self._dims) == 0: return x return [ x[:, d1:d2] for d1, d2 in zip([0] + self._cumsum[:-1], self._cumsum) ] class SwapAxeModule(nn.Module): def __init__(self, dim1, dim2): super().__init__() self._dim1, self._dim2 = dim1, dim2 def forward(self, x): return x.transpose(self._dim1, self._dim2) class DotAttentionModule(nn.Module): def __init__(self, inp, out, qk_dim=None, concat=True): super().__init__() self._concat = concat qk_dim = out if qk_dim is None else qk_dim self.v_fc = nn.Linear(inp, out) self.k_fc = nn.Linear(inp, qk_dim) self.q_fc = nn.Linear(inp, qk_dim) def forward(self, xs): xs = torch.stack(xs, dim=1) # (batch, n, inp) q = self.q_fc(xs) k = self.k_fc(xs) v = self.v_fc(xs) score = torch.bmm(q, k.transpose(1, 2)) score = score / sqrt(xs.size(1)) score = torch.softmax(score, dim=-1) res = torch.bmm(score, v) # (batch, n, out) if self._concat: return res.view(res.size(0), -1) else: return [res[:, i, :] for i in res.size(1)] class GatedAttetionModule(nn.Module): def __init__(self, inp, hidden=None, use_sigmoid=True, use_tanh=False): super().__init__() self._use_sigmoid = use_sigmoid self._use_tanh = use_tanh if hidden is not None: self.embed1 = nn.Sequential( nn.Linear(inp, hidden), ACT, nn.Linear(hidden, 1) ) if use_tanh: self.embed2 = nn.Sequential( nn.Linear(inp, hidden), ACT, nn.Linear(hidden, inp) ) else: self.embed1 = nn.Linear(inp, 1) if use_tanh: self.embed2 = nn.Linear(inp, inp) def forward(self, xs, return_score=False): xs = torch.stack(xs, dim=1) # (batch, n, inp) score = self.embed1(xs) # (batch, n, 1) if self._use_sigmoid: score = torch.sigmoid(score) else: score = torch.softmax(score, dim=1) if self._use_tanh: xs = self.embed2(xs) # (batch, n, inp) xs = torch.tanh(xs) res = (xs * score).sum(dim=1) if return_score: return res, score return res # 会报错，因为GRU只能在train mode下运行 # class GRUModule(nn.Module): # def __init__(self, inp, hidden=50, dropout=0.5): # super().__init__() # self.embed = nn.GRU( # inp, hidden_size=hidden, num_layers=1, # batch_first=True, dropout=dropout # ) # def forward(self, xs): # xs = torch.stack(xs, dim=1) # (batch, n, inp) # return self.embed(xs)[0][:, -1]

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0.293659

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0.335356

3,790

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